Prostate organoids: emerging experimental tools for translational research

Organoid technology has provided new translational research opportunities in oncology, in part by enabling the development of patient-representative living biobanks. Prostate cancer research historically has been constrained to a small number of in vitro models, limiting the ability to translate experimental conclusions for contemporary, heterogeneous patient populations. The facility of organoid culture methods to maintain luminal prostate epithelia, the common lineage of prostate cancers, has greatly expanded the phenotypic and genotypic diversity of available tractable models, including luminal stem/progenitor cells and progressive patient-derived cancers. Biobanks of patient prostate cancer organoids enable increased accuracy in predicting therapeutic efficacy and informative clinical trial designs. Here, we discuss how prostate organoid technology is currently being used, the promising areas of future therapeutic applications, and the current obstacles to be overcome.

Tumor-derived biomarkers predict efficacy of B7H3 antibody-drug conjugate treatment in metastatic prostate cancer models

Antibody-drug conjugates (ADCs) are a promising targeted cancer therapy; however, patient selection based solely on target antigen expression without consideration for cytotoxic payload vulnerabilities has plateaued clinical benefits. Biomarkers to capture patients who might benefit from specific ADCs have not been systematically determined for any cancer. We present a comprehensive therapeutic and biomarker analysis of a B7H3-ADC with pyrrolobenzodiazepine(PBD) payload in 26 treatment-resistant, metastatic prostate cancer (mPC) models. B7H3 is a tumor-specific surface protein widely expressed in mPC, and PBD is a DNA cross-linking agent. B7H3 expression was necessary but not sufficient for B7H3-PBD-ADC responsiveness. RB1 deficiency and/or replication stress, characteristics of poor prognosis, and conferred sensitivity were associated with complete tumor regression in both neuroendocrine (NEPC) and androgen receptor positive (ARPC) prostate cancer models, even with low B7H3 levels. Non-ARPC models, which are currently lacking efficacious treatment, demonstrated the highest replication stress and were most sensitive to treatment. In RB1 WT ARPC tumors, SLFN11 expression or select DNA repair mutations in SLFN11 nonexpressors governed response. Importantly, WT TP53 predicted nonresponsiveness (7 of 8 models). Overall, biomarker-focused selection of models led to high efficacy of in vivo treatment. These data enable a paradigm shift to biomarker-driven trial designs for maximizing clinical benefit of ADC therapies.