A Robust Prognostic Gene Signature Based on eRNAs-Driven Genes in Prostate Cancer
Prostate cancer (PCa) is the second most common malignancy in men, but its exact pathogenetic mechanisms remain unclear. This study explores the effect of enhancer RNAs (eRNAs) in PCa. Firstly, we screened eRNAs and eRNA -driven genes from The Cancer Genome Atlas (TCGA) database, which are related t...
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Frontiers Media S.A.
2021-06-01
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Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2021.676845/full |
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author | Shuaishuai Fan Zheng Wang Zheng Wang Li Zhao ChenHui Zhao ChenHui Zhao DaJiang Yuan Jingqi Wang |
author_facet | Shuaishuai Fan Zheng Wang Zheng Wang Li Zhao ChenHui Zhao ChenHui Zhao DaJiang Yuan Jingqi Wang |
author_sort | Shuaishuai Fan |
collection | DOAJ |
description | Prostate cancer (PCa) is the second most common malignancy in men, but its exact pathogenetic mechanisms remain unclear. This study explores the effect of enhancer RNAs (eRNAs) in PCa. Firstly, we screened eRNAs and eRNA -driven genes from The Cancer Genome Atlas (TCGA) database, which are related to the disease-free survival (DFS) of PCa patients;. screening methods included bootstrapping, Kaplan–Meier (KM) survival analysis, and Pearson correlation analysis. Then, a risk score model was established using multivariate Cox analysis, and the results were validated in three independent cohorts. Finally, we explored the function of eRNA-driven genes through enrichment analysis and analyzed drug sensitivity on datasets from the Genomics of Drug Sensitivity in Cancer database. We constructed and validated a robust prognostic gene signature involving three eRNA-driven genes namely MAPK15, ZNF467, and MC1R. Moreover, we evaluated the function of eRNA-driven genes associated with tumor microenvironment (TME) and tumor mutational burden (TMB), and identified remarkable differences in drug sensitivity between high- and low-risk groups. This study identified a prognostic gene signature, which provides new insights into the role of eRNAs and eRNA-driven genes while assisting clinicians to determine the prognosis and appropriate treatment options for patients with PCa. |
first_indexed | 2024-12-19T21:42:11Z |
format | Article |
id | doaj.art-b97c819d264d40fdbcd4b90a65dc22f9 |
institution | Directory Open Access Journal |
issn | 1664-8021 |
language | English |
last_indexed | 2024-12-19T21:42:11Z |
publishDate | 2021-06-01 |
publisher | Frontiers Media S.A. |
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series | Frontiers in Genetics |
spelling | doaj.art-b97c819d264d40fdbcd4b90a65dc22f92022-12-21T20:04:38ZengFrontiers Media S.A.Frontiers in Genetics1664-80212021-06-011210.3389/fgene.2021.676845676845A Robust Prognostic Gene Signature Based on eRNAs-Driven Genes in Prostate CancerShuaishuai Fan0Zheng Wang1Zheng Wang2Li Zhao3ChenHui Zhao4ChenHui Zhao5DaJiang Yuan6Jingqi Wang7First Clinical Medical College, Shanxi Medical University, First Hospital of Shanxi Medical University, Taiyuan, ChinaFirst Clinical Medical College, Shanxi Medical University, First Hospital of Shanxi Medical University, Taiyuan, ChinaPeople’s Hospital of Zezhou County, Jincheng, ChinaDepartment of Anesthesia, Shanxi Medical University, Taiyuan, ChinaFirst Clinical Medical College, Shanxi Medical University, First Hospital of Shanxi Medical University, Taiyuan, ChinaThe First People’s Hospital of Jinzhong, Jinzhong, ChinaDepartment of Anesthesia, Shanxi Medical University, Taiyuan, ChinaFirst Clinical Medical College, Shanxi Medical University, First Hospital of Shanxi Medical University, Taiyuan, ChinaProstate cancer (PCa) is the second most common malignancy in men, but its exact pathogenetic mechanisms remain unclear. This study explores the effect of enhancer RNAs (eRNAs) in PCa. Firstly, we screened eRNAs and eRNA -driven genes from The Cancer Genome Atlas (TCGA) database, which are related to the disease-free survival (DFS) of PCa patients;. screening methods included bootstrapping, Kaplan–Meier (KM) survival analysis, and Pearson correlation analysis. Then, a risk score model was established using multivariate Cox analysis, and the results were validated in three independent cohorts. Finally, we explored the function of eRNA-driven genes through enrichment analysis and analyzed drug sensitivity on datasets from the Genomics of Drug Sensitivity in Cancer database. We constructed and validated a robust prognostic gene signature involving three eRNA-driven genes namely MAPK15, ZNF467, and MC1R. Moreover, we evaluated the function of eRNA-driven genes associated with tumor microenvironment (TME) and tumor mutational burden (TMB), and identified remarkable differences in drug sensitivity between high- and low-risk groups. This study identified a prognostic gene signature, which provides new insights into the role of eRNAs and eRNA-driven genes while assisting clinicians to determine the prognosis and appropriate treatment options for patients with PCa.https://www.frontiersin.org/articles/10.3389/fgene.2021.676845/fullprostate cancerenhancer RNAprognostic gene signaturerisk score modeldrug sensitivity |
spellingShingle | Shuaishuai Fan Zheng Wang Zheng Wang Li Zhao ChenHui Zhao ChenHui Zhao DaJiang Yuan Jingqi Wang A Robust Prognostic Gene Signature Based on eRNAs-Driven Genes in Prostate Cancer Frontiers in Genetics prostate cancer enhancer RNA prognostic gene signature risk score model drug sensitivity |
title | A Robust Prognostic Gene Signature Based on eRNAs-Driven Genes in Prostate Cancer |
title_full | A Robust Prognostic Gene Signature Based on eRNAs-Driven Genes in Prostate Cancer |
title_fullStr | A Robust Prognostic Gene Signature Based on eRNAs-Driven Genes in Prostate Cancer |
title_full_unstemmed | A Robust Prognostic Gene Signature Based on eRNAs-Driven Genes in Prostate Cancer |
title_short | A Robust Prognostic Gene Signature Based on eRNAs-Driven Genes in Prostate Cancer |
title_sort | robust prognostic gene signature based on ernas driven genes in prostate cancer |
topic | prostate cancer enhancer RNA prognostic gene signature risk score model drug sensitivity |
url | https://www.frontiersin.org/articles/10.3389/fgene.2021.676845/full |
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