European journal of cancer (Oxford, England : 1990)
August 18, 2026 · via Europe PMC
Expression patterns of potential targets for antibody-directed therapy in metastatic castration-resistant prostate cancer patients.
van Dijk TC, Smid M, Robbrecht DGJ, Isebia KT, Martens JWM, Beije N.
AI summary — for doctors, generated from the abstract only
Antibody-targetable antigen expression in mCRPC varies by transcriptomic subtype, with CD46 emerging as a broadly expressed target, including in tumors lacking PSMA, KLK2 and STEAP1.
What was studied
Gene expression analysis of 62 antibody-targetable proteins in 296 mCRPC biopsies, with validation in an independent cohort and single-cell transcriptomics.
Key findings
- KLK2, FOLH1 (PSMA) and STEAP1 had highest median expression
- Target expression did not correlate with genomic alterations such as HRD, MSI, CDK12, TP53, PTEN or AR
- CRPC-AR and CRPC-SCL subtypes expressed the most targets; CRPC-WNT generally low
- CRPC-NE heterogeneous with high CD46
- CD46 highly expressed in tumors with low established targets, a poor-prognosis group
Clinical relevance
This suggests transcriptomic subtyping could inform selection for antibody-based therapies and supports investigating CD46-directed agents, though protein-level and clinical validation are needed.
Who should care
Limitations
RNA-level expression may not reflect surface protein abundance; no treatment outcome data.
Not all prostate cancers express PSMA-like targets, and CD46 may fill the gap.
This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.
Abstract
Introduction
Survival in metastatic castration-resistant prostate cancer (mCRPC) patients remains limited and treatment is complicated by tumor heterogeneity. As antibody-based therapeutics emerge, identifying actionable antigen targets and patient subgroups most likely to benefit is essential.
Materials & methods
Gene expression of 62 antibody-targetable proteins was analyzed in 296 mCRPC biopsies. These genes encode proteins targeted by approved or investigational antibody-based cancer therapeutics. Associations between target expression with genomic classifications and transcriptomic subtypes were evaluated. Target expression was also assessed in tumors with low expression of established mCRPC targets. Subgroup-specific targets were validated in an independent cohort and single-cell transcriptomics.
Results
Established targets KLK2, FOLH1 (PSMA) and STEAP1 showed the highest median expression across the cohort. Target expression did not correlate with genomic classifications, including homologous recombination deficiency, microsatellite instability, CDK12, TP53, PTEN or AR alterations Target expression did associate with transcriptomic subtypes: CRPC-AR (driven by androgen receptor-signaling) and CRPC-SCL (stem cell-like features, AP-1/YAP/TAZ-driven), displayed the highest expression of multiple targets, including KLK2, FOLH1, and SLC44A4. CRPC-NE (neuroendocrine phenotype) showed heterogeneous expression, with high CD46 expression, whereas CRPC-WNT (Wnt-signaling driven) generally showed low target expression. Notably, CD46 was highly expressed in tumors with low KLK2, FOLH1, and STEAP1 expression, a subgroup associated with poor prognosis.
Conclusions
Although several antibody targets showed broad expression in mCRPC-tumors, expression varied by transcriptomic subtype. Subgroups such as CRPC-WNT expressed fewer targets, suggesting the need for alternative therapeutic strategies. CD46 emerged as a promising target, with wide expression across multiple subtypes, including clinically challenging CRPC-NE and mCRPC tumors lacking expression of established targets.
DOI
10.1016/j.ejca.2026.116992
PMID
42623835
Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.
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