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Colorectal cancer (CRC) is highly heterogeneous at the genetic and molecular level, which has major repercussions on the efficacy of immunotherapy. A small subset of CRCs exhibit microsatellite instability (MSI), a molecular indicator of defective DNA mismatch repair (MMR), but the majority are microsatellite-stable (MSS). The high tumor mutational burden (TMB) and neoantigen load in MSI tumors favors the infiltration of immune effector cells, and antitumor immune responses within these tumors are strong relative to their MSS counterparts. MSI has emerged as a major predictive marker for the efficacy of immune checkpoint blockade over the last few years and nivolumab or pembrolizumab targeting PD-1 has been approved for patients with MSI refractory or metastatic CRC. However, some MSS tumors show DNA polymerase epsilon (POLE) mutations that also confer a very high TMB and may also be heavily infiltrated by immune cells making them amenable to respond to immune checkpoint inhibitors (ICI). In this review we discuss the role of the different immune landscapes in CRC and their relationships with defined CRC genetic subtypes. We discuss potential reasons why immune checkpoint blockade has met with limited success for the majority of CRC patients, despite the finding that immune cell infiltration of primary non-metastatic tumors is a strong predictive, and prognostic factor for relapse and survival. We then consider in which ways CRC cells develop mechanisms to resist ICI. Finally, we address the latest advances in CRC vaccination and how a personalized neoantigen vaccine strategy might overcome the resistance of MSI and MSS tumors in patients for whom immune checkpoint blockade is not a treatment option.

Limited previous studies focused on the death and progression risk stratification of colorectal cancer (CRC) lung metastasis patients. The aim of this study is to construct a nomogram model combing machine learning-pathomics, radiomics features, Immunoscore and clinical factors to predict the postoperative outcome of CRC patients with lung metastasis. In this study, a total of 103 CRC patients having metastases limited to lung and undergoing radical lung resection were identified. Patch-level convolutional neural network training in weakly supervised manner was used to perform whole slides histopathological images survival analysis. Synthetic minority oversampling technique and support vector machine classifier were used to identify radiomics features and build predictive signature. The Immunoscore for each patient was calculated from the density of CD3+ and CD8+ cells at the invasive margin and the center of metastatic tumor which were assessed on consecutive sections of automated digital pathology. Finally, pathomics and radiomics signatures were successfully developed to predict the overall survival (OS) and disease free survival (DFS) of patients. The predicted pathomics and radiomics scores are negatively correlated with Immunoscore and they are three independent prognostic factors for OS and DFS prediction. The combined nomogram showed outstanding performance in predicting OS (AUC = 0.860) and DFS (AUC = 0.875). The calibration curve and decision curve analysis demonstrated the considerable clinical usefulness of the combined nomogram. Taken together, the developed nomogram model consisting of machine learning-pathomics signature, radiomics signature, Immunoscore and clinical features could be reliable in predicting postoperative OS and DFS of colorectal lung metastasis patients.

Background The tumor microenvironment (TME) plays an important role in the occurrence and development of gastric cancer (GC) and is widely used to assess the treatment outcomes of GC patients. Immunohistochemistry (IHC) and gene sequencing are the main analysis methods for the TME but are limited due to the subjectivity of observers, the high cost of equipment and the need for professional analysts. Methods The ImmunoScore (IS) was developed in the TCGA cohort and validated in GEO cohorts. The Radiomic ImmunoScore (RIS) was developed in the TCGA cohort and validated in the Nanfang cohort. A nomogram was developed and validated in the Nanfang cohort based on RIS and clinical features. Results For IS, the area under the curves (AUCs) were 0.798 for 2-year overall survival (OS) and 0.873 for 4-year overall survival. For RIS, in the TCGA cohort, the AUCs distinguishing High-IS or Low-IS and predicting prognosis were 0.85 and 0.81, respectively; in the Nanfang cohort, the AUC predicting prognosis was 0.72. The nomogram performed better than the TNM staging system according to the ROC curve (all P < 0.01). Patients with TNM stage II and III in the High-nomogram group were more likely to benefit from adjuvant chemotherapy than Low-nomogram group patients. Conclusions The RIS and the nomogram can be used to assess the TME, prognosis and adjuvant chemotherapy benefit of GC patients after radical gastrectomy and are valuable additions to the current TNM staging system. High-nomogram GC patients may benefit more from adjuvant chemotherapy than Low-nomogram GC patients.

Therapeutic options for metastatic colorectal cancer (mCRC) are very limited, and the prognosis using combination therapy with a chemotherapeutic drug and a targeted agent, e.g., epidermal growth factor receptor or tyrosine kinase, remains poor. Therefore, mCRC is associated with a poor median overall survival (mOS) of only 25–30 months. Current immunotherapies with checkpoint inhibitor blockade (ICB) have led to a substantial change in the treatment of several cancers, such as melanoma and non-small cell lung cancer. In CRC, ICB has only limited effects, except in patients with microsatellite instability-high (MSI-H) or mismatch repair-deficient (dMMR) tumors, which comprise about 15% of sporadic CRC patients and about 4% of patients with metastatic CRC. The vast majority of sporadic CRCs are microsatellite-stable (MSS) tumors with low levels of infiltrating immune cells, in which immunotherapy has no clinical benefit so far. Immunotherapy with checkpoint inhibitors requires the presence of infiltrating T cells into the tumor microenvironment (TME). This makes T cells the most important effector cells in the TME, as evidenced by the establishment of the immunoscore—a method to estimate the prognosis of CRC patients. The microenvironment of a tumor contains several types of T cells that are anti-tumorigenic, such as CD8+ T cells or pro-tumorigenic, such as regulatory T cells (Tregs) or T helper 17 (Th17) cells. However, even CD8+ T cells show marked heterogeneity, e.g., they can become exhausted, enter a state of hyporesponsiveness or become dysfunctional and express high levels of checkpoint molecules, the targets for ICB. To kill cancer cells, CD8+ T cells need the recognition of the MHC class I, which is often downregulated on colorectal cancer cells. In this case, a population of unconventional T cells with a γδ T cell receptor can overcome the limitations of the conventional CD8+ T cells with an αβT cell receptor. γδ T cells recognize antigens in an MHC-independent manner, thus acting as a bridge between innate and adaptive immunity. Here, we discuss the effects of different T cell subsets in colorectal cancer with a special emphasis on γδ T cells and the possibility of using them in CAR-T cell therapy. We explain T cell exclusion in microsatellite-stable colorectal cancer and the possibilities to overcome this exclusion to enable immunotherapy even in these “cold” tumors.

Colorectal cancer (CRC) is a major cause of cancer-related deaths globally. While treatment advancements have improved survival rates, primarily through targeted therapies based on KRAS, NRAS, and BRAF mutations, personalized treatment strategies for CRC remain limited. Immunotherapy, mainly immune checkpoint blockade, has shown efficacy in various cancers but is effective in only a small subset of patients with CRC with deficient mismatch repair (dMMR) proteins or high microsatellite instability (MSI). Recent research has challenged the notion that CRC is immunologically inert, revealing subsets with high immunogenicity and diverse lymphocytic infiltration. Identifying precise biomarkers beyond dMMR and MSI is crucial to expanding immunotherapy benefits. Hence, exploration has extended to various biomarker sources, such as the tumor microenvironment, genomic markers, and gut microbiota. Recent studies have introduced a novel classification system, consensus molecular subtypes, that aids in identifying patients with CRC with an immunogenic profile. These findings underscore the necessity of moving beyond single biomarkers and toward a comprehensive understanding of the immunological landscape in CRC, facilitating the development of more effective, personalized therapies. The findings of this study underscore the necessity of moving beyond single biomarkers and toward a comprehensive understanding of the immunological landscape in colorectal cancer, facilitating the development of more effective, personalized therapies.

Following initial success in melanoma and lung tumours, immune checkpoint inhibitors (ICIs) are now well recognized as a major immunotherapy treatment modality for multiple types of solid cancers. In colorectal cancer (CRC), the small subset that is mismatch-repair-deficient and microsatellite-instability-high (dMMR/MSI-H) derive benefit from immunotherapy; however, the vast majority of patients with proficient MMR (pMMR) or with microsatellite stable (MSS) CRC do not. Immunoscore and the consensus molecular subtype classifications are promising biomarkers in predicting therapeutic efficacy in selected CRC. In pMRR/MSS CRC, biomarkers are also needed to understand the molecular mechanisms governing immune reactivity and to predict their relationship to treatment. The continuous development of such biomarkers would offer new perspectives and more personalized treatments by targeting oncological options, including ICIs, which modify the tumour-immune microenvironment. In this review, we focus on CRC and discuss the current status of ICIs, the role of biomarkers to predict response to immunotherapy, and the approaches being explored to render pMMR/MSS CRC more immunogenic through the use of combined therapies.

To explore the immune microenvironment of RAS ‐mutated ( RAS mt) microsatellite stable (MSS) colon cancer (CC), we retrospectively performed whole exome sequencing, RNA sequencing, and robust digital pathology analyses and studied immune markers in a cohort of 161 patients treated with standard‐of‐care therapies with early stage disease (both fresh frozen and formalin‐fixed paraffin‐embedded [FFPE] samples) or 121 patients with metastatic setting (primary tumor FFPE samples). Only a small proportion of cases exhibited a highly infiltrated immune microenvironment, with a strong association between Immunoscore ® (IS)‐high (13% of the samples) and Tumor Lymphocytes Infiltrating Score (TuLIS)‐high scores (25% of the samples). Immunoscore Immune‐Checkpoint (ISIC)‐high tumors (52% of the samples) shared a similar microenvironment composition to IS‐high and TuLIS‐like high tumors and displayed higher mutational burdens than ISIC‐low tumors. In conclusion, a substantial proportion of MSS RAS mt CCs exhibit high ISIC scores, meriting evaluation in prospective trials of immunotherapy‐based combination regimens.

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related death in the world. Immunological analysis of the tumor microenvironment (immunoscore) shows great promise for improved prognosis and prediction of response to immunotherapy. However, the exact immune cell composition in NSCLC remains unclear. Here, we used flow cytometry to characterize the immune infiltrate in NSCLC tumors, non-cancerous lung tissue, regional lymph node, and blood. The cellular identity of >95% of all CD45 immune cells was determined. Thirteen distinct immune cell types were identified in NSCLC tumors. T cells dominated the lung cancer landscape (on average 47% of all CD45 immune cells). CD4 T cells were the most abundant T cell population (26%), closely followed by CD8 T cells (22%). Double negative CD4 CD8 T cells represented a small fraction (1.4%). CD19 B cells were the second most common immune cell type in NSCLC tumors (16%), and four different B cell sub-populations were identified. Macrophages and natural killer (NK) cells composed 4.7 and 4.5% of the immune cell infiltrate, respectively. Three types of dendritic cells (DCs) were identified (plasmacytoid DCs, CD1c DCs, and CD141 DCs) which together represented 2.1% of all immune cells. Among granulocytes, neutrophils were frequent (8.6%) with a high patient-to-patient variability, while mast cells (1.4%), basophils (0.4%), and eosinophils (0.3%) were less common. Across the cohort of patients, only B cells showed a significantly higher representation in NSCLC tumors compared to the distal lung. In contrast, the percentages of macrophages and NK cells were lower in tumors than in non-cancerous lung tissue. Furthermore, the fraction of macrophages with high HLA-DR expression levels was higher in NSCLC tumors relative to distal lung tissue. To make the method readily accessible, antibody panels and flow cytometry gating strategy used to identify the various immune cells are described in detail. This work should represent a useful resource for the immunomonitoring of patients with NSCLC.

IntroductionThe tumor microenvironment (TME) in colorectal cancer (CRC) includes the gut microbiome, immune cells, angiogenic factors, and fibroblasts and plays a major role in cancer progression. The Immunoscore (IS) is based on tumor infiltration by immune cells that are known prognostic biomarkers for CRC. However, the interrelation between the IS, microbiome, and other TME factors in human CRC remains unclear.Patients and methodsA cohort of 94 patients with CRC was examined at the Shiga University of Medical Science Hospital in Japan. The expression levels of CD3, CD8, CD31, and alpha-smooth muscle actin (α-SMA) in the primary tumor were evaluated by immunohistochemistry. The IS was calculated based on the results of the CD3 and CD8 staining assays. Microbiomes in patients with CRC were examined by amplicon sequencing.ResultsThe expression levels of α-SMA and tumor-infiltrating lymphocytes in patients with CRC were negatively correlated (P = 0.006). A high IS was associated with high abundance of Lachnospiraceae in the microbiomes of patients with CRC.ConclusionLymphocyte infiltration into the primary tumor was marked by reduced density of cancer-associated fibroblasts and enrichment of the Lachnospiraceae family in the gut microbiome, which may influence CRC progression.

The fifth “Melanoma Bridge Meeting” took place in Naples, December 1–5th, 2015. The main topics discussed at this meeting were: Molecular and Immuno advances, Immunotherapies and Combination Therapies, Tumor Microenvironment and Biomarkers and Immunoscore. The natural history of cancer involves interactions between the tumor and the immune system of the host. The immune infiltration at the tumor site may be indicative of host response. Significant correlations were shown between the levels of immune cell infiltration in tumors and patient’s clinical outcome. Moreover, incredible progress comes from the discovery of mutation-encoded tumor neoantigens. In fact, as tumors grow, they acquire mutations that are able to influence the response of patients to immune checkpoint inhibitors. It has been demonstrated that sensitivity to PD-1 and CTLA-4 blockade in patients with advanced NSCLC and melanoma was enhanced in tumors enriched for clonal neoantigens. The road ahead is still very long, but the knowledge of the mechanisms of immune escape, the study of tumor neo-antigens as well as of tumor microenvironment and the development of new immunotherapy strategies, will make cancer a more and more treatable disease.