Establishment of a novel glycolysis-related prognostic gene signature for ovarian cancer and its relationships with immune infiltration of the tumor microenvironment.

ABSTRACT:

Background

Glycolysis affects tumor growth, invasion, chemotherapy resistance, and the tumor microenvironment. In this study, we aimed to construct a glycolysis-related prognostic model for ovarian cancer and analyze its relationship with the tumor microenvironment's immune cell infiltration.

Methods

We obtained six glycolysis-related gene sets for gene set enrichment analysis (GSEA). Ovarian cancer data from The Cancer Genome Atlas (TCGA) database and two Gene Expression Omnibus (GEO) datasets were divided into two groups after removing batch effects. We compared the tumor environments' immune components in high-risk and low-risk groups and analyzed the correlation between glycolysis- and immune-related genes. Then, we generated and validated a predictive model for the prog

SUBMITTER: Bi J 

PROVIDER: S-EPMC8425093 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature