Identification of an Immune Signature Predicting Prognosis Risk and Lymphocyte Infiltration in Colon Cancer
Xinyu Li, Dacheng Wen, Xiaokang Li, Chunli Yao, Wei Chong, Hao Chen
Abstract
Increasing studies have pointed out the effects of the tumor immune microenvironment (TIM) on colon cancer (CC) tumorigenesis, prognosis and metastasis. However, there has no reliable molecular marker that can effectively estimate the immune infiltration and predict the CC relapse risk. Here, we leveraged the gene expression profile and clinical characteristics from 1430 samples, including four GEO databases and TCGA database, to construct an immune risk signature that could be used as a predictor of survival outcome and immune activity. A risk model consisting of 10 immune-related genes were screened out in the LASSO-cox model and were then aggregated to generate the immune risk signature based on the regression coefficients. The signature demonstrated robust prognostic ability in discovery and validation datasets, and this association remained significant in the multivariate analysis after controlling for age, gender, clinical stage or MSI status. Leucocyte subpopulation analysis indicated that low-risk signature was enriched with cytotoxic cells (activated CD4/CD8+ T cell and NK cell) and depleted of MDSC and regulatory T cell. Further analysis indicated patients with low-risk signature harbored higher tumor mutation load and lower mutational frequencies in significantly mutated genes of APC and FBXW7. Together, our constructed signature could predict prognosis and represent the TIM of CC, which promotes individualized treatment and provides a promising novel molecular marker for immunotherapy.