Development and validation of a novel ferroptosis‑related lncRNA prognostic signature for pancreatic adenocarcinoma
- Jian Li
- Wenhua Li
- Huaizhi Wang
- Bing Ni
- Yongkang Liu
Affiliations: Department of Pathophysiology, College of High Altitude Military Medicine, Third Military Medical University, Chongqing 400038, P.R. China, Department of Cadre Ward, Air Force Hospital of Western Theater Command, Chengdu, Sichuan 610065, P.R. China, Institute of Hepatopancreatobiliary Surgery, Southwest Hospital, Third Military Medical University, Chongqing 400038, P.R. China, Department of Pathophysiology, College of High Altitude Military Medicine, Third Military Medical University, Chongqing 400038, P.R. China, Department of General Surgery, Air Force Hospital of Western Theater Command, Chengdu, Sichuan 610065, P.R. China
- Published online on: January 18, 2023 https://doi.org/10.3892/mmr.2023.12943
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Long non‑coding RNAs (lncRNAs) serve a pivotal role in the regulation of cancer cell ferroptosis. However, the prognostic value of ferroptosis‑related lncRNAs in pancreatic adenocarcinoma (PAAD) largely remains unclear. We aimed at constructing a lncRNA‑based signature to improve the prognosis prediction of PAAD. In the present study, the transcriptome profiling data and clinical information of patients with PAAD were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Gene Consortium (ICGC) databases. Univariate Cox regression analysis of the TCGA cohort demonstrated that 26 ferroptosis‑related lncRNAs had significant prognostic value for PAAD (all P<0.01). Least absolute shrinkage and selection operator regression and multivariate Cox proportional hazards regression analyses were performed to construct a prognostic ferroptosis‑related lncRNA signature (FRLS) comprising nine ferroptosis‑related lncRNAs. The efficacy of this FRLS was verified in the training (TCGA) and validation (ICGC) cohorts. Based on the risk model, high risk scores were significantly correlated with poor overall survival (OS) (hazard ratio, 1.314; 95% confidence interval, 1.218‑1.418; P<0.001). The receiver operating characteristic curves and principal component analysis further demonstrated the robust prognostic ability of the FRLS. Furthermore, a nomogram with favorable predictive efficacy for the prediction of OS was constructed based on the FRLS and clinical features. Gene set enrichment analysis demonstrated that the genes in the FRLS participated in a number of cancer‑associated immunoregulatory pathways. Importantly, it was demonstrated that immune infiltration and response to cancer immunotherapy differed significantly between the high and low‑risk groups according to the FRLS. In conclusion, the risk signature based on the FRLS has potential for the clinical prediction of prognosis and immunotherapy response in patients with PAAD.