Development and validation of a metabolic gene signature for predicting overall survival in patients with colon cancer

• Published in: Clinical and experimental medicine 2020-11, Vol.20 (4), p.535-544
• Main Authors: Ren, Jun, Feng, Juan, Song, Wei, Wang, Chuntao, Ge, Yuhang, Fu, Tao
• Format: Article
• Language: English
• Subjects: Colon cancer; Colorectal cancer; Gene expression; Genomes; Hematology; Internal Medicine; Medical prognosis; Medicine; Medicine & Public Health; Metabolism; Nomograms; Oncology; Original Article; Risk groups; Tumorigenesis
• ISSN: 1591-8890; 1591-9528
• DOI: 10.1007/s10238-020-00652-1

The reprogramming of cellular metabolism is a hallmark of tumorigenesis. However, the prognostic value of metabolism-related genes in colon cancer remains unclear. This study aimed to identify a metabolic gene signature to categorize colon cancer patients into high- and low-risk groups and predict prognosis. Samples from the Gene Expression Omnibus database were used as the training cohort, while samples from The Cancer Genome Atlas database were used as the validation cohort. A metabolic gene signature was established to investigate a robust risk stratification for colon cancer. Subsequently, a prognostic nomogram was established combining the metabolism-related risk score and clinicopathological characteristics of patients. A total of 351 differentially expressed metabolism-related genes were identified in colon cancer. After univariate analysis and least absolute shrinkage and selection operator-penalized regression analysis, an eight-gene metabolic signature ( MTR , NANS , HADH , IMPA2 , AGPAT1 , GGT5 , CYP2J2 , and ASL ) was identified to classify patients into high- and low-risk groups. High-risk patients had significantly shorter overall survival than low-risk patients in both the training and validation cohorts. A high-risk score was positively correlated with proximal colon cancer ( P  = 0.012), BRAF mutation ( P  = 0.049), and advanced stage ( P  = 0.027). We established a prognostic nomogram based on metabolism-related gene risk score and clinicopathologic factors. The areas under the curve and calibration curves indicated that the established nomogram showed a good accuracy of prediction. We have established a novel metabolic gene signature that could predict overall survival in colon cancer patients and serve as a biomarker for colon cancer.