Screening and prognostic value of potential biomarkers for ovarian cancer.

ABSTRACT:

Background

Ovarian cancer is a common gynecological malignant tumor that greatly threatens women's health, so we screened potential biomarkers of ovarian cancer and analyzed their prognostic value.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to analyze the ovarian cancer-related genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to analyze the function of ovarian cancer-related genes. The survival-related genes were screened out through the least absolute shrinkage and selection operator (LASSO) method. Multivariate Cox regression model and stepwise regression analysis were performed to construct the risk model. The receiver operating characteristic (ROC) and the area under the

SUBMITTER: Li H 

PROVIDER: S-EPMC8267297 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature