4.6 Article

A Robust Prognostic Gene Signature Based on eRNAs-Driven Genes in Prostate Cancer

期刊

FRONTIERS IN GENETICS
卷 12, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2021.676845

关键词

prostate cancer; enhancer RNA; prognostic gene signature; risk score model; drug sensitivity

资金

  1. National Natural Science Foundation of China [81800668]
  2. Natural Science Foundation of Shanxi province [201801D221276]

向作者/读者索取更多资源

This study identified a prognostic gene signature in prostate cancer by screening eRNAs and eRNA-driven genes from the TCGA database, establishing a risk score model, and validating it in three independent cohorts. Significant differences in drug sensitivity between high- and low-risk groups were found, providing new insights into prognosis and treatment options for patients with 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 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.

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