Abstract A009: Integrative drug screening and multi-omic characterization of patient-derived bladder cancer organoids reveals novel molecular correlates of chemotherapy response

Abstract Introduction: Predicting response to therapy for each patient’s tumor is critical to improving long-term outcomes for muscle-invasive bladder cancer (MIBC). Our objective is to establish ex vivo bladder cancer patient-derived organoid (PDO) models that are representative of patients’ tumors and determine potential efficacy of standard-of-care and curated experimental therapies. Methods: Tumor material was prospectively collected from consented patients with bladder cancer to generate short-term PDO models, which were screened against a panel of clinically relevant drugs in ex vivo 3D culture. Drugs were tested at the maximum plasma concentration (Cmax) in human trials, so as to provide physiologic relevance. When material was sufficient, cells were additionally tested using full dose response. The number of drugs screened was dependent upon amount of tissue available, with up to 34 drugs screened at Cmax and 9 drugs screened in dose response format. Multiomic profiling was utilized to validate the PDO models, establish the molecular characteristics of each tumor, assess gene expression (GEX) patterns between paired primary tissue and PDOs, and identify potential biomarkers of drug response using Pearson correlation coefficients and Kruskal-Wallis tests with Dunn’s post-hoc pairwise comparison testing. Results: 106 tumors were collected from 97 patients, with 65 samples yielding sufficient material for complete multiomic molecular characterization and PDO screening with 6 to 32 drugs/combinations. RNA sequencing and GSEA enriched pathways across organoids were compared to other published datasets, noting high levels of correlation between our organoid models and in particular the Cancer Cell Line Encyclopedia urethral lines. Moreover, analysis of subtype and mutation/copy number data further indicate that our organoid dataset is representative of the full spectrum of disease. RNA sequencing and subtyping of cultured organoids compared to patient tissue indicate that organoid models are representative of patient tissue and do not undergo subtype shifts in our short-term 3D cultures. Our drug screening results highlight the large spectrum of response to chemotherapies that in fact, clinically benefit only a small proportion of patients in the neoadjuvant setting. Utilizing an integrative approach, novel correlations between ex vivo drug responses and genomic alterations, GEX, and protein expression were identified, including a multiomic signature of gemcitabine response. Conclusions: Rapid organoid development, characterization, and drug screening allows for the prediction of therapeutic response in ~10 days following sample collection. Use of this technique on tissue provided during disease work-up may further guide selection of effective therapeutic agents in patients with bladder cancer, beyond the typical unranked lists derived from genomic analyses. This work would help maximize the overall benefits of standard of care therapies and could be used to identify alternative therapeutics for patients who progress on standard therapies. Citation Format: Nathan M. Merrill, Samuel D. Kaffenberger, Liwei Bao, Nathalie Vandecan, Laura E. Goo, Athena Apfel, Xu Cheng, Zhaoping Qin, Chia-Jen Liu, Armand Bankhead, Yin Wang, Varun Kathawate, Lila Tudrick, Habib Serhan, Zackariah Farah, Chad Ellimoottil, Khaled S. Hafez, Lindsey A. Herrel, Jeffrey S. Montgomery, Todd M. Morgan, Simpa S. Salami, Alon Z. Weizer, Peter J. Ulintz, Mark L. Day, Matthew B. Soellner, Phillip L. Palmbos, Sofia D. Merajver, Aaron M. Udager. Integrative drug screening and multi-omic characterization of patient-derived bladder cancer organoids reveals novel molecular correlates of chemotherapy response abstract. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30 (10Suppl): Abstract nr A009.