Abstract PR030: Integrating multi-omic datasets investigating stress response biology decodes prostate cancer dynamic disease progression and places IRE1 activity at the epicentre of acquired treatment resistance

Abstract Prostate cancer (PCa) is an androgen receptor (AR) driven, high-incidence disease significantly contributing to cancer mortality. PCa is in need of better risk stratification at diagnosis and treatment outcomes in patients at high risk of metastasis. The unfolded protein response (UPR) is an AR-dependent process. However, the impact of the UPR transducer IRE1 on AR-dependent biology and treatment resistance has not been defined. We use diverse pre-clinical models of stress response to describe IRE1 activity impact on multiple disease stages and demonstrate its involvement with poor prognosis (RB1 loss), and cell lineage determination (club phenotypes). We genetically and pharmacologically perturbed AR and IRE1 activity in multiple pre-clinical PCa models and observed that long-term adaptation to IRE1 activity loss, leads to a lineage shift that confers treatment resistance characteristics in AR sensitive models. In parallel, we show that castration resistant PCa (CRPC) models have low IRE1 activity and that androgen deprivation therapy (ADT) suppresses IRE1 activity. By treating these CRPC models with an IRE1 activator, we sensitised them to both physiological and pharmacological (Enzalutamide) ADT. Integrating clinical, pre-clinical, bulk, single cell and spatial transcriptomic datasets, we chart IRE1 activity throughout PCa evolution by developing an IRE1 activity gene set (IRE1_18) reflecting both tumoral and micro-environmental niches. IRE1_18 has distinct expression profiles in AR positive (HSPC and CRPC) and AR negative (CRPC) disease reflecting tumoral identity as well as tumoral content. Using diverse datasets such as the Dream Team West Coast, META855 and 55K GRID cohorts we validated IRE1_18 against multiple clinical correlates. As such, IRE1_18 significantly correlates with response to ARSI, grade group, NCCN and Decipher scores. Finally, it prognosticas localised and metastatic disease independently from AR activity in terms of metastatic progression, biochemical recurrence, prostate cancer specific mortality and consequently, may guide IRE1 modulation as a novel combination therapeutic. Our study showcases a forward translation, data integration pipeline which may distil actionable targets and biomarkers from studying a fundamental biological homeostatic mechanism that represents cells in both the tumour and the microenvironment. Citation Format: Dimitrios Doultsinos, Ingrid Tomljanovic, Eleftherios Pilalis, Sophia Abusamra, Sandy Figiel, Romuald Parmentier, Imogen Bridges, Joanna Hester, Yanis Zekri, Damien Leach, Charlotte Bevan, Alastair Lamb, Wilbert Zwart, Aristotelis Chatziioannou, Clementine Le Magnen, Mohammed Alshalalfa, Elai Davicioni, Rensheng Wan, David Quigley, Alfonso Urbanucci, JP Theurillat, Jichang Zhang, Ian Mills. Integrating multi-omic datasets investigating stress response biology decodes prostate cancer dynamic disease progression and places IRE1 activity at the epicentre of acquired treatment resistance [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Innovations in Prostate Cancer Research and Treatment; 2026 Jan 20-22; Philadelphia PA. Philadelphia (PA): AACR; Cancer Res 2026;86(2_Suppl):Abstract nr PR030.