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Genomic Biomarker for Prostate Cancer Focal Therapy: Post Hoc Assessment of a Phase II Clinical Trial

  • 0Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA.
Jco Precision Oncology +

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September 17, 2025

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September 17, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

A high Decipher genomic classifier (GC) score predicts treatment failure in prostate cancer (PCa) patients undergoing focal therapy. This biomarker can help personalize PCa treatment and improve outcomes.

Area Of Science

  • Oncology
  • Genomics
  • Urology

Background

  • Prostate cancer (PCa) focal therapy offers a less invasive treatment option.
  • Predicting treatment success after focal therapy remains a challenge.
  • A reliable biomarker is needed to guide treatment decisions and patient selection.

Purpose Of The Study

  • To evaluate the association between the Decipher genomic classifier (GC) score and treatment failure after focal therapy for PCa.
  • To determine if a high GC score can predict recurrence in patients treated with hemigland cryoablation.

Main Methods

  • Post hoc analysis of a phase II trial involving 108 patients with unilateral grade group 2-4 PCa.
  • Transcriptomic profiling of pretreatment biopsy tissue to generate GC scores.
  • Assessing the correlation between GC-low (<0.45) vs. GC-high (≥0.45) and in-field recurrence (GG ≥2) at 6 months post-treatment.

Main Results

  • Patients with a high GC score (n=37) had a 46% treatment failure rate, compared to 21% in the low GC score group (n=71).
  • A high GC score was independently associated with treatment failure (OR, 2.61; P=.04).
  • Significant differences in recurrence rates were also observed at 18 months (76% vs. 44%).

Conclusions

  • A high Decipher genomic classifier score (≥0.45) is independently associated with treatment failure in prostate cancer patients undergoing focal therapy.
  • The GC score, derived from diagnostic biopsy, can serve as a predictive biomarker for focal therapy outcomes.
  • This finding supports the use of genomic classifiers to personalize PCa management and improve treatment efficacy.