Multi-gene risk-score for prediction of clinical outcomes in treatment-naïve metastatic castrate resistant prostate cancer.

IF 3.4 Q2 ONCOLOGY JNCI Cancer Spectrum Pub Date : 2025-02-28 DOI:10.1093/jncics/pkaf025

Muhammad Zaki Hidayatullah Fadlullah, David Nix, Cameron Herberts, Corinne Maurice-Dror, Alexander W Wyatt, Bogdana Schmidt, Brayden Fairbourn, Aik-Choon Tan, Liang Wang, Manish Kohli

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Abstract

Background: To determine the performance of a multi-gene copy number variation (MG-CNV) risk score in metastatic tissue and plasma biospecimens from treatment-naïve metastatic castrate-resistant prostate cancer (mCRPC) patients for prediction of clinical outcomes.

Methods: mCRPC tissue and plasma cell-free DNA (cfDNA) biospecimen sequencing results obtained from publicly accessed cohorts in dbGaP, cBioPortal, and an institutional mCRPC cohort were used to develop a MG-CNV risk score derived from gains in AR, MYC, COL22A1, PIK3CA, PIK3CB, NOTCH1 and losses in TMPRSS2, NCOR1, ZBTB16, TP53, NKX3-1 in independent cohorts for determining overall survival (OS), progression free survival (PFS) to first-line Androgen Receptor Pathway Inhibitors (ARPIs). The range of the risk scores for each cohort was dichotomized into "high-risk" group and "low-risk" groups and association with OS/PFS determined. Univariate and multi-variate Cox Proportional Hazard Regressions were applied for survival analyses (P < .05 for statistical significance).

Results: Of 1,137 metastatic tissue-plasma biospecimens across all cohorts, 699/1137 were treatment-naive mCRPC (235/699 metastatic tissue; 464/699 plasma-cfDNA) and 311/1137 were matched tissue-cfDNA pairs. In multivariate analysis the MG-CNV risk score derived from metastatic tissue or in cfDNA was statistically significantly associated with OS with high score associated with short survival, Hazard Ratio (HR) 2.65 (CI: 1.99- 3.51; P = 1.35-11) and shorter PFS to ARPIs (median PFS of 7.8 months) compared to 14 months in patients with low-risk score.

Conclusions: A molecular risk score in treatment-naïve mCRPC state obtained either in metastatic tissue or cfDNA predicts clinical survival outcomes and offers a tumor biology-based tool to design biomarker -based enrichment clinical trials.

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