Development and validation of an individualized gene expression-based signature to predict overall survival of patients with high-grade serous ovarian carcinoma.

ABSTRACT:

Background

High-grade serious ovarian carcinoma (HGSOC) is a subtype of ovarian cancer with a different prognosis attributable to genetic heterogeneity. The prognosis of patients with advanced HGSOC requires prediction by genetic markers. This study systematically analyzed gene expression profile data to establish a genetic marker for predicting HGSOC prognosis.

Methods

The RNA-seq data set and information on clinical follow-up of HGSOC were retrieved from Gene Expression Omnibus (GEO) database, and the data were standardized by DESeq2 as a training set. On the other hand, HGSOC RNA sequence data and information on clinical follow-up were retrieved from The Cancer Genome Atlas (TCGA) as a test set. Additionally, ovarian cancer microarray data set was obtained from GEO as the

SUBMITTER: Yuan D 

PROVIDER: S-EPMC10604403 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature