Identification of prognostic immune-related signature predicting the overall survival for colorectal cancer.

2020 
OBJECTIVE: The morbidity and mortality of patients with colorectal cancer, one of the most common malignant tumors worldwide, is steadily increasing. The aim of this study was to investigate the association between prognostic immune-related gene profile and the outcome of colorectal cancer in patients by analyzing datasets from The Cancer Genome Atlas (TCGA). MATERIALS AND METHODS: Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) further demonstrated that these genes were enriched in many immune-related biological processes. Univariate Cox regression analysis was applied to examine the association of immune-related genes with the prognosis in patients with colorectal cancer. The least absolute shrinkage and selection operation (LASSO) Cox regression model was then used to establish the immune-related signature for the prognostic evaluation of colorectal cancer in patients. Survival differences were assessed by the Kaplan-Meier method along with the log-rank test. RESULTS: A total of 133 prognostic immune-related signatures were identified by using the univariate Cox proportional hazards regression analysis. A 14-gene signature-based risk score was constructed using the LASSO Cox regression. According to the cut-off of the risk-score, patients were assigned to the low-risk and high-risk groups. The log-rank test suggested that the survival time of the low-risk group was significantly higher than that of the high-risk group. In the time-dependent ROC curve analysis, the AUC for 1-year, 3-year, and 5-year overall survival (OS) were 0.781, 0.742, and 0.791, respectively. GO and KEGG analysis further revealed that the gene sets were actively involved in immune and inflammatory response, as well as the cytokine-cytokine receptor interaction pathway. CONCLUSIONS: To summarize, we identified a novel 14-gene immune-related signature that may potentially serve as a prognostic predictor for colorectal cancer, thereby contributing to patient personalized treatment decisions. Further research needs to be conducted to validate the prognostic value of the selected genes.
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