Abstract 3882: Patterns of genomic patient-model conservation and evolution in the Human Cancer Models Initiative (HCMI) next-generation cancer model resource

Background: Patient-derived cancer models advance therapeutic development and are essential to studies of treatment resistance mechanisms. The Human Cancer Models Initiative (HCMI) has created 665 patient-derived models, including organoids, neurospheres, and conditionally reprogrammed cells, all paired with patient tumors and clinical annotations. This resource provides an opportunity to study genomic conservation and divergence during model development at scale in a large pan-cancer cohort of matched tumor-model pairs. Methods: We characterized the genomes of models and parent tumors, computing allele specific Copy Number Variation (CNV), Single Nucleotide Variants (SNV), small Insertions and Deletions (InDels) and Structural Variations (SV) from bulk whole genome and whole exome Sequencing. We used pyclone to study changes in clonal abundances between tumor and model, MutationTimeR to understand the timing of model specific CNVs and Whole Genome Doubling (WGD), and AmpliconArchitect to identify ecDNA. Results: HCMI models exhibited high concordance with matching tumors when evaluated on SNVs, SVs, InDels and CNVs, with 69% of SNV/InDel drivers and 43% of CNV drivers conserved between tumor and model. Only 2% of investigated models (9/405) showed significantly divergent patterns of aneuploidy and presence of distinct clonal outgrowth in the model. This included two pancreatic cancer models with oncogenic KRAS point mutations that differed from those in the parent tumor. The cohort included models and tumors with ecDNA affecting known oncogenes including EGFR in GBM samples, CCNE1/KRAS in esophageal cancer and MYC in pancreatic cancer. ecDNA were the least conserved aberration type; 20% (50/254) of tumor-detected ecDNA were retained in an associated model while 35% (50/143) of model-detected ecDNA were found in their parent tumors. While the tumors and models generally showed similar WGD states, 10% of models exhibited WGD private to the model, and this model specific WGD generally occurred later in estimated mutational evolution time than models for which the tumor and model were both WGD. Surprisingly, not all models were pure for cancer cells with 19 models, enriched for melanomas, containing more than 20% diploid presumably non-tumor cells. Discussion: HCMI models exhibited high genomic concordance with their matching tumors across all cancer types. We catalogued classes of genomic divergence representing either selection of subclones or evolution during model development. SNVs and InDels exhibited greater conservation compared to CNVs, with ecDNA showing the highest variability between the tumor and the model. Our results provide full visibility into the genomic fidelity of each HCMI model, and enable researchers to select the most relevant HCMI model for their study. Citation Format: Andrew W. McPherson, Seongmin Choi, William F. Hooper, Jennifer M. Shelton, Timothy R. Chu, Dina ElHarouni, Mushriq Al-Jazrawe, 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 J. Garnett, David A. Tuveson, Andrea Califano, Paul T. Spellman, Keith L. Ligon, Daniela S. Gerhard, Louis Staudt, Jesse Boehm. Patterns of genomic patient-model conservation and evolution in the Human Cancer Models Initiative (HCMI) next-generation cancer model resource [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 3882.