EpCAM–PSMA: Potential predictors of treatment outcomes for PSMA-targeted alpha therapies in metastatic castration-resistant prostate cancer

TL;DR

This study identifies EpCAM and PSMA as potential biomarkers for predicting treatment response in prostate cancer patients undergoing PSMA-targeted therapies.

Contribution

The study reveals dynamic changes in EpCAM and PSMA levels on circulating tumor cells as predictive biomarkers for therapy resistance in mCRPC.

Findings

Nonresponders had higher EpCAM and lower PSMA levels compared to responders at baseline and after treatment.

Responder CTCs maintained EpCAM but progressively lost PSMA over treatment cycles.

Transcriptome analysis linked EpCAM-PSMA dynamics to DNA repair and anti-apoptotic pathways contributing to resistance.

Abstract

Targeted radionuclide therapy and targeted alpha therapy directed at prostate-specific membrane antigen (PSMA) represent emerging treatment modalities for metastatic castration-resistant prostate cancer (mCRPC). However, therapeutic resistance remains a significant barrier to their clinical success. We discovered that dynamic changes in cell surface levels of epithelial cell adhesion molecule (EpCAM) and PSMA can serve as predictive biomarkers in late-stage mCRPC patients treated with the beta-minus-particle-emitting [177Lu]Lu-PSMA-617, in combination with the alpha-particle-emitting [225Ac]Ac-PSMA-617, and we further explored the underlying molecular mechanisms. Using flow cytometry to profile EpCAM and PSMA on circulating tumor cells (CTCs), we observed that Nonresponders displayed significantly higher EpCAM and lower PSMA levels than Responders, both at baseline and after the first treatment cycle. Over subsequent cycles, both markers declined in Nonresponders, whereas Responder CTCs maintained EpCAM expression but progressively lost PSMA. Transcriptome analysis identified upregulation of hub genes involved in the regulation of key pathways such as enhanced DNA-damage repair, anti-apoptotic activity, increased tumor cell growth, and altered surface marker trafficking and recycling, potentially driving EpCAM-PSMA dynamics and contributing to therapy resistance. Ultimately, integrating surface-marker-driven treatment response predictions with novel treatment strategies may help to overcome treatment resistance in mCRPC.

This study examines circulating tumor cells from patients with advanced prostate cancer undergoing PSMA-targeted radionuclide therapy. Dynamic changes in EpCAM and PSMA surface markers reveal therapy-driven phenotypic plasticity indicative of treatment response. These findings underscore the value of CTC profiling for understanding treatment response and resistance in late-stage metastatic disease.

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