Towards the introduction of the ‘Immunoscore’ in the classification of malignant tumours

Abstract

The American Joint Committee on Cancer/Union Internationale Contre le Cancer (AJCC/UICC) TNM staging system provides the most reliable guidelines for the routine prognostication and treatment of colorectal carcinoma. This traditional tumour staging summarizes data on tumour burden (T), the presence of cancer cells in draining and regional lymph nodes (N) and evidence for distant metastases (M). However, it is now recognized that the clinical outcome can vary significantly among patients within the same stage. The current classification provides limited prognostic information and does not predict response to therapy. Multiple ways to classify cancer and to distinguish different subtypes of colorectal cancer have been proposed, including morphology, cell origin, molecular pathways, mutation status and gene expression-based stratification. These parameters rely on tumour-cell characteristics. Extensive literature has investigated the host immune response against cancer and demonstrated the prognostic impact of the in situ immune cell infiltrate in tumours. A methodology named ‘Immunoscore’ has been defined to quantify the in situ immune infiltrate. In colorectal cancer, the Immunoscore may add to the significance of the current AJCC/UICC TNM classification, since it has been demonstrated to be a prognostic factor superior to the AJCC/UICC TNM classification. An international consortium has been initiated to validate and promote the Immunoscore in routine clinical settings. The results of this international consortium may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune). © 2013 The Authors. Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Long non-coding RNAs in colorectal cancer: implications for pathogenesis and clinical application

“…[40][41][42] This disease-specific focus has identified novel oncogenic drivers, and the genes contributing to functional change, 43 importantly, revealed that different molecular features contribute to individual differences that occurred in clinicopathological characteristics, disease behavior, prognosis, and response to treatments, which thus helped to establish definitions of molecular subtypes and identified new biomarkers on the basis of omic alterations. [44][45][46] It is now well known that some CRC cases are linked to some factors, such as environment, 47 inflammation, 48,49 immunity, 50 and epigenetic alterations 51,52 rather than heritable genetic changes. An interesting thing is that these factors can influence each other, for instance, epigenetic aberrations induced by environmental factors contribute to cancer processes; 53 interaction of drug and molecular characteristics can influence lncRNAs and clinical outcome; 46,54,55 and epigenetic factors such as lncRNAs can also coordinate cellular responses to environment in turn.…”

Cell-to-cell distances between tumor-infiltrating inflammatory cells have the potential to distinguish functionally active from suppressed inflammatory cells

“…Recent data suggested to include an "immunoscore" in the TNM classification of malignant tumors (TNM). 4 Yet, the interaction of inflammatory cells might not only depend on the frequency of immune cells, but also on the inter-individual distances as cells might interact via soluble factors but also via cell-cell contact. Accordingly, the mapping of the tumor microenvironment has recently gained importance.…”

Immunological metagene signatures derived from immunogenic cancer cell death associate with improved survival of patients with lung, breast or ovarian malignancies: A large-scale meta-analysis

“…While the number of cancer patients included in this study (>1,000 per cancer-type) may partly compensate for patient-to-patient tumor heterogeneity yet emerging evidence suggests that immunological tumor heterogeneity (e.g., tumor core vs. invasive margins) needs to be taken into consideration for prognostic analysis. 6 In this sense, it would be also important to differentiate between expression profiles of cancer cells versus immune cells -a point that could not be achieved in the current study. Even more importantly, differential expression of certain immunegenes may not be representative of their signaling context.…”

“…This reaffirms the standing notion in the field of immune-prognostics that T cell activity/function-related biomarkers have a great probability of having a 'pan-cancer' positive prognostic impact in cancer patients. 5,6,37,41 However, what was peculiar was, that it was not always the same aspect of T cell activity/function that had a prognostic impact across all cancer types. For instance, T cell infiltration (CD8 C B, CD8 C A, CD4 C ) and Th17 polarization (IL17A, IL17RA) markers associated with prolonged survival in breast cancer patients; on the other hand, T cell motility (CD2, PSTPIP1) and T-cell receptor (TCR)-associated signaling (IFNGR1, CD247, PTPN7) based markers showed positive prognostic impact in lung cancer patients while Th1/Th17 polarization (CD4 C , IFNG, IL17A, IL17RA), T cell-based cytotoxicity (PRF1, GZMA) and T cell proliferation (IL2RG, IL2RB) related biomarkers showed positive prognostic impact in ovarian cancer patients.…”

“…Ideally, biomarkers should reflect the complexity of a tumor mass across various cancer-types. 5 Several clinical and pathological indicators have been introduced for estimating patient prognosis 6,7 however, while such systems are valuable, they mostly rely on clinical parameters or cancer cell-related factors. 6 The recently emerging role of the cancer cell-immune cell interface in shaping tumorigenesis [2][3][4] and the appearance of anticancer immunotherapy 8,9 has increased the need to identify new integrated as well as broad sets of prognostic biomarkers based on the cancer cell-immune cell interface.…”