Integrative analysis of key candidate genes and signaling pathways in ovarian cancer by bioinformatics.

ABSTRACT:

Background

Ovarian cancer is one of the most common gynecological tumors, and among gynecological tumors, its incidence and mortality rates are fairly high. However, the pathogenesis of ovarian cancer is not clear. The present study aimed to investigate the differentially expressed genes and signaling pathways associated with ovarian cancer by bioinformatics analysis.

Methods

The data from three mRNA expression profiling microarrays (GSE14407, GSE29450, and GSE54388) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes between ovarian cancer tissues and normal tissues were identified using R software. The overlapping genes from the three GEO datasets were identified, and profound analysis was performed. The overlapping genes were used

SUBMITTER: Dong C 

PROVIDER: S-EPMC8276467 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature