ArticleBiomedicines2024
Differential Protein-Coding Gene Expression Profile in Patients with Prostate Cancer.
Article in Biomedicines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Article
- Non-Coding RNA Biomarkers in Prostate Cancer: Evidence Mapping and In Silico Characterization.Life (Basel, Switzerland) · 2026Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundProstate cancer is the second most common neoplasm in men, with projections estimating over one million new cases by 2045. Differentially expressed genes can significantly enhance the diagnosis, treatment, monitoring, and prognosis of this disease. PURPOSE: to systematically review and analyze validated differentially expressed mRNAs in prostate cancer patients to propose a robust molecular profile for clinical diagnostics.
methodsA systematic review was conducted following PRISMA guidelines, searching literature databases for mRNAs with validated differential expression in adult prostate cancer patients. Identified mRNAs were analyzed using STRING, Cytoscape, and DrugBank to explore protein-protein interactions and potential drug targets.
resultsA total of 5003 participants from Europe, Asia, America, and Oceania were included, and 144 mRNAs (
conclusionBased on our comprehensive in silico analysis of validated differentially expressed mRNAs, we propose a molecular profile of twenty-five mRNAs with significant potential for clinical diagnosis of prostate cancer. These findings offer a valuable foundation for developing precision oncology strategies to improve patient outcomes.
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