Comprehensive Analysis of Genomic and Expression Data Identified Potential Markers for Predicting Prognosis and Immune Response in CRC

Colorectal cancer (CRC) is the most prevalent type of malignant tumor of the gastrointestinal tract. In the current study, we characterized the landscape of genomic alterations in CRC patients. Based on the results of whole-exome sequencing (WES), we identified 31 significantly mutated genes. Among them, several genes including TP53, KRAS, APC, PI3KCA, and BRAF were reported as significantly mutated genes in previous studies. In the current study, the most frequently mutated gene was TP53, which encodes tumor suppressor p53, affecting approximately 60% of CRC patients. In addition, we performed the expression profiles of significantly mutated genes between the normal group and tumor groups and identified 20 differentially expressed genes (DEGs); among them, CSMD3, DCHS2, LRP2, RYR2, and ZFHX4 were significantly negatively correlated with PFS. Moreover, consensus clustering analysis for CRC based on the expression of significantly somatic mutated genes was performed. In total, three subtypes of CRC were identified in CRC, including cluster1 (n = 453), cluster2 (n = 158), and cluster 3 (n = 9), based on expression level of significantly somatic mutated genes. Clinicopathological features analysis showed subtype C1 had the longest progression-free survival (PFS) with median time of 8.2 years, while subtypes C2 and C3 had 4.1 and 2.7 years of PFS, respectively. Moreover, we found three subtypes related to tumor infiltration depth, lymph node metastasis, and distant metastasis. Immune infiltration analysis showed the tumor infiltration levels of B cell native, T cell CD8+, T cell CD4+ memory activated, T cell gamma delta, NK cell resting, macrophage M0, macrophage M2, myeloid dendritic cell activated, mast cell activated, and mast cell resting significantly changed among the three groups, demonstrating the three subgroups classified by 22 somatically significantly mutated genes had a high capacity to differentiate patients with different immune statuses, which is helpful for the prediction of immunotherapy response of CRC patients. Our findings could provide novel potential predictive indicators for CRC prognosis and therapy targets for CRC immunotherapy.