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

Bibliographic Details
Title: Construction of a prognostic model for ovarian cancer based on a comprehensive bioinformatics analysis of cuproptosis-associated long non-coding RNA signatures
Authors: Rujun Chen, Yating Huang, Ke Sun, Fuyun Dong, Xiaoqin Wang, Junhua Guan, Lina Yang, He Fei
Source: Heliyon, Vol 10, Iss 15, Pp e35004- (2024)
Publisher Information: Elsevier, 2024.
Publication Year: 2024
Collection: LCC:Science (General)
LCC:Social sciences (General)
Subject Terms: Cuproptosis, Prognostic model, Long non-coding RNAs signature, Patient survival, Immune infiltration, Science (General), Q1-390, Social sciences (General), H1-99
More Details: 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 protein atlas (HPA) databases. Immune analysis revealed a higher ImmuneScore in Cluster1. GSEA identified associated signaling pathways. LASSO regression included 11 CuLncs to construct and validate a survival prediction model, classifying patients into high-risk and low-risk groups. Correlations between riskScore, Cluster phenotype, ImmuneScore, and immune cell infiltration were explored. Cell experiments showed that knocking down AC023644.1 decreases OCa cell viability. In conclusion, we constructed an accurate prognostic model for OCa based on 11 CuLncs, providing a basis for prognosis assessment and potential immunotherapy targets.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2405-8440
Relation: http://www.sciencedirect.com/science/article/pii/S2405844024110353; https://doaj.org/toc/2405-8440
DOI: 10.1016/j.heliyon.2024.e35004
Access URL: https://doaj.org/article/de061308d1f14e73942034bce51dff96
Accession Number: edsdoj.061308d1f14e73942034bce51dff96
Database: Directory of Open Access Journals
More Details
ISSN:24058440
DOI:10.1016/j.heliyon.2024.e35004
Published in:Heliyon
Language:English