Prediction of Survival Rate and Chemotherapy Effect by an Immune Score Model in Colorectal Cancer

Abstract

Colorectal cancer is the third most common cancer and the second leading cause of cancer-related deaths. Immune cells in the tumor microenvironment play an important role in the development of tumors. In this study, CIBERSORT was used to estimate the subset of the immune cells using bulk gene expression data (i.e., TCGA, GEO, and cBioPortal databases). 1,087 samples were included in the analysis. The results revealed that among the 22 immune cell subsets that were evaluated, resting and activated NK cells, macrophage M1 and M2, and resting mast cells are associated with significant improvements in patient survival of colorectal cancer. The 15-year survival rates for the training cohort showed 49.1% and 32.5%, respectively, for the low- and high-risk groups. Likewise, the validation and entire cohorts showed 77.3% versus 47.2% and 65.3% versus 46.5%, respectively, for the low- and high-risk groups. Also, the prognostic immune score in predicting the chemotherapy effects showed that the low-risk group had a better survival superiority over the high-risk group, whether patients received chemotherapy or not. The gene set enrichment analysis showed that the low-risk group was highly enriched in pathways or processes related to immune response. The immune checkpoint assessment revealed significantly higher mRNA expressions of CTLA4 in the lower risk group than in the higher risk group. Altogether, this study offers information that could improve the prognosis of colorectal cancer.