Abstract 1165: The landscape of molecular targets across 665 next-generation cancer models in the human cancer models initiative identifies opportunities for improved therapy and overcoming resistance

Abstract Advancing precision oncology requires a diverse and robust repository of patient-derived cancer models that faithfully reflect the clinical, therapeutic, and molecular attributes of patients’ tumor. Traditional models, while invaluable, often lack sufficient clinical data and fail to capture the genetic and phenotypic complexity of human cancers, limiting their translational relevance. To address these challenges, the Human Cancer Models Initiative (HCMI) generated 665 next-generation cancer models from over 2,500 donors across 27 cancer subtypes. The HCMI cohort comprises 78% three-dimensional (3D) organoid cultures from 19 tumor types, 6% 3D neurospheres, and 16% two-dimensional (2D) adherent cell lines from 13 tumor types and includes 48 unique models from 17 rare cancer subtypes. Molecular profiling using whole-genome and exome sequencing, RNA-seq, and methylation analysis shows high concordance between models and their parent tumors, underscoring the fidelity and preclinical relevance of these models. Analysis also identified rare molecular targets and expression states in cancer types underrepresented in current collections, including desmoid tumors, breast lobular carcinoma, and nephroblastoma, significantly advancing research into rare and undercharacterized malignancies. Analyses of treatment-naive (62%) and post-treatment (38%) models revealed molecular features associated with therapeutic exposures, supported by a median clinical follow-up time of 1.4 years. These exposures include chemotherapy, immunotherapy, targeted therapies, molecular antibody treatments, and radiation, enabling preclinical correlation. Treatment-associated mutational signatures, such as temozolomide (TMZ)-induced alterations in glioblastoma and APOBEC mutational activity in colorectal cancer, were observed and correlated with patient outcomes. We identified specific models with preserved patterns of extrachromosomal DNA (ecDNA) amplification of oncogenes of high interest for preclinical studies, including EGFR, MDM4, CCND1, MYC and FGFR3. Such targets were preserved across paired tumors and models including correlation with increased target expression in models. To facilitate accessibility and exploration, HCMI models and their accompanying clinical data are made available through multiple platforms, including the HCMI searchable catalog, cBioPortal, the HCMI Explorer Suite for interactive analyses of treatment timelines and molecular profiles, and the ATCC. In summary, this comprehensive resource should aid both basic research and therapy development for future precision oncology studies. 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, William F. Hooper, Jennifer M. Shelton, Timothy R. Chu, 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, Andrew McPherson, Mathew J. Garnett, David A. Tuveson, Andrea Califano, Paul T. Spellman, Keith L. Ligon, Daniela S. Gerhard, Louis M. Staudt, Jesse S. Boehm. The landscape of molecular targets across 665 next-generation cancer models in the human cancer models initiative identifies opportunities for improved therapy and overcoming resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1165