Construction of a prognostic model for ovarian cancer based on a comprehensive bioinformatics analysis of cuproptosis-associated long non-coding RNA signatures
Rujun Chen,
Yating Huang,
Ke Sun,
Fuyun Dong,
Xiaoqin Wang,
Junhua Guan,
Lina Yang,
He Fei
Affiliations
Rujun Chen
Department of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China
Yating Huang
Department of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China
Ke Sun
Department of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China
Fuyun Dong
Department of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China
Xiaoqin Wang
Department of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China
Junhua Guan
Department of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China
Lina Yang
Department of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China; Central Laboratory, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China; Corresponding author. Department of Obstetrics and Gynecology & Central laboratory, Shanghai Fifth People's Hospital, Fudan University, No.801 Heqing Road, Minhang District, Shanghai, 200240, PR China.
He Fei
Department of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China; Corresponding author. Department of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, No.801 Heqing Road, Minhang District, Shanghai, 200240, PR China.
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.
