accelerated progression of chronic lymphocytic
TRANSCRIPT
ACCELERATED PROGRESSION OF CHRONIC LYMPHOCYTIC
LEUKEMIA IN Eµ-TCL1 TRANSGENIC MICE EXPRESSING CATALYTICALLY-INACTIVE RECOMBINATION-ACTIVATING GENE 1
___________________________________
By
VINCENT KIHARA NGANGA
___________________________________
A DISSERTATION
Submitted to the Faculty of the Graduate School of the Creighton
University in Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy in the Department of Medical Microbiology and
Immunology
_________________________________
Omaha, Nebraska
July, 31, 2013
iii
ABSTRACT
Chronic lymphocytic leukemia (CLL) is the most prevalent adult leukemia
and mainly affects the elderly. CLL is a heterogeneous disease that is
characterized by progressive accumulation of small lymphocytes that express
CD19, CD5, and CD23 in the blood and lymphoid organs. The origins of CLL
remain unclear but emerging evidence suggests that CLL likely evolves from a
more benign biologically similar condition known as monoclonal B cell
lymphocytosis. However, what initiates this condition or how it evolves to CLL is
unknown.
Recently developed transgenic mice that express catalytically inactive
RAG1 in the periphery (dnRAG1 mice) develop an early-onset indolent CD5+ B
cell lymphocytosis, caused in part by a defect in secondary V(D)J
rearrangements initiated to alter autoreactive B cell receptor specificity.
Hypothesizing that the CD5+ B cells accumulating in these animals represent a
CLL precursor, dnRAG1 mice were crossed with CLL-prone Eµ-TCL1 mice,
which carry the T cell leukemia/lymphoma 1 (TCL1) transgene, to determine
whether dnRAG1 expression in Eµ-TCL1 mice accelerates the onset of CLL-like
disease. These experiments showed that CD5+ B cell expansion and CLL
progression occurred more rapidly and uniformly in double-transgenic mice (DTG
mice) compared to Eµ-TCL1 mice, but with similar phenotypic and leukemogenic
features. Interestingly, splenic CD3+TCRβ+CD4-CD8- (double-negative) and
CD4+CD25+ regulatory T cells increased in frequency as a function of age in
DTG mice, suggesting they may be linked to the expanding CD5+ B cells.
iv
Comparative analysis of gene expression profiles in normal and
transgenic CD5+ B cells indicate that CLL may develop by distinct but convergent
pathways that may be nurtured by loss of tolerance. These studies also reveal a
possible role for prolactin signaling in the regulation of receptor editing.
The work in this dissertation suggests that the B cell antigen receptor
plays a significant role in CLL pathogenesis in that failure to remodel the receptor
in response to autoreactivity may promote the benign accumulation of CD5+ B
cells, which may then be subjected to secondary genetic lesions that promote
CLL progression.
v
DEDICATION
This dissertation is dedicated to:
My father, John Nganga Manjie, and my mother, Elizabeth Wanjiru Nganga
vi
ACKNOWLEDGEMENTS
First and foremost I would like to thank my advisor, Dr. Patrick Swanson,
for his guidance and relentless support during my graduate career. I would like to
thank him specifically for allowing me to pursue my education in his laboratory
and for his patience, encouragement, as well as willingness to entertain new
ideas. Secondly, I would like to thank the members of my committee, Dr. Jason
Bartz, Dr. Michael Belshan, Dr. Kristen Drescher, and Dr. Hina Naushad for their
continued direction and support. I acknowledge their genuine effort and expert
advice to mould me into a better student and scientist.
My experience as a student would not have been as exciting without the
wonderful working environment of the Swanson laboratory. I would like to
acknowledge former members, Aleksei Kriatchko, Ming Zhang, Prafulla Raval,
Sushil Kumar, and Dirk Anderson for initiating me into this laboratory and
teaching me most of the techniques I know. Furthermore, this work would not
have been possible without the excellent assistance of Dirk Anderson, Victoria
Palmer, Michele Kassmeier, and Nathan Schabla. I would also like to thank
Koushik Mondal, Mary Rothermund, and Razia-Aziz Seible for their valuable
input, especially to Koushik Mondal for many a discussions as well as his
friendship.
I would also like to extend my gratitude to the Creighton University
Medical Microbiology and Immunology department and its staff and faculty for
financial, administrative, and educational support. I wish to acknowledge the
outstanding flow cytometry services of Dr. Greg Perry as well as his technical
vii
and scientific advice over the years. Additionally, I want to thank former and
currents students, who were a source of friendship and encouragement over the
years, particularly, Charles Schutt, Cameron Schweitzer, Philip Kurpiel, and Ming
Zhang.
Finally, I would like to thank my family for their unyielding moral and
financial support. To my parents, brothers and sisters, thank you for offering your
finances and moral support as well as your patience. This is also goes to the
extended Manjie family as well, including my grandmother, Zipporah Njeri Manjie,
for her never-ending encouragement. I also wish to extend my genuine
appreciation to my uncle Stephen Kirumba and his family for both financial and
moral encouragement throughout my school years, and to the Njenga family for
moral support as well as their friendship.
The work in this thesis was supported by the Health Future Foundation,
the Nebraska LB506 and LB595 Cancer and Smoking Disease Research
Programs, and the Nebraska LB692 Biomedical Research Program grants
awarded to Dr. Patrick Swanson.
viii
TABLE OF CONTENTS
Abstract .............................................................................................................. iii
Dedication ........................................................................................................... v
Acknowledgements ........................................................................................... vi
Table of contents .............................................................................................. vii
List of Figures .................................................................................................. xiii
List of Tables .................................................................................................... xv
List of Abbreviations ....................................................................................... xvi
Chapter 1: Introduction ...................................................................................... 1
1.1 B-cell chronic lymphocytic leukemia history & epidemiology… ....... 2
1.1.1 A brief history of CLL ..................................................... 2
1.1.2 Descriptive epidemiology ............................................... 4
1.2 Clinical characteristics of CLL ......................................................... 7
1.2.1 Diagnosis and natural history .......................................... 7
1.2.2 Heterogeneity ................................................................ 14
1.2.3 Current therapy ............................................................. 17
1.3 Cellular and molecular characteristics of CLL ............................... 22
1.3.1 Normal B cell development and CLL cell of origin ......... 22
1.3.2 Genetic and chromosomal defects in CLL .................... 34
1.3.3 Role of the B cell receptor ............................................ 37
1.3.4 Role of the tumor microenvironment ............................ 42
ix
1.4 Animal models of CLL ................................................................... 48
1.4.1 Xenograft mice. ............................................................. 48
1.4.2 New Zealand mice ........................................................ 49
1.4.3 Eμ-TCL1 transgenic mice.............................................. 52
1.4.4 APRIL transgenic mice ................................................. 55
1.4.5 TRAF2DN/BCL2 transgenic mice ................................. 56
1.4.6 PKCα-KR graft mice ...................................................... 58
1.4.7 SV40 large T antigen transgenic mice .......................... 59
1.4.8 DLEU2/miR15a/16-1 knock-out mice ............................ 60
1.4.9 miR29 transgenic mice ................................................. 61
1.5. Research goals and specific aims ................................................. 63
Chapter 2: Methods .......................................................................................... 67
2.1 Mice .............................................................................................. 67
2.2 Flow cytometry .............................................................................. 67
2.3 Adoptive transfer ........................................................................... 69
2.4 α-galactosylceramide treatment .................................................... 69
2.5 Cell culture .................................................................................... 69
2.6 Histopathology and WBC counts ................................................... 70
2.7 Clonality ........................................................................................ 71
2.8 Immunoglobulin gene sequencing and analysis ............................ 71
2.9 Immunoglobulin levels ................................................................... 73
2.10 Microarray ..................................................................................... 74
x
2.11 Real-time quantitative PCR ........................................................... 76
2.12 Statistics ........................................................................................ 77
Chapter 3: Results..............................................................................................79
3.1 dnRAG1 expression accelerates leukemogenesis in
Eμ-TCL1 mice…….. ...................................................................... 79
3.1.1 Expression of dnRAG1 in Eμ-TCL1 mice shortens
survival .......................................................................... 79
3.1.2 Time course analyses of CLL-like disease progression
in DTG mice… ............................................................. 82
3.1.3 B cells of DTG mice are clonally transformed and bear
unmutated Ig genes ...................................................... 88
3.2 dnRAG1 expression in Eμ-TCL1 mice suppresses
immunoglobulin production ........................................................... 95
3.3 Distinct gene expression profiles in CD5+ B cells in both young
and old transgenic mice ................................................................ 97
3.3.1 Gene expression profiles in 12-week-old mice .............. 97
3.3.2 Gene expression profiles in ill DTG and age-matched
counterparts ................................................................ 102
3.3.3 Tolerogenic and BCR genes are perturbed in
transgenic mice .......................................................... 108
3.4 Alteration of the T cell compartment in transgenic mice .............. 110
3.4.1 Increase in CD4+CD25+ T cells in DTG mice and
xi
CD3+TCRβ+CD4-CD8- (double-negative) T cells in
Eµ-TCL1 and DTG Mice ............................................ 110
3.4.2 The role double-negative T cells in transgenic mice .. 120
Chapter 4: Discussion .................................................................................... 129
4.1 Failure in self-tolerance promotes CLL progression .................... 129
4.1.1 Expression of dominant-negative RAG1 accelerates
CLL progression in Eµ-TCL1 mice ............................. 129
4.1.2 Breaching tolerance promotes CLL ............................. 132
4.1.1 Significance of Prl2a1 expression in dnRAG1 and
DTG mice .................................................................... 137
4.2 Role of regulatory T cells in CLL ................................................. 139
4.2.1 CD4+CD25+ T cells...................................................... 139
4.2.2 Double-negative T cells ............................................... 140
4.3 Lessons from murine models of benign and malignant CD5+
B cell expansion .......................................................................... 142
4.4 Future work ................................................................................. 145
4.4.1 Mechanisms of disease acceleration in DTG
Mice ............................................................................ 145
4.4.2 Role of hormone gene superfamily in normal and
leukemic B cells .......................................................... 146
4.4.3 Role of CD1d .............................................................. 148
4.4.4 Identitiy of double-negative T cells .............................. 149
xii
4.5 Concluding remarks .................................................................... 150
Chapter 5: References…….. .......................................................................... 151
xiii
LIST OF FIGURES
Figure 1.1 : B cell development and differentiation .......................................... 23
Figure 1.2 : Mechanisms of self- tolerance in B cells ........................................ 27
Figure 1.3 : Accumulation of B1-like CD5+ B cells with age in dnRAG1
mice ............................................................................................. 65 66
Figure 3.1 : dnRAG1 expression in Eµ-TCL1 mice enhances
lymphoproliferation and shortens lifespan .................................... 80
Figure 3.2 : dnRAG1 expression in Eµ-TCL1 mice accelerates accumulation
of CLL-like cells ............................................................................. 81
Figure 3.3 : Surface immunophenotype of CLL-like cells in DTG mice ............. 83
Figure 3.4 : Characterization of CLL-like disease progression in DTG mice .... 84
Figure 3.5 : DTG mice show evidence of CLL like disease at 36 weeks .......... 86
Figure 3.6 : Bone marrow and kidney histology of 36-week-old mice ............... 87
Figure 3.7: Engraftment of leukemic cells from DTG mice in SCID mice ......... 89
Figure 3.8 : Clonal transformation of B cells from DTG mice ............................ 96
Figure 3.10 : Identification of differentially expressed genes in WT
CD19+B220hiCD5- B cells and CD19+CD5+ B cells from
dnRAG1, Eµ-TCL1, and DTG mice at 12 weeks ......................... 98
Figure 3.11 : CD5+ B cells from dnRAG1, Eμ-TCL1, and DTG mice are most
similar to normal B1a B cells ..................................................... 100
Figure 3.12 : Identification of differentially expressed genes in WT
CD19+B220hiCD5- B cells and CD19+CD5+ B cells from ill
xiv
DTG mice and age-matched dnRAG1 and Eµ-TCL1 mice ........ 103
Figure 3.13 : Validation of differentially expressed genes by quantitative
PCR .......................................................................................... 106
Figure 3.14 : CD23 expression on leukemic cells from an ill DTG mouse ...... 107
Figure 3.15 : Hierarchical clustering analysis of genes involved in B cell
receptor signaling from 12-week-old and older WT and
transgenic mice ........................................................................ 109
Figure 3.16 : Characterization of T cell subsets in transgenic mice .............. 111
Figure 3.17 : Characterization of lymph node T cells ...................................... 113
Figure 3.18 : Expansion of CD4+CD25+ T cells in DTG mice .......................... 115
Figure 3.19 : Expansion of CD3+TCRβ+CD8-CD4- (DN) T cells in transgenic
mice .......................................................................................... 116
Figure 3.20 : CD1d expression in CD5+ B cells of transgenic mice ............... 117
Figure 3.21 : α-GalCer treatment has little effect on CD5+ B cell
accumulation in DTG mice ......................................................... 118
Figure 3.22 : Expression of CD160, BTLA, HVEM, and DX5 in DN T or
CD5+ B cells ............................................................................... 119
Figure 3.23 : DN T cells inhibit accumulation of CD5+ cells after adoptive
transfer ....................................................................................... 121
Figure 3.24 : DN T cells inhibit expansion of CD5+ B cells in cell culture ....... 123
Figure 4.1 : Model for how defects in receptor editing can promote
development of MBL and CLL ..................................................... 133
xv
LIST OF TABLES
Table 1.1 : Rai and Binet staging systems ........................................................ 11
Table 1.2 : Murine models of CLL ..................................................................... 51
Table 2.1 : Primers for RT-PCR ........................................................................ 78
Table 3.1 : Analysis of IgVH sequences from ill Eµ-TCL1 and DTG mice ......... 93
Table 3.2 : Analysis of IgVL sequences from ill Eµ-TCL1 and DTG mice ......... 94
Table 3.3 : Top 50 differentially expressed genes between 12-week dnRAG1
and DTG ....................................................................................... 125
Table 3.4 : Top common differentially expressed genes among older transgenic
mice compared to WT mice .......................................................... 126
Table 3.5 : Top 50 differentially expressed genes between ill DTG mouse
(M53) and Eµ-TCL1 mouse (M52) ................................................ 127
Table 3.6 : Top 50 differentially expressed genes between ill DTG mouse
(M57) and Eµ-TCL1 mouse (M52) ................................................ 128
xvi
LIST OF ABBREVIATIONS
APRIL A proliferation-inducing ligand
BAFF B cell-activating factor of TNF family
BCR B cell receptor
BM bone marrow
CLL B cell chronic lymphocytic leukemia
CTLA4 cytotoxic T-lymphocyte antigen 4
dnRAG1 dominant-negative recombination activating gene 1
DN T double-negative T cell
DTG double-transgenic mice
FACS fluorescence-activated cell sorting
FO mature follicular B cell
Ig immunoglobulin
IgH immunoglobulin heavy chain
IgL immunoglobulin light chain
IL-10 interleukin-10
LN lymph node
MZ marginal zone B cell
NKT natural killer T cells
NZB/W New Zealand black/white
PB peripheral blood
PerC peritoneal cavity
xvii
Prl2a1 prolactin family 2, subfamily a, member 1
Prl2a1 prolactin family 7, subfamily c, member 1
Prl8a2 prolactin family 8, subfamily a, member 2
RAG1 recombination activating gene 1
RAG2 recombination activating gene 2
RE receptor editing
SCID severe combined immunodeficiency
SHM somatic hypermutation
SLE systemic lupus erythematosus
SLL small lymphocytic lymphoma
T transitional B cell
TCL1 T cell leukemia/lymphoma 1
Treg regulatory T cell
V(D)J variable (diversity) joining
1
CHAPTER I: INTRODUCTION
B-cell chronic lymphocytic leukemia (CLL) is the most prevalent adult
leukemia and mainly affects the elderly (Redaelli et al., 2004; Morton et al. 2007;
Watson et al., 2008). CLL is characterized by abnormal accumulation of small
lymphocytes that express CD19, CD5, and CD23 in blood and lymphoid tissues
such as bone marrow, lymph nodes, or spleen (Matutes and Polliack, 2000;
Dighiero and Hamblin, 2008). CLL is a heterogeneous disease that exhibits a
variable clinical course; some patients have an indolent disease that may not
require medical intervention while others suffer an aggressive disease associated
with short survival (Damle et al., 1999; Hamblin et al., 1999; Van Bockstaele et
al., 2009). Emerging evidence suggests that CLL likely evolves from a more
benign biologically similar condition known as monoclonal B cell lymphocytosis
(Rawstron et al., 2002; Rawstron et al., 2008; Lanasa et al., 2011; Kern et al.,
2012). However, what initiates this condition or why it evolves to CLL is unknown.
What is apparent is that the feedback between CLL cells and their environment
through various receptors, including those that bind antigens, is important but
how these interactions contribute to CLL pathogenesis is still debatable. CLL is
currently incurable.
2
1.1 B-CELL CHRONIC LYMPHOCYTIC LEUKEMIA (CLL) HISTORY AND
EPIDEMIOLOGY
1.1.1 A Brief History of CLL
The understanding of what we now know as leukemia began earnestly in
Europe in the 19th century. Between 1811 and 1841, at least six physicians
published cases of their patients who had blood and spleen abnormalities that
may have been leukemia (Piller, 2001). However, John Hughes Bennett, an
English physician, and Rudolph Virchow, a German pathologist, were the first,
independent of each other, to identify leukemia as a distinct disease in 1845
(Piller, 2001; Marti and Zenger, 2004). Bennett described a disease of
“suppuration of the blood”, which he named leucocythemia, that was associated
with enlargement of the spleen and liver (Bennett, 1845; Bennett, 1851). Virchow
noted that in addition to an enlarged spleen, his patient had a reversed ratio of
pigmented to colorless corpuscles. He named this disease leukemia (Virchow,
1845; Virchow, 1847; Hamblin, 2000).
As interest in this new disease grew, others such as Ernst Neumann
showed that leukemia also involved the marrow, and supported Virchow in that
leukemia could be further divided into splenomedullary/pyoid (myeloid leukemias
today) and lymphatic/lymphadenoid forms (Rai, 1993; Hamblin, 2000). These two
forms of leukemia were formally confirmed with the advent of tri-acidic aniline
dye-based differential stains for blood cells in smears (Erlich, 1891). Additionally,
the terms “acute” and “chronic” would come into use to describe those leukemias
that progressed rapidly or gradually, respectively (Piller, 2001). As cases of new
3
and old blood cell disorders continued to accumulate in the medical literature in
the latter half of the 19th century, it became necessary to categorize them.
Pathologist Hans Kundrat would introduce a systematic distinction approach
between leukemias, pseudoleukemias, and lymphosarcoma (lymphoma),
observing that the latter spread through connected nodes while sparing blood
and marrow (Marti and Zenger, 2004).
In the early 20th century, Turk (1903) and Osler (1909) offered the first
comprehensive description and classification of the entity we now know as B cell
chronic lymphocytic leukemia (CLL) (Hamblin, 2000; Marti and Zenger, 2004;
Linet et al., 2007). Turk would also note that CLL was indistinguishable from
some lymphomas (Hamblin, 2000). The most elaborate, and probably the most
accurate, description of CLL, however, would come in 1924 in a large by Minot
and Isaacs. In that study, they described the natural history of CLL in 98 patients
and attempted to treat the patients with radiation, which reduced tumor mass, but
failed to improve overall survival (Minot and Isaacs, 1924).
In the following decades there was substantial progress in understanding
and treating CLL. The most notable success in treating CLL was with the
alkylating agent Chlorambucil (Galton, 1961). Other progress came in refining the
description, diagnostic criteria, and prognosis of CLL as larger studies were
performed. It became quite clear that there was a wide ranging survival time
among patients, with some displaying stable disease while others had
progressive disease, leading to the proposal to stratify diagnostic criteria (Boggs,
1966; Galton, 1966; Dameshek, 1967).
4
Shortly following the breakthrough using antibodies to identify and
distinguish B and T lymphocytes, it was shown that CLL was a disease of B
lymphocytes and that CLL cells additionally expressed the T lymphocyte antigen,
CD5 (Wilson and Nossal, 1971; Papamichail et al., 1971; Caligaris-Cappio et
al.,1982). This period also saw the development of two clinical staging systems
(Table 1) (Rai et al., 1975; Binet et al., 1981). These two systems, unlike earlier
ones, consisted of readily measurable clinical and laboratory parameters and
became widely adopted (Rai, 1993) and are still used today. Additional
prognostic factors together with the Rai/Binet staging systems, and improved
understanding of how CLL cells interact with their surroundings have allowed for
better prediction of clinical outcome and tailored therapy, which continue to
improve the management of CLL.
1.1.2 Descriptive Epidemiology
CLL is the most common adult leukemia in Australia, Europe, and North
America (Redaelli et al., 2004; Morton et al. 2007; Watson et al., 2008), including
the United States, where CLL cases account for over 30% of all leukemias (Yuille
et al., 2000; Hawlader et al., 2012). The Surveillance Epidemiology and End
Results (SEER) program of the National Cancer Institute, which has probably the
most comprehensive cancer registry, estimates that 16,060 Americans will be
diagnosed with CLL, and 4,580 will die from the disease in 2012 (Hawlader et al.,
2012). According to SEER, the overall CLL incidence is 4.2 per 100,000
Americans. Most CLL patients are men as they have a higher incidence of 5.8
5
per 100,000 compared to 3.0 for women. CLL risk varies with race; the order of
decreasing risk is White > Black > Indian/Alaska Native > Hispanic >
Asian/Pacific Islander. CLL is a disease of older adults. Based on SEER data
from 2005-2009, only 1.8% of CLL patients were diagnosed before age 44 and
less than 9.8% of CLL patients before age 54. The median age at diagnosis is 72
years. The 5-year relative survival based on 2002-2008 data is 78.8%. The
lifetime risk of developing CLL based on 2007-2009 data is 0.49%; alternatively 1
in 202 Americans will develop CLL in their lifetime.
The cause of CLL remains unknown but environmental risk factors have
been sought. Factors such as radiation, industrial chemicals, and cigarette
smoke, which are known to contribute to other cancers, have been of particular
interest (Linet et al., 2007). Although radiation has been linked to other
leukemias, no strong link could be made for CLL in studies involving nuclear
facility/radiation workers (Gluzman et al., 2006; Muirhead et al., 2009). Moreover,
retrospective studies show the relative risk of CLL among Japanese atomic bomb
survivors remains low despite increases in other types of lymphoproliferative
diseases (Finch et al., 1969; Hsu et al., 2013). An extensive review by Blair et al.
(2007) on studies investigating CLL link to chemicals such as industrial solvents,
chemotherapy alkylating agents, pesticides, and cosmetic dyes found little
evidence for increased risk of CLL except possibly for certain pesticides and
chemicals such as benzene and butadiene, which are commonly used in the
petroleum and rubber occupations. A stronger occupational risk is for
6
farming/agricultural industries, which has been linked to pesticide use and
possibly fertilizers (Blair et al., 2007; Linet et al., 2007).
Infectious agents have also been speculated as potential causes of CLL
(Hamblin, 2006). Landgren et al. (2007) suggested that pneumonia can possibly
trigger CLL based on their findings that previous pneumonia infection and
frequency was significantly correlated with CLL risk. Furthermore, CLL cases that
exclusively use IgHV4-34 antibodies were found to carry higher than normal
Epstein-Barr virus (EBV) and cytomegalovirus (CMV) nucleic acid material,
suggesting that viral antigens may be involved in the etiology of CLL in some
cases (Kostareli et al., 2004). These possibilities are also supported by Messmer
and colleagues (2004) who reported that CLL cells from unrelated patients in
different geographic regions share striking similarities in the structure of their
antigen receptors, which would not be expected to occur by chance, suggesting
that these receptors are selected by a limited set of common antigens. Bacterial
polysaccharide capsules, viral coats, fungal cell wall glucans, and even self-
antigens have all been speculated to contribute to CLL pathogenesis (Redaelli et
al., 2004; Ghiotto et al., 2004; Hoogebom et al., 2013; Herve et al., 2005).
Familial studies suggest that there is a stronger genetic risk for CLL as
compared to the environment. The risk of developing CLL is increased 2-8-fold
for first-degree relatives of CLL patients (Crowther-Swanepoel and Houlston,
2009; Di Bernardo et al., 2008). Based on both linkage and association studies,
the risk alleles identified for CLL include those related to cell death and immune
regulation (Crowther-Swanepoel and Houlston, 2009; Di Bernardo et al., 2008;
7
Slager et al., 2010). However, others have noted that these risk genes are also
associated with other lymphoproliferative disorders, suggesting they are not
unique for CLL (Yuille et al., 2000). The role of genetics is further clarified by the
observation that CLL risk does not change with immigration. For example,
immigrants from Asia who move to the West where the incidence of CLL is
higher, remain at low risk for developing CLL as do their descendants (Herrinton
et al., 1996; Pan et al., 2002).
1.2 CLINICAL CHARACTERISTICS
1.2.1 Diagnosis and Natural History
CLL is characterized by the accumulation of small mature lymphocytes
typically with scanty cytoplasm, clumped chromatin, and inconspicuous nucleoli
with a CD19+CD20loCD5+CD23+IgMloIgDloCD22lo/-CD79loFMC7lo/-
immunophenotype. CLL cells tend to be fragile and form readily observable
smudges in blood smears (Matutes and Polliack, 2000; Dighiero and Hamblin,
2008; Nowakowski et al., 2007). Diagnosis of CLL is established by a finding of
an absolute peripheral blood (PB) lymphocytosis of > 5x109/L and lymphocytes
with at least one B cell marker, CD19 or CD20, that are monoclonal (commonly
determined by light chain restriction), and co-express CD5 and CD23 (Pangalis
et al., 2002; Redaeli et al., 2004). A finding of lymphadenopathy, splenomegaly,
or other organ infiltration by cells with a CLL immunophenotype but with an
absolute PB lymphocytosis below 5x109/L is considered a different manifestation
8
of the disease, and is known as small lymphocytic lymphoma (SLL) (Harris et al.,
1999; Campo et al., 2011) and comprises 25% of all CLL/SLL cases (Dores et
al., 2007). While bone marrow (BM) examination is not required for all patients at
diagnosis, involvement is considered when there is at least 30% infiltration by
lymphoid cells (Redaeli et al., 2004). The most common considerations in the
differential diagnosis of CLL are: (i) mantle cell lymphoma (MCL), which
expresses CD5, but not CD23, and carries a recurrent (11;14)(q13;q32)
chromosomal translocation associated with cyclin D1 overexpression, or (ii) less
closely related follicular lymphoma, hairy-cell leukemia, and marginal-zone
lymphoma, which are CD5-. Follicular lymphoma, but not CLL, expresses CD10,
and hairy-cell leukemia has morphologically conspicuous hair-like projections
(Dighiero and Hamblin, 2008). The median age at CLL diagnosis is 72 years with
twice as many men as women (Hawlader et al., 2012). Some patients have no
symptoms at diagnosis, but lymphadenopathy (80%), followed by splenomegaly
(50%) are the most common findings. Those with advanced disease usually
present with constitutional symptoms, mainly fatigue, weight loss, infections,
bleeding, anemia, and thrombocytopenia (Redaeli et al., 2004).
Rai and Binet are two widely used clinical staging systems in CLL (Rai et
al., 1975; Binet et al., 1981). Rai and Binet systems are based on clinical and
hematological findings of lymphocytosis, lymphadenopathy and other
organomegaly, anemia, and thrombocytopenia which segregate patients into
three and five stages, respectively, with three main categories that reflect
differences in survival (Table 1). About 80% of patients have low tumor burden
9
and fall in the first stage but those presenting with extensive lymphadenopathy or
hepatosplenomegaly, with anemia and/or thrombocytopenia have the worst
prognosis (Van Bockstaele et al., 2009).
Additional prognostic factors, which usually correlate with Rai and Binet
systems, relate to serum proteins and cellular characteristics. (i) Serum markers
such as elevated levels of lactate dehydrogenase, β2-microglobulin, soluble
CD23, CD27, CD44, and thrombopoietin are associated with shorter survival (Rai
et al., 2004; Van Bockstaele et al., 2009). (ii) Proliferation markers such as
absolute lymphocyte count doubling time (lymphocyte doubling time) of less than
12 months, elevated thymidine kinase, and shorter telomeres and high
telomerase activity are associated with progressive disease and shorter survival
(Rai et al., 2004; Van Bockstaele et al., 2009). (iii) Cytogenetic abnormalities,
typically detected by FISH, are present in 80% of cases (Zenz et al., 2011). The
most common of these is chromosome 13q14 deletion which is seen in 40-60%
of patients but with a median survival of 133 months these case have a relatively
better outcome even beyond those with a normal karyotype. Trisomy 12 (15-30%
of cases) has an equally fair outcome with a median survival of 114 months,
which is comparable that of a normal karyotype. 11q22-q23 and 17p13 deletion
are less common (~10-20%) but with survival times of 79 and 32 months,
respectively, these cases are associated with an aggressive disease and
refractory therapy (Dohner et al., 1995; Dohner et al., 1997; Dohner et al., 2000).
(iv) IgVH mutational status - Presence or absence of mutations in Ig genes is
based on greater or lesser than 98% homology to the closest germline. About
10
half of CLL cases carry mutated IgVH and have good prognosis with a median
survival of ~24 years, whereas those with unmutated IgVH have a relatively
shorter survival of ~9 years (Damle et al., 1999; Hamblin et al., 1999).
A subset of patients carrying IgVH3-21 has poor survival irrespective of
mutational status (Ghia et al., 2008; Krober et al., 2006). ZAP-70 and/or CD38
expression correlate with mutational status and are associated with poor
prognosis (Damle et al., 1999; Crespo et al., 2003). Because of the relative ease
and low cost of measuring CD38 and ZAP-70 expression by flow cytometry,
these can act as surrogate markers for mutation status (Damle et al., 1999;
Crespo et al., 2003). However there is no absolute consensus on what fraction of
CLL should express these proteins to consider them positive (typically, cases are
considered positive if > 30% (CD38) or >20% (ZAP-70) of CLL express these
proteins). These surrogate markers for mutational status should also be used
carefully since ZAP-70 or CD38 expression levels can fluctuate in some patients
(Hamblin et al., 2002; Van Bockstaele et al., 2009). Expression of lipoprotein
lipase also correlates with lack of mutations and can similarly distinguish the two
clinical groups of CLL (Haslinger et al., 2004; Heintel et al., 2005).
Immunological dysfunction has been known in CLL for decades (Jim,
1956; Dameshek, 1967; Chiorazzi et al., 1979). Immunological defects primarily
involve the leukemic cells but also extend to other immune cells. The most
common is loss of immunocompetence by the B cells manifested by
hypogammaglobulinemia, poor response to vaccinations, and autoimmune
11
Table 1.1 Rai and Binet staging systemse
Category Features
Median
survival
(years)
Rai stage
0 Low risk Lymphocytosisa 13+
I Intermediate risk Lymphocytosis and enlarged nodes 8
II Lymphocytosis and enlarged spleen or liver
III High risk Lymphocytosis and anemiab 2
IV Lymphocytosis and thrombocytopeniac
Binet stage
A Low risk Hemoglobin ≥ 100g/L, platelets ≥ 100x109/L, 15
and < 3 enlarged lymphoid areasd
B Intermediate risk Hemoglobin ≥ 100g/L, platelets ≥ 100x109/L, 5
and ≥ 3 enlarged lymphoid areas
C High risk Hemoglobin < 100g/L and or platelets < 100x109/L, 3
regardless of number of enlarged lymphoid areas
a Blood absolute lymphocyte count ≥ 5x10
9/L with monoclonal B cells with a CLL immunophenotype.
b Hemoglobin < 110g/L, with or without enlarged lymph nodes, spleen or liver.
c Platelets < 100x10
9/L, with or without anemia or enlarged lymph nodes, spleen or liver.
d One of five areas: cervival, axillary, and inguinal lymph nodes, spleen, and liver.
e Rai et al., 1975; Rai et al., 1987; Binet et al., 1981; Rai et al., 2004.
12
phenomena (Dearden, 2008). Progressive hypogammaglobulinemia is a
common feature in CLL patients. Rozman et al. (1988) reported that 19.5% of
240 previously untreated patients had hypogammaglobulinemia at diagnosis and
severity was correlated to clinical stage and survival. About 70% of patients
develop hypogammaglobulinemia within 7 years of diagnosis and the probability
of having deficiency for at least one Ig class is even higher (Dearden, 2008).
Progressive hypogammaglobulinemia is not primarily due to BM failure since
reconstitution is rarely seen after therapy (Colovic et al., 2001; Dearden, 2008).
Serum IgG and IgA, but not IgM levels appear to be better predictors of survival
(Rozman et al., 1988). Ig production defects, which also lead to suboptimal
response to vaccinations in CLL patients (Sinisalo et al., 2001; Hartkamp, et al.,
2001), likely originate from intrinsic B cell defects as well leukemia-induced T cell
dysfunction.
Defects are also observed in other immune cells. T cells, for instance,
display altered function and perturbed frequencies. The ratio of circulating CD4+
to CD8+ T cells is inverted in PB but CD4+ T cells are increased in the LN (Kay
1981; Herrmann et al., 1982). Most of these T cells are oligoclonal or clonal,
defective in immunological synapse formation, and exhibit signs of anergy or
exhaustion (Farace et al., 1994; Serrano et al., 1997; Gorgun et al., 2009; Riches
et al., 2013). Tregs, which are immunosuppressive in nature, are also increased
in CLL (D’Arena et al., 2012). Reduced NK and monocyte cytotoxicity, neutrophil
chemotaxis and phagocytic activity, and complement activation defects all
contribute to systematic immune dysfunction in CLL (Dearden, 2008).
13
Cytopenias are the most common autoimmune manifestations in CLL
(Zent and Kay, 2010). Autoimmune hemolytic anemia (AIHA) is the most
common of these and occurs in 5-10% of cases followed by immune
thrombocytopenia (ITP; 2%), and pure red cell aplasia and neutropenia, which
are the least common with each accounting for 0.5% of cases. AIHA and ITP
findings increase with clinical stage and indicate poor prognosis (Zent and Kay,
2010; Hodgson et al., 2011). Interestingly, autoantibodies in CLL cases are
mainly contributed by non-leukemic B cells, probably due to impaired peripheral
tolerance (Zent and Kay, 2010). Cytopenias are also induced frequently by
certain therapies such as purine analogues like fludarabine (Zent and Kay,
2010).
Other complications in CLL, which are primarily attributed to immune
dysfunction, include infections and secondary malignancies and are the most
common causes of death (Itala et al., 1992; Molica et al., 1993; Kyasa et al.
2004). The majority of infections are attributed to hypogammaglobulinemia and
are caused by common bacteria such as Streptococcus pneumoniae,
Haemophilus influenzae, Escherichia coli, Klebsiella pneumoniae, and
Pseudomonas aeruginosa (Morrison, 2010). Viral and fungal infections are less
common and are usually a side effect of certain therapies. Infections most
commonly involve herpes family viruses (herpes simplex, varicella zoster, CMV,
and EBV), and Aspergillus, Pneumocystis, and Candida (Morrison, 2010). The
mucosa is the most common site of involvement, and pulmonary diseases
14
(overwhelmingly pneumonia) are the main cause of hospitalization and death
(Ahmed et al., 2003).
CLL patients are at increased risk of developing a second malignancy,
which are mainly non-hematological solid malignancies of skin and lung as well
as lymphomas, or other hematological malignancies (Maddocks-Christianson et
al., 2007; Hisada et al., 2001). Additionally CLL cells can transform into a high
grade lymphoproliferative disorder in 5-10% of cases (Tsimberidou et al., 2006;
Reiniger et al., 2006). Kyasa et al. (2004) found 16% of 132 CLL patients
developed an additional malignancy, which was the most common cause of
death followed by progressive CLL disease and infections. Although increased
risk of secondary malignancies is well documented following therapy, genetic
predisposition and loss of tumor surveillance are purported to play a role (Robak
et al., 2004; Maddocks-Christianson et al., 2007).
1.2.2 Heterogeneity
Using a wealth of CLL patient data gathered over twenty years, Boggs and
colleagues (Boggs et al., 1966) found variability in survival among patients,
confirming earlier hints that CLL was not a uniform disease. In the late 1990s, it
was established that mutational status of the IgVH genes was linked to clinical
outcome; leukemia cells that harbor mutated Ig genes (~50%) are associated
with indolent CLL, whereas lack of mutations in the Ig genes is associated with
aggressive disease and poor outcome (Damle et al., 1999; Hamblin et al., 1999).
The median survival for mutated is ~24 years compared to ~9 years for
15
unmutated cases (Damle et al., 1999; Hamblin et al., 1999). Expression of other
markers, particularly CD38 and ZAP-70, has additionally been shown to correlate
with unmutated status but can also be independent prognosticators of disease
outcome (Hamblin et al., 2002; Crespo et al., 2003; Schroers et al., 2005).
Chromosomal defects, which are prognostic factors as well, may correspond to
mutational status. For example, cases with 13q14 deletion are also more likely to
carry mutations, and 11q22-q23 cases usually bear unmutated IgVH genes (Van
Bockstaele et al., 2009; Zenz et al., 2011). Unmutated cases also tend to have a
higher incidence of AIHA (Maura et al., 2013). Differences in clinical outcomes
can be traced to cellular properties, which show that unmutated CLL BCR are
more likely to bind self-antigens, and are more proficient at BCR signaling, partly
attributed to presence of ZAP-70 and/or CD38 (Herve et al., 2005; Guarini et al.,
2008).
Emerging evidence suggests that CLL likely evolves from a more benign
and biologically similar condition known as monoclonal B cell lymphocytosis
(MBL). Rawstron and co-workers (2002) sought to identify whether seemingly
healthy individuals carry CLL-like cells analogous to a monoclonal gammopathy
of undetermined significance (M-GUS) condition that precedes multiple myeloma.
They determined that ~3.5% of otherwise healthy adults over 40 years of age
carry monoclonal cells with a CLL immunophenotype. MBL is diagnosed (often
incidentally) by a finding of monoclonal B cell lymphoctosis < 5x109/L with CLL-
like cells in the absence of cytopenias, lymphadenopathy, or organomegaly
(Marti et al., 2005). First-degree relatives of CLL patients have a higher incidence
16
of MBL (13.5 % - 18%) than controls (Shim et al., 2010). MBL with lymphocytosis
progresses to CLL requiring treatment at the rate of 1.1% per year (Rawstron et
al., 2008).
MBL has several features similar to CLL: the ratio of male to female
incidence is 1.9:1, the most common cytogenetic defects are 13q14 deletion
(48%) and trisomy 12 (20%), and there is a frequent increase in clonal T cell
populations (Rawstron et al., 2002; Rawstron et al., 2008; Fazi et al., 2011). In
addition, it has been reported that individuals with MBL have an increased risk of
developing bacterial infections. In one study, 16.2% of MBL and 18.4% of CLL
required hospitalization due to infections compared to 6.2% of controls (Moreira
et al., 2013). These similarities, taken together with gene profiling studies which
reveal that MBL has a characteristic profile of “good prognosis CLL”, has led to
the suggestion that MBL should be classified as early-stage CLL (Lanasa et al.,
2011; Kern et al., 2012). The observation that most MBL already harbor
cytogenetic defects of CLLyet progress slowly to CLL, suggests that these
defects may predispose individuals to CLL, but are not adequate for developing
frank CLL, which requires additional stochastic mutations to promote disease
progression.
About 5-10% of CLL cases transform into refractory high grade
lymphoproliferative disorders known as Richter’s transformation and
prolymphocytic transformation (Tsimberidou et al., 2006; Reiniger et al., 2006).
The appearance of large cells with reticular chromatin and prominent nucleoli
(mainly diffuse large B cell lymphoma) in CLL cases is termed Richter’s
17
transformation. This transformation is usually accompanied by organomegaly
and constitutional symptoms, and reduced survival of less than 15 months
(Richter, 1928; Foucar and Rydell, 1980). In prolymphocytic transformation, the
CLL cells turn into immature-like lymphoblasts that retain the CLL
immunophenotype and survival ranges from a few months to 2 years (Enno et
al., 1979; Kjeldsberg and Marty, 1981; Ghani et al., 1986). The risk of developing
Richter’s is increased by a predominant nodal disease, CD38 expression, IgVH4
gene usage, and lack of 13q14 deletion (Rossi et al., 2008). Both Richter’s and
prolymphocytic transformations may be caused by miss-targeted AID, EBV
infection, and nucleoside analogue treatment (Robak et al., 2004; Thornton et al.,
2005).
1.2.3 Current Therapy
Early treatment of CLL, which was limited to radiation and chemotherapy
with arsenic compounds, was rarely effective (Minot and Isaacs, 1924; Wintrobe
and Hasenbush, 1939; Galton, 1959). However, advances came in the 1940s
and 1950s following a surge in development of chemotherapeutic compounds,
both new and those that had been successful in treating other cancers (Galton
1955; Galton, 1961; Shaw, 1961; Kaung et al., 1964). Of these, alkylating agents,
chlorambucil and cyclophosphamide, and the corticosteroid, prednisone, were
found to be fairly effective in treating CLL in clinical trials. Furthermore, these
drugs were easily administered orally and had modest side effects, except for
prednisone, which was associated with increased infections but was most
18
effective for resolving hemolytic anemia and thrombocytopenia (Galton 1955;
Shaw, 1961; Galton, 1961; Kaung et al., 1964). These drugs became first-line
therapy for CLL for the following decades. Due to its low toxicity and convenient
administration, chlorambucil remains the best choice for elderly patients who are
unfit for standard therapy (Hallek, 2010).
Standard therapy for CLL today is based on chemoimmunotherapy.
Overall, CLL therapy currently draws from several drug classes that include
alkylating agents (chlorambucil, cyclophosphamide, and bendamustine), purine
nucleoside analogues (fludarabine, pentostatin, and cladribine), corticosteroids
such as prednisone, and monoclonal antibodies directed against CD20 (rituximab
and ofatumumab) and CD52 (alemtuzumab) (Halek et al., 2008; Gribben and
O’brien, 2011; Hallek, 2010). The purine analogues tend to be more effective
than alkylating agents or corticosteroids as monotherapies but they are more
myelotoxic (Keating et al., 1989; Hallek, 2010). However, combination therapies
are preferred in treating CLL because they provide superior overall responses
and survival. For instance, fludarabine plus cyclophosphamide can achieve an
overall response rate of over 80% and a complete remission rate of ~ 20%
(Catovsky et al., 2007; Hallek, 2010). Furthermore, addition of the monoclonal
antibody, rituximab, to the fludarabine and cyclophosphamide regimen is even
more effective with an overall response rate of over 90% and a complete
remission rate of over 40% in previously untreated patients (Keating et al., 2005;
Hallek, 2010). These monoclonal antibodies function through a variety of
mechanisms to achieve clearance of leukemic cells that include antibody-
19
dependent cell cytotoxicity, complement-dependent cytotoxicity, and direct
signaling that promotes cell death (Jaglowski et al., 2010). They can be effective
even as single agents but function better in combination therapies, and are
particularly useful in treating autoimmune complications and relapsed/refractory
disease (Cheson, 2010; Jaglowski et al., 2010).
Based on variability in clinical outcomes in CLL, low-risk patients without
progressive disease are monitored rather than treated. In fact, studies have
shown that chemotherapy in early asymptomatic CLL does not alter survival
(Dighiero et al., 1998). Therefore, CLL patients in Rai stage 0/Binet stage A with
stable disease usually are not treated unless they show signs of progression
(Hallek, 2008). Symptomatic patients at any stage, or Rai stage III and IV/Binet
stage C patients are recommended for standard treatment, which generally
involves a combination of fludarabine, cyclophosphamide, and rituximab (Hallek,
2008). Refractory/relapsed or high-risk CLL, for example cases with 17p13
deletion or p53 mutations, can benefit from other regimens such as alemtuzumab
alone or in combination with fludarabine, or bendamustine with/without rituximab,
or the immunomodulator lenalidomide. CLL patients who fail these second-line
treatments may be eligible for a clinical trial or reduced-intensity allogeneic stem
cell transplant. Complications from AIHA or ITP are still best treated with
corticosteroids. Monoclonal antibodies specific for CD20 and CD52 have also
shown considerable effect (Gribben and O’brien, 2011). Otherwise, splenectomy
may be necessary (Hallek et al, 2008; Gribben and O’brien, 2011). There is no
20
standard therapy for transformations, such as Richter’s, but it is often treated like
other high-grade non-Hodgkin’s lymphomas (Gribben and O’brien, 2011).
Newer therapies have greatly improved the management of CLL.
Monoclonal antibodies, for instance, have now become part of standard therapy
but they have also found utility in treating complicated disease as well. Their
success has inspired investigation on new and existing antibodies used in other
conditions for their effect on CLL. They include additional antibodies against
CD20 and to other markers expressed on CLL cells such as CD19, CD23, CD37,
CD38, CD40, and CD74 (Jaglowski et al. 2010; Cheson, 2010; Hallek, 2010).
Lenalidomide is a thalidomide-derived immunomodulatory agent with activity
against CLL (Kotla et al., 2009). This drug, which is in phase III clinical trials, has
been shown to be effective in treating relapsed and refractory CLL, and is one of
the few alternatives currently available where other therapy has failed (Chanan-
Khan et al., 2006; Ferrajoli et al., 2008; Hallek, 2010; Ramsay et al., 2008;
Schulz et al., 2013). Although the precise mechanism of action of lenalidomide in
CLL is unclear, this drug purportedly targets the tumor microenvironment through
multiple effects such as in reducing angiogenetic factors, reducing the interaction
of CLL cells with non-tumor support cells, and enhancing anti-tumor immune
responses through augmentation of NK and T cells activity as well as antigen
presentation by CLL cells (Kotla et al., 2009; Ramsay and Gribben, 2009).
Recently, lenalidomide has been shown to have the ability to block inhibitory
receptors on CLL cells thus restoring the formation of a functional immunological
synapse with T cells (Ramsay et al., 2012).
21
Autologous stem cell transplant (SCT) in CLL is not curative but allogeneic
SCT has the potential of curing the disease. However, these therapies are only
indicated for a fraction of CLL patients (mainly younger patients with high-risk
disease) due to the advanced age and comorbidities in the typical CLL patient
(Toze et al., 2012). Due to high mortality rates associated with myeloablative
allogeneic SCT, even in younger patients, reduced-intensity conditioning (RIC)
allogeneic SCT is preferred for patients eligible for SCT (Toze et al., 2012;
Jaglowski and Byrd, 2012).
Our understanding of CLL biology has facilitated the development of
several novel targeted therapies that are very promising. These include: (i) Bcl2
family antagonists (ABT-263 and oblimersen) (Billard, 2012); (ii) cyclin-
dependent kinase inhibitors such as dinaciclib, and flavopiridol, an alternative
salvage therapy in phase III trials (Jaglowski and Byrd, 2012); and (iii) BCR
signaling inhibitors, mostly directed toward BCR kinases Syk (fostamatinib), Lyn
(dasatinib), and BTK (Ibrutinib), and PI3-kδ (GS1101) (Woyach et al., 2012).
Recently, T cells engineered to express a chimeric antigen receptor (CAR)
have shown promise in a small study. This CAR consists of CD19-specific
antigen-binding domains of an antibody coupled to T cell receptor signaling
domains to bypass major histocompatibility complex restriction. When autologous
CAR T cells were infused into three patients with advanced and chemorefractory
CLL (two patients had the 17p13 deletion), they expanded, persisted, and drove
leukemia into remission in two patients and induced partial response in the third
one. However, patients inevitably develop hypogammaglobulinemia because
22
CAR T cells target leukemic and non-leukemic B cells all of which express CD19
(Kalos et al., 2011). Despite these major advances in treatment, CLL remains an
incurable disease.
1.3 CELLULAR AND MOLECULAR CHARACTERISTICS OF CLL
1.3.1 Normal B Cell Development and CLL Cell of Origin
B lymphocytes are white blood cells in the humoral arm of the adaptive
immune system where that produce antibodies to eliminate harmful antigens
(Cooper et al., 1965; Cooper, 1987). To generate an antibody repertoire with the
diversity required to indentify a potentially infinite number of foreign but not self-
antigens, these cells employ a number of diversification and selection
mechanisms in a highly ordered differentiation and developmental process
(Tonegawa, 1983; Hardy and Hayakawa, 2001; Glanville et al., 2009). Total or
partial failure in these mechanisms can lead to disorders ranging from
immunodeficiency and autoimmunity to B cell malignancies (Ballow, 2002; Sinha
et al., 1990; Goodnow, 1997; Shaffer et al., 2002).
B cell development after birth begins in hematopoietic progenitors found in
the BM and is completed in peripheral lymphoid organs (Figure 1.1). B cells arise
from the common lymphoid progenitor and proceed through several intermediate
differentiation stages to maturity as they gain immunocompetence. These
immature and mature B cell populations are distinguishable by expression of
23
Figure 1.1 B cell development and differentiation. B cells arise from the common
lymphoid progenitor (CLP) in the bone marrow, where they develop initially in an
antigen-independent manner, and complete their maturation in secondary lymphoid
organs such as the spleen. The early B cell subsets are marked by formation of the B
cell receptor during three main waves of RAG1/2 expression to rearrange the
immunoglobulin heavy chain, light chain, and to remodel the light chain after recognizing
self-antigens (receptor editing), which is also postulated to occur in peripheral
transitional B cells that still retain autoreactivity and germinal center B cells that become
autoreactive after acquiring somatic hypermutations. Immature B cells migrate to the
spleen and progress through transitional (T) stages 1 and 2 to become follicular (FO)
mature B cells, which when stimulated by antigens differentiate into antibody-producing
plasma cells and memory B cells. Transitional B cells also give rise to marginal zone
(MZ) B cells, and to a lesser extent, to B1 B cells, which largely derive from liver
progenitors in the fetus and neonate (Adapted from Hardy, 2006 and Hardy et al.,
2007)specific markers, morphology, function, or a combination of these features (Hardy
and Hayakawa, 2001).
24
Early B-lineage cells in mice express pan-B cell markers, namely B220
followed by CD19 and are marked by the ordered assembly of immunoglobulin
(Ig) gene segments, which are otherwise separated on the chromosome, to form
Ig heavy and light chain genes that encode the B cell receptor (BCR) (Tonegawa,
1983; Hardy et al., 2007). The process of Ig gene assembly, together with other
diversification mechanisms, has been estimated to yield B cells with an excess of
3.5x1010 unique specificities in humans (Glanville et al., 2009). The Ig gene
assembly process begins at the B220+CD43+ pro-B cell stage, where the
recombination activating genes 1 and 2 (RAG1 and RAG2) are expressed
(Oettinger et al., 1990). The RAG1 and RAG2 proteins together initiate site-
specific DNA recombination that joins variable (V), diversity (D), and joining (J)
immunoglobulin gene segments in a process known as V(D)J recombination
(Early et al., 1980; Oettinger et al., 1990). This process begins in the Ig heavy
chain (IgH) locus with the joining of a DH and JH gene segment, followed by
joining of an upstream VH segment to the rearranged DH-JH gene segments to
form the variable exon of the heavy chain gene. Imprecise joining of these gene
segments in developing lymphocytes during V(D)J recombination contributes
additional diversity to antigen receptors (Gersteins and Lieber, 1993; Lieber et
al., 2004).
Upon successful completion of rearrangement, transcription ensues and
the variable exon is joined to a µ constant region by RNA splicing to produce the
mature IgHµ mRNA (Ghia et al., 1998; Hardy et al., 2007). RAG1/2 expression is
extinguished and the rearranged IgHμ heavy chain pairs with a surrogate light
25
chain, which is composed of the proteins VpreB and λ5, and is expressed on the
cell surface as the pre-B cell receptor (pre-BCR) (Tsubata and Reth, 1990). The
pre-BCR marks a critical checkpoint in determining the functionality of the
rearranged heavy chain; successful pre-BCR formation allows signaling that
leads to proliferation of late pro-B cells to become large pre-B cells. When large
pre-B cells cease proliferating, they become small pre-B cells at which point
RAG1 and RAG2 are re-expressed to assemble the Ig light chain (IgL). In mice
and humans, rearrangement begins at a single IgLκ allele, followed by the
second allele, and finally IgLλ until a productive light chain is achieved. Failure to
produce functional rearrangements in either the IgH or IgL loci leads the B cell to
undergo apoptosis. Successful pairing of IgHμ with a light chain leads to the
assembly of a BCR that is capable of antigen binding and is expressed on the
cell surface, which marks the immature B cell stage
(CD19+B220+CD43+IgMhiIgD) (Hardy et al. 2007).
Since “primary” V(D)J rearrangement is an antigen-independent process,
a large number (up to 75%) of newly-formed immature B cells are inherently
autoreactive (Wardemann et al., 2003; Nemazee, 2006). This immature B cell
stage therefore, marks a critical checkpoint in enforcement of central tolerance
by negative selection or “re-education” of B cells that bind self-antigens.
Depending on the anatomical location and the nature of self-antigens bound by
immature B cells, there are three possible outcomes (Figure 1.2): (i) clonal
deletion by programmed cell death, (ii) receptor editing, and (iii) functional
inactivation (Jankovic et al., 2004; Goodnow et al., 2005; Hillion et al., 2005;
26
Nemazee, 2006). Receptor editing involves re-expression of RAG1 and RAG2
and subsequent rearrangement of the light chain in an attempt to remodel the
autoreactive BCR into an innocuous one (Tiegs et al., 1993; Girschick et al.,
2001; Nemazee, 2006). Mechanisms of inactivation include intrinsic programs
that downregulate the BCR and its positive regulators and upregulate its negative
regulators such as CD5 rendering the B cell anergic, or extrinsic factors such as
limitation of growth factors and costimulation/inflammatory signals, as well as the
activity of regulatory cells (Goodnow et al., 2005; Basten and Silveira, 2010).
Through alternative RNA splicing, immature B cells begin to express IgD
on the surface and migrate from the BM as transitional (T) B cells to continue
differentiation in peripheral lymphoid organs such as spleen and lymph nodes.
Functionality as well as variation in IgD, IgM, CD21, and CD23 levels can further
distinguish transitional B cells into T1, T2, and T3 subsets. A fraction of T1 B
cells may undergo receptor editing to remove remnant or new unwanted
specificities. T1 B cells progress to the T2 stage, and eventually to
CD19+B220+IgMintIgDhiCD21loCD23+ competent mature follicular (FO) B cells
(King and Monroe, 2000; Chung et al., 2003; Carsetti et al., 2004). In addition to
FO B cells, transitional B cells also give rise to other mature B cell populations
including marginal zone (MZ) and B1 B cells, but this appears to occur in a
ligand-dependent manner (Berland and Wortis, 2002; Pillai and Cariappa, 2009).
Naïve mature FO B cells that encounter a pathogen and receive costimulation
27
Figure 1.2 Mechanisms of self-tolerance in B cells. To maintain tolerance, B cells
that bind self-antigens during development either re-express RAG1/2 and undergo
secondary V(D)J rearrangement (receptor editing) to remodel the B cell receptor,
become functionally inactivated through indiction of intrinsic programs or B cell extrinsic
factors, or are deleted by apoptosis (Adapted from Goodnow et al., 2005).
28
from follicular helper T cells that recognize the cognate antigen form proliferation
structures in lymphoid follicles known as germinal centers (GCs) in secondary
lymphoid organs ( Shlomchik and Weisel, 2012; Victora and Nussenzweig,
2012). Between cycles of proliferation in the GC, point mutations are introduced
into the variable regions of the BCR genes by the enzyme activation-induced
cytidine deaminase (AID) in a process also known as somatic hypermutation
(SHM) (Muramatsu et al., 2000). Mutations that change the amino acid sequence
also alter the binding affinity of the receptor. This is followed by a series of
positive selection events and proliferation of B cells with high affinity BCRs in
what is known as affinity maturation (Rajewsky, 1996). B cells that receive
catastrophic mutations or gain autoreactivity through SHM generally undergo cell
death (Rajewsky, 1996). In some instances, B cells acquiring autoreactivity in
response to SHM or infection/immunization may undergo receptor revision, which
is similar to receptor editing but occurs in the periphery as opposed to the BM
(Noia and Neuberger, 2007; Victora and Nussenzweig, 2012; Hillion et al., 2005;
Nemazee and Weigert, 2000). AID activity can also lead to DNA double-strand
breaks that foster replacement of the µ heavy chain constant region genes with
other classes/isotypes of heavy chain constant region genes in what is known as
class switch recombination (CSR). CSR alters the constant and not variable
portion of the receptor, and therefore affects antibody function but not specificity
(Muramatsu et al., 2000; Stavnezer et al., 2008). B cells that survive these
germinal center reactions terminally differentiate into long-lived memory B cells
or antibody-producing plasma cells (Shlomchik and Weisel, 2012).
29
Beside conventional B cells, innate-like MZ and B1 B cells contribute to
the pool of mature B cell subsets in the periphery. MZ and B1 B cells display a
limited repertoire of antigen receptors compared to mature FO B cells that are
believed to be selected by antigens during development. These cells however,
have evolved as such to provide rapid responses early during infection at the
expense of forming classical memory B cells (Martin et al., 2001; Bendelac et al.,
2001).
MZ B cells, which are distinguished by expression of high levels of CD21
and CD1d and low levels of CD23, are thought to originate by positive selection
from the conventional B2 lineage during development by antigens that induce
BCR signaling in a thymus independent (TI) manner (Wen et al., 2005; Pillai et
al., 2005). MZ B cells derive their name from splenic marginal zone areas in
follicles where they reside. This location allows them to be among the first B cells
to encounter particulate blood-borne antigens and thus they are important in
early control of pathogens during infection (Martin et al., 2001).
B1 B cells are long-lived self-renewing CD19+B220loIgMhiIgDloCD23- B
cells that can be either be CD5+ (B1a) or CD5- (B1b) that populate peritoneal and
pleural cavities (Berland and Wortis, 2002; Hardy, 2006). B1 B cells are thought
to originate primarily through a distinct lineage from neonatal/fetal precursors in
the liver and omentum but may also be derived through induced differentiation of
transitional B cells in the conventional B2 lineage via BCR cross-linking by
multivalent TI antigens (Hayakawa et al., 2003; Berland and Wortis, 2002; Hardy,
2006; Montecino-Rodriguez et al., 2006; Montecino-Rodriguez and Dorshkind
30
2012). Consequently, B1 B cells express BCRs that have a limited repertoire
which lack mutations, and possess naturally low affinity and polyreactivity toward
foreign and self-antigens. In fact, many known specificities of B1 B cells are to
membrane lipids, oxidized lipids, and red blood cell epitopes. It is therefore not
surprising that B1 cells are implicated in several autoimmune conditions when
tolerance is breached (Jamin et al., 1993; Pao et al., 2007; Jellusova et al.,
2010). However, these B cells are maintained because their BCRs also cross-
react with epitopes found on common pathogens such as bacterial capsular
polysaccharides (Hardy, 2006; Berland and Wortis, 2002). Therefore, like MZ B
cells, these cells form a critical first line of defense by spontaneous production of
IgM antibodies (natural antibodies) particularly against encapsulated bacteria
(Bendelac et al., 2001; Carsetti et al., 2004).
The origins of a lymphoproliferative disorder are linked to the
differentiation stage at which it occurs (Kuppers, 2005). Identifying normal
counterparts, which are often blurred by atypical characteristics in malignant
cells, is critical to understanding the etiology and pathogenesis of these
diseases. Transformation by chromosomal translocations involving Ig loci and
(proto)oncogenes are molecular hallmarks of many types of B cell malignancies,
but such defining lesions are absent in CLL, leaving its origins unresolved
(Kuppers, 2005). However, based on the ability of CLL patients’ hematopoietic
stem cells (HSCs) to form unique CLL-like oligoclonal or monoclonal B cells
when transplanted in mice, Kikushige et al. (2011) suggest that transformation
events can also occur much earlier than perceived. Since CLL cases carrying
31
mutated Ig variable heavy chain (IgVH) genes are associated with good
prognosis while those with unmutated IgVH show poor survival (Hamblin et al.,
1999), it is unclear whether these two clinically opposed groups develop by
divergent or convergent mechanisms.
Comparative gene expression profiling using oligonucleotide microrrays
has been a powerful tool in gaining insight into the origins of CLL. Several
studies utilizing microarrays show that CLL cells have a distinct gene expression
profile compared to normal B cell subsets or other malignant populations (Klein
et al., 2001; Rosenwald et al., 2001; Jelinek et al., 2003). Moreover, clinically
heterogeneous CLL cases distinguished on the basis of IgVH mutation status
display a common gene expression profile suggesting that they derive from the
same precursor or undergo similar transformation mechanisms (Klein et al.,
2001; Rosenwald et al., 2001). Interestingly, Klein et al. (2001) reported that CLL
cells are mostly related to normal memory B cells compared to normal naïve,
CD5+, or GC B cell subsets. This finding contradicted the previous view that CLL
was a disease of naïve B cells, but was supported by Damle and colleagues
(2002) by showing that CLL cells express CD23, CD25, CD69, CD71, and have
reduced expression of CD22, FcγRIIb, CD79b, and IgD, which is a surface
phenotype associated with antigen-experienced B cells. CLL cells additionally
express the memory marker, CD27, but this marker is also expressed on human
MZ B cells. MZ B cells can also express other memory B-like markers, and
because they can participate in both thymus-dependent and independent antigen
responses and bear BCR configurations that are either mutated or unmutated,
32
this subset provides convenient possibilities for how mutated and unmutated CLL
may emerge. However, MZ B cells typically do not express CD5 or CD23
(Chiorazzi and Ferrarini, 2011; Weill et al., 2009).
More recently, Seifert et al. (2012) using comparative gene profiling of
CLL cells and sorted normal B cell subsets, reported that CLL originates from
CD5+ B cells. Unlike earlier studies, CD27+ memory B cells, which are not a
homogeneous population, were split into IgM+ and class-switched memory B
cells, and adult PB mature CD5+ B cell subsets were chosen instead of using
cells derived from umbilical cord blood, which is conveniently rich in CD5+ B cells
but are mainly immature. Gene expression profiles of CLL cells were compared
with that of normal mature CD5+, naïve, splenic MZ, and IgM+ and class-switched
memory B cells. This study found that while CLL cells have a distinct gene
expression signature compared to normal B cell subsets, the leukemic cells are
most closely related to CD5+ and naïve B cells. Furthermore, CLL with
unmutated IgVH most closely resemble mature CD5+CD27- PB B cells while CLL
with mutated IgVH genes most closely resemble a previously unknown
CD5+IgM+CD27+ post-GC B cell subset (Seifert et al., 2012).
CD5 is a hallmark of CLL cells as well as the murine B1a B cell.
Additionally, CLL and B1a B cells share other features including interleukin 10
(IL-10) production, and a limited BCR repertoire, leading to the hypothesis that
the natural counterpart for CLL is the human equivalent of the B1a B cell (Dono
et al., 2004; Nordgren and Joshi, 2010). Both CLL cells and murine B1 B cells
are known to produce IL-10, which they probably use as an autocrine growth
33
factor or for immunosuppressive functions (O’Garra et al, 1992; Gary-Gouy et al.,
2002; 2010; DiLillo et al., 2013). CLL exhibits a restricted Ig gene repertoire and
displays an antibody reactivity profile skewed toward cytoskeletal and
membrane-associated self, modified self, and bacterial antigens (Rosen et al.,
2010). This reactivity profile is also shared by B1 and MZ B cells that are
positively selected for these specificities, as well as subsets of developing
(transitional) and extrafollicular B cells that exhibit self-reactivity produced by
primary Ig gene rearrangements, or as an unintended consequence of somatic
mutation, respectively (Rosen et al., 2010). The human B1 B cell, however, is
elusive since CD5 is not a B cell subset marker in humans. A recent description
of a CD20+CD27+CD43+CD70- human blood B1 B cell population that shares
properties with murine B1 cells such as unmutated repertoire, antigenic
specificity, BCR signaling, and natural antibody production was received with
controversy (Griffin et al., 2011, Griffin et al., 2012, Reynaud and Weill, 2012;
Descatoire et al., 2011).
Approximately 30% of circulating B cells in humans display CD5 on their
surface, which is expressed constitutively or upon induction (Youinou et al.,
1999). CD5 can be expressed in transitional or extrafollicular B cells undergoing
receptor editing or revision, respectively (Hillion et al., 2005; Sims et al., 2005). In
addition, CD5 expression may be induced on B cells rendered anergic by chronic
(auto)antigenic stimulation (Hippen et al., 2000). CD5 negatively regulates B cell
receptor signaling, which, given the proclivity of CD5+ B cells toward self-
reactivity, can serve a protective role by suppressing B cell activation to limit
34
autoantibody production (Youinou et al., 2006). Thus, because CLL shares a
similar pattern of antigenic reactivity and several markers including CD5
expression with a variety of B cell subsets, all these may be considered potential
etiological sources of human CLL, which may partly explain the clinical
heterogeneity of this disease.
1.3.2 Genetic and Chromosomal Defects in CLL
Although there is no single lesion that defines all CLL, a series of
chromosomal abnormalities and deregulated genes are frequently detected
(Klein and Dalla-Favera, 2010; Kuppers, 2005. The first chromosomal defects in
CLL were found using conventional cytogenetics but this was complicated by the
fact that mitogens were required to induce mitosis since CLL cells divide slowly.
These methods found that ~50% of CLL cases carried chromosomal defects with
the most common being trisomy 12 and chromosome 13q deletion (Juliusson et
al., 1990). More sensitive methods utilizing comparative genomic hybridization or
fluorescence in-situ hybridization show that over 80% of CLL patients carry a
chromosomal abnormality (Bentz et al., 1995; Dohner et al., 2000). The most
common are 13q14 deletion (40-60%), 11q22-q23 deletion (15-20%), trisomy 12
(15-30%), 17p13 deletion (~10%), 6q deletion (6%), and rare abnormalities
(trisomy 3q, trisomy 8q, and translocation involving 14q32) accounting for 12% of
cases (Matutes et al., 1996; Dohner et al., 2000; Van Bockstaele et al., 2009).
Most chromosomal defects in CLL are prognostic factors that define
subgroups. Patients with CLL cells bearing 17p13 and 11q22-q23 deletion have
35
the worst prognosis with median survival of 32 and 79 months, respectively
(Dohner et al., 2000). Interestingly, the most common defect (13q14 deletion) is
associated with a better outcome (133 months) compared to normal karyotype
(111 months) while trisomy 12, although associated with atypical morphology,
remains relatively stable with a median survival of 114 months (Dohner et al.,
2000; Matutes et al., 1996). Moreover, 17p13 and 11q22-q23 deletions are
associated with late diagnosis in addition to an aggressive nodal disease for
11q22-q23 deletions (Dohner et al., 1997), and refractory therapy in 17p13
deletions (Dohner et al., 1995).
That cytogenetic defects are related to clinical outcomes suggests that
certain genes in the affected loci are involved in CLL etiology or progression.
Some of these deletions are quite large and involve many genes. However, gene
expression profiling of CLL subgroups defined by chromosomal aberrations
confirms that many of the differentially expressed genes map to the deleted
regions in the respective chromosomes (Haslinger et al., 2004). Trisomy 12, for
example, implicates dosage alteration for an unknown number of genes. The
most common aberration, 13q14 deletion, involves a cluster of genes in the
minimally deleted region that include a potential tumor suppressor DLEU2, and
microRNAs miR15a and miR16-1 (Liu et al., 1997; Calin et al., 2002). These
miRNAs, which are known to play a role in prostate cancer, are reduced in ~68%
of CLL cases (Bonci et al., 2008; Calin et al., 2002). miR15a and miR16-1 targets
include CCND1, Wnt3a, and Bcl2 in prostate tumors (Bonci et al., 2008) and can
inhibit Bcl2 leading to apoptosis of leukemia cell lines (Cimmino et al., 2005).
36
Deletion of this region in mice leads to a spectrum of CLL-like lymphoproliferative
diseases suggesting that it may be involved in pathogenesis of CLL (Klein et al.,
2010; Lia et al., 2011). The next common defect, 11q22-q23 deletion, is
associated with loss the DNA double-strand break sensing gene ataxia
telangiactasia mutated (ATM). Additionally, it is common to find mutations in the
remaining allele or mutations in both alleles without a deletion, suggesting that
ATM is important for driving pathogenesis in a subset of CLL cases (Schaffner et
al., 1999). Skowronska et al. (2011) analyzed ATM mutations and deletions in
CLL cells and found that a single loss of ATM at one allele was unlikely to initiate
CLL but rather influenced rapid disease progression through total loss of ATM
after a stochastic mutation in the remaining allele. 17p13 deletion leads to loss of
the tumor suppressor protein TP53 (p53). About 4.5% of CLL patients show loss
of p53 but without 17p deletion, which is associated with poor prognosis and is
attributed to mutation of this gene (Zenz et al., 2010).
Other gene defects occur frequently but are not associated with
chromosomal aberrations. For example miR-29 and miR-181, which target and
are inversely correlated with expression of the proto-oncogene T cell leukemia 1
(TCL1), are commonly downregulated in poor prognosis CLL (Pekarsky et al.,
2006). Bcl2 and other Bcl2-family genes are known to be overexpressed in CLL
and confer resistance to apoptosis (Hanada et al., 1993; Buggins and Pepper
2010). Other genes that are often overexpressed in CLL include Notch1, SF3B1,
and DAPK. Deregulation of many of these genes has been attributed to
epigenetics. For instance, abnormal methylation patterns have been shown to
37
alter TCL1, DAPK1, and Bcl2 expression in CLL (Plass et al., 2007; Zenz 2010;
Mansouri et al., 2012).
1.3.3 The Role of the B Cell Receptor
Many B cell lymphoproliferative disorders, like normal B cells, depend on
the BCR expression for survival (Kuppers, 2005). There is increasing evidence
that CLL does not only depend on the BCR, but the BCR plays a central role in
pathogenesis. During analyses of CLL BCRs in the 1990s, it was discovered that
mutation status of IgVH genes separates CLL cases into two groups: those
bearing mutations (mutated) and those without (unmutated) (Schroeder and
Dighiero, 1994; Fais et al., 1998). Thereafter, it was shown that mutation status
(defined as greater or lesser than 98% homology to the nearest germline) is
related to clinical outcome; the BCRs in approximately half of CLL cases are
mutated and the patients have good prognosis while the remaining cases have
unmutated BCRs and the patients have poor prognosis (Hamblin et al., 1999;
Damle et al., 1999; Maura et al., 2013). In a clever experiment, Herve et al.
(2005) showed that unmutated CLL expressed polyreactive and autoreactive
antibodies that were not seen in mutated cases; however, in vitro reversion of
mutations back to the germline configuration in the latter cases restored capacity
to bind self-antigens, suggesting that signaling through the BCR may explain
clinical heterogeneity based on mutation status. These differences in mutation
status raise the question whether unmutated and mutated cases derive from two
precursors: naïve and post-GC B cells, respectively (Fais et al., 1998).
38
Additional evidence that the BCR itself is involved in the etiology of CLL
stems from the observation that CLL has a biased repertoire, and 20-30% of
cases have highly similar or even identical BCRs based on complementarity
determining region 3 (CDR3) homology, which is referred to as stereotypy
(Messmer et al., 2004; Ghiotto et al., 2004; Widhopf et al., 2004; Stamatopoulos
et al., 2007; Agathangelidis et al., 2012). The CDR3 is a hypervariable region
formed at the V(D)J junction that determines the specificity of the receptor (Xu
and Davis , 2000). In humans, the probability of getting the same three gene
segments in a heavy chain is 1 in 7650 and over 1 in 1.5 million for both heavy
and κ light chain (Widhopf et al., 2004). The remarkable odds at which
stereotypic BCRs occur in CLL imply that selection of CLL cells is driven by a
limited group of common antigens (Ghiotto et al., 2004). The most frequently
used IgVH genes are VH1-69, VH3-07, and VH4-34. These genes preferentially
associate with a set of D and J genes resulting in similar structures. Typically,
VH1-69 has a long acidic CDR3 with many tyrosines and lacks mutations; VH3-
07 has a short CDR3 that is minimally acidic and generally mutated; VH4-34 also
has long acidic CDR3 with many tyrosines and may either be mutated or
unmutated (Chiorazzi and Ferrarini, 2003). Some CLL cases use VH3-21 which
tends to pair with Vλ2-14 and is associated with poor survival independent of
mutation status (Thorselius et al., 2006).
CLL cells have a restricted Ig repertoire that recognizes apoptotic cell
debris and microbial motifs (Rosen et al., 2010). Earlier knowledge that CLL
patients have a high incidence of autoimmune hemolytic anemia and
39
thrombocytopenia and that CD5+ B cells are involved in autoimmune conditions
in mice has led to the finding that serum from CLL patients contains
crossreactive antibodies with specificities to formed blood elements and
cytoplasmic and nuclear antigens (Hamblin et al., 1986; Brooker et al., 1988;
Sthoeger et al., 1989). More recently, screening the specificities of expressed
and purified CLL antibodies found that antibodies bound neoantigens revealed
during apoptosis such as non-muscle myosin heavy chain IIA, vimentin, filamin
B, coffilin-1, cardiolipin, and proline-rich acidic protein-1, and modified epitopes
such as oxidized Low-density lipoprotein (Ox-LDL). CLL antibodies also bound
Streptococcus pneumoniae polysaccharide which like Ox-LDL, contains
phosphorylcholine (Catera et al., 2008; Myhrinder et al., 2008; Chu et al., 2010).
Reactivity to other microbial antigens have been reported by Hoogeboom et al.
(2013) who found that a subset of mutated CLL recognized fungal glycans, and
Kostareli et al. (2009) who found persistent EBV and CMV DNA in a subset of
patients using VH4-34, suggesting that fungal and viral antigens could be
involved in CLL pathogenesis in a subset of patients. This reactivity profile
skewed toward cytoskeletal and membrane-associated self, modified self, and
bacterial antigens is also shared by B1 and MZ B cells that are positively
selected for these specificities (Bendelac et al., 2001). Since natural antibodies
from healthy population also recognize most of these antigens (Catera et al.,
2008), Myhrinder et al., 2008), and Chu et al., 2010), it raises the possibility that
CLL derives from B cells endowed with scavenger ability for apoptotic debris and
removal of pathogenic bacteria.
40
The BCR in CLL appears to be engaged by antigens but atypical
expression of signaling components indicate some slight differences from normal
BCR signaling (Woyach et al., 2012). BCR signal transduction occurs through a
multicomponent cascade regulated primarily by protein tyrosine kinases and
phosphatases. The BCR is linked to Igα (CD79a) and Igβ (CD79b), which contain
immunoreceptor tyrosine-based activation motifs (ITAMs). This BCR signaling
complex is also coupled with a number of positive (CD19, CD45, and CD21) and
negative (CD5, CD22, CD72, and FcγRIIB) regulators that balance immunity and
tolerance. Activation occurs when BCRs are crosslinked by antigens, leading to
oligomerization and phosphorylation of the ITAMs by the Src family protein
tryrosine kinase, Lyn. Lyn also phosphorylates the cytoplasmic tail of CD19 to
activate phosphatidylinositol 3-kinase (PI3-K) signaling. Spleen tyrosine kinase
(Syk) is recruited to the phosphorylated ITAMs and phosphorylates a number of
targets in turn setting off a cascade that activates NF-κB and MAP kinase
pathways (Goodnow, 2001; Xu et al., 2005; Kurosaki et al., 2010; Stevenson et
al., 2011). Expression patterns of BCR signaling components in CLL indicate
previous or on-going engagement of the antigen receptor. CD5 is a scavenger
receptor family glycoprotein normally expressed in T cells but also seen in a
subset of B cells. In T cells, CD5 acts as a negative regulator in fine-tuning T cell
receptor (TCR) signals in response to antigens (Azzam et al., 2001). In B cells,
CD5 appears to play the same role in negatively regulating BCR signals in
response to antigens since genetic disruption of CD5 leads to loss of tolerance in
mice (Bikah et al., 1996; Hippen et al., 2000). CD5 functions by recruiting the
41
inhibitory protein tyrosine phosphatase SHP-1 to the BCR in B1 cells (Sen et al.,
1999; Ochi and Watanabe, 2000). Downregulation of B220, an isoform of CD45
(Ptprc) and pan-B cell marker that acts as a positive regulator of BCR signaling,
suggests a concerted effort with CD5 to quell antigen-induced BCR signals in
B1a B cells (Hardy and Hayakawa, 2001; Berland and Wortis, 2002). The surface
immunophenotype comprising of CD5, a hallmark of CLL, reduced expression of
IgM, IgD, and CD79b, and expression of activation markers postulate that these
cells derive or are driven by antigenic stimulation (Caligaris-Cappio et al., 1982;
Matutes and Polliack, 2000; Damle et al., 1999). Functionally, ligation of the
BCR in CLL cell has been shown to induce the expression of anti-apoptotic
molecules Bcl2 and Mcl1 through NF-κB leading to increased survival,
particularly in unmutated cases (Bernal et al., 2001; Guarini et al., 2008).
CLL cells oddly express TCR signaling components. Cytotoxic T-
lymphocyte antigen 4 (CTLA4) is expressed in T cells as an inhibitor of TCR
signals since mice with this deficiency have uncontrolled proliferation of T cells
and develop autoimmunity (Alegre et al., 2001; Goodnow et al., 2005). CTLA4 is
also expressed on CLL B cells but its expression correlates inversely with
disease progression, indicating that CTLA4 plays a similar role in B cells and
consequently, loss of BCR signal suppression leads to expansion of CLL cells
(Kosmaczewska et al., 2005; Joshi et al., 2007). ζ–chain-associated protein
kinase 70 (ZAP-70) is expressed in T cells and natural killer cells and is required
for propagating receptor signals (Au-Yeung et al., 2009). Rosenwald et al.
(2001), using microarrays, found the most reliable gene that discriminated
42
unmutated and mutated CLL cases was ZAP-70. Expression of ZAP-70 in CLL is
associated with poor prognosis (Durig et al., 2003). In CLL cells, ZAP-70 plays a
similar role to Syk and enhances BCR signals (Stevenson et al., 2011; Woyach
et al., 2012). CD38 is highly expressed in activated B and T cells as well as a
subset of CLL cells (Malavasi et al., 2011). Moreover, CD38 expression, similar
to unmutated and ZAP-70+ CLL, is associated with a distinct gene expression
profile and poor prognosis, linking BCR signals to cell function and clinical
outcome (Damle et al., 1999, Deaglio et al., 2003; Joshi et al., 2007). Because of
the relative ease in determining CD38 and ZAP-70 expression by flow cytometry,
they can act as surrogate markers for mutation status (Hamblin et al., 2002;
Crespo et al., 2003). Inhibition of BCR signaling with small molecule inhibitors
that target Syk (fostamatinib) and phosphatidylinositol 3-kinase delta (PI3-kδ)
inhibitor (CAL-101) or deleting PKCβ blocks BCR signaling and CLL cell survival
and migration in vitro, and tumor growth in mice (Quiroga et al., 2009; Suljagic et
al., 2010; Hoellenriegel et al., 2011; Holler et al., 2009). Currently, there are nine
inhibitors that target BCR signaling in early phase clinical trials for B cell
malignancies that include four for CLL (fostamatinib, Dasatinib, CAL-101, and
Ibrutinib) (Woyach et al., 2012).
1.3.4 Role of theTumor Microenvironment
CLL cells undergo spontaneous apoptosis in vitro and are refractory to
long-term culture (Collins et al., 1989). This is remarkable since CLL cells often
overexpress anti-apoptotic molecules such as Bcl2 and Mcl1 (Buggins and
43
Pepper 2010). In fact, for many years, CLL was regarded as a disease of
accumulation, rather than proliferation, of lymphocytes defective in apoptosis
(Dameshek, 1967; Andreeff et al., 1980; Caligaris-Cappio and Hamblin, 1999).
This later changed when in vivo labeling with heavy water showed that CLL cells
proliferate and have a much higher turnover than earlier perceived (Messmer et
al., 2005). This contradiction between in vivo and in vitro activity of CLL cells
strongly implicates the involvement of some extrinsic cellular or soluble factor(s)
that typical cultures do not recapitulate.
Infiltration of CLL cells disrupts and re-organizes the normal architecture
of lymphoid organs (Fecteau and Kipps, 2012). In the lymph node (LN), BM, and
spleen to a smaller extent, CLL cells can be found intermixed non-leukemic cells
such as T cells and follicular dendritic cells (FDCs) in histological structures
named pseudofollicles or proliferation centers (PCs) (Swerdlow et al., 1984;
Soma et al., 2006; Schmid and Isaacson, 2007). CLL cells in pseudofollicles
express the proliferation marker Ki67 and constitutively activate NF-κB (Herreros
et al., 2010). These specialized niches or microenvironments are common in
many tumors and provide support for tumor growth, escape from immune
surveillance, and chemoresistance (Whiteside, 2008).
The CLL tumor microenviroment is comprised of a feedback network
between leukemic and support cells that is mediated by cytokines/chemokines,
and direct interaction. The major cytokine/chemokine players are those of the
tumor necrosis factor (TNF) family cytokines such B cell-activating factor of TNF
family (BAFF) and a proliferation-inducing ligand (APRIL), which are produced by
44
accessory cells (Fecteau and Kipps, 2012; Endo et al., 2007). BAFF and APRIL
have been reported to support survival of CLL cells in vitro by engaging their
receptors, B cell maturation antigen (BCMA) and transmembrane activator and
calcium modulator cyclophilin ligand-interactor (TACI) on CLL cells, to activate
canonical NFκ-B signaling (Endo et al., 2007). The chemokines CXCL12 (stromal
cell-derived factor-1, SDF-1) and CXCL13, also produced by support cells, attract
leukemic cells and other lymphocytes that express CXCR4 (Fecteau and Kipps,
2012). CLL cells can also receive direct signals, for example, through
engagement of CD40 on leukemia cells and CD40L on T cells. Stimulated CLL
cells, in turn, produce CCL3, CCL4 and CCL22 to recruit more T cells and
monocytes to the pseudofollicles (Endo et al., 2007; Fecteau and Kipps, 2012).
Co-culture experiments show that normal cells such as FDCs, endothelial
cells, and BM stromal cells (BMSCs) can enhance survival of CLL cells
(Pedersen et al. 2002; Maffei et al., 2011; Panayiotidis et al., 1996). BM stromal
cells (BMSCs), which naturally support developing B cell precursors, have been
found to prolong survival and prevent apoptosis of CLL cells in vitro, indicating
that these cells have the potential to protect CLL cells in the BM (Panayiotidis et
al., 1996). BMSCs produce SDF-1 to attract leukemic cells, which express
CXCR4, and tether them via VCAM-1 on their surface to CD49d on the leukemic
cells (Fecteau and Kipps, 2012). BMSCs can also induce resistance to
chemotherapeutic drugs in vitro in a mechanism that involves Notch signaling
(Kamdje et al., 2012). BMSCs may contribute to pathogenetic mechanisms since
45
this interaction can induce genetic changes in leukemic cells including
upregulation of the TCL1, a known oncogene (Sivina et al., 2012).
In an effort to determine other cells that might provide support to cultured
CLL cells, Burger et al. (2000) found large, round, and adherent peripheral blood
mononuclear cells that protected co-cultured leukemic cells from apoptosis akin
to BSMCs. Because these cells were reminiscent of thymic nurse cells, they
were named nurse-like cells (NLCs). NLCs have also been found in spleens of
CLL patients (Burger et al., 2000; Tsukada et al., 2002). NLCs are CD14+
monocyte-derived cells that express SDF-1, normally produced by BM stroma to
support developing early B cell precursors, through which they protect CLL cells
from apoptosis. NLCs additionally secrete BAFF and APRIL, which promote
survival of CLL cells in a SDF-1-independent pathway that requires NF-κB to
induce Mcl-1. NLCs express CD31, a ligand for CD38, which is expressed in a
subset of CLL cases and may provide additional survival signals and modulate
cytokine production by CLL cells (Fecteau and Kipps, 2012). CLL cells not only
subvert NLCs to produce survival factors, but may use them to evade immune
detection, based on comparative gene expression profiling studies showing that
NLCs derived from co-cultures with CLL with CD14+ PBMCs from healthy or CLL
patients exhibit impaired immune competence (Bhattacharya et al., 2011). NLCs
produce chemokines SDF-1 and CXCL13, which recruit CLL cells since they
express their receptors, CXCR4 and CXCR5, respectively. CLL cells, in turn,
produce CCL21, CCL3 and CCL4 to recruit more monocytes and T cells to PCs
(Fecteau and Kipps, 2012).
46
Abnormalities of the T cell compartment in CLL were first reported in
1980s. The ratio of circulating CD4+ T cells to CD8+ T cells is inverted, resulting
in an increase in CD8+ T cells (Kay 1981; Herrmann et al., 1982). However, CD4+
T cells are increased in LN and BM of CLL patients (Caligaris-Cappio and
Hamblin, 1999), suggesting that they are preferentially recruited to these sites.
Researchers have also observed frequent clonal CD4+ and CD8+ T cell
expansion in CLL patients reflecting potential selection by leukemic cells (Farace
et al., 1994; Serrano et al., 1997). CLL cells induce gene expression changes in
CD4+ and CD8+ T cells particularly in those that affect cytoskeleton
polymerization and immune response (Gorgun et al., 2005; Gorgun et al., 2009;
Kiaii et al., 2013). Other changes in T cells from CLL patients include the
expression of markers of anergy or exhaustion and cytokine/chemokine
programs that support CLL survival (Brusa et al., 2013; Riches et al., 2013)
(Gorgun et al., 2005; Gorgun et al., 2009; Brusa et al., 2013; Riches et al., 2013;
Kiaii et al., 2013). Functionally, these T cells are impaired in immunological
synapse formation. Interestingly, these changes are not permanent and can be
reversed by treatment with the immunomodulatory drug, lenalidomide, which
suggests an active interaction between leukemic cells and T cells (Gilling et al.,
2012; Ramsay et al., 2008; Gorgun et al., 2009). CLL cells produce CCL22 to
attract CD4+ T cells to PCs where ligation of CD40 on CLL cells and CD40L on T
cells enhances the survival of CLL cells. In fact, the CD40-CD40L interaction is
often exploited to prolong CLL cultures by propagating them on a layer of
CD40L-transfected fibroblasts (Kater et al., 2004; Ghia et al., 2002). In an
47
investigation by Vogler et al. (2009), CLL cells cultured on a layer of CD40L-
expressing fibroblasts in the presence of IL-4 induced a 1000-fold resistance to a
Bcl2 family antagonist, suggesting that these interactions may contribute to the
chemoresistance often encountered in LNs.
Regulatory T cells (Tregs) are increased in CLL. In several studies
examining the Tregs subset, defined as either CD4+CD25+ or CD4+CD25+ with
Foxp3, or with low or absent CD127, absolute number of Tregs was found to be
increased compared to healthy controls and as a fraction of T cells in most cases
(D’Arena et al., 2012). Higher Treg numbers are associated with advanced
disease and are predictive of time-to-treatment in patients with early-stage CLL
(Weiss et al., 2011). These observations hint that immunosuppression by Tregs
contributes to CLL pathogenesis. However, CLL cells themselves produce
immunosuppressive cytokines, IL-10 and TGFβ. These cytokines skew immunity
from a Th1 to a Th2 profile. Furthermore, T cells from CLL patients express more
CTLA4, an inhibitor of TCR activation, than those in healthy individuals (Ramsay
et al., 2008; DiLillo et al., 2013; Motta et al., 2005). Collectively, this paints a
picture in which T cells in CLL have been subverted to favor tolerance while
neglecting immunity. The presence or role of other cells with anti-tumor activity
(natural killer (NK) and NK T cells (NKT) in pseudofollicles has not been
established. However, NK cell defects in killing and lytic granule production are
well known in CLL (Kay et al., 1984). On the other hand, NKT cells from PB of
CLL patients appear functionally competent for cytotoxicity, and CLL cells
48
express CD1d and retain capacity to present CD1d-restricted antigens to NKT
cells (Guven et al., 2003; Fais et al., 2004).
1.4 ANIMAL MODELS OF CLL
1.4.1 Xenograft Mice
The difficulty in establishing long-term cultures of leukemic cells from CLL
patients has partly contributed to the prominence of CLL animal models (Table
1.2). One of the first approaches to generate CLL models was by xenogeneic
transplantation of primary CLL cells or cell lines into immunodeficient mice. Early
models were plagued by poor engraftment efficiency and retention of leukemic
cells at the inoculation site (Kobayashi et al., 1992; Hummel et al., 1996). The
failure of CLL cells to migrate to other lymphoid tissues may be the result of
compatibility issues with human cells in mice, but CLL cell-intrinsic factors cannot
be discounted because Shimoni et al. (1997) showed that engraftment ability
correlates with Rai tumor stage. CLL cell lines derived from more aggressive
disease (e.g. the JVM3 line derived from a CLL patient with prolymphocytic
transformation) engrafted with close to 100% efficiency in irradiated nude mice,
while a CLL line derived from a patient with less progressed disease, called
MEC2, failed to engraft (Loisel et al. (2005). Recently, Bertilaccio et al. (2009)
using Rag2-/-γc-/- immunodeficient mice, which lack NK cells (unlike earlier
models), found that the CLL cell line, MEC1, could be engrafted with 100%
49
efficiency. Moreover, these cells infiltrated several organs after intravenous or
subcutaneous injection leading to an aggressive disease.
Although xenograft models are usually limited in application by the fact
that they typically rely on transplanting end stages of a disease, Kikushige et al.
(2011) exploited a xenogeneic model to show that oncogenic defects in CLL can
occur in HSCs. In this study, HSCs from CLL patients transferred to NOD/RAG1-/-
IL2rgnull mice gave rise to lymphoid cells including B cells that mature to
oligoclonal or MBL-like B cells. Nevertheless, due to the short generation time of
xenograft mice, they remain a vital tool in evaluating certain disease aspects
such as therapeutic strategies.
1.4.2 New Zealand Mice
New Zealand strains of mice are prone to autoimmunity and spontaneous
development of an age-dependent CLL-like lymphoproliferative disease (Stall et
al., 1988; Kono et al., 1994; Phillips et al., 1992; Raveche et al., 2007). CD5+ B
cells, the predominant subset in fetal and neonatal mice, decline days after birth
and remain relatively low except in the peritoneal and pleural cavities, where they
are abundant throughout life. Some mouse strains such as New Zealand black
(NZB) and New Zealand white (NZW) have a higher frequency of these cells.
For instance, CD5+ B cells make up 5-10% of splenic cells in NZB mice at 3
months of age compared to about 2% in other strains (Hayakawa et al., 1983;
Berland and Wortis, 2002). Interestingly, CD5+ B cells reappear in elderly mice,
and clonal populations capable of self-renewal can be detected in mice older
50
than 15 months in most strains. However, clonal CD5+ B cell populations are
detectable much earlier (3-4 months) in the peritoneum, spleen, and other organs
in NZB, NZW, and are highest in NZB x NZW F1 mice (Stall et al., 1988). Older
NZB mice develop a CLL-like disease characterized by small mature hyperdiploid
CD5+IgM+B220lo B cells with unmutated Ig genes in the spleen, PB, peritoneal
cavity, and rarely in LN but not BM (Phillips et al., 1992; Mahboudi et al., 1992;
Raveche et al., 2007; Salerno et al., 2010). NZ mice have long been used to
study autoimmunity with NZW x NZW F1 hybrid mice being a model of systemic
lupus erythematosus (SLE). Dissection of such crosses found that MHC
haplotypes controlled whether the mice would develop SLE or CLL. Homozygous
H-2z/z mice had the highest frequency of CD5+ B cells and developed CLL while
H-2d/z heterozygotes were prone to SLE (Helyer and Howie, 1963; Okada et al.,
1991; Hamano et al., 1998). Two cytokines, IL-10 and IL-5, which can act as
growth factors for normal B1 cells (Gary-Gouy et al., 2002; Hitoshi et al., 1990),
are critical for CLL development in these mice. Loss of IL-10 in CD5+ B cells of
NZB leads to increased cell-cycle block and apoptosis in CD5+ B cells, and NZB
mice deficient in IL-10 fail to develop CLL. Interestingly, PerC B1 B cells were not
sensitive to loss of IL-10 and their frequency remained unaffected (McCarthy et
al., 2004; Czarneski et al., 2004). Expression of an IL-5 transgene in SLE-prone
NZB x NZW F1 mice, in contrast to normal B1 B cells, reduced production of
antibodies and development of SLE while favoring CLL progression (Wen et al.,
2004). Raveche et al. (2007), using NZB mice crossed to DBA/2 F1 mice in a
genome-wide linkage study to identify loci associated with CLL in these mice,
51
Table 1.2 Murine models of CLL
Model Characteristic features Reference
NZB Spontaneous model; CD5+IgM
+B220
lo B cells in Sp and PerC Phillips et al., 1992;
at 4 mo; miR16-1 mutation; late-onset leukemia. Raveche et al., 2007
Eµ-TCL1 CD5+IgM
+B220
lo B cells first detected in the PerC at 2 mo; Bichi et al., 2002;
leukemia in 13-18 mo; frequent secondary malignancies. Zanesi et al., 2006
TRAF2DN/BCL2 CD5+IgM
hiB220
IntCD11b
+; splenomegaly, lymphadenopathy; Zapata et al., 2004
80% dead by 14 mo.
APRIL B1 neoplasm; CD5+IgM
loB220
lo, detectable in PerC at 4-5 mo; Planelles et al., 2004
pleural effusion, ascites.
PKCα-KR HPCs give rise to CD19hiCD5
+IgM
loCD23
+IgD
lo lymphocytes Nakagawa et al., 2006
in vitro and in Sp & LN of RAG1-/-
mice.
SV40 large T Ag Sporadic expression of SV40 large T antigen; ter Brugge et al., 2009
CD5+B220
+IgM
+CD43
+ in PB, other organs; leukemia by 10 mo.
miR15a/16-1-KO Low penetrance, late onset CD5+IgM
+B220
lo MBL, CLL/SLL in Klein et al., 2010
PerC, Sp, PB, BM, & LN; non-Hodgkin’s lymphoma.
miR29 Indolent leukemia; CD5+CD19
+IgM
+ B cells in Sp at 2 mo; Santanam et al., 2011
humoral defect.
Abbreviations: Perc, peritoneal cavity; Sp, spleen; LN, lymph node; PB, peripheral blood; BM;
bone marrow; HPCs, hematopoietic progenitor cells; mo, months.
52
found previously undescribed risk loci including one with synteny to 13q14 in
humans. 13q14 deletion is the most common cytogenetic defect in human CLL
and implicates loss of miR15a and miR16-1, among other genes, in CLL
development (Matutes et al., 1996; Klein et al., 2010). These microRNA genes
are not deleted in mice but sequencing them revealed a point mutation in the 3'
flanking region of miR16-1 that corresponded with its downregulation in tissues
suggested a possible role in murine CLL as well. Exogenous introduction of
miR15-1 or miR16-1 into cells derived from NZB mice decreased cyclin D1
levels, and increased cell cycle G1 phase block and sensitivity to drug-induced
apoptosis indicating CLL disease in NZB mice is partly due to loss of cell cycle
regulation (Raveche et al., 2007; Salerno et al., 2009). Moreover, these mice
exhibit an inherent genomic instability linked to reduced fidelity in DNA repair
(Raveche et al., 1979; Reddy and Flalkow, 1980). The strong genetic component
in NZ mice is much like familial CLL. More importantly, this model is useful in
dissecting the relationship between CLL and autoimmunity.
1.4.3 Eμ-TCL1 Transgenic Mice
T cell leukemia/lymphoma 1 (TCL1) is a proto-oncogene that is commonly
overexpressed in many lymphoproliferative disorders, including CLL. In CLL,
TCL1 expression levels correlate with shorter time-to-treatment and aggressive
disease suggesting a possible role in pathogenesis (Narducci, et al., 2000;
Herling et al., 2006; Aggarwal et al., 2008). TCL1 was first identified as the gene
commonly involved in chromosomal translocations and inversions in mature T
53
cell leukemias, namely, T cell prolymphocytic leukemia and T cell chronic
lympocytic leukemia (Virgilio et al., 1994). TCL1 is normally expressed early in
lymphocyte development and diminishes in later stages such as in mature T
cells, post-GC B cells, and plasma cells. TCL1 is required for lymphocyte
development sincedeficient mice show loss of both T and B cell numbers and
impaired function (Narducci, et al., 2000; Kang et al., 2005; Herling et al., 2007).
Virgilio et al. (1998) tested the oncogenic potential of TCL1 in mice by placing it
under the control of Lck proximal promoter for targeted overexpression in the T
cell compartment. TCL1 overexpression induced expansion of T cells in young
mice with CD8+ mature T cell leukemias developing in older mice. However,
TCL1 appears to be more tumorigenic in murine B cells since overexpression of
TCL1 in both B and T compartments predominantly generates a variety of mature
B cell lymphomas (Hoyer et al., 2002). The mechanisms of TCL1-mediated
transformation in B cells are still unfolding. Under normal conditions, TCL1 acts
as a co-activator of Akt by binding to its pleckstrin homology domain and
augmenting phosphorytion of Akt and its nuclear translocation to induce growth,
survival, and proliferation (Pekarsky, et al., 2000; Teitell et al., 2005). However,
several other functions of TCL1 have been noted in neoplastic cells such as
transcriptional regulation and inhibition of DNA methylation (Pekarsky, et al.,
2008; Motiwala et al., 2011; Gaudio et al., 2011; Palamarchuk et al., 2011).
Bichi et al. (2002), in a quest to elucidate the role of TCL1 specifically in B
cell malignancies, discovered that targeted overexpression of TCL1 in the B
lineage causes a CLL-like disease in elderly mice. These mice carry the human
54
TCL1 transgene under the control of the VH promoter and IgH μ enhancer (Eμ-
TCL1 mice) for targeted expression in immature and mature B cells. Eμ-TCL1
are characterized by progressive accumulation of G0/G1-arrested
CD5+IgM+B220lo B cells first observed in the PerC at 2 months, in the spleen by
3-5 months, and in the bone marrow by 5-8 months. By 13-18 months, these
mice develop a CLL-like malignancy indicated by hepatosplenomagaly, high
white blood cell (WBC) counts (180x106 cells/mL versus 2.8x106 cells/mL in wild
type mice), and lymphadenopathy. Additionally, Zanesi et al. (2006) observed
that over a third of these mice develop secondary malignancies, a common
feature in human CLL as well, and these may be attributed to genetics or failed
tumor surveillance in untreated mice. Sequencing Ig genes from leukemic B cells
shows that they are mainly unmutated, a characteristic seen in aggressive CLL in
humans, and bear specificities akin to B1 cells directed toward lipid and
polysaccharide motifs common in self and microbial antigens (Yan et al., 2006).
Other features of human CLL demonstrated in these mice include the ability to
induce T cell dysfunction. Eμ-TCL1 leukemic cells induce clonal expansion of T
cells with defective immunological synapse formation and altered gene
expression. These T cell changes are temporary and can be reversed by
lenalidomide therapy (Gorgun et al., 2009; Hofbauer et al., 2011). Because of the
many similarities to aggressive human CLL, Eμ-TCL1 mice have become a
widely accepted pre-clinical tool (Zanesi et al, 2006; Johnson et al., 2006;
Suljagic et al., 2010), as well as a model for dissecting CLL biology (Enzler et al.,
55
2009; Wu et al., 2009; Chen et al., 2009; Bertilaccio et al., 2011; Chen et al.,
2011).
1.4.4 APRIL Transgenic Mice
A proliferation-inducing ligand (APRIL) and B cell activating factor (BAFF)
are two cytokines of the TNF family that mediate survival and differentiation in
normal B cells and resistance to apoptosis in CLL cells (Kern et al., 2003). BAFF
is a critical survival factor for maturating B cells. Loss of BAFF or its receptors
interferes with B cell maturation and overexpression of BAFF is associated with
loss of B cell tolerance and development of autoimmunity. BAFF receptors
include the BAFF receptor, B cell maturation antigen (BMCA), and
transmembrane activator and calcium modulator cyclophilin ligand-interactor
(TACI), of which the latter two are also share with APRIL (Rickert et al., 2011).
Expression of APRIL can stimulate growth of tumor cells, and CLL patients have
increased serum APRIL levels that also correlates with survival implicating it in
the pathogenesis of CLL (Hahne et al., 1998; Planelles et al., 2007). APRIL
transgenic mice were developed by Stein et al., 2002) to investigate the role of
APRIL in lymphocytes. These mice carry a transgene for human APRIL driven by
Lck distal promoter for expression in T lymphocytes. Young APRIL transgenic
mice have no gross abnormalities but show increased T cell proliferation and
survival capacity, and display enhanced thymus-independent responses and
increased serum IgM (Stein et al., 2002). Importantly, older mice develop a B1 B
cell neoplasia that is similar to CLL (Planelles et al., 2004). These B1 cells are
56
detectable in the Perc at 4-5 months and show an age-dependent accumulation.
By 9-12 months ~40% of mice develop tumors in mesenteric lymph nodes and
Peyer’s patches. Further analyses show these cells are CD5+IgMloB220loCD23-
and portray enhanced survival in culture. Leukemic cells progressively infiltrate
other organs including the spleen, leading to splenomegaly, and can be detected
in non-lymphoid tissues such as kidney and liver. These data show that APRIL
can promote development of CLL-like disease in mice. NLCs have been found to
be a source of BAFF and APRIL through which they enhance survival of CLL in
microenvironments (Nishio et al., 2005).
1.4.5 TRAF2DN/BCL2 Transgenic Mice
Bcl2 is an anti-apoptotic protein commonly overexpressed in several
cancers including follicular B cell lymphoma and CLL (Hockenberry et al., 1990;
Hanada et al., 1993). Transgenic overexpression of Bcl2 in mice enhances
lymphocyte survival and fosters development of a low-grade polyclonal
lymphoproliferative disease with lymphadenopathy and splenomegaly
(Kastumata et al., 1992). TNF receptor-associated factor 2 is a member of TNF
receptor-associated factors that link TNF family receptors to intracellular
signaling to regulate cell proliferation and survival in normal cells and in
pathological conditions including cancer, when deregulated (Arch et al., 1998;
Zapata et al., 2000). Mice engineered to overexpress a dominant-negative
TRAF2 mutant protein (TRAF2DN) develop a lymphoproliferative disease that is
characterized by lymphadenopathy and splenomegaly with associated polyclonal
57
B cell expansion (Lee et al., 1997). This TRAF2 mutant lacks part of the N
terminus that contains the RING and zinc finger domains, and therefore mimics
TRAF1, which naturally lacks these domains (Bradley and Pober, 2001). Since
TRAF1 is overexpressed in CLL B cells (Zapata et al., 2000; Munzert et al.,
2002), Zapata and colleagues (2004) tested whether combined overexpression
of Bcl2 and TRAF2DN can promote development of CLL. Double transgenic mice
developed lymphadenopathy, splenomegaly, high WBC counts with common
occurrence of pleural effusions and ascites, and more than 80% of the mice died
by 14 months. FACS analysis and histopathological examination identified a
CLL/SLL-like disease that was defined by expansion of small- to medium-sized
non-cycling CD5+IgMhiB220IntIgDloCD11b+CD21loCD23- lymphocytes in the
spleen, BM, LN, PB and lungs. Lymphocytes from double transgenic mice
demonstrated increased survival in cultures and resistance to fludarabine or
dexamethasone-induced apoptosis suggesting that these lymphocytes
accumulate primarily due to enhanced survival, particularly since they exhibit
lower proliferation compared to those of wild type cells. Recent follow-up work by
the same group shows the TRAF2DN transgene is expressed at low levels and
induces degradation and loss of endogenous TRAF2 (Perez-Chacon et al.,
2012). Therefore, these works demonstrate that loss of TRAF2 and concomitant
overexpression of Bcl2 promotes a CLL/SLL-like disease in mice.
58
1.4.6 PKCα-KR Graft Mice
Protein kinase C (PKC) encompasses multiple isoforms of ubiquitous
serine/threonine protein kinases that regulate cellular proliferation, differentiation,
and survival in normal and malignant conditions (Spitaler and Cantrell, 2004;
Michie and Nakagawa, 2005). PKCs are activated by Ca2+ and diacylglycerol
(which is mimicked by phorbol esters) upon antigen receptor stimulation (Spitaler
and Cantrell, 2004). Recent evidence suggests that CD5 can also activate PKC
in a subset of CLL patients increasing cell survival (Perez-Chacon et al., 2007).
Moreover, a specific inhibitor of PKCδ induces apoptosis of human CLL cells and
genetic deletion of PKCβ or specific inhibition thwarts development of murine
CLL (Ringshausen et al., 2006; Holler et al., 2009). Nakagawa et al. (2006)
tested the potential of PKCα and PKCδ isoforms to transform B cells by stably
expressing their dominant-negative forms (PKCα-KR and PKCδ-KR,
respectively) in murine fetal liver-derived hematopoietic progenitor cells (HPCs),
which were co-cultured with a BM stromal cell line together with growth factors.
PKCα-KR induced more proliferation of the cultured cells and was further
investigated. Flow cytometric analysis showed that greater than 95% of cells
carrying PKCα-KR expressed B cell markers, CD19 and B220, as well as CLL-
related markers, CD5 and CD23 suggesting that subversion of PKCα signaling
promotes the development of a CLL-like phenotype (Nakagawa et al., 2006).
Notably, the authors did not check whether CD23 was co-expressed by the CD5+
B cells. CD5+ B cells showed prolonged survival in in vitro cultures lacking
stroma and growth factors with concomitant expression of Bcl2. HPCs stably
59
expressing PKCα-KR were transplanted into RAG1-/- mice to determine their fate
in vivo. Analyses of spleen and LNs detected cells with the same
immunophenotype as those found in vitro (CD19hiCD5+CD23+IgMloIgDlo).
Infiltration in other organs was not reported but non-CLL tumors were found to
form at injection site. Cells derived from a CLL tumor were mostly in the G0/G1
phase of cell cycle and appeared vulnerable to apoptosis, but resumed
proliferation when cultured on a stromal layer with growth factors. Collectively,
these studies demonstrated that altered PKCα function interferes with cell
survival and proliferation and promotes the outgrowth of CLL-like cells in mouse
tissues.
1.4.7 SV40 Large T Antigen Transgenic Mice
Simian virus 40 (SV40) large T antigen is a potent oncogene that
transforms cells by variety of mechanisms, most commonly, by inhibiting tumor
suppressors such as p53 and Rb (Ahuja et al., 2005). The finding of SV40 large
T antigen sequences human hematopoietic and lymphoid malignancies are
incriminating (Shivapurka et al., 2002; Shivapurkar et al., 2004). Ter Brugge et al.
(2009) investigated the effect of SV40 large T antigen in B lymphocytes with a
targeted SV40 large T antigen transgene that is expressed sporadically. This
transgene, under the control of IgHµ enhancer but without a promoter, was
inserted in the IgH locus between D and J gene segments and in the opposite
transcriptional orientation. This SV40 large T antigen, therefore, is predicted to
be expressed by antisense transcription and under two scenarios: early in
60
development before D-J recombination, and later as long as the targeted allele is
unrearranged. Insertion of the transgene does not appear to hinder
recombination because allotypic markers do not show biased usage toward a
particular allele in young mice. However, analyses of older mice show an age-
dependent progressive increase of large atypical B cells with biased expression
of the non-targeted allele in PB leading to development of CLL-like leukemia by
10 months, which can be accelerated by loss of p53. These B cells were
monoclonal and CD5+B220+IgM+CD43+ and present in the LN, spleen, and BM.
Half of the sequenced tumors (4/8) used the B1 B cell-associated VH11 family
heavy chain and had no mutations while the rest used VHJ558 family and
showed either few or multiple mutations. SV40 large T antigen has not been
detected in CLL, therefore, it is unlikely to be involved in transformation in this
disease. Since SV40 large T antigen targets multiple pathways (Ahuja et al.,
2005) this intriguing model may be useful in identifying signaling mechanisms
that promote CLL development.
1.4.8 DLEU2/miR15a/16-1 Knockout Mice
In CLL, 13q14 deletion occurs in over half of cases, and is the most
common chromosomal aberration in MBL and CLL (Dohner et al., 2000;
Rawstron et al., 2008). This deletion is also common in several lymphoid and
non-hematological solid malignancies suggesting that loss of genes in this region
predisposes an individual to cancer. A 300 kilobase minimally deleted region
(MDR) has been identified (Lui et al., 1997; Migliazza et al., 2001). The MDR
61
encodes for DLEU2, a sterile transcript from a class of long non-coding RNAs
that regulate gene expression, and microRNAs commonly downregulated in CLL
and prostate cancer, miR-15a and miR-16-1 (Calin et al., 2002; Bonci et al.,
2008). To test whether the MDR acts as a tumor suppressor, Klein et al. (2010)
generated mice with MDR deletion, or miR-15a/16-1 deletion only. Young MDR-/-
and miR-15a/16-1-/- appeared normal but older mice (> 9 months) showed
expansion of CD5+IgM+B220lo B cells than began in the PerC. Eventually, 42% of
MDR-/- and 26% of miR-15a/16-1-/- mice develop a spectrum of indolent
lymphoproliferative disorders that range from MBL, CLL/SLL, and non-Hodgkins
lymphomas. Although the role of DLEU2 in development of lymphoproliferative
disorders is unknown, miR-15a and miR-16-1 were found to regulate cell cycle
progression by targeting cyclins and cyclin-dependent kinases. Therefore, loss of
miR-15a and miR-16-1 leads to unchecked cell proliferation. Interestingly,
sequence analysis revealed that CD5+ B cells in the lymphoproliferative disorders
carried unmutated BCRs that shared ≥80% HCDR3 amino acid sequence
homology among different mice (stereotyped) suggesting a role for antigens in
pathogenesis akin to humans.
1.4.9 miR-29 Transgenic Mice
MicroRNA are modulators of gene expression, therefore, they are
implicated in a myriad of conditions when they are deregulated (Ambros et al.,
2004; Garzon et al., 2009). Using microRNA expression profiling, Pekarsky et al.
(2006) found miR-29 regulates TCL1 expression and was downregulated in
62
aggressive compared indolent CLL. This group later found that when compared
to normal cord blood CD19+ B cells, miR-29 was significantly upregulated in
indolent CLL suggesting it could be involved in pathogenesis of these cases of
CLL (Santanam et al., 2010). To test this possibility, they generated mice that
express miR-29 in immature and mature B cells. The majority of miR-29
transgenic mice show expansion of CLL-like cells detectable as early as 2
months in the spleen. These cells were modestly proliferating clonal
CD5+CD19+IgM+ lymphocytes that can be found later in both PB and BM, and in
the liver and kidney in advanced disease. These cells expand slowly but
gradually suggesting an indolent disease. For instance, CD5+ B cells constitute
~20% of all B cells in mice younger than 15 months, ~40% by 15-20 months, and
over 65% by 20-26 months with 4/20 transgenic mice followed to 24-26 months
developing overt leukemia, which was also the cause of death. miR-29
transgenic mice B cells additionally resemble those of human CLL in
immunological incompetence marked by reduction in serum IgG and poor
response to immunization.
Santanam et al. (2010) contend that the mechanism of leukemogenesis
may involve loss of a p53 responsive gene known as peroxidasin (a miR-29
target that was validated in these cells), which is downregulated in acute myeloid
leukemia (AML) (Santanam et al., 2010). Interestingly, transplantation of HSCs
overexpressing miR-29 in mice leads to development of a myeloproliferative
disorder that resembles acute myeloid leukemia (AML) (Han et al., 2010).
Santanam et al. (2010) concluded that miR29 is involved in the pathogenesis of
63
indolent CLL. This implied that the reduction of miR-29 (which also targets TCL1)
observed in aggressive CLL leads to upregulation of one of its targets, TCL1,
causing an aggressive disease.
1.5 RESEARCH GOALS AND SPECIFIC AIMS
CLL is a heterogeneous adult leukemia that is characterized by
progressive accumulation of small lymphocytes that express CD19, CD5, and
CD23 the blood and lymphoid organs (Matutes and Polliack, 2000; Dighiero and
Hamblin, 2008). The origins of CLL remain unclear but emerging evidence
suggests that CLL likely evolves from a more benign biologically similar condition
known as monoclonal B cell lymphocytosis (Rawstron et al., 2002; Rawstron et
al., 2008; Lanasa et al., 2011; Kern et al., 2012). However, what initiates this
condition or how it evolves to CLL is unknown. Accumulating evidence suggest
that that the feedback between CLL cells and their environment through various
receptors, including those that bind antigens partly contributes to CLL
pathogenesis.
CLL exhibits a restricted Ig gene repertoire and displays an antibody
reactivity profile shared by innate-like B1 and marginal zone MZ B, as well as
subsets of transitional and extrafollicular B cells that exhibit self-reactivity
produced by primary Ig gene rearrangements, or as an unintended consequence
of somatic mutation, respectively. CLL cells are also marked by CD5, which is
constitutively expressed on a subset of normal B1 cells and induced in B cells
undergoing receptor editing/revision, or those rendered anergic by chronic
64
(auto)antigenic stimulation, where it may function to negatively regulate B cell
receptor signaling and suppress B cell activation to limit autoantibody production
(Hippen et al., 2000; Hillion et al., 2005; Sims et al., 2005; Youinou et al., 2006).
In principle, B cells undergoing receptor editing/revision may be blocked
from completing this process if a dominant negative form of RAG1 is expressed
in sufficient excess over endogenous RAG1. We recently generated dominant-
negative RAG1 (dnRAG1) mice expressing a catalytically inactive, but DNA
binding-competent, form of RAG1 in the periphery that show evidence of
impaired secondary V(D)J recombination that occurs in response to self-reactivity
(Hassaballa et al., 2011). Interestingly, these animals develop a progressive,
antigen-dependent, accumulation of CD5+ B cells (Figure 1.3) which are clonally
diverse, yet repertoire-restricted, and possess a splenic B1-like
immunophenotype. However, dnRAG1 mice do not develop CD5+ B cell
neoplasia. The indolent accumulation of CD5+ B cells in dnRAG1 mice is
reminiscent of MBL, but the lack of progression to CLL in this model suggests
additional factors are required to promote transformation. TCL1 was considered
a plausible factor because it is often overexpressed in CLL and leads to a CLL-
like disease in aging Eμ-TCL1 mice (Herling et al., 2006; Bichi et al., 2002).
Predicting that molecular defects which promote benign CD5+ B cell
accumulation, such as impaired receptor editing, are a rate-limiting step in CLL
progression, we hypothesized that dnRAG1 expression in Eµ-TCL1 would
accelerate CD5+ B cell accumulation and CLL onset compared to Eµ-TCL1 mice.
65
Figure 1.3 Accumulation of B1-like CD5+ B cells with age in dnRAG1 mice. (A) Flow
cytometric analysis of splenic lymphocytes at 12 weeks in WT and dnRAG1 mice.
Numbers indicate the percentage all of cells represented in a given a gate. (B) The
percentage of splenic CD19+B220lo B cells was evaluated in WT and dnRAG1 mice as a
function of age from fetal day 17 (17dF) to 48 weeks. Differences are significant from 4
weeks of age onward (P<0.001).
66
We proposed two specific aims to test this hypothesis:
1. Determine whether dnRAG1 expression in TCL1 transgenic mice
accelerates CLL development. dnRAG1 mice were bred to Eµ-TCL1 to
generate WT, dnRAG1, Eµ-TCL1, and dnRAG1/Eµ-TCL1 double transgenic
(DTG) mice, which were monitored for accumulation of CD5+ B cell and CLL
characteristics by flow cytometry. Eµ-TCL1 and DTG mice were monitored for
development of CLL and survival.
2. Identify candidate factors involved in CD5+ B cell accumulation in
transgenic mice. CD5+ B cells accumulate in both dnRAG1 and Eµ-TCL1 mice,
but they likely arise through distinct mechanisms. To identify factors that regulate
CD5+ B cell development in these animals, and determine the extent to which the
individual transgenes contribute to CD5+ B accumulation in DTG mice, we
proposed to compare patterns of gene expression in CD5+ B cells from dnRAG1,
Eµ-TCL1, and DTG mice to each other and to normal follicular B cells.
The origins of CLL remain unknown. However, the large parallels between
human and murine B cell development allow us to study its pathogenesis in
these models. Identification of factors that regulate malignant CD5+ B
accumulation could lead to potential biomarkers or therapeutic targets for this
incurable leukemia.
67
CHAPTER 2: METHODS
2.1 MICE
Eµ-TCL1 mice (Bichi et al., 2002) were kindly provided by C. M. Croce
and Y. Pekarsky (Ohio State University, Columbus, Ohio). Eµ-TCL1 mice and
dnRAG1 mice (Hassaballa et al., 2011), both on C57BL/6 backgrounds, were
crossed to generate cohorts of wild type, dnRAG1, Eµ-TCL1, and DTG mice.
Genotyping was performed by polymerase chain reaction (PCR) as described
(Bichi et al., 2002; Hassaballa et al., 2011). Cohorts were euthanized by cervical
dislocation either at predetermined ages (6, 12, 24, and 36 weeks), or when they
became moribund. SCID mice (B6.CB17-prkdcscid/SzJ) were purchased from the
Jackson Laboratory (Bar Harbor, ME). All mice were housed in individually
ventilated microisolator cages in an Association for Assessment and
Accreditation of Laboratory Animal Care certified animal facility in accordance
with university and federal guidelines, and mouse protocols were approved by
the Creighton University Institutional Animal Care and Use Committee. Survival
data was obtained by monitoring a cohort of 11 Eµ-TCL1 and 14 DTG mice until
the animals showed signs of illness, which included hunched posture, labored
breathing, lethargy and reduced grooming, necessitating euthanasia.
2.2 FLOW CYTOMETRY
Lymphoid tissues were collected from ill mice or at predetermined time
points for fluorescence-activated cell sorting (FACS) analysis. Single-cell
suspensions were prepared from spleen, lymph node, and thymus in RF10
68
medium [RPMI 1640 (Invitrogen, Carlsbad, CA) containing 10% (v/v) fetal bovine
serum (FBS, Invitrogen) by shredding with two needles and homogenizing with
syringe. Blood was collected in heparinized tubes either from tail veins of live
mice or by cardiac puncture after euthanasia. BM cells were collected by flushing
marrow from femurs and tibias with RF10 medium into a collection tube. Red
blood cells were depleted from all tissues by hypotonic lysis with ammonium
chloride (0.14M ammonium chloride, 17mM Tris-HCl, pH 7.2). The white blood
cells were centrifuged, resuspended in phosphate-buffered saline (PBS)
containing 4% (v/v) FBS (PBS4) and counted on a particle counter (Coulter
Counter Model Z1, Beckman Coulter, Fullerton, CA). 1x106 cells were stained on
ice for 30 minutes with the following fluorochrome-conjugated monoclonal
antibodies: BD Biosciences (San Jose, CA) anti-B220-PE-TXRD (RA3-6B2), anti-
CD19-APC-Cy7 (ID3), anti-CD5-biotin (53-7.3), anti-CD21/CD35-PE (7G6), anti-
CD11b-PE (M1/70), anti-CD23-Biotin (B3B4), anti-CD4-APC-Cy7 (GK1.5), and
anti-CD25-PE-Cy7 (PC61), and eBioscience (San Diego, CA) anti-CD5-PE (53-
7.3), anti-IgM-APC (II/41), anti-IgD-FITC (11-26c), anti-CD3-APC (145-2C11),
anti-CD8-A700 (53-6.7), anti-TCRβ-FITC (H57-597). Samples containing
biotinylated antibodies were further developed with streptavidin-Qdot585
(Invitrogen). Data collection and cell sorting was performed using a FACSAria
flow cytometer (BD Biosciences). Flow cytometric data was analyzed using the
FlowJo software (Tree Star, Inc. Ashland, OR).
69
2.3 ADOPTIVE TRANSFER
CD19+CD5+ spleen lymphocytes alone or together with CD3+TCRβ+CD4-
CD8- or CD3+TCRβ+CD8+ spleen lymphocytes sorted from Eµ-TCL1 or DTG
mice by FACS were adoptively transferred into SCID mice. Sorted cells were
washed twice and resuspended in PBS. 2x104 to 1x106 sorted lymphocyte
populations (as indicated for specific experiments in the figures) in 200 µL of PBS
were injected into tail veins of 4- to 9-week-old recipient SCID mice. Control
SCID mice received PBS only. Grafting was monitored by FACS on blood
collected from tail veins every few weeks. The mice were euthanized at
experimental endpoint and their lymphoid organs were analyzed by FACS.
2.4 α-GALACTOSYLCERAMIDE TREATMENT
α-GalCer (KRN7000) (Avanti Polar Lipids, Alabaster, AL) stock was
prepared by resuspension at 1mg/mL in DMSO (Sigma, St. Louis, MO). 12-week-
old WT and DTG mice were treated with 5 µg of α-GalCer in 100µL of PBS with
0.025% Tween 20 or 100 µL of PBS with 0.025% Tween 20 by tail vein injection
once every week for 4 weeks. Mice were euthanized one week following the last
dose and their lymphoid organs were harvested and the abundance and
distribution of lymphocyte subsets was analyzed by FACS.
2.5 CELL CULTURE
CD19+CD5+ spleen lymphocytes sorted from DTG mice by FACS were
cultured with or without CD3+TCRβ+CD4-CD8- spleen lymphocytes from the
same mouse. Sorted cells were washed before resuspension with lymphocyte
70
culture medium consisting of RPMI supplemented with 10% FBS, 1x10-5 M β-
mercaptoethanol, 2mM L-glutamine, and 100 μg/mL penicillin and streptomycin
(Takahashi and Strober, 2008). The cells were cultured in 96-well round-bottom
plates at 37oC in a humidified incubator with 5% CO2. Cells were counted on day
3, 7, and 10 in a hemacytometer and viability was determined by trypan blue
exclusion.
2.6 HISTOPATHOLOGY AND WBC COUNTS
Tissues were fixed in 10% buffered formalin, embedded in paraffin,
sectioned, and stained with hematoxylin and eosin. Blood smears were prepared
and stained with Wright-Giemsa. Tissue sections or blood smears of at least
three mice for each genotype were evaluated by light microscopy for changes in
architecture and lymphocyte infiltration. Spleen, BM, liver, and kidney sections,
and blood smears were evaluated with a Nikon i80 microscope (Nikon, Melville,
NY) with a DigiFire camera running ImageSys Digital Imaging System (Soft
Imaging Systems GmBH, Munster, Germany) or a Nikon Eclipse E400
(Nikon) with an Optronics camera running MagnaFire software (Optronics,
Goleta, CA). High magnification BM sections and blood smear images were
acquired with a Nikon i80 microscope and Nikon Digital Sight DS-F1 camera
running the NIS-Elements Imaging software version 2.33. White blood cell (WBC)
counts were performed automatically with a Cellometer Auto X4 cell counter
(Nexcelom Bioscience (Lawrence, MA).
71
2.7 CLONALITY
Clonal V(D)J rearrangements were investigated by Southern blot and PCR
using spleen genomic DNA isolated with Wizard Genomic DNA Purification Kit
(Promega, Madison, WI). For Southern blot, 10-15 µg was digested overnight
with EcoR1 (New England Biolabs, Ipswich, MA), separated on a 0.8% agarose
gel, transferred to Amersham Hybond-N+ nylon membrane (GE Healthcare,
Piscataway, NJ), and hybridized with a 32P-labeled JH probe described by Bichi et
al., 2002). Phosphor images were acquired using a Typhoon 9410 variable mode
imager (GE Healthcare). To detect rearrangements by PCR, spleen genomic
DNA was amplified using primer sets for IgH (VHJ558 sense and 3′ JH4
antisense), Igκ (Vκ sense and 3’ Jκ5 antisense), and CD14 input control as
(Hassaballa et al., 2011). 100 ng of DNA was used in a 50 µL PCR reaction
containing 10 pmol of each primer, 0.2mM dNTPs, 20 mM Tris-HCl, pH 8.4, 50
mM KCl, 1.5 mM MgCl2, and 1.25 units of Taq polymerase. The DNA was
subjected to 30 cycles of amplification with 94oC for 30 sec denaturation, 58oC
for 1 min annealing, and 72oC for 2 min extension with a final extension of 10 min
at 72oC. 15 µL of PCR reactions was fractionated in a 1.5% agarose gel
containing ethidium bromide and imaged under ultra violet light.
2.8 IMMUNOGLOBULIN GENE SEQUENCING AND ANALYSIS
Total RNA was isolated from frozen spleen cells from ill Eµ-TCL1 and DTG mice
using Ambion RiboPure Kit (Ambion, Austin, TX). 5x106 spleen cells per 1 mL of
TRI Reagent were homogenized in 1.5 mL microcentrifuge tubes. After a 5 min
72
incubation at room temperature, 100 µL of bromochloropropane was added and
mixed by vortexing at high speed for 15 sec and incubated at room temperature
for 5 min. Samples were centrifuged at 12,000 x g for 15 min at 4oC to allow
phase separation. The aqueous phase was transferred to a fresh 1.5 mL
microcentrifuge tubes to which 200 µL of 100% ethanol was added. Samples
were immediately mixed by a short vortex (5 sec) and transferred to a glass-fiber
filtration tube. The RNA was washed twice and eluted in 50 µL of elution buffer.
Complementary DNA (cDNA) was prepared from 1 μg of the purified RNA in a 20
μL reaction using Novagen First Strand cDNA Synthesis Kit (EMD Millipore,
Darmstadt, Germany) with 0.5 µg of oligo(dT) primers at 37oC for 1 hour. Ig
genes were amplified from 1-2 μL of the cDNA by PCR using Platinum Taq DNA
Polymerase High Fidelity (Invitrogen) in a 35-cycle PCR reaction with 94oC for 1
min denaturation, 55oC for 1 min annealing, and 68oC for 1 min extension with a
final extension of 10 min at 68oC using MuIgVH5′- A to -F forward and
MuIgMVH3′-1 reverse primers to amplify heavy chain sequences (Mouse Ig-
Primer Sets, Novagen), and mouse universal 5′ Mκ forward and 3′ κC reverse
primers to amplify light chain sequences. 30 µL of the PCR reactions was
fractionated in a1.5% agarose gel and the DNA was isolated using GeneJET Gel
extraction Kit (Fermentas, Thermo Scientific, Waltham, MA). 2 µL of the purified
PCR products was ligated into the PCR 2.1 TOPO TA plasmid vector
(Invitrogen), which was used to transform development and diminishes in later
stages such as in mature T cells, post-GC B cells, and plasma cells. TCL1 is
required for lymphocyte development since Top10 chemically-competent E. coli
73
cells (Invitrogen). Isolated colonies were grown in mini-cultures overnight and
plasmid DNA was recovered using the E.Z.N.A Plasmid Mini Kit I (Omega Bio-
Tek, Norcross, GA). For both heavy and light chain genes, at least 10
independent clones per mouse were sequenced using a commercial vendor
(ACGT, Inc., Wheeling, IL). Sequences, with primer sites omitted, were analyzed
using IMGT/V-QUEST tool (http://www.imgt.org) to identify Ig gene usage,
mutations, CDR3 composition, and isoelectric point.
2.9 IMMUNOGLOBULIN LEVELS
Serum was prepared from blood collected from 12- and 36-week-old mice.
The blood was collected in tubes without anti-coagulants and allowed to clot for
30 minutes then centrifuged at 2000 x g for 10 minutes to obtain the serum.
Serum Igs were measured by ELISA using IMMUNO-TEK mouse IgM and IgG
kits (ZeptoMetrix, Buffalo, NY). Serum was diluted between 1:15,000 to
1:100,000 using the diluent (PBS, Triton X-100, 2-chloroacetamide) and added to
the ELISA plate in duplicate wells of 100 µL volume each. The plate was
incubated at 37oC for 30 min to allow the mouse antibodies to bind, after which
unbound material was removed through four washes with PBS containing Tween
20 and 2-chloroacetamide. 100 µL of anti-mouse IgG or IgM antibodies that are
conjugated to horseradish peroxidase were added to the plate, which was
incubated at 37oC for 30 min. After washing the plate, 100 µL of the substrate,
tetramethyl benzidine, was added and incubated at room temperature for 30 min.
The colorimetric reaction was quenched and optical density was measured at
74
450 nM with a VersaMax microplate reader (Molecular Devices, Sunnyvale, CA).
Serum IgM or IgG concentration was determined based on the optical densities
of IgM or IgG standards, respectively run alongside the test serum.
2.10 MICROARRAY
Total RNA was isolated from sorted splenic CD19+B220hiD5- B cells
obtained from wild type mice and splenic CD19+CD5+ B cells obtained from
transgenic mice using the Ribopure kit (Ambion) as described above. Biotin-end
labeled cDNA was prepared from 100-200 ng of total RNA using whole transcript
labeling kits from either Affymetrix (Affymetrix, Santa Clara, CA) or Ambion.
Resultant cDNA was hybridized overnight to Mouse Gene 1.0 ST Arrays and
washed, stained, and scanned using the Affymetrix GeneChip system with a
3000 7G Affymetrix scanner at the University Nebraska Medical Center
Microarray Core Facility. All procedures were conducted following Affymetrix
suggested protocols. Arrays were normalized using the Robust Multichip
Average algorithm (Irizarry et al., 2003; Irizarry et al., 2006) included in the
Affymetrix Expression Console software. The data is deposited in NCBI’s Gene
Expression Omnibus under series accession number GSE44940.
Unsupervised clustering and principal component analyses of genes
showing the highest variation among arrays were performed on Log2-transformed
expression values using dChip software (Li & Wong, 2001). These genes were
determined using the filtering criteria of a standard deviation for logged data
threshold between 0.85 and 1000 (12-week mice arrays) or 1.40 and 1000 (older
75
mice arrays) and an expression level greater than 5.65 in 25% of the samples.
Supervised clustering was performed on genes involved in regulating BCR
signaling (Kurosaki, 1999; Xu et al., 2005; Stevenson et al., 2011). Pair-wise
comparisons of the differentially expressed genes between genotypes was also
performed on dChip with linear expression values using the lower 90%
confidence bound interval for genes with ±1.2 fold change filtering criterion (12-
week mice) or ±1.5 fold change (older mice). Genes with a mean expression
value of less than 50 in both genotypes in a comparison pair were considered
absent and therefore not included.
To compare transgenic mice CD19+CD5+ B cells with normal B cell
subsets, data sets from 12-week-old mice and those obtained from splenic
transitional, MZ, B1a, mature follicular, and GC, and peritoneal B1a B cells
subsets available within the NCBI GEO series GSE15907 through the
Immunological Genome Project Consortium (ImmGen) (Heng et al., 2008) were
normalized together using the RMA algorithm in the Affymetrix Expression
Console. Batch effects were adjusted using ComBat (Johnson et al., 2007)
before clustering and PCA analysis by dChip. Unsupervised clustering was
performed on 102 genes which showed the highest variation that were selected
by the filtering criterion of a standard deviation for logged data threshold between
1.10 and 1000, and an expression level greater than or equal to 5.65 in 25% of
samples. Principal component analysis was also performed using the filtered
gene set.
76
2.11 REAL-TIME QUANTITATIVE PCR
RNA was isolated from frozen spleen tissue using Ambion Ribopure Kit
(Ambion) as described in the previous sections. RNA was treated with DNAse1
(Sigma) to degrade any DNA carried over by incubating all the purified RNA (~50
µL) with 6 µL of DNAse1 for 15 min with 6 µL of the DNAse1 reaction buffer (20
mM Tris-HCl, pH 8.3, and 2 mM MgCl2). The reaction was terminated by adding
6 µL of 50 mM EDTA and heating at 70oC for 10 min. 1 µg of RNA was used to
generate cDNA in a 50 µL reaction using TaqMan Reverse Transcription
Reagents (Applied Biosystems, Foster City, CA) These reactions contained the
1X reaction buffer (50 mM KCl and 10 mM Tris-HCl, pH 8.3), 5.5 mM MgCl2, 500
µM dNTP mix, 2. 5 µM Random hexamer primers, 0.4 U RNase inhibitor, and
1.25 U reverse transcriptase. Reverse transcription was carried out under the
the following thermal cycling conditions: 25oC (10 min), 48oC (30 min), 95oC (5
min). Control samples were prepared similary but with the omission of reverse
transcriptase. 2 µL of the cDNA reactions was amplified in a 20 µL SYBR Green-
based real-time quantitative PCR reaction (Applied Biosystems) on an ABI 7500
Fast instrument (Applied Biosystems) using the primer sets for Prl2a1, Il10,
Sox4, Rgs13, Sell, and Actb (Table 2.1) under the following thermal cycling
parameters: 50oC for 2 min followed by 35 cycles of 95oC for15 sec and 60oC for
1 min. Relative gene expression levels were calculated using the comparative
threshold cycle method (Livak and Schmittgen, 2001), with expression
normalized to β-actin.
77
2.12 STATISTICS
Statistics were performed using PASW software version 19 (SPSS, Inc.,
Chicago, IL) Differences among groups were determined by one-way ANOVA. A
p value equal to or less than 0.05 was considered significant. Data is presented
in bar graphs as mean ± the standard error. Survival was measured by Kaplan-
Meier method and the curves were compared using the log-rank test.
78
Table 2.1 Primers for RT-PCR
Gene Forward primer sequence (5′ - ′3) Reverse primer sequence (5′ - ′3)
Prl2a1 GGAAAAGAGCAATGGACTCCTGG CAGTCTCTGACTTCAAGGATGCC
Il10 CGGGAAGACAATAACTGCACCC CGGTTAGCAGTATGTTGTCCAGC
Sox4 GCCTCCATCTTCGTACAACC AGTGAAGCGCGTCTACCTGT
Rgs13 CTACATCCAGCCACAGTCTCCT TGAGCTTCTTCAAAGCATGTTTGAG
Sell ATGGTGAGCATCCCAGCCTA CCCCTTCCAGCATTCCATCA
Actb AGAGGGAAATCGTGCGTGAC CAATAGTGACCTGGCCGT
79
CHAPTER 3: RESULTS
3.1 dnRAG1 EXPRESSION ACCELERATES LEUKEMOGENESIS IN Eµ-
TCL1 MICE
3.1.1 Expression of dnRAG1 in Eμ-TCL1 Mice Shortens Survival
To test the hypothesis that dnRAG1 transgene expression accelerates
disease progression in Eµ-TCL1 mice, we crossed Eµ-TCL1 and dnRAG1
transgenic mice and performed survival analysis on a cohort of Eµ-TCL1 (n=11)
and DTG (n=14) mice. Consistent with our hypothesis, DTG mice showed a
significantly shorter lifespan compared to Eµ-TCL1 mice (p= 0.004), with median
survival times of 9.1 and 11.3 months, respectively (Figure 3.1A). At endpoint, all
DTG mice were visibly ill, showing lethargy and a hunched posture with labored
breathing, and evidence of organomegaly that necessitated euthanasia.
Splenomegaly was confirmed on necropsy in and a mixed population of small
and large lymphocytes was evident in peripheral blood smears in all mice (Figure
3.1B). About a quarter of Eµ-TCL1 or DTG mice developed lymphadenopathy
and/or hepatomegaly. Two DTG mice additionally presented with pleural
effusions and/or ascites. All ill Eµ-TCL1 and DTG mice showed an abundance of
CLL-like CD19+CD5+ B cells in the spleen (Figure 3.2A) that displayed an
IgM+IgD+B220+CD11blo/- phenotype, although the relative expression of these
antigens varied slightly between individuals (Figure 3.2B).
80
Figure 3.1 dnRAG1 expression in Eµ-TCL1 mice enhances lymphoproliferation and
shortens lifespan. (A) Kaplan-Meier survival curves of Eµ-TCL1 (n=11) and DTG
(n=14) mice. Statistical analysis between groups was performed using the log-rank test
(median survival: 9.1 and 11.3 months for DTG and Eµ-TCL1 mice; p=0.004). (B)
Peripheral blood smears of ill Eµ-TCL1 and DTG mice at end point were stained with
Wright-Giemsa and imaged at 1000x magnification using Nikon i80 microscope with
Nikon Digital Sight DS-F1 camera running the NIS-Elements Imaging software version
2.33.
81
Figure 3.2 dnRAG1 expression in Eµ-TCL1 mice accelerates accumulation of CLL-
like cells. Flow cytometry was used to analyze splenic lymphocytes from ill mice. (A)
The percentage of splenic CD19+CD5+ B cells among gated lymphocytes is shown at
endpoint for two representative Eµ-TCL1 and DTG mice. (B) Expression of sIgM, sIgD,
B220, and CD11b on CD19+CD5+ B cells from three ill Eμ-TCL1 mice (top row) and
three ill DTG mice (bottom row) is shown in (B). Histograms for the three different mice
are shown as solid, dashed, and dotted lines.
82
3.1.2 Time Course Study of CLL-like Disease Progression in DTG Mice
Since survival analysis suggested that dnRAG1 expression in Eµ-TCL1
mice accelerates disease progression, we analyzed cohorts of wild-type, Eµ-
TCL1, dnRAG1, and DTG mice at 6, 12, 24, and 36 weeks of age to more
carefully compare CD5+ B cell accumulation rates using flow cytometry. The last
time point was chosen because it was close to the median survival of DTG mice.
At 36 weeks, CD19+CD5+ (or alternatively CD19+B220lo) B cells represented a
small fraction of total splenic B cells in WT mice, but were abundant in dnRAG1,
Eµ-TCL1, and DTG mice (Figure 3.3A). Further analysis of the CD19+B220lo
population from dnRAG1, Eµ-TCL1, and DTG mice showed uniform CD5+CD21-
CD23- staining and similar sIgM levels (Figure 3.3B); sIgD levels were
comparable between dnRAG1 and DTG mice, but slightly higher than in Eµ-
TCL1 mice (Figure 3.3B).
As expected, DTG mice showed more rapid CD5+ B cell accumulation
compared to either dnRAG1 or Eµ-TCL1 mice in all tissues tested (lymph nodes,
bone marrow, peripheral blood, and spleen) (Figure 3.4A). However, the
frequency of CD5+ B cells differed substantially between the various tissues
analyzed. For example, at 36 weeks of age, CD5+ B cells comprised on average
5% of lymphocytes in lymph nodes of DTG mice, compared to 1.1%, 2.4%, and
1.5% for dnRAG1, Eµ-TCL1, and WT mice, respectively. In spleen, by contrast,
CD5+ B cells represented on average 67% of lymphocytes in DTG mice,
compared to 33%, 22%, and 2.7% for dnRAG1 Eµ-TCL1, and WT mice,
83
Figure 3.3 Surface immunophenotype of CLL-like cells in DTG mice. Flow
cytometric analysis of splenic lymphocytes from 36-week-old WT, dnRAG1, Eµ-TCL1,
and DTG mice showing the expression of CD19 and either CD5 (top row) or B220
(bottom row). The percentage of CD19+CD5+, CD19+CD5-, CD19+B220hi, CD19+B220lo
cells is shown for representative animals. Flow cytometry was used to compare the
expression of CD5, sIgM, sIgD, CD21, CD23, and CTLA4 expression on splenic WT
CD19+B220hi B cells to splenic CD19+B220lo B cells from dnRAG1, Eμ-TCL1 mice and
DTG mice.
84
Figure 3.4 Characterization of CLL-like disease progression in DTG mice. (A) The
percentage of CD19+CD5+ cells in lymph node (LN), bone marrow (BM), peripheral blood
(PB), and spleen (SPL) of 6, 12, 24, and 36 week-old WT, dnRAG1, Eµ-TCL1, and DTG
mice (n=5-14) animals per genotype per time point) was determined using flow
cytometry as in Figure 3.3A and presented in bar graph format. Error bars represent the
standard error of the mean. Statistically significant differences (p<0.05) between values
obtained for DTG mice relative to WT (a), dnRAG1 (b), or Eµ-TCL1 (c) mice are
indicated. (B) Spleens from representative animals at 36 weeks are shown at left, and
the mean weights of 5-14 animals of each genotype at each time point are presented in
bar graph format at right. Spleen cellularities were used to determine the absolute
number of CD19+CD5+ cells for each genotype at 12, 24, and 36 weeks of age (C).
White blood cell (WBC) counts (D) were compared for WT, dnRAG1, Eμ-TCL1 mice and
DTG mice at 36 weeks of age. Error bars in all graphs represent the standard error of
the mean. *, p<0.05; ***, p< 0.001.
85
respectively. A similar pattern was observed in the values obtained for peripheral
blood and bone marrow, which were intermediate between those determined in
lymph node and spleen (Figure 3.4A). By 36 weeks, all DTG mice showed
massive splenomegaly, with average spleen sizes ranging from 3-4-fold higher
than dnRAG1 and Eµ-TCL1 mice, to over 10-fold greater than WT mice (Figure
3.4B). At all time points tested, DTG mice showed a higher absolute number of
splenic CD5+ B cells compared to the other genotypes (Figure 3.4C).
All 36-week-old DTG mice showed evidence of lymphocytosis by white
blood cells counts and histopathological evaluation of blood smears (Figures
3.4D and 3.5); smudge cells similar to those observed in CLL patients were also
frequently detected (Figure 3.5). In the spleen, extensive lymphocytic infiltrates
were observed in DTG mice, with a corresponding loss of splenic architecture
(Figure 3.5). Abnormal lymphocytic infiltrates were clearly apparent in the livers
of all 36 week-old DTG mice, but bone marrow and kidneys were unremarkable
(Figures 3.5 and 3.6).
These data show that CD5+ B cells in dnRAG1, Eµ-TCL1, DTG mice are
phenotypically similar in terms of surface marker expression and organ
involvement; however, they emerge and accumulate with different kinetics in all
transgenic mice. These cells emerge earliest and accumulate more dramatically
in DTG mice compared to either dnRAG1 or Eµ-TCL1 mice. While they are
detectable earlier in dnRAG1 compared to Eµ-TCL1 mice, they accumulate at a
slower rate since dnRAG1 mice rarely develop frank leukemia.
86
Figure 3.5 DTG mice show evidence of CLL-like disease at 36 weeks. (A) Blood
smears were developed with Wright-Giemsa stain. Images (200x and 1000x) were
acquired using Nikon Eclipse E400 microscope (Nikon, Melville, NY) and
Optronics camera running MagnaFire software (Optronics, Goleta, CA), and a Nikon i80
microscope and Nikon Digital Sight DS-F1 camera running the NIS-Elements Imaging
software version 2.33, respectively. Paraffin-embedded spleen and kidney sections
were developed with hematoxylin and eosin. Images (100x for spleen and 200x for liver)
were acquired using a Nikon i80 microscope and DigiFire camera running ImageSys
digital imaging software (Soft Imaging Systems GmBH, Munster, Germany). DTG mice
at this age show peripheral blood lymphocytosis with frequent occurrence of smudge
cells (arrow, see inset), loss of splenic architecture, and infiltration of leukemic cells in
liver (arrows). Scale bars: blood and liver 100 µM; spleen, 200 µM.
87
Figure 3.6 Bone marrow and kidney histology of 36-week-old mice. Paraffin-
embedded bone marrow and kidney sections were developed with hematoxylin and
eosin. Images in columns 1 and 3 (100x for bone marrow, and 200x for kidney) were
acquired using a Nikon i80 microscope and DigiFire camera running ImageSys digital
imaging software (Soft Imaging Systems GmBH, Munster, Germany). Bone marrow
images in column 2 (1000x) were acquired using a Nikon i80 microscope and Nikon
Digital Sight DS-F1 camera running the NIS-Elements Imaging software version 2.33.
Bone marrow and kidney show little or no abnormal infiltration at this time point. Scale
bars: bone marrow, 200 μM; kidney, 100 μM.
88
3.1.3 B Cells of DTG Mice are Clonally Transformed and Bear Unmutated
Ig Genes
The CLL-like B cells emerging in Eµ-TCL1 mice are known to be
leukemogenic (Zanesi et al., 2006). To test whether CLL-like cells in DTG mice
are also leukemogenic, 106 splenic CD19+CD5+ B cells from two different 36-
week-old DTG mice were injected i.v. into SCID recipient mice. In both cases,
successful engraftment was indicated by flow cytometry six weeks after adoptive
transfer (Figure 3.7A). By three months, all SCID mice receiving CD5+ B cells
from DTG mice developed splenomegaly (Figure
3.7B), peripheral blood lymphocytosis (Figure 3.7C), and infiltration of spleen,
bone marrow, and lymph nodes by leukemic cells (Figure 3.7D), which indicates
that these cells are malignantly transformed.
We previously showed that the CD5+ B cells accumulating in dnRAG1
mice are clonally diverse, but repertoire restricted (Hassaballa et al., 2011). To
determine whether the accumulating CD5+ B cells in DTG mice are also clonally
diverse, or have instead undergone oligoclonal or monoclonal expansion
indicative of transformation, we analyzed genomic DNA prepared from spleens of
36 week-old WT, dnRAG1, Eµ-TCL1, and DTG mice by Southern hybridization to
detect clonal rearrangements in the IgH locus (Figure 3.8A). This analysis was
also performed on DTG donor animals and SCID recipient mice at experimental
endpoint (3 months). We found that about half of the dnRAG1 (1/2), Eµ-TCL1
(2/4), and DTG (4/7) mice analyzed showed the presence of non-germline bands,
indicative of clonal expansion (Figure 3.7A, lanes 2-14). Notably, the pattern of
89
Figure 3.7 Engraftment of leukemic cells from DTG mice in SCID mice. CD19+CD5+
splenocytes (106 cells) were purified by FACS from two different 36 week-old DTG mice
and injected into the tail veins of two recipient SCID mice for each donor; n=4 total.
Normal C57BL/6 mice and sham-injected SCID mice were included as controls.
CD19+CD5+ B cells were readily detected in SCID recipients but not control animals at 6
weeks post-transfer (A). The SCID mice were sacrificed 3 months post-transfer. Spleen
weights were measured (B), and the percentage (C) and/or absolute number (D) of
CD19+IgM+ B cells were determined in spleen, bone marrow (BM), lymph node (LN), and
peripheral blood (PB).
90
Figure 3.8 Clonal transformation of B cells from DTG mice. (A) Genomic DNA
prepared from spleens of 36 week-old WT, dnRAG1, Eµ-TCL1, and DTG mice (lanes 2-
14), as well as DTG donor and SCID recipient mice in panel A (lanes 15-18), was
subjected to Southern hybridization using a JH-probe. Non-germline bands are indicated
by an asterisk. The JH probe contains a portion of the Eµ enhancer, and therefore also
detects the dnRAG1 transgene which contains this element (Hassaballa et al., 2011).
(B) VH-to-DJH and Vκ-to-Jµ rearrangements were amplified by PCR from genomic DNA
samples described in panel B. Rearrangements to a given J segment are shown at
right. The non-rearranging CD14 locus was amplified from the diluted genomic DNA
templates as a loading control.
91
non-germline bands observed in samples prepared from donor DTG mice and
the corresponding SCID recipient mice were identical (Figure 3.8A, lanes 15-18),
suggesting the leukemic cells are stable and do not undergo further IgH gene
rearrangement after adoptive transfer.
Since some Eµ-TCL1 and DTG mice did not show obvious evidence of
clonal outgrowth by Southern blotting, we alternatively used a PCR-based
approach to compare the pattern of IgH and Igκ gene rearrangements between
the four genotypes of animals analyzed in Figure 3.8A. As expected from our
earlier studies (Hassaballa et al., 2011), WT and dnRAG1 mice showed a
clonally diverse B cell repertoire that includes rearrangements to all four
functional JH and Jκ gene segments, but dnRAG1 mice showed a bias toward
Jκ1 and Jκ2 gene usage consistent with a defect in secondary V(D)J
recombination (Figure 3.8B, lanes 3-6). By contrast, all Eµ-TCL1 and DTG mice
showed a highly restricted pattern of V(D)J rearrangements (Figure 3.7B,
compare lanes 3-6 to 7-15). Taken together, these data suggest that CD5+ B
cells accumulating in DTG mice represent a clonal expansion of leukemic B cells.
Previous studies have shown that leukemic cells in Eµ-TCL1 mice harbor
largely unmutated Ig genes that encode CDR3 sequences enriched in serine,
tyrosine, and charged residues, features which are also observed in aggressive
CLL in humans (Yan et al., 2006). To determine whether leukemic cells from
DTG mice share these characteristics, we analyzed IgH and Igκ sequences from
three ill Eµ-TCL1 and DTG mice (Tables 3.1 and 3.2). We found that, like Eµ-
TCL1 mice, Ig gene sequences in DTG mice are mostly unmutated and encode
92
CDR3 regions enriched in serine, tyrosine, and charged residues. Indeed, some
of the same genes and CDR3 sequences are recovered from both genotypes.
For example, sequences utilizing the VH segments 1-55, 5-6, and 5-12 and/or
containing the VH CDR3 sequence encoding “YYGSS” were amplified from both
Eµ-TCL1 and DTG animals. We also detected recurrent Vκ4-91 and Vκ14-126
usage in Eµ-TCL1 and DTG mice. Several of these VH and Vκ sequences were
also represented among those amplified from Eµ-TCL1 mice by Yan et al.
(2006). Many of these gene sequences are associated with reactivity toward
autoantigens such as DNA, cardiolipin, and phosphatidyl choline (Tables 3.1 and
3.2).
93
94
95
3.2 dnRAG1 EXPRESSION IN Eµ-TCL1 MICE SUPPRESSES
IMMUNOGLOBULIN PRODUCTION
Human CLL patients typically develop progressive
hypogammaglobulinemia (Rozman et al., 1988; Caligaris-Cappio and Hamblin,
1999). Our previous studies showed that dnRAG1 mice exhibit defective natural
IgM and IgG antibody production correlated with an intrinsic B cell
hyporesponsiveness toward antigenic stimulation (Hassaballa et al., 2011). To
determine whether Eµ-TCL1 expression influences antibody production in
dnRAG1 mice, we compared serum IgM and IgG levels in WT, dnRAG1, Eµ-
TCL1, and DTG mice at 12 and 36 weeks (Figure 3.9). Consistent with previous
findings (Hassaballa et al., 2011), IgM and IgG levels were reduced 2-3-fold in
dnRAG1 mice compared to WT mice at 12 weeks; at 36 weeks, this reduction
was even more pronounced (4-8 fold). By contrast, IgM and IgG levels in Eµ-
TCL1 and WT mice were quite similar at 12 weeks, but at 36 weeks, Eµ-TCL1
mice showed elevated IgM levels and decreased IgG levels compared to WT
mice. Interestingly, antibody levels in DTG mice resembled dnRAG1 mice, but
showed slightly lower serum IgM and IgG levels at both time points. Thus, these
data suggest that the suppressive effect of dnRAG1 expression on antibody
production in mice is not overcome by concomitant Eµ-TCL1 expression.
96
Figure 3.9 DTG mice show evidence of severe hypogammaglobulinemia. Serum
IgM and IgG levels were measured by ELISA for groups of 5-7 12- and 36-week-old WT,
dnRAG1, Eµ-TCL1, or DTG mice. Individual values and means (indicated by horizontal
bar) are shown for each group; statistically significant differences between groups are
also depicted.
97
3.3 DISTINCT GENE EXPRESSION PROFILES IN CD5+ B CELLS IN BOTH
YOUNG AND OLD TRANSGENIC MICE
To gain insight into the relative contribution of the individual dnRAG1 and
Eµ-TCL1 transgenes in promoting CLL-like disease in DTG mice, and identify
genes that are differentially expressed between the animals as function of age
and disease progression, we compared the gene expression profiles of splenic
CD19+CD5+ B cells from 12-week-old dnRAG1, Eµ-TCL1, and DTG mice and
splenic CD19+B220hiCD5- B cells from two age-matched WT mice, and repeated
this analysis using ill DTG mice, which was evidenced by lethargy accompanied
with organomegally, and their age-matched counterparts.
3.3.1 Gene Expression Profiles in 12-week-old Mice
To determine how closely the B cell populations from WT and transgenic
mice resemble each another, we initially performed unsupervised hierarchical
clustering analysis on expression data sets from sorted B cell populations from
12-week-old mice (Figure 3.10A). Perhaps not surprisingly, CD19+CD5+ B cell
gene expression profiles from transgenic mice were more similar to each other
than to the profiles obtained for WT CD19+B220hiCD5- B cell, which was also true
in older mice (Figure 3.12A). These experiments also revealed that at 12 weeks
of age, CD5+ B cells from DTG mice resembled those from dnRAG1 mice more
closely than Eµ-TCL1 mice (Figure 3.10A). Indeed, only two genes (Neto2 and
Lmo7) were differentially expressed by more than 3-fold between dnRAG1 and
DTG mice (Table 3.3). Additional comparison to gene expression profiles
98
99
Figure 3.10 Identification of differentially expressed genes in WT CD19+B220hiCD5-
B cells and CD19+CD5+ B cells from dnRAG1, Eµ-TCL1, and DTG mice at 12 weeks.
(A) Unsupervised hierarchical clustering of a set of 107 showing the most variation. The
Red and green intensities indicate high to low expression values, respectively. The
dendrogram shows the relationships between the arrays. (B) A list of common genes
among the 50 genes that display the greatest differential expression in WT
CD19+B220hiCD5- B cells relative to CD19+CD5+ B cells from all transgenic mice is
shown in the top panel. A list of common genes among the 50 genes that display the
greatest differential expression in CD19+CD5+ B cells from dnRAG1 and DTG mice
relative to Eµ-TCL1 mice is also shown in the bottom panel.
100
WT (M188)
dnRAG1 (M175)
dnRAG1 (M194)DTG (M176)
DTG (M187)
DTG (M199)
Eµ-TCL1 (M167)Eµ-TCL1 (M173)
WT (M183)
MZ_Sp (1)MZ_Sp (2)
MZ_Sp (3)
T1_Sp (1)
T1-Sp (2)T1_Sp (3)
T2_Sp (1)T2_Sp (2)
T2_Sp (3)
T3_Sp (1)
T3_Sp (2)T3_Sp (3)
B1a_PC (1)
B1a_PC (2)B1a_PC (3)
B1a_Sp (1)B1a_Sp (2)
B1a_Sp (3)
FO_Sp (1)FO_Sp (2)
FO_Sp (3)
GC_Sp (1)
GC_Sp (2)
GC_Sp (3)
MZ
_S
pM
Z_
Sp
MZ
_S
pT
1_
Sp
T1
_S
pT
1_
Sp
Fo
_S
pF
o_
Sp
Fo
_S
pW
TW
TT
2_
Sp
T2
_S
pT
2_
Sp
T3
_S
pT
3_
Sp
T3
_S
pG
C_
Sp
GC
_S
pG
C_
Sp
dn
RA
G1
Eu
-TC
L1
Eu
-TC
L1
B1
a_
PC
B1
a_
PC
B1
a_
PC
B1
a_
Sp
B1
a_
Sp
B1
a_
Sp
DT
GD
TG
dn
RA
G1
DT
G
Cd1d1Cd36S1pr3MyofCeacam2I830077J02RikLOC674190Gm4759BC094916E030037K03RikZfp318Slfn8Cnn3Serpinb1aSellDpp4S1pr1If i203Tlr7S100a10A630033H20RikCd55Stat4Ms4a4cCcr6Gpr174Rasgrp3Fcer2aCr2Satb1Kmo1300014I06RikLrrk2Bcl6CpmCd93Serinc5Rgs13Rassf6Hist1h2bbCenpeFasAicdaHist1h1bMki67C330027C09Rik2810417H13RikCcnb1F630043A04RikGatmPrc1Cep55Kif11Ccna2E2f8Kif2cStilNcapg2Nuf2Plk1Bub1bNcapgTpx2Gcet2Gm600IgjNt5eAnxa2Nek2Racgap1LifrFxyd5Plac8Fcrl5Zc3h12cGm10879Lmo7Prkar2bIl6stNid1Ctla4S100a6Zbtb32Cd80Rbm47AdmFzd61810046K07RikPstpip2Ptpn22Tmem154Pde8aCd9Atxn1Gm10786Cd300lfCcr1Csf2rbDnase1l3Bhlhe41Hepacam2Il5ra
MZ
_S
p_#2
MZ
_S
p_#1
MZ
_S
p_#3
T1_S
p_#1
T1_S
p_#2
T1_S
p_#3
Fo_S
p_#1
Fo_S
p_#2
Fo_S
p_#31
WT
(M
188)
WT
(M
183)
T2_S
p_#1
T2_S
p_#2
T2_S
p_#3
T3_S
p_#1
T3_S
p_#2
T3_S
p_#3
GC
_S
p_#1
GC
_S
p_#2
GC
_S
p_#3
dnR
AG
1 (
M175)
Eu-T
CL1 (
M173)
Eu-T
CL1 (
M167)
B1a_P
C_#3
B1a_P
C_#1
B1a_P
C_#2
B1a_S
p_#2
B1a_S
p_#1
B1a_S
p_#3
DT
G (
M176)
DT
G (
M199)
dnR
AG
1 (
M194)
DT
G (
M187)
Cd1d1Cd36S1pr3MyofCeacam2I830077J02RikLOC674190Gm4759BC094916E030037K03RikZfp318Slfn8Cnn3Serpinb1aSellDpp4S1pr1Ifi203Tlr7S100a10A630033H20RikCd55Stat4Ms4a4cCcr6Gpr174Rasgrp3Fcer2aCr2Satb1Kmo1300014I06RikLrrk2Bcl6CpmCd93Serinc5Rgs13Rassf6Hist1h2bbCenpeFasAicdaHist1h1bMki67C330027C09Rik2810417H13RikCcnb1F630043A04RikGatmPrc1Cep55Kif11Ccna2E2f8Kif2cStilNcapg2Nuf2Plk1Bub1bNcapgTpx2Gcet2Gm600IgjNt5eAnxa2Nek2Racgap1LifrFxyd5Plac8Fcrl5Zc3h12cGm10879Lmo7Prkar2bIl6stNid1Ctla4S100a6Zbtb32Cd80Rbm47AdmFzd61810046K07RikPstpip2Ptpn22Tmem154Pde8aCd9Atxn1Gm10786Cd300lfCcr1Csf2rbDnase1l3Bhlhe41Hepacam2Il5ra
-3.0 -2.8 -2.5 -2.3 -2.1 -1.8 -1.6 -1.4 -1.2 -0.9 -0.7 -0.5 -0.2 0 0.2 0.5 0.7 0.9 1.2 1.4 1.6 1.8 2.1 2.3 2.5 2.8 3.0
A B
Figure 3.11 CD5+ B cells from dnRAG1, Eμ-TCL1, and DTG mice are most similar
to normal B1a B cells. (A) The gene expression profiles of sorted B cells from 12 week-
old mice in this study were compared to those from normal developing, mature, and
activated B cell subsets by unsupervised hierarchical clustering analysis. Clustering was
performed on batch effect-corrected log2 expression values for 102 genes (rows) and 33
arrays (columns), which includes those from sorted splenic wild type CD19+B220hiCD5-
(WT) and transgenic CD19+B220loCD5+ (dnRAG1, Eμ-TCL1, and DTG) B cells from 12
week-old mice reported here, and those obtained from sorted splenic and peritoneal B1a
cells (B1a-Sp and B1a-PC), splenic transitional B cells (T1-T3-Sp), splenic marginal
zone (MZ-Sp) and follicular B cells (FO-Sp), and splenic germinal center (GC-Sp) B cells
available through the ImmGen database (Heng et al., 2008). Red and green intensities
indicate high to low gene expression, respectively. The dendrogram shows the
relationships between the populations. (B) Principal component analysis (PCA) of the
102 genes identified in (A).
101
available for normal B1 cells and splenic developing, mature, and activated B cell
subsets using hierarchical clustering and principal component analyses (PCA)
showed that the CD5+ B cell gene expression profiles from the transgenic mice
studied here most closely resembled the signature for normal splenic B1a cells
by both analyses, but also shared some features of MZ B cells by PCA (Figure
3.11).
To identify specific genes that are differentially expressed between the
sorted B cell populations in the 12-week-old group, we performed a series of
pair-wise comparisons between the microarray data sets. First, we compiled the
50 genes showing the greatest differential expression for each pair-wise
comparison (25 up and 25 down), and generated a list of common genes that are
differentially expressed between transgenic CD5+ B cells and WT B cells in all
three comparisons (Figure 3.10B). Among the genes included on this list are
cytotoxic T-lymphocyte-associated protein 4 (Ctla4; 8.4-16.9 fold increase),
complement receptor 2 (Cr2 [CD21]; 4.5- 5.4 fold decrease) and Fcer2a (CD23;
12-25 fold decrease). These differences were validated at the protein level by
flow cytometry (Figure 3.3B). Several other genes also displayed a consistent
pattern of differential expression, including Pstpip2 (+11-14 fold), Cpm (-11-12
fold), Sell (-4-14 fold), and Lrrk2 (-18-24 fold).
Using the same approach, we next compared the gene expression profiles
from dnRAG1 and DTG mice to those obtained from Eµ-TCL1 mice (Figure
3.10B). In this comparison, most genes showed less than a 10-fold difference in
relative expression. Among the 17 common upregulated genes, two prolactin
102
family members, Prl2a1 and Prl7c1, showed increased expression in CD5+ B
cells from dnRAG1 mice (57 and 3.6 fold, respectively) and DTG mice (53 and
4.4 fold, respectively) relative to Eµ-TCL1 mice. In addition, the gene identified
as LOC100047053 showed elevated expression in CD5+ B cells from both
dnRAG1 (12.07 fold) and DTG (7.01 fold) mice relative to Eµ-TCL1 mice. This
gene is synonymous with Igκv6-32 (Igκv19-32) and was previously shown to be
highly represented in the light chain repertoire of CD19+B220lo B cells in dnRAG1
mice (Hassaballa et al., 2011), which likely explains its apparent upregulation in
CD5+ B cells from dnRAG1 and DTG mice relative to Eµ-TCL1 mice. None of
the 17 downregulated genes on this list showed >10-fold reduction in both pair-
wise comparisons.
3.3.2 Gene Expression Profiles in Ill DTG Mice and Age-matched
Counterparts
Unsupervised hierarchical clustering analysis of array sets of sorted B cell
populations from ill DTG mice (37 & 43 weeks) and their age-matched
transgenic and WT counterparts shows that CD5+ B cells from transgenic mice
are very similar to each other compared to the WT controls (Figure 3.12A).
However, the gene expression profiles obtained from DTG mice showed less
similarity to those from dnRAG1 mice than at 12 weeks, and instead clustered
more closely with the Eµ-TCL1 profile (Figure 3.12A). To identify specific
differentially expressed genes, we repeated pair-wise comparisons as described
for 12-week-old arrays focusing on differences between the transgenic CD5+
103
104
Figure 3.12 Identification of differentially expressed genes in WT CD19+B220hiCD5-
B cells and CD19+CD5+ B cells from ill DTG mice and age-matched dnRAG1 and
Eµ-TCL1 mice. (A) Unsupervised hierarchical clustering of a set of 102 genes showing
the most variation. The Red and green intensities indicate high to low expression values,
respectively. The dendrogram shows the relationships between the arrays. (B) A list of
common genes among the 50 genes that display the greatest differential expression in
CD19+CD5+ B cells from dnRAG1 and DTG mice relative to Eµ-TCL1 mice is shown in
the upper panel, and a list of 24 genes that display the greatest differential expression
(>2-fold) in CD19+CD5+ B cells DTG mice compared to both dnRAG1 and Eµ-TCL1 mice
is shown in the bottom panel.
105
populations, although comparisons to WT CD19+B220hiCD5- B cells were also
made (Table 3.4). First, we compared gene expression data obtained for CD5+ B
cells from ill DTG and age-matched dnRAG1 mice to an older Eµ-TCL1 mouse
(Figure 3.12B). As observed at 12 weeks, Prl2a1 was highly upregulated in
CD5+ B cells from older dnRAG1 and ill DTG mice relative to the Eµ-TCL1
mouse (277 and 235-fold, respectively). Three additional genes, Sox4, Gpr177,
and Prl8a2, were also upregulated more than 10-fold in both dnRAG1 and DTG
CD5+ B cells in this comparison. Quantitative PCR (qPCR) analysis of Prl2a1
and Sox4 expression in whole spleen tissue obtained from 36-week-old WT and
transgenic mice confirmed that both genes were overexpressed in dnRAG1 and
DTG mice relative to both WT and Eµ-TCL1 mice (Figure 3.13). By contrast, 12
genes were downregulated by more than 10-fold among older dnRAG1 and DTG
mice relative to Eµ-TCL1 mice (Figure 3.12B); only one non-Ig-related gene,
Lgals1, appeared on the list of downregulated genes at both time points. We also
performed individual pair-wise comparisons between the CD5+ B cell gene
expression data from the older DTG and Eµ-TCL1 mice (Tables 3.5 and 3.6).
This exercise unexpectedly revealed that CD5+ B cells from one of the DTG mice
highly upregulated CD23 expression (32-fold) relative to the Eµ-TCL1 mouse
(Table 3.6). This observation was confirmed by flow cytometry (Figure 3.14), and
raises the possibility that CD23 expression may be induced in CD5+ B cells in
some cases when DTG mice become ill.
106
Figure 3.13 Validation of differentially expressed genes by quantitative PCR. The
relative expression of Prl2a1, Il10, Sox4, Rgs13, and Sell in whole spleen tissue of 36-
week-old mice (n=3/ genotype) was measured by real-time quantitative PCR. Data is
presented as mean fold change relative to WT mice; error bars represent the standard
error of the mean. Significant differences between genotypes are indicated (*, p<0.05;
**, p< 0.01; ***, p< 0.001).
107
Figure 3.14 CD23 expression on leukemic cells from an ill DTG mouse. Flow
cytometry was used to compare CD23 expression on CD19+B220lo B cells from the Eμ-
TCL1 mouse (M52) and the ill DTG mouse (F57) used for the comparative gene
expression analysis found in Table 3.6, which showed that Fcer2a (CD23) was
unregulated ~32-fold on CD19+CD5+ B cells from the DTG mouse relative to those from
the Eμ-TCL1 mouse.
108
Finally, we compared the gene expression data from ill DTG mice to age-
matched dnRAG1 and Eµ-TCL1 mice to identify genes that were up- or down-
regulated >2-fold in both pair-wise comparisons which distinguish DTG mice from
both dnRAG1 and Eµ-TCL1 mice (Figure 3.12B). The expression of several of
the identified genes in spleen tissue obtained from 36-week-old WT and
transgenic mice was analyzed by qPCR. These studies confirmed that Rgs13
and Sell expression was significantly different between DTG mice and one or
both of the single-transgenic mice (Figure 3.13). The expression of other genes
tested, including Dpp4, Ccl22, and Plaur, showed no significant differences
between the transgenic animals.
3.3.3 Tolerogenic and BCR Signaling Genes are Perturbed in Transgenic
Mice
We evaluated the expression of genes involved in BCR signaling
(Kurosaki, 1999; Xu et al., 2005; Stevenson et al., 2011) and immune
suppression (Alegre et al., 2001; Goodnow et al., 2005; Moore et al., 2001),
some of which are reportedly differentially expressed in CLL. Supervised
hierarchical clustering analysis of BCR signaling genes showed that these genes
clearly differentiate WT CD19+B220hiCD5- B cells from transgenic CD19+CD5+ B
cells at both time points (Figure 3.15). One marker that obviously discriminates
CLL cells from normal adult follicular B cells is CD5. Although Cd5 was not
among the top 50 differentially expressed genes in any of the pair-wise
comparisons earlier, its expression was nevertheless consistently higher among
109
Figure 3.15 Hierarchical clustering analysis of genes involved in B cell receptor
signaling from 12-week-old and older WT and transgenic mice. Supervised
hierarchical clustering analysis was performed using a set of 22 genes known to play a
role in B cell receptor signaling pathways. The relative expression of these genes in WT
CD19+B220hiCD5- B cells compared to transgenic CD19+CD5+ B cells is shown at right
for 12-week-old (top panel) and older animals (bottom panel).
110
transgenic CD5+ B cells compared to WT CD19+B220hiCD5- B cells at 12 weeks
(~1.9-fold), and increased slightly in older mice (2.2-3.3-fold). Several other
genes involved in modulating BCR signaling known to be dysregulated on CLL
cells, including Nfatc1 (Le Roy et al., 2012), and Ptpn22 (Negro et al., 2012),
were also found to be dysregulated on all transgenic CD19+CD5+ B cells
compared to WT CD19+B220hiCD5- B cells. CD22, a negative regulator of BCR
signaling that is also underexpressed in CLL (Damle et al., 2002; Jelinek et al.,
2003), was downregulated at least 2.6-fold in CD5+ B cells at both time points,
except in older Eµ-TCL1 mice where the difference was more modest (-1.2 fold).
Some genes comprising a “tolerogenic signature” for CLL (Gilling et al., 2012;
DiLillo et al., 2012) were also upregulated on transgenic CD19+CD5+ B cells at
both time points and were increased in older mice, including Ctla4 (8.5-22 fold)
and Il10 (4.9-14 fold) (Figure 3.11 and (Table 3.4). Increased expression of both
genes has been confirmed either at the protein level on CD5+ B cells (Ctla4;
Figure 3.3), or at the transcript level in whole spleen tissue from transgenic mice
(Il10; Figure 3.13).
3.4 ALTERATION OF THE T CELL COMPARTMENT IN TRANSGENIC
MICE
3.4.1 Increase in CD4+CD25+ T cells in DTG Mice and CD3+TCRβ+CD4-CD8-
(Double-negative) T Cells in Eµ-TCL1 and DTG Mice
Because abnormalities in the T cell compartment are prevalent in CLL
(Kay 1981; Farace et al., 1994; D’Arena et al., 2012) and they have been
observed in Eµ-TCL1 mice (Hofbauer et al., 2011), we considered that DTG
111
112
Figure 3.16 Characterization of T cell subsets in transgenic mice. (A) T cells were
identified by co-expression of CD3 and TCRβ by flow cytometry (top). T cells were
further gated based on expression of CD4 and CD8 (bottom) and the percentages of
these subsets in these representative mice are indicated. (B-C) The percentage (B) and
absolute number (C) of CD4+ and CD8+ T cells in the spleen is shown at each time point
and genotype (n=5-14 mice per genotype per time point). Error bars represent the
standard error of the mean. Statistically significant differences (p<0.05) between values
obtained for DTG mice relative to WT (a), dnRAG1 (b), or Eμ-TCL1 (c) mice are
indicated.
113
Figure 3.17 Characterization of lymph node T cells. Lymph node T cell subsets
[CD4+ and CD8+ (A), DN (B), and CD4+CD25+ (C)] were identified by flow cytometry at
36 weeks as in figures 13.16 and 3.18 (n=3-14 mice per genotype). Error bars represent
the standard error of the mean. Statistically significant differences (p<0.05) between
values obtained for DTG mice relative to WT (a), dnRAG1 (b), or Eμ-TCL1 (c);
significant differences between Eμ-TCL1 mice relative to WT (d), dnRAG1 (e), or DTG
(f) mice are also indicated.
114
mice harbor these abnormalities as well. To characterize T cell frequency and
abundance, we used flow cytometry to analyze cohorts of WT, dnRAG1, Eµ-
TCL1, and DTG mice at 6, 12, 24, and 36 weeks of age. This analysis detected a
slight increase in the CD4+ T cell fraction in DTG mice at early time points but a
shift toward CD8+ T cell increase at 36 weeks in the spleen (Figure 3.16A & B).
Increase in CD8+ T cells and subsequent inversion of CD4+ and CD8+ T cell
ratios, which has been reported in Eµ-TCL1 mice (Hofbauer et al., 2011), was
noticeable in both Eµ-TCL1 and DTG mice at 36 weeks in spleen and LN, but is
more pronounced in Eµ-TCL1 mice (Figures 3.16B, C, and 3.17A). Although
absolute numbers of both CD4+ and CD8+ T cells was higher in transgenic
compared to WT mice at 36 weeks in spleen and LN, significant differences were
only established for DTG mice (Figures 3.16C and 3.17A). Further gating of
CD4+ T cells based on CD25 expression showed a significant increase in splenic
CD4+CD25+ T cells in DTG mice by percentage at 36 weeks and in absolute
numbers at 24 and 36 weeks (Figure 3.18). This population of T cells,
presumably Tregs, is commonly expanded in CLL (D’Arena et al., 2012).
Interestingly, we noticed that T cells that were doubly-negative for CD4 or
CD8 expression [CD3+TCRβ+CD8-CD4- (DN T cells)] were increased in
transgenic compared to WT mice particularly at later time points in Eµ-TCL1 and
DTG mice (Figures 3.16A, 3.17B, and 3.19). While the abundance of peripheral
DN T in WT mice is very low (Ford et al., 2006), these cells were significantly
increased in Eµ-TCL1 mice in LN and DTG mice in spleen (Figures 3.17B and
3.19). We hypothesized that DN T cells were a kind of regulatory cell such as
115
Figure 3.18 Expansion of CD4+CD25+ T cells in DTG mice. (A) The percentage of
gated CD4+CD25+ T cells in the spleen identified by flow cytometry is shown. The mean
percentage of these cells for each genotype at 6, 12, 24, and 36 weeks (B), and
absolute numbers at 12, 24, and 36 weeks (C) (n=3-8 mice per genotype per time point)
are represented by bar graphs. Error bars represent the standard error of the mean.
Statistically significant differences (p<0.05) between values obtained for DTG mice
relative to WT (a), dnRAG1 (b), or Eμ-TCL1 (c) mice are indicated.
116
Figure 3.19 Expansion of CD3+TCRβ+CD8-CD4- (DN) T cells in transgenic mice.
Double-negative (DN) T cells are CD3+TCRβ+CD8-CD4- T cells indentified by flow
cytometry as shown in figure 3.16A. The mean percentage of these cells for each
genotype at 6, 12, 24, and 36 weeks (A), and absolute numbers at 12, 24, and 36 weeks
(B) (n=5-8 mice per genotype per time point) are represented by bar graphs. Error bars
represent the standard error of the mean. Statistically significant differences (p<0.05)
between values obtained for DTG mice relative to WT (a), dnRAG1 (b), or Eμ-TCL1 (c);
significant differences between Eμ-TCL1 mice relative to WT (d), dnRAG1 (e), or DTG
(f) mice are also indicated.
117
Figure 3.20 CD1d expression in CD5+ B cells of transgenic mice. (A) Comparison of
CD1d transcript levels between older WT CD19+B220hiCD5- and transgenic CD19+CD5+
B cells determined by gene expression profiling. (B) Flow cytometry was used to
compare the expression of CD1d in WT CD19+CD5- (filled histogram) and CD19+CD5+ B
cells from dnRAG1 (dotted), Eμ-TCL1 (dashed), and DTG mice (solid) at 36 weeks. (C)
The mean fluorescence intensities from B for 5-6 animals of each genotype are
presented in bar graph format. Error bars represent the standard error of the mean. ***,
p< 0.001.
118
Figure 3.21 α-GalCer treatment has little effect on CD5+ B cell accumulation in
DTG mice. 12-week-old WT and DTG mice (n=4 each) were treated with 5µg of α-
GalCer by tail vein injection once every week for 4 weeks and sacrificed one week
following the final treatment. (A-B) The percentage (A) and absolute number (B) of
splenic CD19+CD5+ B cells identified by flow cytometry are shown for representative
animals (A) or in bar graph format (B). (C) Absolute numbers of DN T cells in the spleen,
dentified by flow cytometry, are shown in bar graph format.
119
Figure 3.22 Expression of CD160, BTLA, HVEM, and DX5 in DN T or CD5+ B cells.
Expression levels of CD160, BTLA, HVEM, and DX5 in DN T cells (A), and CD160,
BTLA, and HVEM in WT CD19+CD5- and CD19+CD5+ B cells from transgenic mice (B)
was determined by FACS at 36 weeks for 5-6 mice per genotype. Error bars represent
the standard error of the mean. Statistically significant differences (p<0.05) between
values obtained for DTG mice relative to WT (a), dnRAG1 (b), or Eμ-TCL1 (c); Eμ-TCL1
mice relative to WT (d), dnRAG1 (e), or DTG (f) mice are indicated.
120
NKT cells. However it is was unclear whether these cells were expanding to
inhibit or promote the leukemic cells. NKT cells, unlike conventional T cells,
recognize lipid antigens presented by the non-classical major histocompatibility
complex class 1-like molecule, CD1d (Wu et al., 2004). NKT cells mediate broad
functions ranging from immune protection in infections, maintaining tolerance,
and tumor surveillance (Godfrey and Kronenberg, 2004). Moreover, CLL cells
express CD1d (Fais et al., 2002) and in mice, NKT cells can stimulate B1 and MZ
B cells to augment antibody production in a CD1d-dependent manner (Takahashi
and Strober, 2008).
3.4.2 The Role of Double-negative T Cells in Transgenic Mice
To determine the role of DN T cells in transgenic mice, we initially checked
for CD1d expression in CD5+ B cells. We find that CD5+ B cells of dnRAG1 and
DTG mice had elevated CD1d transcript levels by gene expression arrays as well
as high cell surface expression as assessed by flow cytometry (Figure 3.20).
CD1d in Eµ-TCL1, however, was reduced compared to WT mice. Next, we tested
the role of CD1d in the expansion of leukemic and/or DN T cells in DTG mice.
Using α-galactosylceramide (α-GalCer), a potent agonist for CD1d-restricted
NKT cells (Wu et al., 2004), we found that α-GalCer treatment had little effect on
the number of CD5+ B cells or DN T cells in DTG mice (Figure 3.21). In fact, a
modest decrease was observed in CD5+ B cell numbers in α-GalCer-treated
compared to untreated DTG mice, suggesting an antagonistic effect. Based on
these findings, we reconsidered whether the DN T cells are in fact NKT cells, and
121
Figure 3.23 DN T cells inhibit accumulation of CD5+ cells after adoptive transfer.
(A-B) SCID mice were injected with the indicated number of CD5+ B with or without DN T
cells sorted from the same donors indicated. The SCID mice were sacrificed 8 weeks
after transfer and the percentage (A) and absolute number (B) of CD5+ B cells was
determined by flow cytometry.
122
thus explored alternative pathways that could mediate interactions between CD5+
B cells and DNT cells with relevance to CLL. An emerging pathway involves
CD160, B- and T- lymphocyte attenuator (BTLA), and herpes-virus entry
mediator (HVEM) (CD160-BTLA-HVEM signaling), a bi-directional switch that
can mediate inhibitory or stimulatory effects on immune cells (Cai and Freeman,
2009). CLL cells express CD160, normally expressed in NK, NKT, and T cells, to
promote survival (Liu et al., 2010) as well as BTLA, and HVEM (M’Hidi et al.,
2009). We used flow cytometry to define the expression of these markers and the
pan-NK cell marker CD49 (DX5) on CD5+ B cells and DNT cells. These
experiments show that DN T cells from DTG mice express higher levels of
CD160 and BTLA compared to DN T cells from other mice. All DN T cells from all
genotypes uniformly express low levels of HVEM (Figure 3.22A). On the other
hand, all CD5+ B cells express little CD160 and HVEM, and have reduced BTLA
levels compared to WT CD5- B cells (Figure 3.22B). That we did not observe
expression of DX5 in DN T cells from transgenic mice suggests that these cells
may not be NKT cells (Figure 3.22A).
Finally, we investigated the functional interaction between CD5+ B cells
and DN T cells. These experiments revealed that sorted DN T cells, when
adoptively co-transferred with sorted CD5+ B cells from Eµ-TCL1 mice into SCID
mice, inhibit the expansion of the leukemic cells (Figure 3.23). When co-cultured
together, DN T cells similarly inhibit the expansion of leukemic cells (Figure 3.24)
suggesting this effect is direct. Taken together, the data suggest that DN T cells
123
Figure 3.24 DN T cells inhibit expansion of CD5+ B cells in cell culture. 1x105
CD19+CD5+ spleen lymphocytes sorted from DTG mice by FACS were cultured in
duplicates with or without 5x104 spleen DN T cells from the same mouse. Cells were
counted on day 3, 7, and 10 in a hemacytometer and viability was determined by trypan
blue exclusion.
124
expanding in Eµ-TCL1 and DTG mice do not show clear NKT cell properties, but
nevertheless inhibit the expansion of CD5+ B cells both in vitro and in SCID mice.
125
Table 3.3 Top 50 differentially expressed genes between 12-week dnRAG1 and DTG mice
Gene symbol DTG/dnRAG1 Gene description
Neto2 5.26 neuropilin (NRP) and tolloid (TLL)-like 2
Vash2 1.88 vasohibin 2
Tubb3 1.86 tubulin, beta 3
Crip1 1.69 cysteine-rich protein 1 (intestinal)
Pdcd1lg2 1.69 programmed cell death 1 ligand 2
Myadm 1.67 myeloid-associated differentiation marker
Fjx1 1.66 four jointed box 1 (Drosophila)
Tagln2 1.59 transgelin 2
Mid1 1.53 midline 1
Murc 1.48 muscle-related coiled-coil protein
Vim 1.48 vimentin
Olfr767 1.46 olfactory receptor 767
Tyrobp 1.45 TYRO protein tyrosine kinase binding protein
Cln3 1.44
ceroid lipofuscinosis, neuronal 3, juvenile (Batten, Spielmeyer-Vogt
disease)
Lrrc8c 1.38 leucine rich repeat containing 8 family, member C
2010204K13Rik 1.34 RIKEN cDNA 2010204K13 gene
Nid1 1.34 nidogen 1
Ptk2 1.34 PTK2 protein tyrosine kinase 2
Gpr176 1.32 G protein-coupled receptor 176
Mad2l2 1.31 MAD2 mitotic arrest deficient-like 2 (yeast)
Rtn4rl1 1.31 reticulon 4 receptor-like 1
Ppp3ca 1.30 protein phosphatase 3, catalytic subunit, alpha isoform
Mirhg1 1.27 microRNA host gene 1 (non-protein coding)
Jup 1.26 junction plakoglobin
Vapb 1.23 vesicle-associated membrane protein, associated protein B and C
Slamf6 -1.33 SLAM family member 6
Cyb5b -1.35 cytochrome b5 type B
Il2rb -1.36 interleukin 2 receptor, beta chain
Trim7 -1.39 tripartite motif-containing 7
Hmgn3 -1.41 high mobility group nucleosomal binding domain 3
LOC635992 -1.44 similar to ubiquitin-conjugating enzyme E2 variant 2
Olfr99 -1.44 olfactory receptor 99
Rnu12 -1.45 RNA U12, small nuclear // RNA U12, small nuclear
Gm4383 -1.49 predicted gene 4383
4933404M02Rik -1.52 RIKEN cDNA 4933404M02 gene
Pcp4 -1.6 Purkinje cell protein 4
Mpeg1 -1.63 macrophage expressed gene 1
Fcrl5 -1.70 Fc receptor-like 5
Gm7285 -1.71 predicted gene 7285
V165-D-J-C mu -1.76 IgM variable region
Mctp2 -1.77 multiple C2 domains, transmembrane 2
Ipcef1 -1.78 interaction protein for cytohesin exchange factors 1
Clec2d -1.83 C-type lectin domain family 2, member d
Gm9912 -1.89 predicted gene 9912
Zfp420 -1.92 zinc finger protein 420
Slc15a2 -2.06 solute carrier family 15 (H+/peptide transporter), member 2
EG665955 -2.25 predicted gene, EG665955
Gm5571 -2.27 predicted gene 5571 // predicted gene 5571
Igj -2.35 immunoglobulin joining chain
Lmo7 -3.14 LIM domain only 7
126
Table 3.4 Top common differentially expressed genes among older transgenic mice relative to WT
mice
Fold change
Gene symbol dnRAG1/WT TCL1/WT DTG/WT Gene description
1810046K07Rik 27.28 31.4 38.48 RIKEN cDNA 1810046K07 gene
Cyp11a1 11.31 14.22 26.34
cytochrome P450, family 11, subfamily a,
polypeptide 1
Adm 36.41 25.5 23.38 adrenomedullin
Bmpr1a 10.04 17.82 19.52
bone morphogenetic protein receptor, type
1A
Pstpip2 25.95 53.52 18.61
proline-serine-threonine phosphatase-
interacting protein 2
Bhlhe41 14.04 25.41 17.97 basic helix-loop-helix family, member e41
Ctla4 14.74 21.66 16.77
cytotoxic T-lymphocyte-associated protein
4
Vpreb3 -8.90 -13.56 -9.12 pre-B lymphocyte gene 3
Cr2 -12.25 -26.54 -10.4 complement receptor 2
Gm4955 -8.73 -12.58 -12.38 predicted gene 4955
Satb1 -9.08 -38.65 -13.07 special AT-rich sequence binding protein 1
Gpr171 -22.08 -24.98 -19.47 G protein-coupled receptor 171
Stat4 -25.50 -24.02 -21.45
signal transducer and activator of
transcription 4
Lrrk2 -32.24 -37.39 -34.47 leucine-rich repeat kinase 2
Il10* 11.93 12.70 13.91 interleukin 10
*Il10 was not among the top 50 common differentially expressed genes in all pair-wise comparisons.
127
Table 3.5 Top 50 differentially expressed genes between ill DTG mouse (M53) & Eµ-TCL1mouse
(M52)
Gene symbol*
DTG M53/TCL1 M52
Fold change Gene description
Prl2a1 269.40 prolactin family 2, subfamily a, member 1
Sox4 42.75 SRY-box containing gene 4
Prl8a2 21.45 prolactin family 8, subfamily a, member 2
Dpp4 18.78 dipeptidylpeptidase 4
Kcnj5 16.97
potassium inwardly-rectifying channel, subfamily J,
member 5
1300014I06Rik 14.56 RIKEN cDNA 1300014I06 gene
Rpl39l 12.40 ribosomal protein L39-like
Rgs13 11.34 regulator of G-protein signaling 13
Xlr3b 11.27 X-linked lymphocyte-regulated 3B
Atp1b1 10.38 ATPase, Na+/K+ transporting, beta 1 polypeptide
Gm10561 10.21 predicted gene 10561
Tet1 10.18 tet oncogene 1
Scamp1 9.92 secretory carrier membrane protein 1
Gpr177 9.48 G protein-coupled receptor 177
Gm10384 9.15 predicted gene 10384
Wdfy3 9.00 WD repeat and FYVE domain containing 3
Atrnl1 8.60 attractin like 1
Dusp6 8.36 dual specificity phosphatase 6
Rgs18 8.26 regulator of G-protein signaling 18
1110032E23Rik 8.24 RIKEN cDNA 1110032E23 gene
Xlr3c 8.24 X-linked lymphocyte-regulated 3C
Xlr3a 7.85 X-linked lymphocyte-regulated 3A
F11r 7.68 F11 receptor
Tes 7.44 testis derived transcript
Ccdc125 7.25 coiled-coil domain containing 125
Zdhhc2 -8.43 zinc finger, DHHC domain containing 2
Cd68 -9.13 CD68 antigen
Cd3g -9.21 CD3 antigen, gamma polypeptide
Gm410 -9.22 predicted gene 410
Kcnn4 -9.25
potassium intermediate/small conductance calcium-
activated channel, subfamily N, member 4
Fcgrt -10.94 Fc receptor, IgG, alpha chain transporter
Igk-V28 -12.16 immunoglobulin kappa chain variable 28 (V28)
Ighv1-72 -12.48 immunoglobulin heavy variable V1-72
Apobec2 -12.89
apolipoprotein B mRNA editing enzyme, catalytic
polypeptide 2
Fxyd5 -13.16 FXYD domain-containing ion transport regulator 5
Prkar2b -13.75
protein kinase, cAMP dependent regulatory, type
II beta
Fbxw13 -13.79 F-box and WD-40 domain protein 13
Ccbp2 -14.01 chemokine binding protein 2
Emr1 -14.46
EGF-like module containing, mucin-like, hormone
receptor-like sequence 1
Slamf9 -15.19 SLAM family member 9
Gm5486 -17.14 predicted gene 5486
Gstt1 -17.57 glutathione S-transferase, theta 1
Anxa2 -20.23 annexin A2
Fgl2 -20.71 fibrinogen-like protein 2
LOC100047053 -21.50 similar to monoclonal antibody kappa light chain
Pdlim1 -27.54 PDZ and LIM domain 1 (elfin)
LOC674190 -30.31 similar to Ig heavy chain V region IR2 precursor
Igh -33.42 immunoglobulin heavy chain complex
LOC100046894 -112.64 similar to Igk-C protein
V165-D-J-C mu -317.51 IgM variable region
*Items listed in bold are found in both Tables 3.5 and 3.6.
128
Table 3.6 Top 50 differentially expressed genes between ill DTG mouse (F57) & Eµ-TCL1 mouse
(M52)
Gene symbol*
DTG F57/ TCL1 M52
Fold change Gene description
Prl2a1 200.97 prolactin family 2, subfamily a, member 1
Xist 95.10 inactive X specific transcripts
Prl8a2 66.42 prolactin family 8, subfamily a, member 2
Sox4 54.87 SRY-box containing gene 4
Car2 53.97 carbonic anhydrase 2
Gpr126 39.55 G protein-coupled receptor 126
Pfn2 35.98 profilin 2
Cp 34.95 ceruloplasmin
Tnip3 32.26 TNFAIP3 interacting protein 3
Fcer2a 31.59 Fc receptor, IgE, low affinity II, alpha polypeptide
Cpm 30.20 carboxypeptidase M
Gm10879 29.01 predicted gene 10879
Anxa1 25.91 annexin A1
Dusp4 25.75 dual specificity phosphatase 4
Abp1 23.25
amiloride binding protein 1 (amine oxidase, copper-
containing)
Id2 21.62 inhibitor of DNA binding 2
Rnf128 18.68 ring finger protein 128
Fabp7 18.40 fatty acid binding protein 7, brain
Dusp6 17.93 dual specificity phosphatase 6
Slc22a21 15.49
solute carrier family 22 (organic cation transporter), member
21
Akt3 14.84 thymoma viral proto-oncogene 3
Scin 14.54 scinderin
Azgp1 13.03 alpha-2-glycoprotein 1, zinc
Igh-6 12.75 immunoglobulin heavy chain 6 (heavy chain of IgM)
Parp8 12.59 poly (ADP-ribose) polymerase family, member 8
Cln8 -6.79 ceroid-lipofuscinosis, neuronal 8
Neurod4 -7.26 neurogenic differentiation 4
Lrrc25 -7.52 leucine rich repeat containing 25
Gp49a -7.74 glycoprotein 49 A
Tmprss13 -7.96 transmembrane protease, serine 13
Prkar2b -8.03 protein kinase, cAMP dependent regulatory, type II beta
Emr1 -8.05
EGF-like module containing, mucin-like, hormone
receptor-like sequence 1
Kdm5d -8.51 lysine (K)-specific demethylase 5D
Sell -9.15 selectin, lymphocyte
Cd9 -9.97 CD9 antigen
Fgl2 -10.09 fibrinogen-like protein 2
Cd3g -10.35 CD3 antigen, gamma polypeptide
Uty -10.71
ubiquitously transcribed tetratricopeptide repeat gene, Y
chromosome
Fbxw13 -12.03 F-box and WD-40 domain protein 13
Ccbp2 -13.49 chemokine binding protein 2
Gstt1 -13.80 glutathione S-transferase, theta 1
Hpse -13.87 heparanase
Lgals1 -14.20 lectin, galactose binding, soluble 1
V165-D-J-C mu -14.31 IgM variable region
Igh -16.44 immunoglobulin heavy chain complex
Cd36 -16.52 CD36 antigen
Ddx3y -24.47 DEAD (Asp-Glu-Ala-Asp) box polypeptide 3, Y-linked
Eif2s3y -24.72
eukaryotic translation initiation factor 2, subunit 3, structural
gene Y-linked
LOC674190 -37.70 similar to Ig heavy chain V region IR2 precursor
LOC100046894 -48.43 similar to Igk-C protein
*Items listed in bold are found in both Tables 3.5 and 3.6.
129
CHAPTER 4: DISCUSSION
4.1 FAILURE IN SELF-TOLERANCE PROMOTES CLL PROGRESSION
4.1.1 Expression of Dominant-negative RAG1 Accelerates CLL
Progression in Eµ-TCL1 Mice
An emerging model for the etiology of CLL suggests that this disease
originates through the monoclonal expansion of an antigen-experienced
CD5+ B cell displaying poly-reactivity and/or autoreactivity toward molecular
motifs present on and often shared between apoptotic cells and bacteria
(Myhrinder et al., 2008). CD5+ B cells possessing this reactivity profile may
develop through positive selection, such as peritoneal B1 cells and MZ B
cells (Montecino-Rodriguez et al., 2006). Alternatively, they may emerge
from conventional B2 lineage cells that are driven to express CD5 as a
mechanism to attenuate chronic (auto)antigenic BCR signaling in response to
failed attempts at silencing or reprogramming fortuitous germline-encoded
BCR autoreactivity (Jankovic et al., 2004; Hippen et al., 2000). If immune
suppression is breached, the autoreactive B cell may enter the germinal
center reaction, giving rise to somatically mutated B cells with a more
restricted reactivity profile (Herve et al., 2005). In this way, both unmutated
and mutated CLL may be traced to a common polyreactive/autoreactive adult
B lineage precursor (Herve et al., 2005), which is consistent with the
observation that unmutated and mutated CLL show similar gene expression
profiles (Seifert et al., 2012).
130
Receptor editing initiated in response to autoantigen exposure is
thought to occur primarily during the immature/transitional T1 stage of B cell
development (Wang et al., 2007; Keifer et al., 2008). We speculate that a
stochastic mutation which impairs receptor editing induced in response to
self-reactivity may enforce B cell autoreactivity. Based on our previous work
showing that dnRAG1 mice accumulate CD5+ B cells without progressing to
overt CLL (Hassaballa et al., 2011), we propose that autoreactivity enforced
by a receptor editing defect could permit continued autoantigenic stimulation,
and thereby promote sustained CD5 expression and persistence of a CD5+ B
cell clone. This possibility is consistent with the observation that CLL is often
preceded by an indolent monoclonal B cell lymphocytosis (MBL) that is
phenotypically and cytogenetically similar to CLL (Scarfo et al., 2010;
Rawstron et al., 2008). Although the initiating genetic mutation enforcing B
cell autoreactivity would normally expected to be rare and restricted to a
single B cell (thereby driving emergence of an MBL clone), developing B cells
undergoing receptor editing (estimated at 25-75% of B cells (Wardemann et
al., 2003) in dnRAG1 mice may frequently be blocked from successful editing
by dnRAG1 expression. Thus, by facilitating a rate-limiting step in the
emergence of CLL precursors, dnRAG1 expression may accelerate CLL
progression in Eµ-TCL1 mice. If so, one might predict that the clonal B cell
repertoire in ill DTG mice should be more diverse than ill Eµ-TCL1 mice.
Indeed, the observation that DTG mice show a higher number of unique
productively rearranged heavy and light chain genes amplified by PCR lends
131
support to this idea (Table 3.1 and 3.2).
We recognize that the absence of recurrent RAG mutations in CLL
(Puente et al., 2011) argues that CLL does not arise through defects in RAG
activity. However, we emphasize that autoreactivity may be enforced by
RAG-independent mutations which disrupt any of the pathways involved in
initiating or completing receptor editing, or eliminating autoreactive B cells
that fail to successfully edit. The same principle also applies for defects in
receptor revision postulated to occur in B cells in response to acquiring
autoreactivity by somatic hypermutation. Once enforced autoreactivity is
established, subsequent genetic lesions (modeled here by Eµ-TCL1
expression) may promote further expansion and/or transformation of the
CD5+ B cell. A simplified model summarizing the etiology and progression of
CLL promoted by impaired receptor editing is shown in Figure 4.1. While this
model suggests that autoantigenic stimulation induces receptor editing, cell-
autonomous signaling mediated by certain intrinsically
autoreactive/polyreactive heavy chains showing recurrent usage in CLL might
also initiate this process (Duhren-von Minden et al., 2012). One way cell-
autonomous signaling could normally be attenuated is through light chain
receptor editing to permit selection of “editor” light chains that neutralize
interactions mediated by HCDR3. Studies of mice expressing an IgH
transgene specific for dsDNA provide precedence for this possibility (Li et al,
2001). We speculate that CLL cells may retain cell-autonomous signaling
capacity because non-editor light chains have either been positively selected
132
or failed to be replaced by receptor editing.
4.1.2 Breaching Tolerance Promotes CLL
Previous studies have shown that CLL emergence in Eµ-TCL1 mice is
accelerated when B cell tolerance is breached (Enzler et al., 2009; Bertilaccio
et al., 2011). Transgene expression of the pro-survival factor for normal and
leukemic B cells, BAFF (Enzler et al., 2009), and loss of expression of TIR8
(type I transmembrane inhibitory receptor 8; SIGIRR), a negative regulator of
Toll-like receptor and interleukin receptor signaling (Bertilaccio et al., 2011)
both accelerate the onset and progression of murine CLL in Eµ-TCL1 mice.
Both BAFF and TIR8 are implicated in the regulation of B cell tolerance since
autoimmunity develops in BAFF transgenic mice (Mackay et al., 1999; Khare
et al., 2000) as well as in TIR8-/- mice bred onto a lupus-prone strain
background (Lech et al., 2008). That dnRAG1 expression also appears to
interfere with this process (Hassaballa et al., 2011), and similarly accelerates
disease progression in Eµ-TCL1 mice, argues that mechanisms required to
enforce self-tolerance are common targets for disruption in CLL etiology
and/or progression. The connection between loss of self-tolerance,
autoimmunity, and CLL is further underscored by observation that CLL BCRs
bind a multitude of autoantigens and about a quarter of CLL patients develop
autoimmune manifestations during the course of the disease (Kipps et al.,
1988; Rosen et al., 2010; Caligaris-Cappio et al., 1994; Zent and Kay, 2010).
Our studies also show that CLL cells in Eµ-TCL1 and DTG mice carry
133
134
Figure 4.1 Model for how defects in receptor editing can promote development
of MBL and CLL. Non-self-reactive immature B cells arriving from the bone marrow
progress normally through the immature/transitional stages of B cell development
where receptor editing normally occurs. An immature/T1 B cell possessing an
autoreactive specificity normally subjected to editing may acquire a spontaneous
mutation that impairs receptor editing (RE), (modeled here by dnRAG1 expression),
which enforces receptor specificity and leads the B cell to retain or adopt a CD5+ B1-
like (and CLL-like) phenotype. The cell may persist or accumulate as an MBL, which
may or may not require other mutations, such as those causing TCL1 over-
expression. Additional genetic lesions may promote MBL evolution to CLL and
perhaps subsequent transformation to high-grade malignancy such as in Richter’s
syndrome (RS) (Tsimberidou et al., 2006). A similar series of events may also occur
in post-germinal center B cells attempting to undergo receptor revision after having
acquired autoreactivitiy during hypermutation (not shown).
135
BCRs with specificities toward autoantigens such as DNA, membrane
phospholipids, and RBC epitopes, implicating loss of tolerance in the initiation
or progression of leukemia. Additionally, the expression pattern of BCR
components and signaling genes in all transgenic mice suggest that these
cells have encountered antigens. CD5 expression, for example, may be
induced on B cells rendered anergic by chronic antigenic stimulation (Hippen
et al., 2000) which, in principle, would be expected if CLL was driven by self-
antigens which are ubiquitous in nature. Indeed, B cells in dnRAG1 mice
show some evidence of anergy, as they are intrinsically hyporesponsive
toward anti-IgM crosslinking and mitogenic stimulation in vitro and mount
poorer immune responses toward thymus-independent antigens compared to
wild-type controls (Hassaballa et al., 2011). Additional support for the
induction of functional anergy in dnRAG1 and DTG mice comes from the
observation that, serum IgM and IgG levels in these animals was significantly
lower compared to wild-type mice at both 12 and 36
weeks of age (Figure 3.9).
CLL B cells are antigen-experienced with cells from subset of patients
displaying signs of exhaustion (Mockridge et al., 2007; Muzio et al., 2008;
Stevenson et al., 2011). CD5 expression, which can be a marker for anergic
B cells (Hippen et al., 2000), may be induced after prolonged antigenic
exposure through the transcription factor Nfatc1, which itself has been found
136
to be constitutively expressed in CLL or to be upregulated after BCR ligation
more so in cases with unmutated Ig VH genes (Guarini et al., 2008; Le Roy et
al., 2012). CD22, a negative regulator of BCR signaling that is downregulated
in CLL (Jelinek et al., 2003; Damle et al., 2002), was also found to be
downregulated in CD5+ B cells of transgenic mice, suggesting a previous
encounter with antigens (Lajaunias et al., 2002; Damle et al., 2002). The
upregulation of CTLA4, an inhibitory receptor normally expressed in T cells,
in CD5+ B cells from all transgenic mice and human CLL (Rosenwald et al.,
2001), implicates an adaptation to quench BCR signals since CLL cases
where CTLA4 is downregulated are associated with poor prognosis (Joshi et
al., 2007). The expression patterns of these genes may explain why a subset
of CLL cells respond poorly to antigen stimulation (Mockridge et al., 2007;
Muzio et al., 2008), which could be a contributing factor to the
hypogammaglobulinemia seen in CLL patients (Rozman et al., 1988; Colovic
et al., 2001).
Of particular interest is the finding that CD5+ B cells from all transgenic
mice, like CLL cells (Kitabayashi et al., 1995; DiLillo et al., 2013), produce the
anti-inflammatory/immunosuppressive cytokine, IL-10 (Moore et al., 2001).
This supports a similar cell of origin for both species since CD5+ B cells are
the primary source of B cell-derived IL-10 in mice and humans (O’Garra et al,
1992; Gary-Gouy et al., 2002). What is unclear is whether IL-10 is produced
to suppress inflammation and/or as a survival factor for leukemic cells. IL-10
expression has been shown to correlate with clinical stage and CLL
137
progression (Kamper et al., 1999; Karmali et al., 2013), suggesting that it
plays a significant role in pathogenesis. IL-10 protects CLL cells from
apoptosis in culture (Kitabayashi et al., 1995) and loss of IL-10 blocks
leukemia development in NZB mouse strain susceptible to CLL, which
suggests that this cytokine may act as an autocrine growth factor for CLL
cells (Ramachandra et al., 1996; Czarneski et al., 2004). Additionally, IL-10
may contribute to the immunosuppressive phenotype observed in CLL. Since
IL-10 has a direct effect on T cells (Moore et al., 2001), it is possible that a
generalized increase in IL-10 expression limits T cell activation during
infection and even tumor surveillance.
Of note, IL-10 is also produced by regulatory B (Breg) cells, which
reportedly display a CD5+CD1dhiCD21+ phenotype (Mauri and Bosma, 2012).
However, since the splenic CD5+ B cells accumulating in dnRAG1, Eµ-TCL1,
and DTG mice are clearly CD21- (Figure 3.3), we conclude that these cells
are unlikely to be Bregs.
4.1.3 Significance of Prl2a1 Expression in dnRAG1 and DTG Mice
Gene expression profiling shows that one gene which distinguishes dnRAG1
and DTG mice from Eµ-TCL1 mice is Prl2a1, which is highly expressed in
CD5+ B cells from dnRAG1 and DTG mice (up to several hundred-fold)
compared with Eµ-TCL1 mice (Figures 3.10, 3.12, and 3.13). Prl2a1 is a
prolactin paralogue and a member of the hormone gene superfamily which
consists of growth hormone, prolactin, prolactin-like proteins, and placental
138
lactogens (Goffin et al., 1996; Wiemers et al., 2003; Simmons et al., 2008).
The hormone gene superfamily members are related, based on sequence
analysis, by sequence and are thought to have originated through gene
duplications. While most mammals, including humans, have a single prolactin
gene, rodents have a least two dozen prolactin paralogues that arose by
divergence after duplication of prolactin (Wiemers et al., 2003; Li and Zhang,
2006). Expression of prolactin and related proteins is regulated both spatially
and temporally, and control a wide range of biological functions ranging from
reproduction and lactation to immunoregulation (Freeman et al., 2000).
Prolactin acts as a cytokine in immune cells by signaling through several
pathways including Jak2/Stat5, MAP kinase, or by activating protein tyrosine
kinases such Src, Fyn, and Tec to induce growth and survival (Clevenger et
al., 1998). Little is known about the role of Prl2a1 especially in the immune
system but the effect of prolactin on lymphocytes is well recognized
(Hiestand et al., 1986; Clevenger et al., 1998; Peeva et al., 2003; Saha et al.,
2009; Shelly et al., 2012). Prolactin or prolactin receptor deficient mice show
normal development of lymphocytes (Bouchard et al., 1999; Dorshkind and
Horseman, 2000), but hyperprolactinemia promotes autoimmunity in both
humans and mice. For instance, hyperprolactenemia is associated with
systemic lupus erythematosus, Sjogren’s syndrome, and rheumatoid arthritis
(Shelly et al., 2012) and prolactin induction exacerbates lupus in susceptible
mouse strains such as NZB/NZW F1 mice, which can be ameliorated by
treatment with bromocriptine (Saha et al., 2011). Bromocriptine is a
139
dopamine receptor agonist (Waddington, 1986), which is thought to function
like dopamine in inhibiting the production of second messengers such as ca2+
and cyclic AMP, which are necessary for prolactin secretion (Enjalbert et al.,
1986; Schettini et al., 1986), Additional evidence suggests prolactin signaling
may regulate B cell tolerance mechanisms (Saha et al., 2011) by promoting
survival of T1 transitional B cells that are normally subjected to negative
selection at this stage (Peeva et al., 2003; Saha et al., 2009; Ledesma-Soto
et al., 2012). We speculate that murine autoreactive B cells transiently
produce Prl2a1 as a pro-survival factor to facilitate receptor editing, but in
dnRAG1 and DTG mice, Prl2a1 expression is sustained because receptor
editing is blocked by dnRAG1 expression. Because humans do not have a
Prl2a1 homologue (Li and Zhang, 2006), its role in B cell development and
CLL cannot be ascertained; whether an orthologous prolactin/growth
hormone family member assumes its function in human B cells remains
unclear.
4.2 ROLE OF REGULATORY T CELLS IN CLL
4.2.1 CD4+CD25+ T cells
Regulatory T cells (Tregs), normally defined as either CD4+CD25+ or
CD4+CD25+ with Foxp3, or with low or absent CD127, are increased in CLL
(D’Arena et al., 2012). The normal role of these cells is to maintain peripheral
tolerance (Sakaguchi et al., 2008) but their expansion in many hematological
140
and solid malignancies suggests that they may also facilitate tumor escape.
This concept is supported by the observation that depletion of Tregs or all
CD4+ T cells restores anti-tumor immunity (Beyer and Schultze, 2006).
The mechanisms of Treg expansion in CLL are unclear. Although
Tregs may be formed through stimulation by tumor antigens, this does not
appear to be the case in CLL (Jak et al., 2009). Malignant, but not normal, B
cells can induce Treg differentiation from CD4+CD25- through direct contact
(Han et al., 2011). Because changes induced on CD4+ and CD8+ T cells by
CLL cells are mediated by direct contact (Gorgun et al., 2005), it is plausible
that a similar mechanism could also induce differentiation to Tregs.
Alternatively, differentiation of Tregs may be fostered by IL-10 and TGF-β
(Zheng et al., 2004), cytokines that are produced by CLL cells (Kitabayashi et
al., 1995; DiLillo et al., 2013; Kremer et al., 1992; Lotz et al., 1994; Schuler et
al., 1999).
The immunosuppressive properties of Tregs in conjunction with CD4+
and CD8+ T cell dysfunction and CLL-derived IL-10 presumably contribute to
the systemic immunodeficiency manifested in CLL patients. This could
explain the high incidence of autoimmune phenomena, infections, and risk of
secondary malignancies in CLL (Zent and Kay, 2010; Itala et al., 1992;
Molica et al., 1993; Kyasa et al. 2004; Maddocks-Christianson et al., 2007).
4.2.2 Double-negative (DN) T Cells
We found an age-dependent increase in splenic DN T cells in both Eµ-
141
TCL1, and DTG mice. While these cells do not show clear NKT cell
properties, they promote clearance of CD5+ B cells both in vitro and when
they are co-transferred with CLL cells into immunodeficient mice (Figures
3.24 and 3.23). Whether these cells play the same role in their natural setting
in ill mice is unclear because CLL cells have a demonstrated proclivity to
inhibit or subvert the function of other cells in tumor microenvironments
(Fecteau and Kipps, 2012). For example, CD4+CD25+ T cells that also
expand in these mice, and are absent in SCID mice, could suppress DN T
cells. It would not be surprising if DN T cells from DTG mice are not active in
their natural setting since they express high levels of BTLA, which can be a
marker for anergy in T cells (Murphy et al., 2006).
Mature T cells that don’t express CD4 or CD8 encompass several
subsets including NKT cells (Godfrey et al., 2010). The role of NKT cells in
CLL is unclear. NKT cells do not appear to be expanded in CLL compared to
healthy population (Gibson et al., 2011) but their frequency is reduced in
patients with progressive compared to indolent disease (Jadidi-Niaragh et al.,
2012). However, NKT cells can be primed by CLL cells through CD1d
resulting in killing of the CLL cells in vitro (Fais et al., 2004). Since CLL cells
can induce functional defects in NK cells (Kay et al., 1984) and T cells
(Ramsey et al., 2008; Riches et al., 2013), it is not clear whether the same is
true for NKT cells in vivo particularly since there is a lack of autologous anti-
tumor immune responses even though CLL cells express tumor antigens
(Krackhardt et al., 2002).
142
The possibility that NKT cells play a contributing role in CLL
pathogenesis is intriguing, but has not been fully investigated. CD1d, which
presents antigens to NKT cells, appears to be elevated in a subset of CLL
cases (Kotsianidis et al., 2011; Anastasiadis et al., 2013; Fais et al., 2004) as
well as in dnRAG1 and DTG mice (Figure 3.20). Although CD1d expression
is higher in B cell lymphoproliferative diseases originating in cells that
naturally express high levels of CD1d, such as splenic MZ lymphoma
compared to CLL (Amano et al., 1998; Kotsianidis et al., 2011), this marker is
nevertheless increased in CD38+ CLL cases and those bearing unmutated Ig
genes (Kotsianidis et al., 2011; Anastasiadis et al., 2013; Fais et al., 2004).
4.3 LESSONS FROM MURINE MODELS OF BENIGN AND
MALIGNANT CD5+ B CELL EXPANSION
Gene expression profiling studies provide evidence of distinct but
convergent pathways for CLL development. The finding that DTG mice more
closely resemble dnRAG1 mice than Eµ-TCL1 mice with respect to
expression profiles at 12 weeks and serum Ig levels at both time points
argues that CD5+ B cell accumulation in DTG mice is driven primarily by
dnRAG1 expression. Thus, CD5+ B cells in Eµ-TCL1 mice and dnRAG1/DTG
mice appear to initially emerge by slightly different mechanisms, yet their
gene expression patterns remain more similar to one another than to other
normal splenic B cell populations.
143
Interestingly, this pattern may be also hold true for other mouse strains
that show evidence of CD5+ B cell accumulation (Hayakawa et al., 1983;
Berland and Wortis, 2002; Hassaballa et al., 2011) including murine models
of CLL (Table 1.2). For instance, most of the CLL models reportedly share an
immunophenotype that is centered on lower expression of B220 than
conventional B cells and lack of CD23, which is expressed on human CLL
cells (Table 1.2; Damle et al., 2002). This would suggest that either the same
B cell/stage is involved in transformation in these models or that the
transforming mechanism itself is similar. However, it is more likely that the
same B cell subset is affected in these models since the original molecular
defects lie in distinct pathways. This possibility is supported partly by the fact
that murine MZ and B1 B cells do not express CD23 (Waldschimidt et al.,
1992; Best et al., 1995). Additionally, in the case of NZB and Eµ-TCL1 mice
for instance, the leukemic cells bear other properties of B1 B cells such as IL-
10 expression, and BCR characteristics (O’Garra et al, 1992; Gary-Gouy et
al., 2002; Czarneski et al., 2004; DiLillo et al., 2013; Phillips et al., 1992; Yan
et al., 2006). Furthermore, the distinct patterns of organ involvement suggest
that leukemia in NZB, APRIL, and Eµ-TCL1 mice most likely originates from
peritoneal B1 cells, while the others may originate from similar cells found in
other organs such as the spleen (Table 1.2). The relatively long generation
time in most of the models suggests that additional defects are necessary to
develop frank leukemia. This possibility is supported by TCL1 expression in
the dnRAG1 mouse.
144
Why do some B cell subsets appear more vulnerable to perturbation
than others? The answer may lie in the different pathways by which these
cells develop and function. B1 and MZ B cells, unlike follicular B cells, are
positively selected by self-antigens such as those resulting from apoptosis
and oxidative processes (Bendelac et al., 2001). In deed, even the
expression of Ig transgenes with specificities toward phosphatidyl choline,
thy-1, RBCs, and Sm, antigens that are principally bound by B1 cells,
expands the B1 compartment in mice (Berland and Wortis, 2002). These
specificities, while seemingly unwanted, are tolerated because they are
beneficial to the host in providing rapid protection against pathogenic
microbes and in clearing of apoptotic cellular debris (Bendelac et al., 2001;
Baumgarth, 2011). B1 cells, in particular, are crucial in these tissue
homeostatic functions since they express several scavenger receptors, of
which CD5 is one (Rodriguez-Manzanet et al., 2010; Jordo et al., 2011).
Therefore, when these cells become diseased in autoimmunity or neoplasia,
they are difficult to purge because they are naturally designed to be
maintained at a cost to the host. That CLL cells are difficult to maintain in
culture (Collins et al., 1989) would support the notion that these cells are
actively maintained in vivo, in essence, by persistent antigen stimulation.
Berland and Wortis (2002), in discussing the origins of B1 cells note
that defects in BCR signaling fundamentally affect the B1 lineage while
sparing conventional B cells for the most part. Deletion or defects in a variety
of positive regulators of BCR signals, namely, Btk, PKCβ, PLCγ, p85α
145
subunit of PI3-K, CD19, BLNK, CD21/35, and vav-1 lead to loss of CD5+ B
cells in mice. On the other hand, defects targeting negative regulators of BCR
signaling, namely, SHP-1, CD22, Lyn, CD72, and more recently, Siglec-G
(Hoffmann et al., 2007; Ding et al., 2007) result in accumulation of CD5+ B
cells. Thus, the CD5 compartment in mice may be a repository for B cells
with certain related defects (Hassaballa et al., 2011). These observations
suggest that regulation of BCR signaling threshold is crucial in the generation
of CD5+ B cells. Collectively and in theory, these studies in murine models
suggest that there are multiple defects that can potentially lead to the
accumulation of CD5+ B cells, which could explain CLL heterogeneity in
humans.
4.4 FUTURE WORK
4.4.1 Mechanisms of Disease Acceleration in DTG Mice
Although we have not established specific factors responsible for
accelerating disease progression in DTG mice presumably because CD5+ B
cells in dnRAG1 and Eµ-TCL1 mice develop in overlapping pathways, we
have identified genes that are differentially expressed in CD5+ B cells from
DTG mice relative to their single-transgene counterparts which may warrant
further study. For example, both Dpp4 upregulation and Sell downregulation
reportedly correlate with poor prognosis in human CLL (Cro et al., 2009;
Stratowa et al., 2001), which is consistent with the earlier onset of disease
146
observed in DTG mice relative to Eµ-TCL1 mice. Another interesting gene
that warrants further attention is PTPN22. PTPN22, which acts as a negative
regulator of BCR signaling in B cells (Arechiga et al., 2009), is upregulated in
CLL (Wang et al., 2004; Negro et al., 2013) and has polymorphisms that are
associated with multiple autoimmune conditions (Bottini et al., 2006; Dai et
al., 2013). Since this gene plays a significant role in BCR signaling fate
(Arechiga et al., 2009) and we found it to be upregulated least 2.5-fold at all
time points in all transgenic mice (Figure 3.15), it is possible that it plays a
significant role in CLL development in mice and humans.
4.4.2 Role of Hormone Gene Superfamily in Normal and Leukemic B
Cells
Besides Prl2a1, we found Prl7c1 and Prl8a2 to be upregulated in
dnRAG1 and DTG mice, implicating prolactin family genes in B cell
development and murine leukemia. Although prolactin and its receptor are
reportedly expressed in lymphocytes and other immune cells (Clevenger et
al., 1998; Peeva et al., 2003), this is the first report, to our knowledge, of
expression of these prolactin-like genes in lymphocytes. It would be
interesting to investigate whether these genes are expressed in normal
murine B and T lymphocytes, and if so, at what stages. Based on this study
and previous studies on prolactin (Peeva et al., 2003; Saha et al., 2009;
Ledesma-Soto et al., 2012), it is likely that these genes would be expressed
in transitional stages or in cells undergoing receptor editing/revision possibly
147
to facilitate survival during selection processes. First and foremost, it would
be important to establish whether prolactin-like proteins have bioactivity on
lymphocytes. Loss of prolactin or its receptor has little effect on lymphocyte
development, but overexpression of prolactin aggravates autoimmune
conditions (Bouchard et al., 1999; Dorshkind and Horseman, 2000; Saha et
al., 2011; Shelly et al., 2012). If prolactin-like proteins also signal through the
prolactin receptor in lymphocytes, then it can be presumed that Prl2a1 knock-
out mice would not have a clear phenotype as well except owing to the fact
others have noted that hormones could act differently under stressful
conditions (Dorshkind and Horseman, 2000). Nevertheless blocking prolactin-
like proteins, by analogy to experiments using bromocriptine to inhibit
prolactin secretion in mice (Peeva et al., 2003), would help to establish
whether these prolactins are required for development of leukemia in mice.
Most importantly, are similar hormones involved in CLL pathogenesis?
Although humans lack these prolactin-like genes, orthologous genes within
the hormone gene superfamily, namely prolactin and growth hormone (Goffin
et al., 1996; Wiemers et al., 2003; Simmons et al., 2008), may assume a
similar function in human B cells. Interestingly, prolactin is involved in the
pathogenesis of some autoimmune conditions such as SLE (Gutierrez et al.,
1995; Saha et al., 2011), and CLL patients are also prone to autoimmunity
including SLE (Zent and Kay, 2010; Lugassy et al., 1992). The possibility that
there exists an intersection between autoimmunity and CD5+ B cell neoplasia
is illustrated by New Zealand mice, which serve as of model for SLE as well
148
as CLL (Stall et al., 1988; Kono et
al., 1994; Phillips et al., 1992; Raveche et al., 2007). Thus, it is possible that
a subset of CLL patients may also have underlying hyperprolactinemia.
4.4.3 Role of CD1d in CLL
Since we found CD1d to be upregulated in dnRAG1 and DTG mice, it
would be interesting to dissect its role in leukemia development in light of the
recent findings that CD1d expression is elevated in aggressive CLL cases
(Fais et al., 2004; Kotsianidis et al., 2011; Anastasiadis et al., 2013). Even
though treatment of mice with α-GalCer seemed to have little effect on
accumulating CD5+ B cells in DTG mice, these experiments could be
extended to include CD1d antagonists or a different agonist (Lombardi et al.,
2010; Szatmari et al., 2006). However, targeted deletion of CD1d in B cells
would reveal whether or not it is required for accumulation of CD5+ B cells in
transgenic mice. Along with these experiments, one might monitor NKT cells
by using CD1d tetramers (Matsuda et al., 2000; Gumperz et al., 2002) to
determine their role in accumulation of CD5+ B cells in these mice. While the
identity of DN T cells found in Eµ-TCL1 and DTG mice remain unclear at
present, it could be determined if they are similar to other known T cell
subsets such as those described by Zhang et al. (2000) and Chen et al.
(2004) based on immunophenotype and secreted molecules.
Of particular interest is the nature and fate of antigens bound by B1
and CLL cells. These cells bear specificities toward peculiar antigens such as
149
carbohydrates and lipids (Bendelac et al., 2001; Catera et al., 2008;
Myhrinder et al., 2008; Chu et al., 2010). That CD1d presents lipid and
glycolipid antigens (Porcelli et al., 1999; Godfrey et al., 2010) raises the
question whether there is a link between these activities in normal or
diseased B cells. For instance, how frequently do lipid-based antigens
internalized with the BCR end up being processed and loaded on CD1d, and
would this be relevant to normal B cell function and disease?
4.4.4 Identity of double-negative T cells
The double-negative (DN) T cells found to be expanding in Eµ-TCL1
and DTG mice do not appear to be NK T cells. There exist other less
common DN regulatory T cells. These cells make 1-5% of peripheral T cells
in mice and humans (Strober et al., 1996; Chen et al., 2004) but similar cells
have been found to expand be expanded in pathological conditions such as
SLE (Shivakumar et al., 1989; Crispin et al., 2008). The DN regulatory T cells
may not express NK cell markers such as NK1.1, as is the case in DTG mice,
but they additionally express markers of activation such as CD25 and CD69
but do not express CD44, and secrete α, β, and γ interferons (Strober et al.,
1996; Zhang et al., 2000; Chen et al., 2004). Functionally, DN T cell normally
regulate tolerance and are potent suppressors of other effector T cells and
thus have been shown to be critical in preventing allograft rejection (Zhang et
al., 2000; Chen et al., 2004). However, these cells can contribute to
pathological conditions such as SLE by producing inflammatory cytokines
150
and enhancing production of autoantibodies (Shivakumar et al., 1989; Crispin
et al., 2008). Recently, a subset of DN T cells has also been reported to be
increased in the peripheral blood in CLL but its role in this disease remains to
be explored (Weinkove et al., 2013).
4.5 CONCLUDING REMARKS
Majority of the work presented in this dissertation (sections 3.1 to 3.3)
is published in Nganga et al. Blood. (2013) 121(19): 3855-66, S1-16. This
dissertation asserts that the BCR is not just a bystander but plays an active
role in CLL. In fact, studies in dnRAG1 and DTG mice imply that failure in
remodeling the BCR in response to autoreactivity can lead to the initiation of
clonal B cells that evolve to CLL by gathering genetic lesions. Moreover,
gene expression profiling studies with dnRAG1, Eµ-TCL1, and DTG mice
provide evidence of distinct but convergent pathways for CLL development.
However, the pathogenesis of murine CLL involves multiple factors including
potentially, prolactin-like hormones such a Prl2a1, and regulatory T cells.
Even though the role of the BCR in CLL is strongly suggested by the
significance of mutational status in clinical course among other factors, these
studies provide additional justification for considering the BCR signaling
pathway and its associated regulatory mechanisms as rational targets in CLL
treatment.
151
CHAPTER 5: REFERENCES
Agathangelidis, A., Darzentas, N., Hadzidimitriou, A., Brochet, X., Murray, F., Yan, X. J., . . . Stamatopoulos, K. (2012). Stereotyped B-cell receptors in one-third of chronic lymphocytic leukemia: a molecular classification with implications for targeted therapies. Blood, 119(19), 4467-4475. doi: 10.1182/blood-2011-11-393694
Aggarwal, M., Villuendas, R., Gomez, G., Rodriguez-Pinilla, S. M., Sanchez-
Beato, M., Alvarez, D., . . . Piris, M. A. (2009). TCL1A expression delineates biological and clinical variability in B-cell lymphoma. Mod Pathol, 22(2), 206-215. doi: 10.1038/modpathol.2008.148
Ahmed, S., Siddiqui, A. K., Rossoff, L., Sison, C. P., & Rai, K. R. (2003).
Pulmonary complications in chronic lymphocytic leukemia. Cancer, 98(9), 1912-1917. doi: 10.1002/cncr.11736
Ahuja, D., Sáenz-Robles, M. T., & Pipas, J. M. (2005). SV40 large T antigen
targets multiple cellular pathways to elicit cellular transformation. Oncogene, 24(52), 7729-7745. doi: 10.1038/sj.onc.1209046
Alegre, M. L., Frauwirth, K. A., & Thompson, C. B. (2001). T-cell regulation by
CD28 and CTLA-4. Nat Rev Immunol, 1(3), 220-228. doi: 10.1038/35105024
Amano, M., Baumgarth, N., Dick, M. D., Brossay, L., Kronenberg, M.,
Herzenberg, L. A., & Strober, S. (1998). CD1 expression defines subsets of follicular and marginal zone B cells in the spleen: beta 2-microglobulin-dependent and independent forms. J Immunol, 161(4), 1710-1717.
Anastasiadis, A., Kotsianidis, I., Papadopoulos, V., Spanoudakis, E.,
Margaritis, D., Christoforidou, A., . . . Tsatalas, C. (2013). CD1d expression as a prognostic marker for chronic lymphocytic leukemia. Leuk Lymphoma. doi: 10.3109/10428194.2013.803222
Anderson, M. A., Huang, D. C., & Roberts, A. W. (2013). BH3 mimetic
therapy: an emerging and promising approach to treating chronic lymphocytic leukemia. Leuk Lymphoma. doi: 10.3109/10428194.2013.769223
Andreeff, M., Darzynkiewicz, Z., Sharpless, T. K., Clarkson, B. D., &
Melamed, M. R. (1980). Discrimination of human leukemia subtypes by flow cytometric analysis of cellular DNA and RNA. Blood, 55(2), 282-293.
152
Arch, R. H., Gedrich, R. W., & Thompson, C. B. (1998). Tumor necrosis factor receptor-associated factors (TRAFs)--a family of adapter proteins that regulates life and death. Genes Dev, 12(18), 2821-2830.
Arechiga, A. F., Habib, T., He, Y., Zhang, X., Zhang, Z. Y., Funk, A., & Buckner, J. H. (2009). Cutting edge: the PTPN22 allelic variant associated with autoimmunity impairs B cell signaling. J Immunol, 182(6), 3343-3347. doi: 10.4049/jimmunol.0713370
Au-Yeung, B. B., Deindl, S., Hsu, L. Y., Palacios, E. H., Levin, S. E., Kuriyan,
J., & Weiss, A. (2009). The structure, regulation, and function of ZAP-70. Immunol Rev, 228(1), 41-57. doi: 10.1111/j.1600-065X.2008.00753.x
Azzam, H. S., DeJarnette, J. B., Huang, K., Emmons, R., Park, C. S.,
Sommers, C. L., . . . Love, P. E. (2001). Fine tuning of TCR signaling by CD5. J Immunol, 166(9), 5464-5472.
Ballow, M. (2002). Primary immunodeficiency disorders: antibody deficiency.
J Allergy Clin Immunol, 109(4), 581-591. Basten, A., & Silveira, P. A. (2010). B-cell tolerance: mechanisms and
implications. Curr Opin Immunol, 22(5), 566-574. doi: 10.1016/j.coi.2010.08.001
Bendelac, A., Bonneville, M., & Kearney, J. F. (2001). Autoreactivity by
design: innate B and T lymphocytes. Nat Rev Immunol, 1(3), 177-186. doi: 10.1038/35105052
Bennett, J. H. (1845). Case of hypertrophy of the spleen and liver, in which
death took place from suppuration of the blood. Edinburgh Medical and Surgical Journal, 64, 413-423.
Bennett, J. H. (1851). On leukocythemia, or blood containing an unusual
number of colourless corpuscles. Monthly Journal of Medical Sciences, 12, 17-38.
Bentz, M., Huck, K., du Manoir, S., Joos, S., Werner, C. A., Fischer, K., . . .
Lichter, P. (1995). Comparative genomic hybridization in chronic B-cell leukemias shows a high incidence of chromosomal gains and losses. Blood, 85(12), 3610-3618.
Berland, R., & Wortis, H. H. (2002). Origins and functions of B-1 cells with
notes on the role of CD5. Annu Rev Immunol, 20, 253-300. doi: 10.1146/annurev.immunol.20.100301.064833
Berland, R., & Wortis, H. H. (2003). Normal B-1a cell development requires B
153
cell-intrinsic NFATc1 activity. Proc Natl Acad Sci U S A, 100(23), 13459-13464. doi: 10.1073/pnas.2233620100
Bernal, A., Pastore, R. D., Asgary, Z., Keller, S. A., Cesarman, E., Liou, H.
C., & Schattner, E. J. (2001). Survival of leukemic B cells promoted by engagement of the antigen receptor. Blood, 98(10), 3050-3057.
Bertilaccio, M. T., Scielzo, C., Simonetti, G., Ponzoni, M., Apollonio, B., Fazi,
C., . . . Ghia, P. (2010). A novel Rag2-/-gammac-/--xenograft model of human CLL. Blood, 115(8), 1605-1609. doi: 10.1182/blood-2009-05-223586
Bertilaccio, M. T., Simonetti, G., Dagklis, A., Rocchi, M., Rodriguez, T. V.,
Apollonio, B., . . . Muzio, M. (2011). Lack of TIR8/SIGIRR triggers progression of chronic lymphocytic leukemia in mouse models. Blood, 118(3), 660-669. doi: 10.1182/blood-2011-01-329870
Best, C. G., Kemp, J. D., & J., W. T. (1995). Murine B-cell subsets defined by
CD23. Methods, 8(1), 3-10. Bhattacharya, N., Diener, S., Idler, I. S., Rauen, J., Häbe, S., Busch, H., . . .
Mertens, D. (2011). Nurse-like cells show deregulated expression of genes involved in immunocompetence. Br J Haematol, 154(3), 349-356. doi: 10.1111/j.1365-2141.2011.08747.x
Bichi, R., Shinton, S. A., Martin, E. S., Koval, A., Calin, G. A., Cesari, R., . . .
Croce, C. M. (2002). Human chronic lymphocytic leukemia modeled in mouse by targeted TCL1 expression. Proc Natl Acad Sci U S A, 99(10), 6955-6960. doi: 99/10/6955 [pii]10.1073/pnas.102181599
Bikah, G., Carey, J., Ciallella, J. R., Tarakhovsky, A., & Bondada, S. (1996).
CD5-mediated negative regulation of antigen receptor-induced growth signals in B-1 B cells. Science, 274(5294), 1906-1909.
Billard, C. (2012). Design of novel BH3 mimetics for the treatment of chronic
lymphocytic leukemia. Leukemia, 26(9), 2032-2038. doi: 10.1038/leu.2012.88
Binet, J. L., Auquier, A., Dighiero, G., Chastang, C., Piguet, H., Goasguen, J.,
. . . Gremy, F. (1981). A new prognostic classification of chronic lymphocytic leukemia derived from a multivariate survival analysis. Cancer, 48(1), 198-206.
Blair, A., Purdue, M. P., Weisenburger, D. D., & Baris, D. (2007). Chemical
exposures and risk of chronic lymphocytic leukaemia. Br J Haematol, 139(5), 753-761. doi: 10.1111/j.1365-2141.2007.06874.x
154
Boggs, D. R., Sofferman, S. A., Wintrobe, M. M., & Cartwright, G. E. (1966).
Factors influencing the duration of survival of patients with chronic lymphocytic leukemia. Am J Med, 40(2), 243-254.
Bonci, D., Coppola, V., Musumeci, M., Addario, A., Giuffrida, R., Memeo, L., . . . De Maria, R. (2008). The miR-15a-miR-16-1 cluster controls prostate cancer by targeting multiple oncogenic activities. Nat Med, 14(11), 1271-1277. doi: 10.1038/nm.1880
Bottini, N., Vang, T., Cucca, F., & Mustelin, T. (2006). Role of PTPN22 in
type 1 diabetes and other autoimmune diseases. Semin Immunol, 18(4), 207-213. doi: 10.1016/j.smim.2006.03.008
Bouchard, B., Ormandy, C. J., Di Santo, J. P., & Kelly, P. A. (1999). Immune
system development and function in prolactin receptor-deficient mice. J Immunol, 163(2), 576-582.
Bradley, J. R., & Pober, J. S. (2001). Tumor necrosis factor receptor-
associated factors (TRAFs). Oncogene, 20(44), 6482-6491. doi: 10.1038/sj.onc.1204788
Brusa, D., Serra, S., Coscia, M., Rossi, D., D'Arena, G., Laurenti, L., . . .
Deaglio, S. (2013). The PD-1/PD-L1 axis contributes to T cell dysfunction in chronic lymphocytic leukemia. Haematologica. doi: 0.3324/haematol.2012.077537
Bröker, B. M., Klajman, A., Youinou, P., Jouquan, J., Worman, C. P., Murphy,
J., . . . Collins, P. (1988). Chronic lymphocytic leukemic (CLL) cells secrete multispecific autoantibodies. J Autoimmun, 1(5), 469-481.
Buggins, A. G., & Pepper, C. J. (2010). The role of Bcl-2 family proteins in
chronic lymphocytic leukaemia. Leuk Res, 34(7), 837-842. doi: 10.1016/j.leukres.2010.03.011
Burger, J. A., Tsukada, N., Burger, M., Zvaifler, N. J., Dell'Aquila, M., &
Kipps, T. J. (2000). Blood-derived nurse-like cells protect chronic lymphocytic leukemia B cells from spontaneous apoptosis through stromal cell-derived factor-1. Blood, 96(8), 2655-2663.
Cai, G., & Freeman, G. J. (2009). The CD160, BTLA, LIGHT/HVEM pathway:
a bidirectional switch regulating T-cell activation. Immunol Rev, 229(1), 244-258. doi: 10.1111/j.1600-065X.2009.00783.x
Caligaris-Cappio, F. (1996). B-chronic lymphocytic leukemia: a malignancy of
anti-self B cells. Blood, 87(7), 2615-2620.
155
Caligaris-Cappio, F., Bertero, M. T., & Bergui, L. (1994). Autoimmunity, autoimmune diseases and lymphoproliferative disorders. Haematologica, 79(6), 487-492.
Caligaris-Cappio, F., Gobbi, M., Bofill, M., & Janossy, G. (1982). Infrequent normal B lymphocytes express features of B-chronic lymphocytic leukemia. J Exp Med, 155(2), 623-628.
Caligaris-Cappio, F., & Hamblin, T. J. (1999). B-cell chronic lymphocytic
leukemia: a bird of a different feather. J Clin Oncol, 17(1), 399-408. Calin, G. A., Dumitru, C. D., Shimizu, M., Bichi, R., Zupo, S., Noch, E., . . .
Croce, C. M. (2002). Frequent deletions and down-regulation of micro- RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc Natl Acad Sci U S A, 99(24), 15524-15529. doi: 10.1073/pnas.242606799
Campo, E., Swerdlow, S. H., Harris, N. L., Pileri, S., Stein, H., & Jaffe, E. S.
(2011). The 2008 WHO classification of lymphoid neoplasms and beyond: evolving concepts and practical applications. Blood, 117(19), 5019-5032. doi: 10.1182/blood-2011-01-293050
Carsetti, R., Rosado, M. M., & Wardmann, H. (2004). Peripheral development
of B cells in mouse and man. Immunol Rev, 197, 179-191. Catera, R., Silverman, G. J., Hatzi, K., Seiler, T., Didier, S., Zhang, L., . . .
Chiorazzi, N. (2008). Chronic lymphocytic leukemia cells recognize conserved epitopes associated with apoptosis and oxidation. Mol Med, 14(11-12), 665-674. doi: 10.2119/2008-00102.Catera
Catovsky, D., Richards, S., Matutes, E., Oscier, D., Dyer, M. J., Bezares, R.
F., . . . Group, N. C. L. L. W. (2007). Assessment of fludarabine plus cyclophosphamide for patients with chronic lymphocytic leukaemia (the LRF CLL4 Trial): a randomised controlled trial. Lancet, 370(9583), 230-239. doi: 10.1016/S0140-6736(07)61125-8
Cerutti, A., Cols, M., & Puga, I. (2013). Marginal zone B cells: virtues of
innate-like antibody-producing lymphocytes. Nat Rev Immunol, 13(2), 118-132. doi: 10.1038/nri3383
Chanan-Khan, A., Miller, K. C., Musial, L., Lawrence, D., Padmanabhan, S.,
Takeshita, K., . . . Czuczman, M. S. (2006). Clinical efficacy of lenalidomide in patients with relapsed or refractory chronic lymphocytic leukemia: results of a phase II study. J Clin Oncol, 24(34), 5343-5349. doi: 10.1200/JCO.2005.05.0401
Chen, S. S., Claus, R., Lucas, D. M., Yu, L., Qian, J., Ruppert, A. S., . . .
156
Byrd, J. C. (2011). Silencing of the inhibitor of DNA binding protein 4 (ID4) contributes to the pathogenesis of mouse and human CLL. Blood, 117(3), 862-871. doi: 10.1182/blood-2010-05-284638
Chen, S. S., Raval, A., Johnson, A. J., Hertlein, E., Liu, T. H., Jin, V. X., . . . Plass, C. (2009). Epigenetic changes during disease progression in a murine model of human chronic lymphocytic leukemia. Proc Natl Acad Sci U S A, 106(32), 13433-13438. doi: 10.1073/pnas.0906455106
Chen, W., Ford, M. S., Young, K. J., & Zhang, L. (2004). The role and
mechanisms of double negative regulatory T cells in the suppression of immune responses. Cell Mol Immunol, 1(5), 328-335.
Cheson, B. D. (2010). Monoclonal antibody therapy of chronic lymphocytic
leukaemia. Best Pract Res Clin Haematol, 23(1), 133-143. doi: 10.1016/j.beha.2010.01.006
Chiorazzi, N., & Ferrarini, M. (2003). B cell chronic lymphocytic leukemia:
lessons learned from studies of the B cell antigen receptor. Annu Rev Immunol, 21, 841-894. doi: 10.1146/annurev.immunol.21.120601.141018
Chiorazzi, N., & Ferrarini, M. (2011). Cellular origin(s) of chronic lymphocytic
leukemia: cautionary notes and additional considerations and possibilities. Blood, 117(6), 1781-1791. doi: 10.1182/blood-2010-07-155663
Chiorazzi, N., Fu, S. M., Montazeri, G., Kunkel, H. G., Rai, K., & Gee, T.
(1979). T cell helper defect in patients with chronic lymphocytic leukemia. J Immunol, 122(3), 1087-1090.
Chu, C. C., Catera, R., Zhang, L., Didier, S., Agagnina, B. M., Damle, R. N., .
. . Chiorazzi, N. (2010). Many chronic lymphocytic leukemia antibodies recognize apoptotic cells with exposed nonmuscle myosin heavy chain IIA: implications for patient outcome and cell of origin. Blood, 115(19), 3907-3915. doi: 10.1182/blood-2009-09-244251
Chung, J. B., Silverman, M., & Monroe, J. G. (2003). Transitional B cells: step
by step towards immune competence. Trends Immunol, 24(6), 343-349.
Chung, S. A., & Criswell, L. A. (2007). PTPN22: its role in SLE and
autoimmunity. Autoimmunity, 40(8), 582-590. doi: 10.1080/08916930701510848
Cimmino, A., Calin, G. A., Fabbri, M., Iorio, M. V., Ferracin, M., Shimizu, M., .
. . Croce, C. M. (2005). miR-15 and miR-16 induce apoptosis by
157
targeting BCL2. Proc Natl Acad Sci U S A, 102(39), 13944-13949. doi: 10.1073/pnas.0506654102
Clevenger, C. V., Freier, D. O., & Kline, J. B. (1998). Prolactin receptor signal
transduction in cells of the immune system. J Endocrinol, 157(2), 187-197.
Collins, R. J., Verschuer, L. A., Harmon, B. V., Prentice, R. L., Pope, J. H., &
Kerr, J. F. (1989). Spontaneous programmed death (apoptosis) of B-chronic lymphocytic leukaemia cells following their culture in vitro. Br J Haematol, 71(3), 343-350.
Colovic, N., Bogdanovic, A., Martinovic-Cemerikic, V., & Jankovic, G. (2001).
Prognostic significance of serum immunoglobulins in B-chronic lymphocytic leukemia. Archive of Oncology, 9(2), 79-82.
Cooper, M. D. (1987). Current concepts. B lymphocytes. Normal
development and function. N Engl J Med, 317(23), 1452-1456. doi: 10.1056/NEJM198712033172306
Crespo, M., Bosch, F., Villamor, N., Bellosillo, B., Colomer, D., Rozman, M., .
. . Montserrat, E. (2003). ZAP-70 expression as a surrogate for immunoglobulin-variable-region mutations in chronic lymphocytic leukemia. N Engl J Med, 348(18), 1764-1775. doi: 10.1056/NEJMoa023143
Crispín, J. C., Oukka, M., Bayliss, G., Cohen, R. A., Van Beek, C. A.,
Stillman, I. E., . . . Tsokos, G. C. (2008). Expanded double negative T cells in patients with systemic lupus erythematosus produce IL-17 and infiltrate the kidneys. J Immunol, 181(12), 8761-8766.
Cro, L., Morabito, F., Zucal, N., Fabris, S., Lionetti, M., Cutrona, G., . . .
Baldini, L. (2009). CD26 expression in mature B-cell neoplasia: its possible role as a new prognostic marker in B-CLL. Hematol Oncol, 27(3), 140-147. doi: 10.1002/hon.888
Crowther-Swanepoel, D., & Houlston, R. S. (2009). The molecular basis of
familial chronic lymphocytic leukemia. Haematologica, 94(5), 606-609. doi: 10.3324/haematol.2009.006296
Czarneski, J., Lin, Y. C., Chong, S., McCarthy, B., Fernandes, H., Parker, G.,
. . . Raveche, E. (2004). Studies in NZB IL-10 knockout mice of the requirement of IL-10 for progression of B-cell lymphoma. Leukemia, 18(3), 597-606. doi: 10.1038/sj.leu.2403244
D'Arena, G., Rossi, G., Vannata, B., Deaglio, S., Mansueto, G., D'Auria, F., . .
158
. Musto, P. (2012). Regulatory T-Cells in Chronic Lymphocytic Leukemia and Autoimmune Diseases. Mediterr J Hematol Infect Dis, 4(1), e2012053. doi: 10.4084/MJHID.2012.053
Dai, X., James, R. G., Habib, T., Singh, S., Jackson, S., Khim, S., . . .
Rawlings, D. J. (2013). A disease-associated PTPN22 variant promotes systemic autoimmunity in murine models. J Clin Invest, 123(5), 2024-2036. doi: 10.1172/JCI66963
Dameshek, W. (1967). Chronic lymphocytic leukemia--an accumulative
disease of immunologically incompetent lymphocytes. Blood, 29(4), Suppl:566-584.
Damle, R. N., Ghiotto, F., Valetto, A., Albesiano, E., Fais, F., Yan, X. J., . . .
Chiorazzi, N. (2002). B-cell chronic lymphocytic leukemia cells express a surface membrane phenotype of activated, antigen-experienced B lymphocytes. Blood, 99(11), 4087-4093.
Damle, R. N., Wasil, T., Fais, F., Ghiotto, F., Valetto, A., Allen, S. L., . . .
Chiorazzi, N. (1999). Ig V gene mutation status and CD38 expression as novel prognostic indicators in chronic lymphocytic leukemia. Blood, 94(6), 1840-1847.
Deaglio, S., Capobianco, A., Bergui, L., Dürig, J., Morabito, F., Dührsen, U.,
& Malavasi, F. (2003). CD38 is a signaling molecule in B-cell chronic lymphocytic leukemia cells. Blood, 102(6), 2146-2155. doi: 10.1182/blood-2003-03-0989
Dearden, C. (2008). Disease-specific complications of chronic lymphocytic
leukemia. Hematology Am Soc Hematol Educ Program, 450-456. doi: 10.1182/asheducation-2008.1.450
Descatoire, M., Weill, J. C., Reynaud, C. A., & Weller, S. (2011). A human
equivalent of mouse B-1 cells? J Exp Med, 208(13), 2563-2564; author reply 2566-2569. doi: 10.1084/jem.20112232
Di Bernardo, M. C., Crowther-Swanepoel, D., Broderick, P., Webb, E.,
Sellick, G., Wild, R., . . . Houlston, R. S. (2008). A genome-wide association study identifies six susceptibility loci for chronic lymphocytic leukemia. Nat Genet, 40(10), 1204-1210. doi: 10.1038/ng.219
Di Noia, J. M., & Neuberger, M. S. (2007). Molecular mechanisms of antibody
somatic hypermutation. Annu Rev Biochem, 76, 1-22. doi: 10.1146/annurev.biochem.76.061705.090740
159
Dighiero, G., & Hamblin, T. J. (2008). Chronic lymphocytic leukaemia. Lancet, 371(9617), 1017-1029. doi: 10.1016/S0140-6736(08)60456-0
Dighiero, G., Maloum, K., Desablens, B., Cazin, B., Navarro, M., Leblay, R., .
. . Travade, P. (1998). Chlorambucil in indolent chronic lymphocytic leukemia. French Cooperative Group on Chronic Lymphocytic Leukemia. N Engl J Med, 338(21), 1506-1514. doi: 10.1056/NEJM199805213382104
DiLillo, D. J., Matsushita, T., & Tedder, T. F. (2010). B10 cells and regulatory B cells balance immune responses during inflammation, autoimmunity, and cancer. Ann N Y Acad Sci, 1183, 38-57. doi: 10.1111/j.1749-6632.2009.05137.x
DiLillo, D. J., Weinberg, J. B., Yoshizaki, A., Horikawa, M., Bryant, J. M.,
Iwata, Y., . . . Tedder, T. F. (2013). Chronic lymphocytic leukemia and regulatory B cells share IL-10 competence and immunosuppressive function. Leukemia, 27(1), 170-182. doi: 10.1038/leu.2012.165
Ding, C., Liu, Y., Wang, Y., Park, B. K., Wang, C. Y., & Zheng, P. (2007).
Siglecg limits the size of B1a B cell lineage by down-regulating NFkappaB activation. PLoS One, 2(10), e997. doi: 10.1371/journal.pone.0000997
Dono, M., Cerruti, G., & Zupo, S. (2004). The CD5+ B-cell. Int J Biochem Cell
Biol, 36(11), 2105-2111. doi: 10.1016/j.biocel.2004.05.017 Dores, G. M., Anderson, W. F., Curtis, R. E., Landgren, O., Ostroumova, E.,
Bluhm, E. C., . . . Linet, M. S. (2007). Chronic lymphocytic leukaemia and small lymphocytic lymphoma: overview of the descriptive epidemiology. Br J Haematol, 139(5), 809-819. doi: 10.1111/j.1365-2141.2007.06856.x
Dorshkind, K., & Horseman, N. D. (2000). The roles of prolactin, growth
hormone, insulin-like growth factor-I, and thyroid hormones in lymphocyte development and function: insights from genetic models of hormone and hormone receptor deficiency. Endocr Rev, 21(3), 292-312.
Döhner, H., Fischer, K., Bentz, M., Hansen, K., Benner, A., Cabot, G., . . .
Stilgenbauer, S. (1995). p53 gene deletion predicts for poor survival and non-response to therapy with purine analogs in chronic B-cell leukemias. Blood, 85(6), 1580-1589.
Döhner, H., Stilgenbauer, S., Benner, A., Leupolt, E., Kröber, A., Bullinger, L.,
. . . Lichter, P. (2000). Genomic aberrations and survival in chronic lymphocytic leukemia. N Engl J Med, 343(26), 1910-1916. doi:
160
10.1056/NEJM200012283432602 Döhner, H., Stilgenbauer, S., James, M. R., Benner, A., Weilguni, T., Bentz,
M., . . . Lichter, P. (1997). 11q deletions identify a new subset of B-cell chronic lymphocytic leukemia characterized by extensive nodal involvement and inferior prognosis. Blood, 89(7), 2516-2522.
Dühren-von Minden, M., Übelhart, R., Schneider, D., Wossning, T., Bach, M.
P., Buchner, M., . . . Jumaa, H. (2012). Chronic lymphocytic leukaemia is driven by antigen-independent cell-autonomous signalling. Nature, 489(7415), 309-312. doi: 10.1038/nature11309
Dürig, J., Nückel, H., Cremer, M., Führer, A., Halfmeyer, K., Fandrey, J., . . . Dührsen, U. (2003). ZAP-70 expression is a prognostic factor in chronic lymphocytic leukemia. Leukemia, 17(12), 2426-2434. doi: 10.1038/sj.leu.2403147
Early, P., Huang, H., Davis, M., Calame, K., & Hood, L. (1980). An
immunoglobulin heavy chain variable region gene is generated from three segments of DNA: VH, D and JH. Cell, 19(4), 981-992.
Ehrlich, P. (1891). Farbenanalytische Untersuchungen Zur Histologie und
Klinik Des Blutes. Hirschwald, Berlin. Endo, T., Nishio, M., Enzler, T., Cottam, H. B., Fukuda, T., James, D. F., . . .
Kipps, T. J. (2007). BAFF and APRIL support chronic lymphocytic leukemia B-cell survival through activation of the canonical NF-kappaB pathway. Blood, 109(2), 703-710. doi: 10.1182/blood-2006-06-027755
Enjalbert, A., Sladeczek, F., Guillon, G., Bertrand, P., Shu, C., Epelbaum, J.,
. . . Kordon, C. (1986). Angiotensin II and dopamine modulate both cAMP and inositol phosphate productions in anterior pituitary cells. Involvement in prolactin secretion. J Biol Chem, 261(9), 4071-4075.
Enno, A., Catovsky, D., O'Brien, M., Cherchi, M., Kumaran, T. O., & Galton,
D. A. (1979). 'Prolymphocytoid' transformation of chronic lymphocytic leukaemia. Br J Haematol, 41(1), 9-18.
Enzler, T., Kater, A. P., Zhang, W., Widhopf, G. F., Chuang, H. Y., Lee, J., . .
. Kipps, T. J. (2009). Chronic lymphocytic leukemia of Emu-TCL1 transgenic mice undergoes rapid cell turnover that can be offset by extrinsic CD257 to accelerate disease progression. Blood, 114(20), 4469-4476. doi: 10.1182/blood-2009-06-230169
Fais, F., Ghiotto, F., Hashimoto, S., Sellars, B., Valetto, A., Allen, S. L., . . .
Chiorazzi, N. (1998). Chronic lymphocytic leukemia B cells express restricted sets of mutated and unmutated antigen receptors. J Clin
161
Invest, 102(8), 1515-1525. doi: 10.1172/JCI3009 Fais, F., Morabito, F., Stelitano, C., Callea, V., Zanardi, S., Scudeletti, M., . . .
Grossi, C. E. (2004). CD1d is expressed on B-chronic lymphocytic leukemia cells and mediates alpha-galactosylceramide presentation to natural killer T lymphocytes. Int J Cancer, 109(3), 402-411. doi: 10.1002/ijc.11723
Farace, F., Orlanducci, F., Dietrich, P. Y., Gaudin, C., Angevin, E., Courtier,
M. H., . . . Triebel, F. (1994). T cell repertoire in patients with B chronic lymphocytic leukemia. Evidence for multiple in vivo T cell clonal expansions. J Immunol, 153(9), 4281-4290.
Fazi, C., Scarfò, L., Pecciarini, L., Cottini, F., Dagklis, A., Janus, A., . . . Ghia,
P. (2011). General population low-count CLL-like MBL persists over time without clinical progression, although carrying the same cytogenetic abnormalities of CLL. Blood, 118(25), 6618-6625. doi: 10.1182/blood-2011-05-357251
Fecteau, J. F., & Kipps, T. J. (2012). Structure and function of the
hematopoietic cancer niche: focus on chronic lymphocytic leukemia. Front Biosci (Schol Ed), 4, 61-73.
Ferrajoli, A., Lee, B. N., Schlette, E. J., O'Brien, S. M., Gao, H., Wen, S., . . .
Keating, M. J. (2008). Lenalidomide induces complete and partial remissions in patients with relapsed and refractory chronic lymphocytic leukemia. Blood, 111(11), 5291-5297. doi: 10.1182/blood-2007-12-130120
Finch, S. C., Hoshino, T., Itoga, T., Ichimaru, M., & Ingram, R. H. (1969).
Chronic lymphocytic leukemia in Hiroshima and Nagasaki, Japan. Blood, 33(1), 79-86.
Ford, M. S., Zhang, Z. X., Chen, W., & Zhang, L. (2006). Double-negative T
regulatory cells can develop outside the thymus and do not mature from CD8+ T cell precursors. J Immunol, 177(5), 2803-2809.
Foucar, K., & Rydell, R. E. (1980). Richter's syndrome in chronic lymphocytic
leukemia. Cancer, 46(1), 118-134. Freeman, M. E., Kanyicska, B., Lerant, A., & Nagy, G. (2000). Prolactin:
structure, function, and regulation of secretion. Physiol Rev, 80(4), 1523-1631.
Galton, D. A. (1966). The pathogenesis of chronic lymphocytic leukemia. Can
Med Assoc J, 94(19), 1005-1010.
162
Galton, D. A., Wiltshaw, E., Szur, L., & Dacie, J. V. (1961). The use of
chlorambucil and steroids in the treatment of chronic lymphocytic leukaemia. Br J Haematol, 7, 73-98.
Gary-Gouy, H., Harriague, J., Bismuth, G., Platzer, C., Schmitt, C., & Dalloul,
A. H. (2002). Human CD5 promotes B-cell survival through stimulation of autocrine IL-10 production. Blood, 100(13), 4537-4543. doi: 10.1182/blood-2002-05-1525
Garzon, R., Calin, G. A., & Croce, C. M. (2009). MicroRNAs in Cancer. Annu
Rev Med, 60, 167-179. doi: 10.1146/annurev.med.59.053006.104707 Gaudio, E., Spizzo, R., Paduano, F., Luo, Z., Efanov, A., Palamarchuk, A., . .
. Croce, C. M. (2012). Tcl1 interacts with Atm and enhances NF-κB activation in hematologic malignancies. Blood, 119(1), 180-187. doi: 10.1182/blood-2011-08-374561
Gellert, M. (2002). V(D)J recombination: RAG proteins, repair factors, and
regulation. Annu Rev Biochem, 71, 101-132. doi: 10.1146/annurev.biochem.71.090501.150203
Gerstein, R. M., & Lieber, M. R. (1993). Extent to which homology can
constrain coding exon junctional diversity in V(D)J recombination. Nature, 363(6430), 625-627. doi: 10.1038/363625a0
Ghani, A. M., Krause, J. R., & Brody, J. P. (1986). Prolymphocytic
transformation of chronic lymphocytic leukemia. A report of three cases and review of the literature. Cancer, 57(1), 75-80.
Ghia, E. M., Jain, S., Widhopf, G. F., Rassenti, L. Z., Keating, M. J., Wierda,
W. G., . . . Kipps, T. J. (2008). Use of IGHV3-21 in chronic lymphocytic leukemia is associated with high-risk disease and reflects antigen-driven, post-germinal center leukemogenic selection. Blood, 111(10), 5101-5108. doi: 10.1182/blood-2007-12-130229
Ghia, P., Strola, G., Granziero, L., Geuna, M., Guida, G., Sallusto, F., . . .
Caligaris-Cappio, F. (2002). Chronic lymphocytic leukemia B cells are endowed with the capacity to attract CD4+, CD40L+ T cells by producing CCL22. Eur J Immunol, 32(5), 1403-1413. doi: 10.1002/1521-4141(200205)32:5<1403::AID-IMMU1403>3.0.CO;2-Y
Ghia, P., ten Boekel, E., Rolink, A. G., & Melchers, F. (1998). B-cell
development: a comparison between mouse and man. Immunol Today, 19(10), 480-485.
163
Ghiotto, F., Fais, F., Valetto, A., Albesiano, E., Hashimoto, S., Dono, M., . . . Chiorazzi, N. (2004). Remarkably similar antigen receptors among a subset of patients with chronic lymphocytic leukemia. J Clin Invest, 113(7), 1008-1016. doi: 10.1172/JCI19399
Ghosn, E. E., Yamamoto, R., Hamanaka, S., Yang, Y., Herzenberg, L. A., &
Nakauchi, H. (2012). Distinct B-cell lineage commitment distinguishes adult bone marrow hematopoietic stem cells. Proc Natl Acad Sci U S A, 109(14), 5394-5398. doi: 10.1073/pnas.1121632109
Gilling, C. E., Mittal, A. K., Chaturvedi, N. K., Iqbal, J., Aoun, P., Bierman, P.
J., . . . Joshi, S. S. (2012). Lymph node-induced immune tolerance in chronic lymphocytic leukaemia: a role for caveolin-1. Br J Haematol, 158(2), 216-231. doi: 10.1111/j.1365-2141.2012.09148.x
Girschick, H. J., Grammer, A. C., Nanki, T., Mayo, M., & Lipsky, P. E. (2001).
RAG1 and RAG2 expression by B cell subsets from human tonsil and peripheral blood. J Immunol, 166(1), 377-386.
Glanville, J., Zhai, W., Berka, J., Telman, D., Huerta, G., Mehta, G. R., . . .
Pons, J. (2009). Precise determination of the diversity of a combinatorial antibody library gives insight into the human immunoglobulin repertoire. Proc Natl Acad Sci U S A, 106(48), 20216-20221. doi: 10.1073/pnas.0909775106
Nadgornaya, V., Zavelevich, M., & Machilo, V. (2006). Patterns of
hematological malignancies in Chernobyl clean-up workers (1996-2005). Exp Oncol, 28(1), 60-63.
Godfrey, D. I., & Kronenberg, M. (2004). Going both ways: immune regulation
via CD1d-dependent NKT cells. J Clin Invest, 114(10), 1379-1388. doi: 10.1172/JCI23594
Godfrey, D. I., Stankovic, S., & Baxter, A. G. (2010). Raising the NKT cell
family. Nat Immunol, 11(3), 197-206. doi: 10.1038/ni.1841 Goffin, V., Shiverick, K. T., Kelly, P. A., & Martial, J. A. (1996). Sequence-
function relationships within the expanding family of prolactin, growth hormone, placental lactogen, and related proteins in mammals. Endocr Rev, 17(4), 385-410.
Goodnow, C. C. (1997). Balancing immunity, autoimmunity, and self-
tolerance. Ann N Y Acad Sci, 815, 55-66. Goodnow, C. C. (2001). Pathways for self-tolerance and the treatment of
autoimmune diseases. Lancet, 357(9274), 2115-2121.
164
Goodnow, C. C., Sprent, J., Fazekas de St Groth, B., & Vinuesa, C. G.
(2005). Cellular and genetic mechanisms of self tolerance and autoimmunity. Nature, 435(7042), 590-597. doi: 10.1038/nature03724
Gorgun, G., Ramsay, A. G., Holderried, T. A., Zahrieh, D., Le Dieu, R., Liu,
F., . . . Gribben, J. G. (2009). E(mu)-TCL1 mice represent a model for immunotherapeutic reversal of chronic lymphocytic leukemia-induced T-cell dysfunction. Proc Natl Acad Sci U S A, 106(15), 6250-6255. doi: 10.1073/pnas.0901166106
Gribben, J. G., & O'Brien, S. (2011). Update on therapy of chronic
lymphocytic leukemia. J Clin Oncol, 29(5), 544-550. doi: 10.1200/JCO.2010.32.3865
Griffin, D. O., Holodick, N. E., & Rothstein, T. L. (2011). Human B1 cells in
umbilical cord and adult peripheral blood express the novel phenotype CD20+ CD27+ CD43+ CD70-. J Exp Med, 208(1), 67-80. doi: 10.1084/jem.20101499
Griffin, O. D., Quach, T., Batliwalla, F., Andreopoulos, D., Holodick, N. E., &
Rothstein, T. L. (2012). Human CD11b+ B1 cells are not monocytes: a reply to "gene profiling of CD11b+ and CD11b- B1 cell subsets reveals potential cell sorting artifacts". J Exp Med, 209(3), 434-436.
Guarini, A., Chiaretti, S., Tavolaro, S., Maggio, R., Peragine, N., Citarella, F.,
. . . Foà, R. (2008). BCR ligation induced by IgM stimulation results in gene expression and functional changes only in IgV H unmutated chronic lymphocytic leukemia (CLL) cells. Blood, 112(3), 782-792. doi: 10.1182/blood-2007-12-127688
Gumperz, J. E., Miyake, S., Yamamura, T., & Brenner, M. B. (2002).
Functionally distinct subsets of CD1d-restricted natural killer T cells revealed by CD1d tetramer staining. J Exp Med, 195(5), 625-636.
Gutiérrez, M. A., Molina, J. F., Jara, L. J., Cuéllar, M. L., García, C.,
Gutiérrez-Ureña, S., . . . Espinoza, L. R. (1995). Prolactin and systemic lupus erythematosus: prolactin secretion by SLE lymphocytes and proliferative (autocrine) activity. Lupus, 4(5), 348-352.
Görgün, G., Holderried, T. A., Zahrieh, D., Neuberg, D., & Gribben, J. G.
(2005). Chronic lymphocytic leukemia cells induce changes in gene expression of CD4 and CD8 T cells. J Clin Invest, 115(7), 1797-1805. doi: 10.1172/JCI24176
165
Hahne, M., Kataoka, T., Schröter, M., Hofmann, K., Irmler, M., Bodmer, J. L., . . . Tschopp, J. (1998). APRIL, a new ligand of the tumor necrosis factor family, stimulates tumor cell growth. J Exp Med, 188(6), 1185-1190.
Hallek, M. (2010). Therapy of chronic lymphocytic leukaemia. Best Pract Res
Clin Haematol, 23(1), 85-96. doi: 10.1016/j.beha.2009.12.002 Hallek, M., Cheson, B. D., Catovsky, D., Caligaris-Cappio, F., Dighiero, G.,
Döhner, H., . . . Leukemia, I. W. o. C. L. (2008). Guidelines for the diagnosis and treatment of chronic lymphocytic leukemia: a report from the International Workshop on Chronic Lymphocytic Leukemia updating the National Cancer Institute-Working Group 1996 guidelines. Blood, 111(12), 5446-5456. doi: 10.1182/blood-2007-06-093906
Hamano, Y., Hirose, S., Ida, A., Abe, M., Zhang, D., Kodera, S., . . . Shirai, T.
(1998). Susceptibility alleles for aberrant B-1 cell proliferation involved in spontaneously occurring B-cell chronic lymphocytic leukemia in a model of New Zealand white mice. Blood, 92(10), 3772-3779.
Hamblin, T. (2000). Historical aspects of chronic lymphocytic leukaemia. Br J
Haematol, 111(4), 1023-1034. Hamblin, T. (2006). Is chronic lymphocytic leukemia a response to infectious
agents? Leuk Res, 30(9), 1063-1064. doi: 10.1016/j.leukres.2005.11.022
Hamblin, T. J., Davis, Z., Gardiner, A., Oscier, D. G., & Stevenson, F. K.
(1999). Unmutated Ig V(H) genes are associated with a more aggressive form of chronic lymphocytic leukemia. Blood, 94(6), 1848-1854.
Hamblin, T. J., Orchard, J. A., Ibbotson, R. E., Davis, Z., Thomas, P. W.,
Stevenson, F. K., & Oscier, D. G. (2002). CD38 expression and immunoglobulin variable region mutations are independent prognostic variables in chronic lymphocytic leukemia, but CD38 expression may vary during the course of the disease. Blood, 99(3), 1023-1029.
Han, Y., Wu, J., Bi, L., Xiong, S., Gao, S., Yin, L., . . . Zhang, S. (2011).
Malignant B cells induce the conversion of CD4+CD25- T cells to regulatory T cells in B-cell non-Hodgkin lymphoma. PLoS One, 6(12), e28649. doi: 10.1371/journal.pone.0028649
Han, Y. C., Park, C. Y., Bhagat, G., Zhang, J., Wang, Y., Fan, J. B., . . . Gu,
H. (2010). microRNA-29a induces aberrant self-renewal capacity in
166
hematopoietic progenitors, biased myeloid development, and acute myeloid leukemia. J Exp Med, 207(3), 475-489. doi: 10.1084/jem.20090831
Hanada, M., Delia, D., Aiello, A., Stadtmauer, E., & Reed, J. C. (1993). bcl-2
gene hypomethylation and high-level expression in B-cell chronic lymphocytic leukemia. Blood, 82(6), 1820-1828.
Hardy, R. R. (2006). B-1 B cell development. J Immunol, 177(5), 2749-2754. Hardy, R. R., & Hayakawa, K. (2001). B cell development pathways. Annu
Rev Immunol, 19, 595-621. doi: 10.1146/annurev.immunol.19.1.595 Hardy, R. R., Kincade, P. W., & Dorshkind, K. (2007). The protean nature of
cells in the B lymphocyte lineage. Immunity, 26(6), 703-714. doi: 10.1016/j.immuni.2007.05.013
Harris, N. L., Jaffe, E. S., Diebold, J., Flandrin, G., Muller-Hermelink, H. K.,
Vardiman, J., . . . Bloomfield, C. D. (1999). World Health Organization classification of neoplastic diseases of the hematopoietic and lymphoid tissues: report of the Clinical Advisory Committee meeting-Airlie House, Virginia, November 1997. J Clin Oncol, 17(12), 3835-3849.
Hartkamp, A., Mulder, A. H., Rijkers, G. T., van Velzen-Blad, H., & Biesma,
D. H. (2001). Antibody responses to pneumococcal and haemophilus vaccinations in patients with B-cell chronic lymphocytic leukaemia. Vaccine, 19(13-14), 1671-1677.
Haslinger, C., Schweifer, N., Stilgenbauer, S., Döhner, H., Lichter, P., Kraut,
N., . . . Abseher, R. (2004). Microarray gene expression profiling of B-cell chronic lymphocytic leukemia subgroups defined by genomic aberrations and VH mutation status. J Clin Oncol, 22(19), 3937-3949. doi: 10.1200/JCO.2004.12.133
Hassaballa, A. E., Palmer, V. L., Anderson, D. K., Kassmeier, M. D., Nganga,
V. K., Parks, K. W., . . . Swanson, P. C. (2011). Accumulation of B1-like B cells in transgenic mice over-expressing catalytically inactive RAG1 in the periphery. Immunology, 134(4), 469-486. doi: 10.1111/j.1365-2567.2011.03509.x
Hayakawa, K., Asano, M., Shinton, S. A., Gui, M., Wen, L. J., Dashoff, J., &
Hardy, R. R. (2003). Positive selection of anti-thy-1 autoreactive B-1 cells and natural serum autoantibody production independent from bone marrow B cell development. J Exp Med, 197(1), 87-99.
Hayakawa, K., Hardy, R. R., Parks, D. R., & Herzenberg, L. A. (1983). The
167
"Ly-1 B" cell subpopulation in normal immunodefective, and autoimmune mice. J Exp Med, 157(1), 202-218.
Heintel, D., Kienle, D., Shehata, M., Kröber, A., Kroemer, E., Schwarzinger,
I., . . . Group, C. S. (2005). High expression of lipoprotein lipase in poor risk B-cell chronic lymphocytic leukemia. Leukemia, 19(7), 1216-1223. doi: 10.1038/sj.leu.2403748
Helyer, B. J., & Howie, J. B. (1963). Renal disease associated with positive
lupus erythematosus tests in a cross-bred strain of mice. Nature, 197, 197.
Heng, T. S., Painter, M. W., & Consortium, I. G. P. (2008). The
Immunological Genome Project: networks of gene expression in immune cells. Nat Immunol, 9(10), 1091-1094. doi: 10.1038/ni1008-1091
Herling, M., Patel, K. A., Hsi, E. D., Chang, K. C., Rassidakis, G. Z., Ford, R.,
& Jones, D. (2007). TCL1 in B-cell tumors retains its normal b-cell pattern of regulation and is a marker of differentiation stage. Am J Surg Pathol, 31(7), 1123-1129. doi: 10.1097/PAS.0b013e31802e2201
Herling, M., Patel, K. A., Khalili, J., Schlette, E., Kobayashi, R., Medeiros, L.
J., & Jones, D. (2006). TCL1 shows a regulated expression pattern in chronic lymphocytic leukemia that correlates with molecular subtypes and proliferative state. Leukemia, 20(2), 280-285. doi: 10.1038/sj.leu.2404017
Herman, S. E., & Johnson, A. J. (2012). Molecular pathways: targeting
phosphoinositide 3-kinase p110-delta in chronic lymphocytic leukemia. Clin Cancer Res, 18(15), 4013-4018. doi: 10.1158/1078-0432.CCR-11-1402
Herreros, B., Rodríguez-Pinilla, S. M., Pajares, R., Martínez-Gónzalez, M. A.,
Ramos, R., Munoz, I., . . . Piris, M. A. (2010). Proliferation centers in chronic lymphocytic leukemia: the niche where NF-kappaB activation takes place. Leukemia, 24(4), 872-876. doi: 10.1038/leu.2009.285
Herrinton, L. J., Goldoft, M., Schwartz, S. M., & Weiss, N. S. (1996). The
incidence of non-Hodgkin's lymphoma and its histologic subtypes in Asian migrants to the United States and their descendants. Cancer Causes Control, 7(2), 224-230.
Herrmann, F., Lochner, A., Philippen, H., Jauer, B., & Rühl, H. (1982).
Imbalance of T cell subpopulations in patients with chronic lymphocytic leukaemia of the B cell type. Clin Exp Immunol, 49(1), 157-162.
168
Hervé, M., Xu, K., Ng, Y. S., Wardemann, H., Albesiano, E., Messmer, B. T.,
. . . Meffre, E. (2005). Unmutated and mutated chronic lymphocytic leukemias derive from self-reactive B cell precursors despite expressing different antibody reactivity. J Clin Invest, 115(6), 1636-1643. doi: 10.1172/JCI24387
Hiestand, P. C., Mekler, P., Nordmann, R., Grieder, A., & Permmongkol, C.
(1986). Prolactin as a modulator of lymphocyte responsiveness provides a possible mechanism of action for cyclosporine. Proc Natl Acad Sci U S A, 83(8), 2599-2603.
Hillion, S., Saraux, A., Youinou, P., & Jamin, C. (2005). Expression of RAGs
in peripheral B cells outside germinal centers is associated with the expression of CD5. J Immunol, 174(9), 5553-5561.
Hippen, K. L., Tze, L. E., & Behrens, T. W. (2000). CD5 maintains tolerance
in anergic B cells. J Exp Med, 191(5), 883-890. Hisada, M., Biggar, R. J., Greene, M. H., Fraumeni, J. F., & Travis, L. B.
(2001). Solid tumors after chronic lymphocytic leukemia. Blood, 98(6), 1979-1981.
Hitoshi, Y., Yamaguchi, N., Mita, S., Sonoda, E., Takaki, S., Tominaga, A., &
Takatsu, K. (1990). Distribution of IL-5 receptor-positive B cells. Expression of IL-5 receptor on Ly-1(CD5)+ B cells. J Immunol, 144(11), 4218-4225.
Hockenbery, D., Nuñez, G., Milliman, C., Schreiber, R. D., & Korsmeyer, S. J.
(1990). Bcl-2 is an inner mitochondrial membrane protein that blocks programmed cell death. Nature, 348(6299), 334-336. doi: 10.1038/348334a0
Hodgkin. (1832). On some Morbid Appearances of the Absorbent Glands and
Spleen. Med Chir Trans, 17, 68-114. Hodgson, K., Ferrer, G., Montserrat, E., & Moreno, C. (2011). Chronic
lymphocytic leukemia and autoimmunity: a systematic review. Haematologica, 96(5), 752-761. doi: 10.3324/haematol.2010.036152
Hodgson, K., Ferrer, G., Pereira, A., Moreno, C., & Montserrat, E. (2011).
Autoimmune cytopenia in chronic lymphocytic leukaemia: diagnosis and treatment. Br J Haematol, 154(1), 14-22. doi: 10.1111/j.1365-2141.2011.08707.x
Hoellenriegel, J., Meadows, S. A., Sivina, M., Wierda, W. G., Kantarjian, H.,
169
Keating, M. J., . . . Burger, J. A. (2011). The phosphoinositide 3'-kinase delta inhibitor, CAL-101, inhibits B-cell receptor signaling and chemokine networks in chronic lymphocytic leukemia. Blood, 118(13), 3603-3612. doi: 10.1182/blood-2011-05-352492
Hofbauer, J. P., Heyder, C., Denk, U., Kocher, T., Holler, C., Trapin, D., . . .
Egle, A. (2011). Development of CLL in the TCL1 transgenic mouse model is associated with severe skewing of the T-cell compartment homologous to human CLL. Leukemia, 25(9), 1452-1458. doi: 10.1038/leu.2011.111
Hoffmann, A., Kerr, S., Jellusova, J., Zhang, J., Weisel, F., Wellmann, U., . . .
Nitschke, L. (2007). Siglec-G is a B1 cell-inhibitory receptor that controls expansion and calcium signaling of the B1 cell population. Nat Immunol, 8(7), 695-704. doi: 10.1038/ni1480
Holler, C., Piñón, J. D., Denk, U., Heyder, C., Hofbauer, S., Greil, R., & Egle,
A. (2009). PKCbeta is essential for the development of chronic lymphocytic leukemia in the TCL1 transgenic mouse model: validation of PKCbeta as a therapeutic target in chronic lymphocytic leukemia. Blood, 113(12), 2791-2794. doi: 10.1182/blood-2008-06-160713
Howlader, N., Noone, A., Krapcho, M., Neyman, N., Aminou, R., Waldron,
W., . . . Cronin, K. (2012). SEER Cancer Statistics Review, 1975-2009 (Vintage 2009 Populations). Retrieved 9-4-12, 2012, from http://seer.cancer.gov/csr/1975_2009_pops09/
Hoyer, K. K., French, S. W., Turner, D. E., Nguyen, M. T., Renard, M.,
Malone, C. S., . . . Teitell, M. A. (2002). Dysregulated TCL1 promotes multiple classes of mature B cell lymphoma. Proc Natl Acad Sci U S A, 99(22), 14392-14397. doi: 10.1073/pnas.212410199
Hsu, W. L., Preston, D. L., Soda, M., Sugiyama, H., Funamoto, S., Kodama,
K., . . . Mabuchi, K. (2013). The Incidence of Leukemia, Lymphoma and Multiple Myeloma among Atomic Bomb Survivors: 1950-2001. Radiat Res. doi: 10.1667/RR2892.1
Hummel, J. L., Lichty, B. D., Reis, M., Dubé, I., & Kamel-Reid, S. (1996).
Engraftment of human chronic lymphocytic leukemia cells in SCID mice: in vivo and in vitro studies. Leukemia, 10(8), 1370-1376.
Irizarry, R. A., Hobbs, B., Collin, F., Beazer-Barclay, Y. D., Antonellis, K. J.,
Scherf, U., & Speed, T. P. (2003). Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics, 4(2), 249-264. doi: 10.1093/biostatistics/4.2.249
170
Irizarry, R. A., Wu, Z., & Jaffee, H. A. (2006). Comparison of Affymetrix GeneChip expression measures. Bioinformatics, 22(7), 789-794. doi: 10.1093/bioinformatics/btk046
Itälä, M., Helenius, H., Nikoskelainen, J., & Remes, K. (1992). Infections and
serum IgG levels in patients with chronic lymphocytic leukemia. Eur J Haematol, 48(5), 266-270.
Jadidi-Niaragh, F., Jeddi-Tehrani, M., Ansaripour, B., Razavi, S. M.,
Sharifian, R. A., & Shokri, F. (2012). Reduced frequency of NKT-like cells in patients with progressive chronic lymphocytic leukemia. Med Oncol, 29(5), 3561-3569. doi: 10.1007/s12032-012-0262-4
Jaffe, E. S., Harris, N.L., Stein, H. & Vardiman, J.W. (eds.). (2001). World
Health Organization classification of tumours: pathology and genetics of tumours of haematopoietic and lymphoid tissues. Lyon: IARC Press.
Jaglowski, S. M., Alinari, L., Lapalombella, R., Muthusamy, N., & Byrd, J. C.
(2010). The clinical application of monoclonal antibodies in chronic lymphocytic leukemia. Blood, 116(19), 3705-3714. doi: 10.1182/blood-2010-04-001230
Jaglowski, S. M., & Byrd, J. C. (2012). Novel therapies and their integration
into allogeneic stem cell transplant for chronic lymphocytic leukemia. Biol Blood Marrow Transplant, 18(1 Suppl), S132-138. doi: 10.1016/j.bbmt.2011.11.018
Jak, M., Mous, R., Remmerswaal, E. B., Spijker, R., Jaspers, A., Yagüe, A., .
. . Van Oers, M. H. (2009). Enhanced formation and survival of CD4+ CD25hi Foxp3+ T-cells in chronic lymphocytic leukemia. Leuk Lymphoma, 50(5), 788-801. doi: 10.1080/10428190902803677
Jamin, C., Lamour, A., Pennec, Y. L., Hirn, M., Le Goff, P., & Youinou, P.
(1993). Expression of CD5 and CD72 on T and B cell subsets in rheumatoid arthritis and Sjögren's syndrome. Clin Exp Immunol, 92(2), 245-250.
Jankovic, M., Casellas, R., Yannoutsos, N., Wardemann, H., & Nussenzweig,
M. C. (2004). RAGs and regulation of autoantibodies. Annu Rev Immunol, 22, 485-501. doi: 10.1146/annurev.immunol.22.012703.104707
Jelinek, D. F., Tschumper, R. C., Stolovitzky, G. A., Iturria, S. J., Tu, Y.,
Lepre, J., . . . Kay, N. E. (2003). Identification of a global gene expression signature of B-chronic lymphocytic leukemia. Mol Cancer Res, 1(5), 346-361.
171
Jellusova, J., Wellmann, U., Amann, K., Winkler, T. H., & Nitschke, L. (2010).
CD22 x Siglec-G double-deficient mice have massively increased B1 cell numbers and develop systemic autoimmunity. J Immunol, 184(7), 3618-3627. doi: 10.4049/jimmunol.0902711
Jim, R. T. (1957). Serum gamma globulin levels in chronic lymphocytic
leukemia. Am J Med Sci, 234(1), 44-47. Johnson, A. J., Lucas, D. M., Muthusamy, N., Smith, L. L., Edwards, R. B.,
De Lay, M. D., . . . Byrd, J. C. (2006). Characterization of the TCL-1 transgenic mouse as a preclinical drug development tool for human chronic lymphocytic leukemia. Blood, 108(4), 1334-1338. doi: 10.1182/blood-2005-12-011213
Johnson, W. E., Li, C., & Rabinovic, A. (2007). Adjusting batch effects in
microarray expression data using empirical Bayes methods. Biostatistics, 8(1), 118-127. doi: 10.1093/biostatistics/kxj037
Jordö, E. D., Wermeling, F., Chen, Y., & Karlsson, M. C. (2011). Scavenger
receptors as regulators of natural antibody responses and B cell activation in autoimmunity. Mol Immunol, 48(11), 1307-1318. doi: 10.1016/j.molimm.2011.01.010
Joshi, A. D., Hegde, G. V., Dickinson, J. D., Mittal, A. K., Lynch, J. C., Eudy,
J. D., . . . Joshi, S. S. (2007). ATM, CTLA4, MNDA, and HEM1 in high versus low CD38 expressing B-cell chronic lymphocytic leukemia. Clin Cancer Res, 13(18 Pt 1), 5295-5304. doi: 10.1158/1078-0432.CCR-07-0283
Juliusson, G., Oscier, D. G., Fitchett, M., Ross, F. M., Stockdill, G., Mackie,
M. J., . . . Gahrton, G. (1990). Prognostic subgroups in B-cell chronic lymphocytic leukemia defined by specific chromosomal abnormalities. N Engl J Med, 323(11), 720-724. doi: 10.1056/NEJM199009133231105
Kalos, M., Levine, B. L., Porter, D. L., Katz, S., Grupp, S. A., Bagg, A., &
June, C. H. (2011). T cells with chimeric antigen receptors have potent antitumor effects and can establish memory in patients with advanced leukemia. Sci Transl Med, 3(95), 95ra73. doi: 10.1126/scitranslmed.3002842
Kamper, E. F., Papaphilis, A. D., Angelopoulou, M. K., Kopeikina, L. T.,
Siakantaris, M. P., Pangalis, G. A., & Stavridis, J. C. (1999). Serum levels of tetranectin, intercellular adhesion molecule-1 and interleukin-10 in B-chronic lymphocytic leukemia. Clin Biochem, 32(8), 639-645.
172
Kang, S. M., Narducci, M. G., Lazzeri, C., Mongiovì, A. M., Caprini, E.,
Bresin, A., . . . Russo, G. (2005). Impaired T- and B-cell development in Tcl1-deficient mice. Blood, 105(3), 1288-1294. doi: 10.1182/blood-2004-04-1453
Karmali, R., Paganessi, L. A., Frank, R. R., Jagan, S., Larson, M. L.,
Venugopal, P., . . . Christopherson, K. W. (2013). Aggressive disease defined by cytogenetics is associated with cytokine dysregulation in CLL/SLL patients. J Leukoc Biol, 93(1), 161-170. doi: 10.1189/jlb.0612301
Kater, A. P., Evers, L. M., Remmerswaal, E. B., Jaspers, A., Oosterwijk, M.
F., van Lier, R. A., . . . Eldering, E. (2004). CD40 stimulation of B-cell chronic lymphocytic leukaemia cells enhances the anti-apoptotic profile, but also Bid expression and cells remain susceptible to autologous cytotoxic T-lymphocyte attack. Br J Haematol, 127(4), 404-415. doi: 10.1111/j.1365-2141.2004.05225.x
Kay, N. E. (1981). Abnormal T-cell subpopulation function in CLL: excessive
suppressor (T gamma) and deficient helper (T mu) activity with respect to B-cell proliferation. Blood, 57(3), 418-420.
Keating, M. J., Kantarjian, H., Talpaz, M., Redman, J., Koller, C., Barlogie, B.,
. . . McCredie, K. B. (1989). Fludarabine: a new agent with major activity against chronic lymphocytic leukemia. Blood, 74(1), 19-25.
Keating, M. J., O'Brien, S., Albitar, M., Lerner, S., Plunkett, W., Giles, F., . . .
Kantarjian, H. (2005). Early results of a chemoimmunotherapy regimen of fludarabine, cyclophosphamide, and rituximab as initial therapy for chronic lymphocytic leukemia. J Clin Oncol, 23(18), 4079-4088. doi: 10.1200/JCO.2005.12.051
Kern, C., Cornuel, J. F., Billard, C., Tang, R., Rouillard, D., Stenou, V., . . .
Kolb, J. P. (2004). Involvement of BAFF and APRIL in the resistance to apoptosis of B-CLL through an autocrine pathway. Blood, 103(2), 679-688. doi: 10.1182/blood-2003-02-0540
Kern, W., Bacher, U., Haferlach, C., Dicker, F., Alpermann, T., Schnittger, S.,
& Haferlach, T. (2012). Monoclonal B-cell lymphocytosis is closely related to chronic lymphocytic leukaemia and may be better classified as early-stage CLL. Br J Haematol, 157(1), 86-96. doi: 10.1111/j.1365-2141.2011.09010.x
Khare, S. D., Sarosi, I., Xia, X. Z., McCabe, S., Miner, K., Solovyev, I., . . .
Hsu, H. (2000). Severe B cell hyperplasia and autoimmune disease in
173
TALL-1 transgenic mice. Proc Natl Acad Sci U S A, 97(7), 3370-3375. doi: 10.1073/pnas.050580697
Kiaii, S., Kokhaei, P., Mozaffari, F., Rossmann, E., Pak, F., Moshfegh, A., . . .
Mellstedt, H. (2013). T cells from indolent CLL patients prevent apoptosis of leukemic B cells in vitro and have altered gene expression profile. Cancer Immunol Immunother, 62(1), 51-63. doi: 10.1007/s00262-012-1300-y
Kiefer, K., Nakajima, P. B., Oshinsky, J., Seeholzer, S. H., Radic, M., Bosma,
G. C., & Bosma, M. J. (2008). Antigen receptor editing in anti-DNA transitional B cells deficient for surface IgM. J Immunol, 180(9), 6094-6106.
Kikushige, Y., Ishikawa, F., Miyamoto, T., Shima, T., Urata, S., Yoshimoto,
G., . . . Akashi, K. (2011). Self-renewing hematopoietic stem cell is the primary target in pathogenesis of human chronic lymphocytic leukemia. Cancer Cell, 20(2), 246-259. doi: 10.1016/j.ccr.2011.06.029
King, L. B., & Monroe, J. G. (2000). Immunobiology of the immature B cell:
plasticity in the B-cell antigen receptor-induced response fine tunes negative selection. Immunol Rev, 176, 86-104.
Kipps, T. J., Robbins, B. A., Kuster, P., & Carson, D. A. (1988). Autoantibody-
associated cross-reactive idiotypes expressed at high frequency in chronic lymphocytic leukemia relative to B-cell lymphomas of follicular center cell origin. Blood, 72(2), 422-428.
Kitabayashi, A., Hirokawa, M., & Miura, A. B. (1995). The role of interleukin-
10 (IL-10) in chronic B-lymphocytic leukemia: IL-10 prevents leukemic cells from apoptotic cell death. Int J Hematol, 62(2), 99-106.
Kjeldsberg, C. R., & Marty, J. (1981). Prolymphocytic transformation of
chronic lymphocytic leukemia. Cancer, 48(11), 2447-2457. Klein, U., & Dalla-Favera, R. (2010). New insights into the pathogenesis of
chronic lymphocytic leukemia. Semin Cancer Biol, 20(6), 377-383. doi: 10.1016/j.semcancer.2010.10.012
Klein, U., Lia, M., Crespo, M., Siegel, R., Shen, Q., Mo, T., . . . Dalla-Favera,
R. (2010). The DLEU2/miR-15a/16-1 cluster controls B cell proliferation and its deletion leads to chronic lymphocytic leukemia. Cancer Cell, 17(1), 28-40. doi: 10.1016/j.ccr.2009.11.019
Klein, U., Tu, Y., Stolovitzky, G. A., Mattioli, M., Cattoretti, G., Husson, H., . . .
Dalla-Favera, R. (2001). Gene expression profiling of B cell chronic
174
lymphocytic leukemia reveals a homogeneous phenotype related to memory B cells. J Exp Med, 194(11), 1625-1638.
Kobayashi, R., Picchio, G., Kirven, M., Meisenholder, G., Baird, S., Carson,
D. A., . . . Kipps, T. J. (1992). Transfer of human chronic lymphocytic leukemia to mice with severe combined immune deficiency. Leuk Res, 16(10), 1013-1023.
Kono, D. H., Burlingame, R. W., Owens, D. G., Kuramochi, A., Balderas, R.
S., Balomenos, D., & Theofilopoulos, A. N. (1994). Lupus susceptibility loci in New Zealand mice. Proc Natl Acad Sci U S A, 91(21), 10168-10172.
Kosmaczewska, A., Ciszak, L., Suwalska, K., Wolowiec, D., & Frydecka, I.
(2005). CTLA-4 overexpression in CD19+/CD5+ cells correlates with the level of cell cycle regulators and disease progression in B-CLL patients. Leukemia, 19(2), 301-304. doi: 10.1038/sj.leu.2403588
Kostareli, E., Hadzidimitriou, A., Stavroyianni, N., Darzentas, N.,
Athanasiadou, A., Gounari, M., . . . Stamatopoulos, K. (2009). Molecular evidence for EBV and CMV persistence in a subset of patients with chronic lymphocytic leukemia expressing stereotyped IGHV4-34 B-cell receptors. Leukemia, 23(5), 919-924. doi: 10.1038/leu.2008.379
Kotla, V., Goel, S., Nischal, S., Heuck, C., Vivek, K., Das, B., & Verma, A.
(2009). Mechanism of action of lenalidomide in hematological malignancies. J Hematol Oncol, 2, 36. doi: 10.1186/1756-8722-2-36
Kotsianidis, I., Nakou, E., Spanoudakis, E., Bouchliou, I., Moustakidis, E.,
Miltiades, P., . . . Tsatalas, C. (2011). The diagnostic value of CD1d expression in a large cohort of patients with B-cell chronic lymphoproliferative disorders. Am J Clin Pathol, 136(3), 400-408. doi: 10.1309/AJCP2F2DOXOTXHZA
Krackhardt, A. M., Harig, S., Witzens, M., Broderick, R., Barrett, P., &
Gribben, J. G. (2002). T-cell responses against chronic lymphocytic leukemia cells: implications for immunotherapy. Blood, 100(1), 167-173.
Kremer, J. P., Reisbach, G., Nerl, C., & Dörmer, P. (1992). B-cell chronic
lymphocytic leukaemia cells express and release transforming growth factor-beta. Br J Haematol, 80(4), 480-487.
Kröber, A., Bloehdorn, J., Hafner, S., Bühler, A., Seiler, T., Kienle, D., . . .
Stilgenbauer, S. (2006). Additional genetic high-risk features such as
175
11q deletion, 17p deletion, and V3-21 usage characterize discordance of ZAP-70 and VH mutation status in chronic lymphocytic leukemia. J Clin Oncol, 24(6), 969-975. doi: 10.1200/JCO.2005.03.7184
Kurosaki, T. (1999). Genetic analysis of B cell antigen receptor signaling.
Annu Rev Immunol, 17, 555-592. doi: 10.1146/annurev.immunol.17.1.555
Kurosaki, T., Shinohara, H., & Baba, Y. (2010). B cell signaling and fate
decision. Annu Rev Immunol, 28, 21-55. doi: 10.1146/annurev.immunol.021908.132541
Kyasa, M. J., Hazlett, L., Parrish, R. S., Schichman, S. A., & Zent, C. S.
(2004). Veterans with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) have a markedly increased rate of second malignancy, which is the most common cause of death. Leuk Lymphoma, 45(3), 507-513.
Küppers, R. (2005). Mechanisms of B-cell lymphoma pathogenesis. Nat Rev
Cancer, 5(4), 251-262. doi: 10.1038/nrc1589 Lajaunias, F., Nitschke, L., Moll, T., Martinez-Soria, E., Semac, I.,
Chicheportiche, Y., . . . Izui, S. (2002). Differentially regulated expression and function of CD22 in activated B-1 and B-2 lymphocytes. J Immunol, 168(12), 6078-6083.
Lanasa, M. C., Allgood, S. D., Slager, S. L., Dave, S. S., Love, C., Marti, G.
E., . . . Caporaso, N. E. (2011). Immunophenotypic and gene expression analysis of monoclonal B-cell lymphocytosis shows biologic characteristics associated with good prognosis CLL. Leukemia, 25(9), 1459-1466. doi: 10.1038/leu.2011.117
Lanemo Myhrinder, A., Hellqvist, E., Sidorova, E., Söderberg, A., Baxendale,
H., Dahle, C., . . . Rosén, A. (2008). A new perspective: molecular motifs on oxidized LDL, apoptotic cells, and bacteria are targets for chronic lymphocytic leukemia antibodies. Blood, 111(7), 3838-3848. doi: 10.1182/blood-2007-11-125450
Le Roy, C., Deglesne, P. A., Chevallier, N., Beitar, T., Eclache, V., Quettier,
M., . . . Varin-Blank, N. (2012). The degree of BCR and NFAT activation predicts clinical outcomes in chronic lymphocytic leukemia. Blood, 120(2), 356-365. doi: 10.1182/blood-2011-12-397158
Lech, M., Kulkarni, O. P., Pfeiffer, S., Savarese, E., Krug, A., Garlanda, C., . .
. Anders, H. J. (2008). Tir8/Sigirr prevents murine lupus by suppressing the immunostimulatory effects of lupus autoantigens. J
176
Exp Med, 205(8), 1879-1888. doi: 10.1084/jem.20072646 Ledesma-Soto, Y., Blanco-Favela, F., Fuentes-Pananá, E. M., Tesoro-Cruz,
E., Hernández-González, R., Arriaga-Pizano, L., . . . Chávez-Rueda, A. K. (2012). Increased levels of prolactin receptor expression correlate with the early onset of lupus symptoms and increased numbers of transitional-1 B cells after prolactin treatment. BMC Immunol, 13, 11. doi: 10.1186/1471-2172-13-11
Lee, S. Y., Reichlin, A., Santana, A., Sokol, K. A., Nussenzweig, M. C., &
Choi, Y. (1997). TRAF2 is essential for JNK but not NF-kappaB activation and regulates lymphocyte proliferation and survival. Immunity, 7(5), 703-713.
Li, C., & Hung Wong, W. (2001). Model-based analysis of oligonucleotide
arrays: model validation, design issues and standard error application. Genome Biol, 2(8), RESEARCH0032.
Li, H., Jiang, Y., Prak, E. L., Radic, M., & Weigert, M. (2001). Editors and
editing of anti-DNA receptors. Immunity, 15(6), 947-957. Li, Y., & Zhang, Y. (2006). Molecular evolution of prolactin gene family in
rodents. Acta Genetica Sinica, 33(7), 590-597. Lia, M., Carette, A., Tang, H., Shen, Q., Mo, T., Bhagat, G., . . . Klein, U.
(2012). Functional dissection of the chromosome 13q14 tumor-suppressor locus using transgenic mouse lines. Blood, 119(13), 2981-2990. doi: 10.1182/blood-2011-09-381814
Lieber, M. R., Ma, Y., Pannicke, U., & Schwarz, K. (2004). The mechanism of
vertebrate nonhomologous DNA end joining and its role in V(D)J recombination. DNA Repair (Amst), 3(8-9), 817-826. doi: 10.1016/j.dnarep.2004.03.015
Linet, M. S., Schubauer-Berigan, M. K., Weisenburger, D. D., Richardson, D.
B., Landgren, O., Blair, A., . . . Dores, G. M. (2007). Chronic lymphocytic leukaemia: an overview of aetiology in light of recent developments in classification and pathogenesis. Br J Haematol, 139(5), 672-686. doi: 10.1111/j.1365-2141.2007.06847.x
Liu, F. T., Giustiniani, J., Farren, T., Jia, L., Bensussan, A., Gribben, J. G., &
Agrawal, S. G. (2010). CD160 signaling mediates PI3K-dependent survival and growth signals in chronic lymphocytic leukemia. Blood, 115(15), 3079-3088. doi: 10.1182/blood-2009-08-239483
Liu, Y., Corcoran, M., Rasool, O., Ivanova, G., Ibbotson, R., Grandér, D., . . .
177
Oscier, D. (1997). Cloning of two candidate tumor suppressor genes within a 10 kb region on chromosome 13q14, frequently deleted in chronic lymphocytic leukemia. Oncogene, 15(20), 2463-2473. doi: 10.1038/sj.onc.1201643
Livak, K. J., & Schmittgen, T. D. (2001). Analysis of relative gene expression
data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods, 25(4), 402-408. doi: 10.1006/meth.2001.1262
Loisel, S., Ster, K. L., Quintin-Roue, I., Pers, J. O., Bordron, A., Youinou, P.,
& Berthou, C. (2005). Establishment of a novel human B-CLL-like xenograft model in nude mouse. Leuk Res, 29(11), 1347-1352. doi: 10.1016/j.leukres.2005.04.017
Lombardi, V., Stock, P., Singh, A. K., Kerzerho, J., Yang, W., Sullivan, B. A., .
. . Akbari, O. (2010). A CD1d-dependent antagonist inhibits the activation of invariant NKT cells and prevents development of allergen-induced airway hyperreactivity. J Immunol, 184(4), 2107-2115. doi: 10.4049/jimmunol.0901208
Lotz, M., Ranheim, E., & Kipps, T. J. (1994). Transforming growth factor beta
as endogenous growth inhibitor of chronic lymphocytic leukemia B cells. J Exp Med, 179(3), 999-1004.
Lugassy, G., Lishner, M., & Polliack, A. (1992). Systemic lupus
erythematosus and chronic lymphocytic leukemia: rare coexistence in three patients, with comments on pathogenesis. Leuk Lymphoma, 8(3), 243-245. doi: 10.3109/10428199209054911
M'Hidi, H., Thibult, M. L., Chetaille, B., Rey, F., Bouadallah, R., Nicollas, R., .
. . Xerri, L. (2009). High expression of the inhibitory receptor BTLA in T-follicular helper cells and in B-cell small lymphocytic lymphoma/chronic lymphocytic leukemia. Am J Clin Pathol, 132(4), 589-596. doi: 10.1309/AJCPPHKGYYGGL39C
Mackay, F., Woodcock, S. A., Lawton, P., Ambrose, C., Baetscher, M.,
Schneider, P., . . . Browning, J. L. (1999). Mice transgenic for BAFF develop lymphocytic disorders along with autoimmune manifestations. J Exp Med, 190(11), 1697-1710.
Maddocks-Christianson, K., Slager, S. L., Zent, C. S., Reinalda, M., Call, T.
G., Habermann, T. M., . . . Shanafelt, T. D. (2007). Risk factors for development of a second lymphoid malignancy in patients with chronic lymphocytic leukaemia. Br J Haematol, 139(3), 398-404. doi: 10.1111/j.1365-2141.2007.06801.x
178
Maffei, R., Fiorcari, S., Bulgarelli, J., Martinelli, S., Castelli, I., Deaglio, S., . . . Marasca, R. (2012). Physical contact with endothelial cells through β1- and β2- integrins rescues chronic lymphocytic leukemia cells from spontaneous and drug-induced apoptosis and induces a peculiar gene expression profile in leukemic cells. Haematologica, 97(6), 952-960. doi: 10.3324/haematol.2011.054924
Mahboudi, F., Phillips, J., & Raveche, E. (1992). Immunoglobulin gene
sequence-analysis of B-1 (cd5+b) cell clones in a murine model of chronic lymphocytic-leukemia and richters syndrome. Int J Oncol, 1(4), 459-465.
Malavasi, F., Deaglio, S., Damle, R., Cutrona, G., Ferrarini, M., & Chiorazzi,
N. (2011). CD38 and chronic lymphocytic leukemia: a decade later. Blood, 118(13), 3470-3478. doi: 10.1182/blood-2011-06-275610
Mansouri, L., Cahill, N., Gunnarsson, R., Smedby, K. E., Tjönnfjord, E.,
Hjalgrim, H., . . . Rosenquist, R. (2013). NOTCH1 and SF3B1 mutations can be added to the hierarchical prognostic classification in chronic lymphocytic leukemia. Leukemia, 27(2), 512-514. doi: 10.1038/leu.2012.307
Marti, G. E., Rawstron, A. C., Ghia, P., Hillmen, P., Houlston, R. S., Kay, N., .
. . Consortium, I. F. C. (2005). Diagnostic criteria for monoclonal B-cell lymphocytosis. Br J Haematol, 130(3), 325-332. doi: 10.1111/j.1365-2141.2005.05550.x
Marti, G. E., & Zenger, V. (2004). The natural history of CLL: historical
perspective. In G. Faguet (Ed.), Contemporary Hematology (pp. 3-54). Totowa, NJ: Humana Press.
Martin, F., Oliver, A. M., & Kearney, J. F. (2001). Marginal zone and B1 B
cells unite in the early response against T-independent blood-borne particulate antigens. Immunity, 14(5), 617-629.
Matsuda, J. L., Naidenko, O. V., Gapin, L., Nakayama, T., Taniguchi, M.,
Wang, C. R., . . . Kronenberg, M. (2000). Tracking the response of natural killer T cells to a glycolipid antigen using CD1d tetramers. J Exp Med, 192(5), 741-754.
Matutes, E., Oscier, D., Garcia-Marco, J., Ellis, J., Copplestone, A.,
Gillingham, R., . . . Catovsky, D. (1996). Trisomy 12 defines a group of CLL with atypical morphology: correlation between cytogenetic, clinical and laboratory features in 544 patients. Br J Haematol, 92(2), 382-388.
179
Matutes, E., & Polliack, A. (2000). Morphological and immunophenotypic features of chronic lymphocytic leukemia. Rev Clin Exp Hematol, 4(1), 22-47.
Maura, F., Visco, C., Falisi, E., Reda, G., Fabris, S., Agnelli, L., . . .
Cortelezzi, A. (2013). B-cell receptor configuration and adverse cytogenetics are associated with autoimmune hemolytic anemia in chronic lymphocytic leukemia. Am J Hematol, 88(1), 32-36. doi: 10.1002/ajh.23342
Mauri, C., & Bosma, A. (2012). Immune regulatory function of B cells. Annu
Rev Immunol, 30, 221-241. doi: 10.1146/annurev-immunol-020711-074934
Mauri, C., & Ehrenstein, M. R. (2008). The 'short' history of regulatory B cells.
Trends Immunol, 29(1), 34-40. doi: 10.1016/j.it.2007.10.004 McCarthy, B. A., Mansour, A., Lin, Y. C., Kotenko, S., & Raveche, E. (2004).
RNA interference of IL-10 in leukemic B-1 cells. Cancer Immun, 4, 6. Messmer, B. T., Albesiano, E., Efremov, D. G., Ghiotto, F., Allen, S. L., Kolitz,
J., . . . Chiorazzi, N. (2004). Multiple distinct sets of stereotyped antigen receptors indicate a role for antigen in promoting chronic lymphocytic leukemia. J Exp Med, 200(4), 519-525. doi: 10.1084/jem.20040544
Messmer, B. T., Messmer, D., Allen, S. L., Kolitz, J. E., Kudalkar, P., Cesar,
D., . . . Chiorazzi, N. (2005). In vivo measurements document the dynamic cellular kinetics of chronic lymphocytic leukemia B cells. J Clin Invest, 115(3), 755-764. doi: 10.1172/JCI23409
Michie, A. M., & Nakagawa, R. (2005). The link between PKCalpha regulation
and cellular transformation. Immunol Lett, 96(2), 155-162. doi: 10.1016/j.imlet.2004.08.013
Migliazza, A., Bosch, F., Komatsu, H., Cayanis, E., Martinotti, S., Toniato, E.,
. . . Dalla-Favera, R. (2001). Nucleotide sequence, transcription map, and mutation analysis of the 13q14 chromosomal region deleted in B-cell chronic lymphocytic leukemia. Blood, 97(7), 2098-2104.
Minot, G. B., & Isaacs, R. (1924). Lymphatic Leukemia; Age Incidence,
Duration, and Benefit Derived from Irradiation. Boston Med Surg J, 191(1), 1-9.
Molica, S., Levato, D., & Levato, L. (1993). Infections in chronic lymphocytic
leukemia. Analysis of incidence as a function of length of follow-up.
180
Haematologica, 78(6), 374-377. Montecino-Rodriguez, E., & Dorshkind, K. (2012). B-1 B cell development in
the fetus and adult. Immunity, 36(1), 13-21. doi: 10.1016/j.immuni.2011.11.017
Montecino-Rodriguez, E., Leathers, H., & Dorshkind, K. (2006). Identification
of a B-1 B cell-specified progenitor. Nat Immunol, 7(3), 293-301. doi: 10.1038/ni1301
Moore, K. W., de Waal Malefyt, R., Coffman, R. L., & O'Garra, A. (2001).
Interleukin-10 and the interleukin-10 receptor. Annu Rev Immunol, 19, 683-765. doi: 10.1146/annurev.immunol.19.1.683
Moreira, J., Rabe, K. G., Cerhan, J. R., Kay, N. E., Wilson, J. W., Call, T. G., .
. . Shanafelt, T. D. (2013). Infectious complications among individuals with clinical monoclonal B-cell lymphocytosis (MBL): a cohort study of newly diagnosed cases compared to controls. Leukemia, 27(1), 136-141. doi: 10.1038/leu.2012.187
Morrison, V. A. (2010). Infectious complications of chronic lymphocytic
leukaemia: pathogenesis, spectrum of infection, preventive approaches. Best Pract Res Clin Haematol, 23(1), 145-153. doi: 10.1016/j.beha.2009.12.004
Morton, L. M., Turner, J. J., Cerhan, J. R., Linet, M. S., Treseler, P. A.,
Clarke, C. A., . . . Weisenburger, D. D. (2007). Proposed classification of lymphoid neoplasms for epidemiologic research from the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph). Blood, 110(2), 695-708. doi: 10.1182/blood-2006-11-051672
Motiwala, T., Zanesi, N., Datta, J., Roy, S., Kutay, H., Checovich, A. M., . . .
Jacob, S. T. (2011). AP-1 elements and TCL1 protein regulate expression of the gene encoding protein tyrosine phosphatase PTPROt in leukemia. Blood, 118(23), 6132-6140. doi: 10.1182/blood-2011-01-323147
Motta, M., Rassenti, L., Shelvin, B. J., Lerner, S., Kipps, T. J., Keating, M. J.,
& Wierda, W. G. (2005). Increased expression of CD152 (CTLA-4) by normal T lymphocytes in untreated patients with B-cell chronic lymphocytic leukemia. Leukemia, 19(10), 1788-1793. doi: 10.1038/sj.leu.2403907
Munzert, G., Kirchner, D., Stobbe, H., Bergmann, L., Schmid, R. M., Döhner,
H., & Heimpel, H. (2002). Tumor necrosis factor receptor-associated
181
factor 1 gene overexpression in B-cell chronic lymphocytic leukemia: analysis of NF-kappa B/Rel-regulated inhibitors of apoptosis. Blood, 100(10), 3749-3756. doi: 10.1182/blood.V100.10.3749
Muramatsu, M., Kinoshita, K., Fagarasan, S., Yamada, S., Shinkai, Y., &
Honjo, T. (2000). Class switch recombination and hypermutation require activation-induced cytidine deaminase (AID), a potential RNA editing enzyme. Cell, 102(5), 553-563.
Murphy, K. M., Nelson, C. A., & Sedý, J. R. (2006). Balancing co-stimulation
and inhibition with BTLA and HVEM. Nat Rev Immunol, 6(9), 671-681. doi: 10.1038/nri1917
Nakagawa, R., Soh, J. W., & Michie, A. M. (2006). Subversion of protein
kinase C alpha signaling in hematopoietic progenitor cells results in the generation of a B-cell chronic lymphocytic leukemia-like population in vivo. Cancer Res, 66(1), 527-534. doi: 10.1158/0008-5472.CAN-05-0841
Narducci, M. G., Pescarmona, E., Lazzeri, C., Signoretti, S., Lavinia, A. M.,
Remotti, D., . . . Russo, G. (2000). Regulation of TCL1 expression in B- and T-cell lymphomas and reactive lymphoid tissues. Cancer Res, 60(8), 2095-2100.
Negro, R., Gobessi, S., Longo, P. G., He, Y., Zhang, Z. Y., Laurenti, L., &
Efremov, D. G. (2012). Overexpression of the autoimmunity-associated phosphatase PTPN22 promotes survival of antigen-stimulated CLL cells by selectively activating AKT. Blood, 119(26), 6278-6287. doi: 10.1182/blood-2012-01-403162
Nemazee, D. (2006). Receptor editing in lymphocyte development and
central tolerance. Nat Rev Immunol, 6(10), 728-740. doi: 10.1038/nri1939
Nemazee, D., & Weigert, M. (2000). Revising B cell receptors. J Exp Med,
191(11), 1813-1817. Nganga, V. K., Palmer, V. L., Naushad, H., Kassmeier, M. D., Anderson, D.
K., Perry, G. A., . . . Swanson, P. C. (2013). Accelerated progression of chronic lymphocytic leukemia in Eμ-TCL1 mice expressing catalytically inactive RAG1. Blood, 121(19), 3855-3866, S3851-3816. doi: 10.1182/blood-2012-08-446732
Nishio, M., Endo, T., Tsukada, N., Ohata, J., Kitada, S., Reed, J. C., . . .
Kipps, T. J. (2005). Nurselike cells express BAFF and APRIL, which can promote survival of chronic lymphocytic leukemia cells via a
182
paracrine pathway distinct from that of SDF-1alpha. Blood, 106(3), 1012-1020. doi: 10.1182/blood-2004-03-0889
Nordgren, T. M., & Joshi, S. S. (2010). The etiology of chronic lymphocytic
leukemia: another look at the relationship between B1 and cells and CLL. Open Leuk J, 3, 69-73.
Nowakowski, G. S., Hoyer, J. D., Shanafelt, T. D., Geyer, S. M., LaPlant, B.
R., Call, T. G., . . . Kay, N. E. (2007). Using smudge cells on routine blood smears to predict clinical outcome in chronic lymphocytic leukemia: a universally available prognostic test. Mayo Clin Proc, 82(4), 449-453. doi: 10.4065/82.4.449
Nwabo Kamdje, A. H., Bassi, G., Pacelli, L., Malpeli, G., Amati, E., Nichele, I.,
. . . Krampera, M. (2012). Role of stromal cell-mediated Notch signaling in CLL resistance to chemotherapy. Blood Cancer J, 2(5), e73. doi: 10.1038/bcj.2012.17
O'Garra, A., Chang, R., Go, N., Hastings, R., Haughton, G., & Howard, M.
(1992). Ly-1 B (B-1) cells are the main source of B cell-derived interleukin 10. Eur J Immunol, 22(3), 711-717. doi: 10.1002/eji.1830220314
Ochi, H., & Watanabe, T. (2000). Negative regulation of B cell receptor-
mediated signaling in B-1 cells through CD5 and Ly49 co-receptors via Lyn kinase activity. Int Immunol, 12(10), 1417-1423.
Oettinger, M. A., Schatz, D. G., Gorka, C., & Baltimore, D. (1990). RAG-1
and RAG-2, adjacent genes that synergistically activate V(D)J recombination. Science, 248(4962), 1517-1523.
Okada, T., Takiura, F., Tokushige, K., Nozawa, S., Kiyosawa, T., Nakauchi,
H., . . . Shirai, T. (1991). Major histocompatibility complex controls clonal proliferation of CD5+ B cells in H-2-congenic New Zealand mice: a model for B cell chronic lymphocytic leukemia and autoimmune disease. Eur J Immunol, 21(11), 2743-2748. doi: 10.1002/eji.1830211114
Palamarchuk, A., Yan, P. S., Zanesi, N., Wang, L., Rodrigues, B., Murphy,
M., . . . Pekarsky, Y. (2012). Tcl1 protein functions as an inhibitor of de novo DNA methylation in B-cell chronic lymphocytic leukemia (CLL). Proc Natl Acad Sci U S A, 109(7), 2555-2560. doi: 10.1073/pnas.1200003109
Pan, J. W., Cook, L. S., Schwartz, S. M., & Weis, N. S. (2002). Incidence of
leukemia in Asian migrants to the United States and their
183
descendants. Cancer Causes Control, 13(9), 791-795. Panayiotidis, P., Jones, D., Ganeshaguru, K., Foroni, L., & Hoffbrand, A. V.
(1996). Human bone marrow stromal cells prevent apoptosis and support the survival of chronic lymphocytic leukaemia cells in vitro. Br J Haematol, 92(1), 97-103.
Pangalis, G. A., Vassilakopoulos, T. P., Dimopoulou, M. N., Siakantaris, M.
P., Kontopidou, F. N., & Angelopoulou, M. K. (2002). B-chronic lymphocytic leukemia: practical aspects. Hematol Oncol, 20(3), 103-146. doi: 10.1002/hon.696
Pao, L. I., Lam, K. P., Henderson, J. M., Kutok, J. L., Alimzhanov, M.,
Nitschke, L., . . . Rajewsky, K. (2007). B cell-specific deletion of protein-tyrosine phosphatase Shp1 promotes B-1a cell development and causes systemic autoimmunity. Immunity, 27(1), 35-48. doi: 10.1016/j.immuni.2007.04.016
Papamichail, M., Brown, J. C., & Holborow, E. J. (1971). Immunoglobulins on
the surface of human lymphocytes. Lancet, 2(7729), 850-852. Pedersen, I. M., Kitada, S., Leoni, L. M., Zapata, J. M., Karras, J. G.,
Tsukada, N., . . . Reed, J. C. (2002). Protection of CLL B cells by a follicular dendritic cell line is dependent on induction of Mcl-1. Blood, 100(5), 1795-1801.
Peeva, E., Michael, D., Cleary, J., Rice, J., Chen, X., & Diamond, B. (2003).
Prolactin modulates the naive B cell repertoire. J Clin Invest, 111(2), 275-283. doi: 10.1172/JCI16530
Pekarsky, Y., Koval, A., Hallas, C., Bichi, R., Tresini, M., Malstrom, S., . . .
Croce, C. M. (2000). Tcl1 enhances Akt kinase activity and mediates its nuclear translocation. Proc Natl Acad Sci U S A, 97(7), 3028-3033. doi: 10.1073/pnas.040557697
Pekarsky, Y., Palamarchuk, A., Maximov, V., Efanov, A., Nazaryan, N.,
Santanam, U., . . . Croce, C. M. (2008). Tcl1 functions as a transcriptional regulator and is directly involved in the pathogenesis of CLL. Proc Natl Acad Sci U S A, 105(50), 19643-19648. doi: 10.1073/pnas.0810965105
Pekarsky, Y., Santanam, U., Cimmino, A., Palamarchuk, A., Efanov, A.,
Maximov, V., . . . Croce, C. M. (2006). Tcl1 expression in chronic lymphocytic leukemia is regulated by miR-29 and miR-181. Cancer Res, 66(24), 11590-11593. doi: 10.1158/0008-5472.CAN-06-3613
184
Perez-Chacon, G., Vargas, J. A., Jorda, J., Morado, M., Rosado, S., Martin-Donaire, T., . . . Perez-Aciego, P. (2007). CD5 provides viability signals to B cells from a subset of B-CLL patients by a mechanism that involves PKC. Leuk Res, 31(2), 183-193. doi: 10.1016/j.leukres.2006.03.021
Phillips, J. A., Mehta, K., Fernandez, C., & Raveché, E. S. (1992). The NZB
mouse as a model for chronic lymphocytic leukemia. Cancer Res, 52(2), 437-443.
Pillai, S., & Cariappa, A. (2009). The follicular versus marginal zone B
lymphocyte cell fate decision. Nat Rev Immunol, 9(11), 767-777. doi: 10.1038/nri2656
Pillai, S., Cariappa, A., & Moran, S. T. (2005). Marginal zone B cells. Annu
Rev Immunol, 23, 161-196. doi: 10.1146/annurev.immunol.23.021704.115728
Piller, G. (2001). Leukaemia - a brief historical review from ancient times to
1950. Br J Haematol, 112(2), 282-292. Planelles, L., Carvalho-Pinto, C. E., Hardenberg, G., Smaniotto, S., Savino,
W., Gómez-Caro, R., . . . Hahne, M. (2004). APRIL promotes B-1 cell-associated neoplasm. Cancer Cell, 6(4), 399-408. doi: 10.1016/j.ccr.2004.08.033
Planelles, L., Castillo-Gutiérrez, S., Medema, J. P., Morales-Luque, A.,
Merle-Béral, H., & Hahne, M. (2007). APRIL but not BLyS serum levels are increased in chronic lymphocytic leukemia: prognostic relevance of APRIL for survival. Haematologica, 92(9), 1284-1285.
Plass, C., Byrd, J. C., Raval, A., Tanner, S. M., & de la Chapelle, A. (2007).
Molecular profiling of chronic lymphocytic leukaemia: genetics meets epigenetics to identify predisposing genes. Br J Haematol, 139(5), 744-752. doi: 10.1111/j.1365-2141.2007.06875.x
Ponader, S., Chen, S. S., Buggy, J. J., Balakrishnan, K., Gandhi, V., Wierda,
W. G., . . . Burger, J. A. (2012). The Bruton tyrosine kinase inhibitor PCI-32765 thwarts chronic lymphocytic leukemia cell survival and tissue homing in vitro and in vivo. Blood, 119(5), 1182-1189. doi: 10.1182/blood-2011-10-386417
Porcelli, S. A., & Modlin, R. L. (1999). The CD1 system: antigen-presenting
molecules for T cell recognition of lipids and glycolipids. Annu Rev Immunol, 17, 297-329. doi: 10.1146/annurev.immunol.17.1.297
185
Puente, X. S., Pinyol, M., Quesada, V., Conde, L., Ordóñez, G. R., Villamor, N., . . . Campo, E. (2011). Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia. Nature, 475(7354), 101-105. doi: 10.1038/nature10113
Pérez-Chacón, G., Llobet, D., Pardo, C., Pindado, J., Choi, Y., Reed, J. C., &
Zapata, J. M. (2012). TNFR-associated factor 2 deficiency in B lymphocytes predisposes to chronic lymphocytic leukemia/small lymphocytic lymphoma in mice. J Immunol, 189(2), 1053-1061. doi: 10.4049/jimmunol.1200814
Quiroga, M. P., Balakrishnan, K., Kurtova, A. V., Sivina, M., Keating, M. J.,
Wierda, W. G., . . . Burger, J. A. (2009). B-cell antigen receptor signaling enhances chronic lymphocytic leukemia cell migration and survival: specific targeting with a novel spleen tyrosine kinase inhibitor, R406. Blood, 114(5), 1029-1037. doi: 10.1182/blood-2009-03-212837
Rai, K. R. (1987). A critical analysis of staging in CLL Chronic lymphocytic
leukemia: recent progress and future direction (Vol. 59, pp. 253-264). New York.
Rai, K. R. (1993). Progress in chronic lymphocytic leukaemia: a historical
perspective. Baillieres Clin Haematol, 6(4), 757-765. Rai, K. R., Sawitsky, A., Cronkite, E. P., Chanana, A. D., Levy, R. N., &
Pasternack, B. S. (1975). Clinical staging of chronic lymphocytic leukemia. Blood, 46(2), 219-234.
Rajewsky, K. (1996). Clonal selection and learning in the antibody system.
Nature, 381(6585), 751-758. doi: 10.1038/381751a0 Ramachandra, S., Metcalf, R. A., Fredrickson, T., Marti, G. E., & Raveche, E.
(1996). Requirement for increased IL-10 in the development of B-1 lymphoproliferative disease in a murine model of CLL. J Clin Invest, 98(8), 1788-1793. doi: 10.1172/JCI118978
Ramsay, A. G., Clear, A. J., Fatah, R., & Gribben, J. G. (2012). Multiple
inhibitory ligands induce impaired T-cell immunologic synapse function in chronic lymphocytic leukemia that can be blocked with lenalidomide: establishing a reversible immune evasion mechanism in human cancer. Blood, 120(7), 1412-1421. doi: 10.1182/blood-2012-02-411678
Ramsay, A. G., & Gribben, J. G. (2009). Immune dysfunction in chronic
lymphocytic leukemia T cells and lenalidomide as an immunomodulatory drug. Haematologica, 94(9), 1198-1202. doi:
186
10.3324/haematol.2009.009274 Ramsay, A. G., Johnson, A. J., Lee, A. M., Gorgün, G., Le Dieu, R., Blum,
W., . . . Gribben, J. G. (2008). Chronic lymphocytic leukemia T cells show impaired immunological synapse formation that can be reversed with an immunomodulating drug. J Clin Invest, 118(7), 2427-2437. doi: 10.1172/JCI35017
Raveche, E. S., Salerno, E., Scaglione, B. J., Manohar, V., Abbasi, F., Lin, Y.
C., . . . Marti, G. E. (2007). Abnormal microRNA-16 locus with synteny to human 13q14 linked to CLL in NZB mice. Blood, 109(12), 5079-5086. doi: 10.1182/blood-2007-02-071225
Raveché, E. S., Tjio, J. H., & Steinberg, A. D. (1979). Genetic studies in NZB
mice. II. Hyperdiploidy in the spleen of NZB mice and their hybrids. Cytogenet Cell Genet, 23(3), 182-193.
Rawstron, A. C., Bennett, F. L., O'Connor, S. J., Kwok, M., Fenton, J. A.,
Plummer, M., . . . Hillmen, P. (2008). Monoclonal B-cell lymphocytosis and chronic lymphocytic leukemia. N Engl J Med, 359(6), 575-583. doi: 10.1056/NEJMoa075290
Rawstron, A. C., Green, M. J., Kuzmicki, A., Kennedy, B., Fenton, J. A.,
Evans, P. A., . . . Hillmen, P. (2002). Monoclonal B lymphocytes with the characteristics of "indolent" chronic lymphocytic leukemia are present in 3.5% of adults with normal blood counts. Blood, 100(2), 635-639.
Redaelli, A., Laskin, B. L., Stephens, J. M., Botteman, M. F., & Pashos, C. L.
(2004). The clinical and epidemiological burden of chronic lymphocytic leukaemia. Eur J Cancer Care (Engl), 13(3), 279-287. doi: 10.1111/j.1365-2354.2004.00489.x
Reddy, A. L., & Fialkow, P. J. (1980). Chromosome fragility in New Zealand
black mice: effect of ultraviolet and gamma radiations on fetal fibroblasts in vitro. J Natl Cancer Inst, 64(4), 939-941.
Reiniger, L., Bödör, C., Bognár, A., Balogh, Z., Csomor, J., Szepesi, A., . . .
Matolcsy, A. (2006). Richter's and prolymphocytic transformation of chronic lymphocytic leukemia are associated with high mRNA expression of activation-induced cytidine deaminase and aberrant somatic hypermutation. Leukemia, 20(6), 1089-1095. doi: 10.1038/sj.leu.2404183
Riches, J. C., Davies, J. K., McClanahan, F., Fatah, R., Iqbal, S., Agrawal, S.,
. . . Gribben, J. G. (2013). T cells from CLL patients exhibit features of
187
T-cell exhaustion but retain capacity for cytokine production. Blood, 121(9), 1612-1621. doi: 10.1182/blood-2012-09-457531
Richter, M. N. (1928). Generalized Reticular Cell Sarcoma of Lymph Nodes
Associated with Lymphatic Leukemia. Am J Pathol, 4(4), 285-292.287. Rickert, R. C., Jellusova, J., & Miletic, A. V. (2011). Signaling by the tumor
necrosis factor receptor superfamily in B-cell biology and disease. Immunol Rev, 244(1), 115-133. doi: 10.1111/j.1600-065X.2011.01067.x
Ringshausen, I., Oelsner, M., Weick, K., Bogner, C., Peschel, C., & Decker,
T. (2006). Mechanisms of apoptosis-induction by rottlerin: therapeutic implications for B-CLL. Leukemia, 20(3), 514-520. doi: 10.1038/sj.leu.2404113
Robak, T., Blonski, J. Z., Gora-Tybor, J., Kasznicki, M., Konopka, L.,
Ceglarek, B., . . . Całbecka, M. (2004). Second malignancies and Richter's syndrome in patients with chronic lymphocytic leukaemia treated with cladribine. Eur J Cancer, 40(3), 383-389.
Rodriguez-Manzanet, R., Sanjuan, M. A., Wu, H. Y., Quintana, F. J., Xiao, S.,
Anderson, A. C., . . . Kuchroo, V. K. (2010). T and B cell hyperactivity and autoimmunity associated with niche-specific defects in apoptotic body clearance in TIM-4-deficient mice. Proc Natl Acad Sci U S A, 107(19), 8706-8711. doi: 10.1073/pnas.0910359107
Rosenwald, A., Alizadeh, A. A., Widhopf, G., Simon, R., Davis, R. E., Yu, X., .
. . Staudt, L. M. (2001). Relation of gene expression phenotype to immunoglobulin mutation genotype in B cell chronic lymphocytic leukemia. J Exp Med, 194(11), 1639-1647.
Rossi, D., Cerri, M., Capello, D., Deambrogi, C., Rossi, F. M., Zucchetto, A., .
. . Gaidano, G. (2008). Biological and clinical risk factors of chronic lymphocytic leukaemia transformation to Richter syndrome. Br J Haematol, 142(2), 202-215. doi: 10.1111/j.1365-2141.2008.07166.x
Rosén, A., Murray, F., Evaldsson, C., & Rosenquist, R. (2010). Antigens in
chronic lymphocytic leukemia--implications for cell origin and leukemogenesis. Semin Cancer Biol, 20(6), 400-409. doi: 10.1016/j.semcancer.2010.09.004
Rozman, C., & Montserrat, E. (1995). Chronic lymphocytic leukemia. N Engl
J Med, 333(16), 1052-1057. doi: 10.1056/NEJM199510193331606 Rozman, C., Montserrat, E., & Viñolas, N. (1988). Serum immunoglobulins in
188
B-chronic lymphocytic leukemia. Natural history and prognostic significance. Cancer, 61(2), 279-283.
Ruchlemer, R., & Polliack, A. (2012). Geography, ethnicity and "roots" in
chronic lymphocytic leukemia. Leuk Lymphoma. doi: 10.3109/10428194.2012.740670
Saha, S., Gonzalez, J., Rosenfeld, G., Keiser, H., & Peeva, E. (2009).
Prolactin alters the mechanisms of B cell tolerance induction. Arthritis Rheum, 60(6), 1743-1752. doi: 10.1002/art.24500
Saha, S., Tieng, A., Pepeljugoski, K. P., Zandamn-Goddard, G., & Peeva, E.
(2011). Prolactin, systemic lupus erythematosus, and autoreactive B cells: lessons learnt from murine models. Clin Rev Allergy Immunol, 40(1), 8-15. doi: 10.1007/s12016-009-8182-6
Sakaguchi, S., Yamaguchi, T., Nomura, T., & Ono, M. (2008). Regulatory T
cells and immune tolerance. Cell, 133(5), 775-787. doi: 10.1016/j.cell.2008.05.009
Salerno, E., Scaglione, B. J., Coffman, F. D., Brown, B. D., Baccarini, A.,
Fernandes, H., . . . Raveche, E. S. (2009). Correcting miR-15a/16 genetic defect in New Zealand Black mouse model of CLL enhances drug sensitivity. Mol Cancer Ther, 8(9), 2684-2692. doi: 10.1158/1535-7163.MCT-09-0127
Salerno, E., Yuan, Y., Scaglione, B. J., Marti, G., Jankovic, A., Mazzella, F., .
. . Raveche, E. (2010). The New Zealand black mouse as a model for the development and progression of chronic lymphocytic leukemia. Cytometry B Clin Cytom, 78 Suppl 1, S98-109. doi: 10.1002/cyto.b.20544
Santanam, U., Zanesi, N., Efanov, A., Costinean, S., Palamarchuk, A.,
Hagan, J. P., . . . Pekarsky, Y. (2010). Chronic lymphocytic leukemia modeled in mouse by targeted miR-29 expression. Proc Natl Acad Sci U S A, 107(27), 12210-12215. doi: 10.1073/pnas.1007186107
Scarfò, L., Dagklis, A., Scielzo, C., Fazi, C., & Ghia, P. (2010). CLL-like
monoclonal B-cell lymphocytosis: are we all bound to have it? Semin Cancer Biol, 20(6), 384-390. doi: 10.1016/j.semcancer.2010.08.005
Schaffner, C., Stilgenbauer, S., Rappold, G. A., Döhner, H., & Lichter, P.
(1999). Somatic ATM mutations indicate a pathogenic role of ATM in B-cell chronic lymphocytic leukemia. Blood, 94(2), 748-753.
Schettini, G., Hewlett, E. L., Cronin, M. J., Koike, K., Yasumoto, T., &
189
MacLeod, R. M. (1986). Dopaminergic inhibition of anterior pituitary adenylate cyclase activity and prolactin release: the effects of perturbing calcium on catalytic adenylate cyclase activity. Neuroendocrinology, 44(1), 1-7.
Schmid, C., & Isaacson, P. G. (1994). Proliferation centres in B-cell malignant
lymphoma, lymphocytic (B-CLL): an immunophenotypic study. Histopathology, 24(5), 445-451.
Schroeder, H. W., & Dighiero, G. (1994). The pathogenesis of chronic
lymphocytic leukemia: analysis of the antibody repertoire. Immunol Today, 15(6), 288-294. doi: 10.1016/0167-5699(94)90009-4
Schroers, R., Griesinger, F., Trümper, L., Haase, D., Kulle, B., Klein-Hitpass,
L., . . . Dürig, J. (2005). Combined analysis of ZAP-70 and CD38 expression as a predictor of disease progression in B-cell chronic lymphocytic leukemia. Leukemia, 19(5), 750-758. doi: 10.1038/sj.leu.2403707
Schuler, M., Tretter, T., Schneller, F., Huber, C., & Peschel, C. (1999).
Autocrine transforming growth factor-beta from chronic lymphocytic leukemia-B cells interferes with proliferative T cell signals. Immunobiology, 200(1), 128-139.
Schulz, A., Dürr, C., Zenz, T., Döhner, H., Stilgenbauer, S., Lichter, P., &
Seiffert, M. (2013). Lenalidomide reduces survival of chronic lymphocytic leukemia cells in primary cocultures by altering the myeloid microenvironment. Blood, 121(13), 2503-2511. doi: 10.1182/blood-2012-08-447664
Seifert, M., Sellmann, L., Bloehdorn, J., Wein, F., Stilgenbauer, S., Dürig, J.,
& Küppers, R. (2012). Cellular origin and pathophysiology of chronic lymphocytic leukemia. J Exp Med, 209(12), 2183-2198. doi: 10.1084/jem.20120833
Sen, G., Bikah, G., Venkataraman, C., & Bondada, S. (1999). Negative
regulation of antigen receptor-mediated signaling by constitutive association of CD5 with the SHP-1 protein tyrosine phosphatase in B-1 B cells. Eur J Immunol, 29(10), 3319-3328. doi: 10.1002/(SICI)1521-4141(199910)29:10<3319::AID-IMMU3319>3.0.CO;2-9
Serrano, D., Monteiro, J., Allen, S. L., Kolitz, J., Schulman, P., Lichtman, S.
M., . . . Gregersen, P. K. (1997). Clonal expansion within the CD4+CD57+ and CD8+CD57+ T cell subsets in chronic lymphocytic leukemia. J Immunol, 158(3), 1482-1489.
190
Shaffer, A. L., Rosenwald, A., & Staudt, L. M. (2002). Lymphoid malignancies: the dark side of B-cell differentiation. Nat Rev Immunol, 2(12), 920-932. doi: 10.1038/nri953
Shelly, S., Boaz, M., & Orbach, H. (2012). Prolactin and autoimmunity.
Autoimmun Rev, 11(6-7), A465-470. doi: 10.1016/j.autrev.2011.11.009 Shim, Y. K., Middleton, D. C., Caporaso, N. E., Rachel, J. M., Landgren, O.,
Abbasi, F., . . . Vogt, R. F. (2010). Prevalence of monoclonal B-cell lymphocytosis: a systematic review. Cytometry B Clin Cytom, 78 Suppl 1, S10-18. doi: 10.1002/cyto.b.20538
Shimoni, A., Marcus, H., Canaan, A., Ergas, D., David, M., Berrebi, A., &
Reisner, Y. (1997). A model for human B-chronic lymphocytic leukemia in human/mouse radiation chimera: evidence for tumor-mediated suppression of antibody production in low-stage disease. Blood, 89(6), 2210-2218.
Shivakumar, S., Tsokos, G. C., & Datta, S. K. (1989). T cell receptor
alpha/beta expressing double-negative (CD4-/CD8-) and CD4+ T helper cells in humans augment the production of pathogenic anti-DNA autoantibodies associated with lupus nephritis. J Immunol, 143(1), 103-112.
Shivapurkar, N., Harada, K., Reddy, J., Scheuermann, R. H., Xu, Y.,
McKenna, R. W., . . . Gazdar, A. F. (2002). Presence of simian virus 40 DNA sequences in human lymphomas. Lancet, 359(9309), 851-852. doi: 10.1016/S0140-6736(02)07921-7
Shivapurkar, N., Takahashi, T., Reddy, J., Zheng, Y., Stastny, V., Collins, R.,
. . . Gazdar, A. F. (2004). Presence of simian virus 40 DNA sequences in human lymphoid and hematopoietic malignancies and their relationship to aberrant promoter methylation of multiple genes. Cancer Res, 64(11), 3757-3760. doi: 10.1158/0008-5472.CAN-03-3307
Shlomchik, M. J., & Weisel, F. (2012). Germinal center selection and the
development of memory B and plasma cells. Immunol Rev, 247(1), 52-63. doi: 10.1111/j.1600-065X.2012.01124.x
Siegel, R., Naishadham, D., & Jemal, A. (2013). Cancer statistics, 2013. CA
Cancer J Clin, 63(1), 11-30. doi: 10.3322/caac.21166 Simmons, D. G., Rawn, S., Davies, A., Hughes, M., & Cross, J. C. (2008).
Spatial and temporal expression of the 23 murine Prolactin/Placental Lactogen-related genes is not associated with their position in the
191
locus. BMC Genomics, 9, 352. doi: 10.1186/1471-2164-9-352 Sims, G. P., Ettinger, R., Shirota, Y., Yarboro, C. H., Illei, G. G., & Lipsky, P.
E. (2005). Identification and characterization of circulating human transitional B cells. Blood, 105(11), 4390-4398. doi: 10.1182/blood-2004-11-4284
Sinha, A. A., Lopez, M. T., & McDevitt, H. O. (1990). Autoimmune diseases:
the failure of self tolerance. Science, 248(4961), 1380-1388. Sinisalo, M., Aittoniemi, J., Oivanen, P., Käyhty, H., Olander, R. M., & Vilpo,
J. (2001). Response to vaccination against different types of antigens in patients with chronic lymphocytic leukaemia. Br J Haematol, 114(1), 107-110.
Sivina, M., Hartmann, E., Vasyutina, E., Boucas, J. M., Breuer, A., Keating,
M. J., . . . Burger, J. A. (2012). Stromal cells modulate TCL1 expression, interacting AP-1 components and TCL1-targeting micro-RNAs in chronic lymphocytic leukemia. Leukemia, 26(8), 1812-1820. doi: 10.1038/leu.2012.63
Skowronska, A., Austen, B., Powell, J. E., Weston, V., Oscier, D. G., Dyer, M.
J., . . . Stankovic, T. (2012). ATM germline heterozygosity does not play a role in chronic lymphocytic leukemia initiation but influences rapid disease progression through loss of the remaining ATM allele. Haematologica, 97(1), 142-146. doi: 10.3324/haematol.2011.048827
Slager, S. L., Goldin, L. R., Strom, S. S., Lanasa, M. C., Spector, L. G.,
Rassenti, L., . . . Cerhan, J. R. (2010). Genetic susceptibility variants for chronic lymphocytic leukemia. Cancer Epidemiol Biomarkers Prev, 19(4), 1098-1102. doi: 10.1158/1055-9965.EPI-09-1217
Soma, L. A., Craig, F. E., & Swerdlow, S. H. (2006). The proliferation center
microenvironment and prognostic markers in chronic lymphocytic leukemia/small lymphocytic lymphoma. Hum Pathol, 37(2), 152-159. doi: 10.1016/j.humpath.2005.09.029
Spitaler, M., & Cantrell, D. A. (2004). Protein kinase C and beyond. Nat
Immunol, 5(8), 785-790. doi: 10.1038/ni1097 Stall, A. M., Fariñas, M. C., Tarlinton, D. M., Lalor, P. A., Herzenberg, L. A., &
Strober, S. (1988). Ly-1 B-cell clones similar to human chronic lymphocytic leukemias routinely develop in older normal mice and young autoimmune (New Zealand Black-related) animals. Proc Natl Acad Sci U S A, 85(19), 7312-7316.
192
Stamatopoulos, K., Belessi, C., Moreno, C., Boudjograh, M., Guida, G., Smilevska, T., . . . Davi, F. (2007). Over 20% of patients with chronic lymphocytic leukemia carry stereotyped receptors: Pathogenetic implications and clinical correlations. Blood, 109(1), 259-270. doi: 10.1182/blood-2006-03-012948
Stavnezer, J., Guikema, J. E., & Schrader, C. E. (2008). Mechanism and
regulation of class switch recombination. Annu Rev Immunol, 26, 261-292. doi: 10.1146/annurev.immunol.26.021607.090248
Stein, J. V., López-Fraga, M., Elustondo, F. A., Carvalho-Pinto, C. E.,
Rodríguez, D., Gómez-Caro, R., . . . Hahne, M. (2002). APRIL modulates B and T cell immunity. J Clin Invest, 109(12), 1587-1598. doi: 10.1172/JCI15034
Stevenson, F. K., Krysov, S., Davies, A. J., Steele, A. J., & Packham, G.
(2011). B-cell receptor signaling in chronic lymphocytic leukemia. Blood, 118(16), 4313-4320. doi: 10.1182/blood-2011-06-338855
Sthoeger, Z. M., Wakai, M., Tse, D. B., Vinciguerra, V. P., Allen, S. L.,
Budman, D. R., . . . Chiorazzi, N. (1989). Production of autoantibodies by CD5-expressing B lymphocytes from patients with chronic lymphocytic leukemia. J Exp Med, 169(1), 255-268.
Stratowa, C., Löffler, G., Lichter, P., Stilgenbauer, S., Haberl, P., Schweifer,
N., . . . Wilgenbus, K. K. (2001). CDNA microarray gene expression analysis of B-cell chronic lymphocytic leukemia proposes potential new prognostic markers involved in lymphocyte trafficking. Int J Cancer, 91(4), 474-480.
Suljagic, M., Longo, P. G., Bennardo, S., Perlas, E., Leone, G., Laurenti, L.,
& Efremov, D. G. (2010). The Syk inhibitor fostamatinib disodium (R788) inhibits tumor growth in the Eμ- TCL1 transgenic mouse model of CLL by blocking antigen-dependent B-cell receptor signaling. Blood, 116(23), 4894-4905. doi: 10.1182/blood-2010-03-275180
Swerdlow, S. H., Murray, L. J., Habeshaw, J. A., & Stansfeld, A. G. (1984).
Lymphocytic lymphoma/B-chronic lymphocytic leukaemia--an immunohistopathological study of peripheral B lymphocyte neoplasia. Br J Cancer, 50(5), 587-599.
Szatmari, I., Pap, A., Rühl, R., Ma, J. X., Illarionov, P. A., Besra, G. S., . . .
Nagy, L. (2006). PPARgamma controls CD1d expression by turning on retinoic acid synthesis in developing human dendritic cells. J Exp Med, 203(10), 2351-2362. doi: 10.1084/jem.20060141
193
Takahashi, T., & Strober, S. (2008). Natural killer T cells and innate immune B cells from lupus-prone NZB/W mice interact to generate IgM and IgG autoantibodies. Eur J Immunol, 38(1), 156-165. doi: 10.1002/eji.200737656
Teitell, M. A. (2005). The TCL1 family of oncoproteins: co-activators of
transformation. Nat Rev Cancer, 5(8), 640-648. doi: 10.1038/nrc1672 ter Brugge, P. J., Ta, V. B., de Bruijn, M. J., Keijzers, G., Maas, A., van Gent,
D. C., & Hendriks, R. W. (2009). A mouse model for chronic lymphocytic leukemia based on expression of the SV40 large T antigen. Blood, 114(1), 119-127. doi: 10.1182/blood-2009-01-198937
Thornton, P. D., Bellas, C., Santon, A., Shah, G., Pocock, C., Wotherspoon,
A. C., . . . Catovsky, D. (2005). Richter's transformation of chronic lymphocytic leukemia. The possible role of fludarabine and the Epstein-Barr virus in its pathogenesis. Leuk Res, 29(4), 389-395. doi: 10.1016/j.leukres.2004.09.008
Thorsélius, M., Kröber, A., Murray, F., Thunberg, U., Tobin, G., Bühler, A., . .
. Rosenquist, R. (2006). Strikingly homologous immunoglobulin gene rearrangements and poor outcome in VH3-21-using chronic lymphocytic leukemia patients independent of geographic origin and mutational status. Blood, 107(7), 2889-2894. doi: 10.1182/blood-2005-06-2227
Tiegs, S. L., Russell, D. M., & Nemazee, D. (1993). Receptor editing in self-
reactive bone marrow B cells. J Exp Med, 177(4), 1009-1020. Tonegawa, S. (1983). Somatic generation of antibody diversity. Nature,
302(5909), 575-581. Toze, C. L., Dalal, C. B., Nevill, T. J., Gillan, T. L., Abou Mourad, Y. R.,
Barnett, M. J., . . . Shepherd, J. D. (2012). Allogeneic haematopoietic stem cell transplantation for chronic lymphocytic leukaemia: outcome in a 20-year cohort. Br J Haematol, 158(2), 174-185. doi: 10.1111/j.1365-2141.2012.09170.x
Tsimberidou, A. M., & Keating, M. J. (2006). Richter's transformation in
chronic lymphocytic leukemia. Semin Oncol, 33(2), 250-256. doi: 10.1053/j.seminoncol.2006.01.016
Tsubata, T., & Reth, M. (1990). The products of pre-B cell-specific genes
(lambda 5 and VpreB) and the immunoglobulin mu chain form a complex that is transported onto the cell surface. J Exp Med, 172(3), 973-976.
194
Tsukada, N., Burger, J. A., Zvaifler, N. J., & Kipps, T. J. (2002). Distinctive
features of "nurselike" cells that differentiate in the context of chronic lymphocytic leukemia. Blood, 99(3), 1030-1037.
Van Bockstaele, F., Verhasselt, B., & Philippé, J. (2009). Prognostic markers
in chronic lymphocytic leukemia: a comprehensive review. Blood Rev, 23(1), 25-47. doi: 10.1016/j.blre.2008.05.003
Victora, G. D., & Nussenzweig, M. C. (2012). Germinal centers. Annu Rev
Immunol, 30, 429-457. doi: 10.1146/annurev-immunol-020711-075032 Virchow, R. (1845). Weisses Blut. Neue Notizen aus dem Gebiete der Natur-
und Heilkunde, 36, 151-156. Virchow, R. (1847). Zur pathologischen Physiologie des Bluts. II. Weisses
Blut (Leukämie). Virchows Arch. Path. Anat, 1, 563-572. Virgilio, L., Lazzeri, C., Bichi, R., Nibu, K., Narducci, M. G., Russo, G., . . .
Croce, C. M. (1998). Deregulated expression of TCL1 causes T cell leukemia in mice. Proc Natl Acad Sci U S A, 95(7), 3885-3889.
Virgilio, L., Narducci, M. G., Isobe, M., Billips, L. G., Cooper, M. D., Croce, C.
M., & Russo, G. (1994). Identification of the TCL1 gene involved in T-cell malignancies. Proc Natl Acad Sci U S A, 91(26), 12530-12534.
Vogler, M., Butterworth, M., Majid, A., Walewska, R. J., Sun, X. M., Dyer, M.
J., & Cohen, G. M. (2009). Concurrent up-regulation of BCL-XL and BCL2A1 induces approximately 1000-fold resistance to ABT-737 in chronic lymphocytic leukemia. Blood, 113(18), 4403-4413. doi: 10.1182/blood-2008-08-173310
Waddington, J. L. (1986). Bromocriptine, selective D2 dopamine receptor
agonists and D1 dopaminergic tone. Trends Pharmacol Sci., 7, 223-224.
Waldschmidt, T., Snapp, K., Foy, T., Tygrett, L., & Carpenter, C. (1992). B-
cell subsets defined by the Fc epsilon R. Ann N Y Acad Sci, 651, 84-98.
Wang, H., Feng, J., Qi, C. F., Li, Z., Morse, H. C., & Clarke, S. H. (2007).
Transitional B cells lose their ability to receptor edit but retain their potential for positive and negative selection. J Immunol, 179(11), 7544-7552.
Wang, J., Coombes, K. R., Highsmith, W. E., Keating, M. J., & Abruzzo, L. V.
195
(2004). Differences in gene expression between B-cell chronic lymphocytic leukemia and normal B cells: a meta-analysis of three microarray studies. Bioinformatics, 20(17), 3166-3178. doi: 10.1093/bioinformatics/bth381
Wardemann, H., Yurasov, S., Schaefer, A., Young, J. W., Meffre, E., &
Nussenzweig, M. C. (2003). Predominant autoantibody production by early human B cell precursors. Science, 301(5638), 1374-1377. doi: 10.1126/science.1086907
Watson, L., Wyld, P., & Catovsky, D. (2008). Disease burden of chronic
lymphocytic leukaemia within the European Union. Eur J Haematol, 81(4), 253-258. doi: 10.1111/j.1600-0609.2008.01114.x
Weill, J. C., Weller, S., & Reynaud, C. A. (2009). Human marginal zone B
cells. Annu Rev Immunol, 27, 267-285. doi: 10.1146/annurev.immunol.021908.132607
Weiss, L., Melchardt, T., Egle, A., Grabmer, C., Greil, R., & Tinhofer, I.
(2011). Regulatory T cells predict the time to initial treatment in early stage chronic lymphocytic leukemia. Cancer, 117(10), 2163-2169. doi: 10.1002/cncr.25752
Weinkove, R., Brooks, C. R., Carter, J. M., Hermans, I. F., & Ronchese, F.
(2013). Functional invariant natural killer T-cell and CD1d axis in chronic lymphocytic leukemia: implications for immunotherapy. Haematologica, 98(3), 376-384. doi: 10.3324/haematol.2012.072835
Wen, L., Brill-Dashoff, J., Shinton, S. A., Asano, M., Hardy, R. R., &
Hayakawa, K. (2005). Evidence of marginal-zone B cell-positive selection in spleen. Immunity, 23(3), 297-308. doi: 10.1016/j.immuni.2005.08.007
Wen, X., Zhang, D., Kikuchi, Y., Jiang, Y., Nakamura, K., Xiu, Y., . . . Hirose,
S. (2004). Transgene-mediated hyper-expression of IL-5 inhibits autoimmune disease but increases the risk of B cell chronic lymphocytic leukemia in a model of murine lupus. Eur J Immunol, 34(10), 2740-2749. doi: 10.1002/eji.200425267
Whiteside, T. L. (2008). The tumor microenvironment and its role in
promoting tumor growth. Oncogene, 27(45), 5904-5912. doi: 10.1038/onc.2008.271
Widhopf, G. F., Rassenti, L. Z., Toy, T. L., Gribben, J. G., Wierda, W. G., &
Kipps, T. J. (2004). Chronic lymphocytic leukemia B cells of more than 1% of patients express virtually identical immunoglobulins. Blood,
196
104(8), 2499-2504. doi: 10.1182/blood-2004-03-0818 Wiemers, D. O., Shao, L. J., Ain, R., Dai, G., & Soares, M. J. (2003). The
mouse prolactin gene family locus. Endocrinology, 144(1), 313-325. Wilson, J. D., & Nossal, G. J. (1971). Identification of human T and B
lymphocytes in normal peripheral blood and in chronic lymphocytic leukaemia. Lancet, 2(7728), 788-791.
Wintrobe, M. M., & Hasenbush, L. L. (1939). Chronic leukemia: the early
phase of chronic leukemia, the results of treatment and effects of complicating infections; a study of eighty-six adults. Arch Intern Med, 64(4), 701-718.
Woyach, J. A., Johnson, A. J., & Byrd, J. C. (2012). The B-cell receptor
signaling pathway as a therapeutic target in CLL. Blood, 120(6), 1175-1184. doi: 10.1182/blood-2012-02-362624
Wu, D., Xing, G. W., Poles, M. A., Horowitz, A., Kinjo, Y., Sullivan, B., . . .
Wong, C. H. (2005). Bacterial glycolipids and analogs as antigens for CD1d-restricted NKT cells. Proc Natl Acad Sci U S A, 102(5), 1351-1356. doi: 10.1073/pnas.0408696102
Wu, Q. L., Zierold, C., & Ranheim, E. A. (2009). Dysregulation of Frizzled 6 is
a critical component of B-cell leukemogenesis in a mouse model of chronic lymphocytic leukemia. Blood, 113(13), 3031-3039. doi: 10.1182/blood-2008-06-163303
Xu, J. L., & Davis, M. M. (2000). Diversity in the CDR3 region of V(H) is
sufficient for most antibody specificities. Immunity, 13(1), 37-45. Xu, Y., Harder, K. W., Huntington, N. D., Hibbs, M. L., & Tarlinton, D. M.
(2005). Lyn tyrosine kinase: accentuating the positive and the negative. Immunity, 22(1), 9-18. doi: 10.1016/j.immuni.2004.12.004
Yan, X. J., Albesiano, E., Zanesi, N., Yancopoulos, S., Sawyer, A., Romano,
E., . . . Chiorazzi, N. (2006). B cell receptors in TCL1 transgenic mice resemble those of aggressive, treatment-resistant human chronic lymphocytic leukemia. Proc Natl Acad Sci U S A, 103(31), 11713-11718. doi: 10.1073/pnas.0604564103
Youinou, P., Hillion, S., Jamin, C., Pers, J. O., Saraux, A., & Renaudineau, Y.
(2006). B lymphocytes on the front line of autoimmunity. Autoimmun Rev, 5(3), 215-221. doi: 10.1016/j.autrev.2005.06.011
Youinou, P., Jamin, C., & Lydyard, P. M. (1999). CD5 expression in human
197
B-cell populations. Immunol Today, 20(7), 312-316. Yuille, M. R., Matutes, E., Marossy, A., Hilditch, B., Catovsky, D., & Houlston,
R. S. (2000). Familial chronic lymphocytic leukaemia: a survey and review of published studies. Br J Haematol, 109(4), 794-799.
Zanesi, N., Aqeilan, R., Drusco, A., Kaou, M., Sevignani, C., Costinean, S., . .
. Croce, C. M. (2006). Effect of rapamycin on mouse chronic lymphocytic leukemia and the development of nonhematopoietic malignancies in Emu-TCL1 transgenic mice. Cancer Res, 66(2), 915-920. doi: 10.1158/0008-5472.CAN-05-3426
Zapata, J. M., Krajewska, M., Krajewski, S., Kitada, S., Welsh, K., Monks, A.,
. . . Reed, J. C. (2000). TNFR-associated factor family protein expression in normal tissues and lymphoid malignancies. J Immunol, 165(9), 5084-5096.
Zapata, J. M., Krajewska, M., Morse, H. C., Choi, Y., & Reed, J. C. (2004).
TNF receptor-associated factor (TRAF) domain and Bcl-2 cooperate to induce small B cell lymphoma/chronic lymphocytic leukemia in transgenic mice. Proc Natl Acad Sci U S A, 101(47), 16600-16605. doi: 10.1073/pnas.0407541101
Zent, C. S., & Kay, N. E. (2010). Autoimmune complications in chronic
lymphocytic leukaemia (CLL). Best Pract Res Clin Haematol, 23(1), 47-59. doi: 10.1016/j.beha.2010.01.004
Zenz, T., Eichhorst, B., Busch, R., Denzel, T., Häbe, S., Winkler, D., . . .
Stilgenbauer, S. (2010). TP53 mutation and survival in chronic lymphocytic leukemia. J Clin Oncol, 28(29), 4473-4479. doi: 10.1200/JCO.2009.27.8762
Zenz, T., Mertens, D., Döhner, H., & Stilgenbauer, S. (2011). Importance of
genetics in chronic lymphocytic leukemia. Blood Rev, 25(3), 131-137. doi: 10.1016/j.blre.2011.02.002
Zhang, Z. X., Yang, L., Young, K. J., DuTemple, B., & Zhang, L. (2000).
Identification of a previously unknown antigen-specific regulatory T cell and its mechanism of suppression. Nat Med, 6(7), 782-789. doi: 10.1038/77513
Zheng, S. G., Wang, J. H., Gray, J. D., Soucier, H., & Horwitz, D. A. (2004).
Natural and induced CD4+CD25+ cells educate CD4+CD25- cells to develop suppressive activity: the role of IL-2, TGF-beta, and IL-10. J Immunol, 172(9), 5213-5221.