Genome instability-related long non-coding RNA in clear renal cell carcinoma determined using computational biology

Abstract Background There is evidence that long non-coding RNA (lncRNA) is related to genetic stability. However, the complex biological functions of these lncRNAs are unclear. Method TCGA - KIRC lncRNAs expression matrix and somatic mutation information data were obtained from TCGA database. “GSVA”...

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Main Authors: Yutao Wang, Kexin Yan, Linhui Wang, Jianbin Bi
Format: Article
Language:English
Published: BMC 2021-06-01
Series:BMC Cancer
Subjects:
Online Access:https://doi.org/10.1186/s12885-021-08356-9
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spelling doaj-ebc7de330af244fda5a58c8f1328ca0f2021-06-27T11:46:47ZengBMCBMC Cancer1471-24072021-06-0121111310.1186/s12885-021-08356-9Genome instability-related long non-coding RNA in clear renal cell carcinoma determined using computational biologyYutao Wang0Kexin Yan1Linhui Wang2Jianbin Bi3Department of Urology, China Medical University, The First Hospital of China Medical UniversityDepartment of Dermatology, China Medical University, The First Hospital of China Medical UniversityDepartment of Urology, China Medical University, The First Hospital of China Medical UniversityDepartment of Urology, China Medical University, The First Hospital of China Medical UniversityAbstract Background There is evidence that long non-coding RNA (lncRNA) is related to genetic stability. However, the complex biological functions of these lncRNAs are unclear. Method TCGA - KIRC lncRNAs expression matrix and somatic mutation information data were obtained from TCGA database. “GSVA” package was applied to evaluate the genomic related pathway in each samples. GO and KEGG analysis were performed to show the biological function of lncRNAs-mRNAs. “Survival” package was applied to determine the prognostic significance of lncRNAs. Multivariate Cox proportional hazard regression analysis was applied to conduct lncRNA prognosis model. Results In the present study, we applied computational biology to identify genome-related long noncoding RNA and identified 26 novel genomic instability-associated lncRNAs in clear cell renal cell carcinoma. We identified a genome instability-derived six lncRNA-based gene signature that significantly divided clear renal cell samples into high- and low-risk groups. We validated it in test cohorts. To further elucidate the role of the six lncRNAs in the model’s genome stability, we performed a gene set variation analysis (GSVA) on the matrix. We performed Pearson correlation analysis between the GSVA scores of genomic stability-related pathways and lncRNA. It was determined that LINC00460 and LINC01234 could be used as critical factors in this study. They may influence the genome stability of clear cell carcinoma by participating in mediating critical targets in the base excision repair pathway, the DNA replication pathway, homologous recombination, mismatch repair pathway, and the P53 signaling pathway. Conclusion subsections These data suggest that LINC00460 and LINC01234 are crucial for the stability of the clear cell renal cell carcinoma genome.https://doi.org/10.1186/s12885-021-08356-9Genome instabilityLong non-coding RNAComputational biologyGene set variation analysisRisk signature
collection DOAJ
language English
format Article
sources DOAJ
author Yutao Wang
Kexin Yan
Linhui Wang
Jianbin Bi
spellingShingle Yutao Wang
Kexin Yan
Linhui Wang
Jianbin Bi
Genome instability-related long non-coding RNA in clear renal cell carcinoma determined using computational biology
BMC Cancer
Genome instability
Long non-coding RNA
Computational biology
Gene set variation analysis
Risk signature
author_facet Yutao Wang
Kexin Yan
Linhui Wang
Jianbin Bi
author_sort Yutao Wang
title Genome instability-related long non-coding RNA in clear renal cell carcinoma determined using computational biology
title_short Genome instability-related long non-coding RNA in clear renal cell carcinoma determined using computational biology
title_full Genome instability-related long non-coding RNA in clear renal cell carcinoma determined using computational biology
title_fullStr Genome instability-related long non-coding RNA in clear renal cell carcinoma determined using computational biology
title_full_unstemmed Genome instability-related long non-coding RNA in clear renal cell carcinoma determined using computational biology
title_sort genome instability-related long non-coding rna in clear renal cell carcinoma determined using computational biology
publisher BMC
series BMC Cancer
issn 1471-2407
publishDate 2021-06-01
description Abstract Background There is evidence that long non-coding RNA (lncRNA) is related to genetic stability. However, the complex biological functions of these lncRNAs are unclear. Method TCGA - KIRC lncRNAs expression matrix and somatic mutation information data were obtained from TCGA database. “GSVA” package was applied to evaluate the genomic related pathway in each samples. GO and KEGG analysis were performed to show the biological function of lncRNAs-mRNAs. “Survival” package was applied to determine the prognostic significance of lncRNAs. Multivariate Cox proportional hazard regression analysis was applied to conduct lncRNA prognosis model. Results In the present study, we applied computational biology to identify genome-related long noncoding RNA and identified 26 novel genomic instability-associated lncRNAs in clear cell renal cell carcinoma. We identified a genome instability-derived six lncRNA-based gene signature that significantly divided clear renal cell samples into high- and low-risk groups. We validated it in test cohorts. To further elucidate the role of the six lncRNAs in the model’s genome stability, we performed a gene set variation analysis (GSVA) on the matrix. We performed Pearson correlation analysis between the GSVA scores of genomic stability-related pathways and lncRNA. It was determined that LINC00460 and LINC01234 could be used as critical factors in this study. They may influence the genome stability of clear cell carcinoma by participating in mediating critical targets in the base excision repair pathway, the DNA replication pathway, homologous recombination, mismatch repair pathway, and the P53 signaling pathway. Conclusion subsections These data suggest that LINC00460 and LINC01234 are crucial for the stability of the clear cell renal cell carcinoma genome.
topic Genome instability
Long non-coding RNA
Computational biology
Gene set variation analysis
Risk signature
url https://doi.org/10.1186/s12885-021-08356-9
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AT kexinyan genomeinstabilityrelatedlongnoncodingrnainclearrenalcellcarcinomadeterminedusingcomputationalbiology
AT linhuiwang genomeinstabilityrelatedlongnoncodingrnainclearrenalcellcarcinomadeterminedusingcomputationalbiology
AT jianbinbi genomeinstabilityrelatedlongnoncodingrnainclearrenalcellcarcinomadeterminedusingcomputationalbiology
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