Abstract B025: Integrative clinical and molecular analysis of 665 next-generation in vitro cancer models generated by the the Human Cancer Models Initiative (HCMI) for advancing precision medicine and functional drug discovery
Authors: Dina ElHarouni, Mushriq Al-Jazrawe, Seongmin Choi, Merve Dede, Toshinori Hinoue, Sean A Misek, Heeju Noh, Luca Zanella, Moony Tseng, Hayley E Francies, Priya Sridevi, Rachana Agarwal, Cindy W Kyi, Julyann Perez-Mayoral, Megan J Stine, Eva Tonsing-Carter, James M Clinton, The HCMI Network, Peter W Laird, Calvin J Kuo, Olivier Elemento, David L Spector, Andrew D Cherniack, Kyle Ellrott, Martin L Ferguson, Rameen Beroukhim, Katherine A Hoadley, Nicolas Robine, Mathew Garnett, Andrea Califano, Paul T Spellman, David A Tuveson, Keith L Ligon, Daniela S Gerhard, Louis M Staudt, Jesse Boehm
Journal: Cancer Research (2025)

Abstract Advancing precision medicine research relies heavily on laboratory models that accurately reflect the rich intra- and inter-patient diversity of human tumors. While large-scale resources built on historical cell lines have provided valuable insights, these models often lack the molecular diversity needed for comprehensive translational research and may undergo genetic drift in culture, reducing their fidelity. Recent advances in technologies, such as organoid culture, have improved model derivation; however, systematic pan-cancer comparisons of genomic, transcriptomic, and epigenomic integrity following long-term ex vivo expansion remain limited. Here, we report on the Human Cancer Models Initiative (HCMI), an international program that has generated and systematically characterized 665 organoid, spheroid, and cell line models derived from over 2,500 consented donors. These models have undergone comprehensive whole-genome, exome, methylome, and transcriptome analyses. The HCMI collection includes 47 unique models representing 16 rare and histologically distinct cancer subtypes, including one of a kind disease models (e.g. desmoid tumor) and greatly broadening the diversity of available cancer models. Through integrative concordance analysis, we demonstrate that 96% of the 417 analyzed models closely mirror the molecular profiles of their parental tumors. Interesting rare exceptions to this concordance include subsets of models, where cell culture media conditions, tumor stroma, or population selection appear to influence cellular characteristics. We validated observed cellular state shifts using single-cell RNA sequencing, providing insights into the impact of ex vivo culture on model integrity. We further explored the translational utility of this resource by investigating treatment exposures, post-treatment mutational signatures, and extrachromosomal DNA (ecDNA) amplifications and their potential implications on treatment resistance within these models. This community resource offers a comprehensive roadmap for capturing a broader spectrum of cancer diversity in preclinical models, ultimately supporting and advancing therapeutic discovery. Citation Format: Dina ElHarouni, Mushriq Al-Jazrawe, Seongmin Choi, Merve Dede, Toshinori Hinoue, Sean A Misek, Heeju Noh, Luca Zanella, Moony Tseng, Hayley E Francies, Priya Sridevi, Rachana Agarwal, Cindy W Kyi, Julyann Perez-Mayoral, Megan J Stine, Eva Tonsing-Carter, James M Clinton, The HCMI Network, Peter W Laird, Calvin J Kuo, Olivier Elemento, David L Spector, Andrew D Cherniack, Kyle Ellrott, Martin L Ferguson, Rameen Beroukhim, Katherine A Hoadley, Nicolas Robine, Mathew Garnett, Andrea Califano, Paul T Spellman, David A Tuveson, Keith L Ligon, Daniela S Gerhard, Louis M Staudt, Jesse Boehm. Integrative clinical and molecular analysis of 665 next-generation in vitro cancer models generated by the the Human Cancer Models Initiative (HCMI) for advancing precision medicine and functional drug discovery [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Functional and Genomic Precision Medicine in Cancer: Different Perspectives, Common Goals; 2025 Mar 11-13; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(5 Suppl):Abstract nr B025.