Plasma Extracellular Vesicle Proteomics Nominates Candidate Biomarkers of 177Lu-PSMA-617 Outcomes in Metastatic Prostate Cancer Patients

For decades, liquid biopsy in oncology has been dominated by circulating tumor DNA (ctDNA) analysis, and deep proteomic profiling has been largely confined to tissue biopsies.^1,2 This is in part because plasma is flooded with abundant proteins such as albumin and immunoglobulins that overwhelm the detection of rare tumor-derived protein signals. Extracellular vesicles (EVs) offer a way around this problem. These nanoscale membrane-bound particles, shed by virtually all cells including tumor cells, selectively concentrate and protect proteins that reflect the biology of their cell of origin.³ With the recent approval of 177Lu-PSMA-617, we sought to determine whether plasma EV proteomics could uncover the tumor biology driving response and resistance to this radiopharmaceutical therapy.⁴

To test this, we prospectively enrolled 100 mCRPC patients receiving 177Lu-PSMA-617 at the University of Minnesota Masonic Cancer Center, collecting baseline plasma samples prior to the first treatment dose. Using data-independent acquisition mass spectrometry (DIA-MS), we identified 5,137 unique EV-derived proteins, representing, to our knowledge, the largest prospective blood-based study linking mass spectrometry proteomics to clinical outcomes in this setting, and the first to do so in patients receiving radioligand therapy.

The biology was bidirectional. High EV levels of PSMA, B7-H3, Trop-2, and STEAP1 were associated with worse survival, tracking closely with PSMA-PET molecular tumor volume and conventional serum markers such as PSA. We also identified proteins associated with better outcomes, including CXCR4, CD46, CD151, and CNTN1, and found in GSEA analysis that an activated E2F pathway unexpectedly predicted improved survival, likely reflecting tumor vulnerability to radiation-induced DNA damage. Importantly, elevated ABCB1 (P-glycoprotein), a well-established mediator of multidrug resistance, was detectable in EV cargo and may help distinguish patients better served by 177Lu-PSMA-617 from those more likely to benefit from chemotherapy, a distinction with direct clinical relevance given that treatment sequencing decisions remain largely empirical.

A key methodological advance in this paper is the first application of the Algorithm for Linking Activity Networks (ALAN) to proteomics data. ALAN, previously developed and applied in transcriptomic contexts, was adapted here to cross-compare all 5,137 proteins against each other across 100 patient samples, revealing that PSMA, B7-H3, Trop-2, STEAP1, and HER2 behave as a coordinated network, while KIF2A and INPP4B exhibit inverse relationships. This systems-level view of the EV proteome is not achievable with conventional differential expression analysis alone and opens a new dimension for how protein networks can be interrogated in liquid biopsy studies.

The clinical relevance of our study extends beyond 177Lu-PSMA-617. We are entering an era of protein-targeting therapies in prostate cancer and across oncology, including antibody-drug conjugates, bispecific T cell engagers, and trispecific killer engagers. A blood-based platform that can simultaneously quantify these targets, track their co-expression with tumor burden markers, and link their levels to survival outcomes is directly positioned to support biomarker-stratified clinical trials across all of these programs. The same EV proteomics infrastructure is disease-agnostic and can, in principle, be extended to any malignancy where protein-targeting agents are under development.

Independent external validation is the essential next step, and that work is now actively underway in several 177Lu-PSMA-treated cohorts and across other malignancies.

Written by: Ali Arafa, MD,¹ Justin Hwang, PhD,² Justin Drake, PhD,³ and Emmanuel Antonarakis, MD²

Department of Pharmacology, University of Minnesota, Minneapolis, MN, USA.
Division of Hematology, Oncology and Transplantation, Department of Medicine, University of Minnesota, Minneapolis, MN, USA; Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA.
Department of Pharmacology, University of Minnesota, Minneapolis, MN, USA; Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA; Department of Urology, University of Minnesota, Minneapolis, MN, USA; Astrin Biosciences, Saint Paul, MN, USA.

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