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The widespread use of potent androgen receptor signaling inhibitors (ARSIs) has led to an increasing emergence of AR-independent castration-resistant prostate cancer (CRPC), typically driven by loss of AR expression, lineage plasticity, and transformation to prostate cancers (PCs) that exhibit phenotypes of neuroendocrine or basal-like cells. The anti-apoptotic protein BCL2 is upregulated in neuroendocrine cancers and may be a therapeutic target for this aggressive PC disease subset. There is an unmet clinical need, therefore, to clinically characterize BCL2 expression in metastatic CRPC (mCRPC), determine its association with AR expression, uncover its mechanisms of regulation, and evaluate BCL2 as a therapeutic target and/or biomarker with clinical utility. Here, using multiple PC biopsy cohorts and models, we demonstrate that BCL2 expression is enriched in AR-negative mCRPC, associating with shorter overall survival and resistance to ARSIs. Moreover, high BCL2 expression associates with lineage plasticity features and neuroendocrine marker positivity. We provide evidence that BCL2 expression is regulated by DNA methylation, associated with epithelial-mesenchymal transition, and increased by the neuronal transcription factor ASCL1. Finally, BCL2 inhibition had antitumor activity in some, but not all, BCL2-positive PC models, highlighting the need for combination strategies to enhance tumor cell apoptosis and enrich response.

Therapies that abrogate persistent androgen receptor (AR) signaling in castration-resistant prostate cancer (CRPC) remain an unmet clinical need. The N-terminal domain of the AR that drives transcriptional activity in CRPC remains a challenging therapeutic target. Herein we demonstrate that BCL-2-associated athanogene-1 (BAG-1) mRNA is highly expressed and associates with signaling pathways, including AR signaling, that are implicated in the development and progression of CRPC. In addition, interrogation of geometric and physiochemical properties of the BAG domain of BAG-1 isoforms identifies it to be a tractable but challenging drug target. Furthermore, through BAG-1 isoform mouse knockout studies, we confirm that BAG-1 isoforms regulate hormone physiology and that therapies targeting the BAG domain will be associated with limited "on-target" toxicity. Importantly, the postulated inhibitor of BAG-1 isoforms, Thio-2, suppressed AR signaling and other important pathways implicated in the development and progression of CRPC to reduce the growth of treatment-resistant prostate cancer cell lines and patient-derived models. However, the mechanism by which Thio-2 elicits the observed phenotype needs further elucidation as the genomic abrogation of BAG-1 isoforms was unable to recapitulate the Thio-2-mediated phenotype. Overall, these data support the interrogation of related compounds with improved drug-like properties as a novel therapeutic approach in CRPC, and further highlight the clinical potential of treatments that block persistent AR signaling which are currently undergoing clinical evaluation in CRPC., (©2024 The Authors; Published by the American Association for Cancer Research.)

Patient-derived organoid (PDO) models of cancer are a multifunctional research system that better recapitulates human disease as compared to cancer cell lines. PDO models can be generated by culturing patient tumor cells in extracellular basement membrane extracts (BME) and plating them as three-dimensional domes. However, commercially available reagents that have been optimized for phenotypic assays in monolayer cultures often are not compatible with BME. Herein, we describe a method to plate PDO models and assess drug effects using an automated live-cell imaging system. In addition, we apply fluorescent dyes that are compatible with kinetic measurements to quantify cell health and apoptosis simultaneously. Image capture can be customized to occur at regular time intervals over several days. Users can analyze drug effects in individual Z-plane images or a Z Projection of serial images from multiple focal planes. Using masking, specific parameters of interest are calculated, such as PDO number, area, and fluorescence intensity. We provide proof-of-concept data demonstrating the effect of cytotoxic agents on cell health, apoptosis, and viability. This automated kinetic imaging platform can be expanded to other phenotypic readouts to understand diverse therapeutic effects in PDO models of cancer.