Construction of a Signature Composed of 14 Immune Genes to Judge the Prognosis and Immune Infiltration of Colon Cancer

Background: Colon cancer (CC) is an immunogenic tumor and immune-targeting disease. In this study, we analyzed differentially expressed genes (DEGs) from the expression profile data in CC of The Cancer Genome Atlas. Methods and Results: Using univariate and multivariate Cox regression analysis, an immune gene-risk model containing 14 immune genes was established. Four hundred seventeen CC samples were divided into high-risk and low-risk groups, and Kaplan-Meier analysis revealed that high-risk score predicted poor survival. Meanwhile, we found the model was an independent prognostic factor for CC. Weighted gene coexpression network analysis was used to identify key gene modules between high- and low-risk groups. The methods of CIBERSORT and single-sample Gene Set Enrichment Analysis were used to evaluate the correlation between immune cells and our model. Conclusion: Taken together, our study suggested that the immune gene-related risk model may be developed as a potential tool in the prognostic assessment of CC.