ArticleCanadian journal of gastroenterology & hepatology2022
Construction of a Prognostic Model Based on Cuproptosis-Related lncRNA Signatures in Pancreatic Cancer.
Article in Canadian journal of gastroenterology & hepatology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- LINC01963 promotes pancreatic ductal adenocarcinoma proliferation via METTL3/IGF2BP2 axis-mediated m⁶A modification of c-Myc.Journal of experimental & clinical cancer research : CR · 2026Article
- Epigenetic modification of cuproptosis by non-coding RNAs in cancer drug resistance.Molecular cancer · 2025Review
- lncRNAs as prognostic markers and therapeutic targets in cuproptosis-mediated cancer.Clinical and experimental medicine · 2024Review
- Article
- Construction of an oxidative stress-related lncRNAs signature to predict prognosis and the immune response in gastric cancer.Scientific reports · 2023Article
- Expression Profiles of Cuproptosis-Related Genes Determine Distinct Subtypes of Pancreatic Ductal Adenocarcinoma.Current oncology (Toronto, Ont.) · 2023Article
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Authors and funding
4 authors.
Funding
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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.
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