Blood DNA Test Predicts Who Benefits Most From Lutetium-177 Prostate Cancer Therapy
A ctDNA analysis of the TheraP trial identifies genomic biomarkers that predict response to Lu-177-PSMA-617 in metastatic prostate cancer.
Summary
Researchers analyzed circulating tumor DNA from 180 men with metastatic castration-resistant prostate cancer enrolled in the randomized TheraP trial comparing lutetium-177-PSMA-617 to cabazitaxel chemotherapy. They found that patients with low levels of ctDNA in the blood before treatment had dramatically better responses to Lu-177-PSMA-617, with 100% achieving PSA50 response versus 58% in high-ctDNA patients, and median progression-free survival of 14.7 versus 6.0 months. Certain gene mutations also mattered: PTEN alterations worsened cabazitaxel outcomes, while ATM defects were linked to favorable Lu-177 responses. Importantly, no single gene change clearly explained why tumors eventually resisted either treatment.
Detailed Summary
Lutetium-177-PSMA-617 (Lu-177) has become a standard treatment for metastatic castration-resistant prostate cancer (mCRPC), yet clinicians currently lack reliable genomic tools to predict which patients will benefit most. This gap in precision oncology motivated a detailed biomarker analysis nested within the prospective TheraP trial.
The study examined 290 serial plasma cell-free DNA samples from 180 molecular imaging-selected mCRPC patients randomized to Lu-177-PSMA-617 (n=97) or cabazitaxel chemotherapy (n=83). Researchers profiled prostate cancer driver genes before and after treatment to identify predictive and resistance-associated alterations. Primary endpoint was PSA50 biochemical response; secondary endpoints included progression-free survival and overall survival.
The standout finding was that a low pretreatment ctDNA fraction powerfully predicted Lu-177 benefit. Patients with low ctDNA achieved 100% PSA50 response versus 58% in those with high ctDNA, and their median PFS was 14.7 months compared to just 6.0 months — a hazard ratio of 0.12. Critically, this predictive value was independent of PSMA-PET imaging parameters, the current standard selection tool. However, this ctDNA advantage did not translate into improved overall survival.
Gene-level analysis revealed that deleterious PTEN alterations worsened outcomes on cabazitaxel for both PFS and OS, while ATM defects appeared in patients with favorable Lu-177 responses. Serial ctDNA sampling at progression showed population-level genomic shifts but no dominant single-gene mechanism driving acquired resistance to either therapy, including no clear role for FOLH1 (the PSMA gene).
These findings nominate ctDNA fraction and specific genomic alterations as actionable biomarkers for treatment selection in mCRPC. The analytical framework developed here could enhance precision management for Lu-177 and future PSMA-targeted therapies, though prospective validation is needed before clinical implementation.
Key Findings
- Low pretreatment ctDNA fraction predicted 100% PSA50 response vs 58% on Lu-177-PSMA-617 (P=0.0067).
- Low ctDNA patients on Lu-177 had median PFS of 14.7 vs 6.0 months (HR 0.12), independent of PSMA-PET.
- PTEN alterations were associated with worse PFS and OS on cabazitaxel chemotherapy.
- ATM gene defects correlated with favorable outcomes in select Lu-177-treated patients.
- No dominant single-gene mechanism explained acquired resistance to Lu-177 or cabazitaxel at progression.
Methodology
Post-hoc biomarker analysis of the randomized phase 2 TheraP trial (NCT03392428) using 290 serial plasma cell-free DNA samples from 180 PSMA-PET-selected mCRPC patients. Prostate cancer driver genes were profiled at pretreatment and progression timepoints to assess predictive and resistance biomarkers across both treatment arms.
Study Limitations
This is a post-hoc biomarker analysis and not a pre-specified primary endpoint, limiting causal inference. The ctDNA benefit was not reflected in overall survival outcomes, raising questions about its clinical significance. Findings require prospective validation before informing routine treatment selection.
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