Abstract 6914: Genomic landscape and stability of preclinical models in NCI's patient-derived models repository
Authors: Chang Ting-Chia , Das Biswajit , Chen Li , Wu Peter I-Fan , Evrard Yvonne A. , Pauly Rini , Newton Dianne L. , Jiwani Shahanawaz , Alcoser Sergio Y. , Stockwin Luke H. , Camalier Corinne E. , Forbes Tomas , Nair Nikitha , Chapman Alyssa , Dutko Lindsay , Mullendore Michael , Grinnage-Pulley Tara , Klarmann Kimberly , Miller Sarah B. , Karlovich Chris A. , Chen Alice P. , Williams P Mickey , Hollingshead Melinda G. , Doroshow James H. 
Published: March 2024

Abstract
Background: Patient-derived xenograft (PDX) models serve as a powerful tool for cancer translational research. However, it is unclear to what extent PDX models reflect the genomic intratumoral heterogeneity and genomic aberrations present within the original tumor sample. The National Cancer Institute (NCI) has developed a Patient-Derived Models Repository (PDMR; https://pdmr.cancer.gov/) consisting of PDX, organoids (PDOrg), and tumor cell cultures (PDC) from patients with diverse cancer histologies. We have conducted an in-depth investigation into the genomic stability of PDXs at early passaging and tumor heterogeneity in a large set of preclinical models including rare cancers.
Methods: Tumor specimens were used to establish 1114 models from 1034 patients. For whole exome sequencing (WES) and RNASeq analysis, 1059 models with at least 1 PDX sample and 55 models with only a PDC or PDOrg were used. Analyzed specimens represent the original patient specimens, PDX passages P0, P1, P2, and P3+ and in vitro models. 80% of the PDX specimens were within passages P0 to P2.
Results: Genomic stability in PDMR models was maintained through early passages (P0 - P2) and across independent lineages in PDMR models based on the following observations: 1) variant allele frequencies (VAF) of somatic driver mutations showed no major deviations (exceeding ±10%) when using the stromal fraction corrected VAF from originator data over PDX passages; 2) the median change in the fraction of genome impacted by copy number alterations (CNA) from the originator specimens through passages P0 - P2 was statistically inconsequential, although there was a significant increase in CNA fraction, from 5.3% at P0 initially to 18% by P3; 3) gene expression profiles of specimens within a given PDX model formed clusters in principal component analysis (PCA) plots and showed high correlation (&gt;99.5% models with a Spearman coefficient of &gt;= 0.8). The majority of the PDC and PDOrg specimens exhibited similar findings when compared to the original tumor samples. Furthermore, the positive percent agreement (PPA) was performed to measure the similarity between the patient's tumor and all available derived PDX specimens, with a median PPA over 90%, indicating a high level of retained heterogeneity within the PDX models. Lastly, 69% of models in NCI PDMR had predictive biomarkers, ranging from OncoKB level of evidence 1-4, which could be used to evaluate targeted therapeutics in preclinical studies.
Conclusion: The NCI PDMR has a large and histologically diverse cancer representation. In this analysis, the PDXs exhibited genomic stability within early passages and preserved the majority of tumor heterogeneity observed in the patient specimens. NCI PDMR thus represents a valuable resource for researchers interested in preclinical drug screening or other investigations.
Citation Format: Ting-Chia Chang, Biswajit Das, Li Chen, Peter I-Fan Wu, Yvonne A. Evrard, Rini Pauly, Dianne L. Newton, Shahanawaz Jiwani, Sergio Y. Alcoser, Luke H. Stockwin, Corinne E. Camalier, Tomas Forbes, Nikitha Nair, Alyssa Chapman, Lindsay Dutko, Michael Mullendore, Tara Grinnage-Pulley, Kimberly Klarmann, Sarah B. Miller, Chris A. Karlovich, Alice P. Chen, P Mickey Williams, Melinda G. Hollingshead, James H. Doroshow. Genomic landscape and stability of preclinical models in NCI's patient-derived models repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6914.