Abstract C120: Spatial transcriptomic analysis of patient-derived explants identifies biomarkers of aggressive disease

Abstract Prostate Cancer (PCa) is the most common non-cutaneous cancer and the second leading cause of cancer deaths in American men, with African American (AA) men experiencing higher PCa incidence and mortality rates than Caucasian American (CA) men. PCa development and progression is driven by androgen receptor (AR), a hormone-activated transcription factor. Metastatic PCa is commonly treated with androgen deprivation therapy (ADT) as a first-line therapy, but nearly all cases develop resistance to ADT, leading to lethal recurrence known as castration-resistant prostate cancer (CRPC). The introduction of second-generation AR inhibitors, such as enzalutamide, has added another standard-of-care treatment for both hormone-sensitive and castration-resistant stages of disease. However, treatment resistance remains a challenge leading to the progression to lethal disease. Thus, there is a need for better preclinical models which effectively capture the heterogeneity of PCa and treatment response to develop personalized treatment approaches. To investigate the molecular underpinnings of response to enzalutamide, this study utilized patient derived explants (PDEs), an established method of culturing patient tissue ex vivo. Briefly, when a patient undergoes radical prostatectomy, pieces of tumor and non-neoplastic adjacent tissue are placed on dental sponges and treated ex vivo to examine response. PDEs maintain the native tumor microenvironment, tissue morphology, and molecular signaling, allowing for the assessment of treatment response and the identification of relevant mechanisms of drug response or resistance. Spatial transcriptomic analysis was performed on tumor and non-neoplastic adjacent tissue collected at Day 0 and on tumor tissue treated with either vehicle or enzalutamide collected at Day 6. Specimens were paired from CA and AA patients to elucidate differences in treatment response based on ancestry. This allowed for molecular subtype grouping and identification of signatures of responsiveness to AR inhibition treatment. Initial data suggests that CA and AA patients differ in multiple ways, with AA patients exhibiting metabolic rewiring leading to more aggressive disease. The results of this study will provide unique insight into the molecular differences driving treatment response or lack of thereof in a diverse cohort of PCa patients while also allowing for characterization of heterogeneous models that represent the broad range of PCa disease presentation. Citation Format: Orly Richter, Stefan DiFazio, Elise DeArment, Kathryn Sun, Ramkrishna Mitra, Kathleen Cormier, George Eng, Karen Knudsen, Christopher McNair, Xiaofeng Su, Ayesha Shafi. Spatial transcriptomic analysis of patient-derived explants identifies biomarkers of aggressive disease abstract. In: Proceedings of the 18th AACR Conference on the Science of Cancer Health Disparities; 2025 Sep 18-21; Baltimore, MD. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(9 Suppl):Abstract nr C120.