A prognostic nomogram based on competing endogenous RNA network for clear‐cell renal cell carcinoma
Abstract Background Clear‐cell renal cell carcinoma (ccRCC) is stubborn to traditional chemotherapy and radiation treatment, which makes its clinical management a major challenge. Recently, we have made efforts in understanding the etiology of ccRCC. Increasing evidence revealed that the competing e...
Main Authors: | , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-08-01
|
Series: | Cancer Medicine |
Subjects: | |
Online Access: | https://doi.org/10.1002/cam4.4109 |
id |
doaj-a388baaa22134cd191eaa4245f093f29 |
---|---|
record_format |
Article |
spelling |
doaj-a388baaa22134cd191eaa4245f093f292021-08-16T11:21:36ZengWileyCancer Medicine2045-76342021-08-0110165499551210.1002/cam4.4109A prognostic nomogram based on competing endogenous RNA network for clear‐cell renal cell carcinomaYun Peng0Shangrong Wu1Zihan Xu2Dingkun Hou3Nan Li4Zheyu Zhang5Lili Wang6Haitao Wang7Tianjin Institute of UrologyThe 2nd Hospital of Tianjin Medical University Tianjin ChinaTianjin Institute of UrologyThe 2nd Hospital of Tianjin Medical University Tianjin ChinaTianjin Institute of UrologyThe 2nd Hospital of Tianjin Medical University Tianjin ChinaTianjin Institute of UrologyThe 2nd Hospital of Tianjin Medical University Tianjin ChinaTianjin Institute of UrologyThe 2nd Hospital of Tianjin Medical University Tianjin ChinaTianjin Institute of UrologyThe 2nd Hospital of Tianjin Medical University Tianjin ChinaDepartment of Oncology Tianjin Medical University Second Hospital Hexi, Tianjin ChinaDepartment of Oncology Tianjin Medical University Second Hospital Hexi, Tianjin ChinaAbstract Background Clear‐cell renal cell carcinoma (ccRCC) is stubborn to traditional chemotherapy and radiation treatment, which makes its clinical management a major challenge. Recently, we have made efforts in understanding the etiology of ccRCC. Increasing evidence revealed that the competing endogenous RNA (ceRNA) was involved in the development of varied tumors. However, a comprehensive analysis of the prognostic model based on lncRNA‐miRNA‐mRNA ceRNA regulatory network of ccRCC with large‐scale sample size and RNA‐sequencing expression data is still limited. Methods RNA‐sequencing expression data were taken out from GTEx database and TCGA database, a total of 354 samples with ccRCC and 157 normal controlled samples were included in our study. The ccRCC‐specific genes were obtained by WGCNA and differential expression analysis. Following, the communication of mRNAs and lncRNAs with targeted miRNAs were predicted by MiRcode, starBase, miRTarBase, and TargetScan. A gene signature of eight genes was further constructed by univariate Cox regression, Lasso methods, and multivariate Cox regression analysis. Results A total of 2191 mRNAs and 1377 lncRNAs was identified, and a dysregulated ceRNA network for ccRCC was established using 7 mRNAs, 363 lncRNAs, and 3 miRNAs. Further, a gene signature including eight genes based on this ceRNA was determined followed by the development of a nomogram predicting 1‐, 3‐, and 5‐year survival probability for ccRCC. Conclusion It could contribute to a better understanding of ccRCC tumorigenesis mechanism and guide clinicians to make a more accurate treatment decision.https://doi.org/10.1002/cam4.4109competing endogenous RNAgene signaturenomogramsrenal cell carcinoma |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yun Peng Shangrong Wu Zihan Xu Dingkun Hou Nan Li Zheyu Zhang Lili Wang Haitao Wang |
spellingShingle |
Yun Peng Shangrong Wu Zihan Xu Dingkun Hou Nan Li Zheyu Zhang Lili Wang Haitao Wang A prognostic nomogram based on competing endogenous RNA network for clear‐cell renal cell carcinoma Cancer Medicine competing endogenous RNA gene signature nomograms renal cell carcinoma |
author_facet |
Yun Peng Shangrong Wu Zihan Xu Dingkun Hou Nan Li Zheyu Zhang Lili Wang Haitao Wang |
author_sort |
Yun Peng |
title |
A prognostic nomogram based on competing endogenous RNA network for clear‐cell renal cell carcinoma |
title_short |
A prognostic nomogram based on competing endogenous RNA network for clear‐cell renal cell carcinoma |
title_full |
A prognostic nomogram based on competing endogenous RNA network for clear‐cell renal cell carcinoma |
title_fullStr |
A prognostic nomogram based on competing endogenous RNA network for clear‐cell renal cell carcinoma |
title_full_unstemmed |
A prognostic nomogram based on competing endogenous RNA network for clear‐cell renal cell carcinoma |
title_sort |
prognostic nomogram based on competing endogenous rna network for clear‐cell renal cell carcinoma |
publisher |
Wiley |
series |
Cancer Medicine |
issn |
2045-7634 |
publishDate |
2021-08-01 |
description |
Abstract Background Clear‐cell renal cell carcinoma (ccRCC) is stubborn to traditional chemotherapy and radiation treatment, which makes its clinical management a major challenge. Recently, we have made efforts in understanding the etiology of ccRCC. Increasing evidence revealed that the competing endogenous RNA (ceRNA) was involved in the development of varied tumors. However, a comprehensive analysis of the prognostic model based on lncRNA‐miRNA‐mRNA ceRNA regulatory network of ccRCC with large‐scale sample size and RNA‐sequencing expression data is still limited. Methods RNA‐sequencing expression data were taken out from GTEx database and TCGA database, a total of 354 samples with ccRCC and 157 normal controlled samples were included in our study. The ccRCC‐specific genes were obtained by WGCNA and differential expression analysis. Following, the communication of mRNAs and lncRNAs with targeted miRNAs were predicted by MiRcode, starBase, miRTarBase, and TargetScan. A gene signature of eight genes was further constructed by univariate Cox regression, Lasso methods, and multivariate Cox regression analysis. Results A total of 2191 mRNAs and 1377 lncRNAs was identified, and a dysregulated ceRNA network for ccRCC was established using 7 mRNAs, 363 lncRNAs, and 3 miRNAs. Further, a gene signature including eight genes based on this ceRNA was determined followed by the development of a nomogram predicting 1‐, 3‐, and 5‐year survival probability for ccRCC. Conclusion It could contribute to a better understanding of ccRCC tumorigenesis mechanism and guide clinicians to make a more accurate treatment decision. |
topic |
competing endogenous RNA gene signature nomograms renal cell carcinoma |
url |
https://doi.org/10.1002/cam4.4109 |
work_keys_str_mv |
AT yunpeng aprognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT shangrongwu aprognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT zihanxu aprognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT dingkunhou aprognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT nanli aprognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT zheyuzhang aprognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT liliwang aprognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT haitaowang aprognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT yunpeng prognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT shangrongwu prognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT zihanxu prognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT dingkunhou prognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT nanli prognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT zheyuzhang prognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT liliwang prognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma AT haitaowang prognosticnomogrambasedoncompetingendogenousrnanetworkforclearcellrenalcellcarcinoma |
_version_ |
1721205793075757056 |