Abstract The National Cancer Institute's Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) is performing a large-scale preclinical study with 39 patient-derived xenograft (PDX) models of rare cancers (including mesothelioma, MPNST, osteosarcoma, Merkel cell carcinoma) treated with 56 novel therapeutic combinations (targeted and cytotoxic agents) in an exploratory, n-of-4 arm, study design. Drug combinations with additive activity may undergo clinical evaluation in patients with rare cancers. PDX tumors are treated with a set of 8 combinations plus relevant vehicle controls while in parallel enough PDXs are serially passaged for the next passage and drug set. Every serial passage undergoes several quality control assessments that serve as go/no-go criteria. Combinations that show promising responses (e.g., regression or durable tumor growth inhibition) are repeated along with the single agent arms to determine if the response is driven by the combination or only one of the agents. We are currently at the half-way point in the overall study and here report interim results for the early combination agents that have single agent data for comparison. In a combination of a VEGFi and EGFRi, 6/37 models achieved a partial regression (30% shrinkage for more than one consecutive time point) and 17/37 had tumor growth inhibition while drug was on board. Single agent studies have been completed for 17/37 models with this combination and 7/9 responses were due to at least an additive effect of the combination. In contrast, while an HDACi + nucleoside analog combination had 16/36 responsive models, response in most of the single agent studies was due to only one of the agents. As part of this study, 3 models have been identified that have responded to at least 50% of the combinations tested possibly indicating a hypersensitive phenotype: two Merkel cell carcinomas (n=28 and 32) and one Neuroendocrine carcinoma (n=27). There is no immediate link between mechanism of action of the agents in the combinations, and the two Merkel cell carcinoma responses only had a moderate overlap. Finally, two Rhabdomyosarcoma models in the study have been the least responsive models to date. Funded by NCI Contract No. HHSN261200800001E Citation Format: Yvonne A. Evrard, Sergio Y. Alcoser, Suzanne Borgel, Devynn Breen, John Carter, Tiffanie Chase, Alice Chen, Li Chen, Kristen Cooley, Biswajit Das, Emily Delaney, Lyndsay Dutko, Shannon Ecker, Thomas Forbes, Kyle Georgius, Michelle M. Gottholm-Ahalt, Tara Grinnage-Pulley, Sierra Hoffman, Chris Karlovich, Kimberly Klarmann, Shahanawaz Jiwani, Justine Mills, Malorie Morris, Michael Mullendore, Dianne Newton, Gloryvee Rivera, Howard Stotler, Jesse Stottlemyer, Savanna Styers, Cindy R. Timme, Debbie Trail, Shannon Uzelac, Tomas Vilimas, Thomas Walsh, Nikki Walters, P. Mickey Williams, Melinda G. Hollingshead, James H. Doroshow. Single agent response comparisons in a large-scale, preclinical trial of rare cancer PDXs by the National Cancer Institute's patient-derived models repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3010.

Abstract There is an unmet need for preclinical models of rare cancers and rare disease sub-types. The National Cancer Institute's Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) is developing quality-controlled, early-passage, clinically-annotated patient-derived tumor xenografts (PDXs), in vitro tumor cell cultures (PDCs), cancer associated fibroblasts (CAFs), and patient-derived organoids (PDOrg) and has focused on addressing unmet needs in the preclinical model space including developing models from adult and pediatric patients with rare cancers. To date, NCI has created and molecularly characterized over 150 preclinical models of rare cancer including indications such as Hurthle cell carcinoma, osteosarcomas, Merkel cell carcinomas, salivary gland cancers, synovial sarcomas, and carcinosarcomas. Rare cancer models developed to date will be reviewed and their histopathologic and molecular characteristics compared to that reported in the clinical setting. A pipeline to identify fusion proteins in these rare cancers such as the Ewing sarcoma EWSR1-FLI1 fusion and NAB2-STAT6 fusions in solitary fibrous tumors (SFT) has been implemented. Four malignant peripheral nerve sheath tumors (MPNST) PDX models are available for researches; these models were developed from patients diagnosed between the ages of 37-68. At the time of model development, two patients were treatment naïve and two had prior radiotherapy. Two of the MPNST PDX models have NF1 oncogenic mutations, three have deep deletions in CDKN2A/B, and three have a mutation in either EED or SUZ12 consistent with the reported molecular characteristics of patients with MPNST. Also of clinical relevance, of two mesothelioma models available, one carries an NF2 driver mutation and the other BAP1 and LATS2 and a PDX model for Hurthle cell carcinoma has wide-spread loss of heterozygosity (LOH 80%). Models for other rare cancers are in development, including four cholangiocarcinoma PDXs with histopathologic confirmation that are currently being expanded for molecular characterization and distribution. Funded by NCI Contract No. HHSN261200800001E Citation Format: Cindy R. Timme, Sergio Y. Alcoser, Devynn Breen, John Carter, Ting-Chia Chang, Alice Chen, Li Chen, Kristen Cooley, Biswajit Das, Emily Delaney, Michelle A. Eugeni, Michelle M. Gottholm-Ahalt, Tara Grinnage-Polley, Jenna Hull, Chris Karlovich, Kimberly Klarmann, Shahanawaz Jiwani, Candace Mallow, Chelsea McGlynn, Justine Mills, Malorie Morris, Michael Mullendore, Dianne Newton, Tia Shearer, Jesse Stottlemyer, Shannon Uzelac, Thomas Walsh, P. Mickey Williams, Yvonne A. Evrard, Melinda G. Hollingshead, James H. Doroshow. Patient-derived models of rare cancers in the National Cancer Institute's patient-derived models repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3012.

Abstract The National Cancer Institute's Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) is performing a large-scale multi-year preclinical study with 39 PDX models of rare cancers (mesothelioma, MPNST, osteosarcoma, Merkel cell carcinoma, etc) treated with 56 novel therapeutic combinations in an exploratory, n-of-4 arm, study design. Combinations that show promising responses (e.g., regression or durable inhibition of tumor growth) will be repeated along with the single agent arms to determine if the response is driven by the combination or only one of the agents. In order to do this in a timely fashion, relatively speaking, the PDX tumors are serially passaged and each passage is treated with a set of 8 combinations plus relevant vehicle control(s) while in parallel enough PDXs are retained to be expanded for the next passage and drug set. Every serial passage undergoes several quality control assessments that serve as go/no-go criteria including pathology assessment, human:mouse DNA content assessment, and low pass whole genome sequencing to determine the average fraction of genome changed compared to the original donor material. If there is a QC failure, the PDX model is restarted from early passage cryo-material (passage 1-2). An additional quality control effort is to bookend the combination studies with the first set of agents to see if tumor response is similar across passages. To date, most of the models have demonstrated a high degree of stability, though a couple of models have moved toward murine content and have been restarted from early passage material so all drug combinations can be tested. DNA and RNA are retained from all passages so a full NGS evaluation can be performed at a later date. This effort has been ongoing for over a year and the first bookend studies are beginning to be tested to determine if response at first and last passage of the study are consistent with each other, given the constraints of the inherent heterogeneity of the models themselves. Single agent studies of drug combinations that demonstrated a response in 30%-50% of the models tested are also underway to determine which combinations have a more than additive effect compared to the single agents. Promising combinations will be moved forward to early phase clinical trials for these rare cancers. Funded by NCI Contract No. HHSN261200800001E Citation Format: Yvonne A. Evrard, Biswajit Das, Sergio Y. Alcoser, Suzanne Borgel, Devynn Breen, John Carter, Tiffanie Chase, Alice Chen, Lily Chen, Kristen Cooley, Emily Delaney, Raymond Divelbiss, Lyndsay Dutko, Thomas Forbes, Kyle Georgius, Michelle Gottholm-Ahalt, Tara Grinnage-Pulley, Sierra Hoffman, Chris Karlovich, Shahanawaz Jiwani, Justine Mills, Malorie Morris, Michael Mullendore, Dianne Newton, Rajesh Patidar, Gloryvee Rivera, Howard Stotler, Jesse Stottlemyer, Savanna Styers, Debbie Trail, Shannon Uzelac, Thomas Vilimas, Abigail Walke, Thomas Walsh, Nicole Walters, Peng Wang, P. Mickey Williams, Melinda Hollingshead, James H. Doroshow. Quality control efforts in a large-scale, preclinical trial of rare cancer PDXs by the National Cancer Institute's patient-derived models repository (NCI PDMR) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5056.

Background: The National Cancer Institute (NCI) has developed a Patient-Derived Models Repository (PDMR; www.pdmr.cancer.gov) of patient-derived xenografts (PDXs) with clinical annotation and comprehensive genomic characterization using whole exome sequencing (WES) and RNASeq. An in-house data analysis pipeline has been developed and validated to call germline and somatic variants and to perform transcriptional profiling in these models. There is a need to incorporate additional biomarkers into standard data analysis pipeline, including loss of heterozygosity (LOH), microsatellite instability (MSI), structure variants (SVs)/fusions and copy number variation (CNV) for identifying appropriate PDX models for preclinical drug studies. Validation of the methods used for the assessment of these and other genomic biomarkers is a crucial aspect in the development of the PDMR data analysis pipeline. Methods: WGS, WES and RNASeq were conducted on 58 PDX samples and genomic biomarkers were derived from different assays. For LOH calling, a set of ~800,000 heterozygous SNPs was first constructed from a population level genomic database (gnomAD) and a specific list of ~3000 highly heterozygous SNPs from a previous study. LOH regions were detected using Runs of Homozygosity (BCFtools/RoH) based on the genotypes of ~800,000 SNPs. Finally, percent of genomic LOH was calculated as the percent of eligible LOH regions in the whole genome. For MSI calling. mSINGS was used to assign a microsatellite instability score based on the fraction of unstable microsatellite loci. Gene fusions were detected using Tophat-fusion and Fusion-catcher from RNASeq data and Manta from WGS. CNVs were derived from WGS and WES using CNVkit. Results: Genomic biomarkers derived from WES and RNASeq were highly concordant with the ones derived from WGS. Specifically, we found 1) the percent of genomic LOH was highly correlated between WGS and WES across 52 samples with R2=0.99, where LOH% ranged from <1% to ~50% and specimens within the same models had consistent data; 2) a strong concordance rate (91%) of MSI score was observed between WGS and WES across 49 samples; 3) clinically and diagnostically relevant structural variants/fusions (e.g. FGFR3-TACC3 and EWSR1-FLI1) detected from RNASeq data can be detected and validated from WGS data; and 4) CNV genomic profiles were highly correlated between WGS and WES and amplifications/deletions in clinically relevant genes were consistently detected by the two assays. Conclusions: We observed excellent consistency between WGS, WES and RNASeq data in the assessment of percent of LOH, MSI score, SVs/fusions and CNVs. Our data analysis pipeline can accurately call genomic biomarkers from WES and RNASeq data, which facilitates the molecular characterization and prioritization of PDMR models for preclinical drug treatment. Citation Format: Li Chen, Rajesh Patidar, Biswajit Das, Chris Karlovich, Tomas Vilimas, Corinne Camalier, Vivekananda Datta, Shahanawaz Jiwani, William Walsh, Palmer Fliss, Sean McDermott, Justine N. McCutcheon, Amanda Peach, Michelle Ahalt-Gottholm, Carrie Bonomi, Kelly Dougherty, John Carter, Sergio Y. Alcoser, Tiffanie Chase, Raymond Divelbiss1, Marion Gibson, Kelly Hedger, Candace Mallow, Chelsea McGlynn, Malorie Morris, Marianne Radzyminski, Howard Stotler, Jesse Stottlemyer, Debbie Trail, Yvonne Evrard, Melinda G. Hollingshead, Mickey Williams, James H. Doroshow. Comparison of genomic biomarkers identified by the whole exome, RNASeq and whole genome sequencing pipelines developed for the PDMR [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3385.

12023 Background: Patient-derived xenografts (PDXs) are a powerful tool for cancer translational research. However, it is unclear if early passage PDXs faithfully recapitulate the molecular profiles of the corresponding patient tumors. The National Cancer Institute (NCI) has developed a Patient-Derived Models Repository (PDMR; www.pdmr.cancer.gov) of PDXs with clinical annotation and comprehensive genomic data. We used this data set, which represents 13 broad categories of tumor types, to conduct an in-depth investigation of the genomic stability of PDXs with early passaging. Methods: Tumors (biopsy or resection), including some from metastatic sites, were used to establish 211 PDX models from 206 patients. Whole Exome Sequencing and RNA-Seq were performed on 2-9 mice per model. Passages represented include the original clinical sample, P0, P1, P2, and less frequently > P2. Results: By several metrics, genomic profiles of a large majority of PDMR models were stable with early passaging: (1) transcriptome profiles of mice from different passages in a model were found to always cluster together; (2) 75% of PDXs maintained similar copy number alteration profiles compared with the original clinical sample, with no significant differences between passages; (3) the allele frequency (AF) of clinically relevant mutations remained consistent across passages, with only 20% of models having > 15% AF range from the median. Moreover, genomic features of PDMR models were broadly comparable to those in large public patient data sets. For example, melanoma models had the highest tumor mutation burden and a 55% prevalence of BRAF V600X; 11% of colon adenocarcinoma models were MSI-H, with APC (65%), TP53 (59%) and KRAS (53%) being most frequently altered. Conclusions: In this large and histologically diverse PDMR data set, PDXs exhibited genomic stability with early passaging. The molecular landscape of PDMR models is faithfully comparable to large public patient data sets. As the PDMR collection expands additional in-depth analyses will be performed. The PDMR thus represents a valuable resource for researchers interested in pre-clinical drug or other studies.