The National Cancer Institute has developed a Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) comprised of quality-controlled, early passage, and clinically-annotated patient-derived tumor xenografts (PDXs), organoids (PDOrgs), cell cultures (PDCs), and cancer associated fibroblasts (CAFs) available with genomic data to the extramural community for research use. Models are developed by the NCI PDMR in decreasing order of complexity, specifically 1) patient material can be used to develop PDXs, PDOrgs, PDCs, and CAFs, 2) PDX material for PDOrgs and PDCs, and 3) PDOrg material for PDCs, but a PDC is never used to develop a PDOrg or PDX. Eleven pairs of 22 matched PDCs have been developed in parallel from either patient, PDX, patient-derived organoid, or PDX-derived organoid tumor material and sequenced by WES and RNASeq. Genetic stability was assessed using multiple approaches including microsatellite instability (MSI) generated from MSISensor2, percentage of genomic loss of heterozygosity (LOH) using a set of ~800k heterozygous SNPs from a population level genomic database (gnomAD), pairwise Spearman correlation based on BIN level copy number (CN)/RNA expression profiles, and OncoKB annotated oncogenic/likely oncogenic variants. No systematic differences were observed within PDC pairs derived from different origins or compared to their patient and/or PDX material in MSI, LOH% and RNA expression profile but pairwise Spearman correlation (0.66-0.88) in CNV profiles were somewhat variable, likely due to low sequencing depth. In one PDC pair (299254), 3 out of 12 OncoKB annotated Indels and CNV showed opposite level of variant allele frequencies/CN when comparing a model derived from patient material to one developed from a PDX-derived organoid, possibly driven by a lineage-specific subclonal outgrowth when compared to patient and PDX data. Phenotypic characteristics of matched PDCs also overall show no major differences, though variability in growth rates and the ability to form spheroids in serum-free medium were noted. In one pair (919269), the PDC derived from patient material was able to form a cell line xenograft (CLX) in NSG mice but not the PDC developed from a patient-derived organoid. Overall, these models demonstrate a high degree of concordance at the genetic and phenotypic level when compared to the originating patient and/or PDX tumor. Though further characterization (e.g., preclinical drug testing) may be needed to define differences between matched PDC pairs, lack of access to patient tissue or failure to generate tumor cell cultures from one source of material should not hamper development of preclinical in vitro models from other patient-derived model types as long as the source-of-origin is clearly defined. Funded by NCI Contract No. HHSN261200800001E Citation Format: Cindy R. Timme, Ting-Chia Chang, Sergio Y. Alcoser, Gareth Bliss, Carrie Bonomi, Suzanne Borgel, John Carter, Alice Chen, Li Chen, Kevin Cooper, Biswajit Das, Kelly Dougherty, Lindsay Dutko, Marion Gibson, Michelle M. Gottholm-Ahalt, Tara Grinnage-Pulley, Shahanawaz Jiwani, Keegan Kalmbach, Chris Karlovich, Kimberly Klarmann, Tiffanie Chase, Michael Mullendore, Matthew Murphy, Kevin Plater, Gloryvee Rivera, Jessica Steed, Luke Stockwin, Yvonne A. Evrard, Mickey Williams, Dianne L. Newton, Melinda G. Hollingshead, James H. Doroshow. Comparing twenty-two matched patient-derived cell lines developed from either patient, PDX, or organoid tumor cell material [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 36.

Introduction: Structural variants (SVs) are a unique class of mutations which have certain therapeutic implications for the tumor. Certain SVs, such as chromosomal aneuploidy, whole-genome doubling (WGD), have specific therapeutic implications. The underlying cellular processes present in the tumor are reflected in mutational signatures. Here, we describe the landscape of chromosomal aneuploidy, WGD and mutational signatures in the National Cancer Institute’s Patient-Derived Models Repository (NCI PDMR) to facilitate the investigation of their roles in therapeutic responses of the preclinical models. Method: Chromosome arm-level aneuploidy was called by scoring at the individual arm level if >90% of the arm copy number (CN) was gained/lost based on whole-exome sequencing (WES) data. Aneuploidy score was defined as number of arms with aneuploidy. WGD was determined by derived allelic specific CN, purity and ploidy from tumor/normal matched samples and permutation test. Mutational signatures (COSMIC v3) including single base substitutions (SBS), doublet base substitutions (DBS), small insertions and deletions (ID) and CN signatures were derived using SigProfiler for specimens with somatic mutations and CNs. Results: A large fraction (85%) of patient-derived xenograft (PDX) models (N=755) have at least one arm -level aneuploidy. Certain chromosomes and arms (7, 8, 17p and 18) are more frequently aneuploid, which might be biased due to the overrepresentation of gastrointestinal cancer in the cohort. Histology specific differences were observed in the frequency of arm level aneuploidies. For example, synovial sarcoma (SYNS) and endometrioid carcinoma (UEC) have much lower level of aneuploidy than non-small cell lung cancer (NSCLC) or clear cell renal carcinoma (ccRCC) models. 61% of PDX models (N=277) have WGD, in which certain histologies have more WGD [NSCLC: 81%, head and neck squamous cell carcinomas (HNSCC): 71%] than others. Samples having WGD have a higher degree of aneuploidy and chromosomal instability. WGD and aneuploidy remain stable along the passages in 78% PDX models. Intra-model heterogeneity of WGD was observed due to lineage difference. Mutational signatures (SBS6,15,20) indicating concurrent DNA polymerase epsilon (POLE) mutation and defective DNA mismatch repair were highly enriched in microsatellite instability-high models (p<0.01, Fisher’s exact test). Among 30 PDX models where the patients had known platinum-based chemotherapy history, 40% of them had an identifiable platinum chemotherapy treatment signature (SBS31 or DBS5). Chromothripsis associated amplification signature (CN8) was enriched in models with WGD (p<0.05). Conclusion: We have characterized chromosomal aneuploidy, WGD and mutational signatures in NCI PDMR models. The models with SVs can be utilized in preclinical drug studies to understand their role in therapeutic response in patients. Citation Format: Li Chen, Biswajit Das, Ting-Chia Chang, Yvonne A. Evrard, Chris A. Karlovich, Alyssa Chapman, Brandie Fullmer, Ashley Hayes, Ruth Thornton, Nikitha Nair, Shahanawaz Jiwani, Lindsay Dutko, Kelly Benauer, Gloryvee Rivera, Corinne Camalier, John Carter, Suzanne Borgel, Tiffanie Miner, Chelsea McGlynn, Justine Mills, Shannon Uzelac, Tia Shearer, Lauren Hicks, Michelle Norris, Carley Border, Sergio Alcoser, Thomas Walsh, Michael Mullendore, Michelle Eugeni, Dianne Newton, Melinda G. Hollingshead, P. Mickey Williams, James H. Doroshow. Chromosomal aneuploidy, whole-genome doubling and mutational signatures in NCI PDMR models. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6072.

The National Cancer Institute’s Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) has developed a national repository of Patient-Derived Models (PDMs) comprised of patient-derived xenografts (PDXs), in vitro patient-derived tumor cell cultures (PDCs) and cancer associated fibroblasts (CAFs) as well as patient-derived organoids (PDOrg). These PDMs are clinically annotated with molecular information available in an easily accessible database for the extramural community. A key effort in developing these models is to develop matched models sets allowing for larger scale screening efforts using 2D or 3D models to prioritize selection of PDX models for preclinical translational research. To date, over 220 model sets with a PDX, PDOrg, and PDC from a single patient have been developed; 40 of these have matched CAF models allowing for exploration of research questions focused on tumor microenvironment. The largest model sets are in colorectal cancer (COADREAD, n=76), gynecologic cancers (n=33), pancreatic adenocarcinoma (PAAD, n=29), melanoma (MEL, n=19), and head and neck squamous cell carcinomas (HNSCC, n=17). Every model undergoes several quality control assessments that serve as go/no-go criteria including pathology assessment, STR validation, NGS concordance assessment and for PDXs, human:mouse DNA content assessment. It should be noted that not every model is successful in the development or QC phase so additional model sets with only one or two of the model types are also available for researcher requests, for example there are over 125 PDX/PDOrg matched model sets. The NCI is currently performing parallel preclinical screening of PDXs and PDCs or PDOrgs to determine the ability of the in vitro lines to predict in vivo activity. Genetic and histopathologic assessment of these matched model sets have demonstrated a high degree of stability by somatic mutation, copy number alteration (CNA) and gene expression data. Gene expression correlation analysis shows that mean of Spearman r between PDXs 0.89, between matched PDC/PDXs 0.79, and between matched PDOrg/PDXs 0.82. As expected, some variation at the gene expression level when comparing PDX to in vitro cultures by t-SNE can be observed, likely due to the differences in culture conditions. Funded by NCI Contract No. HHSN261200800001E Citation Format: Yvonne A. Evrard, Li Chen, Sergio Alcoser, Gareth Bliss, Carrie Bonomi, Suzanne Borgel, John Carter, Ting-Chia Chang, Alice Chen, Kevin Cooper, Biswajit Das, Kelly Dougherty, Lindsay Dutko, Marion Gibson, Michelle M. Ahalt-Gottholm, Tara Grinnage-Pulley, Keegan Kalmbach, Chris Karlovich, Kimberly Klarmann, Shahanawaz Jiwani, Tiffanie Miner, Michael Mullendore, Matthew Murphy, Kevin Plater, Gloryvee Rivera, Jessica Steed, Luke Stockwin, Cindy R. Timme, Dianne L. Newton, Paul Mickey Williams, Melinda G. Hollingshead, James H. Doroshow. NCI patient derived models repository: PDX, organoid and cell lines from the same patient - bridging the translational pipeline [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 40.

Background: Breast cancer is the second most common cancer in women. In 2022, it accounted for 15% of total new cancer cases and is the number four cause of death among all cancer types. To benefit from precision medicine, distinguishing molecular subtypes for prognosis and treatment in a clinical setting is essential. While intrinsic subtype classification from NGS results of patients is well established, the approach has not been comprehensively described for patient-derived xenograft (PDX) models, which have been shown to be powerful in translational research. The National Cancer Institute's Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) provides rich information in developing the method. Materials and Methods: Normalized gene expression data of breast cancer PDX and patient specimens (originators) were extracted using tximport and DESeq2 based on RNA-seq analysis. The immunohistochemistry (IHC) was used to determine the status of ER, PR and HER2 receptor expression in these tumor specimens. The PAM50 classification was performed by the R package Genefu. For further analysis, the PAM50 centroids for all 5 subtypes were also obtained from Genefu. Results: Using the RNA-seq data from 43 PDX models (180 PDX samples, 4~6 samples/model), we were able to predict subtypes at the model level based on the PAM50 method: There are 1 Luminal A subtypes, 5 Luminal B; 6 Her2; 30 Basal and 1 Normal, which encompasses the whole spectrum of PAM50. Thirty originators were also included and there are 8 Luminal A, 9 Luminal B, 2 Her2 and 11 Basal. With the matched 11 originators and the PDX models, 91% of their predicted subtypes are identical; 0.80 Cohen’s kappa was obtained, indicating high inter-rater agreement. We also described subsequent analysis with IHC data-based subtypes. For the 10 originators having IHC-based subtypes, 90% agreement was observed; for 24 PDX models with IHC data, 88% was observed. Of all the 180 PDX samples, 33 of the 43 PDX models (77%) have consistent predicted PAM50 molecular subtypes across different passages and lineages. Within the discordant samples, we observed cases such as a mixture of luminal B and Basal, which can be reasonably interpreted by AR positive signal from IHC. The discrepancy encourages further PDX subclassification from the Basal subtype. Conclusions: Using our high-throughput gene expression profiles from many patients and samples from patient derived models, we have demonstrated the feasibility of applying classic PAM50 classification algorithm, which was originally developed with microarray data, to be able to recognize the expression signals from our RNA-seq data. Overall, this study should set a primer for the identification of PDX-based subtypes, starting from breast cancer. Citation Format: Peter I. Wu, Lindsay Dutko, Shahanawaz Jiwani, Li Chen, Biswajit Das, Ting-Chia Chang, Yvonne A. Evrard, Chris A. Karlovich, Alyssa Chapman, Brandie Fullmer, Ashley Hayes, Ruth Thornton, Nikitha Nair, Kelly Benauer, Gloryvee Rivera, Thomas Forbes, John Carter, Suzanne Borgel, Tiffanie Miner, Chelsea McGlynn, Justine Mills, Shannon Uzelac, Tia Shearer, Lauren Hicks, Michelle Norris, Carley Border, Sergio Alcoser, Thomas Walsh, Michael Mullendore, Michelle Eugeni, Dianne Newton, Melinda G. Hollingshead, P. M. Williams, James H. Doroshow. Molecular subclassification of NCI PDMR breast cancer models using PAM50 gene expression signature [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2050.

Background: The National Cancer Institute’s Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) has developed a large number of patient-derived xenograft (PDX) models from a diverse set of rare cancers. These models have been genomically characterized using whole-exome sequencing (WES) and RNAseq. The resource provides a unique opportunity to explore the genomic features of rare tumor models in NCI PDMR and to understand the oncogenic processes in pre-clinical models to identify biomarkers associated with therapeutic responses. Methods: Genomic characterization was done in 4-6 PDX samples across multiple passages and lineages from each model. As the samples exhibited a high level of genomic stability within each model, consensus mutation and copy number variation (CNV), microsatellite instability (MSI), genomic loss of heterozygosity (LOH), homologous recombination deficiency score (scarHRD), and mutational signature data were generated from WES. Fusions were identified from RNASeq data using Star-Fusion and FusionInspector. Gene set enrichment analysis was conducted from the gene expression data obtained from RNAseq. Results: 1) 233 PDX models have been developed and characterized from more than 45 different rare malignancies. Most frequent cancer types are different sarcomas (n=63), head & neck squamous cell carcinoma (n=61), and malignant fibrous histiocytoma (MFH) (n=11); 2) TP53 was the most frequently altered gene, mutated in 51% of models, followed by NOTCH1 (16%) and PIK3CA (11%). In terms of CNVs, ovarian epithelial cancer (OVT) showed relatively high chromosomal instability, while uterine endometrioid carcinoma (UEC) and synovial sarcoma (SYNS) had low instability; 3) MSI-H was observed in only 7 models. Esophageal adenocarcinoma (ESCA), OVT, and cervical squamous cell carcinoma (CESC) had high scarHRD and genomic LOH scores, while both scores were low in UEC and anal squamous cell carcinoma (ANSC). COSMIC v2 mutational signature 3 is significantly associated with a high scarHRD score (p-value < 0.01, Wilcoxon rank-sum test); 4) Characteristic fusions were observed in certain sarcoma models: SS18-SSX1 and ASPSCR1-TFE3 fusions were observed in SYNS and alveolar soft part sarcoma (ASPS) models respectively. EWSR1-FLI1 fusion was present in 2 out of 3 Ewing sarcoma (ES) models. 5) Gene set enrichment analysis from RNASeq data showed that epithelial-mesenchymal transition score could accurately distinguish carcinoma from sarcoma models, confirming the divergent gene expression programs. Conclusion: Comprehensive genomic characterization of NCI PDMR models generated from rare cancers solves an unmet need in the community. It will serve as a valuable resource for translational researchers interested in pre-clinical drug development and discovery. Citation Format: Li Chen, Rini Pauly, Ting-Chia Chang, Biswajit Das, Yvonne A. Evrard, Chris A. Karlovich, Tomas Vilimas, Alyssa Chapman, Nikitha Nair, Luis Romero, Anna Lee Fong, Amanda Peach, Shahanawaz Jiwani, Nastaran Neishaboori, Lindsay Dutko, Kelly Benauer, Gloryvee Rivera, Erin Cantu, Corinne Camalier, Thomas Forbes, Michelle Gottholm-Ahalt, John Carter, Suzanne Borgel, Chelsea McGlynn, Candace Mallow, Emily Delaney, Tiffanie Miner, Michelle A. Eugeni, Dianne Newton, Melinda G. Hollingshead, P. Mickey Williams, James H. Doroshow. Genomic characterization of PDX models from rare cancer patients in the NCI Patient-Derived Models Repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 80.

Abstract Background: The National Cancer Institute's Patient-Derived Models Repository (NCI PDMR; pdmr.cancer.gov) is developing a variety of patient-derived xenograft (PDX) models for pre-clinical drug studies. All NCI PDMR models undergo quality control (QC) processes. Two unique QC challenges are: a) to assess genomic stability across PDX model passages; and b) to confirm the suitability of PDX-derived cancer associated fibroblasts (CAFs) as germline surrogates when blood is not available. Multiple bioinformatics QC assessments have been developed to measure the genomic fidelity in these PDX models using low-pass whole genome sequencing (LP-WGS) and in CAFs using whole exome sequencing (WES). Methods: LP-WGS was performed on 502 PDX samples from 38 models of rare cancer across passages 2 through 9 and WES was performed on 92 CAFs from 32 different histologies. In the QC workflow for estimating the genomic stability of passages within models, BBSplit was used for the assessment of human/mouse DNA content. CNVkit was utilized for copy number (CN) detection. The fraction of genome changed was calculated by comparing the copy numbers of each passage sample to the original patient sample. To evaluate purity of CAFs, three QC steps were constructed: a) plot of SNP variant allele frequency (ideogram); b) variant annotation using OncoKB (www.oncokb.org); c) percentage of genomic loss of heterozygosity (LOH), based on a set of ~800,000 heterozygous SNPs from a population-level genomic database (gnomAD) based on WES data. Results: PDX models showed genomic stability in CN profile when measured by LP-WGS. Human tumor DNA content remains stable ranging from 75-85% across different tiers of PDX passages from Donor +1 to Donor +6 and more. No models showed statistically significant evolution in CN profile, given the average 5 samples per model in each tier of passages. The QC workflow for CAFs generated five categories based on SNP ideograms, the presence/absence of oncogenic variants and LOH. Following observations were made: a) 72.5% CAFs were confirmed as matched diploid CAFs (category 1); b) 6.6% of CAFs were diploid and had >= 1 germline oncogenic variant - classified as category 2. CAFs in category 1&2 were suitable as germline surrogates; c) 12% of CAFs (category 3) showed putative polyploidy on SNP ideograms with no oncogenic variants and suitable for somatic variant calling; d) 8.8% of CAFs (category 4) had polyploidy and oncogenic variants present; e) LOH high CAF (category 5) - we identified a CAF with 42% LOH, later confirmed to be a tumor cell line by immunohistochemistry (IHC). Other CAFs (n=91) showed little variance, ranging from 0.6%-1.7% LOH. Conclusions: We developed standard QC workflows to evaluate genomic stability of PDX models during passaging and qualify CAFs as germline surrogates for pre-clinical study. Citation Format: Ting-Chia Chang, Li Chen, Biswajit Das, Yvonne A. Evrard, Chris A. Karlovich, Tomas Vilimas, Alyssa Chapman, Nikitha Nair, Luis Romero, Anna J. Lee Fong, Amanda Peach, Brandie Fullmer, Lindsay Dutko, Kelly Benauer, Gloryvee Rivera, Erin Cantu, Shahanawaz Jiwani, Nastaran Neishaboori, Tomas Forbes, Corinne Camalier, Luke Stockwin, Michael Mullendore, Michelle A. Eugeni, Dianne Newton, Melinda G. Hollingshead, Mickey P. Williams, James H. Doroshow. Quality control workflows developed for the NCI Patient-Derived Models Repository using low pass whole genome sequencing and whole exome sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1913.

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 Background: Well characterized patient derived xenograft models (PDX) are becoming the preferred pre-clinical tool in translational cancer research for biologic understanding of the disease, development of new treatments, and identifying potential therapy predictive and resistant biomarkers. Characterization of PDX models using a multi-omic approach is most desirable, however such efforts can be expensive and technically demanding. Immunohistochemistry (IHC) has become an indispensable ancillary tool in the accurate classification of tumor types, determination of cell of origin, identification of biologic properties like growth and metastatic potential, and evaluation for the presence/absence of therapeutic or prognostic biomarkers. Methods: 43 IHC assays were validated on the Leica Bond RX automated staining platform to identify common inconsistencies in PDX development including markers for classifying carcinomas, lymphomas, sarcomas, murine tumors, and theragnostic biomarkers. Rabbit antibodies are used rather than mouse antibodies to prevent non-specific staining of murine tissue. Results: 1. IHC evaluation of models within NCI's Patient Derived Models Repository (pdmr.cancer.gov) led to re-classification or sub-classification of 12 tumor models in accordance with WHO guidelines. 2. IHC evaluation of theragnostic markers in 8 breast cancer PDX models showed concordant results throughout passaging, suggesting stability of these biomarkers in our models. 3. We observe malignant transformation of murine or transplanted benign human tissue at a rate of 2.5%. On IHC analysis, 52% were human lymphomas, 20% were murine lymphomas, and 28% were other murine tumors. Conclusions: IHC is a rapid, cost-effective tool that can be used for accurate tumor classification, identifying subclonal outgrowth and tumor evolution, assessing stability of biomarkers and identifying malignant transformation of benign tissue. Funded by NCI Contract No. HHSN261200800001E ANTIBODYCLONEVENDORANTIBODYCLONEVENDORAndrogen Receptor[EPR1535(2)]abcamGATA3[EPR16651]abcamB-Catenin[E247]abcamGCDFP-15[EPR1582Y]abcamCD19polyclonalabcamGFAPpolyclonalDAKO/AgilentCD3polyclonalabcamHER2 ErbB2[SP3]abcamCD20[SP32]abcamKi-67[D2H10]Cell SignalingCD34[EP373Y]abcamKu80[EPR3468]abcamCD45polyclonalabcamMGMTMT3.1MilliporeCD56 (NCAM1)[EPR2566]abcamMitochondria Marker (Biotin)MTC02abcamCD68[EPR20545]abcamMyogenin[EPR4789]abcamCDX2[EPR2764Y]abcamNAPSIN A[EPR6252]abcamChromogranin A[SP12]abcamp63polyclonalGeneTexCK7 (purified)[EPR1619Y]abcamPD-1[EPR4877(2)]abcamCK19[EPR1580Y]abcamPD-L1 (CD274)RBT-PDL1LifeSpan BiosciencesCK20[EPR1622Y]abcamProgesterone Receptor[SP2]abcamCytokeratin wide spectrumpolyclonalabcamProstate Specific Antigen (PSA)[EP1588Y]abcamDesmin[Y66]abcamS100[EPR19013]abcamEBV LMP1[D24-G]abcamSmooth Muscle Actin (SMA)polyclonalabcamERG[EPR3864]abcamSynaptophysin[SP11]abcamEstrogen Receptor[SP1]abcamTTF1[SP141]abcamFOXP1monoclonalLifeSpan BiosciencesVimentin[EPR3776]abcamFOXP3(5H10L18)Invitrogen Citation Format: Lindsay Dutko, Gloryvee Rivera, Erin Cantu, Vishnuprabha Rahulkannan, Kelly Benauer, Tiffanie Chase, Emily Delaney, Jesse Stottlemyer, Chelsea McGlynn, Howard Stotler, John Carter, Suzanne Borgel, Michelle M. Gottholm Ahalt, Michelle Eugeni, Melinda Hollingshead, Yvonne Evrard, Chris Karlovich, Biswajit Das, Mickey Williams, James H. Doroshow, Shahanawaz Jiwani. Applications of immunohistochemistry in characterization of patient derived xenograft models [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 3015.

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; https://pdmr.cancer.gov) of preclinical models including patient-derived xenografts (PDX), organoids (PDOrg) and patient-derived cell cultures (PDC). Extensive clinical annotation and genomic datasets are available for these preclinical models. However, it is unclear if the molecular profiles of the corresponding patient tumors are stably propagated in these models. We have previously demonstrated that PDX models from the NCI PDMR faithfully represent the patient tumors both in terms of genomic stability and tumor heterogeneity. Here, we conduct an in-depth investigation of genomic representation of patient tumors in the PDOrgs and PDCs. Methods: PDOrgs (n=64) and PDCs (n=94) were established from tumor fragments (i.e., initiator specimens) obtained either from patient specimens or from PDX specimens of early passage. For some models (n=19), both PDOrgs and PDCs were generated from the same tumor tissue; in fewer cases (n=4), PDCs were established from organoids derived from patient specimens. Whole Exome Sequencing and RNA-Seq were performed on all PDCs and PDOrgs, and data were compared with patient specimens or early passage PDXs. Results: A majority of the PDOrgs and PDCs have stably inherited the genome of the corresponding patient specimens based on the following observations: (1) >87% of PDOrgs and PDCs maintained similar copy number alteration profiles compared with the initiator specimens of the preclinical model; (2) the variant allele frequency (VAF) of clinically relevant mutations remained consistent between the PDOrgs, PDCs, and the initiator specimens, with none of the PDCs or PDOrgs deviating by >15% VAF; and (3) clinically relevant biomarkers (e.g., MSI, LOH, mutational signatures etc.) are concordant amongst the PDOrgs, PDCs, and the initiator specimens. We observed that the majority of SNVs and indels present in the initiator specimens were also found in the PDOrgs and PDCs, suggesting almost all the tumor heterogeneity was preserved in these preclinical models. Conclusions: This large and histologically diverse set of PDOrgs and PDCs from the NCI PDMR exhibited genomic stability and faithfully represented the tumor heterogeneity observed in corresponding patient specimens. These preclinical models thus represent a valuable resource for researchers interested in pre-clinical drug or other studies. Citation Format: Biswajit Das, Yvonne A. Evrard, Li Chen, Rajesh Patidar, Tomas Vilimas, Justine N. McCutcheon, Amanda L. Peach, Nikitha V. Nair, Thomas D. Forbes, Brandie A. Fullmer, Anna J. Lee Fong, Luis E. Romero, Alyssa K. Chapman, Kelsey A. Conley, Robin D. Harrington, Shahanawaz S. Jiwani, Peng Wang, Michelle M. Gottholm-Ahalt, Erin N. Cantu, Gloryvee Rivera, Lindsay M. Dutko, Kelly M. Benauer, Vishnuprabha R. Kannan, Carrie A. Bonomi, Kelly M. Dougherty, Joseph P. Geraghty, Marion V. Gibson, Savanna S. Styers, Abigail J. Walke, Jenna E. Moyer, Anna Wade, Mariah L. Baldwin, Kaitlyn A. Arthur, Kevin J. Plater, Luke Stockwin, Matthew R. Murphy, Michael E. Mullendore, Dianne L. Newton, Melinda G. Hollingshead, Chris A. Karlovich, Paul M. Williams, James H. Doroshow. Patient-derived organoid and cell culture models from the NCI Patient-Derived Models Repository (NCI PDMR) preserve genomic stability and heterogeneity of patient tumor specimens [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 3916.

Abstract Background: Acquired Uniparental Disomy (aUPD) is relatively common in cancer. Occurrence of aUPD is more frequent in some tumor histologies (e.g., serous ovarian, colorectal) and may be relevant for choice of therapy. The Patient-Derived Models Repository (PDMR; https://pdmr.cancer.gov) developed by The National Cancer Institute (NCI) includes patient-derived xenograft (PDX) models from multiple tumor histologies with different passages and lineages. The associated clinical annotation and genomic data make it possible to assess the prevalence of aUPD in the PDMR cohort and the stability of aUPD in different passages and lineages within a PDX model. Methods: High tumor purity in the PDX specimens (after removal of mouse reads representing the stroma) enabled highly accurate assessment of loss of heterozygosity (LOH). Variants called by GATK Haplotype caller from whole exome sequencing (WES) data were used to identify segments of homozygosity using BCFtools/RoH (runs of homozygosity). The RoH segments were then intersected with the bed file for chromosome arms to get %LOH at the arm level. If %LOH on a chromosome arm was >90%, we considered the sample to have aUPD at the arm level. WES was also used to look for associations between DNA damage repair (DDR) pathway alterations and aUPD. Results: We made the following observations: a) aUPD was observed most frequently in chr18q (75/427, 17.6%) and chr3p (69/427, 16%) of PDX models; b) aUPD was observed more frequently in certain tumor histologies, e.g., clear cell renal cell carcinoma (6/8), small cell lung cancer (3/4) and non-small cell lung cancer (25/38); c) extensive aUPD was observed in 4 PDMR models (>50% of evaluated chromosome arms in these models have aUPD); d) aUPD was not observed in some tumor histologies, i.e., synovial sarcoma, uterine endometrioid carcinoma; e) in the vast majority of PDMR models (>90%), aUPD is maintained faithfully across lineages and through multiple passaging; f) subclonal aUPD events were observed in some models across different lineages; g) significant enrichment of double strand DNA break repair (DSBR) pathway alterations was observed in PDMR models without aUPD (p=0.0007, Fisher's exact test) suggesting defects in DSBR are not associated with aUPD; and h) aUPD was rarely observed in MSI-high models (1/30) suggesting mutual exclusivity of mismatch repair (MMR) pathway defects and aUPD. Conclusion: We observed a relatively high frequency of UPD in the PDMR models (at least 1 arm of a chromosome). UPD was more frequently observed in specific chromosomal arms. The frequency of aUPD was higher in some tumor histologies and absent in others. aUPD was stably maintained across passages and lineages, although some heterogeneity was observed. Our data suggest aUPD is not associated with defects in DSBR and MMR pathways. Preclinical drug studies using NCI PDMR models may suggest appropriate therapeutic options for cancers with aUPD. Citation Format: Rajesh Patidar, Li Chen, Chris A. Karlovich, Biswajit Das, Yvonne A. Evrard, Tomas Vilimas, Justine N. McCutcheon, Amanda L. Peach, Nikitha V. Nair, Thomas D. Forbes, Brandie A. Fullmer, Anna J. Lee Fong, Luis E. Romero, Alyssa K. Chapman, Kelsey A. Conley, Robin D. Harrington, Shahanawaz S. Jiwani, Peng Wang, Michelle M. Gottholm Ahalt, Erin N. Cantu, Gloryvee Rivera, Lindsay M. Dutko, Kelly M. Benauer, Vishnuprabha R. Kannan, Suzanne D. Borgel, John P. Carter, Jesse M. Stottlemyer, Tiffanie L. Miner, Devynn R. Breen, Emily T. Delaney, Chelsea A. McGlynn, Candace N. Mallow, Marianne Radzyminski, Shannon N. Uzelac, Sergio Y. Alcoser, Tara L. Grinnage-Pulley, Michelle A. Eugeni, Dianne L. Newton, Melinda G. Hollingshead, Paul M. Williams, James H. Doroshow. Genomic landscape of acquired uniparental disomy in NCI PDMR patient derived xenograft models [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 3554.

Abstract Background: Patient-derived tumor xenografts (PDX) are powerful tools to study cancer biology, cancer genomics and developmental therapeutics. A common problem in the development of PDX models is proliferation of atypical lymphocytes at the implantation site, which often overtake or limit the growth of the original tumor. This atypical lymphocyte proliferation has been described as XABLD in our PDX models. In this study, we characterized XABLD cases by morphology, immunophenotyping and genomic profiling. We hypothesize that XABLD tumors are morphologically and phenotypically similar to EBV-driven post-transplant lymphoproliferative disease (PTLD) and diffuse large B cell lymphoma (DLBCL). XABLD is a surrogate model to study EBV-driven PTLD and DLBCL. Materials and Methods: Models were generated from patient tissue collected under NCI Tissue Procurement Protocol (clinicaltrials.gov: NCT00900198) and CIRB Tissue Procurement Protocol 9846 for development of models for NCI’s Patient-Derived Models Repository (https://pdmr.cancer.gov). Specimens were implanted subcutaneously in NOD/SCID/IL2Rg null (NSG) mice and animal health was monitored throughout the study. Tumors in mice with suspected XABLD were harvested and reviewed by histology and immunohistochemical analysis for CD45, B and T cell markers, EBV status, B-cell clonality assay. All samples were also classified by the Lymph2Cx NanoString cell of origin assay and transcriptome profiling. Results: XABLD cases were found to originate from both solid tumor and circulating tumor cell implants. XABLD is a rapidly growing tumor positive for CD45, CD20, and LMP1 stains, 36 of 42 cases are strongly positive for PD-L1 stain. 39 of 42 cases exhibited an activated B cell (ABC) phenotype with evidence of elevated NF-kB signaling. Most cases were monoclonal for IGK/IGH and contained high numbers of tumor infiltrating CD8-positive T-cells with associated high mRNA expression of activated T cell markers. Conclusion: The clinical presentation, morphology and molecular characteristics of XABLD cases were similar to EBV-driven DLBCL. As the XABLD models exhibited frequent PD-L1 expression and marked infiltration of CD8-positive T cells, they may be useful for in vitro evaluation of checkpoint inhibitor response and T cell antitumor activity. Grant Support: This project has been funded in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. Citation Format: Tomas Vilimas, Gloryvee Rivera, Brandie Fullmer, Wiem Lassoued, Lindsay Dutko, Amanda Peach, Corinne Camalier, Li Chen, Rajesh Patidar, Suzanne Borgel, John Carter, Howard Stotler, Raymond Divelbiss, Jesse Stottlemyer, Michelle M. Gottholm-Ahalt, Michelle Crespo-Eugeni, Sean McDermott, William Jacob, Liqiang Xi, Pallavi Galera, Yvonne A. Evrard, Melinda G. Hollingshead, Elaine S. Jaffe, Mark Raffeld, Biswajit Das, Chris Karlovich, Vivekananda Datta, James H. Doroshow, P. Mickey Williams. Xenograft-associated B cell lymphoproliferative disease (XABLD) as a surrogate model to study Epstein-Barr virus (EBV) driven B cell Diseases [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 1056.

Abstract Background: Patient-derived tumor xenografts (PDX) are powerful tools to study cancer biology, cancer genomics and developmental therapeutics. A common problem in the development of PDX models is proliferation of atypical lymphocytes at the implant site, which often overtake or limit the growth of the original tumor. This atypical proliferation has been described as Xenograft-Associated B cell Lymphoproliferative Disease (XABLD) in our PDX models. In this study, we characterized XABLD cases by morphology, immunophenotyping and genomic profiling. We hypothesize that XABLD tumors are morphologically and phenotypically similar to EBV-driven lymphoma of the elderly and may function as a surrogate model for that lymphoma. Materials and Methods: Models were generated from patient tissue collected under NCI Tissue Procurement Protocol (clincialtrials.gov: NCT00900198) and CIRB Tissue Procurement Protocol 9846 for development of models for NCI's Patient-Derived Models Repository (https://pdmr.cancer.gov). Specimens were implanted subcutaneously in NOD/SCID/IL2Rg null (NSG) mice and animal health was monitored throughout the study. Tumors in mice with suspected XABLD were harvested and reviewed by histology and immunohistochemical analysis for CD45, B and T cell markers and EBV status. All samples in this study were classified by the Lymph2Cx NanoString cell of origin assay and transcriptome profiling. Results: XABLD-associated mice had rapidly growing CD45-positive tumors at the implantation site. Histopathological features were consistent with EBV-driven diffuse large B-cell lymphoma (DLBCL) primarily of polymorphous subtype. All XABLD specimens were diffusely positive for CD20 and EBNA, and most cases contained tumor infiltrating CD8-positive T-cells. Out of 42 cases, 36 were PD-L1-positive and 26 were PD-1-positive by IHC. 39 cases exhibited an activated B cell (ABC) phenotype, which is predominant in EBV-positive DLBCL. Conclusion: XABLD development has been seen across multiple patient histologies from both solid tumor and circulating tumor cells tissues of origin. The clinical presentation, morphology and molecular characteristics of XABLD cases were similar to EBV-driven DLBCL. As DLBCL is an aggressive disease with limited treatment options, our early-passage XABLD models may be useful in the preclinical evaluation of new therapies for EBV-positive DLBCL. Grant Support: This project has been funded in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. Citation Format: Tomas Vilimas, Gloryvee Rivera, Brandie Fullmer, Wiem Lassoued, Lindsay Dutko, William Walsh, Amanda Peach, Corinne Camalier, Li Chen, Rajesh Patidar, Suzanne Borgel, John Carter, Howard Stotler, Raymond Divelbiss, Jesse Stottlemyer, Margaret Defreytas, Michelle M. Gottholm-Ahalt, Michelle A. Crespo-Eugeni, Sean McDermott, Yvonne A. Evrard, Melinda G. Hollingshead, Biswajit Das, Chris Karlovich, Vivekananda Datta, James H. Doroshow, P. Mickey Williams. Xenograft-associated B cell lymphoproliferative disease as a surrogate model to study Epstein-Barr virus (EBV) driven lymphoma of the elderly [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1038.

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.