Abstract LB435: Large panel organoid drug testing combined with biomarker analysis: Unveiling prospects for mechanism of action identification and preclinical patient stratification
Authors: Xue Linda , Wijler Liza , Hornsveld Marten , Guo Sheng , Price Leo , Putker Marrit , Bourre Ludovic 
Published: April 2024

Abstract
Introduction The development of oncology drugs has a persistently high attrition rate of greater than 95%, requiring the development and implementation of novel models and technologies aimed at better predictive abilities during the preclinical phase. Among these, organoid technologies, which involve propagating tumor stem cells in a near-native state, have proven to markedly advance drug testing with enhanced precision. Our previously developed assay-ready organoid technology has paved the way for large panel organoid screening, allowing organoids to augment the efficiency of drug development pipelines, boost patient-derived model usage in preclinical studies, and facilitate accurate predictions of drug action mechanisms. Here, we present a proof-of-concept (POC) large scale organoid experiment, studying the responses of 50 models to the cytotoxic agent paclitaxel, using next generation sequencing data to analyze the drug mechanism of action (MOA) and identify biomarkers that predict drug responses.
Methods A panel of 50 organoid models was characterized for paclitaxel response in 9-dose-response curves by measuring ATP levels after a 5-day exposure. Models were genomically profiled by whole-exome sequencing (n = 47) and whole-transcriptome sequencing (n = 44) to analyze the association between organoid pharmacology data and genomic information and elucidate genes and pathways that may be related with, or predictive of, the treatment responses. We performed biomarker analysis on gene expression, mutation, and copy number alteration levels.
Results By assessing organoid sensitivity to paclitaxel, we observed no significant indication-specific difference in organoid responses across 7 cancer types. The 50 models were then categorized into responders (AUC &lt; 1.5; n=15) and non-responders (AUC &gt; 2.6; n=14) for biomarker discovery. Differential expression analysis and pathway activation analysis revealed genes and pathways involved in the cell cycle and DNA replication. DNA recombination differentiates responders from non-responders, while genes involved in epithelial cell proliferation, differentiation, and wound healing are associated with drug resistance. Mutation of proto-oncogene RB Transcriptional Corepressor 1, RB1 (a negative regulator of the cell cycle), was found to be a biomarker enriched in non-responders to paclitaxel, corroborating earlier clinical findings. Using the identified profile, we predicted responses for non-tested models in our biobank and validated our approach.
Conclusion Large panel organoid drug screening in combination with biomarker analysis brings great opportunities for increasing drug pipeline efficiency. The POC here presented highlights how such a screen can identify MOAs and identify relevant biomarker profiles to be used in clinical trial patient stratification.
Citation Format: Linda Xue, Liza Wijler, Marten Hornsveld, Sheng Guo, Leo Price, Marrit Putker, Ludovic Bourre. Large panel organoid drug testing combined with biomarker analysis: Unveiling prospects for mechanism of action identification and preclinical patient stratification [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB435.