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This study explored the relationship between PSMA expression on CTCs and PSMA imaging in patients with mCRPC

PSMA Imaging and CTCs Reveal Heterogeneity in Prostate Cancer

Publication Title: Correlative Biomarker Analysis of PSMA Expression on CTCs and PSMA Imaging in a Phase I Study of PSMA Targeted Tubulysin Conjugate EC1169.

Summary

Question
This study explored the relationship between prostate-specific membrane antigen (PSMA) expression on circulating tumor cells (CTCs) and PSMA imaging in patients with metastatic castration-resistant prostate cancer (mCRPC). The authors aimed to assess the heterogeneity of PSMA expression and its potential as a biomarker for predicting treatment response.
Why it Matters
Prostate cancer is a leading cause of cancer-related death in men, and mCRPC is a particularly aggressive form that often resists standard treatments. PSMA-targeted therapies have shown promise in treating mCRPC, but their effectiveness varies. Understanding the variability (heterogeneity) in PSMA expression could help identify patients most likely to benefit from these therapies and improve treatment outcomes. This research could also guide future development of diagnostic tools and therapies for mCRPC.
Methods
This Phase 1 study included 103 men with mCRPC who had previously failed androgen receptor signaling inhibitors (ARSIs). The trial investigated a PSMA-targeted therapy, EC1169, and a PSMA imaging agent, 99mTc-EC0652. Patients underwent PSMA imaging, and blood samples were analyzed to detect PSMA-positive CTCs. The study compared imaging results with CTC data to assess PSMA expression before and after treatment.
Key Findings
The study found significant variability in PSMA expression among patients. Some individuals with predominantly PSMA-positive imaging results still had PSMA-negative CTCs, indicating heterogeneity in PSMA expression. Patients who experienced a reduction in PSMA-positive CTCs after treatment had longer radiographic progression-free survival (rPFS), suggesting that changes in CTC levels could predict treatment outcomes. However, EC1169 demonstrated limited overall effectiveness as a therapy.
Implications
The findings highlight the potential of combining PSMA imaging and CTC analysis to better understand PSMA expression variability in mCRPC. This approach could improve patient selection for PSMA-targeted therapies and monitor treatment effectiveness. Additionally, identifying PSMA-negative CTCs with neuroendocrine-like features may provide insights into treatment resistance and guide the development of new therapeutic strategies.
Next Steps
Future research should validate these findings in larger clinical trials using FDA-approved PSMA-targeted therapies and imaging tools. Studies should also explore the biological mechanisms underlying PSMA heterogeneity and its role in treatment resistance, as well as develop more comprehensive biomarkers for monitoring therapy effectiveness and disease progression.
Funding Information
This research was supported by the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Yale University also provided funding and support for this research.

Full Citation

Zaidi S, Kuo P, Paiva Prudente T, Lacuna K, Babiker H, Aparicio R, Schonhoft J, Fernandez L, Messmann R, Groaning M, Tolcher A, Gordon M, Yoo D, Vaishampayan U, Picus J, Petrylak D, Sartor O, Morris M. Correlative Biomarker Analysis of PSMA Expression on CTCs and PSMA Imaging in a Phase I Study of PSMA Targeted Tubulysin Conjugate EC1169. Clinical Cancer Research 2026, of1-of11. PMID: 41591990, PMCID: PMC13034684, DOI: 10.1158/1078-0432.ccr-25-2313.

Authors

  • Samir Zaidi

    First Author
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  • Michael J Morris

    Last Author
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Yale School of Medicine Authors

Other Authors

  • Phillip H Kuo;
  • Kristine P Lacuna;
  • Hani M Babiker;
  • Renan Aparicio;
  • Joseph D Schonhoft;
  • Luisa Fernandez;
  • Richard Messmann;
  • Michael Groaning;
  • Anthony W Tolcher;
  • Michael S Gordon;
  • Don C Yoo;
  • Ulka Vaishampayan;
  • Joel Picus;
  • Oliver Sartor

Research Themes

Concepts