The Landscape of the Tumor-Infiltrating Immune Cell and Prognostic Nomogram in Colorectal Cancer

Abstract

Tumor-infiltrating immune cells are associated with prognosis and immunotherapy targets in colorectal cancer (CRC). The recently developed CIBERSORT method allows immune cell analysis by deconvolution of high-throughput data onto gene expression. In this study, we analyzed the relative proportions of immune cells in GEO (94 samples) and TCGA (522 samples) CRC data based on the CIBERSORT method. A total of 22 types of tumor-infiltrating immune cells were evaluated. Combined with GEO and TCGA data, it was found that naive B cells, M2 macrophages, and resting mast cells were highly expressed in normal tissues, while M0 macrophages, M1 macrophages, activated mast cells, and neutrophils were highly expressed in tumors. Moreover, we constructed a prognostic model by infiltrating immune cells that showed high specificity and sensitivity in both the training (AUC of 5-year survival = 0.699) and validation (AUC of 5-year survival = 0.844) sets. This provides another basis for clinical prognosis. The results of multiple immunofluorescence detection showed that there were differences in the results of bioinformatics analysis. Neutrophils were highly expressed in normal tissues, and M2 macrophages were highly expressed in tumor tissues. Collectively, our data suggested that infiltrating immune cells in CRC may be an important determinant of prognosis and immunotherapy.