Affiliations: [a] Department of Urology, Affiliated Hospital of Guilin Medical College Guilin, Guangxi, China | [b] Centre for Genomic and Personalized Medicine Guangxi Medical University, Nanning, Guangxi, China | [c] Department of Health Management, The People’s Hospital of Guangxi Zhuang Autonomous Region and Research Center of Health Management, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China
Correspondence:
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Corresponding author: Yan Qin, Department of Health Management, The People’s Hospital of Guangxi Zhuang Autonomous Region and Research Center of Health Management, Guangxi Academy of Medical Sciences, Nanning, Guangxi 530021, China. E-mail: [email protected].
Abstract: INTRODUCTION: Ferroptosis is a recently discovered type of programmed cell death that plays a crucial role in tumor occurrence and progression. However, no prognostic model has been established yet for clear cell renal cell carcinoma (ccRCC) using ferroptosis-related long non-coding RNAs (lncRNAs). METHODS: In the present study, lncRNA expression profiles, sex, age, TMN stage, and other clinical data of ccRCC samples were extracted from The Cancer Genome Atlas database. In addition, ferroptosis-related lncRNAs were identified using co-expression analysis, and the risk model was established using Cox regression and least absolute shrinkage and selection operator regression analyses. Log-rank test and Kaplan-Meier analysis were performed to evaluate the predictive accuracy of the risk model for the overall survival (OS) of patients with ccRCC. Moreover, the functional enrichment of ferroptosis-related lncRNAs was performed and visualized using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. RESULTS: Eight prognostic ferroptosis-related lncRNAs were identified, such as LINC01615, AC026401.3, LINC00944, AL590094.1, DLGAP1-AS2, AC016773.1, AC147651.1, and AP000439.2, making up the ferroptosis-related lncRNA risk model. The risk model effectively divided patients with ccRCC into high- and low-risk groups, and their survival time was calculated. The high-risk group showed significantly shorter OS compared to the low-risk group. The nomogram to predict the survival rate of the patients revealed that the risk score was the most critical factor affecting OS in patients with ccRCC. The ferroptosis-related lncRNA risk model was an independent predictor of prognostic risk assessment in patients with ccRCC. CONCLUSION: The ferroptosis-related lncRNAs risk model and genomic clinicopathological nomogram have the potential to accurately predict the prognosis of patients with ccRCC and could serve as potential therapeutic targets in the future.
