ReviewDiscover oncology2026
Integrative advances in biomarker-driven prostate cancer management from genomic discovery to precision oncology.
Review in Discover oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prostate cancer (PCa) is the second most common malignancy in men worldwide, with rising mortality linked to late-stage diagnoses. While current diagnostic strategies rely heavily on biomarker detection, their limitations highlight the need for comprehensive and integrative biomarker discovery. This review consolidates recent advances in PCa biomarkers, encompassing genetic, proteomic, liquid biopsy, and imaging-based approaches. Genetic mutations inform disease prognosis and therapy selection, while proteomic biomarkers elucidate molecular mechanisms and therapeutic targets. Blood- and urine-based biomarkers, including exosome-derived markers, circulating tumor DNA (ctDNA), PCA3, and SelectMDx, enable minimally invasive risk stratification. Artificial intelligence-assisted analysis of multiparametric MRI and PSMA PET/CT has been explored to support lesion detection and staging, although most AI-based tools remain investigational. Integrating these biomarker-driven strategies into clinical workflows supports precision oncology and improves patient outcomes. Despite challenges in assay standardization, validation, cost, and ethical implementation, the convergence of genomics, liquid biopsy, and AI technologies marks a transformative step toward personalized prostate cancer management. To distinguish clinically validated tools from emerging candidates, biomarkers are discussed according to their level of evidence and clinical readiness.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.