TEST:

Prolaris®

26 clinical impact evidence studies and four health economic evaluation studies were included. Most clinical studies indicated that genomic tests reclassified patients' risk predictions into both lower- and higher-risk groups. The reclassification outcomes influenced patients' treatment decisions between active surveillance and radical treatment. The prognostic value of the genomic tests was validated in terms of biopsy upgrade, metastasis and death. The limited number of health economic studies reported that the Oncotype DX Prostate Score and ProMark were cost-effective, while the Prolaris was cost-saving in the US but not in Canada. The evaluation of the Decipher Genomic Classifier at the time of diagnosis was not available. More long-term clinical evidence is needed, as are updated health economic evaluations, to determine the cost-effectiveness of integrating genomic risk stratification into prostate cancer treatment decision-making in clinical practice.

"Myriad Genetics...will present new data at the 2026 ASCO-GU conference supporting its Precise MRDTM (Molecular Residual Disease) Test, Prolaris® Prostate Cancer Prognostic Test and MyRisk® Hereditary Cancer Tests. These data highlight Myriad’s expanding role across the cancer care continuum, including ultra-sensitive molecular residual disease detection, prognostic stratification, and inherited cancer risk assessment."

P=N/A, N=140, Active, not recruiting, British Columbia Cancer Agency | Trial completion date: Dec 2026 --> Oct 2034

P=N/A, N=900, Recruiting, University of Michigan Rogel Cancer Center | Trial completion date: Dec 2025 --> Apr 2031 | Trial primary completion date: Dec 2025 --> Apr 2028

This narrative review demonstrates that although PSA remains the mainstay of prostate cancer diagnosis, emerging molecular and genomic biomarkers are enhancing diagnostic specificity, refining risk stratification, and enabling more personalized patient care. The integration of routinely used and novel biomarkers can improve early detection, optimize treatment decisions, and ultimately improve outcomes of prostate cancer patients.

This study is among the first to show that histopathology-based AI algorithms applied to small samples of tumor tissue can predict the risk of lethal PCa. These algorithms perform comparably to commonly used genomic classifiers, and their predictive performance is enhanced when combined with clinicopathologic variables.

Current evidence supports the multidisciplinary integration of these biomarkers to overcome the limitations of PSA, improve biopsy decision-making, better distinguish indolent from aggressive tumors, and optimize therapeutic strategies. Finally, future research directions aimed at validating and incorporating emerging biomarkers into clinical practice are outlined, with the goal of improving outcomes in patients with localized prostate cancer.

We show contemporary, real-world GC utilization trends, costs, and associations with treatment patterns. Prospective trials are ongoing to validate GC-informed treatment, but US uptake has expanded and management is associated with the use and type of GC.

P=N/A, N=900, Recruiting, University of Michigan Rogel Cancer Center | Trial completion date: Jul 2025 --> Dec 2025 | Trial primary completion date: Jul 2025 --> Dec 2025

Methionine deprivation through MEGL-targeted gene therapy may be a viable option for inducing cancer cell death compared to unrestricted levels of methionine.

There is no consistent association between MRI-visible cancer and Prolaris risk profile. When utilizing multigene molecular testing in prostate cancer, each individual patient must be evaluated to decide the appropriate level of care.

Correlation between 22-gene GC and either GPS-derived or CCP-derived signatures is minimal to moderate. These tests are not interchangeable, and their use should be guided by the specific evidence supporting each signature.