Improving the efficacy of immunotherapy for colorectal cancer: Targeting tumor microenvironment-associated immunosuppressive cells.

Currently, immune checkpoint inhibitors (ICIs) have changed the treatment paradigm for many malignant tumors. As the most common digestive tract malignancy, colorectal cancer (CRC) shows a good response to ICIs only in a small subset of patients with MSI-H/dMMR CRC. In contrast, patients with MSS/pMMR CRC show minimal response to ICIs. The results of the REGONIVO study suggest that targeting the tumor microenvironment (TME) to improve immunotherapy outcomes in MSS/pMMR CRC patients is a feasible strategy. Therefore, this article focuses on exploring the feasibility of targeting the TME to enhance immunotherapy outcomes in CRC, collecting recent basic research on targeting the TME to enhance immunotherapy outcomes in CRC and analyzing ongoing clinical trials to provide a theoretical basis and future research directions for improving immunotherapy outcomes in MSS/pMMR CRC.

Construction and validation of a colon cancer prognostic model based on tumor mutation burden-related genes.

Currently, immunotherapy has entered the clinical diagnosis and treatment guidelines for colon cancer, but existing immunotherapy markers cannot predict the effectiveness of immunotherapy well. This study utilized the TCGA-COAD queue to perform differential gene analysis on high and low-mutation burden samples, and screen differentially expressed genes (DEGs). To explore new molecular markers or predictive models of immunotherapy by using DEGs for NMF classification and prognostic model construction. Through systematic bioinformatics analysis, the TCGA-COAD cohort was successfully divided into high mutation burden subtypes and low mutation burden subtypes by NMF typing using DEGs. The proportion of MSI-H between high mutation burden subtypes was significantly higher than that of low mutation burden subtypes, but there was no significant difference in immunotherapy efficacy between the two subtypes. Drug sensitivity analysis showed significant differences in drug sensitivity between the two subtypes. Subsequently, we constructed a prognostic model using DEGs, which can effectively predict patient survival and immunotherapy outcomes. The prognosis and immunotherapy outcomes of the low-risk group were significantly better than those of the high-risk group. The external dataset validation of the constructed prognostic model using the GSE39582 dataset from the GEO database yielded consistent results. At the same time, we also analyzed the TMB and MSI situation between the high and low-risk groups, and the results showed that there was no significant difference in TMB between the high and low-risk groups, but the proportion of MSI-H in the high-risk group was significantly higher than that in the low-risk group. Finally, we conclude that TMB is not a suitable molecular marker for predicting the efficacy of immunotherapy in colon cancer. The newly constructed prognostic model can effectively differentiate the prognosis of colon cancer patients and predict their immunotherapy efficacy.