Construction of a novel prognostic-predicting model correlated to ovarian cancer.

ABSTRACT:

Background

Ovarian cancer (OC) is one of the most lethal gynecological cancers worldwide. The pathogenesis of the disease and outcomes prediction of OC patients remain largely unclear. The present study aimed to explore the key genes and biological pathways in ovarian carcinoma development, as well as construct a prognostic model to predict patients' overall survival (OS).

Results

We identified 164 up-regulated and 80 down-regulated differentially expressed genes (DEGs) associated with OC. Gene Ontology (GO) term enrichment showed DEGs mainly correlated with spindle microtubes. For Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, cell cycle was mostly enriched for the DEGs. The protein-protein interaction (PPI) network yielded 238 nodes and 1284 edges. Top three modu

SUBMITTER: Tang W 

PROVIDER: S-EPMC7414523 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature