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Identification of a three-m6A related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent malignancies worldwide, N6-methyladenosine (m6A) has been shown to play important roles in regulating gene expression and phenotypes in both health and disease. Here, our purpose is to construct a m6A-regulrator-based r...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085294/ https://www.ncbi.nlm.nih.gov/pubmed/32219036 http://dx.doi.org/10.7717/peerj.8827 |
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author | Zhao, Yiqiao Tao, Zijia Chen, Xiaonan |
author_facet | Zhao, Yiqiao Tao, Zijia Chen, Xiaonan |
author_sort | Zhao, Yiqiao |
collection | PubMed |
description | BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent malignancies worldwide, N6-methyladenosine (m6A) has been shown to play important roles in regulating gene expression and phenotypes in both health and disease. Here, our purpose is to construct a m6A-regulrator-based risk score (RS) for prediction of the prognosis of ccRCC. METHODS: We used clinical and expression data of m6A related genes from The Cancer Genome Atlas (TCGA) dataset and the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis to develop an RS to predict survival of patients with ccRCC, and analyzed correlations between RS and other clinical indicators such as age, grade and stage. Validation of this RS was then engaged in another cohort, E-MTAB-1980 from the ArrayExpress dataset. Finally, we used quantitative real-time PCR to analyze the expression profile of genes consists of the RS. RESULTS: A three-gene RS including METTL3, METTL14 and HNRNPA2B1 which can predict overall survival (OS) of ccRCC patients from TCGA. After applying this RS into the validation cohort from Arrayexpress, we found that it successfully reproduced the result; furthermore, the results of PCR validation were in line with our analysis. CONCLUSION: To sum up, our study has identified an RS composed of m6A related genes that may predict the prognosis of ccRCC patients, which might be helpful for future therapeutic strategies. Our results call for further experimental studies for validations. |
format | Online Article Text |
id | pubmed-7085294 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-70852942020-03-26 Identification of a three-m6A related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma Zhao, Yiqiao Tao, Zijia Chen, Xiaonan PeerJ Bioinformatics BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent malignancies worldwide, N6-methyladenosine (m6A) has been shown to play important roles in regulating gene expression and phenotypes in both health and disease. Here, our purpose is to construct a m6A-regulrator-based risk score (RS) for prediction of the prognosis of ccRCC. METHODS: We used clinical and expression data of m6A related genes from The Cancer Genome Atlas (TCGA) dataset and the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis to develop an RS to predict survival of patients with ccRCC, and analyzed correlations between RS and other clinical indicators such as age, grade and stage. Validation of this RS was then engaged in another cohort, E-MTAB-1980 from the ArrayExpress dataset. Finally, we used quantitative real-time PCR to analyze the expression profile of genes consists of the RS. RESULTS: A three-gene RS including METTL3, METTL14 and HNRNPA2B1 which can predict overall survival (OS) of ccRCC patients from TCGA. After applying this RS into the validation cohort from Arrayexpress, we found that it successfully reproduced the result; furthermore, the results of PCR validation were in line with our analysis. CONCLUSION: To sum up, our study has identified an RS composed of m6A related genes that may predict the prognosis of ccRCC patients, which might be helpful for future therapeutic strategies. Our results call for further experimental studies for validations. PeerJ Inc. 2020-03-18 /pmc/articles/PMC7085294/ /pubmed/32219036 http://dx.doi.org/10.7717/peerj.8827 Text en © 2020 Zhao et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Zhao, Yiqiao Tao, Zijia Chen, Xiaonan Identification of a three-m6A related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma |
title | Identification of a three-m6A related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma |
title_full | Identification of a three-m6A related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma |
title_fullStr | Identification of a three-m6A related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma |
title_full_unstemmed | Identification of a three-m6A related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma |
title_short | Identification of a three-m6A related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma |
title_sort | identification of a three-m6a related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085294/ https://www.ncbi.nlm.nih.gov/pubmed/32219036 http://dx.doi.org/10.7717/peerj.8827 |
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