Exploration of a Metabolism-Related Gene Signature Predicting Prognosis for Ovarian Cancer

Abstract Background: Dysregulation of metabolism plays a critical role in the pathogenesis and progression of ovarian cancer (OC). However, the expression pattern of metabolic genes in OC and the prognostic value of metabolism-related genes for OC patients remains to be elucidated. Thus, this study aimed to identify a metabolism-related prognostic gene signature for OC. Methods: The expression profiles of metabolism-related genes and associated clinicopathological characteristics were obtained from online datasets (The Cancer Genome Atlas, TCGA and The Genotype-Tissue Expression, GTEx). The differently expressed genes were subjected to functional enrichment analysis. By means of LASSO, univariate and multivariate Cox regression analyses, this predictive signature was constructed and validated by internal and external databases. Genomic alterations, immune infiltration, tumor microenvironment, and drug sensitivity associated with the signature were also described.Results: A total of 302 metabolism-related differentially expressed genes were identified. These genes were mainly enriched in functions associated with substance and energy metabolism. Based on the 302 identified genes, a prognostic signature of 21 metabolic genes was constructed and validated across internal and external cohorts. The patients in the high-risk group had significantly longer overall survival compared to those in the low-risk group. By univariate and multivariate Cox regression, the signature was identified as an independent prognostic predictor for overall survival. There were also noticeable differences with regards to genetic alteration, immune infiltration, tumor microenvironment and drug sensitivity between the two groups.Conclusion: Our study suggests that clinical outcomes of OC patients are associated with dysregulated metabolic genes and that the metabolism-related prognostic signature can be used as a predictor for the overall survival of OC patients.