Identification of immune subtypes and their prognosis and molecular implications in colorectal cancer

Abstract

Immune composition is commonly heterogeneous and varies among colorectal cancer (CRC) patients. A comprehensive immune classification may act as important characteristics to predict CRC prognosis. Thus, we aimed to identify novel immune specific subtypes to guide future therapies. Unsupervised clustering was used to classify CRC samples into different immune subtypes based on abundances of immune cell populations, during which TCGA and GSE17536 datasets were used as training and validation sets, respectively. The associations between the immune subtypes and patient prognosis were investigated. Further, we identified differentially expressed genes (DEGs) between immune high and low subtypes, followed by functional enrichment analyses of DEGs. The expression levels of 74 immunomodulators (IMs) across immune subtypes were analyzed. As a result, we clustered CRC samples into three distinct immune subtypes (immune high, moderate, and low). Patients with immune-high subtype showed the best prognosis, and patients with immune-low subtype had the worst survival in both TCGA and GSE17536 cohorts. A group of 2735 up-regulated DEGs were identified across immune high and low subtypes. The main DEGs were the members of complement components, chemokines, immunoglobulins, and immunosuppressive genes that are involved in immune modulation-related pathways (e.g., cytokine-cytokine receptor interaction) or GO terms (e.g., adaptive immune response and T cell activation). The expression levels of 63 IMs were significantly varied across immune subtypes. In conclusion, this study provides a conceptual framework and molecular characteristics of CRC immune subtypes, which may accurately predict prognosis and offer novel targets for personalized immunotherapy through modifying subtype-specific tumor immune microenvironment.