Construction of a Prognostic Model Based on Cuproptosis-Related lncRNA Signatures in Pancreatic Cancer. (11th November 2022)

• Record Type: Journal Article
• Authors: Jiang, Wenkai; Du, Yan; Zhang, Wenlong; Zhou, Wence
• Other Names: Solimando Antonio Giovanni Academic Editor.
• Is Part Of: Canadian journal of gastroenterology & hepatology. Volume 2022(2022)
• Publication Date: 2022-11-11
• Subjects: Digestive organs -- Diseases -- Periodicals; Gastroenterology -- Periodicals; Digestive organs -- Diseases; Gastroenterology; Canada; Digestive System Diseases -- Periodicals; Gastroenterology -- Periodicals; Periodicals; Electronic journals; Fulltext; Internet Resources; Periodicals; 616.3
• DOI: 10.1155/2022/4661929
• Languages: English
• ISSNs: 2291-2789

Abstract

Abstract : Aim . The aim of this study is to identify cuproptosis-related lncRNAs and construct a prognostic model for pancreatic cancer patients for clinical use. Methods . The expression profile of lncRNAs was downloaded from The Cancer Genome Atlas database, and cuproptosis-related lncRNAs were identified. The prognostic cuproptosis-related lncRNAs were obtained and used to establish and validate a prognostic risk score model in pancreatic cancer. Results . In total, 181 cuproptosis-related lncRNAs were obtained. The prognostic risk score model was constructed based on five lncRNAs (AC025257.1, TRAM2-AS1, AC091057.1, LINC01963, and MALAT1). Patients were assigned to two groups according to the median risk score. Kaplan–Meier survival curves showed that the difference in the prognosis between the high- and low-risk groups was statistically significant. Multivariate Cox analysis showed that our risk score was an independent risk factor for pancreatic cancer patients. Receiver operator characteristic curves revealed that the cuproptosis-related lncRNA model can effectively predict the prognosis of pancreatic cancer. The principal component analysis showed a difference between the high- and low-risk groups intuitively. Functional enrichment analysis showed that different genes were involved in cancer-related pathways in patients in the high- and low-risk groups. Conclusion . The risk model based on five prognostic cuproptosis-related lncRNAs can well predict the prognosis of pancreatic cancer patients. Cuproptosis-related lncRNAs could be potential biomarkers for pancreatic cancer diagnosis and treatment.