Contribution of Immunoscore and Molecular Features to Survival Prediction in Stage III Colon Cancer

Principles of risk assessment in colon cancer: immunity is key

In clinical practice, the administration of adjuvant chemotherapy (ACT) following tumor surgical resection raises a critical dilemma for stage II colon cancer (CC) patients. The prognostic features used to identify high-risk CC patients rely on the pathological assessment of tumor cells. Currently, these factors are considered for stratifying patients who may benefit from ACT at early CC stages. However, the extent to which these factors predict clinical outcomes (i.e. recurrence, survival) remains highly controversial, also uncertainty persists regarding patients' response to treatment, necessitating further investigation. Therefore, an imperious need is to explore novel biomarkers that can reliably stratify patients at risk, to optimize adjuvant treatment decisions. Recently, we evaluated the prognostic and predictive value of Immunoscore (IS), an immune digital-pathology assay, in stage II CC patients. IS emerged as the sole significant parameter for predicting disease-free survival (DFS) in high-risk patients. Moreover, IS effectively stratified patients who would benefit most from ACT based on their risk of recurrence, thus predicting their outcomes. Notably, our findings revealed that digital IS outperformed the visual quantitative assessment of the immune response conducted by expert pathologists. The latest edition of the WHO classification for digestive tumor has introduced the evaluation of the immune response, as assessed by IS, as desirable and essential diagnostic criterion. This supports the revision of current cancer guidelines and strongly recommends the implementation of IS into clinical practice as a patient stratification tool, to guide CC treatment decisions. This approach may provide appropriate personalized therapeutic decisions that could critically impact early-stage CC patient care.

Digital Pathology for Better Clinical Practice

(1) Background: Digital pathology (DP) is transforming the landscape of clinical practice, offering a revolutionary approach to traditional pathology analysis and diagnosis. (2) Methods: This innovative technology involves the digitization of traditional glass slides which enables pathologists to access, analyze, and share high-resolution whole-slide images (WSI) of tissue specimens in a digital format. By integrating cutting-edge imaging technology with advanced software, DP promises to enhance clinical practice in numerous ways. DP not only improves quality assurance and standardization but also allows remote collaboration among experts for a more accurate diagnosis. Artificial intelligence (AI) in pathology significantly improves cancer diagnosis, classification, and prognosis by automating various tasks. It also enhances the spatial analysis of tumor microenvironment (TME) and enables the discovery of new biomarkers, advancing their translation for therapeutic applications. (3) Results: The AI-driven immune assays, Immunoscore (IS) and Immunoscore-Immune Checkpoint (IS-IC), have emerged as powerful tools for improving cancer diagnosis, prognosis, and treatment selection by assessing the tumor immune contexture in cancer patients. Digital IS quantitative assessment performed on hematoxylin-eosin (H&E) and CD3+/CD8+ stained slides from colon cancer patients has proven to be more reproducible, concordant, and reliable than expert pathologists' evaluation of immune response. Outperforming traditional staging systems, IS demonstrated robust potential to enhance treatment efficiency in clinical practice, ultimately advancing cancer patient care. Certainly, addressing the challenges DP has encountered is essential to ensure its successful integration into clinical guidelines and its implementation into clinical use. (4) Conclusion: The ongoing progress in DP holds the potential to revolutionize pathology practices, emphasizing the need to incorporate powerful AI technologies, including IS, into clinical settings to enhance personalized cancer therapy.

Analysis of the factors influencing moderate to poor performance status in patients with cancer after chemotherapy: a cross-sectional study comparing three models

There are no models for assessing the factors that determine moderate to poor performance status in patients with cancer after chemotherapy. This study investigated the influencing factors and identified the best model for predicting moderate-poor performance status. A convenience sampling method was used. Demographic and clinical data and evaluation results for fatigue, pain, quality of life and Eastern Cooperative Oncology Group status were collected three days after the end of chemotherapy. Decision tree, random forest and logistic regression models were constructed. Ninety-four subjects in the case group had moderate to poor performance status, and 365 subjects in the control group had no or mild activity disorders. The random forest model was the most accurate model. Physical function, total protein, general quality of life within one week before chemotherapy, hemoglobin, pain symptoms and globulin were the main factors. Total protein and hemoglobin levels reflect nutritional status, and globulin levels are an index of liver function. Therefore, physical function, nutritional status, general quality of life and pain symptoms within one week before chemotherapy and liver function can be used to predict moderate-poor performance status. Nurses should pay more attention to patients with poor physical function, poor nutritional status, lower quality of life and pain symptoms after chemotherapy.

The Overlooked Role of Specimen Preparation in Bolstering Deep Learning-Enhanced Spatial Transcriptomics Workflows

The application of deep learning methods to spatial transcriptomics has shown promise in unraveling the complex relationships between gene expression patterns and tissue architecture as they pertain to various pathological conditions. Deep learning methods that can infer gene expression patterns directly from tissue histomorphology can expand the capability to discern spatial molecular markers within tissue slides. However, current methods utilizing these techniques are plagued by substantial variability in tissue preparation and characteristics, which can hinder the broader adoption of these tools. Furthermore, training deep learning models using spatial transcriptomics on small study cohorts remains a costly endeavor. Necessitating novel tissue preparation processes enhance assay reliability, resolution, and scalability. This study investigated the impact of an enhanced specimen processing workflow for facilitating a deep learning-based spatial transcriptomics assessment. The enhanced workflow leveraged the flexibility of the Visium CytAssist assay to permit automated H&E staining (e.g., Leica Bond) of tissue slides, whole-slide imaging at 40x-resolution, and multiplexing of tissue sections from multiple patients within individual capture areas for spatial transcriptomics profiling. Using a cohort of thirteen pT3 stage colorectal cancer (CRC) patients, we compared the efficacy of deep learning models trained on slide prepared using an enhanced workflow as compared to the traditional workflow which leverages manual tissue staining and standard imaging of tissue slides. Leveraging Inceptionv3 neural networks, we aimed to predict gene expression patterns across matched serial tissue sections, each stemming from a distinct workflow but aligned based on persistent histological structures. Findings indicate that the enhanced workflow considerably outperformed the traditional spatial transcriptomics workflow. Gene expression profiles predicted from enhanced tissue slides also yielded expression patterns more topologically consistent with the ground truth. This led to enhanced statistical precision in pinpointing biomarkers associated with distinct spatial structures. These insights can potentially elevate diagnostic and prognostic biomarker detection by broadening the range of spatial molecular markers linked to metastasis and recurrence. Future endeavors will further explore these findings to enrich our comprehension of various diseases and uncover molecular pathways with greater nuance. Combining deep learning with spatial transcriptomics provides a compelling avenue to enrich our understanding of tumor biology and improve clinical outcomes. For results of the highest fidelity, however, effective specimen processing is crucial, and fostering collaboration between histotechnicians, pathologists, and genomics specialists is essential to herald this new era in spatial transcriptomics-driven cancer research.

Multi-Institutional Evaluation of Pathologists' Assessment Compared to Immunoscore

BACKGROUND

The Immunoscore (IS) is a quantitative digital pathology assay that evaluates the immune response in cancer patients. This study reports on the reproducibility of pathologists' visual assessment of CD3+- and CD8+-stained colon tumors, compared to IS quantification.

METHODS

An international group of expert pathologists evaluated 540 images from 270 randomly selected colon cancer (CC) cases. Concordance between pathologists' T-score, corresponding hematoxylin-eosin (H&E) slides, and the digital IS was evaluated for two- and three-category IS.

RESULTS

Non-concordant T-scores were reported in more than 92% of cases. Disagreement between semi-quantitative visual assessment of T-score and the reference IS was observed in 91% and 96% of cases before and after training, respectively. Statistical analyses showed that the concordance index between pathologists and the digital IS was weak in two- and three-category IS, respectively. After training, 42% of cases had a change in T-score, but no improvement was observed with a Kappa of 0.465 and 0.374. For the 20% of patients around the cut points, no concordance was observed between pathologists and digital pathology analysis in both two- and three-category IS, before or after training (all Kappa < 0.12).

CONCLUSIONS

The standardized IS assay outperformed expert pathologists' T-score evaluation in the clinical setting. This study demonstrates that digital pathology, in particular digital IS, represents a novel generation of immune pathology tools for reproducible and quantitative assessment of tumor-infiltrated immune cell subtypes.

Identification of Spatial Proteomic Signatures of Colon Tumor Metastasis: A Digital Spatial Profiling Approach

Over 150,000 Americans are diagnosed with colorectal cancer (CRC) every year, and annually >50,000 individuals are estimated to die of CRC, necessitating improvements in screening, prognostication, disease management, and therapeutic options. CRC tumors are removed en bloc with surrounding vasculature and lymphatics. Examination of regional lymph nodes at the time of surgical resection is essential for prognostication. Developing alternative approaches to indirectly assess recurrence risk would have utility in cases where lymph node yield is incomplete or inadequate. Spatially dependent, immune cell-specific (eg, tumor-infiltrating lymphocytes), proteomic, and transcriptomic expression patterns inside and around the tumor-the tumor immune microenvironment-can predict nodal/distant metastasis and probe the coordinated immune response from the primary tumor site. The comprehensive characterization of tumor-infiltrating lymphocytes and other immune infiltrates is possible using highly multiplexed spatial omics technologies, such as the GeoMX Digital Spatial Profiler. In this study, machine learning and differential co-expression analyses helped identify biomarkers from Digital Spatial Profiler-assayed protein expression patterns inside, at the invasive margin, and away from the tumor, associated with extracellular matrix remodeling (eg, granzyme B and fibronectin), immune suppression (eg, forkhead box P3), exhaustion and cytotoxicity (eg, CD8), Programmed death ligand 1-expressing dendritic cells, and neutrophil proliferation, among other concomitant alterations. Further investigation of these biomarkers may reveal independent risk factors of CRC metastasis that can be formulated into low-cost, widely available assays.

Inferring spatial transcriptomics markers from whole slide images to characterize metastasis-related spatial heterogeneity of colorectal tumors: A pilot study

Over 150 000 Americans are diagnosed with colorectal cancer (CRC) every year, and annually over 50 000 individuals will die from CRC, necessitating improvements in screening, prognostication, disease management, and therapeutic options. Tumor metastasis is the primary factor related to the risk of recurrence and mortality. Yet, screening for nodal and distant metastasis is costly, and invasive and incomplete resection may hamper adequate assessment. Signatures of the tumor-immune microenvironment (TIME) at the primary site can provide valuable insights into the aggressiveness of the tumor and the effectiveness of various treatment options. Spatially resolved transcriptomics technologies offer an unprecedented characterization of TIME through high multiplexing, yet their scope is constrained by cost. Meanwhile, it has long been suspected that histological, cytological, and macroarchitectural tissue characteristics correlate well with molecular information (e.g., gene expression). Thus, a method for predicting transcriptomics data through inference of RNA patterns from whole slide images (WSI) is a key step in studying metastasis at scale. In this work, we collected tissue from 4 stage-III (pT3) matched colorectal cancer patients for spatial transcriptomics profiling. The Visium spatial transcriptomics (ST) assay was used to measure transcript abundance for 17 943 genes at up to 5000 55-micron (i.e., 1-10 cells) spots per patient sampled in a honeycomb pattern, co-registered with hematoxylin and eosin (H&E) stained WSI. The Visium ST assay can measure expression at these spots through tissue permeabilization of mRNAs, which are captured through spatially (i.e., x-y positional coordinates) barcoded, gene specific oligo probes. WSI subimages were extracted around each co-registered Visium spot and were used to predict the expression at these spots using machine learning models. We prototyped and compared several convolutional, transformer, and graph convolutional neural networks to predict spatial RNA patterns at the Visium spots under the hypothesis that the transformer- and graph-based approaches better capture relevant spatial tissue architecture. We further analyzed the model's ability to recapitulate spatial autocorrelation statistics using SPARK and SpatialDE. Overall, the results indicate that the transformer- and graph-based approaches were unable to outperform the convolutional neural network architecture, though they exhibited optimal performance for relevant disease-associated genes. Initial findings suggest that different neural networks that operate on different scales are relevant for capturing distinct disease pathways (e.g., epithelial to mesenchymal transition). We add further evidence that deep learning models can accurately predict gene expression in whole slide images and comment on understudied factors which may increase its external applicability (e.g., tissue context). Our preliminary work will motivate further investigation of inference for molecular patterns from whole slide images as metastasis predictors and in other applications.

The current understanding of the immune landscape relative to radiotherapy across tumor types

Radiotherapy is part of the standard of care treatment for a great majority of cancer patients. As a result of radiation, both tumor cells and the environment around them are affected directly by radiation, which mainly primes but also might limit the immune response. Multiple immune factors play a role in cancer progression and response to radiotherapy, including the immune tumor microenvironment and systemic immunity referred to as the immune landscape. A heterogeneous tumor microenvironment and the varying patient characteristics complicate the dynamic relationship between radiotherapy and this immune landscape. In this review, we will present the current overview of the immunological landscape in relation to radiotherapy in order to provide insight and encourage research to further improve cancer treatment. An investigation into the impact of radiation therapy on the immune landscape showed in several cancers a common pattern of immunological responses after radiation. Radiation leads to an upsurge in infiltrating T lymphocytes and the expression of programmed death ligand 1 (PD-L1) which can hint at a benefit for the patient when combined with immunotherapy. In spite of this, lymphopenia in the tumor microenvironment of 'cold' tumors or caused by radiation is considered to be an important obstacle to the patient's survival. In several cancers, a rise in the immunosuppressive populations is seen after radiation, mainly pro-tumoral M2 macrophages and myeloid-derived suppressor cells (MDSCs). As a final point, we will highlight how the radiation parameters themselves can influence the immune system and, therefore, be exploited to the advantage of the patient.

CD8 + T-cell Density Is an Independent Predictor of Survival and Response to Adjuvant Chemotherapy in Stage III Colon Cancer

We assessed CD8 + T-cell density in 351 resected stage II to III colon cancers from 2011 to 2015 and correlated the findings with disease-free survival and survival effect of adjuvant chemotherapy. Most tumors (70%) had high/intermediate CD8 + T-cell density, and this was significantly associated with mismatch repair deficiency compared with tumors with low CD8 + T-cell density (28% vs. 13%, P =0.003). Fewer tumors with high/intermediate CD8 + T-cell density had adverse histologic features compared with tumors with low CD8 + T-cell density including high tumor budding (16% vs. 27%) and venous (22% vs. 35%), lymphatic (54% vs. 65%), and perineural (23% vs. 33%) invasion (all with P <0.05). In the stage III cohort, high/intermediate CD8 + T-cell density was an independent predictor of disease-free survival on multivariate analysis (hazard ratio: 0.39, 0.21 to 0.71 95% CI, P =0.002). For stage III patients with high/intermediate CD8 + T-cell density, adjuvant chemotherapy was significantly associated with improved disease-free survival (hazard ratio: 0.28, 0.11 to 0.74 95% CI, P =0.01) whereas stage III patients with low CD8 + T-cell density did not have improved survival with adjuvant chemotherapy. In conclusion, in stage III colon cancer, CD8 + T-cell density is an independent prognostic biomarker for disease-free survival and may help to identify patients who benefit from adjuvant chemotherapy.

Multicenter International Study of the Consensus Immunoscore for the Prediction of Relapse and Survival in Early-Stage Colon Cancer

Background: The prognostic value of Immunoscore was evaluated in Stage II/III colon cancer (CC) patients, but it remains unclear in Stage I/II, and in early-stage subgroups at risk. An international Society for Immunotherapy of Cancer (SITC) study evaluated the pre-defined consensus Immunoscore in tumors from 1885 AJCC/UICC-TNM Stage I/II CC patients from Canada/USA (Cohort 1) and Europe/Asia (Cohort 2). METHODS: Digital-pathology is used to quantify the densities of CD3+ and CD8+ T-lymphocyte in the center of tumor (CT) and the invasive margin (IM). The time to recurrence (TTR) was the primary endpoint. Secondary endpoints were disease-free survival (DFS), overall survival (OS), prognosis in Stage I, Stage II, Stage II-high-risk, and microsatellite-stable (MSS) patients. RESULTS: High-Immunoscore presented with the lowest risk of recurrence in both cohorts. In Stage I/II, recurrence-free rates at 5 years were 78.4% (95%-CI, 74.4−82.6), 88.1% (95%-CI, 85.7−90.4), 93.4% (95%-CI, 91.1−95.8) in low, intermediate and high Immunoscore, respectively (HR (Hi vs. Lo) = 0.27 (95%-CI, 0.18−0.41); p < 0.0001). In Cox multivariable analysis, the association of Immunoscore to outcome was independent (TTR: HR (Hi vs. Lo) = 0.29, (95%-CI, 0.17−0.50); p < 0.0001) of the patient’s gender, T-stage, sidedness, and microsatellite instability-status (MSI). A significant association of Immunoscore with survival was found for Stage II, high-risk Stage II, T4N0 and MSS patients. The Immunoscore also showed significant association with TTR in Stage-I (HR (Hi vs. Lo) = 0.07 (95%-CI, 0.01−0.61); P = 0.016). The Immunoscore had the strongest (69.5%) contribution χ2 for influencing survival. Patients with a high Immunoscore had prolonged TTR in T4N0 tumors even for patients not receiving chemotherapy, and the Immunoscore remained the only significant parameter in multivariable analysis. CONCLUSION: In early CC, low Immunoscore reliably identifies patients at risk of relapse for whom a more intensive surveillance program or adjuvant treatment should be considered.

Validation of the prognostic value of CD3 and CD8 cell densities analogous to the Immunoscore® by stage and location of colorectal cancer: an independent patient cohort study

In addition to the traditional staging system in colorectal cancer (CRC), the Immunoscore® has been proposed to characterize the level of immune infiltration in tumor tissue and as a potential prognostic marker. The aim of this study was to examine and validate associations of an immune cell score analogous to the Immunoscore® with established molecular tumor markers and with CRC patient survival in a routine setting. Patients from a population-based cohort study with available CRC tumor tissue blocks were included in this analysis. CD3+ and CD8+ tumor infiltrating lymphocytes in the tumor center and invasive margin were determined in stained tumor tissue slides. Based on the T-cell density in each region, an  immune cell score closely analogous to the concept of the Immunoscore® was calculated and tumors categorized into IS-low, IS-intermediate, or IS-high. Logistic regression models were used to assess associations between clinicopathological characteristics with the immune cell score, and Cox proportional hazards models to analyze associations with cancer-specific, relapse-free, and overall survival. From 1,535 patients with CRC, 411 (27%) had IS-high tumors. Microsatellite instability (MSI-high) was strongly associated with higher immune cell score levels (p < 0.001). Stage I-III patients with IS-high had better CRC-specific and relapse-free survival compared to patients with IS-low (hazard ratio [HR] = 0.42 [0.27-0.66] and HR = 0.45 [0.31-0.67], respectively). Patients with microsatellite stable (MSS) tumors and IS-high had better survival (HR_CSS  = 0.60 [0.42-0.88]) compared to MSS/IS-low patients. In this population-based cohort of CRC patients, the immune cell score was significantly associated with better patient survival. It was a similarly strong prognostic marker in patients with MSI-high tumors and in the larger group of patients with MSS tumors. Additionally, this study showed that it is possible to implement an analogous immune cell score approach and validate the Immunoscore® using open source software in an academic setting. Thus, the Immunoscore® could be useful to improve the traditional staging system in colon and rectal cancer used in clinical practice.

Association of tumor-infiltrating lymphocytes with survival depends on primary tumor sidedness in stage III colon cancers (NCCTG N0147) [Alliance]

BACKGROUND

Tumor-infiltrating lymphocytes (TILs) are a robust and independent prognostic variable in localized colon cancer. Given reported differences in molecular features and prognosis of right- versus left-sided tumors, we examined the association of TIL densities with patient survival by primary tumor sidedness in stage III cancers, including clinical low- (T1-3, N1) and high-risk (T4 and/or N2) groups.

PATIENTS AND METHODS

In a phase III trial of FOLFOX-based adjuvant chemotherapy, TIL densities were analyzed and dichotomized in colon carcinomas (N = 1532) based on a previously determined cut point optimized for disease-free survival (DFS). Right-sided tumors were defined as proximal to the splenic flexure. Associations of TILs and sidedness with 5-year DFS were examined using Kaplan-Meier methodology along with multivariable modeling and relative contribution analysis by Cox regression.

RESULTS

Lower TIL densities were found in left- versus right-sided tumors (P < 0.0001). The association of TIL densities with DFS differed significantly by tumor sidedness (Pinteraction = 0.045). Overall, patient tumors with low (versus high) TILs had significantly poorer DFS in right-sided (hazard ratio 2.02, 95% confidence interval 1.45-2.82; Padj < 0.0001), but not left-sided tumors (Padj = 0.1731). Among clinical low-risk patients, low (versus high) TILs were adversely prognostic only in right-sided tumors (Padj = 0.0058). Among high-risk patients, low TILs were prognostic independent of sidedness (Padj < 0.025). The relative contribution of TILs to DFS was substantially greater in right- versus left-sided tumors (24% versus 1.5%). In high-risk tumors, TILs had the highest relative contribution to DFS (42%) of all variables. In low-risk tumors, the contribution of TILs (16%) to DFS was second to KRAS.

CONCLUSIONS

The association of TIL densities with patient survival differed by primary tumor sidedness and clinical risk group, suggesting that TILs should be interpreted in this context among stage III colon cancers.

CLINICALTRIALS

GOV IDENTIFIER

NCT00079274; https://clinicaltrials.gov/ct2/show/NCT00079274.

Clinical Performance of the Consensus Immunoscore in Colon Cancer in the Asian Population from the Multicenter International SITC Study

BACKGROUND: In this study, we evaluated the prognostic value of Immunoscore in patients with stage I−III colon cancer (CC) in the Asian population. These patients were originally included in an international study led by the Society for Immunotherapy of Cancer (SITC) on 2681 patients with AJCC/UICC-TNM stages I−III CC. METHODS: CD3+ and cytotoxic CD8+ T-lymphocyte densities were quantified in the tumor and invasive margin by digital pathology. The association of Immunoscore with prognosis was evaluated for time to recurrence (TTR), disease-free survival (DFS), and overall survival (OS). RESULTS: Immunoscore stratified Asian patients (n = 423) into different risk categories and was not impacted by age. Recurrence-free rates at 3 years were 78.5%, 85.2%, and 98.3% for a Low, Intermediate, and High Immunoscore, respectively (HR[Low-vs-High] = 7.26 (95% CI 1.75−30.19); p = 0.0064). A High Immunoscore showed a significant association with prolonged TTR, OS, and DFS (p < 0.05). In Cox multivariable analysis stratified by center, Immunoscore association with TTR was independent (HR[Low-vs-Int+High] = 2.22 (95% CI 1.10−4.55) p = 0.0269) of the patient’s gender, T-stage, N-stage, sidedness, and MSI status. A significant association of a High Immunoscore with prolonged TTR was also found among MSS (HR[Low-vs-Int+High] = 4.58 (95% CI 2.27−9.23); p ≤ 0.0001), stage II (HR[Low-vs-Int+High] = 2.72 (95% CI 1.35−5.51); p = 0.0052), low-risk stage-II (HR[Low-vs-Int+High] = 2.62 (95% CI 1.21−5.68); p = 0.0146), and high-risk stage II patients (HR[Low-vs-Int+High] = 3.11 (95% CI 1.39−6.91); p = 0.0055). CONCLUSION: A High Immunoscore is significantly associated with the prolonged survival of CC patients within the Asian population.

Immunoscore Is Prognostic in Low-Risk and High-Risk Stage III Colon Carcinomas Treated With Adjuvant Infusional Fluorouracil, Leucovorin, and Oxaliplatin in a Phase III Trial

PURPOSE

The recommended duration of adjuvant fluoropyrimidine and oxaliplatin chemotherapy for patients with stage III colon cancer is based on tumor classification into clinically low-risk (T1-3 N1) and high-risk (T4 or N2) groups. We determined whether Immunoscore can enhance prognostication within these risk groups.

MATERIALS AND METHODS

Patients with stage III colon carcinomas (N = 600) were randomly selected from the infusional fluorouracil, leucovorin, and oxaliplatin arm of adjuvant trial NCCTG N0147 (Alliance for Clinical Trials in Oncology). Tumors were evaluated for Immunoscore that quantifies CD3+ and CD8+ T-cell densities in the tumor center and invasive margin by digital image analysis. Disease-free survival (DFS) by Immunoscore was analyzed using a multivariable Cox regression model in each risk group with adjustment for covariates including KRAS, BRAFV600E, and mismatch repair status.

RESULTS

Of 559 cancers with Immunoscore data, 299 (53.5%) were classified as clinically low-risk (T1-3 N1) and 260 (46.5%) as clinically high-risk (T4 and/or N2). Among patients with low-risk tumors, those with Immunoscore-Low versus Immunoscore-High tumors had significantly worse 5-year DFS rates (77.5% v 91.8%; hazard ratio, 1.70; 95% CI, 1.03 to 2.79; P = .037). Among patients with high-risk tumors, those with Immunoscore-Low versus Immunoscore-High tumors also had significantly worse DFS (55.3% v 70.3%; hazard ratio, 1.65; 95% CI, 1.11 to 2.47; P = .013). Tumors that were low-risk/Immunoscore-Low had similar outcomes as did tumors that were high-risk/Immunoscore-High (P = .174). Prognostication was significantly improved in multivariable models where Immunoscore was added to clinical risk parameters and limited biomarkers (likelihood ratio test P = .0003).

CONCLUSION

Immunoscore can refine patient prognosis beyond clinical risk group classification, suggesting its potential utility for adjuvant decision making.

Immune Response in Colorectal Carcinoma: A Review of Its Significance as a Predictive and Prognostic Biomarker

Colorectal carcinoma is a leading cause of cancer-related death worldwide. There is significant prognostic heterogeneity in stage II and III tumours, necessitating the development of new biomarkers to better identify patients at risk of disease progression. Recently, the tumour immune environment, particularly the type and quantity of T lymphocytes, has been shown to be a useful biomarker in predicting prognosis for patients with colorectal carcinoma. In this review, the significance of the immune response in colorectal carcinoma, including its influence on prognosis and response to therapy, will be detailed.

Updates in the Treatment of Patients With Colorectal Cancer

A number of assays are now available to estimate the prognosis of early-stage colorectal cancer, including multigene assays, the Immunoscore, and circulating tumor DNA (ctDNA). Although the results of these assays may provide prognostic information regarding the risk for recurrence, their use as a predictive assay has not yet been validated. Therefore, although these assays may be useful for prognostication, further validation would be required to include in the NCCN Guidelines. For the treatment of metastatic colorectal cancer, major advances have included the use of checkpoint inhibition in metastatic disease. Studies are currently underway to further define their optimal use.

Biomarkers of Response and Resistance to Immunotherapy in Microsatellite Stable Colorectal Cancer: Toward a New Personalized Medicine

Immune Checkpoint Inhibitors (ICIs) are well recognized as a major immune treatment modality for multiple types of solid cancers. However, for colorectal cancer (CRC), ICIs are only approved for the treatment of Mismatch-Repair-Deficient and Microsatellite Instability-High (dMMR/MSI-H) tumors. For the vast majority of CRC, that are not dMMR/MSI-H, ICIs alone provide limited to no clinical benefit. This discrepancy of response between CRC and other solid cancers suggests that CRC may be inherently resistant to ICIs alone. In translational research, efforts are underway to thoroughly characterize the immune microenvironment of CRC to better understand the mechanisms behind this resistance and to find new biomarkers of response. In the clinic, trials are being set up to study biomarkers along with treatments targeting newly discovered immune checkpoint molecules or treatments combining ICIs with other existing therapies to improve response in MSS CRC. In this review, we will focus on the characteristics of response and resistance to ICIs in CRC, and discuss promising biomarkers studied in recent clinical trials combining ICIs with other therapies.

Comparison of Immune Response Assessment in Colon Cancer by Immunoscore (Automated Digital Pathology) and Pathologist Visual Scoring

Simple Summary

The immune response to colon cancer (CC) is highly variable among patients and is clinically relevant. In this study, we compared the immune response assessment for early-stage CC, as measured by Immunoscore (IS), to pathologist visual scoring of the CD3+ and CD8+ T-cell densities at the tumor site (T-score). The objectives were to determine the inter-observer agreement between pathologists and the concordance between the two methods. Agreement between pathologists was minimal to weak. Moreover, a weak concordance between the two methods was observed, leading to misclassification of 48% of cases by pathologist scoring. Due to the high level of immune infiltrate heterogeneity resulting in disagreement of interpretation among pathologists, IS is unlikely to be reproduced via non-standardized methods.

Abstract

Adjunction of immune response into the TNM classification system improves the prediction of colon cancer (CC) prognosis. However, immune response measurements have not been used as robust biomarkers of pathology in clinical practice until the introduction of Immunoscore (IS), a standardized assay based on automated artificial intelligence assisted digital pathology. The strong prognostic impact of the immune response, as assessed by IS, has been widely validated and IS can help to refine treatment decision making in early CC. In this study, we compared pathologist visual scoring to IS. Four pathologists evaluated tumor specimens from 50 early-stage CC patients and classified the CD3+ and CD8+ T-cell densities at the tumor site (T-score) into 2 (High/Low) categories. Individual and overall pathologist scoring of immune response (before and after training for immune response assessment) were compared to the reference IS (High/Low). Pathologists’ disagreement with the reference IS was observed in almost half of the cases (48%) and training only slightly improved the accuracy of pathologists’ classification. Agreement among pathologists was minimal with a Kappa of 0.34 and 0.57 before and after training, respectively. The standardized IS assay outperformed expert pathologist assessment in the clinical setting.

Classification of early-stage colon cancer with Immunoscore®: clinical evidence and case studies

Immunoscore^® is a digital pathology diagnostic immunoassay used to complement tumor node metastasis staging for the prediction of recurrence risk in patients with early-stage colon cancer. In combination with standard clinicopathological features, Immunoscore informs adjuvant chemotherapy decision-making for patients with early-stage colon cancer. Immunoscore has been validated in patients with stage II/III colon cancer and demonstrated to be a stronger prognostic factor for survival than tumor node metastasis staging alone. Immunoscore improves the prognostic definition of patients with colon cancer, the identification of those patients at high risk of tumor recurrence, and the ability to predict which patients will derive most benefit from the use of adjuvant chemotherapy. Immunoscore has robust analytical performance characteristics which include good interlaboratory reproducibility and overall assay precision.

Clinicopathological Features Combined With Immune Infiltration Could Well Distinguish Outcomes in Stage II and Stage III Colorectal Cancer: A Retrospective Study

Background

The Immunoscore predicts prognosis in patients with colorectal cancer (CRC). However, a few studies have incorporated the Immunoscore into the construction of comprehensive prognostic models in CRC, especially stage II CRC. We aimed to construct and validate multidimensional models integrating clinicopathological characteristics and the Immunoscore to predict the prognosis of patients with stage II–III CRC.

Methods

Patients (n = 254) diagnosed with stage II–III CRC from 2009 to 2016 were used to generate Cox models for predicting disease-free survival (DFS) and overall survival (OS). The variables included basic clinical indicators, blood inflammatory markers, preoperative tumor biomarkers, mismatch repair status, and the Immunoscore (CD3⁺ and CD8⁺ T-cell densities). Univariate and multivariate Cox proportional regressions were used to construct the prognostic models for DFS and OS. We validated the predictive accuracy and ability of the prognostic models in our cohort of 254 patients.

Results

We constructed two predictive prognostic models with C-index values of 0.6941 for DFS and 0.7138 for OS in patients with stage II–III CRC. The Immunoscore was the most informative predictor of DFS (11.92%), followed by pN stage, carcinoembryonic antigen (CEA), and vascular infiltration. For OS, the Immunoscore was the most informative predictor (8.59%), followed by pN stage, age, CA125, and CEA. Based on the prognostic models, nomograms were developed to predict the 3- and 5-year DFS and OS rates. Patients were divided into three risk groups (low, intermediate, and high) according to the risk scores obtained from the nomogram, and significant differences were observed in the recurrence and survival of the different risk groups (p < 0.0001). Calibration curve and time-dependent receiver operating characteristic (ROC) analysis showed good accuracy of our models. Furthermore, the decision curve analysis indicated that our nomograms had better net benefit than pathological TNM (pTNM) stage within a wide threshold probability. Especially, we developed a website based on our prognostic models to predict the risks of recurrence and death of patients with stage II–III CRC.

Conclusions

Multidimensional models including the clinicopathological characteristics and the Immunoscore were constructed and validated, with good accuracy and convenience, to evaluate the risks of recurrence and death of stage II–III CRC patients.

Pan-Asian adapted ESMO Clinical Practice Guidelines for the diagnosis treatment and follow-up of patients with localised colon cancer

The most recent version of the European Society for Medical Oncology (ESMO) Clinical Practice Guidelines for the diagnosis, treatment and follow-up of localised colon cancer was published in 2020. It was decided by both the ESMO and the Japanese Society of Medical Oncology (JSMO) to convene a special virtual guidelines meeting in March 2021 to adapt the ESMO 2020 guidelines to take into account the ethnic differences associated with the treatment of localised colon cancer in Asian patients. These guidelines represent the consensus opinions reached by experts in the treatment of patients with localised colon cancer representing the oncological societies of Japan (JSMO), China (CSCO), India (ISMPO), Korea (KSMO), Malaysia (MOS), Singapore (SSO) and Taiwan (TOS). The voting was based on scientific evidence and was independent of the current treatment practices and drug availability and reimbursement situations in the different Asian countries.

Impact of Immunoscore on the Management of Stage II Colon Cancer Patients: A Physician Survey

Simple Summary

Selection of appropriate stage II colon cancer patients for adjuvant chemotherapy (AC) is controversial. A novel immune response classifier has previously been validated to refine patient selection, but its impact on oncologist treatment planning had yet to be described. In this survey, all but one oncologist altered clinical practice recommendations, and recommendations for AC prescriptions were reduced by half (among the Immunoscore-high cases (low recurrence risk)). This study revealed that the Immunoscore results could significantly decrease AC use in patients with stage II colon cancer who may not benefit from it, thereby reducing the administration of nonvalue care.

Abstract

Background: Adjuvant chemotherapy use in stage II colon cancer is controversial. Current prognostic risk factors do not take the tumor immune microenvironment into account. Consideration of the Immunoscore, which measures the host immune response at the tumor site, may assist clinicians in reducing adjuvant chemotherapy use in patients who are unlikely to benefit from it. This study sought to determine the potential clinical utility of the Immunoscore, via its effect on medical oncologists’ recommendations for management of patients with stage II colon cancer. Methods: De-identified vignettes of 10 patients with stage II colon cancer were presented to 25 practicing medical oncologists. Each participant completed surveys indicating recommendations for adjuvant chemotherapy and surveillance strategies. An educational session was subsequently conducted, and the same patient profiles were re-presented but included immunoscore results. Participants were again asked to provide their recommendations. A participant was counted as influenced if their responses were altered after immunoscore test results were provided. Results: All but one participant (96%) altered a management recommendation for ≥1 case. For individual cases, a mean of 55% (range, 40–80%) of participants altered their recommendations for adjuvant chemotherapy and/or surveillance. For the immunoscore-high cases (low-risk of recurrence), recommendations for adjuvant chemotherapy use decreased from 60% to 31%. Conclusions: These results indicate a willingness by oncologists to integrate immunoscore information into clinical practice recommendations. Incorporation of immunoscore data resulted in the reduction of nonvalue care in the simulated population. Confirmation in prospective studies is planned.

Association of Adiponectin and Vitamin D With Tumor Infiltrating Lymphocytes and Survival in Stage III Colon Cancer

Background

Adipocyte-derived adiponectin may play a role in the host inflammatory response to cancer. We examined the association of plasma adiponectin with the density of tumor-infiltrating lymphocytes (TILs) in colon cancers and with vitamin D, clinicopathological features, and patient survival.

Methods

Plasma adiponectin and 25-hydroxyvitamin D [25(OH)D] were analyzed by radioimmunoassay in 600 patients with stage III colon cancer who received FOLFOX-based adjuvant chemotherapy (NCCTG N0147 [Alliance]). TIL densities were determined in histopathological sections. Associations with disease-free survival (DFS), time to recurrence, and overall survival were evaluated by multivariable Cox regression adjusting for potential confounders (ie, body mass index, race, TILs, and N stage). All statistical tests were 2-sided.

Results

We found a statistically significant reduction in adiponectin, but not 25(OH)D, levels in tumors with high vs low TIL densities (median = 6845 vs 8984 ng/mL; P = .04). A statistically significant reduction in adiponectin was also observed in obese (body mass index >30 kg/m²) vs nonobese patients (median = 6608 vs 12 351 ng/mL; P < .001), in men vs women (median = 8185 vs 11 567 ng/mL; P < .001), in Blacks vs Whites or Asians (median = 6412 vs 8847 vs 7858 ng/mL; P < .03), and in those with fewer lymph node metastases (N1 vs N2: median = 7768 vs 9253 ng/mL; P = .01). Insufficiency of 25(OH)D (<30 ng/mL) was detected in 291 (48.5%) patients. In multivariable analyses, neither adiponectin nor 25(OH)D were associated with a statistically significant difference in DFS, overall survival , or time to recurrence in models adjusted for potential confounders. We found a statistically significant association of TILs with prognosis, yet no such interaction was observed for the association of adiponectin with TILs for DFS.

Conclusions

Lower circulating adiponectin levels were associated with a statistically significant increase in TIL densities in colon cancers, indicating an enhanced antitumor immune response. In contrast to TILs, neither adiponectin nor 25(OH)D was independently prognostic.

Tumor microenvironment-adjusted prognostic implications of the KRAS mutation subtype in patients with stage III colorectal cancer treated with adjuvant FOLFOX

Several studies have reported that the prognostic effect of KRAS mutations on colorectal cancers (CRCs) varies depending on the type of mutation. Considering the effect of KRAS mutations on tumor microenvironment, we analyzed the prognostic significance of KRAS mutation types after adjusting for the tumor-infiltrating lymphocytes (TIL) and tumor-stromal percentage (TSP) statuses. In two independent cohorts, KRAS mutations were analyzed by Sanger sequencing and/or next-generation sequencing. TIL density and the TSP were quantified from whole-slide immunohistochemical images. KRAS-mutant CRCs were divided into three subgroups (G12D/V, other codon 12 mutations and codon 13 mutations) to examine their differential effect on TIL density, the TSP and recurrence-free survival (RFS). Among the KRAS mutations, only the G12D/V subgroups showed significantly less TIL infiltration than the wild-type CRCs. According to survival analysis, G12D/V mutations were associated with short RFS; codon 13 mutations showed discordant trends in the two cohorts, and other codon 12 mutations showed no significant association. Multivariate analysis further supported the prognostic value of G12D/V mutations. This result is not only consistent with a recent study suggesting the immunosuppressive effect of mutant KRAS but also provides insight into the type-specific prognostic effect of KRAS mutations.

Tumour immune microenvironment biomarkers predicting cytotoxic chemotherapy efficacy in colorectal cancer

The role of the local tumour and stromal immune landscape is increasingly recognised to be important in cancer development, progression and response to therapy. The composition, function, spatial orientation and gene expression profile of the infiltrate of the innate and adaptive immune system at the tumour and surrounding tissue has an established prognostic role in colorectal cancer (CRC). Multiple studies have confirmed that a tumour immune microenvironment (TIME) reflective of a type 1 adaptive immune response is associated with improved prognosis. There have been significant efforts to evolve these observations into validated, histopathology-based prognostic biomarkers, such as the Immunoscore. However, the clinical need lies much more in the development of predictive, not prognostic, biomarkers which have the potential to improve patient outcomes. This is particularly pertinent to help guide cytotoxic chemotherapy use in CRC, which remains the standard of care. Cytotoxic chemotherapy has recognised immunomodulatory activity distinct from its antimitotic effects, including mechanisms such as immunogenic cell death (ICD) and induction/inhibition of key immune players. Response to chemotherapy may differ with regard to molecular subtype of CRC, which are strongly associated with immune phenotypes. Thus, immune markers are potentially useful, though under-reported, predictive biomarkers. In this review, we discuss the impact of the TIME on response to cytotoxic chemotherapy in CRC, with a focus on baseline immune markers, and associated genomic and transcriptomic signatures.

Immune Checkpoint Inhibitors in Triple Negative Breast Cancer Treatment: Promising Future Prospects

Immunotherapy has emerged as the fifth pillar of cancer treatment alongside surgery, radiotherapy, chemotherapy, and targeted therapy. Immune checkpoint inhibitors are the current superheroes of immunotherapy, unleashing a patient's own immune cells to kill tumors and revolutionizing cancer treatment in a variety of cancers. Although breast cancer was historically believed to be immunologically silent, treatment with immune checkpoint inhibitors has been shown to induce modest responses in metastatic breast cancer. Given the inherent heterogeneity of breast tumors, this raised the question whether certain breast tumors might benefit more from immune-based interventions and which cancer cell-intrinsic and/or microenvironmental factors define the likelihood of inducing a potent and durable anti-tumor immune response. In this review, we will focus on triple negative breast cancer as immunogenic breast cancer subtype, and specifically discuss the relevance of tumor mutational burden, the plethora and diversity of tumor infiltrating immune cells in addition to the immunoscore, the presence of immune checkpoint expression, and the microbiome in defining immune checkpoint blockade response. We will highlight the current immune checkpoint inhibitor treatment options, either as monotherapy or in combination with standard-of-care treatment modalities such as chemotherapy and targeted therapy. In addition, we will look into the potential of immunotherapy-based combination strategies using immune checkpoint inhibitors to enhance both innate and adaptive immune responses, or to establish a more immune favorable environment for cancer vaccines. Finally, the review will address the need for unambiguous predictive biomarkers as one of the main challenges of immune checkpoint blockade. To conclude, the potential of immune checkpoint blockade for triple negative breast cancer treatment could be enhanced by exploration of aforementioned factors and treatment strategies thereby providing promising future prospects.

Gutting it Out: Developing Effective Immunotherapies for Patients With Colorectal Cancer

Risk factors for colorectal cancer (CRC) include proinflammatory diets, sedentary habits, and obesity, in addition to genetic syndromes that predispose individuals to this disease. Current treatment relies on surgical excision and cytotoxic chemotherapies. There has been a renewed interest in immunotherapy as a treatment option for CRC given the success in melanoma and microsatellite instable (MSI) CRC. Immunotherapy with checkpoint inhibitors only plays a role in the 4%-6% of patients with MSIhigh tumors and even within this subpopulation, response rates can vary from 30% to 50%. Most patients with CRC do not respond to this modality of treatment, even though colorectal tumors are frequently infiltrated with T cells. Tumor cells limit apoptosis and survive following intensive chemotherapy leading to drug resistance and induction of autophagy. Pharmacological or molecular inhibition of autophagy improves the efficacy of cytotoxic chemotherapy in murine models. The microbiome clearly plays an etiologic role, in some or most colon tumors, realized by elegant findings in murine models and now investigated in human clinical trials. Recent results have suggested that cancer vaccines may be beneficial, perhaps best as preventive strategies. The search for therapies that can be combined with current approaches to increase their efficacy, and new knowledge of the biology of CRC are pivotal to improve the care of patients suffering from this disease. Here, we review the basic immunobiology of CRC, current "state-of-the-art" immunotherapies and define those areas with greatest therapeutic promise for the future.

The Immunoscore in Localized Urothelial Carcinoma Treated with Neoadjuvant Chemotherapy: Clinical Significance for Pathologic Responses and Overall Survival

Simple Summary

The prognosis of localized muscle-invasive bladder cancer is poor and the prognostic and predictive biomarkers of the response to treatment are lacking. We retrospectively investigated the role of the Immunoscore in the neoadjuvant setting, where the Immunoscore is a standardized quantitative assay of lymphocytes in the tumor microenvironment. We found it allowed for the stratification of patient prognoses and the prediction of response to neoadjuvant chemotherapy.

Abstract

(1) Background—The five-year overall survival (OS) of muscle-invasive bladder cancer (MIBC) with neoadjuvant chemotherapy and cystectomy is around 50%. There is no validated biomarker to guide the treatment decision. We investigated whether the Immunoscore (IS) could predict the pathologic response to neoadjuvant chemotherapy and survival outcomes. (2) Methods—This retrospective study evaluated the IS in 117 patients treated using neoadjuvant chemotherapy for localized MIBC from six centers (France and Greece). Pre-treatment tumor samples were immunostained for CD3+ and CD8+ T cells and quantified to determine the IS. The results were associated with the response to neoadjuvant chemotherapy, time to recurrence (TTR), and OS. (3) Results—Low (IS-0), intermediate (IS-1–2), and high (IS-3–4) ISs were observed in 36.5, 43.7, and 19.8% of the cohort, respectively. IS was positively associated with a pathologic complete response (pCR; p-value = 0.0096). A high IS was found in 35.7% of patients with a pCR, whereas it was found in 11.3% of patients without a pCR. A low IS was observed in 48.4% of patients with no pCR and in 21.4% of patients with a pCR. Low-, intermediate-, and high-IS patients had five-year recurrence-free rates of 37.2%, 36.5%, and 72.6%, respectively. In the multivariable analysis, a high IS was associated with a prolonged TTR (high vs. low: p = 0.0134) and OS (high vs. low: p = 0.011). (4) Conclusions—This study showed the significant prognostic and predictive roles of IS regarding localized MIBC.

The immune contexture and Immunoscore in cancer prognosis and therapeutic efficacy

The international American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) tumour-node-metastasis (TNM) staging system provides the current guidelines for the classification of cancer. However, among patients within the same stage, the clinical outcome can be very different. More recently, a novel definition of cancer has emerged, implicating at all stages a complex and dynamic interaction between tumour cells and the immune system. This has enabled the definition of the immune contexture, representing the pre-existing immune parameters associated with patient survival. Even so, the role of distinct immune cell types in modulating cancer progression is increasingly emerging. An immune-based assay named the 'Immunoscore' was defined to quantify the in situ T cell infiltrate and was demonstrated to be superior to the AJCC/UICC TNM classification for patients with colorectal cancer. This Review provides a broad overview of the main immune parameters positively or negatively shaping cancer development, including the Immunoscore, and their prognostic and predictive value. The importance of the immune system in cancer control is demonstrated by the requirement for a pre-existing intratumour adaptive immune response for effective immunotherapies, such as checkpoint inhibitors. Finally, we discuss how the combination of multiple immune parameters, rather than individual ones, might increase prognostic and/or predictive power.

No time to die: the consensus immunoscore for predicting survival and response to chemotherapy of locally advanced colon cancer patients in a multicenter international study

The multicenter international Society for Immunotherapy of Cancer (SITC) study of the consensus Immunoscore demonstrated the prediction of survival and response to chemotherapy in 763 Stage III colon cancer (CC) patients. Similar Immunoscore groups were found in elderly patients, and densities of immune cells and intratumoral T-cell repertoire were not decreasing with age in the tumor microenvironment. In two independent cohorts, Immunoscore significantly predicted time to recurrence (TTR), disease-free survival (DFS), and overall survival (OS), including within high-risk (T4 or N2) and low-risk (T1-3, N1) patients. In stratified Cox multivariable analysis for TTR, DFS, and OS, Immunoscore’s association to outcomes was independent of the patient’s age, sidedness, gender, T-stage, N-stage, and microsatellite instability status. Furthermore, the relative contribution to the risk test showed that Immunoscore had the highest contribution to survival. Importantly Immunoscore predicted the likelihood of response to chemotherapy. Only patients with a high-Immunoscore significantly benefited from chemotherapy. The prognostic value of Immunoscore was confirmed in two independent phase 3 clinical trials (NCCTG-N0147, n = 559; Prodige-IDEA, n = 1062). Moreover, results from IDEA phase 3 randomized trial revealed the predictive value of Immunoscore for response to adjuvant FOLFOX chemotherapy duration. The latest edition of the WHO Digestive System Tumors classification introduced the immune response as measured by Immunoscore as essential and desirable diagnostic criteria for CC, and Immunoscore was introduced into the 2020 ESMO Clinical Practice Guidelines for CC to refine the prognosis and adjust chemotherapy decision-making process in stages II and III patients. These results highlight the clinical utility of Immunoscore.

Usefulness and robustness of Immunoscore for personalized management of cancer patients

This review details the analytical performance characteristics of the consensus Immunoscore, measuring the immune response to cancer, improving the estimation of risk of recurrence, and predicting response to treatment for patients with colon cancer. The analytical validation of Immunoscore has been documented. Immunoscore is a robust, reproducible, quantitative, and standardized immune assay, with a high prognostic performance, independent of all of the prognostic markers currently used in clinical practice. Immunoscore evaluation within the tumor microenvironment is clinically relevant, and Immunoscore was recently introduced into ESMO Clinical Practice Guidelines for colon cancer and into the WHO classification of the Digestive System Tumors. This paves the way for the use of Immunoscore in clinical practice in colorectal tumors and likely soon in many other solid tumors.

The consensus Immunoscore in phase 3 clinical trials; potential impact on patient management decisions

The consensus Immunoscore has a prognostic value that has been confirmed in two randomized phase 3 clinical trials, and it provides a reliable estimate of the recurrence risk in colon cancer. The latest edition of the WHO classification of the Digestive System Tumors introduced for the first time the immune response as an essential and desirable diagnostic criteria for digestive cancers. Therefore, the immune response and Immunoscore evaluation within the tumor microenvironment is clinically relevant. In addition, the evaluation of the Immunoscore in stage III colon cancer patients from the IDEA France clinical trial evaluating 3 versus 6 months of oxaliplatin-based adjuvant chemotherapy demonstrated the predictive value of Immunoscore for treatment duration. Immunoscore predicted response to 6 months FOLFOX chemotherapy both in low- and high-risk Stage III patients. Low-risk patients (T_1-3, N₁) with High-Immunoscore had the 3-year DFS of 91.4% when treated with the 6-month FOLFOX, and only 80.8% with the 3-month regimen. The international validation of the prognostic value of the consensus Immunoscore together with its predictive value to guide treatment provides important information for the personalized management of colon cancer patients.

The consensus Immunoscore in phase 3 clinical trial (N0147) and impact on patient management decisions

The consensus Immunoscore is a routine assay quantifying the adaptive immune response within the tumor microenvironment. It has a prognostic value that has been confirmed in a phase 3 clinical trial (NCCTG N0147) in stage III colon cancers. Moreover, results from another phase 3 randomized trial revealed the predictive value of Immunoscore for response to adjuvant chemotherapy duration. These results highlight the clinical utility of Immunoscore. In its latest edition, the World Health Organization classification of Digestive System Tumors introduced for the first time the immune response as an essential and desirable diagnostic criterion for colorectal cancer. Within the tumor microenvironment, the immune response provides an important estimate of the risk of recurrence and death in colon cancer. The international validation of the prognostic value of the consensus Immunoscore together with its prognostic value in the N0147 trial and its predictive utility for response to chemotherapy in stage III patients provide valuable information for patient management.

The consensus immunoscore: toward a new classification of colorectal cancer

In its latest edition, the WHO classification of the Digestive System Tumors introduced for the first time the immune response as essential and desirable diagnostic criteria for colorectal cancer. The immune response within the tumor microenvironment is therefore clinically relevant. The consensus Immunoscore has a prognostic value that has been confirmed in a meta-analysis on more than 10,000 patients, and it provides a reliable estimate of the recurrence risk in colon cancer. The international validation of the prognostic value of the consensus Immunoscore for time to recurrence, disease-free survival and overall survival in colon cancer together with its predictive value of response to chemotherapy provides valuable information for patient care management.