UMEÅ  UNIVERSITY  MEDICAL  DISSERTATIONS    

New  Series  No.  1522                                ISSN  0346-­‐6612                                ISBN  978-­‐91-­‐7459-­‐481-­‐2      

     

Telomere  length  -­‐  Dynamics  and  role  as  a  biological  marker                        

in  malignancy      

Ulrika  Svenson    

       

 

                           

Department  of  Medical  Biosciences,  Pathology  Umeå  University  

Umeå  2012    

 

Responsible  publisher  under  Swedish  law:  the  Dean  of  the  Medical  Faculty  This  work  is  protected  by  the  Swedish  Copyright  Legislation  (Act  1960:729)    New  Series  No:  1522                                  ISSN:  0346-­‐6612                                  ISBN:  978-­‐91-­‐7459-­‐481-­‐2  E-­‐version  available  at:  http://umu.diva-­‐portal.org/      Cover  and  figure  design:  Ulrika  Svenson  Printed  by:  Print  &  Media,  Umeå,  Sweden,  2012    ©  Ulrika  Svenson,  2012                                                                

 

         

To  my  family  and  friends                                                

”Anything's possible if you've got enough nerve”

J.K. Rowling

   

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TABLE  OF  CONTENTS      TABLE  OF  CONTENTS   i  ABSTRACT   iii  ORIGINAL  ARTICLES     iv  LIST  OF  ABBREVIATIONS   v  POPULÄRVETENSKAPLIG  SAMMANFATTNING   vi  INTRODUCTION   1  

TELOMERE  BIOLOGY   1     IT  STARTS  WITH  THE  END   1     THE  TELOMERASE  ENZYME   2     FACTORS  INFLUENCING  TELOMERE  LENGTH   3     TELOMERE  LENGTH  IN  PERIPHERAL  BLOOD  CELLS   5       The  hematopoietic  and  immune  system  -­‐  an  overview   5       Blood  telomere  length  in  health  and  disease   7       Telomeres  and  telomerase  in  blood  cell  subpopulations   7     APPROACHES  FOR  TELOMERE  LENGTH  ESTIMATION  –  A  SUMMARY   9  TUMOR  BIOLOGY   11     THE  HALLMARKS  OF  CANCER   11     TUMORS  AND  TELOMERES   11     THE  IMMUNE  SYSTEM  AND  CANCER   13     SPECIFIC  TUMOR  TYPES   15     Breast  cancer   15     Renal  cell  carcinoma   16  

AIMS   18  MATERIALS  AND  METHODS   19  

  STUDY  POPULATIONS  AND  TISSUE  SAMPLES   19     MAGNETIC  IMMUNE  CELL  SEPARATION   21     TELOMERE  LENGTH  MEASUREMENTS   21     Telomere  real-­‐time  PCR   21     Southern  blot   22     Single  Telomere  Length  Analysis  (STELA)   22     TELOMERASE  ACTIVITY   23     FLOW  CYTOMETRY     23     MULTIPLEX  CYTOKINE  ANALYSIS   23     STATISTICAL  ANALYSIS   24  

RESULTS   25       PAPER  I   25       PAPER  II   26       PAPER  III   27       PAPER  IV   28      

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DISCUSSION     30     BLOOD  TELOMERE  LENGTH  AS  A  RISK  MARKER  IN  MALIGNANCY   30   TELOMERE  LENGTH  AS  A  PROGNOSTIC  INDICATOR  FOR     32     CANCER  SURVIVAL     THE  IMPACT  OF  IMMUNOLOGICAL  FACTORS  ON  TELOMERE  LENGTH   34     TELOMERE  LENGTH  DYNAMICS  IN  LEUKOCYTES  AND  THEIR  SUBSETS   36  CONCLUDING  SUMMARY   39  ACKNOWLEDGEMENTS   40  REFERENCES   43                                                                    

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ABSTRACT    Telomeres  are  protective  structures  at  the  end  of  our  chromosomes,  composed  of  multiple  repeats   of   the   DNA   sequence   TTAGGG.   They   are   essential   for  maintaining   chromosomal  stability  by  preventing  damage  and  degradation  of  the   chromosome  ends.   Telomeres  are  normally  shortened  with  each  cell  division  until  a  critical  length  is  reached,  at  which  stage  cell  cycle  arrest   is   induced.  Telomere  shortening  can  be  prevented   in  the  presence  of   the  telomere-­‐elongating   enzyme   telomerase.   Telomerase   is   expressed   during   embryogenesis  and   in   certain   normal   cell   types,   but   most   somatic   cells   exhibit   undetectable   levels   of  telomerase   activity.   In   contrast,   most   cancer   cells   express   telomerase   enabling   them   to  proliferate  indefinitely.    There  is  a  search  for  reliable  molecular  markers  that  can  be  used  to  help  predict  cancer  risk  and   outcome.   The   interest   of   investigating   telomere   length   as   a   potential   biomarker   in  malignancy  has  grown  rapidly,  and  both  tumors  and  normal  tissues  have  been  in  focus  for  telomere   length  measurements.   In   this   thesis,   telomere   length  was   investigated   in  breast  cancer  patients  and  in  patients  with  renal  cell  carcinoma  (RCC).  The  breast  cancer  patients  were  found  to  have  significantly  longer  mean  telomere  length  in  peripheral  blood  cells  (i.e.  immune   cells)   compared   to   a   tumor-­‐free   control   group.   Moreover,   patients   with   the  longest   blood   telomere   length   had   a   significantly   worse   outcome   compared   to   patients  with  shorter  blood  telomeres.   In  a  patient  group  with  clear  cell  RCC,  telomere  length  was  investigated  in  peripheral  blood  cells,  in  tumors  and  in  corresponding  kidney  cortex.  Again,  patients   with   the   longest   blood   telomere   length   had   a   significantly   worse   prognosis  compared  to  those  with  shorter  blood  telomeres.  In  contrast,  telomere  length  in  tumor  and  kidney  cortex  tissues  did  not  predict  outcome  per  se.      Immunological   components   may   play   a   role   in   telomere   length   dynamics   as   well   as   in  cancer   development.   We   aimed   to   investigate   a   possible   association   between   telomere  length   and   certain   immunological   parameters,   including   various   cytokines   and   peripheral  levels   of   a   blood   cell   type   with   suppressor   function   [regulatory   T   cells   (Tregs)].   In   our  patients  with   clear   cell   RCC,   three   cytokines   correlated   significantly  with   tumor   telomere  length,  but  not  with  telomere  length  in  peripheral  blood  cells.  In  a  separate  patient  group  with  various  RCC  tumors,  blood  telomere   length  correlated  positively  with  the  amount  of  Tregs.  It  might  be  speculated  that  a  subset  of  patients  with  long  blood  telomeres  has  a  less  efficient  immune  response  due  to  high  Treg  levels,  contributing  to  a  worse  prognosis.      Another  aim  of  this  thesis  was  to  explore  telomere  length  changes  over  time.  Evaluation  of  blood  samples  collected  at  a  6-­‐month  interval  from  50  individuals,  showed  that  half  of  the  participants   experienced   a   decline   in  mean   telomere   length   during   the   time   period.   This  group   had   longer   telomere   length   at   baseline   compared   to   those   who   demonstrated  increased/stable   telomere   length.   In  a  separate  group  of   five  blood  donors,  a   remarkable  drop   in   telomere   length  was  detected   in  one  donor  over   a  6-­‐month  period,  whereas   the  other  donors  exhibited  only  small  fluctuations  in  telomere  length.    In  conclusion,  the  results  of  this  thesis  indicate  that  blood  telomere  length  has  potential  to  act   as   an   independent   prognostic  marker   in  malignancy.   Adding   to   the   complexity   is   the  fact  that  changes  in  blood  telomere  length  might  occur  within  relatively  short  time  spans,  indicating  that  telomere  length  is  a  dynamic  character.  

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ORIGINAL  ARTICLES    

 PAPER  I  Breast  cancer  survival  is  associated  with  telomere  length  in  peripheral  blood  cells.  Svenson  U*,  Nordfjäll  K*,  Stegmayr  B,  Manjer  J,  Nilsson  P,  Tavelin  B,  Henriksson  R,  Lenner  P,    Roos  G.  Cancer  Res.  2008;68:3618-­‐23.                                                                                                                                                                                    *  Authors  contributed  equally    PAPER  II  Telomere  length  in  peripheral  blood  predicts  survival  in  clear  cell  renal  cell  carcinoma.  Svenson  U,  Ljungberg  B,  Roos  G.  Cancer  Res.  2009;69:2896-­‐901.      PAPER  III  Telomere  length  in  relation  to  immunological  parameters  in  patients  with  renal  cell  carcinoma.  Svenson  U,  Grönlund  E,  Söderström  I,  Sitaram  RT,  Ljungberg  B,  Roos  G.  Manuscript  2012;  submitted.    PAPER  IV  Blood  cell  telomere  length  is  a  dynamic  feature.  Svenson  U,  Nordfjäll  K,  Baird  D,  Roger  L,  Osterman  P,  Hellenius  ML,  Roos  G.  PLoS  One.  2011;6:e21485.                      

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LIST  OF  ABBREVIATIONS    ALT         Alternative  lengthening  of  telomeres  ANCOVA       Analysis  of  covariance  B-­‐F-­‐B  cycle       Breakage-­‐fusion-­‐bridge  cycle  ccRCC         Clear  cell  renal  cell  carcinoma  Ct         Cycle  threshold  CV         Coefficient  of  variation  DSB         Double-­‐strand  DNA  breaks  ER         Estrogen  receptor  G-­‐CSF         Granulocyte  colony-­‐stimulating  factor  G-­‐rich         Guanine-­‐rich  HCC         Hepatocellular  carcinoma  HCS         Hematopoietic  stem  cell  hTERT         Human  telomerase  reverse  transcriptase  hTR           Human  telomerase  RNA  template  IL         Interleukin  M  cells         Myeloid  cells  MCP-­‐1         Monocyte  chemotactic  protein-­‐1  MHC         Major  histocompatibility  complex    MIP-­‐1β       Macrophage  inflammatory  protein-­‐1  beta  NK  cell         Natural  killer  cell  OR         Odds  ratio  PAP         Physical  activity  on  prescription  Q-­‐FISH         Quantitative  fluorescence  in  situ  hybridization  RCC         Renal  cell  carcinoma  RTM         Regression  to  the  mean  RT-­‐PCR       Real-­‐time  polymerase  chain  reaction    SSB         Single-­‐strand  DNA  breaks  STELA         Single  telomere  length  analysis  TA         Telomerase  activity  T/N         Tumor  to  non-­‐tumor  TNM         Tumor  Node  Metastasis  Tregs         Regulatory  T  cells  TRF         Terminal  restriction  fragment  T/S  ratio       Telomere  repeat  copy  number  to  single-­‐copy  gene  copy  number                        

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POPULÄRVETENSKAPLIG  SAMMANFATTNING        Inuti   våra  cellers   cellkärna   finns  arvsmassan,  DNA,   innehållande  gener   som  kodar   för  olika   proteiner.   DNA-­‐strängarna   är   organiserade   i   så   kallade   kromosomer   och   i  ändarna   av   dessa   återfinns   telomererna.     Hos  människan   består  telomererna  av   den  repetitiva   DNA-­‐sekvensen   TTAGGG   tillsammans   med   associerade   proteiner.  Telomererna  har  en  mycket  viktig  roll  eftersom  de  skyddar  kromosomändarna  från  att  skadas   och   brytas   ned.   Inför   varje   celldelning   kopieras   kromosomerna   i   en   process  kallad   replikation   och   under   denna   process   sker   i   de   flesta   celler   en   förkortning   av  telomererna.   Eftersom   telomerer   inte   innehåller   några   informationsbärande   gener  förloras   dock   inget   viktigt   genetiskt   material.   Så   småningom   nås   dock   en  kritisk  telomerlängd  där  kromosomerna  riskerar  att  skadas  vid  fortsatt  förkortning.  Då  aktiveras  speciella   signalvägar   som  gör  att   cellen  permanent   slutar   att  dela   sig.  Vissa  celler   har   dock  förmågan  att   förhindra   telomerförkortning   genom   att  aktivera   ett  enzym,   telomeras,  som   förlänger   telomererna.   Telomeras   är   inaktivt   hos   de   flesta  normala   celler,   med   undantag   för   t.ex.   stamceller,   könsceller   och   vissa   celler   inom  immunförsvaret.   Däremot   är   telomeras   aktivt   i   de   flesta   cancerceller,   vilket   gör   att  dessa   celler   kan   bibehålla   sina   telomerer.   På   så   sätt   erhåller   de   potential   att   kunna  dela  sig   i  det  oändliga.  En  rad   faktorer   tros  ha  en   inverkan  på  telomerlängden,  bland  annat   ärftlighet,   hormoner,   livsstil   och   omgivningsfaktorer.   Generellt   ses   även   en  förkortning   av   telomerlängden   med   åldern,   även   om   det   råder   stor   spridning   i  telomerlängd  mellan  personer  i  samma  åldrar.    Cancer   utgörs   av   en   rad  olika   tumörsjukdomar   (maligniteter)  med  det   gemensamma  att   celler   börjat   dela   sig   okontrollerat   på   grund   av   förändringar/mutationer   i  arvsmassan.  Godartade  tumörer  kallas  benigna  och  växer  lokalt,  medan  cancer  utgörs  av  maligna  tumörer  med  potentiell  förmåga  att  sprida  sig  till  andra  vävnader  i  kroppen,  s.k.  metastasering.  Det  har   länge  pågått   intensiv  forskning  kring  att  hitta  pålitliga  och  lättanalyserade   molekyler   i   kroppen,   biologiska   markörer,   som   kan   förutsäga  exempelvis  insjuknanderisk,  överlevnadstid  (prognos)  och/eller  behandlingsresultat  vid  cancersjukdom.   De   senaste   åren   har   allt   fler   forskare   intresserat   sig   för   om  telomerernas   längd   kan   agera   biologisk  markör   vid   en   rad   olika   sjukdomar.   Speciellt  har   intresset   för  att  analysera  telomerlängden   i  blodets  celler,  mer  specifikt   i  blodets  immunceller,  ökat.  Blod  är  en  lättillgänglig  vävnad  och  blodcellernas  telomerlängd  har  visat   sig   korrelera  med   andra   vävnaders   telomerlängd.   En   rad  studier   har   dessutom  observerat   signifikanta   skillnader   i   medellängd   mellan   friska   kontrollpersoners  blodtelomerer   och   telomererna   hos   patienter   med   diverse   åldersrelaterade  sjukdomar,  däribland  cancer.      Ett  av  målen  med  detta  forskningsprojekt  har  varit  att  undersöka  om  telomerlängd  kan  ge   information   om   risk   och/eller   prognos   vid   malignitet.   Fokus   har   legat   på  telomerlängdsanalys   hos   patienter   med   nydiagnosticerad   bröstcancer   respektive  njurcancer.   I   den   första   delstudien   observerades   att   bröstcancerpatienter   hade  signifikant  längre  blodtelomerer  jämfört  med  en  tumörfri  kontrollgrupp.  Vidare  visade  sig  patienterna  med  längst  blodtelomerer  ha  en  sämre  prognos  jämfört  med  patienter  

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med   kortare   telomerlängd.  I   den   andra   delstudien,   vilken   inkluderade  patienter  med  klarcellig   njurcancer,   analyserades   telomerlängden   dels   i   perifera   blodceller,   dels   i  tumörvävnad   och   i   närliggande   tumörfri   njurvävnad.   Liknande   som   för  bröstcancerpatienterna  fann  vi  att  njurcancerpatienter  med  långa  blodtelomerer  hade  en   sämre   överlevnadstid   jämfört   med   patienter   med   kortare   telomerer.   I   två   olika  cancergrupper   visade   sig   alltså   blodtelomerlängd   bära   på   prognostisk   information.  Däremot   var   inte   telomerlängden   i   tumörvävnad   eller   korresponderande   tumörfri  njurvävnad  signifikant  kopplad  till  prognos.    Immunsystemet  skyddar  oss  mot  sjukdomsalstrande  agens  och  tros  även  vara  viktigt  i  vårt  försvar  mot  cancer.  Systemet  är  komplext  och  består  av  olika  sorters  immunceller  och   diverse   molekyler.   Komponenter   inom   immunförsvaret   kan   dock   även  orsaka  vävnadsskada   och   vissa   immunologiska   faktorer   tycks   snarare   gynna  cancercellernas   tillväxt   än   tvärtom.   Vi   spekulerade   i   att   cancerpatienter   med   långa  blodtelomerer   eventuellt   uppvisade   sämre   prognos   på   grund   av   ett  mindre   effektivt  immunförsvar.  Mindre  aktiva   immunceller   bör,   åtminstone   i   teorin,   kunna   bibehålla  telomerlängden   i   högre   grad   på   grund   av   färre   celldelningar.  Det   finns   speciella  immunceller,   regulatoriska   T-­‐celler   (Tregs),  med   en   hämmande   funktion   på   delar   av  immunförsvaret.  De  tros  bland  annat  skydda  mot  autoimmuna  sjukdomar,  men  höjda  nivåer   av   Tregs   har   också  kopplats   till   sämre   prognos   i   flera   cancerstudier.   I   en   av  studierna   i   detta   arbete   fann   vi   att   njurcancerpatienter   med   långa   blodtelomerer  tenderade   att   ha   högre   nivåer   av   T-­‐regs,   vilket   stämmer  med   vår   hypotes.  Andra  immunologiska   komponenter   kan   också   ha   en   inverkan   på   telomerlängden.   Till  exempel  har   en  del   signalmolekyler   (cytokiner)   inom   immunförsvaret   visat   sig   kunna  stimulera  telomeras.   Vi   mätte   ett   antal   olika   cytokiner   hos   vår   patientgrupp   med  klarcellig   njurcancer   och   fann   att   höjda   nivåer   av   vissa   cytokiner   korrelerade   med  längre  telomerer  i  tumörvävnaden.      Ett   ytterligare   mål   var   att   undersöka   hur   telomerlängden   förändras   över   tid.   På   en  grupp   jämnåriga   (och   överviktiga)   individer   mättes   telomerlängden   i   blodprov  insamlade  med  6  månaders  intervall.  Vi  fann  att  hälften  av  individerna  förkortade  sina  telomerer  under  denna  period,  medan  övriga  uppvisade  stabil  eller  ökad  telomerlängd.  De   individer  med   längst   blodtelomerer   vid   första   provtagningstillfället   tenderade   att  förkorta   sina   telomerer   mest   och   vice   versa.   Resultatet   stämmer   överens   med   en  tidigare   studie   från   vår   forskargrupp   där   uppföljningstiden   var   längre   (10   år).   I   en  parallell  studie  på  fem  blodgivare  fann  vi  att  en  av  dessa  blodgivare  uppvisade  en  tydlig  telomerförkortning   under   en   6-­‐månadersperiod,   medan   övriga   låg   mer   stabilt   i   sin  blodtelomerlängd.    Sammanfattningsvis   tyder   resultaten   i  denna  avhandling  på  att  blodtelomerlängd  har  potential  att  agera  prognostisk  markör  vid  cancersjukdom.  Detta  skulle  i  sin  tur  kunna  ha  betydelse   för   framtida  behandlingsstrategier.  En  komplicerande   faktor  är  dock  att  telomerlängden  hos  blodceller  tycks  kunna  förändras  under  relativt  korta  tidsperioder.  Av  den  anledningen  är  det  sannolikt  bäst  att  göra  upprepade  mätningar  av  en  patients  blodtelomerlängd.

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I  N  T  R  O  D  U  C  T  I  O  N      TELOMERE  BIOLOGY      IT  STARTS  WITH  THE  END    Telomeres   are   specialized   chromosomal   structures   composed   of   tandem  repeats   of   the  DNA   sequence   "TTAGGG"   together  with   specific   proteins.   The  word   telomere   is   derived   from   the   Greek   terms   telos   ("end")   and   meros  ("part"),   hence   "end   part".   As   the   name   hints,   telomeres   are   located   at   the  very   end   of   eukaryotic   chromosomes   and   they   are   essential   for  maintaining  chromosomal  stability.   In  humans,  telomeres  typically  range  between  5  to  15  kilobase  pairs  in  length,  and  terminate  in  a  guanine  (G)-­‐rich  overhang  of  single  stranded  DNA  [1].  Telomeric  DNA  is  organized  into  loop  structures  which  act  as  a  protective  cap,  preventing  chromosomal  end-­‐to-­‐end  fusions,  rearrangements  and  exonucleolytic  degradation  (Figure  1)  [1]  [2].  Six  proteins  form  a  telomere-­‐specific   complex   (the   Shelterin   complex),  which  promotes   the   formation   and  stabilization  of  these  telomeric  loops  [2].    Normally,  telomeres  shorten  with  each  cell  division  due  to  the  inability  of  DNA  polymerase   to   completely   synthesize   the   lagging   strand   during   DNA  replication,  the  so  called  "end-­‐replication  problem"  [3].  Approximately  50-­‐200  base  pairs  are  lost  during  each  round  of  replication  until,  eventually,  a  critical  length   is   reached   (Hayflick's   limit)   [4]   [5].   Functional   telomeres   prevent   the  chromosome  ends  from  being  recognized  as  DNA  breaks  by  cellular  DNA-­‐repair  systems.   Critically   short   telomeres,   however,   are   dysfunctional   and   are  therefore   detected   as   damaged  DNA,   leading   to   senescence   (permanent   cell  cycle   arrest)   and/or   cell   death   through   apoptosis   [6]   [7].   Thus,   a   limited  number  of  cell  divisions  can  occur  before  senescence   is  triggered   in  a  normal  somatic   cell.   Telomere   length   is   hence   a   determinant   factor   for   cellular  replicative  capacity   [5].  For   this   reason,   telomeres  are  sometimes   referred   to  as  a  "biological  clock"  of  the  cell.                      

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             Figure  1  –  From  chromosome  to  telomere.  Simplified  scheme  showing  the  telomeric  structure   at   the   chromosome   end.   The   G-­‐rich   single-­‐stranded   overhang   is   normally  concealed  inside  the  loop  structure.      THE  TELOMERASE  ENZYME    The  progressive  loss  of  telomeric  DNA  with  each  cell  division  can  be  prevented  in  the  presence  of  a  telomere-­‐elongating  enzyme  called  telomerase  [8]  (Figure  2).   Telomerase   is   a   reverse   transcriptase   composed   of   the   catalytic   subunit  hTERT  and  the  RNA  template  hTR,  and  it  acts  by  adding  TTAGGG  repeats  onto  the  chromosome  end  [9].  hTR,  in  contrast  to  hTERT,  is  constitutively  expressed  in   human   cells;   hTERT   is   therefore   considered   to   be   the   rate-­‐limiting  determinant  of   telomerase  activity   [9].  Most   somatic   cells  have  undetectable  levels   of   telomerase   activity,   but   the   enzyme   is   active   during   embryogenesis  and   in   certain  normal   somatic   cell   types,   such  as   germ  cells,   adult   stem  cells  and  in  activated  immune  cells  [10].  In  addition,  the  majority  of  cancer  cells  (85-­‐90%)   [11]   show   telomerase   activity,   allowing   them   telomere   maintenance,  long-­‐term   growth   and   immortalization.   Findings   have   indicated   that  telomerase  acts  preferentially  on  the  shortest   telomeres,  most   likely  because  these   telomeres  have  a  more  disrupted  structure  and  are  more  accessible   to  telomerase  [12]  [13].  There  is  no  obvious  correlation  between  telomere  length  and  telomerase  activity,  as  exemplified  by  the  fact  that  most  tumor  cells  have  shorter  telomeres  than  their  corresponding  normal  tissue,  despite  telomerase  activity  [14].    

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                                 Figure  2  –  The  telomerase  enzyme.  Telomerase  consists  of  the  catalytic  subunit  hTERT  and   the   RNA-­‐template   hTR,   together   with   associated   proteins   (not   shown).   The  enzyme  adds  TTAGGG  repeats  to  the  3’-­‐end  of  telomeric  DNA.      FACTORS  INFLUENCING  TELOMERE  LENGTH    Telomeres  differ  considerably   in   length  between   individuals,  across  cell   types  and  even  among  individual  chromosome  arms.  At  the  same  time,  there  is  often  a  significant  correlation  in  telomere  length  between  different  tissues  within  an  individual  [15]  [16].    Several   studies   have   indicated   that   telomere   length   is   partly   genetically  determined   and   the   heritability   has   been   estimated   to   range   from   36%   to   >  80%   [17]   [18]   [19]   [20]   [21].   Both  paternal   and  X-­‐linked   inheritance  patterns  have  been  proposed,  but  the  paternal  influence  seems  to  be  the  strongest  [20]  [22]   [23]   [24].   A   few   loci   believed   to   be   of   importance   for   telomere   length  variations  have  also  been  mapped   [19]   [21],  but  genes  with  direct  effects  on  telomere   length   remain   largely   unknown.   Plausible   candidates   are   the   two  major   genes   associated   with   the   telomerase   enzyme   (hTERT   and   hTR).  Accordingly,   it   was   recently   reported   that   variations   in   these   genes   were  associated  with  better  telomere  length  maintenance  [25].  However,  it  has  also  been   shown   that   parent-­‐child   correlations   of   telomere   length   weaken   with  increasing   age   [24],   supporting   the   notion   that   non-­‐heritable/environmental  factors  influence  telomere  length  dynamics  during  life.    Apart  from  genetic  factors,  telomere  maintenance  is  affected  by  e.g.  oxidative  

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stress,   hormones   and   epigenetic   modifications   of   the   chromatin   [26].  Epigenetic   events   include   telomeric   histone   modifications   and   DNA  methylation   of   subtelomeric   regions   and   there   is   evidence   of   an   association  between  epigenetic  alterations  and  telomere  length  deregulation  [27].    Oxidative   stress   (i.e.   imbalance   between   oxidative   and   antioxidative  processes),  which   is  often  associated  with   inflammatory  processes  and   tissue  aging,   is   believed   to   be   an   important   cause   of   telomere   shortening   [28].  Oxidative   stress   can   cause   DNA   damage   in   several   different   ways,   including  oxidation   of   bases   and   formation   of   single/double-­‐strand  breaks   (SSBs/DSBs)  [29]   [30].   Because   of   their   G-­‐richness,   telomeres   are   highly   sensitive   to  oxidative  species   [31]   [32].   In  addition,  compared  to  the  bulk  of   the  genome,  the   repair   of   SSBs   is   less   efficient   in   telomeres   [33].   As   a   consequence,  telomeric   DNA   is   prone   to   enter   replication   with   a   higher   degree   of   single-­‐strand  breaks,  resulting  in  enhanced  telomere  shortening  [30].  Oxidative  stress  has   been   linked   to   the   pathology   of   a   variety   of   diseases,   including  atherosclerosis,   diabetes,   neurodegenerative   disorders,   cancer   and  inflammatory   diseases   [34].   In   accordance,   such   diseases   have   also   been  associated  with  alterations  in  telomere  length  [35].    As   an   example   of   hormonal   impact,   estrogen   has   been   shown   to   influence  telomere  dynamics  through  several  different  mechanisms,  including  activation  of   the   hTERT   gene   promoter,   posttranscriptional   regulation   of   hTERT   and  through   antioxidative   capacity   [36]   [37]   [38].   Studies   have   also   shown   that  women  display  longer  telomeres  than  men  and  estrogen  has  been  proposed  as  the  most   likely  candidate  for  this  gender  difference  [39]  [40].  Components  of  the   immune   system   may   also   influence   telomere   length   dynamics.   For  example,   several   cytokines   (i.e.   signaling   molecules   involved   in   immune  responses)  have  shown  potential  to  activate  the  telomerase  enzyme  [41]  [42]  [43]  [44]  [45].      In   recent  years,  a  number  of   studies  have  shown  that   individuals  with   longer  telomere   length  at  baseline  exhibit  a   faster   telomere  attrition  rate  compared  to  those  with  shorter  baseline  telomere   length  [46]  [47]  [48]  [49]  [50].  These  findings  may  reflect  a  regulatory  machinery  giving  priority   to  short   telomeres  and/or   that   long   telomeres   are   more   susceptible   to   telomere-­‐damaging  factors,  such  as  oxidative  stress.      Altogether,  the  collected  data  indicate  that  telomere  length  is  a  complex  trait  determined   by   a   variety   of   components,   including   genetic,   epigenetic   and  environmental  factors.  

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TELOMERE  LENGTH  IN  PERIPHERAL  BLOOD  CELLS    The  hematopoietic  and  immune  system  -­‐  an  overview    The   blood   system   comprises   a   variety   of   different   cell   types,   which   can   be  broadly   divided   into   red   blood   cells   (erythrocytes),   white   blood   cells  (leukocytes)   and   platelets.   These   cells   are   all   derived   from   common  hematopoietic   stem   cells   (HSCs)   in   the   bone   marrow.   HSCs   give   rise   to  multipotent   progenitors,   which   in   turn   give   rise   to   oligopotent   progenitors  with  more   restricted   lineage   potential   [51].  Ultimately,   the   different   effector  blood  cells  are  formed,  as  illustrated  by  Figure  3.    

 

 

       Figure   3   -­‐   Simplified  diagram  of   hematopoiesis.   The  different   peripheral   blood   cells  are   derived   from   lineage-­‐committed   progenitor   cells   (all   not   shown),   which   in   turn  originate  from  multipotent  hematopoietic  stem  cells  with  self-­‐renewal  capacity.            

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Leukocytes,   the   cells   of   the   immune   system,   derive   from   the   myeloid   and  lymphoid   lineages.   More   specifically,   the   myeloid   progenitors   give   rise   to  granulocytes   (i.e.   neutrophils,   basophils   and   eosinophils)   and   monocytes/  macrophages,   whereas   the   lymphoid   lineage   produces   T   and   B   lymphocytes  and  natural  killer  (NK)  cells  [52].  Neutrophils  normally  accounts  for  50-­‐70%  of  the   peripheral   leukocytes,   whereas   circulating   lymphocytes   (the   majority   of  which  are  T  cells)  comprise  20-­‐40%  of  the  blood  leukocyte  count.    The   immune   system   is   a   complex   biological   system   that   can   be   broadly  classified  into  two  branches:  the  innate  and  adaptive  immune  systems.  Cells  of  the  myeloid   lineage,   along  with  NK   cells,   are  primarily   involved   in   the   innate  immune  response,  serving  as  a  first  line  of  defense.  Lymphocytes  on  the  other  hand   are   key   players   in   the   adaptive   immune   response,   which   relies   on   the  recognition   of   specific   antigens.   These   cells   circulate   between   the   blood   and  lymphoid  organs  throughout  the  body.  Whereas  B  lymphocytes  mature  in  the  bone   marrow,   the   maturation   of   T   lymphocytes   occurs   in   the   thymus.   T  lymphocytes   can  be  divided   into   two  major  groups:  CD4+  T   cells   and  CD8+  T  cytotoxic  cells.  CD4+  T  cells  can  be  further  subdivided  into  e.g.  T  helper  subsets  and   regulatory   T   cells   (Tregs).   In   brief,   T   helper   cells   are   involved   in   the  stimulation  of  cytotoxic  T  cells  to  destroy  target  cells  infected  with  intracellular  pathogens,   and   of   B   cells   to   produce   pathogen-­‐recognizing   antibodies   [53].  Tregs   possess   regulatory/suppressive   properties   and   are   of   importance   for  peripheral  self-­‐tolerance  and  immune  suppression  [54].  Their  suggested  role  in  cancer  disease  will  be  discussed  further  below.    Naïve  mature   lymphocytes   are   those   that   have   not   yet   encountered   foreign  antigens.  Upon  contact  with  an  antigen,  an  enormous  number  of  effector  cells  are   formed   through  clonal   expansion   of   the   selected   naïve   cell.   When   the  immune   challenge   is   eliminated  most   effector   cells   undergo   apoptosis,   but   a  few   cells   become   long-­‐lived   memory   cells   that   respond   rapidly   upon   re-­‐encounter  with  the  same  antigen  [53].  Like  other  tissues,  there  are  age-­‐related  changes  of  the  immune  system.  For  example,  there  is  a  shift  in  the  proportion  of   different   blood   cell   subpopulations   with   age,   including   a   decrease   in  lymphocytes   and   an   increase   in   monocytes,   as   well   as   a   shift   from   naïve  lymphocytes  towards  memory  cells  [55].              

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Blood  telomere  length  in  health  and  disease    Blood   telomere   length,   in   this   context   referring   to   the   telomere   length   of  peripheral   blood   leukocytes,   is   often   used   as   a   proxy   for   telomere   length   in  other   normal   tissues.   As   already   mentioned,   there   is   generally   a   good  correlation   in   telomere   length   between   different   tissue   compartments   of   an  individual,  and  blood   is  an  easily  accessible  tissue.  For   this   reason,  peripheral  blood  leukocytes  have  been  in  the  focus  of  human  telomere  research  for  many  years.   Well-­‐established   features   include   large   variations   in   mean   blood  telomere   length  between   individuals  of   similar   ages   [17]   [18]   [56]   [57]   and  a  decline   in   telomere   length   over   time   [56]   [58]   [59]   [60]   [61],  with   the  most  rapid  loss  occurring  during  early  childhood  [57]  [58].    Over  the  last  decade,  a  large  number  of  studies  have  associated  alterations  in  blood  telomere   length  to  various  age-­‐related  diseases,  such  as  cardiovascular  disease,   diabetes   and   cancer   [62]   [63]   [64]   [65]   [66]   [67]   [68].   Also   lifestyle  factors,   such   as   physical   activity,   stress,   smoking   and   socio-­‐economic   status,  have   been   related   to   blood   telomere   length   [69]   [70]   [71].   The   majority   of  studies   have   found   significant   associations   between   short   blood   telomere  length   and   disease,   but   the   underlying  mechanisms   are   not   yet   understood.  Whether   alterations   in   blood   telomere   length   contribute   directly   to   disease  development,  whether  they  reflect  ongoing  processes   leading  to  disease  or   if  the  disease   itself   (or   its   treatment)  causes  changes   in  blood   telomere   length,  remains   to   be   further   elucidated.   It   should   also   be   mentioned   that   several  studies   have   been   unable   to   find   any   significant   associations   between   blood  telomere  length  and  pathological  conditions,  as  summarized  in  [72].      Telomeres  and  telomerase  in  blood  cell  subpopulations    Clonal   cell   expansion   is   crucial   for   both   B   and   T   lymphocyte   function   and  among   the   peripheral   immune   cells,   only   activated   lymphocytes   express  telomerase   activity   [73].   These   cells   thus   possess   mechanisms   for   telomere  maintenance,   enabling   them   increased   replicative   potential.   However,  telomerase  activity  levels  are  not  sufficient  to  fully  inhibit  telomere  shortening  [74].  Accordingly,  memory  T  cells  display  shorter  telomeres  compared  to  their  naïve   counterparts   [57]   [75],   indicating   that   T   cell   differentiation   results   in  telomere   shortening.   B   cells,   on   the   other   hand,   exhibit   a   slower   age-­‐dependent   telomere   loss   compared   to   T   cells   [59]   [76]   and   telomeres   in  memory   B   cells   have   been   found   to   be   of   similar   length   [77]   [78]   or   even  longer   [59]   than   in   naïve   B-­‐cells.   These   findings   suggest   that   B   cells   employ  

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different  mechanisms  for  telomere  maintenance  compared  to  T-­‐cells  [59]  [78].      In  contrast  to  lymphocytes  and  bone  marrow  progenitor  cells,  mature  cells  of  the  myeloid  lineage  do  not  undergo  cell  proliferation  and  show  no  expression  of   telomerase   [79].   Telomere   shortening   in   these   cells   therefore   reflects  telomeric   loss   at   the   progenitor   cell   level   [26].   In   accordance,   the   telomere  length   of   bone   marrow   progenitor   cells   was   found   to   correlate   strongly   to  blood  granulocyte  telomere  length  but  more  weakly  (although  significantly)  to  the   telomere   length   of   lymphocytes   [80].   Furthermore,   granulocytes   have  been  shown  to  display   longer  telomeres  than   lymphocytes   in  adults,  and  also  to  exhibit  a  slower  age-­‐dependent  decline  in  telomere  length  [40]  [57]  [81].      Thus,   telomeres   vary   in   length   among   different   immune   cell   subsets.  Blood/leukocyte   telomere   length   therefore   represents   the   average   telomere  length  of  a  heterogeneous  group  of  blood  cells.                                                      

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APPROACHES  FOR  TELOMERE  LENGTH  ESTIMATION  –  A  SUMMARY    There  are  several  methods  in  use  for  telomere  length  analysis.  Table  1  provides  a  summary  of  advantages  and  disadvantages  for  each  method.      Southern   blot   is   often   described   as   the   golden   standard   for   telomere   length  measurements.   In   this   method,   DNA   is   cut   in   the   subtelomeric   regions   by  restriction  enzymes  to  generate  terminal   restriction   fragments   (TRF).   In  brief,  the  cut  DNA   is   separated  by  electrophoresis,   transferred   to  a  membrane  and  hybridized   with   a   labeled   telomere-­‐specific   probe.   The   resulting   smear-­‐like  signal   is   converted   into   an   actual   telomere   length   in   kilo   base  pairs   by   using  various   algorithms.   The   method   is   for   example   useful   when   comparing  telomere  lengths  between  and  within  different  cell  populations.    A   widely   used   approach   for   telomere   length   evaluation   is   the   qPCR-­‐based  method   originally   developed   by   Richard   Cawthon   in   2002   [82].   This  method,  sometimes  referred  to  as  "Tel-­‐PCR",  is  based  on  a  primer  design  with  flapping  3'  ends,  minimizing  the  risk  of  primer  dimer  formation.  The  method  provides  a  ratio  between  the  telomere  repeat  copy  number  (T)  and  single-­‐copy  gene  copy  number  (S),  which  is  proportional  to  the  average  telomere  length.  T/S  ratios  of  unknown   samples   are   compared   to   the   T/S   ratio   of   a   reference   DNA,  generating   relative   values   of   telomere   lengths.   Hence,   a   relative   telomere  length   value  of   1  means   that   the   sample  DNA  has   the   same  T/S   ratio   as   the  reference   DNA.  More   recently   a   promising  multiplex   version   of   this  method  was   presented   by   Cawthon,   showing   a   high   reproducibility   and   a   strong  correlation  to  the  Southern  blot  method  [83].    A   slot   blot   technique,   in   which   denatured   and   filter   cross-­‐linked   DNA   is  hybridized   to   a   labeled   telomere-­‐specific   probe,   has   been   presented   as   a  useful  method   for  estimation  of   telomeric  DNA  content   in   formalin   fixed  and  paraffin  embedded  tissues  [84]  [85].  Extracted  DNA  from  such  tissues  is  often  of   poor   quality,   making   Southern   blot   and   qPCR   less   suitable.   The   slot   blot  method  at  least  provides  a  rough  estimation  of  tissue  telomere  lengths.      In   Q-­‐FISH   (quantitative   fluorescence   in   situ   hybridization),   telomeres   can   be  visualized   and   quantified   in   metaphase   spreads   and   interphase   cells   by  measuring  the  fluorescence  signal  from  a  telomeric  peptide  nucleic  acid  probe    [86]   [87].   Flow-­‐FISH,  which   is  based  on   flow  cytometric  analysis,   is   a   suitable  method  for  telomere  length  analysis  of  cells   in  suspension  [88]  [89].  FISH  and  immunostaining   can  also  be  performed   simultaneously,  making   it   possible   to  identify  specific  cell  types  among  a  mixture  of  cells.  

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Finally,   STELA   (single   telomere   length   analysis)   is   a   PCR-­‐based   technique   for  analysis   of   individual   telomeres,   taking   advantage   of   chromosome   specific  subtelomeric  regions  [90].        TABLE  1    -­‐  A  summary  of  methods  for  telomere  length  assessment  

METHOD   ADVANTAGES   DISADVANTAGES    Southern  blot  analysis  

"Golden  standard";  generates  telomere  length  distributions  in  kilobase  pairs.  

Time-­‐consuming;  requires  large  amounts  of  DNA  (5-­‐10  µg);  the  subtelomeric  region  is  included;  variability  in  interpretation  across  laboratories.  

 qPCR                    (Tel-­‐PCR)    

Large  sets  of  samples  can  be  analyzed  within  relatively  short  time  spans;  requires  small  amounts  of  DNA  (ng  range).    

Standard  protocols  are  lacking  and  results  are  presented  differently  across  laboratories;  does  not  provide  actual  telomere  lengths  but  rather  the  mean  relative  telomere  content  of  a  sample.  

 Slot  blot  assay  

Can  be  used  on  fixed  tissues  where  the  DNA  quality  is  poor;  requires  low  amounts  of  DNA.  

Provides  the  mean  telomere  content,  not  actual  lengths;  no  detection  of  cell  type-­‐specific  telomere  lengths.  

 Q-­‐FISH  

Telomeres  can  be  analyzed  in  fixed  tissues  and  in  a  cell-­‐specific  manner;  informative  in  analyses  of  metaphase  spreads  and  interphase  cells.    

Many  factors  can  affect  the  hybridization  process;  difficult  to  compare  results  across  laboratories;  does  not  provide  actual  telomere  lengths.    

 Flow-­‐FISH  

Useful  for  telomere  length  analysis  of  hematopoietic  cells  in  suspension;  provides  telomere  length  distributions;  cells  can  be  analyzed  in  combination  with  immunostaining.    

Laborious;  cannot  be  performed  on  fixed  tissues.    

 STELA  

Detects  the  telomere  length  of  individual  chromosomes;  possible  to  visualize  extremely  short  telomeres.    

Laborious;  primers  have  not  been  developed  for  all  chromosome  arms;  difficult  to  analyze  very  long  telomeres.  

Modified  after  ref.  [91]  

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TUMOR  BIOLOGY        THE  HALLMARKS  OF  CANCER    Cancer  comprises  a  complex  and  diverse  group  of  diseases  with  multifactorial  origins.  A   large   amount   of   data   suggest   that   malignant   cells   arise   through  multistep   events,   reflecting   an   accumulation   of   genetic   alterations,   such   as  deletions,   translocations   or   amplifications   of   DNA   sequences,   as   well   as  epigenetic   alterations.   These   changes   might   result   in   a   loss   of   tumor  suppressors  and  activation  of  oncogenes,  leading  to  an  uncontrolled  cell  cycle.      In  the  year  of  2000,  Hanahan  and  Weinberg  proposed  six  hallmarks  of  cancer  which  together  enable  malignant  growth:  evasion  of  growth  suppressors,  self-­‐sufficiency   in   growth   signals,   ability   to   resist   cell   death,   ability   to   induce  angiogenesis,  gain  of  replicative  immortality,  and  ability  of  tissue  invasion  and  metastasis   [92].   These   capabilities   provide   the   basis   for   understanding   the  development   and   progression   of   diverse   human   tumors.   Recently,   the   same  authors   presented   two   additional   (emerging)   hallmarks:   deregulation   of  energy   metabolism   and   evasion   of   immune   destruction   [93].   In   addition,  "genome  instability  and  mutation"  and  "tumor-­‐promoting  inflammation"  were  described   as   enabling   characteristics,  underlying   the   cancer   hallmarks.   An  overview  of  all  proposed  features  is  presented  in  Figure  4.      TUMORS  AND  TELOMERES    Telomere  dysfunction  has  dual  roles  in  carcinogenesis  since  it  can  either  trigger  or  suppress  tumor  growth  [14]  (Figure  5).  If  functional  DNA  damage  pathways  are  present,   cells  with  critically   short   telomeres  enter   replicative  senescence,  which  thus  functions  as  an  important  tumor  suppressor  mechanism.  However,  cells  with   inactivated  cell  cycle  checkpoints  might  circumvent  this  barrier  and  continue  to  divide  with  extremely  short  telomeres,  along  with  an  accumulation  of   genetic   alterations.   One   mechanism   through   which   telomeric   loss   causes  genomic   instability   is   via   the   breakage-­‐fusion-­‐bridge   (B-­‐F-­‐B)   cycle,   which  involves  the   fusion  of  uncapped  chromosome  ends  and  subsequent  breakage  during  mitosis   [94].  Since  breakage  occurs  at  a  position  other  than  the  fusion  site,  one  chromosome  will  experience  a  gain  of  DNA  while  the  other  will  have  a  loss   of   DNA.   Cells   with   disabled   checkpoints   accumulate   chromosomal  aberrations  through  recurrent  B-­‐F-­‐B  cycles,  eventually  leading  to  a  crisis  phase  in  which  most  cells  die   [94].  On   rare  occasion,  a   few  cells  are  able   to  escape  

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from  crisis  by  activating  mechanisms  for  telomere  stabilization,  either  through  reactivation  of  telomerase  or,  more  rarely,  through  Alternative  lengthening  of  telomeres  (ALT)  which  involves  homologous  recombination  [95].  The  ability  of  maintaining  telomeres  through  these  mechanisms  is  a  typical  feature  of  cancer  cells,   enabling   them   indefinite   growth   [96].  Gain   of   replicative   immortality   is  also  one  of  the  hallmarks  of  cancer,  as  described  above.        

   Figure   4     -­‐   The   hallmarks   of   cancer.   In   2011,   Hanahan   and   Weinberg   added   two  "emerging   hallmarks"   and   two   "enabling   characteristics"   to   their   proposed   list   of  common  cancer  traits,  believed  to  underlie  tumor  development  and  progression  [93].      

Several   studies   have   reported   that   telomere   length   in   solid   tumors   has  potential   to   act   as   a   prognostic   biomarker,   as   summarized   in   previous   and  recent  reviews  [68]  [91]  [97].  The  average  telomere  length  of  a  tumor  reflects  the   combined   result   of   various   tumor-­‐associated   factors   with   impact   on  telomere  homeostasis,  which  might  vary  depending  on  the  specific  tumor  type  and   the   tumor   microenvironment.  The   majority   of   studies   have   shown  significant  associations  between  altered   tumor   telomere   length  and  a  poorer  clinical   outcome,   but   the   direction   of   the   alterations   (i.e.   short   vs.   long  telomere   length)   appears   to   be   tissue   dependent.   At   the   present   time,   the  underlying   mechanisms   are   unclear   and   remain   to   be   further   elucidated.        

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     Figure   5   -­‐   The   dual   role   of   telomere   shortening   in   carcinogenesis.   Telomere  shortening  to  a  critical  length  normally  induces  replicative  senescence,  causing  cells  to  stop   dividing.   However,   short   telomeres   are   also   associated  with   increased   genomic  instability  and  in  the  absence  of  functional  cell  cycle  checkpoints,  senescence  may  be  circumvented.   Subsequent   activation   of   telomerase   (or   more   rarely   ALT)   leads   to  telomere  stabilization  and  limitless  growth  capacity,  which  is  characteristic  for  cancer  cells.  (Figure  modified  after  ref.  [98].)          THE  IMMUNE  SYSTEM  AND  CANCER    During   the   last  decade   it  has  become  clear   that   the   immune  system  plays  an  essential   role   in   cancer   disease,   but   the   role   seems   to   be   double-­‐edged.   On  one   hand,   cells   of   the   immune   system   might   limit   cancer   development   by  recognizing  and  destroying  tumor  cells  (so  called  immune  surveillance).  On  the  other   hand,   tumor   cells   can   modify   the   immune   reactivity,   promote  inflammation   and   gain   ability   to   evade   immune   destruction   [93].  Data   from  immunosuppressed   patients   have   revealed   significant   increases   in   the  incidence   of   a   variety   of   tumors   [99],   supporting   the   theory   that   a   healthy  immune   system   is   important   for   cancer   protection.  Cavallo   et   al.   recently  described  three  major  immune  hallmarks  of  cancer,  namely  the  ability  to  thrive  in   a   chronically   inflamed   microenvironment,   ability   to   evade   immune  recognition,  and  ability   to   suppress   immune   reactivity   [100].  Mechanisms   for  evading   immune   recognition   include   downregulation   of   glycoproteins   of   the  

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major   histocompatibility   complex   (MHC)   located   on   the   cell   membrane,  thereby  inhibiting  the  recognition  of  MHC-­‐associated  tumor  peptides  by  T  cells  [100].  Suppression   of   immunological   reactivity   can   be   achieved   by   the  recruitment  of   regulatory   T   cells.  As  mentioned  above,   Tregs   are   suppressive  cells   involved   in   the   protection   against   autoimmunity,   but   they   are   also  believed   to   be  key   players   in   establishing   tumor   immune   tolerance   [54].  Increased  levels  of  Tregs  have  been  detected  in  a  variety  of  cancers  [101]  and  they   are   thought   to   act   through   several   mechanisms,   including  cytolytic  activity,   secretion   of   immunosuppressive   mediators   [e.g.   interleukin   (IL)-­‐10  and   transforming   growth   factor   (TGF)-­‐β],   metabolic   disruption   of   effector   T  cells,   and   suppressive   interactions   with   dendritic   cells   [54]   [102].   Another  feature  of  cancerous   tissue   is   the  presence  of  a  variety  of  cytokines  secreted  by   cells   in   the   tumor  microenvironment   and   by   the   tumor   cells   themselves.  The  role  of  these  cytokines  in  carcinogenesis  is  dual:  they  might  inhibit  tumor  growth   by   mediating   anti-­‐tumor   responses,   but   their   presence   might   also  contribute   to   create   a   tumor-­‐favorable  microenvironment   [103]   [104].   As   an  example,   IL-­‐6   has   been   shown   to   stimulate   tumor   growth   and  metastasis   in  several  different  cancers  [105].    In  summary,  the  role  of  the  immune  system  in  cancer  disease  is  highly  complex  and  there  seems  to  be  a  delicate  balance  between  antitumor  activities  versus  tumor-­‐promoting  events.                                        

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SPECIFIC  TUMOR  TYPES    Breast  cancer    Breast  cancer  is  the  most  common  cancer  among  women  worldwide,  affecting  approximately   1  million   individuals   each   year   [106].  Nearly   8000  women   are  every  year  diagnosed  with  the  disease   in  Sweden,  and  although  the  mortality  has  decreased  (the  5-­‐year  survival  rate  being  almost  90%  today),  the  incidence  has  increased  during  the  past  20  years  [107].    Well   known   risk   factors   for   developing   breast   cancer   include   age,   a   family  history  of  breast  cancer  and  factors  associated  with  reproduction  and  estrogen  exposure   (such   as   early  menarche,   late  menopause,   nulliparity   and  hormone  replacement  therapy)  [108].  Most  breast  cancer  cases  are  sporadic,  suggesting  that  lifestyle  and/or  environmental  factors  are  of  importance  in  breast  cancer  etiology   [109]   [110].  Mutations  in   the  BRCA1  and  BRCA2   genes   are   the  most  well   known   hereditary   causes   of   breast   cancer   and   associated  with   high-­‐risk  genetic  predisposition  [111].    An   important   part   of   breast   cancer   diagnostics   is   the   triple   test,   including  clinical   examination   of   the   breast   (and   lymph  nodes),   radiologic   examination  and  fine  needle  aspiration/biopsy  for  histological  examination  [112]  [113].  The  most   common   morphological   subtype,   invasive   ductal   carcinoma,   is   derived  from   glandular   ducts   of   the   breast   and   accounts   for    ~   75%   of   all   breast  cancers.  Invasive  lobular  carcinoma,  which  arises  from  the  lobular  units  of  the  breast  glands,  is  the  second  most  common  subtype  (5-­‐15  %)  [114].      Breast   cancer   treatment   relies   on   surgical   removal   of   the   tumor   (and  sometimes   axillary   dissection),   in   combination   with   radiotherapy   and/or  systemic   therapy,   such   as   chemotherapy,   endocrine   treatment   and   targeted  drugs.  70-­‐80%  of  all  breast  carcinomas  express  the  estrogen  receptor  (ER)  and  require   estrogen   for   cell   proliferation   and   survival   [115].   The  goal   with  endocrine   therapy   is   therefore   to   block   the   ER   or   to   decrease   circulating  estrogen   levels.   The   monoclonal   antibody   Trastuzumab   is   an   example   of  targeted   therapy.   The   drug   is   directed   against   the   HER2   receptor,   which   is  overexpressed   in   15-­‐30%   of   breast   cancers   and   associated   with   a   worse  prognosis  [116].    TNM  stage,  i.e.  primary  tumor  size  (T),  lymph  node  status  (N)  and  presence  of  distant  metastasis   (M),   is   a  well-­‐established  and   important  prognostic   tool   in  breast   cancer   (as  well   as   in   other  malignancies)   and   influences   the   choice  of  

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treatment.  However,   in  order   to   identify  prognostically   important   subgroups,  additional   parameters   are   needed.   One   such   parameter   is   the   Nottingham  histological   grade   system,   which   provides   a   combined   score   based   on   the  amount   of   gland   formation,   nuclear   atypia   and   mitotic   activity   [117].   Other  prognostic  and/or  treatment  predictive  parameters   include  age,  estrogen  and  progesterone   receptor   status,   HER2   status   and   levels   of   the   proliferation  marker   Ki67.  In   addition,   lifestyle   factors   such   as   physical   activity,   diet   and  weight   have   been   related   to   prognosis   [118].   Still,   since   breast   cancer  comprises   a   heterogeneous   group  of   tumors  with   varying   characteristics   and  survival  patterns,  an  important  goal  within  the  field  of  breast  cancer  research  is   to   find   reliable   and   useful   biomarkers   for   early   detection,   prognosis   and  treatment  response  in  breast  cancer  subgroups.      Renal  cell  carcinoma    Renal   cell   carcinoma   (RCC)   of   the   kidney   accounts   for   ~   2-­‐3   %   of   all   human  cancers  worldwide  [119].  In  Sweden,  more  than  1000  individuals  are  diagnosed  with   the   disease   each   year,   with   a   male-­‐to-­‐female   ratio   of   ~   2:1  [107].  Hereditary  forms  account  for  only  2-­‐4  %  of  all  RCC  [120].  The  majority  of  cases  are  thus  sporadic  and  several  risk  factors  have  been  identified,  including  cigarette   smoking,   obesity   and   hypertension   [121].  The   classic   triad   of  hematuria,   flank  pain  and  abdominal  mass   is  present   in  only   a   small   fraction  (10%)   of   the   patients  at   diagnosis.   Instead,   symptoms   (if   present)   are   often  diffuse   and   more   than   50   %   of   the   RCC   tumors   are   detected   incidentally  through   radiographic   examination   [122].   RCC   is   associated   with   a   high  mortality   rate   and   approximately   one   third   of   the   patients   have   advanced  disease/distant  metastases  at  diagnosis  [122].    Similar  to  other  cancers,  RCC  comprises  a  heterogeneous  group  of  tumors  with  differences  in  genetics  and  clinical  behavior.  Clear  cell  RCC  (ccRCC)  is  the  most  common  histological  subtype,  representing  75-­‐80  %  of  all  RCC.  The  majority  of  these  tumors  carry  a  deletion  of  the  von  Hippel-­‐Lindau  (vHL)  suppressor  gene  on  chromosome  3p  [123]  [124].  Inactivation  of  this  gene  causes  accumulation  of  hypoxia  inducible  factor  (HIF)-­‐1α,  which  in  turn  leads  to  various  HIF-­‐related  events,  including  induction  of  angiogenesis  via  the  vascular  endothelial  growth  factor   (VEGF)   [125].   In   accordance,   ccRCC   tumors   are   typically   highly  vascular.  Although   ccRCC   is   the   most   common   form   of   RCC,   several   other  histological  subtypes  exist.  According  to  the  Heidelberg  classification,  these  are  papillary  RCC  (10-­‐15%),  chromophobe  RCC  (5%),  collecting  duct  RCC  (<1%)  and  unclassified  RCC  (3-­‐5%)  [126].    

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Curative  RCC  treatment   is  only  possible   in  patients  with   localized  disease  and  requires  complete  removal  of  the  tumor.  Radical  nephrectomy,  which  involves  resection   of   kidney,   perirenal   fat   and   ipsilateral   adrenal   gland   (often   in  combination   with   lymphadenectomy),   is   the   most   common   approach.  Nephron-­‐sparing   surgery   is   an   alternative   procedure,   typically   reserved   for  patients  with  small  tumors  or  for  patients  with  poor  renal  function  or  solitary  kidney  [127].  An  obstacle  to  successful  treatment  of  more  advanced  disease  is  the   fact   that  RCC  tumors  are  radioresistant  [128]  and  show  poor  response  to  chemotherapy   [129].   Cytokine   therapy   with   IL-­‐2   and   interferon-­‐α   has   been  tried  in  metastatic  RCC,  but  this  treatment  is  fairly  toxic  [130]  [131].  Emerging  treatment   strategies   instead   focus   on   targeting   agents,   such   as   anti-­‐VEGF  monoclonal  antibodies   [132]   [133],  multikinase   inhibitors   [134]  and   inhibitors  of  the  mTOR  pathway  [135]  [136].    TNM  stage  is  the  most  important  prognostic  tool  in  RCC.  Additional  parameters  in   use   (among   others)   include   histological   cell   type,   nuclear   grade,   vascular  invasion   and   hemoglobin   levels   [127].   Due   to   the   diverse   features   and  unpredictable  nature  of  RCC  tumors,  there  is  an  intense  search  for  better  and  more   informative  biomarkers.  Although  a   large  number  of  molecular  markers  have   been   investigated,   including   various   tumor   tissue-­‐derived,   immunologic  and   blood/urine-­‐based   markers,   there   is   still   a   lack   of   clinically   validated  biomarkers  in  RCC  at  the  present  time  [137]  [138].                                        

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AIMS      GENERAL  AIM  

 In   recent   years,   telomere   length   has   gained   considerable   attention   as   a  potential  biological  marker  in  a  variety  of  diseases,  cancer  included.  The  work  of   this   thesis   has   been   centered   around   telomere   length   research,   with   a  special  focus  on  telomere  length  dynamics  and  role  as  a  potential  biomarker  in  cancer  disease.          SPECIFIC  AIMS    PAPER  I:    To   investigate  blood  cell  telomere   length  as  a  potential  marker  of  risk  and/or  prognosis  in  breast  cancer  patients.    PAPER  II:    To   investigate   telomere   length   in   peripheral   blood   cells,   tumor   tissue   and  corresponding   kidney   cortex   in   relation   to   survival   in   patients  with   clear   cell  renal  cell  carcinoma.    PAPER  III:    To   investigate   telomere   length   in   relation   to   immunological   components   in  patients  with  renal  cell  carcinoma.      PAPER  IV:    To  investigate  changes  in  blood  cell  telomere  length  over  time.                  

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MATERIALS  AND  METHODS  

 STUDY  POPULATIONS  AND  TISSUE  SAMPLES    All  samples  were  obtained  after  informed  consent  and  ethical  approval.    Paper  I    The   patient   group   consisted   of   265   newly   diagnosed   breast   cancer   patients  (median   age   57   years)   referred   to   the   Oncology   Clinic   at   Umeå   University  Hospital,  Västerbotten  County,  Sweden.  All  patients  were  untreated  except  for  surgical   removal   of   the   tumor   and   blood   samples   were   collected   within   3  months  after  morphological  diagnosis.  Date  of  diagnosis  ranged  from  1990  to  2006.  The  control  material  consisted  of  two  population-­‐based  groups  (median  age  55  years),  both  representative  for  the  general  population  of  Sweden:  300  women  from  the  Northern  Sweden  MONICA  study  [139]  and  146  women  from  the  Malmö  Cancer  and  Diet  Study  [140].  Data  regarding  ER  status,  tumor  size  and  nodal  status  were  collected  from  the  clinical  charts  at  the  Oncology  Clinic,  Umeå  University  Hospital.  Information  regarding  cause  of  death  was  obtained  from  clinical  charts  and  death  certificates  with  the  last  follow-­‐up  in  May  2007.  DNA   was   extracted   from   buffy   coats   (i.e.   leukocytes)   collected   from   breast  cancer   patients   and   controls   of   the   MONICA   study,   and   from   granulocyte  preparations  collected  from  controls  of  the  Malmö  Cancer  and  Diet  study.    Paper  II    A   total   of   105   patients   (61  men   and   44  women,  median   age   65   years)   with  newly  diagnosed  clear   cell  RCC  were   included   in   the   study.  Date  of  diagnosis  ranged   from   2001   to   2007.   All   patients   were   nephrectomized   at   the  Department   of   Urology,   Umeå  University   Hospital,   Umeå,   Sweden.   No   other  treatment   had   been   given   prior   to   blood   sampling.   Staging   was   performed  according   to   the   2002   TNM   classification   system   [141],   nuclear   grading   was  performed   according   to   Fuhrman   et   al.   [142]   and   histological   subtype   was  defined   according   to   the   Heidelberg   consensus   [126].   Survival   data   were  obtained   from  clinical   charts  and  death  certificates  with   the   last   follow-­‐up   in  March   2008.   DNA   was   extracted   from   buffy   coats   and   from   freshly   frozen  tissues  (tumors  and  corresponding  kidney  cortex).          

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Paper  III      Two  patient  groups  were  included  in  this  study,  all  referred  to  the  Department  of  Urology,  Umeå  University  Hospital,  Umeå,  Sweden.  The   first  patient  group  consisted  of  the  same  ccRCC  patients  as  described  in  Paper  II.  Serum  samples  for   cytokine   analysis   were   available   for   102   of   these   patients.   In   addition,  CHAPS   (zwitterionic   detergent)   extracts   from   35   patients   were   available   for  telomerase  activity  analysis.  The  second  patient  group  comprised  51  patients  (30   men   and   21   women,   median   age   68   years)   with   RCC   tumors   diagnosed  between   2008   and   2010.   Tumor   subtypes   included   clear   cell   RCC   (n   =   32),  papillary   RCC   (n   =   9),   chromophobe  RCC   (n   =   2)   and  oncocytoma   (n   =   8).   All  blood  samples  were  collected  prior  to  any  therapy,  except  for  surgical  removal  of  the  tumor.      Paper  IV    The   study   encompassed   three   separate   groups   of   individuals.   The   "6-­‐month  study"  comprised  56   individuals  (age  68  or  69),  all  sedentary,  overweight  and  with   abdominal   obesity.   Blood   samples   (whole   blood)   were   collected   twice  from  each  individual  with  a  6-­‐month  interval.  During  this  period,  half  the  group  received   physical   activity   on   prescription   whereas   the   other   half   received  minimal  intervention  in  the  form  of  written  information  about  physical  activity  [143].   Samples   from   6   individuals   were   later   excluded   due   to   unsuccessful  qPCR,   whereas   the   remaining   50   individuals   were   included   in   the   statistical  analysis.  The  "10-­‐year  study"  consisted  of  31  individuals  (all  aged  ≥  60  years  to  match   the   ages   of   the   6-­‐month   study)   originally   included   in   a   previously  described  larger  (n  =  959)  longitudinal  study  on  telomere  length  dynamics  (for  more   detailed   information,   see   [46]).   Data   for   the   31   individuals   were   re-­‐analyzed   regarding   telomere   length   changes   over   time   and   compared   with  data   from   the   6-­‐month   study.   The   "Blood   donor   study"   comprised   blood  samples   (peripheral   blood   mononuclear   cells)   from   five   blood   donors   (one  women   and   four   men),   with   baseline   ages   ranging   from   26   to   43   years.  Samples  were   collected   at   three   different   occasions   from   each   blood   donor,  with  intervals  ranging  from  2  to  25  months.                  

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MAGNETIC  IMMUNE  CELL  SEPARATION  (PAPER  III)    In   paper   III,   leukocytes   were   separated   into   immune   cell   subsets   using  Dynabead-­‐coupled   antibodies   (Dynal   Biotech   Dynabeads,   Norway)   against   T  cell   marker   CD3   (Cat.No.   111.51)   and   B   cell   marker   CD19   (Cat.No   111.43),  according   to   the   supplier's   protocol.   The   method   is   based   on   magnetic  separation   technology.   DNA   extraction   was   thereafter   performed   on   the  resulting  cell  fractions  [T  cells,  B  cells  and  the  remaining  myeloid  (M)  cells]  and  on  whole  blood.  DNA  was  purified  using  the  BioRobot  M48  Workstation  with  MagAttract  technology  (Qiagen,  Germany).  A  few  samples  were  excluded  due  to   poor   DNA   yield.   The   remaining   samples   were   included   in   the   telomere  length   analysis   described   below   (whole   blood:   n   =   50,   B-­‐fraction:   n   =   44,   T-­‐fraction:  n  =  50,  M-­‐fraction:  n  =  47).        TELOMERE  LENGTH  MEASUREMENTS    Telomere  real-­‐time  PCR  (Paper  I-­‐IV)    In  all  papers,  telomere  length  was  assessed  by  a  real-­‐time  PCR  (qPCR)  method  first  described  by  Richard  Cawthon  in  2002  [82],  and  later  slightly  modified  in  our  lab  [22]  [144].  The  method  uses  a  primer  design  that  minimizes  the  risk  of  primer   dimer   products.   The   single-­‐copy   gene   human   beta-­‐globin   (HBG)   was  used  in  order  to  normalize  DNA  loading.    Telomere  and  HBG  primer  sequences  were:  CGGTTTGTTTGGGTTTGGGTTTGGGTTTGGGTTTGGGTT  (Tel1b),  

GGCTTGCCTTACCCTTACCCTTACCCTTACCCTTACCCT  (Tel2b),  

TGTGCTGGCCCATCACTTTG  (HBG3),  

ACCAGCCACCACTTTCTGATAGG  (HBG4).  

Two   96-­‐well   plates   were   prepared   for   each   experiment,   one   using   telomere  primers  to  determine  the  cycle  threshold  (Ct)  value  for  telomere  amplification,  and   one   using   HBG   primers   to   determine   the   Ct   value   for   control   gene  amplification.   Telomere/single   copy   gene   (T/S)   values   were   then   calculated  using   the   formula   T/S   =   2-­‐ΔCt,   where   ΔCt   =   average   Cttelomere−   average   CtHBG.  Relative  T/S  values  were  generated  by  dividing  sample  T/S  values  with  the  T/S  value   of   a   reference   cell   line   DNA   (CCRF-­‐CEM)   included   in   all   plates.   The  reference   DNA   was   also   used   for   standard   curve   construction   in   order   to  monitor  the  PCR  efficiency  of  each  run.    

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Prior  to  analysis,  all  samples  were  diluted  to  1.75  ng/μl  in  TE  buffer  containing  Escherichia  coli  DNA  (a  genome  without  telomeres)  (Sigma  Aldrich)  to  stabilize  the  PCR   reactions.  Samples  were   thereafter  denatured  at  95°C  and  cooled  at  4°C.   Each   sample   was   loaded   in   triplicate   in   optical   96-­‐well   plates   (17.5   ng  DNA/aliquot)  for  qPCR  analysis.  A  negative  control  was  included  in  all  runs.  For  a   detailed   description   of   PCR   reagents   and   cycling   conditions,   see   [144].   All  qPCR   amplifications   were   performed   in   an   ABI   Prism   7900   HT   sequence  detection  system  (Applied  Biosystems),  and  results  were  analyzed  with  the  ABI  Prism   7900   SDS   Software   (v.2.1-­‐2.4)   (Applied   Biosystems).   The   mean   inter-­‐assay  coefficient  of  variation  (CV)  for  the  method  ranges  between  4–8%  in  our  laboratory  [145]  [146].      Southern  Blot  (paper  IV)    Six  DNA  samples  from  the  Blood  donor  study  were  selected  for  Southern  blot  analysis.  Briefly,  DNA  samples  were  cut  over  night  with  Hinf  I  and  separated  by  electrophoresis   on   an   agarose   gel.   The  DNA  was   transferred   to   a  Hybond-­‐XL  membrane   (GE   Healthcare/Amersham   Biosciences,   Sweden)   and   the  membrane   was   air-­‐dried   and   UV   cross-­‐linked.   After   pre-­‐hybridization   in  QuikHyb   solution   (Stratagene,  USA),   a  mixture  of   32P-­‐end   labeled   (TTAGGG)4-­‐probe  and  salmon  sperm  DNA  was  added  to  the  solution  and  hybridized  to  the  DNA.   After   washing,   the  membrane   was   exposed   to   a   phosphor   screen   and  scanned   in   a   Typhoon   9400   imager   (GE   Healthcare/Amersham   Biosciences,  Sweden).      Single  telomere  length  analysis  (STELA)  (paper  IV)    Six  DNA  samples  from  the  6-­‐month  study  and  five  DNA  samples  from  the  Blood  donor  study  were  selected  for  telomere  length  analyses  at  the  XpYp  telomeres,  using   a   modification   of   the   STELA   assay   previously   described   [90]   [147].   In  brief,  genomic  DNA  was  digested  by  EcoRI,  quantified  and  diluted  in  Tris-­‐HCl.  A  Telorette2  linker  was  ligated  to  the  telomere  ends,  and  multiple  PCR  reactions  were   carried   out   with   a   Teltail   primer   (complementary   to   the   linker)   and   a  chromosome-­‐specific   telomere-­‐adjacent  primer,   in  order   to  amplify   the  XpYp  telomeres.   All   PCR   reactions   were   performed   using   an   MJ   PTC-­‐225  thermocycler   (MJ   research).   Thereafter,   DNA   fragments   were   resolved   by  agarose   gel   electrophoresis   and   detected   by   two   separate   Southern  hybridizations   with   a   random-­‐primed   α-­‐33P   labeled   (Amersham   Biosciences,  UK)   telomere   repeat   probe   and   a   telomere-­‐adjacent   probe,   along   with  

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molecular   weight   marker   probes.   Subsequent   phosphorimaging   was  performed  with  a  Molecular  Dynamics  Storm  860  phosphorimager  (Amersham  Biosciences,  UK)  and  molecular  weights  of  the  DNA  fragments  were  calculated  using  the  Phoretix  1D  quantifier  (Nonlinear  Dynamics,  UK).      TELOMERASE  ACTIVITY  (PAPER  III)      CHAPS   extracts   (250   ng/sample)   from   35   ccRCC   tumors   were   evaluated   for  telomerase  activity  with  a  quantitative   telomerase  detection   (QTD)  kit   (Allied  Biotech   Inc,   USA).   Assays   were   performed   according   to   the   manufacturer's  protocol,   using   the   ABI   Prism   7900   HT   sequence   detection   system   (Applied  Biosystems)   for   real-­‐time   PCR   amplification.   The  QTD   kit   also   includes   a   TSR  control   template   to   be   used   as   a   positive   control   and   for   standard   curve  construction.  Telomerase  activity  was  evaluated  using  ABI  Prism  SDS  Software  2.4  (Applied  Biosystems).      FLOW  CYTOMETRY  (PAPER  III)      One   of   the   aims   in   paper   III   was   to   measure   peripheral   levels   of   Tregs   in  patients  with  RCC   tumors.  For   this  purpose,  blood  samples  were  analyzed  by  flow   cytometry   for   immunophenotyping.   All   analyses  were   performed  within  24   (-­‐   48)   hours   from   blood   sampling.   Fluorochrome-­‐labeled   monoclonal  antibodies   were   targeted   against:   CD8-­‐FITC   (BDBiosciences),   CD127-­‐PE  (BDPharmingen),  CD4-­‐PerCp   (BDBiosciences),  CD19-­‐PECy7   (Beckman  Coulter),  CD25-­‐APC  (BDBiosciences),  CD3-­‐APCAlexa  750  (Beckman  Coulter),  CD16-­‐Pacific  Blue  (BDBiosciences)  and  CD45-­‐AmCyan  (BDBiosciences).  Briefly,  50  µl  of  each  blood   sample  was   incubated  with   antibodies.   Samples   were   then   lysed  with  ammonium  chloride,  followed  by  repeated  centrifugation  and  washing  in  PBS.  Analyses  were  performed  on  a  FACSCantoII  flow  cytometer  with  the  FACSDiva  software   (BD   Biosciences).   Lymphoid   cells   were   identified   according   to   their  strong  CD45  expression  and   low  side  scatter  and  Tregs  were   identified  as  the  CD4+CD25highCD127low/-­‐  cell  subset  population.      MULTIPLEX  CYTOKINE  ANALYSIS  (PAPER  III)    Cytokines   from  102  ccRCC  patients  were  analyzed   in  previously  stored  serum  samples.   A   17-­‐plex   human   cytokine   panel   was   used   with   the   Bio-­‐PlexTM  Suspension   Array   System   (Bio-­‐Rad,   Hercules,   USA).   The   following   cytokines  

24    

were   included   in  the  17-­‐plex  panel:   IL-­‐1β,   IL-­‐2,   IL-­‐4,   IL-­‐5,   IL-­‐6,   IL-­‐7,   IL-­‐8,   IL-­‐10,  IL-­‐12,   IL-­‐13,   IL-­‐17,   granulocyte   colony-­‐stimulating   factor   (G-­‐CSF),   granulocyte-­‐macrophage   colony-­‐stimulating   factor   (GM-­‐CSF),   interferon-­‐gamma   (IFN-­‐γ),  monocyte  chemotactic  protein-­‐1  (MCP-­‐1),  macrophage  inflammatory  protein-­‐1  beta   (MIP-­‐1β)   and   tumor   necrosis   factor-­‐alpha   (TNF-­‐α).   Assays   were  performed   according   to   the   manufacturer’s   instructions,   except   that   each  serum   sample   was   diluted   1:3   in   sample   diluent   [148].   An   internal   control,  consisting  of  four  pooled  patient  serum  samples,  was  included  in  each  run.  All  samples  were  assayed   in  duplicate  and  analyzed  with  a  Luminex  200  Labmap  system  (Luminex,  Austin,  USA).  Data  was  evaluated  using  the  Bio-­‐Plex  Manager  software   version   4.1.1   (Bio-­‐Rad).   Three   patients   were   found   to   be   extreme  high   outliers   and   were   removed   from   further   analysis.   The   remaining   99  patients  were  included  in  the  statistical  calculations.      STATISTICAL  ANALYSIS    SPSS  version  15.0   (Paper   I-­‐II)   or  PASW  statistics  18.0   (Paper   III-­‐IV)  were  used  for   statistical   analyses.   Continuous   data  were   checked   for   normality   (and   ln-­‐transformed   if   required)   before   using   parametric   tests.   Nonparametric   tests  were  used  when  data  were  not  normally  distributed  and/or  samples  sizes  were  small.   Correlations   between   continuous   variables   were   investigated   with  Pearson's   correlation   coefficient,   Spearman’s   rank   correlation   or   partial  correlation  with  covariate  adjustment.  Odds  ratios  for  breast  cancer  risk  (paper  I)   were   calculated   by   binary   logistic   regression.   Between-­‐group   differences  were   investigated  by   Student's   t-­‐test   (paired  or  unpaired),  Mann-­‐Whitney  U-­‐test   or   ANCOVA   (analysis   of   covariance)   with   covariate   adjustment.   Survival  analysis  was  performed  using  Kaplan-­‐Meier  with  the   log-­‐rank  test  and  hazard  ratios   were   obtained   by   multivariate   Cox   regression   analysis.   Statistical  significance  refers  to  P  ≤  0.05  (two-­‐tailed).        

 

 

 

 

 

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RESULTS  

The  main  results  for  each  paper  are  presented  below.  More  detailed  data  and  figures  can  be  found  in  the  original  articles  of  this  thesis.      PAPER  I    Telomere   length   in   peripheral   blood   is   associated  with   risk   and  outcome   in  breast  cancer  patients.    In   paper   I,   the   ability   of   blood   telomere   length   to   predict   cancer   risk   and  survival   was   explored   in   patients   with   breast   cancer,   the   most   common  malignancy  in  women  worldwide.  In  total,  265  newly  diagnosed  breast  cancer  patients   and   446   female   controls   were   included   in   the   study.   Both   groups  showed  a  significant  age-­‐dependent  decline  in  telomere  length.  However,  the  breast   cancer   patients   displayed   significantly   longer   blood   telomere   length  compared  to  controls,   regardless  of  age.  Adjusted  odds  ratios   (OR)   for  breast  cancer   risk   were   found   to   increase   with   increasing   telomere   length,   with   a  maximal  OR  of  5.17  for  the  quartile  with  the  longest  telomeres.      Interestingly,  we  also  found  that  blood  telomere  length  was  a  predictive  factor  for  cancer-­‐specific  death.  Patients  <  50  years  of  age  (approximate  menopausal  age)  with   telomere   lengths   above  median  had   a   significantly  worse  outcome  compared  to  patients  with  shorter  telomeres.  For  patients  ≥  50  years  of  age  a  trend  towards  a  similar  pattern  was  observed.  Analyses  of  subgroups  based  on  tumor  size  and  nodal  status  (two  established  prognostics  factors)  showed  that  telomere   length   carried   prognostic   information   for   patients   with   advanced  disease.  More  specifically,  long  blood  telomeres  were  associated  with  a  worse  survival   among   node-­‐positive   patients   and   patients   with   a   tumor   size   above  median.  Telomere  length  was  not  related  to  survival  in  node-­‐negative  patients  or  in  patients  with  smaller  tumors,  but  due  to  few  events  in  these  groups  the  statistical   calculations   should   be   interpreted   with   caution.   Multivariate   Cox  regression   analysis,   including   age,   blood   telomere   length,   nodal   status   and  tumor   size,   verified   blood   telomere   length   as   a   significant   independent  prognostic  factor.    Blood  telomere  length  was  also  investigated  in  relation  to  ER  status.  The  mean  telomere  length  value  was  slightly  higher  in  the  ER+  group  compared  to  the  ER-­‐  group,   but   the   difference   was   not   statistically   significant.   In   both   groups,  telomere  lengths  above  median  were  associated  with  a  worse  outcome.  

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PAPER  II    Blood   telomere   length,   in  contrast   to   telomere   length   in   tumors  and  kidney  cortex,  predicts  survival  in  clear  cell  renal  cell  carcinoma.            The   aim   of   paper   II   was   to   investigate   whether   telomere   length   can   be   a  predictor  for  survival  in  newly  diagnosed  patients  with  clear  cell  RCC,  the  most  common  form  of  kidney  cancer.  The  study  included  105  patients,  61  men  and  44  women.  Telomere  length  was  evaluated  in  peripheral  blood  cells  as  well  as  in   tumor   samples   and   in   corresponding   kidney   cortex.   Comparison   between  the   three   tissue   compartments   showed   that   tumor   samples   displayed  significantly   shorter   telomeres   compared   to   kidney   cortex   and   blood.   In  addition,   blood   telomeres   were   significantly   shorter   than   the   telomeres   of  kidney   cortex.   At   the   same   time,   all   three   tissues   were   found   to   correlate  positively  with  each  other  regarding  telomere  length.  In  contrast,  no  significant  correlations   were   observed   between   telomere   length   values   and   various  clinical   parameters,   such   as   haemoglobin,   albumin   or   erythrocyte  sedimentation   rate.   Tumor   size,   however,   correlated   positively   with   tumor  telomere   length   and   tumor/non-­‐tumor   (T/N)   telomere   ratio.   An   age-­‐dependent   decline   in   telomere   length   was   observed   in   all   tissue  compartments.      As   expected,   established  prognostic   parameters   (such   as   TNM   stage,   nuclear  grade   and   anaemia)   were   associated   with   survival   in   our   patient   group.  Interestingly,  and  similar  to  our  breast  cancer  patients,  blood  telomere  length  was   also   associated  with   outcome.   Patients  with   long   blood   telomere   length  (4th   quartile)   had   a   significantly   poorer   outcome   compared   to   patients  with  shorter   telomeres,   irrespective   of   age.   Analysis   restricted   to   subgroups  revealed   a   highly   significant   association   between   long   blood   telomeres   and  poor   survival   among   non-­‐metastatic   patients,   whereas   patients   with   distant  metastasis  had  a  poor  outcome  regardless  of  the  telomere  length  status.  Blood  telomere   length   was   verified   as   an   independent   prognostic   factor   in   a  multivariate   Cox   regression   model,   including   age,   TNM   stage   and   blood  telomere  length.  In  contrast,  telomere  length  in  tumor  tissue  or  kidney  cortex  could   not   predict   outcome   per   se.   There   was,   however,   a   trend   to   shorter  survival  in  patients  with  a  high  T/N  telomere  ratio.              

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PAPER  III      Telomere   length   is   associated   with   immunological   parameters   in   patients  with  renal  cell  carcinoma.    Immunological  components  are  of  importance  in  cancer  disease  and  may  also  influence   telomere   length.   One   of   the   aims   of   paper   III   was   to   investigate  peripheral   levels   of   various   cytokines   in   relation   to   telomere   length   in  peripheral   blood,   ccRCC   tumors   and   corresponding   kidney   cortex,   using   the  same   group   of   ccRCC   patients   as   described   in   paper   II.   In   addition,   we  hypothesized  that  our  previous  findings  of  an  association  between  long  blood  telomeres   and   a   poorer   cancer-­‐specific   survival   could   reflect   a   suppressed  immune   system   (with   fewer   cell   divisions)   in   a   subset   of   our   patients.   We  therefore   investigated   telomere   length   in   whole   blood   and   in   blood   cell  subpopulations   in   relation   to   peripheral   levels   of   Treg   cells  (CD4+CD25highCD127low/-­‐).      99   ccRCC   patients   of   the   cytokine   study   were   included   in   the   statistical  evaluation.   Among   the   seventeen   cytokines   analysed,   eight   analytes   were  detected   above   threshold   in   ≥   10   %   of   the   patients   and   were   included   for  further   statistical   evaluation.   These   were   IL-­‐5,   IL-­‐6,   IL-­‐7,   IL-­‐8,   IL-­‐10,   G-­‐CSF,  MCP-­‐1   and  MIP-­‐1β.   Three   of   these   cytokines   (IL-­‐7,   IL-­‐8   and   IL-­‐10)   showed   a  significant   positive   correlation   with   tumor   telomere   length   and   with   T/N  telomere  ratio.  No  significant  correlations  were  found  between  cytokine  levels  and  telomere  length  of  peripheral  blood  cells  or  normal  kidney  cortex.  Tumor  telomerase  activity  (TA)  could  be  measured  in  only  a  subset  of  the  patients  (n  =  35).   In   these   patients,   tumor   TA   was   found   to   correlate   inversely   to   the  cytokines   IL-­‐7   and   IL-­‐8,   as   well   as   to   T/N   telomere   ratio.   In   contrast,   no  significant   correlations   were   observed   between   tumor   TA   and   telomere  lengths  in  blood,  kidney  cortex  or  tumors.      The   Treg   study   comprised   51   RCC   patients   with   various   RCC   subtypes,   the  majority  with  clear  cell  RCC  (n  =  32).  Calculations  were  performed  on  the  total  group   in   order   to   gain  more   statistical   power,   but   restricting   the   analyses   to  the  ccRCC  subgroup  did  not  change  the  results.  Data  evaluation  revealed  that  whole   blood   and   the   M   cell   fraction   displayed   significantly   longer   telomere  length  compared   to   the  B  and  T  cell   fractions.  No  significant   telomere   length  differences  were  observed  between  B  and  T  cells,  or  between  the  M  fraction  and   whole   blood.   An   age-­‐dependent   decline   in   telomere   length   was   found  among  the  T  cells,  but  not  in  the  other  cell  fractions.      

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Interestingly,   peripheral   Treg   levels   correlated   positively   with   whole   blood  telomere   length.   Furthermore,   the   strongest   correlation  was   found   between  Treg   levels   and   telomere   length   of   the   T   cell   fraction.   Thus,   patients   with   a  higher  number  of  Tregs  had  longer  T  cell  telomeres.  In  contrast,  no  significant  correlations  were  observed  between  Tregs   and   telomere   length  of   the  other  cell  subsets  (B  and  M  cells).      PAPER  IV      Peripheral  blood  telomeres  fluctuate  in  length  over  time  and  marked  changes  can  occur  within  months.    Telomere   length   is  believed  to  be   influenced  by  a  number  of  factors,   intrinsic  as   well   as   extrinsic.   In   a   previous   longitudinal   study   with   approximately   10  years  follow-­‐up  time  [46],  we  showed  that  the  rate  of  telomere  shortening  in  blood   cells   was   associated   with   baseline   telomere   length.   More   specifically,  individuals   with  long   telomeres   at   baseline   exhibited   the   most   pronounced  telomere   shortening   and   vice   versa.   In   paper   III,   we   aimed   to   further  investigate  blood  telomere   length  changes  over   time,  using  shorter   follow-­‐up  periods.      In  our  6-­‐month  study,  50  individuals  (15  men  and  35  women)  were  included  in  the  statistical  analysis.  All  participants  were  of  a  similar  age  (68-­‐69  years)  and  overweight.   Blood   samples   had   been   collected   twice   at   a   6-­‐month   interval,  during  which  period  half  of  the  group  received  physical  activity  on  prescription  (PAP)  and  the  other  half  minimal  intervention  treatment.  Statistical  evaluation  showed   no   significant   differences   between   the   PAP   vs.  minimal   intervention  groups   regarding   baseline   or   follow-­‐up   telomere   lengths.   Further   statistical  calculations  were  therefore  performed  on  the  group  as  a  whole.  Among  the  50  individuals,  25  exhibited  a  decrease   in  telomere   length  over  time  whereas  25  displayed   elongated/stable   telomeres.   The   latter   group   had   significantly  shorter   median   telomere   length   at   baseline   compared   to   those   who  experienced   telomere   shortening.   Correlation   analysis   revealed   significant  correlations  between  monthly  telomere  changes  and  baseline  telomere  length,  which  is  in  concordance  with  our  previous  longitudinal  10-­‐year  study  [46].  We  therefore   reanalyzed   data   from   that   study,   including   only   individuals   ≥   60  years   of   age   to   better   match   the   ages   of   the   6-­‐month   study.   The   monthly  telomere  changes  were  found  to  be  considerably  smaller  in  the  10-­‐year  study  compared  to  the  6-­‐month  study.  At  the  same  time,  telomere  length  values  at  baseline   correlated   significantly   with   follow-­‐up   values   in   the   6-­‐month   study,  

29    

but   not   in   the   10-­‐year   study.   No   significant   correlations   were   observed  between  telomere   length  and  body  mass   index  (BMI),  neither  at  baseline  nor  at  follow-­‐up.      We   also   investigated   telomere   length   dynamics   in   a   separate   material  consisting  of  five  blood  donors.  Three  samples  collected  at  different  occasions  with  varying  time  spans  were  available  from  each  donor.  In  the  first  evaluation  round,   telomere   length  was  measured  by  qPCR.  Four  of  the  donors  exhibited  only  small  fluctuations  in  telomere  length  over  time,  but  one  donor  showed  a  marked  decrease   in   telomere   length  over  a  6-­‐month  period.  This   finding  was  further   evaluated   by   additional  methods   for   telomere   length  measurements  (Southern   blot   and   STELA),   generating   similar   results.   For   the   donor   with   a  marked  loss  in  telomere  length,  there  was  a  considerable  decrease  in  telomere  heterogeneity  over  the  6-­‐month  period,  with  a  noteworthy  loss  of  the  longest  telomeres.                                                      

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DISCUSSION      BLOOD  TELOMERE  LENGTH  AS  A  RISK  MARKER  IN  MALIGNANCY    (PAPER  I)    Over  the   last  decade,   telomere   length  has  gained  considerable  attention  as  a  potential   marker   of   cancer   risk.   Two  meta-­‐analyses   were   recently   published  regarding  telomere  length  in  surrogate  tissue  (predominantly  peripheral  blood  cells)  and  associations  with  cancer  [149]  [150].  For  the  majority  of  cancer  types  investigated,   e.g.   kidney,   bladder   and   gastric   cancers,   significant   associations  between  short   telomere   length  and  cancer   risk  were   reported.  However,   the  results   from   this   research   field   are   not   uniform   and   for   breast   cancer   in  particular   the   results   are   highly   inconsistent.   Our   finding   of   an   association  between   long  blood   telomere   length  and   increased   risk  of  breast   cancer  was  recently  supported  by  Gramatges  et  al.  [151].  Similarly  to  our  observation,  they  found   that   breast   cancer   patients   had   significantly   longer   blood   telomere  length   than  unaffected   controls,  with   an   increasing   risk   for   breast   cancer   for  each   longer   quartile.   In   contrast,   other   studies   have   observed   either   no  association  between  telomere   length  and  breast  cancer  risk   [152]   [153]   [154]  [155]  or  an  increased  (but  not  always  statistically  significant)  risk  among  breast  cancer  patients  with  short  telomere  lengths  [152]  [156]  [157].    The   conflicting   results   may   have   several   causes   and   various   plausible  explanations   have   been   presented.   One   potentially   important   factor   is  differences   in   the   study   design.   For   example,   the   two   meta-­‐analyses  mentioned   above   found   that   the   association   of   telomere   length   and   risk   of  various   cancers   were   stronger   in   retrospective   studies   compared   to  prospective   studies.   The   latter   study   type   is   considered  more   powerful,   less  potentially  biased  and  better  suited  for  examining  a  possible  exposure-­‐disease  relationship.  On   the  downside,   it   requires  a  more  costly  and   time-­‐consuming  design   and   the  number  of   prospective   studies  within   the   field   are   sparse   (as  summarized   in   refs.   [158]   and   [159]).   Another   possible   explanation   for   the  inconsistent   data   includes   differences   in   the  methodology   used   for   telomere  length  measurements.   Although  qPCR  has   been   the  method  of   choice   in   the  majority   of   studies,   standardized   protocols   are   lacking.   In   addition,   some  studies  have  measured  telomere  length   in  buffy  coats  or  whole  blood,  others  in  lymphocytes  or  other  specific  blood  cell  subtypes.  Another  important  factor  to  consider  is  the  timing  for  sample  collection.  In  our  breast  cancer  study,  only  untreated   patients   (except   for   surgical   removal   of   the   tumor)  were   included  and   all   blood   samples   were   collected   within   3   months   after   morphological  diagnosis.  None  of  the  patients  had  received  radiotherapy  or  systemic  therapy  

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prior   to  blood  sampling,   factors   that  may  have  an   impact  on  telomere   length  dynamics   [160]   [161]   [162]   [163].   Several   retrospective   studies   lack  information  on   the   timing  of   sample  collection  or   treatment   initiation,  and   it  cannot   be   ruled   out   that   reverse   causation   bias   influenced   the   associations  observed   in   some   of   these   studies.   Telomere   shortening   might   thus   have  occurred   predominantly   after   diagnosis   as   a   result   of   e.g.   treatment   effects.  Other   contributing   factors   to   the   discrepancy   could   be   differences   regarding  sample  size  or   tumor   type,  measurement  errors,  and  variability   in  potentially  confounding  factors.        Nevertheless,  several  plausible  biological  mechanisms  have  been  presented  to  explain  the  observed  associations  between  altered  blood  telomere  length  and  cancer   risk.  As  mentioned   in   the   introduction,   there   is  a  connection  between  short   telomeres   and   genetic   instability.   The   genetic   disorder   dyskeratosis  congenita,   which   is   characterized   by   e.g.   bone  marrow   failure,   is   associated  with  very  short  telomeres  and  a  significantly  increased  (11-­‐fold)  risk  of  cancer  [164].  Bladder  cancer,  which  is  a  smoking-­‐related  cancer,  has  been  associated  with   short  blood   telomere   length   in   several   studies   [149]   [150].   It   is  possible  that   telomere   shortening   in   these   patients   reflects   an   increased   burden   of  oxidative  stress  due  to  smoking   [165].  As   for   long  blood  telomere   length  and  increased  cancer  risk,  we  speculated  that  prolonged  estrogen  exposure  could  be   an   important   factor   in   our   breast   cancer   study,   since   breast   cancer   is   a  hormone-­‐related   cancer.   Several   studies   have   reported   that   women   display  longer   telomere   length   than   men   [39]   [166]   [167]   [168]   [169]   [170].   In  addition,   postmenopausal   women   receiving   hormone   replacement   therapy  were  found  to  have  significantly  longer  telomeres  compared  to  those  without  such  treatment  [171].  As  previously  mentioned,  estrogen  has  the  ability  to  up-­‐regulate  telomerase  and  it  is  also  capable  of  reducing  oxidative  stress  [36]  [37]  [38].   In   our   breast   cancer   group,  women  with   ER+  breast   cancer   had   slightly  longer  mean  telomere  length  compared  to  ER-­‐  patients,  but  the  difference  was  not   statistically   significant.   Long   blood   telomere   length   has   also   been  associated   with   increased   risk   of   melanoma   [172],   hepatocellular   carcinoma  [173]   and   non-­‐Hodgkin   lymphoma   [174].   It   has   been   suggested   that   long  telomeres   may   favor   delayed   cell   senescence   due   to   enhanced   replicative  potential,  thereby   increasing  the  risk  of  acquiring  genetic  abnormalities  along  the  way  [158]   [174].  However,   the  exact  role  of   telomere   length   in  surrogate  tissues   in  relation  to  cancer  risk  remains   largely  unknown  and  the  cause-­‐and-­‐effect  question  remains  open.  To   further  explore  this   topic,   large  prospective  studies  are  warranted.  In  a  previous  longitudinal  study  conducted  by  our  group  [46],  blood  telomere  length  was  evaluated  at  baseline  and  after  approximately  10  years  follow-­‐up  time,  where  after  controls  were  compared  with  those  who  

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had  developed  cancer  after  the  second  blood  draw.  Surprisingly,  we  could  not  detect   any   significant   differences   in   blood   telomere   length   or   attrition   rates  between  the  control  and  patient  groups.  However,  the  latter  group  comprised  patients  with   a   variety   of   different   cancers.   Thus,   there   is   still   the   possibility  that  altered  blood  telomere  length  is  associated  with  increased  risk  of  specific  tumor  types.  A  recent   longitudinal  study  by  Cui  et  al.  [175]  showed  that  both  very   short   and   very   long   blood   telomere   lengths   were   associated   with  increased  risk  of  colorectal  cancer,  adding  further  complexity  to  the  issue.          Still,   whether   an   altered   blood   telomere   length   reflects   an   overall   altered  telomere   profile,   whether   it   is   a   marker   of   immune   dysfunction   and/or  whether  the  cancer  disease  itself  affects  the  telomere  length  of  leukocytes  (or  their  progenitors)  remains  to  be  further  explored.      TELOMERE   LENGTH   AS   A   PROGNOSTIC   INDICATOR   FOR   CANCER   SURVIVAL  (PAPER  I  +  II)    There   is   growing   evidence   that   telomere   length   has   potential   to   act   as   a  prognostic   marker   in   malignancy.   The   majority   of   studies   have   focused   on  telomere   length   investigations   in   tumor   samples,   and   the   research   field   has  been  previously  reviewed  [68]  [91]  [97].  Many  of  these  studies  have  reported  associations   between   altered   tumor   telomere   length   and   a   poorer   outcome,  but  the  type  of  alteration  (long  or  short  telomere  length)  seems  to  depend  on  the  histological  type  of  tumor.  For  example,  short  tumor  telomere  length  was  related   to   a   poor   outcome   in   sarcoma   [176],   and   reduced   telomere   DNA  content  (measured  by  a  slot  blot  method)  was  associated  with  a  worse  survival  in   breast   and   prostate   cancer   [177]   [178]   [179]   [180]   [181].   As   for  hematological   malignancies,   the   collected   data   indicate   that   short   telomere  length  is  coupled  to  progressive  disease  and  a  worse  outcome  [68].  In  contrast,  long   tumor   telomere   length   and   a   high   T/N   telomere   ratio   have   been  associated   with   advanced   disease   in   patients   with   e.g.   hepatocellular  carcinoma   [182],   colorectal   carcinoma   [183]   [184],   head   and   neck   tumors          [185]  and  Barrett  carcinoma  [186].      In   our   patients   with   ccRCC   (paper   II),   the   majority   of   tumors   displayed  significantly   shorter   telomeres   than   the   corresponding   tumor-­‐free   kidney  cortex,  which   is   consistent  with  previous   results   in  various   cancer   types   [14].  Surprisingly,   tumor   telomere   length   per   se   was   not   associated   with   survival  when   comparing   patients   with   long   vs.   short   telomere   length   (based   on  quartiles).   We   did,   however,   observe   a   trend   towards   a   poorer   outcome   in  

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patients   with   an   increased   T/N   telomere   ratio.   In   addition,   both   tumor  telomere  length  and  T/N  telomere  ratio  correlated  positively  and  significantly  with   tumor   size,   suggesting   that   long   tumor   telomere   length   might   reflect  telomere  stabilization  and  tumor  progression.          One   of   the   main   aims   of   paper   I   and   II   was   to   investigate   blood   telomere  length  as  a  possible  prognostic  tool  in  malignancy.  In  contrast  to  tumor  tissue,  blood   is   easily   accessible,   minimally   invasive   and   inexpensively   collected.   As  discussed  above,  a   large  number  of  studies  have   investigated  blood  telomere  length  as  a  possible  marker  of  cancer  risk.  However,  studies   investigating  the  prognostic  value  of  this  parameter   in  cancer  patients  were  previously   lacking.  Most   interestingly,  we  found  that  blood  telomere   length  carried   independent  prognostic   information   in   both   breast   cancer   (paper   I)   and   ccRCC   (paper   II).  More  specifically,  patients  with   long  blood   telomeres  had  a  worse   survival   in  both   patient   groups.   In   our   breast   cancer   patients,   the   association   between  blood  telomere   length  and  outcome  was  strongest   for  node-­‐positive  patients  and  for  patients  with  large  tumors,  whereas  the  prognosis  was  good  regardless  of  the  telomere  length  status  in  patients  with  local  disease/small  tumors.  Our  ccRCC  patients  with  metastatic  disease  showed  a  generally  poor  outcome  and  blood  telomere  length  was  not  associated  with  survival  in  this  group.  Instead,  blood   telomere   length   was   found   to   be   a   significant   prognostic   marker   in  nonmetastatic   patients.   Consistent   with   our   findings   in   breast   and   kidney  cancer,  Liu  et  al.   [187]   recently   reported  that  hepatocellular  carcinoma  (HCC)  patients   with   long   blood   telomeres   had   a   poorer   survival.   Furthermore,   the  association  was  strongest  in  patients  with  large  tumors,  which  is  in  accordance  with   our   findings   in   the   breast   cancer   group.   In   addition,   and   similar   to   our  observations,  blood  telomere  length  was  unrelated  to  various  clinical  features.    Together,  these  findings  indicate  that  leukocyte  telomere  length  may  serve  as  a   prognostic   biological   marker   in   various   cancer   types.   Assessing   this  parameter  might  hence  be  helpful   in   identifying  subgroups  of  patients  with  a  poorer/better  outcome,  which  in  turn  could  influence  the  choice  of  treatment.  A   complicating   factor,   however,   is   the   large   variation   in   blood   cell   telomere  length  among  individuals  of  the  same  age,  making  it  difficult  to  set  a  reference  range  for  "normal"  vs.  "pathological"  telomere  lengths.  An  important  question  is  therefore  to  what  extent  blood  telomere  length  can  be  informative  not  only  at  a  group  level,  but  also  at  the  individual  level.  Further  research  is  needed  to  clarify   this   issue.   The   reason   behind   the   observed   association   between   long  leukocyte  telomeres  and  a  poorer  survival  remains  to  be  clarified  as  well.  We  speculated  that  immunological  components,  such  as  cytokines  and  suppressive  immune  cells,  could  be  of  importance  and  in  paper  III  we  aimed  to  explore  this  hypothesis  further.    

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THE   IMPACT   OF   IMMUNOLOGICAL   FACTORS   ON   TELOMERE   LENGTH                  (PAPER  III)    The  immune  system  plays  a  complex  role  in  cancer  since  it  can  be  involved  in  antitumoral   responses,   as   well   as   in   tumor   progression.   There   is   also   a   link  between   immunological   components   and   telomere   length   homeostasis.   For  example,  oxidative  stress   (which   is  associated  with  chronic   inflammation)  can  cause   enhanced   telomere   shortening,   whereas   several   cytokines   appear  capable   of   inducing   telomerase   expression   [41]   [42]   [43]   [44]   [45].   In   recent  years,   the   role   of   suppressive   Treg   cells   in   cancer   disease   has   gained  considerable   attention.   They   are   believed   to   be   important   for   self-­‐tolerance  but   there   is  also  growing  evidence   that  Tregs  suppress  antitumoral   immunity  and   promote   tumor   growth   [54],   and   they   have   been   detected   in   increased  levels  in  a  variety  of  cancers  [101].      Based   on   our   findings   in   paper   I   and   II,   where   significant   associations   were  observed   between   long   blood   telomere   length   and   poorer   cancer-­‐specific  survival,   we   speculated   that   a   subset   of   patients   could   have   a   suppressed  immune   response,   e.g.   through   the   action   of   Tregs.   At   least   in   theory,  decreased  proliferation  of  immune  cells  would  lead  to  less  telomere  attrition.  We  also  hypothesized  that  a  relationship  might  exist  between  serum  levels  of  cytokines  and  telomere  length  of  peripheral  leukocytes  and  tumor  tissue.    Interestingly,   we   found   that   three   cytokines   (IL-­‐7,   IL-­‐8   and   IL-­‐10)   correlated  significantly  and  positively  with  tumor  telomere  length  and  T/N  telomere  ratio  in   our   ccRCC   patients.   As   with   other   correlation   analyses,   the   observed  correlations  reveal  nothing  about  cause  and  effect,  but   it  cannot  be  excluded  that  a  functional  link  exists  between  these  parameters.  We  also  found  that  IL-­‐7,   IL-­‐8   and   T/N   telomere   ratio   were   significantly   associated   with   tumor  telomerase  activity.  However,   these   correlations  were  all   inverse.  Hence,   the  relationship   between   the   above-­‐mentioned   cytokines   and   tumor   telomere  length  does  not  seem  to  be  explained  by  increased  telomerase  activity.  As  for  tumor   telomere   length   and   telomerase   activity,   a   trend   towards   a   negative  correlation   was   observed.   This   might   seem   contradictory,   but   telomerase  expression   does   not   necessarily   correlate   positively  with   telomere   length.   In  fact,  negative  correlations  between  these  variables  have  been  observed  in  e.g.  hematologic  malignancies  [188]  [189].      In   contrast   to   the   tumor   tissue,   no   significant   associations   were   observed  between  serum  cytokines  and  telomere   length  of   leukocytes  or  nontumorous  kidney   cortex.   Although   we   cannot   exclude   that   associations   might   exist  

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between   cytokines   and   telomere   length   of   specific   immune   cell   subsets,   the  investigated   cytokines   do   not   seem   to   explain   the   association   between   long  blood  telomeres  and  a  poor  survival  in  ccRCC.      In  our  parallel   Treg   study,  encompassing  patients  with  various  RCC   subtypes,  Treg   cells   were   analyzed   by   flow   cytometry   and   defined   as   the  CD4+CD25highCD127low/-­‐-­‐cell   subset.   Tregs   are   comprised   of   at   least   two  subtypes,   natural   and   inducible   Tregs,   which   both   express   the   forkhead  transcription   factor  Foxp3  (a  nuclear  protein)   [190].  Compared  to  cell   surface  staining,   intracellular   staining   is   a   more   time-­‐consuming   process.   In   recent  years   the   cell   surface   marker   CD127   (the   IL7-­‐receptor   α   chain)   has   proven  useful   in   distinguishing   Tregs   from   activated   conventional   T-­‐cells,   showing   a  significant   inverse   correlation  with   Foxp3   expression   [191]   [192]   [193]   [194].  We  therefore  used   the  CD4+CD25highCD127low/-­‐   -­‐phenotype  when  defining   the  Treg  population.  Most  interestingly,  and  in  line  with  our  hypothesis,  peripheral  Treg  levels  correlated  positively  with  leukocyte  telomere  length.  This  finding  is  also   consistent   with   recent   observations   from   Liu   and   colleagues   [187].   As  mentioned   above,   Liu   et   al.   found   that   long   blood   telomere   length   was  associated  with  poor   survival   in  HCC  patients.  However,   they  also   found   that  patients  with  long  blood  telomeres  had  increased  levels  of  Tregs.  In  our  study,  telomere  length  was  measured  not  only  in  whole  blood  but  also  in  immune  cell  subsets.  Of  special  interest  is  our  observation  that  Treg  levels  correlated  most  strongly   with   the   telomere   length   of   the   T   cell   subset.   Effector   T   cells   are  important   targets   for   Treg-­‐mediated   suppression   and   the   association   is  therefore   plausible.   It   is   also   reasonable   to   think   that   a   suppressed  immunological  response  with  fewer  cell  divisions  could  result  in  less  telomere  shortening  and  reduced  antitumoral  activity.      Taken   together,   the   results   of   paper   III   indicate   that   immunological  components,  such  as  cytokines  and  Tregs,  are  associated  with  telomere  length  in   patients   with   RCC.   Although   not   providing   any   definite   answers,   our   Treg  findings  may  give  a  clue  to  our  observation  that  long  blood  telomere  length  is  associated  with  a  poorer  cancer  survival.                  

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TELOMERE   LENGTH   DYNAMICS   IN   LEUKOCYTES   AND   THEIR   SUBSETS                        (PAPER  III  +  IV)    Leukocytes   constitute   a   heterogeneous   group   of   blood   cells   with   different  immunological  functions.  When  telomere  length  is  analyzed  in  whole  blood  or  buffy  coats  (the  leukocyte  concentrate),  the  received  data  therefore  represent  the   average   telomere   length   of   a   diverse   set   of   cells.   As   discussed   in   the  introduction,   telomere   length  dynamics  differ  between  different   immune  cell  subsets.   In   paper   III,   significantly   longer  mean   telomere   length  was   found   in  whole   blood   and   in   the   myeloid   cell   fraction   (predominantly   granulocytes)  compared   to   the   lymphocyte   fractions   (B   and   T   cells),   which   is   in   line   with  previous   findings   [40]   [57]   [81].   The   result   is   also   in   accordance   with   our  observation   in   paper   I,   where   no   difference   in   mean   telomere   length   was  found   between   the   MONICA   controls   (buffy   coats)   and   the   controls   of   the  Malmö  diet  and  cancer  study  (granulocytes).    Granulocyte   telomere   length   has   been   shown   to   correlate   highly   with   the  telomere  length  of  myeloid  bone  marrow  cells  [80],  and  it  can  be  assumed  to  reflect   the   proliferation   and   replicative   history   of   hematopoietic   progenitor  cells.   The   age-­‐dependent   decline   seems   to   follow   a   biphasic   curve   in   both  lymphocytes  and  granulocytes,  with  the  fastest  decline  occurring  in  newborns  and   in   the   elderly   [195].   Additionally,   previous   reports   have   shown   that   the  decline  in  telomere  length  with  age  is  more  rapid  in  lymphocytes  compared  to  granulocytes   [40]   [57]   [81].   This   may   partly   be   explained   by   the   increase   in  memory  T  cell  number  with  age,  since  memory  T  cells  have  shorter  telomeres  compared  to  naïve  T  cells  [57]  [75].  In  contrast,  memory  B  cells  have  similar  or  even   longer   telomere   lengths   compared   to   their   naïve   counterpart   [59]   [77]  [78].   In   the   patient   group   with   various   RCC   tumors   in   Paper   III,   only   T   cell  telomere   length  was   significantly   associated  with   age.   Further,   no   significant  difference   in   mean   telomere   length   was   found   between   the   B   and   T   cell  fractions,  but  the  inter-­‐individual  variation  in  telomere  length  was  larger  within  the   B   cell   fraction.   The   lack   of   correlation   between   whole   blood   telomere  length   and   age   could   partly   be   due   to   the   relatively   small   sample   size,   since  significant  age-­‐related  correlations  were  found  in  our  larger  breast  cancer  and  ccRCC   patient   groups   (Paper   I   and   II   respectively).   Nevertheless,   the   overall  pattern   regarding   telomere   length   differences   in   immune   cell   subsets   in   our  RCC   patients   is   similar   to   the   findings   of   previous   studies   with   healthy  individuals.    In   recent   years,   a   growing   number   of   studies   have   reported   significant  associations   between   baseline   telomere   length   and   telomere   attrition   rates  

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[46]  [47]  [48]  [49]  [50],  showing  that  individuals  with  longer  telomeres  tend  to  exhibit   a   faster   age-­‐dependent   decline   in   telomere   length.   In   our   previous  study  with   10   years   follow-­‐up   time   [46],   a   strong   correlation   between   these  two  parameters  were  observed.  We  speculated  that  the  results  might  reflect  a  telomere   maintenance   machinery   giving   priority   to   short   telomeres   and/or  that   long   telomeres   are  more   susceptible   to   e.g.   oxidative   stress,   leading   to  faster   telomere   shortening.   In   paper   IV,   we   again   observed   significant  correlations   even   though   the   follow-­‐up   time   was   considerably   shorter   (6  months)   and   the   group   of   participants   was   much   smaller   and   more  homogenous   (all   of   similar   age   and   obese).   No   differences   were   observed  between   individuals   receiving   physical   activity   on   prescription   vs.   those  receiving   minimal   intervention   treatment.   In   the   whole   group   of   fifty  individuals,   half   of   the   participants   experienced   telomere   shortening   (as  compared  to   two-­‐third   in   the  10-­‐year  study).   In  a   recent  diabetes  prevention  study  from  Finland  [50],  in  which  overweight  individuals  with  impaired  glucose  tolerance   were   randomized   into   either   a   lifestyle   intervention   group   or   a  control   group   (receiving   general   dietary/lifestyle   advice),   leukocyte   telomere  length  was  found  to   increase   in  two-­‐thirds  of  the  participants  over  a  4.5  year  period,   with   similar   patterns   in   both   groups.   Individuals   with   the   shortest  baseline   telomeres   exhibited   the   largest   increase   in   telomere   length.   The  results  are  similar  to  our  findings  of  paper  IV,  but  the  underlying  mechanisms  remain   unclear.   What   should   also   be   pointed   out   is   that,   although   the  correlation   between   baseline   telomere   length   and   monthly   changes   was  statistically   significant   in   the   6-­‐month   study,   the   correlation   was   far   from  absolute.  Hence,  not  all  individuals  with  longer  blood  telomeres  experienced  a  more   rapid  telomere   shortening   compared   to   those   with   shorter   telomeres.  Interestingly,  however,  the  monthly  changes  were  larger  in  the  6-­‐month  study  compared   to   the   10-­‐year   study.  As   mentioned   already,   the   actual   telomere  length   is   the   result   of   various   factors   with   impact   on   telomere   length  homeostasis,  such  as  telomerase  expression,  replication  rates,  oxidative  stress  etc.   There   is   also   a   large   heterogeneity   in   telomere   length   at   individual  chromosome  ends  within  a  cell  [195].  At  a  population  level,  the  collected  data  from   the   field   indicate   that   leukocyte   telomere   length   shortens  with   age.   At  the   individual   level,   mean   blood   telomere   length   appears   to   follow   a   more  oscillating  pattern,  which  levels  out  at  longer  follow-­‐up  periods.    Even   though   the   majority   of   individuals   are   likely   to   exhibit   only   small  fluctuations   over   shorter   time   spans,   our   findings   in   paper   IV   indicate   that  some   individuals   might   experience   marked   telomere   length   changes   within  months.  In  the  blood  donor  study,  one  donor  exhibited  a  substantial  decrease  in   telomere   length   over   a   6-­‐month   period   where   after   the   telomere   length  

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remained   stable   over   the   following   12  months.   The   qPCR   result   was   further  confirmed   by   Southern   blot   and   STELA.   By   permitting   analysis   of   individual  chromosome  arms  (XpYp),  STELA  revealed  a  considerable  decrease  in  telomere  heterogeneity  and  a  loss  of  the  longest  telomeres.    An   important   question   to   address   is   whether   additional   factors   might   have  influenced   or   confounded   the   estimated   blood   telomere   length   values.   For  example,  a  change  in  the  proportion  of  different  immune  cell  subsets  between  two  samplings  may,  at  least  in  theory,  affect  the  average  telomere  length  of  a  blood   sample.   In   a   recent   review   [196],   potential   mechanisms   behind  leukocyte   telomere   lengthening   are   discussed.   The   author   suggests   that  telomerase-­‐mediated   lengthening   could   be   called   “actual   lengthening”,  whereas   an   observed   increase   in   telomere   length   due   to   a   redistribution   of  leukocyte   subsets   might   be   called   “pseudo-­‐lengthening”.   Another   factor   to  consider   is  "regression  to  the  mean"  (RTM)  -­‐  a  statistical  phenomenon  where  random   variations   in   repeated   data   looks   like   real   changes   [197].   More  specifically,   if   an   extreme   value   is   generated   in   the   first   analysis   due   to  measurement  error,  the  second  analysis   is   likely  to  generate  a  value  closer  to  the  mean.  There  are  strategies  to  avoid  a  potential  RTM,  e.g.  by  a  randomized  design  and  by  using  the  mean  of  multiple  measurements  [197].  For  this  reason,  each   sample  was   analyzed   twice   at   different   occasions   in   the   6-­‐month   study  and   the  mean   value   of   the   two   qPCR  measurements  was   used.   In   the   blood  donor   study,   each   sample   was  measured   three   times.   The  mean   inter-­‐assay  coefficient  of  variation  (CV)  was  low  (6.7%  and  5.3%  respectively),  indicating  a  high   reproducibility   for   the   method.  The   reliability   of   the   qPCR   method   has  been   a   topic   of   discussion   among   researchers   within   the   field,   and  standardized   protocols   are   warranted.   The   method,   however,   is   well  established  in  our   lab,  generating  satisfactory   intra-­‐  and  inter-­‐assay  CVs  [145]  [146]   [198]   and   correlating   very   well   with   the   Southern   blot   method   [199].  Nevertheless,  when   investigating   telomere   length   changes  between  different  time   points,   the   variability   of   available  measurement   techniques   should   also  be   taken   into   account,   along   with   other   factors   that   might   influence   the  analysis.    In   summary,   the   results   of   paper   III   and   IV   support   previous   findings   that  leukocyte  telomere  length  is  a  complex  trait,  showing  a  dynamic  character  and  differing  between   immune  cell   subsets.  To  what  extent  e.g.   lifestyle  changes,  ageing  and  disease  may  affect  telomere  length  dynamics  in  these  cells  remain  to   be   further   elucidated,   preferably   by   using   a   study   design  where   telomere  length  is  measured  repeatedly  over  time.    

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CONCLUDING  SUMMARY    • Significantly   longer  blood   telomere   length  was   found   in  our  breast   cancer  

patients  compared  to  controls.  Breast  cancer  risk  increased  with  increasing  telomere   length,   with   the   highest   risk   for   the   quartile   with   the   longest  telomeres.  At  the  present  time,  the  collected  results  from  this  research  area  are   inconsistent   and   large   prospective   studies   are  warranted   to   elucidate  the   role   of   blood   telomere   length   as   a   potential  marker   of   breast   cancer  risk.  

 • Blood   telomere   length   was   found   to   be   an   independent   prognostic  

indicator   in   both   breast   cancer   patients   and   patients   with   RCC.   For   both  cancer   types,   long   blood   telomere   length   was   associated   with   a   worse  survival,   indicating   a   potential   role   for   this   parameter   as   a   prognostic  marker   in   malignancy.   Further   research   is   needed   in   order   to   clarify  whether   blood   telomere   length   may   act   as   a   prognostic   tool   also   at   the  individual  level.    

 • Significant   associations   were   observed   between   certain   immunological  

components   and   telomere   length   in   patients   with   RCC.  More   specifically,  three   cytokines   (IL-­‐7,   IL-­‐8   and   IL-­‐10)   correlated   positively   with   tumor  telomere  length.  Moreover,  whole  blood  and  T  cell  telomere  length  showed  significant   positive   correlations   with   peripheral   levels   of   Treg   cells.   The  association  between  increased  Tregs  and  long  blood  telomere  length  might  reflect   a   suppressed   immune   response  with   less   cell   proliferation   (leading  to   decreased   telomere   shortening)   and   reduced   antitumoral   activity.   The  finding  thus  provides  a  possible  underlying  mechanism  for  our  observation  that  long  blood  telomere  length  is  associated  with  a  poorer  cancer  survival.    

 • Changes  in  blood  telomere  length  over  a  6-­‐month  period  were  significantly  

correlated  with  telomere   length  values  at  baseline  and  follow-­‐up.   In  some  individuals,  marked  changes  in  mean  blood  telomere  length  were  observed  within  months,   supporting   the   notion   that   leukocyte   telomere   length   is   a  dynamic  character.    

 • For   blood   telomere   length   to   be   informative   at   the   individual   level,  

repeated   measurements   over   time   should   be   considered   rather   than  measuring   telomere   length   at   a   single   occasion.   Also,  given   the   fact   that  leukocytes   comprise   a   heterogeneous   group   of   immune   cells,  telomere  length  analysis  in  specific  blood  cell  subsets  might  be  a  preferable  approach  in  future  studies.    

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ACKNOWLEDGEMENTS  

 In English Research is all about teamwork and without the help and support from enthusiastic co-workers, this thesis would not have existed. Therefore, to all colleagues worldwide who have, in any way, been involved in my projects: THANK YOU! I would also like to express my gratitude to all my colleagues at the Department of Medical Biosciences for creating such an enjoyable and inspiring working environment. You rock! In Swedish Jag skulle ju varken bli forskare eller läkare...eller bo i Norrland. Tur livet inte alltid blir som man tänkt sig! :) Ett stort antal personer har betytt oerhört mycket för mig under mina år som doktorand i Umeå och jag vill därför rikta ett varmt tack till följande: Min handledare Göran Roos - Självfallet vill jag rikta det första och absolut största tacket till dig Göran! Under hela resans gång har du stått vid min sida och jag har alltid känt att jag kan prata med dig i alla lägen. Jag är även oändligt tacksam över att vi hittat vägar för att kunna kombinera mina doktorand- och läkarstudier. Ett STORT tack för allt! Börje Ljungberg - Vår trevliga samarbetspartner som hann bli officiell bihandledare lagom till disputationen. Tack för allt gott samarbete Börje! Roosgruppens medarbetare: Magnus B - Min trogna rumskompis som utan tvekan hör till de smartaste och roligaste personer jag känner. Tack för alla skratt, vintips och allmänt intelligenta kommentarer! Kattis N - Ex-labbpartner, mentor och "storasyster", som har bidragit med ovärderlig hjälp till detta arbete (och som tillsammans med maken Andreas dessutom förgyllde mina praktikveckor i Östersund). Tack för allt!

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Helene S - Gruppens förträffliga nytillskott som jag lärt känna i rekordfart. Och min hittills enda walkie-talkie-kompis! Jag förstår inte hur jag klarat mig utan dig tidigare Helene!?! Sofie D - Oumbärlig gruppmedlem som ställer upp i alla lägen. Även känd som gruppens chokladoholic. Du är grym! Ravi - Rumskompis nummer två; alltid glad och hjälpsam och expert på de senaste Apple-prylarna. Emma A - Gruppens bak- och stickexpert! Emma, nu när din halvt utslagna tand fixats och min brutna näsa läkt kanske vi vågar börja träna med varandra igen? Linda K – Alltid lugn som en filbunke och en riktig hejare på gener! Pawel G - Ex-medlem, tidigare rumskompis och den snällaste ortopeden i stan! Aihong - Du är en riktig kämpe och vi håller alla våra tummar för dig! Pia O, Elisabeth G, Ingegerd S och Stamcellslabb – Stort tack för all labbhjälp! Och tack till alla andra trevliga som samarbetar med gruppen (Magnus H, Susann H, Statistik-Mattias och alla jag glömt nämna)! Tack även till Richard P - för att du alltid livar upp stämningen och för att du låtit bli att placera mig i källaren (trots upprepade hot :P) och till Thomas B - för att du tillslut fick mig att "vakna" och söka till läkarprogrammet! Jag har även lärt känna fantastiska människor på biomedicin- och läkarprogrammen. Utan er hade jag aldrig varit där jag är idag. Annalena L och Vincy E - Två av mina allra bästa vänner! I love you guys! Lisa W, Johan W och Fariba J - Ex-biomedicinare och mina (numera utexaminerade) "mentorer" på läkarprogrammet. Tack för oumbärlig hjälp och support!! Emma F, Anna S och Anna M - Mina hemskt trevliga fika-partners och de första läkarstudenter jag lärde känna. . Min nuvarande klass på läkarprogrammet och övriga vänner från biomedicin - Ni vet vilka ni är! Gänget på Farmakologen - Tack för att ni alltid får mig på gott humör! Speciellt tack till Stisse J - för att du är bäst helt enkelt! :)

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Jag vill även rikta ett särskilt tack till alla fina människor som jag fått förmånen att jobba tillsammans med genom mina uppdrag för biomedicin- och läkarprogrammen. Ingen nämnd, ingen glömd! Och sist men förstås inte minst... Min familj, min släkt och mina vänner i Stockholm/Täby/Södern. Ni betyder ALLT! Mamma, Pappa, Patrik och Henke - Alltid stöttande, tröstande och närvarande - trots alla mil som skiljer oss åt! Min fantastiska släkt Johanna W - Min soulmate o tillika kusin. Annelie o Johan, Malin o Magnus, Maria F, Kattis G, Yvonne C - Förhoppningsvis vänner för livet! Karin H.E. - fantastisk (ex-)granne och nära vän till familjen. Eva o Oskar - Mina fina svärföräldrar. Min Gustav - The love of my life. Tack för att du står ut med mig precis som jag är! ♥

   

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