Society for Immunotherapy of Cancer Immunoscore Validation Project

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Alternative tumor-interrogatory methods, such as characterizing gene expression and mutational burden, molecular pathways, cellular morphology, and cellular origin, can be used to distinguish between cancer subtypes and may offer some additional prognostic value.²However, instances in which clinical outcomes are drastically different between patients within the same stage, patients who maintain stable late-stage disease for years, or the rapid decline of early-stage patients, underscore the limited ability of the current staging systems.

Although solid tumors can be infiltrated by varied populations of immune cells, the presence of T lymphocytes, specifically cytotoxic and memory T cells, has been associated with a favorable prognosis across diverse cancer types, including colorectal, lung, breast, and skin cancer.³This discovery has changed the way in which cancer is conceptualized.

Implicit in the tumor-centric classification systems is the idea that malignancy is an active process within a permissive host, but it is now recognized that the extent to which cancer can progress depends upon the robustness of the host antitumoral immunity.^4,5Therefore, the classification of cancer should consider both sides of the equation—the malignant imperative and the immune counter defense—for the greatest prognostic power. Ideally, such a method should also possess the characteristics of a good biomarker so that it can be integrated easily into clinical practice, that is, it should be objective, specific, and quantitative.²

Proof of principle for an immune-based classification system was first demonstrated in 2006 for colorectal cancer, where it was noted that lymphocytic infiltrates were not randomly dispersed throughout the tumor.6 Rather, the immune cells were organized with concentrations in the center of the tumor (CT) and at the invasive margin (IM). Furthermore, high densities of total T lymphocytes as well as cytotoxic and memory T cell subsets (CD3, CD8, granzyme, CD45RO) at these sites correlated with a favorable prognosis and were found to be more predictive of clinical outcome (disease-free survival and overall survival) than standard TNM staging, with implications for the identification of high-risk patients “hidden” in early TNM stages.⁶The prognostic value of scoring the immune response in this way has since been reproduced in a variety of other malignancies.⁷In 2012, the Society for Immunotherapy of Cancer convened a worldwide consortium to validate the Immunoscore as a standardized assay for use in routine clinical settings.⁸

This international validation project was initiated with 23 pathology centers across 17 countries, and more than 3,500 samples from patients with stage I-III colon cancer were evaluated. The patient samples that met selection criteria were divided among 3 distinct cohorts: the training subset used to define the mean score and Immunoscore ranges and 2 independent cohorts to validate the training set parameters. To ensure feasibility and reproducibility across institutions, the standardized method utilized immunohistochemistry (CD3+ and CD8+) and digital pathology to assess the density of immune cells in the CT as well as the IM. Patients were then stratified into Immunoscore-Low (immune cell-poor) and Immunoscore-High (immune cell-rich) groups based on the density of T lymphocytes present, and the data for all samples was analyzed by external statisticians.

The primary endpoint of time-to-recurrence for this study has been met and the results of this global validation initiative were presented recently. Time-to-recurrence was significantly longer in Immunoscore-High patients (stages I/II/III) in all 3 cohorts of patients tested compared to patients with a low score, with similar results for disease-free survival and overall survival.

Further illustrating the need to consider the immune component of cancer, the Low-Immunoscore group identified a subgroup of patients with high-risk stage II colon cancer whose disease had recurred more quickly. Thus, the predictive power of the Immunoscore over TNM staging supports the addition of the first immune-based biomarker assay for the classification of cancer and reinforces the powerful influence of the immune system on cancer pathogenesis.

This is a particularly timely finding in the era of immunotherapy, as Immunoscore-based assays could be used to predict which patients would be more likely to benefit from treatment modalities such as checkpoint blockade or whether strategies such as adjuvant therapy or cancer vaccines to prime immunity might be more appropriate. More broadly, the results of the Immunoscore study have potential implications for the field of immune monitoring as a rapid means of determining response to treatment.

References:

1. Edge SB, Compton CC. The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM.Ann. Surg. Oncol.2010;17:1471-4.
2. Galon J, Mlecnik B, Bindea G, et al. Towards the introduction of the ‘Immunoscore’ in the classification of malignant tumours.J. Pathol.2014;232:199-209.
3. Fridman WH, Pages F, Sautes-Fridman C, et al. The immune contexture in human tumours: impact on clinical outcome.Nat. Rev. Cancer2012;12:298-306.
4. Pages F, Galon J, Dieu-Nosjean MC, et al. Immune infiltration in human tumors: a prognostic factor that should not be ignored.Oncogene.2010;29:1093-102.
5. Galon J, Angell HK, Bedognetti D, et al. The continuum of cancer immunosurveillance: prognostic, predictive, and mechanistic signatures.Immunity.2013;39:11-26.
6. Galon J, Costes A, Sanchez-Cabo F, et al. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome.Science.2006;313:1960-4.
7. Ascierto ML, De Giorgi V, Liu Q, et al. An immunologic portrait of cancer.J. Transl. Med.2011;9:146.
8. Galon J, Pages F, Marincola FM, et al. The immune score as a new possible approach for the classification of cancer.J. Transl. Med.2012;10:1.