ArticlePloS one2025
Identification and validation of stage-specific microRNAs and target genes for prostate cancer: Utilizing bioinformatics tools for diagnostic marker discovery.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07255729 (Machine Learning-Based Exosomal microRNA Signature for Preoperative Staging and Chemotherapy Eligibility in Colon Cancer), which is not on this map. Not yet cited in PubMed.
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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
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Machine Learning-Based Exosomal microRNA Signature for Preoperative Staging and Chemotherapy Eligibility in Colon Cancer
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Authors and funding
8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Given the urgent need for more specific, sensitive, and non-invasive markers for prostate cancer screening and differential diagnosis, circulating miRNAs have emerged as valuable candidates. Sixty seven prostate cancer subjects in different stages were included in this study. The participants were categorized into groups based on their pathological characteristics as local, biochemical relapse and metastatic. We retrieved eligible datasets from GEO database to identify stage-specific differentially expressed up/down-regulated genes. Cytohubba, built-in application of Cytoscape software, and Reactome pathway database were applied to select hub genes. To select upstream miRNAs, we utilized the MiRWalk and miRNet online tools. To construct the miRNA-mRNA regulatory networks, we employed rna22. Finally, three miRNAs and five target genes were validated in peripheral blood mononuclear cells of PCa patients compared with benign prostate hyperplasia. PSA level was also measured using ELISA. Our findings revealed the potential role of PRC1 and UBA52 to be used as biomarkers for the metastatic stage, RCC1 for both biochemical relapse, and metastatic subjects. Furthermore, elevated levels of miR-124-3p and downregulation of miR-133a-3p can be introduced as biochemical relapse stage identifier. We also identified the tumor suppressor role of miR-17-5p, which was associated with higher Gleason scores. We propose PRC1, UBA52, RCC1, miR-124-3p and miR133a-3p as stage-specific PCa identifiers.
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