angel curopimmunol 2013

COIMMU-1196; NO. OF PAGES 7

tne,2

Available online at www.sciencedirect.comimmune cells, cytokines, chemokines and products ofcellular metabolism. The inherent complexity of such amultifactorial disease renders the process of patient prog-nosis and prediction of response to therapy extremelydifficult. A good prognostic marker is a biomarker thatprovides information on the likely course of the disease inan untreated individual or regardless of treatment. How-ever, a predictive biomarker can be used to identifysubpopulations of patients who are most likely to respondto therapy.

system, it is becoming recognized within the cancercommunity that clinical outcome can significantly varyamong patients within the same stage. The current classi-fication provides limited prognostic information, and doesnot predict response to therapy. Advances in this fieldhave alluded to the importance of the immune prevalencewithin the tumor microenvironment. A strong lympho-cyte infiltration has been reported to be associated with anantitumor response and improved clinical outcome. Thiscorrelation between the prevalence of tumor infiltrating

www.sciencedirect.com Current Opinion in Immunology 2013, 25:17From the immune contexture toprognostic and predictive immuHelen Angell1,2,3 and Jerome Galon1

The inherent complexity of multifactorial diseases such as

cancer renders the process of patient prognosis and prediction

of response to therapy extremely difficult. Many markers,

signatures, and methods have been described to evaluate the

prognosis of cancer patients, yet very few translate into the

clinic. Systems biology approaches have facilitated analysis of

the complex interaction between tumors and the host-immune

response, and allowed the definition of the immune contexture.

Here we review the potential of the immune contexture,

quantified by the Immunoscore, to provide a statistically strong

parameter for prognosis. Finally we introduce the concept that

the host-immune reaction could be the critical element in

determining response to therapy. The effect on the immune

response could be the underlying factor behind many of the

predictive makers.

Addresses1 INSERM, U872, Laboratory of Integrative Cancer Immunology, Paris,

France2 Universite Paris Descartes, Paris, France3 Centre de Recherche des Cordeliers, Universite Pierre et Marie Curie

Paris 6, Paris, France

Corresponding author: Galon, Jerome ([email protected])

Current Opinion in Immunology 2013, 25:xxyy

This review comes from a themed issue on Cancer immunotherapy:

clinical translation

Edited by Tom Gajewski and Ton Schumacher

0952-7915/$ see front matter, Published by Elsevier Ltd.

http://dx.doi.org/10.1016/j.coi.2013.03.004

IntroductionThe evolution of cancer is greatly influenced by thecomplex milieu and microenvironment in which it devel-ops, harboring tumorcell interactions with host endo-thelial cells, fibroblasts, blood vessels, lymph vessels,Please cite this article in press as: Angell H, Galon J. From the immune contexture to the Immun(2013), http://dx.doi.org/10.1016/j.coi.2013.03.004he Immunoscore: the role of markers in cancer

,3

Definition of immune contextureHistological analysis of human tumors, in particular color-ectal tumors (CRC), has highlighted the importance ofthe combination of immune variables. Tumor immuneinfiltrates include macrophages, dendritic cells (DC),mast cells, natural killer (NK) cells, nave and memorylymphocytes, B cells and effector T cells. Analysis ofthese in situ immune components and their organizationhas revealed large heterogeneity between tumor typesand also a broad patient-to-patient diversity. The role ofthe immune system in controlling tumor progression andits effect on tumor escape, and thus patient prognosis, isbecoming increasingly understood. We have previouslydescribed these major immune parameters, associatedwith survival, as the immune contexture [1]. Theimmune contexture is defined as the type, functionalorientation, density and location of adaptive immunecells within distinct tumor regions [1,2,3,4]. As sum-marized in Figure 1a, the parameters that establish theimmune contexture comprise the density of CD8+ cyto-toxic T lymphocytes (CTL) and memory T cells(CD45RO+), their location at the tumor center (CT)and invasive margin (IM), combined with the qualityof tertiary lymphoid structures (TLS) and additionalfunctionality entities such as TH1-related factors (IFNG,Tbet, IRF1, IL12), chemokines (CX3CL1, CXCL9,CXCL10, CCL5, CCL2), adhesion molecules (MAD-CAM1, ICAM1, VCAM1) and cytotoxic factors (gran-zymes, perforin, granulysin).

Immune markers as prognostic markersTraditionally, the anatomic extent of the tumor burden inCRC and all solid tumors has been the most importantprognostic factor (Figure 1b). Data on the tumor burden(T), combined with the presence of cancer cells in drain-ing and regional lymph nodes (N) and evidence ofmetastases (M), amalgamate to provide tumor staging(AJCC/UICC-TNM classification). TNM stages estimatepatient postoperative outcome and the rationale for adju-vant therapy. Despite the prognostic power of this stagingoscore: the role of prognostic and predictive immune markers in cancer, Curr Opin Immunol

2 Cancer immunotherapy: clinical translation

COIMMU-1196; NO. OF PAGES 7Figure 1

OSDFS

I II

T1

T2

T3

T4

(a) (b)

Key ParametersImmune Key ParametersTNM

OSDFS

CD8+

CD45RO+

Tumour centre

Invasive margin

TLS

Cytotoxicfactors

ChemokinesCytokines

Adhesionmolecules

Th1

Tumour Stage: immune cells and patient outcome has been well docu-mented in melanoma [58], ovarian [9,10,11], head andneck [1214], bladder [15,16], breast [1720], urothelial[16], colorectal [2,21,22,23,2440], renal [41], prostatic[4244] and lung cancer [4549]. The majority of studieshave demonstrated that high densities of CD3+ T cells,CD8+ cytotoxic T cells and CD45RO+ memory T cellsare associated with a longer disease free survival (DFS)and/or improved overall survival (OS) [3].

Immunoscore as prognostic markerAccumulating data, collected from large cohorts ofhuman cancers, have demonstrated the impact ofimmune-classification, which has a prognostic valuethat may add to the significance of the AJCC/UICCTNM-classification. Derived from the immune contex-ture, a simple and powerful immune-classification hasbeen termed the Immunoscore (Figure 1c). TheImmunoscore (I) is based on the numeration of twolymphocyte populations (CD3/CD45RO, or CD3/CD8or CD8/CD45RO) quantified within the CT and IM.These parameters provide a scoring system ranging

Please cite this article in press as: Angell H, Galon J. From the immune contexture to the Immun(2013), http://dx.doi.org/10.1016/j.coi.2013.03.004

Functionalorientation

Th1 cell-associated factorsCytotoxic factorsChemokines, cytokinesAdhesion molecules

Density Continuous

LocationTumour centre (CT)Invasive margin (IM)Presence and quality of TLS

TypeCTLs (CD3+CD8+)Memory T cells(CD3+CD45RO+)

Contexture

1.38/0.09 ns 1.18/0.2

Cox analysis(ref. 23)

DFS OS HR/P-value HR/P-va

Metastases(M) Evidence of distant sit

Lymph node(N)

Presence of cancer ceand regional lymph no

Tumour (T) Longitudinal extent of Staging

Characteristic : complex Characteristic : current standard class

Schematic representation and accompanying key parameters distinguishing

and tertiary lymphoid structures (TLS); (b) the TNM classification system, high

the importance of the immune reaction regardless of tumor burden. CT, tum

disease specific survival; IM, invasive margin; OS, overall survival.

Current Opinion in Immunology 2013, 25:17 III IV

N+ M+

(c)

Key ParametersImmuno-

OSDFS

OS DFS

Tumour Immune Reaction

I0 I4I1, I2, I3Immunoscore:from Immunoscore 0 (I0), which has low densities ofboth cell types in both regions; to Immunoscore 4 (I4),having high densities of both cell populations in bothregions. The prognostic value of using these immunecriteria was demonstrated in patients with early stageCRC (AJCC/UICC TNM stage III CRC) to predictsurvival and relapse [27]. The five Immunoscore groupswere associated with dramatic differences in DFS andOS (P < 0.0001). Five years after diagnosis, only 4.8%of patients with high densities of CD8 and CD45ROcells had tumor recurrence, and 86.2% survived. Incontrast, the tumor recurred in 75% of patients withlow densities of these cell populations and only 27.5%survived [27].

Combined evidence illustrates the dependency of thecurrent staging stratification on factors of the immuneresponse. In particular, the nature, functional orientation,density, and location of adaptive immune cells withindistinct tumor regions have been illustrated to have aprognostic value that may be superior to the TNM-classification. Cox multivariate analysis shows that tumor

oscore: the role of prognostic and predictive immune markers in cancer, Curr Opin Immunol

9 ns 1.43/0.10 ns

DSSlue HR/P-value

e metastases

lls in drainingdes

tumour burden

0.64/

Prognostic and predictive immune markers in cancer Angell and Galon 3

COIMMU-1196; NO. OF PAGES 7progression and invasion is statistically dependent on theImmunoscore. Indeed, the immune pattern remained theonly significant criterion over the classical AJCC/UICCTNM classification for DFS and OS [50]. In patients whodid not relapse, the density of CD8 infiltrates was inverselycorrelated with T stage, whereas in patients with recur-rence the number of CD8 cells was low, regardless of the Tstage of the tumor [23]. Thus, evidence supports the notionto introduce immunological biomarkers, implemented as atool for the prediction of prognosis and response to therapy.Incorporating the Immunoscore into traditional classifi-cation could result in a greatly improved prognostic andpotentially predictive tool [51,52]. Immunophenotypingas part of routine diagnostic and prognostic assessment oftumors may provide crucial novel prognostic information,facilitate clinical decision-making including rational stra-tification of patient treatment and guide therapeutic strat-egies [53,54].

Additional prognostic markersPrognostic markers are clinical measures used to estimatean individual patients outcome, such as recurrence ofdisease, and correlate with survival independently ofsystemic therapy. These prognostic factors range fromsimple measures such as the stage of disease or tumorburden, to more complex markers, including geneticmutations. Many of the important prognostic markershave been established for numerous diseases, however,the translation of new markers into the clinic is becomingincreasingly difficult. Established markers include theamplification of the MYCN proto-oncogene as anindicator of poor outcome in neuroblastoma [55]. Thenumber of lymph nodes has a strong influence on theprognosis of recurrence-free survival in breast cancer[56,57]. In addition, the mutational status of K-ras is alsoused as a prognostic marker, for example in non small celllung cancer (NSCLC) [58].

The development of high throughput cDNA microarrayand tumor array technologies has led to the investi-gation of global gene and protein expression profiles,which has begun to revolutionize the search for pre-dictive and prognostic markers. The detection of subtlechanges in the genetic composition of different tumorstages offers the possibility of defining more preciseclinical outcomes. Example predictors include the 70-gene signature [59] and intrinsic-subtype classifiers[60] in breast cancer, among many others in additionaldisease settings [6164]. Unfortunately accuracies ofthese predictors are still lower than 80% and thus itremains difficult to identify a highly precise prognosticbiomarker for use across multiple patient cohorts. Stu-dies have also attempted to find gene predictor lists inovarian cancer. Nine gene signatures were reported

with almost no common genes between each signature(similarly to other cancer types) and none of these havebeen implemented into the clinic.


www.sciencedirect.com Genomics-based technologies have resulted in significantadvances in cancer diagnostics and prognostics, whereingenomic instability, caused during dysregulated prolifer-ation, is becoming increasingly investigated for its role indiagnostics. A mutation in the adenomatous polyposis coli(APC) gene occurs in approximately 60% of CRCpatients, as well as many others and is being used as abiomarker to determine the stage, disease recurrence andto monitor disease progression or response to therapy inesophageal cancer [65]. An increase in the level of hyper-methylated APC in the blood is associated with poorsurvival.

The success and global utilization of a prognostic markerrequires key features in its implementation, includingfeasible in routine settings, simple, inexpensive, rapid,robust, reproducible, quantitative, standardized, andpowerful. The Immunosore appears to fulfill theserequirements [52]. Many markers, signatures, andmethods have been described to evaluate the prognosisof cancer patients. Yet very few such markers and labora-tory assays translate into clinical practice or reach thestatistical power of the Immunoscore. It is acknowledgedthat additional markers may be used to further refine theprognostic value of the Immunoscore.

Predictive markersPrognostic markers are useful to assess the risk of anindividual patient, however, they do not provide infor-mation on whether a therapeutic regime will bebeneficial. Thus, we require additional biomarkers toaid in treatment selection. For example, HER-2 over-expression has been associated with improved response totrastuzumab (monoclonal antibody against HER-2) inbreast cancer [66,67].

Numerous different therapeutic regimes are currentlyused to treat cancer, including cytotoxic therapies suchas chemotherapy and radiotherapy. Antibody therapiesinclude cancer centric approaches (tyrosine kinase inhibi-tor), tumor microenvironment directed strategies (anti-VEGF antibodies [68]) or immune focused interventionsuch as anti-PD1 [69,70] and the anti-CTLA4 antibodyipilimumab [71,72,73]. In addition, the implementationof small molecule inhibitors is increasing, for exampleBRAF inhibitors [74]. Immunotherapeutic approachesinclude Toll-like receptor (TLR) agonists, DC basedvaccines, peptide vaccines and adoptive T cell therapy(ACT) [75]. It is becoming apparent that the majority ofthe aforementioned therapies have an impact on theimmune system [3] (Figure 2a).

The efficacy of an anticancer therapy is primarily eval-uated by its ability to inhibit the proliferation of tumor

cells. Whether or not the tumor immune contexturepredicts therapeutic response is of paramount importancein patient clinical management [3]. One of the hurdles


Current Opinion in Immunology 2013, 25:17


COIMMU-1196; NO. OF PAGES 7

alll

mu

pre

adirelated to the development of novel cancer immunothera-pies is the absence of immune response biomarkers toindicate the efficacy and kinetics of the antitumorresponse. Current studies begin to highlight the inter-action between tumor cell death, triggered by chemother-apy/radiotherapy and how this initiates animmunoadjuvant pathway that may contribute to thesuccess of the treatment. The prevalence of immune

Figure 2

ACT AbsTLRag

Vac Chemo Radio

Strong

Null

Weak

Moderate

MajorIm

pact

on

imm

une

resp

onse

Therapy

Smmo

(a) Cancer Treatment

(a) Schematic illustrating the impact of cancer treatments on the host im

difference in overlap between immune and non-immune prognostic and

agonist; Vac, vaccines; Abs, antibodies; Chemo, chemotherapy; Radio, rinfiltrates appears to predict clinical response to someimmunotherapies, including response to cancer vaccines[76]. Breast cancer patients with a loss-of-functionmutation in TLR4 relapsed earlier after receiving anthra-cycline-based chemotherapy [77]. The survival benefit of5-fluorouracil-based chemotherapy in CRC patients wasgreatly improved with the presence of tumor infiltratinglymphocytes (TILs, P = 0.02). Patients with increasedlevels of perforation of the serosa wall also had improvedsurvival (P = 0.16) [78]. Since the presence of TILsreflects an adaptive immune response and perforationis associated with inflammatory response, results suggesta potential interaction between the immune response andchemotherapy.

To demonstrate the predictive value of a biomarker, oneneeds a randomized trial in which a control arm ofuntreated patients should be evaluated; otherwise, aso-called predictive marker is likely to be prognostic aswell.

An immune predictive marker is likely to be aprognostic markerA limitation in the accuracy of many predictive markers isthe assumption that tumor progression is largely a cell-autonomous process with a cancer cell centric focus.


Current Opinion in Immunology 2013, 25:17 However, the presence of immune cells may reflect adistinct underlying biology of the tumor, since geneexpression profiling and confirmatory assays haverevealed the presence of a broad signature of inflam-mation [79]. This signature includes evidence for innateimmune activation, chemokines for T cell recruitment,immune effector molecules, and expression of immuneregulatory factors. Of the aforementioned therapeutic

Current Opinion in Immunology

Prognostic Predictive

Non-immunemarkers

Immunemarkers

(b) Biomarkers

ne response. (b) Diagrammatic representation depicting the potential

dictive markers. ACT, adoptive cell transfer; TLR, toll-like receptor; ag,

otherapy; Small mol, small molecules.strategies, the related predictive markers could in factbe a reflection of a pre-existing immune contexture and ofthe immune response to the therapy. Are predictivemarkers biased depending on their influence on theimmune contexture? Does the patients original immunestatus skew survival outcome, regardless of therapy?Because of this, with a few exceptions, it is our opinionthat a predictive marker is likely to also be a prognosticmarker (Figure 2b). Since tumor molecular features andimmune reactions are inter-related, a comprehensiveassessment of these factors is critical [80]. Examiningthe effects of tumorhost interactions on clinical outcomeand prognosis clearly represents an evolving interdisci-plinary field. Pathological immunity evaluation may pro-vide novel information on prognosis and help identifypatient cohorts more likely to benefit from immunother-apy.

ConclusionsSystems biology and large-scale analysis are powerfulapproaches to uncover mechanisms associated with tumorprogression and tumor recurrence. Integrative analysesevaluating the immune infiltrate in human cancers are ofmajor importance. We have previously described thesemajor immune parameters, associated with survival, as theimmune contexture. The immune contexture is defined


www.sciencedirect.com


COIMMU-1196; NO. OF PAGES 7as the type, functional orientation, density and location ofadaptive immune cells within distinct tumor regions.Compared to the immune contexture, no tumorparameter associated with survival has been reported toachieve the same level of significance in CRC. For routinetesting, a simple method has been proposed and definedas the Immunoscore. The outcome of a current worldwidetask force to validate the Immunoscore in a multicentertrial may result in its implementation as a new componentfor the classification of cancer, designated TNM-I(TNM-Immune). Furthermore, the immune contextureand the Immunoscore may allow the prediction ofresponse to many immune-related therapies. Finally, itis expected that defects in the immune contexture willprovide new therapeutic strategies to treat cancer.

AcknowledgementsWe acknowledge all the scientists who made contributions to the area ofresearch reviewed here that were not cited due to space constraints. Wethank the members of the Laboratory of Integrative Cancer Immunologyfor their invaluable contribution. The work performed in our laboratory wassupported by grants from the Institut National du Cancer (INCa), theCanceropole Ile de France, INSERM, MedImmune, Qatar NationalResearch Fund under its National Priorities Research Program awardnumber NPRP09-1174-3-291, the European Commission (7FP, GenincaConsortium, grant 202230), and the LabEx Immuno-oncology.

References and recommended readingPapers of particular interest, published within the period of review,have been highlighted as:

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From the immune contexture to the Immunoscore: the role of prognostic and predictive immune markers in cancerIntroductionDefinition of immune contextureImmune markers as prognostic markersImmunoscore as prognostic markerAdditional prognostic markersPredictive markersAn immune predictive marker is likely to be a prognostic markerConclusionsAcknowledgementsReferences and recommended reading

angel curopimmunol 2013

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