Colon cancer has a huge incidence and mortality worldwide every year. Immunotherapy could be a new therapeutic option for patients with advanced colon cancer. Tumor mutation burden (TMB) and immune infiltration are considered critical in immunotherapy but their characteristics in colon cancer are still controversial.
The somatic mutation, transcriptome, and clinical data of patients with colon cancer were obtained from the TCGA database. Patients were divided into low or high TMB groups using the median TMB value. Somatic mutation landscape, differentially expressed genes, and immune-related hub genes, Gene Ontology and KEGG, gene set enrichment, and immune infiltration analyses were investigated between the two TMB groups. Univariate and multivariate Cox analyses were utilized to construct a prognostic gene signature. The differences in immune infiltration, and the expression of HLA-related genes and checkpoint genes were investigated between the two immunity groups based on single sample gene set enrichment analysis. Finally, a nomogram of the prognostic prediction model integrating TMB, immune infiltration, and clinical parameters was established. Calibration plots and receiver operating characteristic curves (ROC) were drawn, and the C-index was calculated to assess the predictive ability.
Missense mutations and single nucleotide polymorphisms were the major variant characteristics in colon cancer. The TMB level showed significant differences in N stage, M stage, pathological stage, and immune infiltration. CD8+ T cells, activated memory CD4+ T cells, activated NK cells, and M1 macrophages infiltrated more in the high-TMB group. The antigen processing and presentation signaling pathway was enriched in the high-TMB group. Two immune related genes (CHGB and SCT) were identified to be correlated with colon cancer survival (HR = 1.39,
In this study, we investigated the patterns and prognostic roles of TMB and immune infiltration in colon cancer, which provided new insights into the tumor microenvironment and immunotherapies and the development of a novel nomogram prognostic prediction model for patients with colon cancer.