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A Risk Signature with Autophagy-Related Long Noncoding RNAs for Predicting the Prognosis of Clear Cell Renal Cell Carcinoma: Based on the TCGA Database and Bioinformatics.

Authors :
Xuan Y
Chen W
Liu K
Gao Y
Zuo S
Wang B
Ma X
Zhang X
Source :
Disease markers [Dis Markers] 2021 May 07; Vol. 2021, pp. 8849977. Date of Electronic Publication: 2021 May 07 (Print Publication: 2021).
Publication Year :
2021

Abstract

Background: Disorders of autophagic processes have been reported to affect the survival outcome of clear cell renal cell carcinoma (ccRCC) patients. The purpose of our study was to identify and validate the candidate prognostic long noncoding RNA signature of autophagy.<br />Methods: Transcriptome profiles were obtained from The Cancer Genome Atlas. The autophagy gene list was obtained from the Human Autophagy Database. Based on coexpression analysis, we obtained a list of autophagy-related lncRNAs (ARlncRNAs). GO enrichment analysis and KEGG pathway analysis were conducted to explore the functional annotation of these ARlncRNAs. Univariate and multivariate Cox regression analyses were conducted to elucidate the correlation between overall survival and the expression level of each ARlncRNAs. We then established a prognostic signature that was a linear combination of the regression coefficients from the multivariate Cox regression model ( β ) multiplied by the expression levels of the respective ARlncRNAs in the training cohort. The predictive performance was tested in the validation cohort. Additionally, the independence of the risk signature was assessed, and the relationship between the risk signature and conventional clinicopathological features was explored.<br />Results: Seven autophagy-related lncRNAs with prognostic value (SNHG3, SNHG17, MELTF-AS1, HOTAIRM1, EPB41L4A-DT, AP003352.1, and AC145423.2) were identified and integrated into a risk signature, dividing patients into low-risk and high-risk groups. The risk signature was independent of conventional clinical characteristics as a prognostic indicator of ccRCC (HR, 1.074, 95% confidence interval: 1.036-1.113, p < 0.001) and was valuable in the prediction of ccRCC progression.<br />Conclusion: Our risk signature has potential prognostic value in ccRCC, and these ARlncRNAs may play a significant role in ccRCC tumor biology.<br />Competing Interests: The authors declared that they have no conflict of interest.<br /> (Copyright © 2021 Yundong Xuan et al.)

Details

Language :
English
ISSN :
1875-8630
Volume :
2021
Database :
MEDLINE
Journal :
Disease markers
Publication Type :
Academic Journal
Accession number :
34040677
Full Text :
https://doi.org/10.1155/2021/8849977