Cancer Manag Res. 2026 Jun 23;18:604901. doi: 10.2147/CMAR.S604901. eCollection 2026.
ABSTRACT
PURPOSE: Prostate-specific antigen (PSA), a common screening tool for prostate cancer (PCa), has a high false-positive rate and is largely suboptimal. PSA is also weakly validated in men of African ancestry (moAA), who disproportionately bear the disease burden, necessitating investigation into its widespread use. Previously, we found that plasmacytoma variant translocation 1 (PVT1) exons 4A, 4B, and 9 are overexpressed in PCa tissues. Here, we report on the first serum-based evaluation of these exons to determine their utility in improving detection and risk stratification of PCa.
PATIENTS AND METHODS: Total RNA was extracted from serum samples obtained retrospectively from 144 multiracial men with elevated PSA who underwent prostate biopsy. Likelihood ratio test was used to evaluate the potential benefit of utilizing these alone or in combination with PSA. Regression analysis was used to evaluate the association of individual biomarkers with the odds of PCa and for evaluating endpoint predictions. Model generalizability was assessed using cross-validation and area under the receiver operating characteristic curve (ROC-AUC). All statistical tests were performed at a 5% level of significance using the Sklearn library in Python.
RESULTS: Our results indicate that combining PSA with PVT1 exon 4A or 9 improves PCa risk stratification in the general population, increasing AUC from 0.72 to 0.75 as well as PCa detection, increasing specificity from 0.41 to 0.59. Within moAA, combining PSA with PVT1 exon 4A improves PCa detection substantially, increasing AUC from 0.44 to 0.67. Remarkably, PVT1 exon 4A alone achieves an AUC of 0.79.
CONCLUSION: Our study provides preliminary exploratory evidence to support PVT1 exon 4A and PVT1 exon 9 as promising PCa risk biomarkers that can reduce disparity in PCa detection and management. Further validation in larger patient cohorts will be necessary to establish the clinical utility of these novel biomarkers.
PMID:42376599 | PMC:PMC13310659 | DOI:10.2147/CMAR.S604901
