Mining TCGA database for gene expression in ovarian serous cystadenocarcinoma microenvironment.

ABSTRACT:

Background

Ovarian cancer is one of the leading causes of female deaths worldwide. Ovarian serous cystadenocarcinoma occupies about 90% of it. Effective and accurate biomarkers for diagnosis, outcome prediction and personalized treatment are needed urgently.

Methods

Gene expression profile for OSC patients was obtained from the TCGA database. The ESTIMATE algorithm was used to calculate immune scores and stromal scores of expression data of ovarian serous cystadenocarcinoma samples. Survival results between high and low groups of immune and stromal score were compared and differentially expressed genes (DEGs) were screened out by limma package. The Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and the protein-protein inter

SUBMITTER: Xu Y 

PROVIDER: S-EPMC8103916 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature