Immunoscore as a possible new approach for the classification of cancers

1Jérôme GALON, PhD
Laboratory of Integrative
Cancer Immunology
Université Paris Descartes
Cordeliers Research Centre
Université Pierre et Marie
Curie Paris 6, Paris

Immunoscore as a possible new approach for the classification of cancers

by J. Galon, France

The American Joint Committee on Cancer and the Union Internationale Contre le Cancer (AJCC/UICC)-TNM staging system provides the most reliable guidelines for the classification of colorectal carcinoma. This tumor staging summarizes tumor burden (T), the presence of cancer cells in draining and regional lymph nodes (N), and evidence for distant metastases (M). However, among patients within the same stage, clinical outcome can be very different. There are multiple other ways to distinguish different subtypes of colorectal cancer, including morphology, cell origin, molecular pathways, mutation status, and gene expression–based stratification. However, these parameters rely on tumor-cell characteristics. Systems biology approaches have facilitated analysis of the complex interaction between tumors and the host immune response, and allowed definition of the immune contexture. Extensive literature has demonstrated the prognostic impact of intratumoral immune cells, whose density is influenced by tumor immunogenicity, chemoattraction, and adhesion. This in situ adaptive immune infiltrate can be quantified by a new methodology named “Immunoscore.” In colorectal cancer, incorporating this new methodology may add to the significance of the current classification system, as it is a prognostic factor shown to be superior to the AJCC/ UICC-TNM classification. An international consortium has been initiated to validate and promote Immunoscore in routine clinical settings. Thus, Immunoscore and standardized immune parameters could become elements of the classification of cancer.

Medicographia. 2015;35:334-340 (see French abstract on page 340)

Definition of cancer

Since the launch of the US National Cancer Plan in 1971, intensive research efforts have been underway. The resulting definition of cancer seems to challenge the previously established concept of the disease. Defining cancer is fundamental, because that shapes how we view the factors influencing tumor progression, and thus, its prognosis and how we approach development of appropriate therapeutic strategies. Consequently, the importance of the tumor microenvironment and immune component of cancers has recently taken center stage.

Biological concepts that dominated the 20th century first led to a strictly cell-centric vision of cancer, giving rise to the somatic mutation theory, which defined cancer as a disease of the DNA within tumor cells. That theory held that transfer or modification of the genome gives the cell a selective advantage, in the Darwinian sense, allowing the development of a mutated cell clone. The discovery of the Philadelphia chromosome in chronic myelocytic leukemia encouraged speculation that it might be possible to define cancer as the result of a limited number of key gene alterations. In other words, after a multistep process of acquiring successive random mutations, increasingly aggressive cell clones would be selected by the emergence of a tumor phenotype. In this cell-centric paradigm, the cancerous cell becomes autonomous, operating independently of its microenvironment. Therefore, genetic alterations were thought to dictate the clinical course of cancer, to accompany tumor progression—local, nodal, and metastatic regional— and were expected to correlate strongly with patient prognosis. Thus, it was believed that cancer treatment could aim to correct genetic alterations or to directly eliminate tumor cells.

Figure 1
Figure 1. Immune infiltrates
of tumors and the immune

(A) Immune infiltrates of tumors (at
the tumor center, invasive margin,
and adjacent tertiary lymphoid
structures) include all immune cell
types. (B) The immune contexture
comprises the type, density, and
location of adaptive immune cells
within distinct tumor regions (Immunoscore
specifically quantifies
the density of memory and cytotoxic
lymphocytes in the tumor
center and invasive margin) and
the immune functional orientation
characterized by immune gene
Abbreviations: MDSC, myeloidderived
suppressor cells; NK, natural
killer; TFH, T follicular helper cells;
TLS, tertiary lymphoid structure.

Advances in the understanding of the molecular biology of cancer have gradually revealed the limits of the genomic cellcentric paradigm. In clinical practice, no gene or genomic signature has drastically improved prognostic classification provided by the TNM staging system (tumor, node, metastasis) in over 80 years.

Definition of cancer integrating the tumor microenvironment

Those observations have led to a paradigm shift where the cancer cell is no longer defined by the acquisition of key genomic alterations, but the acquisition of key secondary behavioral characteristics through genomic changes. Six key characteristics were proposed: (i) evasion of apoptosis; (ii) selfsufficiency in growth signals; (iii) insensitivity to antiproliferative signals; (iv) stimulation of angiogenesis; (v) unlimited potential for replication; and (vi) ability to escape the site of origin and metastasize.1 Thus, at the dawn of the 21st century, the immune system was not recognized among the elements associated with cancer. However, more than a century of work by immunologists has shown the importance of that system. Beyond the now recognized essential role of the immune system in the development of cancers, a holistic vision of cancer includes the microenvironment as a real player in the development and evolution of cancer, and therefore its definition. The microenvironment is defined as a set of cellular compartments associated with cancer cells: vascular, neuroendocrine, stromal, epithelial, and immune.2 These compartments form a heterogeneous, dynamic, and communicative interaction network.

Over the years, the field of cancer immunology has endured fluctuating levels of pessimism and was often deemed controversial. The rebirth of tumor immunology really started in the early 2000s. Novel experimental observations have since invigorated the field, encompassing 3 major achievements. Firstly, immunosurveillance,3,4 the equilibrium phase of cancer,5 and immunoediting and its escape3 was shown in mouse models. Secondly, the importance of the intratumoral natural adaptive immune reaction to the survival of the patient was illustrated, showing for the first time that immune parameters come into play beyond tumor progression and invasion (TNM classification).6,7 These parameters were referred to as immune contexture (Figure 1).6 Thirdly, the successes of several immunotherapies boosting this natural immune response have generated tremendous enthusiasm within the cancer immunology field.8

TNM classification

The most common system for classifying the extent of the spread of cancer is the American Joint Committee on Cancer/ Union Internationale Contre le Cancer (AJCC/UICC)-TNM classification.9-11 This tumor staging gives an estimation of the degree of tumor progression and invasion at the time of surgical resection. Furthermore, multiple tumor-cell parameters give an indication of the intrinsic biology of the tumor. The TNM classification has been used for over 80 years and is valuable in estimating the outcome of patients for a variety ofcancers.9-11 It is used in clinical trials to select patients who are eligible for inclusion.12 This powerful approach has stood the test of time for prognostication; nevertheless, it provides incomplete prognostic information. Clinical outcome can dramatically vary among patients within the same histological tumor stage.12 In some patients, advancedstage cancer can remain stable for years, and in some cases, regression of metastatic tumors can occur spontaneously.13

In contrast, relapse, rapid tumor progression and patient death is associated with approximately 25% of TNM I/II stage colorectal cancer (CRC) patients, despite complete surgical resection and no evidence of residual tumor or metastasis.14 The predictive accuracy of this traditional staging system still relies on the assumption that disease progression is largely a tumor cell– autonomous process, and fails to incorporate the effects of the host immune response.15 Though multiple ways to refine cancer classification have been proposed, they all rely on tumor- cell characteristics. Some examples include immunohistochemistry for tumor biomarkers, flow cytometry for DNA content, molecular signatures, or genetic features. Even imperfect, the TNM classification was never surpassed in multivariate analysis by such alternative methods.

However, we have shown that the analysis of a specific type of intratumoral immune response—by a test called Immunoscore— does indeed surpass the TNM classification in multivariate analysis.7,13 Thus, tumor progression should be considered the result of a balance between an invasive tumor process and a defense system whose major component is constituted by the host immune response.6

Figure 2
Figure 2. Classification methods in colorectal cancer.

In colorectal cancer, in addition to the classical TNM staging system, other tumor-cell characteristics
have been used to classify subtypes. However, the host immune response must also be taken into
consideration, as this can be a powerful predictor of tumor recurrence and patient survival. Immunoscore
has the potential to meet this need.
Abbreviations: M, metastasis; N; nodes; T, tumor.

Molecular subtypes of colorectal cancer

Numerous tumor-cell characteristics have been used to classify the multiple subtypes of colorectal cancer (CRC), including morphology, molecular pathways, mutation status, cell of origin, and gene expression. A morphology-based classification allows the distinction of a number of histologic variants: mucinous, signet ring cell, medullary, micropapillary, serrated, cribriform comedo-type, adenosquamous, spindle cell, and undifferentiated.

These histopathological criteria have a modest prognostic value. CRC can also be classified by molecular pathway, eg, chromosomal instability (CIN), microsatellite instability (MSI), and a CpG island methylator phenotype (CIMP). A third method to classify CRC is based on mutation analysis, including adenomatous polyposis coli (APC), Kirsten rat sarcoma viral oncogene homolog (KRAS), tumor protein 53 (TP53), B-Raf proto-oncogene, serine/threonine kinase (BRAF), neuroblastoma RAS viral (v-ras) oncogene homolog (NRAS), phosphatidylinositol- 4,5-bisphosphate 3-kinase, catalytic subunit α (PI3KCA), and catenin (cadherin-associated protein), beta 1, 88 kDa (CTNNB1) genes. The fourth and fifth methods, assessing the cell of origin and gene expression, are molecular based techniques.

Numerous markers, signatures, and methods have been proposed for evaluating tumor prognosis, yet few of these translate into clinical practice or reach the statistical power of the TNM classification. Although the development of each tumor is thought of as a unique carcinogenic process, similarities may occur, ie, common pathogenic mechanisms may be involved. However, other major parameters must be taken into consideration, in particular the tumor microenvironment (Figure 2).

Immunoscore as a new approach for the classification of colorectal cancer

A potential clinical translation of the immune contexture into a prognostic marker in CRC has been established, designated Immunoscore.6,16-18 Immunoscore was initially described several years ago.7 It was shown to be a prognostic factor at baseline,14,19 but could also play a role as a marker to predict the response to biotherapies targeting the immune checkpoints.6,16,20,21 Immunoscore is based on the quantification of 2 lymphocyte populations (CD3/CD8), both at the tumor center (CT) and the tumor invasive margin (IM).14 Similar results were found when using CD3/CD45RO, or CD8/CD45RO combinations. Immunoscore provides a scoring system ranging from Immunoscore 0 (I0), where low densities of both cell types are found in both regions, to Immunoscore 4 (I4), having high immune-cell densities in both locations. Classification using Immunoscore has been shown to have a prognostic significance superior to that of the classical TNM system, for disease- free survival (DFS), disease-specific survival (DSS), and overall survival (OS). Multivariate Cox analysis revealed that the immune criteria significantly associated with prognosis for CRC stages I, II, and III.13 For the first time, tumor progression and invasion were shown to be statistically dependent on the host immune reaction, where the immune pattern remained the only significant criteria over TNM classification.13,22

CRC patients with clinically localized CRC and no detectable tumor spreading to lymph nodes or distant organs are usually treated by surgical removal of the tumor. However, approximately 25% of these patients will have recurrence of their disease, indicating that occult metastases were already present at the time of surgery. No current tumor-associated marker would predict the recurrence of this subgroup of patients, who may benefit from adjuvant therapy. In comparison, the Immunoscore approach was applied to 2 large independent cohorts, where only 4.8% of patients with I4 relapsed after 5 years and 86.2% were still alive. In contrast, 72% of patients with a low score (I0, I1, and I2) experienced tumor recurrence and only 27.5% were alive at 5 years. This illustrates the importance of Immunoscore as these I0, I1, and I2 patients potentially could have benefitted from an adjuvant therapy if Immunoscore had been incorporated into the tumor staging.14 Clinical validation of Immunoscore with standardized procedures is necessary to reach clinical applicability for individual patients. The aforementioned complexity of immunohistochemistry, coupled with protocol variation, contributes to data variability. A standardized consensus method is therefore required. Large-scale assay harmonization is essential to pursue assay uniformity to reduce these limitations. In answer to this, we have performed multiple Immunoscore quality controls to evaluate the methodology for accuracy and repeatability. We observed that automated cell counting achieved a high level of correlation with optical counting for CD3 and CD8 immunostaining. In addition, the variability between users of the software was minimal.

To evaluate Immunoscore in the clinic and measure its prognostic value, we are conducting a prospective, multicenter, French national study of 600 patients from 7 hospitals. In an effort to promote the utilization of Immunoscore in routine clinical settings, we initiated a worldwide Immunoscore consortium, with the support of the Society for Immunotherapy of Cancer (SITC).21 The worldwide Immunoscore consortium, composed of international expert pathologists and immunologists, identified a strategy to show the feasibility and reproducibility of Immunoscore, validate its major prognostic power in colon cancer stage I/II/III, and to show the utility of Immunoscore to predict stage II colon cancer patients with high risk of recurrence. Evidence-based selection of specific markers for Immunoscore was discussed. The combination of 2 markers (CD3 and CD8) in 2 regions (CT and IM) was agreed for validation in standard clinical practice. Precise quantification is currently performed on whole slide sections, following the recommended initial guidelines. Twenty-three international pathology expert centers are now participating in the Immunoscore enterprise. It is hoped that this initiative will result in the implementation of Immunoscore as a new component for the classification of cancer TNM-I (Immune). Immunoscore should better define the prognosis of cancer patients, better identify patients at high risk of tumor recurrence, help to predict and stratify patients who will benefit from therapies,16 and ultimately, to help save the lives of patients with cancer.

Immunoscore for the classification of cancer

To be used globally in a routine manner, evaluation of a novel marker should have the following characteristics: it should be routine, feasible, simple, inexpensive, rapid, robust, reproducible, quantitative, standardized, and powerful. Immunoscore has the potential to fulfill these key criteria (Figure 3, page 338). In addition, Immunoscore provides a tool for novel therapeutic approaches, including immunotherapy.23-26 A meta-analysis summarizes the impact of immune cells including all subsets of T cells on clinical outcome from more than 120 published articles.17 Importantly, the beneficial impact of the immune infiltrate with T cells of the cytotoxic (CTLs) and memory phenotype has been demonstrated in cancers from diverse anatomical sites, including colorectal, but also melanoma, head and neck, breast, bladder, urothelial, ovarian, esophageal, prostatic, pancreatic, cervical, hepatocellular, and gastric cancers, medulloblastoma, and merkel cell carcinoma.17 It is interesting to note that the implications of this immune phenotype apply not only for various organs of cancer origin, but also to various cancer cell types, ie, adenocarcinoma, squamous cell carcinoma, large cell cancer, and melanoma. Thus, general characteristics emerge in which CTLs, memory T cells, and TH1 cells are associated with prolonged survival.6,16,27

Considering the probable universal character of the immune control of tumors, it is essential to take into account the immune parameter as a prognostic factor and to introduce the Immunoscore as a component of cancer classification, not restricted to CRC (Figure 3).15,16,19-21 Accumulating evidence suggests that once human cancer becomes clinically detectable, the adaptive immune response plays a critical role in preventing tumor recurrence. The ability of effector-memory T cells to recall previously encountered antigens leads to a protective response. Following primary exposure to antigen, memory T cells disseminate and are maintained for long periods of time.28 The trafficking properties and the long-lasting antitumor capacity of memory T cells could result in long-term immunity in human cancer. Over the past few years, the area of immune regulation at the level of the tumor microenvironment has gained a forefront position in cancer research, in CRC,6,7,13,14,28-31 in melanoma,32 and all other cancer types.15

Figure 3
Figure 3. Immunoscore
utilizes histopathological
methods with software
to digitally quantify the
density of the in situ
adaptive immune infiltrate
in the tumor center
and invasive margin, assigning
a score that indicates
prognostic risk assessment
on a scale
from I0 to I4, with I0 representing
high risk and
I4, low risk of tumor recurrence.

Abbreviations: FFPE, formalinfixed
paraffin-embedded tissue.

Monitoring of immune parameters beyond immunoscore

The analysis of 28 different types of tumor-infiltrating immune cells illustrated that the cells with the strongest impact on patient survival were adaptive immune cells.29 These include the cells evaluated by Immunoscore assay, T cells (CD3), CTLs (CD8), and memory T cells (CD45RO). Immunoscore represents the most powerful assay for cancer classification at baseline. Other adaptive immune cells, including T follicular helper (TFH) cells and B cells, were shown to be strongly associated with a favorable outcome and protection against tumor recurrence,29 whereas other cells had less impact.

Chemokines have an important role in orchestrating both innate and adaptive immune cell chemotaxis and localization within the tumor. Chemokines can direct development and maintenance of tertiary lymphoid structures (TLS), which has been described in multiple cancer types including non–small cell lung cancer, melanoma, and colorectal carcinoma.29,33-35 We examined the predictive capability of chemokines using data integration of gene expression in primary tumors from CRC patients.36 We discovered a significant prolongation of DFS in patients with high expression of the chemokines CX3CL1, CXCL10, and CXCL9. CX3CL1, also known as fractalkine, mediates T-lymphocyte and monocyte migration and promotes strong adhesion to endothelial cells.37 CXCL10 and CXCL9 are closely related cytokines. They facilitate migration of CTLs, monocytes, natural killer (NK), and dendritic cells. Indeed, CRC patients with elevated gene expression of one of these 3 chemokines had increased percentage and density of CD3+CD8+ T lymphocytes in the tumor as assessed by flow cytometry and immunohistochemistry.36 High expression density of CXCL9 and CXCL10 also accurately predicts prolonged DSS in melanoma patients.35,38 Preclinical studies with melanoma show that blocking CXCL9 or CXCL10 substantially reduces the ability of CTL to traffic to the primary tumor and distant metastatic lesions.38 This may be due to their role in directing CTL homing to the tumor by CD4+ T-cell help.

Another chemokine, CXCL13, that was recently found to be associated with TFH lymphocytes, also predicts patients’ clinical outcome. CXCL13 is produced by and has been associated with generation of TLS within the IM of primary tumors.29,34,39 In conjunction with this observation, CXCL13 as a single biomarker can accurately predictCRC patients’ clinicaloutcome.29 Similarly, in specific subtypes of breast cancer, elevated expression of CXCL13 in the tumor is associated with increased DFS compared with tumors with low expression of CXCL13.40 It is becoming increasingly clear that chemokines have an essential role in trafficking CTL to the tumor site. Furthermore the addition of chemokine expression to Immunoscore has potential to predict patient response to chemotherapy.41

Correlating immune responses and clinical outcome in immunotherapy trials

The efficacy of immunotherapeutic interventions is generally assessed by parameters defining the clinical outcome, such as OS or PFS. Clearly, immune responses can be assessed much earlier than these clinical parameters and thus be used for immunoguiding purposes during therapy, or to stratify patients prior to treatment for maximum benefit.6,42 Various clinically successful immunotherapeutic approaches have been reported, such as sipuleucel-T for prostate cancer43 and ipilimumab for melanoma.24 In contrast to many standard therapies, objective clinical responses are typically delayed under immunotherapy due to the time required for activation and amplification of immune effector mechanisms.44,45 In patients with advanced melanoma, endogenous T-cell responses against melanoma antigen Melan-A and cancer-testis antigen NY-ESO-1, as assessed by intracellular cytokine staining in blood samples, had a strong prognostic impact on survival.46

Additionally, an immune response to NY-ESO-1 provided a predictive value for ipilimumab treatment, where patients with existing antibody and CD8+ T-cell responses against NYESO- 1 experienced a clinical benefit and significant survival advantage.47 Pre-existing T-cell responses in the bone marrow correlated with reduced cancer mortality risk in untreated breast cancer patients.48

Many of the studies that successfully demonstrate a correlation between vaccine- or spontaneously-induced immune responses and clinical benefits are based on well-established immune assays that underwent external validation and followed harmonization guidelines for optimal performance. However, we are still in need of larger data sets in order to establish reliable biomarkers that can be used for broad application of immunoguiding. The immune contexture should also be a target for innovative therapies, particularly immunotherapies.

Indeed, innovative therapies that induce longer survival in patients modify the immune contexture of the tumors, usually by inducing an increased infiltration of CD8+ T cells.17 It is the case for classical chemo-49 and radiotherapies, for targeted therapies such as Braf inhibitors,50 or inhibitors of angiogenesis that decrease regulatory T cells (Tregs) and myeloid derived suppressor cells (MDSCs),51,52 and of course for immunomodulatory antibodies such as anti–CTL-antigen 4 (anti– CTLA-4),24 anti–programmed cell death protein 1 (anti–PD-1)53 and anti–programmed death-ligand 1 (anti–PD-L1).54,55


Given the power of immune-cell–infiltration quantification, it is hoped that Immunoscore will become a new component for the classification of cancer, leading to a TNM-I (Immune) classification.56 Immunoscore should better classify cancer patients at baseline, better define the prognosis of cancer patients, better identify patients at high risk of tumor recurrence, help to predict and stratify patients who will benefit from therapies and, ultimately, to help save the lives of patients with cancer. ■

Acknowledgments: This work was supported by grants from the National Cancer Institute of France (INCa), the Canceropole Ile de France, INSERM, Cancer Research for Personalized Medicine (CARPEM), Paris Alliance of Cancer Research Institutes (PACRI), and LabEx Immuno-Oncology.

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Keywords: adaptive immunity; cancer classification; immune contexture; Immunoscore; immunotherapy; T cell; tumor microenvironment