A Risk Model for Prognosis and Treatment Response Prediction in Colon Adenocarcinoma Based on Genes Associated with the Characteristics of the Epithelial-Mesenchymal Transition

Abstract

The epithelial-mesenchymal transition (EMT) is an important process during metastasis in various tumors, including colorectal cancer (CRC). Thus, the study of its characteristics and related genes is of great significance for CRC treatment. In this study, 26 EMT-related gene sets were used to score each sample from The Cancer Genome Atlas program (TCGA) colon adenocarcinoma (COAD) database. Based on the 26 EMT enrichment scores for each sample, we performed unsupervised cluster analysis and classified the TCGA-COAD samples into three EMT clusters. Then, weighted gene co-expression network analysis (WGCNA) was used to investigate the gene modules that were significantly associated with these three EMT clusters. Two gene modules that were strongly positively correlated with the EMT cluster 2 (worst prognosis) were subjected to Cox regression and least absolute shrinkage and selection operator (LASSO) regression analysis. Then, a prognosis-related risk model composed of three hub genes GPRC5B, LSAMP, and PDGFRA was established. The TCGA rectal adenocarcinoma (READ) dataset and a CRC dataset from the Gene Expression Omnibus (GEO) were used as the validation sets. A novel nomogram that incorporated the risk model and clinicopathological features was developed to predict the clinical outcomes of the COAD patients. The risk model served as an independent prognostic factor. It showed good predictive power for overall survival (OS), immunotherapy efficacy, and drug sensitivity in the COAD patients. Our study provides a comprehensive evaluation of the clinical relevance of this three-gene risk model for COAD patients and a deeper understanding of the role of EMT-related genes in COAD.