An immune-related lncRNA prognostic model in papillary renal cell carcinoma: A lncRNA expression analysis.

Autor: Chen SH; Departments of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China., Lin F; Departments of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China., Zhu JM; Departments of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China., Ke ZB; Departments of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China., Lin TT; Departments of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China., Lin YZ; Departments of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China., Xue XY; Departments of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China., Wei Y; Departments of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China., Zheng QS; Departments of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China., Chen YH; Departments of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China. Electronic address: chenyehui@fjmu.edu.cn., Xu N; Departments of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China. Electronic address: drxun@fjmu.edu.cn.
Jazyk: angličtina
Zdroj: Genomics [Genomics] 2021 Jan; Vol. 113 (1 Pt 2), pp. 531-540. Date of Electronic Publication: 2020 Sep 24.
DOI: 10.1016/j.ygeno.2020.09.046
Abstrakt: Objective: To screen several immune-related long non-coding RNAs (lncRNAs) and construct a prognostic model for papillary renal cell carcinoma (pRCC).
Methods: Transcriptome-sequencing data of pRCC was downloaded and a prognostic model was constructed. Time-dependent receiver operating characteristic (ROC) curve was plotted and the area under curve (AUC) was calculated. We conducted quantitative reverse transcription polymerase chain reaction (RT-PCR) to verify the model. The gene set enrichment analysis (GSEA) was used to show the connection of our model with immune pathways.
Result: We identified four lncRNAs to constructed the model. The model was significantly associated with the survival time and survival state. The expression-levels of the four lncRNAs were measured and the prognosis of high-risk patients was significantly worse. The two immune-gene sets had an active performance in the high-risk patients.
Conclusion: We constructed a prognostic model in pRCC which provided more reference for treatment.
(Copyright © 2020. Published by Elsevier Inc.)
Databáze: MEDLINE
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