Identification of New Gene Labels for Colon Cancer Prognosis Based on Random Survival Forest Model

Objective To investigate the gene expression profile of mRNA in colon cancer and determine the optimal prognostic markers.Method The colon cancer dataset TCGA-COAD was downloaded from the Cancer Genome Atlas (TCGA) database as the training cohort. The random survival forest (RSF) model was used to determine gene labels, and the obtained gene labels were analyzed using the Cox model to construct risk scores. The colon cancer dataset GSE17536 was downloaded from the Gene Expression Database (GEO) as the validation cohort to validate the model, and compared horizontally with similar studies in the past year. Exploring the relationship between gene tags and immune cells through immune cell infiltration.Result A total of 11 gene tags were screened, and the risk score constructed by the multi factor Cox model was an independent prognostic indicator for colon cancer patients. The comparative development of this model is superior to previous studies. Immune cell infiltration revealed a significant correlation (P<0.05) between monocytes and the gene labels used in this study.Conclusion This study identified 11 gene markers with prognostic value for colon cancer, and monocytes may serve as potential therapeutic targets for colon cancer.