ArticleComputational and structural biotechnology journal2022
Identification of key miRNAs in prostate cancer progression based on miRNA-mRNA network construction.
Article in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Multi-Omics Analysis of Primary Prostate Cancer Datasets Reveals Novel Biomarkers.Biochemical genetics · 2025Pooled it
- Article
- Integrative analysis of urinary microRNAs for prostate cancer detection: A proof-of-concept study.Translational oncology · 2026Article
- In silico analysis of prognostic and diagnostic significance of target genes from prostate cancer cell lines derived exomicroRNAs.Cancer cell international · 2023Article
- Article
- A Novel Strategy for Identifying NSCLC MicroRNA Biomarkers and Their Mechanism Analysis Based on a Brand-New CeRNA-Hub-FFL Network.International journal of molecular sciences · 2022Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prostate cancer (PC) is one of the major male cancers. Differential diagnosis of PC is indispensable for the individual therapy, i.e., Gleason score (GS) that describes the grade of cancer can be used to choose the appropriate therapy. However, the current techniques for PC diagnosis and prognosis are not always effective. To identify potential markers that could be used for differential diagnosis of PC, we analyzed miRNA-mRNA interactions and we build specific networks for PC onset and progression. Key differentially expressed miRNAs for each GS were selected by calculating three parameters of network topology measures: the number of their single regulated mRNAs (NSR), the number of target genes (NTG) and NSR/NTG. miRNAs that obtained a high statistically significant value of these three parameters were chosen as potential biomarkers for computational validation and pathway analysis. 20 miRNAs were identified as key candidates for PC. 8 out of 20 miRNAs (
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