Identification of key genes associated with cervical cancer based on bioinformatics analysis.

ABSTRACT:

Background

Cervical cancer has extremely high morbidity and mortality, and its pathogenesis is still in the exploratory stage. This study aimed to screen and identify differentially expressed genes (DEGs) related to cervical cancer through bioinformatics analysis.

Methods

GSE63514 and GSE67522 were selected from the GEO database to screen DEGs. Then GO and KEGG analysis were performed on DEGs. PPI network of DEGs was constructed through STRING website, and the hub genes were found through 12 algorithms of Cytoscape software. Meanwhile, GSE30656 was selected from the GEO database to screen DEMs. Target genes of DEMs were screened through TagetScan, miRTarBase and miRDB. Next, the hub genes screened from DEGs were merged with the target genes screened from DEMs. Finally, ROC c

SUBMITTER: Yang X 

PROVIDER: S-EPMC11282596 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature