Deciphering cervical cancer-associated biomarkers by integrated multi-omics approach.

ABSTRACT:

Objectives

Cervical Squamous Cell Carcinoma (CESC) is one of the most fatal female malignancies, and the underlying molecular mechanisms governing this disease have not been fully explored. In this research, we planned to conduct the analysis of Gene Expression Omnibus (GEO) cervical squamous cell carcinoma microarray datasets by a detailed in silico approach and to explore some novel biomarkers of CESC.

Methods

The top commonly differentially expressed genes (DEGs) from the GSE138080 and GSE113942 datasets were analyzed by Limma package-based GEO2R tool. The protein-protein interaction (PPI) network of the DEGs was drawn through Search Tool for the Retrieval of Interacting Genes (STRING), and top 6 hub genes were obtained from Cytoscape. Expression analysis and valid

SUBMITTER: Li X 

PROVIDER: S-EPMC9827308 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature