Construction of a prognostic model for ovarian cancer based on a comprehensive bioinformatics analysis of cuproptosis-associated long non-coding RNA signatures.

ABSTRACT: Ovarian cancer (OCa) is a common malignancy in women, and the role of cuproptosis and its related genes in OCa is unclear. Using the GSE14407 dataset, we analyzed the expression and correlation of cuproptosis-related genes (CRGs) between tumor and normal groups. From the TCGA-OV dataset, we identified 20 cuproptosis-related long non-coding RNAs (CuLncs) associated with patient survival through univariate Cox analysis. OCa patients were divided into early-stage and late-stage groups to analyze CuLncs expression. Cluster analysis classified patients into two clusters, with Cluster1 having a poorer prognosis. Significant differences in "Lymphatic Invasion" and "Cancer status" were observed between clusters. Seven CRGs showed significant expression differences, validated using the human protei

SUBMITTER: Chen R 

PROVIDER: S-EPMC11336372 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature