Identification and Validation of a Glycolysis Related Metabolic Reprogramming Gene Signature for Predicting Survival in Colon Cancer Patients

Abstract

Background Colon cancer (CC) is one of the most common gastrointestinal malignant tumors with high mortality rate. Because of malignancy and easily metastasis feather, and limited treatments, the prognosis of CC remains poor. Glycolysis is a metabolic process of glucose in anoxic environments which is an important way to provide energy for tumor. The role of glycolysis in CC largely remains unknown and is necessary to be explored. Method In our study, we analyzed glycolysis related genes expression in CC, patients gene expression and corresponding clinical data were downloaded from GEO dataset, glycolysis related genes sets were collected from Msigdb. Through COX regression analysis, prognosis model based on glycolysis-related genes was established. The efficacy of gene model was tested by Survival analysis, ROC analysis and PCA analysis. Furthermore, the relationship between risk scores and clinical characteristic was researched. Results Our findings identified 13 glycolysis related genes (NUP107, SEC13, ALDH7A1, ALG1, CHPF, FAM162A, FBP2, GALK1, IDH1, TGFA, VLDLR, XYLT2 and OGDHL) consisted prognostic prediction model with relative high accuracy. The relationship between prediction model and clinical feathers were specifically studied, results showed age > 65years, TNM III-IV, T3-4, N1-3, M1 and high-risk score were independent prognostic risk factors with poorer prognosis. Finally, model genes were significantly expressed and EMT were activated in CC patients. Conclusion This study provided a new aspect to advance our understanding in the potential mechanism of glycolysis in CC.