ArticleFrontiers in genetics2021
A Robust Prognostic Gene Signature Based on eRNAs-Driven Genes in Prostate Cancer.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Enhancer RNA in cancer: identification, expression, resources, relationship with immunity, drugs, and prognosis.Briefings in functional genomics · 2025Review
- Identification of an immune-related eRNA prognostic signature for clear cell renal cell carcinoma.Aging · 2024Article
- Atypical MAP kinases - new insights and directions from amoeba.Journal of cell science · 2023Review
- Cancer-associated fibroblast-derived gene signatures predict radiotherapeutic survival in prostate cancer patients.Journal of translational medicine · 2022Article
- Review
- A predictive signature based on enhancer RNA associates with immune infiltration and aids treatment decision in clear cell renal cell carcinoma.Frontiers in oncology · 2022Article
- Gene expression analysis reveals a 5-gene signature for progression-free survival in prostate cancer.Frontiers in oncology · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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
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Registered trials
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