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There is a major need in oncology drug development to establish predictive preclinical assays with high translational relevance to patient responses. The National Cancer Institute’s Patient-Derived Models Repository (https://pdmr.cancer.gov) offers a collection of highly characterized models from a variety of cancer types including rare and recalcitrant malignancies and tumors from patients of diverse ancestry. This collection includes matched sets of patient-derived cell lines, organoids, and xenografts (PDXs), which allows comparisons of drug responses from in vitro and in vivo assays performed with the same patient-derived tumor model. A high-throughput screen was conducted using matched sets of patient-derived organoids and cell lines. Patient-derived cell lines were grown as 3D multicellular spheroids mixed with endothelial cells and mesenchymal stem cells. The patient-derived organoids were 100% tumor cells and were plated in 5% basement membrane extract supplemented with growth factors and cytokines. All drugs were tested at concentrations up to their reported clinical Cmax values and cell viability for individual drug treatments and drug combinations were assayed using CellTiter-Glo 3D after seven days drug exposure. Prior to the endpoint viability measurements, growth curves for spheroid median volume and organoid median surface area were calculated from a series of non-invasive brightfield images collected every 12 hours. For some drug combinations, differential responses were observed between the matched organoids and multicellular spheroids, potentially reflecting the contribution of the stromal component in the spheroids. Overall, the drug-dependent growth responses observed from the two 3D in vitro models (i.e., multicellular spheroids and organoids) were frequently comparable to those observed in vivo from PDXs. For example, the in vitro activities of several drug combinations including: BAY1895344 + temozolomide, erlotinib + cediranib, entinostat + talazoparib, and selumetinib + abemaciclib, demonstrated good agreement with the responses observed in vivo. However, among the drug combinations tested ixazomib + panobinostat showed the greatest cytotoxicity in vitro but had no activity in the matched PDX models. The availability of matched patent-derived cell lines, organoids and PDXs provides an opportunity to learn about the features of assay methodologies and data analyses that influence the successful translation of preclinical results between in vitro and in vivo systems. The results of this study are encouraging, but also highlight discrepancies that will be important to investigate, understand and address in order to improve translational capacity of future assays. This project was funded in part with federal funds from the NCI, NIH, under contract no. HHSN261201500003I. Citation Format: Thomas S. Dexheimer, Thomas Silvers, Rene Delosh, Russell Reinhart, Chad Ogle, Zahra Davoudi, Eric Jones, Debbie Trail, John Carter, Justine Mills, Kyle Georgius, Howard Stotler, Michelle Norris, Shannon Uzelac, Suzanne Borgel, Tiffanie Minor, Luke Stockwin, Michael Mullendore, Kevin Plater, Keegan Kalmbach, Jessica Steed, Matthew Murphy, Gareth Bliss, Carrie Bonomi, Kelly Dougherty, Marion Gibson, Kevin Cooper, Dianne Newton, Cindy R. Timme, Yvonne A. Evrard, Melinda G. Hollingshead, Nathan P. Coussens, Ralph E. Parchment, James H. Doroshow, Beverly A. Teicher. Combination therapies in matched 3D in vitro and in vivo preclinical models of rare and recalcitrant cancers from the National Cancer Institute’s Patient-Derived Models Repository. [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 5720.

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.

NCI’s Patient-Derived Models Repository (NCI PDMR; pdmr.cancer.gov) has developed a variety of patient-derived models across most solid tumor histologies. These models are early passage, genetically characterized and associated with limited patient treatment history. As part of this effort, the NCI PDMR worked with the University of Nebraska Medical Center Rapid Autopsy Program and Johns Hopkins University Legacy Gift Rapid Autopsy Program to develop and optimize methods for collection, processing, and shipping of autopsy tumor material to maintain viability during overnight transit for use in patient-derived model development. These methods have been successfully transferred to two other participating rapid autopsy programs. To date, 412 autopsy tumor samples from 76 consented patients have been received for model development; 348 shipped overnight in media for next day implantation into NSG host mice and 64 cryopreserved prior to shipping for a comparative assessment of take-rate versus fresh tumor samples. On average 3-8 tumor samples, primary and metastatic, were collected post-mortem from the truncal region of each patient. Histologies include Pancreatic adenocarcinoma (n=43), Cholangiocarcinoma (n=6), Prostate adenocarcinoma (n=6), and 21 others with 1-2 patients/histology. The overall age range of enrolled patients was 5-88yo. The post-mortem cold ischemic time for collections ranged from 1.5 to 20 hours with a median of 3h (avg. 3.75h; outlier >11h removed). Collection methods were optimized to reduce contamination and increase viability of tumor tissues for successful PDX model generation. Of 348 fresh tumor samples collected to date, 69 PDX models from 33 patients have been generated (range 1-6 models/patient) and an additional 55 samples are being monitored for growth in passage 0. The largest public single-patient PDX model sets are for melanoma (899932-113-R, n=6) and two pancreatic adenocarcinomas (521955-158-R, n=6, 217524-143-R, n=4). Important methods for reducing contaminants in autopsy tumor material include sterilization of the surface of the body prior to opening, use of sterile fields, using separate sterile instruments for each collection site, rinsing the surface of the resected tumor tissue, and use of antibiotics in the collection media. The now established SOPs are publicly available on the NCI PDMR website (pdmr.cancer.gov/sops). We recommend incorporating as many of these methods as possible within the limitations of your individual site. Of the 69 models developed to date, 48 are publicly available from the NCI PDMR while the rest are undergoing quality control process prior to public release. Models developed from autopsy material provide a research tool to investigate tumor evolution, differences between primary and metastatic lesions, and assessment of differences in therapeutic response based on differences in the tumor biology. Citation Format: Yvonne A. Evrard, Michelle Eugeni, Michelle Ahalt-Gottholm, Carrie Bonomi, Suzanne Borgel, Thomas C. Caffrey, John Carter, Ting-Chia Chang, Li Chen, Kevin Cooper, Biswajit Das, Emily Delaney, Kelly Dougherty, Eleonora Duregon, Stephanie Ecker, Joe Geraghty, Marion Gibson, Lauren Hicks, Jenna Hull, Sharon Int Veldt, Shahanawaz Jiwani, Chris A. Karlovich, Jade Loewenstein, Candace Mallow, Chelsea McGlynn, Justine Mills, Tiffanie Miner, Jowaly Schneider, Tia Shearer, Savanna Styers, Shannon Uzelac, Paul Grandgenett, Michael Hollingsworth, Jody E. Hooper, P. Mickey Williams, Melinda Hollingshead, James H. Doroshow. Method development for generation of PDX models from rapid autopsy samples for 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 3120.

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.

Cancer organoids are heterogeneous 3D cellular clusters with complexities that mimic some characteristics of tumors in situ. Thus, assays performed with cancer organoids might enable better predictions of in vivo drug responses than those performed with cell monolayers. The National Cancer Institute (NCI) is developing a national repository of Patient-Derived (PD) models comprised of clinically annotated and molecularly characterized PD xenografts (PDXs), PD tumor cell lines (PDCs), and PD cancer organoids (PDOrgs) (https://pdmr.cancer.gov/). We evaluated the therapeutic activity of a panel of FDA-approved and investigational anticancer agents, including carboplatin, gemcitabine, paclitaxel, SN38, 5-FU, adavosertib, erlotinib, trametinib, and vemurafenib, against a cohort of PDCs, PDOrgs, and PDXs from solid tumors including colon, gastroesophageal, head and neck, NSCLC, pancreatic, bladder, and uterine cancers. Our goal was to investigate whether drug sensitivities determined using PDCs and PDOrgs correlate with responses observed in the matching PDXs. Cultures were exposed to anticancer agents at concentrations ranging from 1 pM to 100 µM for periods of 4 or 6 days. The data indicated that the GI50 values for PDOrgs were in overall agreement with in vivo PDX drug responses measured as relative median to event free survival (RMEFS), where an event is the median time (days) from treatment initiation to tumor volume quadrupling, calculated as median time to tumor volume quadrupling for treated animals/median time to tumor volume quadrupling for control animals. For both paclitaxel and trametinib, responses in PDOrgs, from most sensitive to most resistant, were similar to the corresponding PDXs. Drug sensitivities determined in PDC monolayers were less clearly related to in vivo PDX responses; particularly for PDCs treated with carboplatin, gemcitabine, and SN-38. This work is part of a larger effort to provide a rigorous comparison between fully characterized and annotated PDCs-PDOrgs-PDXs to assess the value of different in vitro model systems for the prediction of PDX drug responses. This research was supported [in part] by the Developmental Therapeutics Program in the Division of Cancer Treatment and Diagnosis of the National Cancer Institute. Funded by NCI Contract No. HHSN261200800001E. Citation Format: Petreena Campbell, Curtis Hose, Lara El Touny, Erik Harris, John Connelly, Carrie Bonomi, Kelly Dougherty, Savanna Styers, Abigail Walke, Jenna Moyer, Mariah Baldwin, Anna Wade, Michael Mullendore, Kaitlyn Arthur, Matthew Murphy, Kevin Plater, Marion Gibson, Joseph Geraghty, Michelle Gottholm-Ahalt, Tara Grinnage-Pulley, Tiffanie Chase, John Carter, Howard Stotler, Debbie Trail, Luke Stockwin, Dianne Newton, Yvonne Evrard, Melinda Hollingshead, Ralph E. Parchment, Nathan P. Coussens, Beverly A. Teicher, James H. Doroshow, Annamaria Rapisarda. Evaluation of patient-derived cell lines and cancer organoids for the prediction of drug responses in 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 3913.

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 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.

The National Cancer Institute (NCI) has developed a Patient-Derived Models Repository (PDMR) comprised of 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). NCI has focused on generating models to complement existing PDX collections and address unmet needs in the preclinical model space. These models are offered to the extramural community for research use (https://pdmr.cancer.gov), along with clinical annotation and molecular information (whole exome sequence, gene expression using RNASeq), via a publicly accessible database. Currently, over 200 PDX models, 50 PDC models, and 100 CAF models are available for distribution to the US research community. Approximately 50 PDOrg models will be released in early 2019. As part of its rare cancer initiative, the NCI is also targeting the collection of infrequently-observed tumor histologies to advance both biological investigations and drug development efforts for under-studied malignancies. Comparison of matched models, models where more than one model type are available (e.g., PDX and PDC), demonstrate a high degree of concordance across the model types. Genetic stability across the models is assessed using multiple criteria including genetic assessment of CNVs and presence of driver mutations. Optimal CNV assessment uses whole exome sequence data corrected for cellularity in the patient specimen using germline reads and corrected for cellularity in the PDX specimens by subtraction of the mouse reads. Histomorphologic comparison of PDXs and cell line xenografts (CLX) generated from in vitro PDCs and PDOrgs also overall show a high degree of concordance, though loss of features and dedifferentiation can be observed in some models. Overall these models demonstrate a high degree of conservation at the genetic and pathologic level when compared to the patient tumor. These models can provide researchers the ability to perform high- or mid-throughput screening in 2D or 3D culture followed by targeted selection of PDX models for in vivo studies. Funded by NCI Contract No. HHSN261200800001E Citation Format: Yvonne A. Evrard, Dianne Newton, Biswajit Das, Sergio Y. Alcoser, Kaitlyn Arthur, Mariah Baldwin, Carrie Bonomi, Suzanne Borgel, John Carter, Tiffany Chase, Alice Chen, Lily Chen, Nikki E. Craig, Vivekananda Datta, Emily Delaney, Raymond Divelbiss, Kelly Dougherty, Thomas Forbes, Kyle Georgius, Joe Geraghty, Marion Gibson, Michelle M. Gottholm-Ahalt, Tara Grinnage-Pulley, Kelly Hedger, Sierra Hoffman, Chris Karlovich, Wiem Lassoued, Shahanawaz Jiwani, Candace Mallow, Chelsea McGlynn, Mallorie Morris, Jenna Moyer, Mike Mullendore, Matt Murphy, Rajesh Patidar, Kevin Plater, Marianne Radzyminski, Nicki Scott, Luke H. Stockwin, Howard Stotler, Jesse Stottlemyer, Savanna Styers, Debbie Trail, Tomas Vilimas, Anna Wade, Abigail Walke, Thomas Walsh, P. Mickey Williams, Melinda G. Hollingshead, James H. Doroshow. Comparison of PDX, PDC, and PDOrg models from the National Cancer Institute’s Patient-Derived Models Repository (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 4524.

The National Cancer Institute (NCI) has developed a Patient-Derived Models Repository (PDMR) comprised of quality-controlled, early-passage, clinically-annotated patient-derived xenografts (PDXs) to serve as a resource for public-private partnerships and academic drug discovery efforts. These models are offered to the extramural community for research use (https://pdmr.cancer.gov/), along with clinical annotation and molecular information (whole exome sequence, RNASeq), which is available in a publicly accessible database. The PDMR was established by NCI at the Frederick National Laboratory for Cancer Research (FNLCR) in direct response to discussions with academia and industry; the oncology community's highest priority need was preclinical models that more faithfully reflect the patient's tumor and are associated with the patient's treatment history. NCI has focused on generating models to complement existing PDX collections and address unmet needs in the preclinical model space. The PDMR generates the majority of its PDXs by subcutaneous implantation except for those histologies having better success rates in either orthotopic or alternate implant sites. All SOPs and quality-control standards developed by the PDMR as well as those shared by collaborators are posted to a public web site that houses the PDMR database. In May 2017, the public website (https://pdmr.cancer.gov/) went live with its first 100 models from histologies including pancreatic, colorectal, renal, head and neck, and lung squamous cell cancers as well as melanoma and adult soft tissue sarcomas. In early 2018, the PDMR will begin releasing models from gynecological cancers, small cell lung cancer, chondro/osteo sarcomas, lung adenocarcinoma, and squamous cell skin and Merkel cell carcinomas. In addition, wherever available germline sequence and somatic variant calls will be added to the existing molecular characterization data for each model. NCI has also increased its focus on creating PDXs from racial and ethnic minorities through several funding opportunities. The overall goal of NCI is to create a long-term home for at least 1000 models such that sufficient biological and clinical diversity is represented to allow researchers to ask questions regarding the impact of tumor heterogeneity on target qualification or clinical response, whether PDXs more faithfully represent the human tumor for pharmacodynamic assay and predictive marker development, or if adequately powered preclinical PDX clinical trials can lead to better evaluation of therapies for future clinical use. Moving forward the PDMR plans to distribute in vitro, early-passage tumor cell cultures and cancer-associated fibroblasts as well as releasing PDX drug response data for a panel of FNA-approved therapeutic agents. Funded by NCI Contract No. HHSN261200800001E Citation Format: Yvonne A. Evrard, Michelle M. Gottholm Ahalt, Sergio . Y. Alcoser, Kaitlyn Arthur, Mariah Baldwin, Linda L. Blumenauer, Carrie Bonomi, Suzanne Borgel, Elizabeth Bradtke, Corinne Camalier, John Carter, Tiffanie Chase, Alice Chen, Lily Chen, Donna W. Coakley, Nicole E. Craig, Biswajit Das, Vivekananda Datta, Jordyn Davidson, Margaret R. DeFreytas, Emily Delaney, Michelle A. Eugeni, Raymond Divelbiss, Palmer Fliss, Thomas Forbes, Marion Gibson, Tara Grinnage-Pulley, Sierra Hoffman, Lilia Ileva, Paula Jacobs, Franklyn Jimenez, Joseph Kalen, Catherine Karangwa, Chris Karlovich, Candace Mallow, Chelsea McGlynn, Jenna E. Moyer, Michael Mullendore, Dianne L. Newton, Nimit Patel, Rajesh Patidar, Kevin Plater, Marianne Radzyminski, Lisa Riffle, Larry Rubinstein, Luke H. Stockwin, Mickey Williams, Melinda G. Hollingshead, James H. Doroshow. The National Cancer Institute's patient-derived models repository (PDMR) [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 986.

Background: Patient-derived Xenograft (PDX) models are being widely used in preclinical studies to identify biomarkers of drug response and to enhance our understanding of cancer biology. Since patients with metastatic cancer have both intra-tumor and inter-site heterogeneity, PDX models generated from different tumor sites may provide a way to study tumor heterogeneity. Characterization of the genomic landscape in these models may also provide better insights into treatment response or resistance. It is rare to have multiple PDX models generated from a single patient over multiple time points during a treatment trajectory. Here, we report the genomic profiles of PDX models generated from 4 distinct tissue specimens over a 7-month period from a patient with metastatic colon adenocarcinoma. The first 2 PDX models were generated from circulating tumor cells (CTCs) and a liver biopsy prior to treatment with a combination pan-AKT + MEK inhibitor regimen. A third PDX model was generated from a liver biopsy while on-treatment and a fourth from an adrenal gland resection at progression. Clinically, all reported metastatic sites, except the adrenal gland, responded to the combination therapy. Results: Genomic characterization of the specimens obtained from these 4 PDX models led to the following observations: 1) PIK3CA E545K and KRAS G12D are present in all the specimens tested for all 4 models and are likely truncal driver mutations; 2) exclusive inter-model SNVs (single nucleotide variants) were identified, and may be model-specific variants representing inter-site heterogeneity in the patient; 3) variants involved in known resistance mechanisms to MEK inhibition were not present in any specimens; 4) overexpression of AKT3 has been reported as a resistance mechanism to a pan-AKT inhibitor and was observed in the adrenal tissue from the patient but not in any other PDX model derived from this patient; 5) intra-model and inter-model heterogeneity in whole genome CNV (copy number variant) profiles was observed between individual PDXs obtained from the pre-treatment CTC-derived model and the on-treatment liver biopsy model. Interestingly, one of the PDXs from the CTC-derived model presented a sub-clonal tumor fraction closely related to the on-treatment liver biopsy model. The multiple inter-model CNV profiles in the liver biopsy derived PDX models represent temporal heterogeneity within a tissue. Conclusions: We observed genomic heterogeneity in PDXs generated from specimens from a patient with metastatic colon adenocarcinoma. Both truncal and sub-clonal variants were identified representing various tumor fractions in these models. This case study illustrates how genomic profiling of multiple tumor sites at different times during course of treatment can provide insight into the complexity of tumor heterogeneity and tumor evolution in patients with metastatic disease. Citation Format: Biswajit Das, Chris Karlovich, Corrine E. Camalier, Rajesh Patidar, Li Chen, Vivekananda Datta, William D. Walsh, Sean P. McDermott, Tomas Vilimas, Palmer Fliss, Justine N. McCutcheon, Amanda Peach, Michelle Ahalt-Gottholm, Carrie Bonomi, Kelly Dougherty, John Carter, Shivaani Kummar, Yvonne A. Evrard, Melinda G. Hollingshead, Paul M. Williams, James H. Doroshow. PDX models generated from a patient with metastatic colon adenocarcinoma display both spatial and temporal tumor heterogeneity [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 1039.

Lentiviral vectors (LVs) are capable of labeling a broad spectrum of cell types, achieving stable expression of transgenes. However, for in vivo studies, the duration of marker gene expression has been highly variable. We have developed a series of LVs harboring different promoters for expressing reporter gene in mouse cells. Long-term culture and colony formation of several LV-labeled mouse melanoma cells showed that promoters derived from mammalian house-keeping genes, especially those encoding RNA polymerase II (Pol2) and ferritin (FerH), provided the highest consistency for reporter expression. For in vivo studies, primary B16BL6 mouse melanoma were infected with LVs whose luciferase-green fluorescence protein fusion gene (Luc/GFP) was driven by either Pol2 or FerH promoters. When transplanted into syngeneic C57BL/6 mice, Luc/GFP-labeled B16BL6 mouse melanoma cells can be monitored by bioluminescence imaging in vivo, and GFP-positive cells can be isolated from the tumors by fluorescence-activated cell sorter. Pol2-Luc/GFP labeling, while lower in activity, was more sustainable than FerH-Luc/GFP labeling in B16BL6 over consecutive passages into mice. We conclude that Pol-2-Luc/GFP labeling allows long-term in vivo monitoring and tumor cell isolation in immunocompetent mouse melanoma models.

Preclinical therapeutic assessment currently relies on the growth response of established human cell lines xenografted into immunocompromised mice, a strategy that is generally not predictive of clinical outcomes. Immunocompetent genetically engineered mouse (GEM)-derived tumor allograft models offer highly tractable preclinical alternatives and facilitate analysis of clinically promising immunomodulatory agents. Imageable reporters are essential for accurately tracking tumor growth and response, particularly for metastases. Unfortunately, reporters such as luciferase and GFP are foreign antigens in immunocompetent mice, potentially hindering tumor growth and confounding therapeutic responses. Here we assessed the value of reporter-tolerized GEMs as allograft recipients by targeting minimal expression of a luciferase-GFP fusion reporter to the anterior pituitary gland (dubbed the "Glowing Head" or GH mouse). The luciferase-GFP reporter expressed in tumor cells induced adverse immune responses in wildtype mouse, but not in GH mouse, as transplantation hosts. The antigenicity of optical reporters resulted in a decrease in both the growth and metastatic potential of the labeled tumor in wildtype mice as compared to the GH mice. Moreover, reporter expression can also alter the tumor response to chemotherapy or targeted therapy in a context-dependent manner. Thus the GH mice and experimental approaches vetted herein provide concept validation and a strategy for effective, reproducible preclinical evaluation of growth and response kinetics for traceable tumors.

We have previously shown that topotecan, a topoisomerase I poison, inhibits hypoxia-inducible factor (HIF)-1α protein accumulation by a DNA damage-independent mechanism. Here, we report that daily administration of topotecan inhibits HIF-1α protein expression in U251-HRE glioblastoma xenografts. Concomitant with HIF-1α inhibition, topotecan caused a significant tumor growth inhibition associated with a marked decrease of angiogenesis and expression of HIF-1 target genes in tumor tissue. These results provide a compelling rationale for testing topotecan in clinical trials to target HIF-1 in cancer patients.

The in vivo hollow fibre model was developed by the National Cancer Institute (NCI) in the United States of America (USA) at a time when the number of potential anti-cancer drugs arising from in vitro screening efforts exceeded the available capacity for testing in traditional xenograft models. Updated analysis of the predictive value of the hollow fibre model continues to indicate that the greater the response in the hollow fibre assay, the more likely it is that activity will be seen in subsequent xenograft models. The original 12 cell line hollow fibre panel has been supplemented with histology-specific panels, and we begin here to analyse their utility in predicting activity in subsequent in vivo models. The key goal of using the hollow fibre model as a way to decrease the cost, both financial and in the number of animals used, to evaluate initial evidence of a compound's capacity to act across physiological barriers continues to be reinforced with our enlarging experience.

The National Cancer Institute (NCI) has developed a Patient-Derived Models Repository (PDMR) comprised of quality-controlled, early-passage, clinically-annotated patient-derived xenografts (PDXs) to serve as a resource for public-private partnerships and academic drug discovery efforts. These models are offered to the extramural community for research use (https://pdmr.cancer.gov/), along with clinical annotation and molecular information (whole exome sequence, RNASeq), which is available in a publicly accessible database. The PDMR was established by NCI at the Frederick National Laboratory for Cancer Research (FNLCR) in direct response to discussions with academia and industry; the oncology community9s highest priority need was preclinical models that more faithfully reflect the patient9s tumor and are associated with the patient9s treatment history. NCI has focused on generating models to complement existing PDX collections and address unmet needs in the preclinical model space. The PDMR generates the majority of its PDXs by subcutaneous implantation except for those histologies having better success rates in either orthotopic or alternate implant sites. All SOPs and quality-control standards developed by the PDMR as well as those shared by collaborators are posted to a public web site that houses the PDMR database. In May 2017, the public website (https://pdmr.cancer.gov/) went live with its first 100 models from histologies including pancreatic, colorectal, renal, head and neck, and lung squamous cell cancers as well as melanoma and adult soft tissue sarcomas. In early 2018, the PDMR will begin releasing models from gynecological cancers, small cell lung cancer, chondro/osteo sarcomas, lung adenocarcinoma, and squamous cell skin and Merkel cell carcinomas. In addition, wherever available germline sequence and somatic variant calls will be added to the existing molecular characterization data for each model. NCI has also increased its focus on creating PDXs from racial and ethnic minorities through several funding opportunities. The overall goal of NCI is to create a long-term home for at least 1000 models such that sufficient biological and clinical diversity is represented to allow researchers to ask questions regarding the impact of tumor heterogeneity on target qualification or clinical response, whether PDXs more faithfully represent the human tumor for pharmacodynamic assay and predictive marker development, or if adequately powered preclinical PDX clinical trials can lead to better evaluation of therapies for future clinical use. Moving forward the PDMR plans to distribute in vitro, early-passage tumor cell cultures and cancer-associated fibroblasts as well as releasing PDX drug response data for a panel of FNA-approved therapeutic agents. Funded by NCI Contract No. HHSN261200800001E Citation Format: Yvonne A. Evrard, Michelle M. Gottholm Ahalt, Sergio . Y. Alcoser, Kaitlyn Arthur, Mariah Baldwin, Linda L. Blumenauer, Carrie Bonomi, Suzanne Borgel, Elizabeth Bradtke, Corinne Camalier, John Carter, Tiffanie Chase, Alice Chen, Lily Chen, Donna W. Coakley, Nicole E. Craig, Biswajit Das, Vivekananda Datta, Jordyn Davidson, Margaret R. DeFreytas, Emily Delaney, Michelle A. Eugeni, Raymond Divelbiss, Palmer Fliss, Thomas Forbes, Marion Gibson, Tara Grinnage-Pulley, Sierra Hoffman, Lilia Ileva, Paula Jacobs, Franklyn Jimenez, Joseph Kalen, Catherine Karangwa, Chris Karlovich, Candace Mallow, Chelsea McGlynn, Jenna E. Moyer, Michael Mullendore, Dianne L. Newton, Nimit Patel, Rajesh Patidar, Kevin Plater, Marianne Radzyminski, Lisa Riffle, Larry Rubinstein, Luke H. Stockwin, Mickey Williams, Melinda G. Hollingshead, James H. Doroshow. The National Cancer Institute9s patient-derived models repository (PDMR) [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 986.

Cancer Organoids are discrete multicellular structures that recapitulate tumor microanatomy (1). These reagents can be generated by extended culture of partially or fully dissociated tumor samples in three-dimensional matrices. By maintaining tumor and accessory cells in an appropriate context, they provide a biosimilar platform for studying disease pathogenesis and cellular pharmacology (2). Similarly, cancer organoid culture is useful for propagating slow growing tumors or those requiring heterotypic cell-cell interactions. Here, preliminary data will be presented regarding generation of organoids from diverse tumor types as part of the NCI patient-derived models (PDM) initiative. This initiative aims to develop a national repository of patient-derived cancer models (PDMs) consisting of clinically annotated patient-derived xenografts (PDXs) and patient-derived tumor cell cultures (PDCs) prepared from primary and metastatic tumors (3). A standardized panel of different organoid media formulations was constructed to optimize culture conditions for disease subsets. Using this approach, organoids were generated for colon, prostate, pancreatic, breast, melanoma, NSCLC, and bladder tumors. Although some samples were refractory to organoid generation, in several instances, samples that failed to generate 2D cultures thrived as organoids. A further finding was that direct implantation of organoid cultures was an efficient means of generating xenografts. Indeed, work will be presented detailing the exact number of organoids required to establish xenograft tumors. Protocols were developed for routine culture, passaging and long-term storage in liquid nitrogen. Similarly, organoids were amenable to characterization by FACS analysis, ICC/IHC and qRT-PCR to evaluate metrics such as tumor type, histological similarity with patient tumor, cell viability, percentage stroma and whether mouse cells persist in PDX-derived organoids. In summary, growth, expansion, analysis and storage of tumor organoids is feasible for a wide range of tumor types. Importantly, for certain samples, generation of cancer organoids appears to be a useful intermediary step for subsequent PDX model and 2D culture generation. Funded by NCI Contract No. HHSN261200800001E. References: 1. Baker LA, Tiriac H, Clevers H, Tuveson DA. Modeling pancreatic cancer with organoids. Trends Cancer. 2016;2:176-90. 2. Cantrell MA, Kuo CJ. Organoid modeling for cancer precision medicine. Genome Med. 2015;7. 3. Doroshow J, Hollingshead M, Evrard Y, Williams M, Datta V, Das B, et al. NCI patient derived models repository. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA). Mol Cancer Ther. 2015;14(12 Suppl 2). Citation Format: Luke H. Stockwin, Jenna Moyer, Anna Wade, Carrie Bonomi, Kelly Dougherty, John Carter, Jesse Stottlemeyer, Kaitlyn Arthur, Vivekananda Datta, Lindsay Dutko, Michael Mullendore, James H. Doroshow, Melinda G. Hollingshead, Dianne L. Newton. Establishing a platform for the generation of organoids from diverse tumor types as part of the NCI patient-derived models (PDM) initiave [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4827. doi:10.1158/1538-7445.AM2017-4827

A series of compounds related to oxathiin carboxanilide has been identified as nonnucleoside reverse transcriptase inhibitors (NNRTIs) of HIV-1, and structure-activity relationships have been described (Buckheit RW, et al.: Antimicrob Agents Chemother 1995;39:2718-2727). Three new analogs (UC040, UC82, and UC781) inhibited laboratory and clinical isolates of HIV-1, including isolates representative of the various clades of HIV-1 found worldwide, in both established and fresh human cells. Virus isolates with the amino acid changes L100I, K103N, V106I, and Y181C in the reverse transcriptase were partially resistant to these compounds. However, UC781 inhibited these virus isolates at low nontoxic concentrations, presenting a broad in vitro therapeutic index. As with other NNRTIs, each of the compounds synergistically interacted with AZT to inhibit HIV-1 replication. UC781 possesses a favorable pharmacokinetic profile in mice with a high level of oral bioavailability. Plasma concentrations reached maximum levels within 2 to 4 hr of oral administration and remained in excess of those required for in vitro anti-HIV activity for at least 24 hr after a single oral dose. When evaluated in a murine hollow fiber implant model of HIV infection, UC781 dosed orally or parenterally was able to suppress HIV replication completely in this model system, providing evidence of the in vivo efficacy of the compound.

Cancer-related deaths are caused principally by recurrence and metastasis arising from residual disease, whose therapeutic responses has been suggested to be substantially different from primary tumors. However, experimental animal models designed for evaluating the therapeutic responses of residual disease are mostly lacking. To overcome this deficiency, we have developed a preclinical model that recapitulates the progression for advanced non-small cell lung cancer (NSCLC). An archived Lewis Lung Carcinoma mouse tumor, propagated only through serial in vivo transplantation and never adapted to cell culture, was stably labeled using lentivirus-encoded biomarkers, consistently expressed through an RNA polymerase II promoter. Labeled tumors were inoculated into syngeneic immunocompetent mice to ensure superior tumor-host interactions. Primary tumors were resected upon reaching a predetermined size, following by treatment in a setting akin to post-surgical first-line adjuvant chemotherapy and routine imaging to monitor the progression of pulmonary metastasis. We discovered that efficacious treatment, instead of reducing disease growth rates, significantly prolonged disease-free survival (DFS) and overall survival (OS). As in the clinic, cisplatin-based regimes were more effective in this model. However, the response of metastases to specific agents could not be predicted from, and often opposed, their effects on subcutaneous “primary” tumors, possibly due to their distinct growth kinetics and host interactions. We here introduce a clinically relevant model of residual metastatic disease that may more accurately predict the therapeutic response of recurrent, metastatic disease.

Inhibition of hypoxia inducible factor-1 (HIF-1) is an attractive therapeutic strategy to target the tumor microenvironment. However, HIF-1 inhibitors may have limited activity as single agents and combination therapies may be required. We tested the hypothesis that HIF-1 inhibition in a hypoxic-stressed tumor microenvironment, which could be generated by administration of antiangiogenic agents, may result in a more pronounced therapeutic effect. The activity of bevacizumab, either alone or in combination with the HIF-1α inhibitor topotecan, was evaluated in U251-HRE xenografts. Tumor tissue was collected at the end of treatment and changes in tumor oxygenation, angiogenesis, proliferation, apoptosis, HIF-1α levels, HIF-1 target genes, and DNA damage were evaluated. Bevacizumab decreased microvessel-density and increased intratumor-hypoxia, but did not induce apoptosis. Moreover, bevacizumab alone caused a significant increase of HIF-1–dependent gene expression in tumor tissue. Addition of a low dose of daily topotecan to bevacizumab significantly inhibited tumor growth, relative to mice treated with topotecan or bevacizumab alone (P < 0.01). The addition of topotecan to bevacizumab was also associated with profound inhibition of HIF-1 transcriptional activity, significant inhibition of proliferation, and induction of apoptosis. Importantly, DNA damage induced by topotecan alone was not augmented by addition of bevacizumab, suggesting that increased cytotoxic activity did not account for the increased antitumor effects observed. These results strongly suggest that combination of anti–vascular endothelial growth factor antibodies with HIF-1 inhibitors is an attractive therapeutic strategy targeting in the hypoxic tumor microenvironment. [Mol Cancer Ther 2009;8(7):1867–77]

Purpose: The use of genetically engineered mouse (GEM) models for preclinical testing of anticancer therapies is hampered by variable tumor latency, incomplete penetrance, and complicated breeding schemes. Here, we describe and validate a transplantation strategy that circumvents some of these difficulties.Experimental Design: Tumor fragments from tumor-bearing MMTV-PyMT or cell suspensions from MMTV-PyMT, -Her2/neu, -wnt1, -wnt1/p53+/−, BRCA1/p53+/−, and C3(1)T-Ag mice were transplanted into the mammary fat pad or s.c. into naïve syngeneic or immunosuppressed mice. Tumor development was monitored and tissues were processed for histopathology and gene expression profiling. Metastasis was scored 60 days after the removal of transplanted tumors.Results: PyMT tumor fragments and cell suspensions from anterior glands grew faster than posterior tumors in serial passages regardless of the site of implantation. Microarray analysis revealed genetic differences between these tumors. The transplantation was reproducible using anterior tumors from multiple GEM, and tumor growth rate correlated with the number of transplanted cells. Similar morphologic appearances were observed in original and transplanted tumors. Metastasis developed in >90% of mice transplanted with PyMT, 40% with BRCA1/p53+/− and wnt1/p53+/−, and 15% with Her2/neu tumors. Expansion of PyMT and wnt1 tumors by serial transplantation for two passages did not lead to significant changes in gene expression. PyMT-transplanted tumors and anterior tumors of transgenic mice showed similar sensitivities to cyclophosphamide and paclitaxel.Conclusions: Transplantation of GEM tumors can provide a large cohort of mice bearing mammary tumors at the same stage of tumor development and with defined frequency of metastasis in a well-characterized molecular and genetic background.

The ability of early passage patient-derived tumor xenografts (PDXs) to recapitulate human tumor biology makes them invaluable tools for pre-clinical drug development (1, 2). Similarly, clinically-annotated human tumor cell lines of low passage have potential as scalable biosimilar reagents for in vitro study. Here, we describe an integrated platform for the purification, expansion, and quality control of tumor cells and cancer-associated fibroblasts (CAFs) from patient biopsies, surgical resections, and mouse PDX models. Following dissociation of solid tumors, cells are cultured on Matrigel® in fibroblast conditioned media containing Y-27632 (a Rho-associated kinase inhibitor). Cells are then analyzed by FACS using a panel of species- or cell type-specific antibodies. This panel (anti-mCD9, hCD9, hCD24, hCD90, MHC, HLA, and hEPCAM) permits quantitation of the percentage of mouse/human cells, and the percentages of tumor cells and CAFs in each patient specimen. From these data, a cell sorting strategy can be selected (e.g. mCD9 and hCD90 with hEpCAM or CD24) that will permit purification of both tumor cells and CAFs, along with removal of any mouse fibroblast contamination (for PDX tumors). Samples are sorted multiple times until target populations reach 99.99% purity (typically 2-3 rounds). Purified cells are then returned to culture, expanded over several weeks, and frozen at low passage. The purity and identity of these cultures is quality-assured using 1) mouse-specific QPCR, 2) a cDNA array designed to differentiate fibroblasts from tumor cells, and 3) STR genotyping. Tumor lines and CAFs are then scaled and re-qualified at passages 10 and 20, an essential step given the propensity of low-frequency mouse and human fibroblasts to ‘overtake’ impure cultures with time. Lastly, cancer lines and CAF cultures undergo genomic characterization and are evaluated for in vivo tumorigenicity (or the lack thereof for CAFs). To date, the platform has been used to generate a growing number of purified cancer and CAF pairs from patient materials. In conclusion, our goal is to provide useful reagents to the extramural community that will accompany current efforts within the Division of Cancer Treatment and Diagnosis (DCTD, NCI) aimed at generating a large and extensively characterized repository of PDX models. Funded by NCI Contract No. HHSN261200800001E. References 1.Hidalgo M, Amant F, Biankin AV, Budinska E, Byrne AT, Caldas C, et al. Patient-derived xenograft models: an emerging platform for translational cancer research. Cancer Discov. 2014;4:998-1013. 2.Rosfjord E, Lucas J, Li G, Gerber HP. Advances in patient-derived tumor xenografts: from target identification to predicting clinical response rates in oncology. Biochem Pharmacol. 2014;91:135-43. Citation Format: Luke H. Stockwin, Michael Mullendore, Carrie Bonomi, Kelly Dougherty, James H. Doroshaw, Melinda G. Hollingshead, Dianne L. Newton. Cell sorting strategies for the isolation of cancer cells and associated fibroblasts from tumor biopsies, surgical resections, and patient-derived xenografts. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5139. doi:10.1158/1538-7445.AM2015-5139

It is well established that cancers are heterogeneous diseases with biological, genetic, and histopathological differences among patients and within individual tumors. Consequently, it is not surprising that animal models based on established cell lines with their clonal nature and adaptations to defined media have limited preclinical value. Recent advances in the generation of patient-derived xenografts (PDX), where patient material is engrafted into immunosuppressed mice, suggests that this approach may provide a more representative surrogate for therapeutic development. In this study, a mixed cell culture derived from a SCLC PDX model was analyzed for clonal heterogeneity. Following two rounds of growth in soft agar, seven clones were derived; three were further characterized. The 1st clone, 7-7-2, similar in morphology to the parental culture was a mixture of cuboidal and spindle-shaped cells. FACs analysis confirmed two populations of cells; EpCAM+/CD90 low and EpCAM-/CD90 high population. The 2nd clone, 2-2-1, consisted of a single population of spindle-shaped EpCAM-/CD90+ cells; the 3rd clone, 7-7-1, contained a homogeneous population of cuboidal cells that were EpCAM+/CD90 low. DNA analysis confirmed all 3 clones were derived from the same patient. Furthermore, all 3 clones were tumorigenic in NSG mice. To exclude fibroblast contamination, the clones were analyzed using a quantitative RT-PCR array capable of identifying human fibroblasts and other stromal constituents. None of the 3 clones had a classical fibroblast profile. Comparison of 2-2-1 relative to the other 2 clones revealed higher expression of VIM mRNA and lower KRT5, CDH1 and EpCAM. Results were confirmed by Western blot. Additionally, ITGAV and TWIST were up-regulated. These results suggest that clone 2-2-1 had undergone epithelial-mesenchymal transition (EMT). Further confirmation was provided by microarray and proteomic analysis where GNG11, MMP2, ZEB, DDR2, TESK2, DESM and MOES were elevated consistent with EMT. Next, clones were tested for sensitivity against a panel of clinically relevant agents (trametinib, everolimus, temozolomide, ABT-888, carboplatin, MK 1775) either alone or in combination. Clone 2-2-1 proved to be more sensitive than parental cells or clones 7-7-1 or 7-7-2 to the majority of these drugs. Further studies showed the combination of temozolomide/ABT-888 was synergistic against each of the clones while the combination of MK 1775/carboplatin lacked synergism. In vivo, the parental tumor responded to the temozolomide/ABT-888 combination with tumor regressions. In summary, these data serve to highlight 1) heterogeneity within this PDX model 2) profound biological differences between clones and 3) EMT is implicated and alters drug responses. Funded by NCI Contract No. HHSN261200800001E. Citation Format: Michael Mullendore, Luke H. Stockwin, Carrie Bonomi, Kelly Dougherty, Howard Stotler, Adrienne Kimmel, Biswajit Das, Vivekananda Datta, Jason Lih, Mickie Williams, James Doroshow, Melinda Hollingshead, Dianne Lynn Newton. Clonal heterogeneity in patient-derived xenografts: The SCLC model LG0904F1496M23 contains stable clones with epithelial or mesenchymal characteristics and differential drug sensitivities. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3236. doi:10.1158/1538-7445.AM2015-3236

The introduction of imaging methods suitable for rodents offers opportunities for new anticancer efficacy models. Traditional models do not provide the level of sensitivity afforded by these precise and quantitative techniques. Bioluminescent endpoints, now feasible because of sensitive charge-coupled device cameras, can be non-invasively detected in live animals. Currently, the most common luminescence endpoint is firefly luciferase, which, in the presence of O(2) and ATP, catalyses the cleavage of the substrate luciferin and results in the emission of a photon of light. In vivo implantation of tumour cells transfected with the luciferase gene allows sequential monitoring of tumour growth within the viscera by measuring these photon signals. Furthermore, tumour cell lines containing the luciferase gene transcribed from an inducible promoter offer opportunities to study molecular-target modulation without the need for ex vivo evaluations of serial tumour samples. In conjunction with this, transgenic mice bearing a luciferase reporter mechanism can be used to monitor the tumour microenvironment as well as to signal when transforming events occur. This technology has the potential to reshape the efficacy evaluations and drug-testing algorithms of the future.

Metabolites of arachidonic acid (AA) have been implicated in the biologic behavior of squamous cell carcinoma of the head and neck (SCCHN). This hypothesis has generally been supported by three types of observations: 1) increased levels of AA metabolites in tumor tissues, 2) the effects of AA metabolites on tumor growth and/or host immune function, and 3) the effects of inhibitors of AA metabolism on tumor growth in vitro and in vivo. Much attention has been focused on prostaglandin E2 (PGE2) due to its multiple immunosuppressive effects. The importance of other cyclooxygenase and lipoxgenase metabolites has not been adequately addressed.

Optical imaging of labeled cells is the most prevailing method for cell tracking in mouse models. However, the immunogenicity of xenobiotic reporter genes, such as the commonly used firefly luciferase (ffLuc) and enhanced green fluorescence protein (eGFP), results in inconsistency in cell labeling and tumor progression, preventing their use in host mice with normal immunity. To resolve this issue, we have generated a reporter gene-tolerized transgenic mouse in which an ffLuc-eGFP fusion gene was targeted to the anterior pituitary gland using a rat Growth Hormone promoter (dubbed the “glowing-head” mouse). When ffLuc-eGFP-labeled Lewis Lung Carcinoma (LLC) tissue was subcutaneously transplanted into syngeneic glowing-head mice (GH-c-brd), their non-transgenic litter-mates (WT-c-brd), and immunocompromised Nod-Scid (balb/c) mice, anti-GFP antibody was induced only in the circulation of WT-c-brd. Labeled LLC also exhibited fewer CD4+ T cells but more macrophages in GH-c-brd than in WT-c-brd, suggesting it induced adaptive immunity in the latter. Moreover, GH-c-brd exhibited faster subcutaneous tumor growth and post-resection metastatic progression, and maintained more consistent tumor labeling, as compared to WT-c-brd and even Nod-Scid mice. Interestingly, in an adjuvant chemotherapeutic setting, the immunogenicity of the labeled tumor was able to deter metastatic progression in a manner similar to that obtained by drug treatment. We conclude that the immunogenicity of xenobiotic labeling markers can significantly influence disease progression and therapeutic responses thereby compromising immunocompetent preclinical cancer models, and that the glowing-head mouse can be used to circumvent such problems and promote consistent disease monitoring. Citation Format: Chi-Ping Day, Zoe Weaver, John Carter, Carrie Bonomi, Terry Van Dyke, Melinda Hollingshead, Glenn Merlino. Immunological naturalization of immunocompetent host mice to luciferase-GFP for consistent tracking of transplanted tumors. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1556. doi:10.1158/1538-7445.AM2013-1556

The questionable predictive power of available preclinical models is explained in part by their failure to adequately replicate the clinical setting. Prevailing human xenograft models do not consider advanced disease, require the use of immunocompromised mice that reconstitute aberrant tumor-host interactions, and employ delayed tumor growth as an endpoint, which has limited clinical relevance. To overcome these deficiencies, we have developed a rapid preclinical model of spontaneous metastasis that more accurately recapitulates clinical procedures for advanced non-small cell lung cancer patients. Lewis Lung Carcinoma tumor tissue that was never adapted to cell culture was stably labeled using lentivirus-encoding bioimaging markers, inoculated into syngeneic C57BL/6 mice, and resected upon reaching a predetermined size. Mice were then treated in a setting akin to post-surgical, first-line adjuvant chemotherapy using cisplatin, paclitaxel and/or antiangiogenic agents. As in the clinic, these drugs were most effective against progression in combination. However, the response of metastases to agents could not be predicted from, and often opposed, their effects on subcutaneous tumors. Time to macrometastatic onset, instead of growth, correlated with mouse survival. Moreover, the most effective adjuvant chemotherapy did not inhibit growth, but rather extended the equivalent of clinical dormancy. These results indicate that metastatic disease is driven by micrometastatic to macrometastatic transition, and resistance to therapies is caused by the failure to maintain clinical dormancy. Identification of the mechanisms involved in these processes will provide new targets of anti-cancer therapies and biomarkers for monitoring therapeutic efficacy. We demonstrate the inadequacies of current preclinical models, and introduce a paradigm for a more clinically relevant model that may more accurately predict therapeutic response in late-stage cancer patients. Citation Information: Clin Cancer Res 2010;16(7 Suppl):A9

Background Development of cancer therapeutics partially depends upon selection of appropriate animal models. Therefore, improvements to model selection are beneficial. Results Forty-nine human tumor xenografts at in vivo passages 1, 4 and 10 were subjected to cDNA microarray analysis yielding a dataset of 823 Affymetrix HG-U133 Plus 2.0 arrays. To illustrate mining strategies supporting therapeutic studies, transcript expression was determined: 1) relative to other models, 2) with successive in vivo passage, and 3) during the in vitro to in vivo transition. Ranking models according to relative transcript expression in vivo has the potential to improve initial model selection. For example, combining p53 tumor expression data with mutational status could guide selection of tumors for therapeutic studies of agents where p53 status purportedly affects efficacy (e.g., MK-1775). The utility of monitoring changes in gene expression with extended in vivo tumor passages was illustrated by focused studies of drug resistance mediators and receptor tyrosine kinases. Noteworthy observations included a significant decline in HCT-15 colon xenograft ABCB1 transporter expression and increased expression of the kinase KIT in A549 with serial passage. These trends predict sensitivity to agents such as paclitaxel (ABCB1 substrate) and imatinib (c-KIT inhibitor) would be altered with extended passage. Given that gene expression results indicated some models undergo profound changes with in vivo passage, a general metric of stability was generated so models could be ranked accordingly. Lastly, changes occurring during transition from in vitro to in vivo growth may have important consequences for therapeutic studies since targets identified in vitro could be over- or under-represented when tumor cells adapt to in vivo growth. A comprehensive list of mouse transcripts capable of cross-hybridizing with human probe sets on the HG-U133 Plus 2.0 array was generated. Removal of the murine artifacts followed by pairwise analysis of in vitro cells with respective passage 1 xenografts and GO analysis illustrates the complex interplay that each model has with the host microenvironment. Conclusions This study provides strategies to aid selection of xenograft models for therapeutic studies. These data highlight the dynamic nature of xenograft models and emphasize the importance of maintaining passage consistency throughout experiments. Electronic supplementary material The online version of this article (doi: 10.1186/1471-2164-15-393) contains supplementary material, which is available to authorized users.