Construction and validation of a comprehensive metabolism-associated prognostic model for predicting survival and immunotherapy benefits in ovarian cancer.

ABSTRACT: Background: Ovarian cancer (OV) is a prevalent malignancy among gynecological tumors. Numerous metabolic pathways play a significant role in various human diseases, including malignant tumors. Our study aimed to develop a prognostic signature for OV based on a comprehensive set of metabolism-related genes (MRGs). Method: To achieve this, a bioinformatics analysis was performed on the expression profiles of 51 MRGs. The OV individuals were subsequently categorized into two molecular clusters based on the expression levels of MRGs. Following this, differentially expressed genes (DEGs) were identified among these clusters. The DEGs aided in the classification of two gene clusters, with a total of 390 DEGs being identified between them. A prognostic signature, constructed using t

SUBMITTER: Ye W 

PROVIDER: S-EPMC11492998 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature