Screening and Identification of Potential Prognostic Biomarkers in Adrenocortical Carcinoma.

ABSTRACT: Objective: Adrenocortical carcinoma (ACC) is a rare but aggressive malignant cancer that has been attracting growing attention over recent decades. This study aims to integrate protein interaction networks with gene expression profiles to identify potential biomarkers with prognostic value in silico. Methods: Three microarray data sets were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) according to the normalization annotation information. Enrichment analyses were utilized to describe biological functions. A protein-protein interaction network (PPI) of the DEGs was developed, and the modules were analyzed using STRING and Cytoscape. LASSO Cox regression was used to identify independent prognostic factors. T

SUBMITTER: Xu WH 

PROVIDER: S-EPMC6749084 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature