18 results on '"Emily Delaney"'
Search Results
2. Highly contiguous assemblies of 101 drosophilid genomes
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Bernard Y Kim, Jeremy R Wang, Danny E Miller, Olga Barmina, Emily Delaney, Ammon Thompson, Aaron A Comeault, David Peede, Emmanuel RR D'Agostino, Julianne Pelaez, Jessica M Aguilar, Diler Haji, Teruyuki Matsunaga, Ellie E Armstrong, Molly Zych, Yoshitaka Ogawa, Marina Stamenković-Radak, Mihailo Jelić, Marija Savić Veselinović, Marija Tanasković, Pavle Erić, Jian-Jun Gao, Takehiro K Katoh, Masanori J Toda, Hideaki Watabe, Masayoshi Watada, Jeremy S Davis, Leonie C Moyle, Giulia Manoli, Enrico Bertolini, Vladimír Košťál, R Scott Hawley, Aya Takahashi, Corbin D Jones, Donald K Price, Noah Whiteman, Artyom Kopp, Daniel R Matute, and Dmitri A Petrov
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Drosophila ,Drosophilidae ,comparative genomics ,genome assembly ,nanopore ,long reads ,Medicine ,Science ,Biology (General) ,QH301-705.5 - Abstract
Over 100 years of studies in Drosophila melanogaster and related species in the genus Drosophila have facilitated key discoveries in genetics, genomics, and evolution. While high-quality genome assemblies exist for several species in this group, they only encompass a small fraction of the genus. Recent advances in long-read sequencing allow high-quality genome assemblies for tens or even hundreds of species to be efficiently generated. Here, we utilize Oxford Nanopore sequencing to build an open community resource of genome assemblies for 101 lines of 93 drosophilid species encompassing 14 species groups and 35 sub-groups. The genomes are highly contiguous and complete, with an average contig N50 of 10.5 Mb and greater than 97% BUSCO completeness in 97/101 assemblies. We show that Nanopore-based assemblies are highly accurate in coding regions, particularly with respect to coding insertions and deletions. These assemblies, along with a detailed laboratory protocol and assembly pipelines, are released as a public resource and will serve as a starting point for addressing broad questions of genetics, ecology, and evolution at the scale of hundreds of species.
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- 2021
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3. Analysis of Cannabinoid-Containing Fluids in Illicit Vaping Cartridges Recovered from Pulmonary Injury Patients: Identification of Vitamin E Acetate as a Major Diluent
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Bryan Duffy, Lingyun Li, Shijun Lu, Lorie Durocher, Mark Dittmar, Emily Delaney-Baldwin, Deepika Panawennage, David LeMaster, Kristen Navarette, and David Spink
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electronic cigarettes ,vaping cartridges ,cannabinoids ,vitamin e acetate ,Chemical technology ,TP1-1185 - Abstract
Beginning in June of 2019, there was a marked increase in reported cases of serious pulmonary injury associated with vaping. The condition, referred to as e-cigarette or vaping product use-associated lung injury (EVALI), does not appear to involve an infectious agent; rather, a chemical adulterant or contaminant in vaping fluids is suspected. In August of 2019, the Wadsworth Center began receiving vaporizer cartridges recovered from patients with EVALI for analysis. Having no a priori information of what might be in the cartridges, we employed untargeted analyses using gas chromatography-mass spectrometry and high-resolution mass spectrometry to identify components of concern. Additionally, we employed targeted analyses used for New York medical marijuana products. Here, we report on the analyses of 38 samples from the first 10 New York cases of EVALI for which we obtained cartridges. The illicit fluids had relatively low cannabinoid content, sometimes with unusual Δ9-/Δ8-tetrahydrocannabinol ratios, sometimes containing pesticides and many containing diluents. A notable diluent was α-tocopheryl acetate (vitamin E acetate; VEA), which was found in 64% of the cannabinoid-containing fluids. To investigate potential sources of the VEA, we analyzed six commercial cannabis-oil diluents/thickeners. Three were found to be >95% VEA, two were found to be primarily squalane, and one was primarily α-bisabolol. The cause(s) of EVALI is unknown. VEA and squalane are components of some personal care products; however, there is growing concern that vaping large amounts of these compounds is not safe.
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- 2020
- Full Text
- View/download PDF
4. Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders.
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Samuel Stanton, Wesley J. Maddox, Nate Gruver, Phillip M. Maffettone, Emily Delaney, Peyton Greenside, and Andrew Gordon Wilson
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- 2022
5. Abstract 3120: Method development for generation of PDX models from rapid autopsy samples for the NCI patient-derived models repository
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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, and James H. Doroshow
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Cancer Research ,Oncology - Abstract
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.
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- 2022
- Full Text
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6. Abstract 80: Genomic characterization of PDX models from rare cancer patients in the NCI Patient-Derived Models Repository
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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, and James H. Doroshow
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Cancer Research ,Oncology - Abstract
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.
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- 2022
- Full Text
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7. The influence of social media on acne treatment: A cross-sectional survey
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Emily Delaney, Rachael Hagen, Stephen M. Davis, Ahmed Yousaf, and Zachary Zinn
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Male ,medicine.medical_specialty ,Adolescent ,Cross-sectional study ,Dermatology ,Article ,030207 dermatology & venereal diseases ,03 medical and health sciences ,Young Adult ,0302 clinical medicine ,Surveys and Questionnaires ,Acne Vulgaris ,Complaint ,medicine ,Humans ,Social media ,Misinformation ,Young adult ,Child ,Acne ,business.industry ,Acne treatment ,Patient Acceptance of Health Care ,West Virginia ,medicine.disease ,Self Care ,Cross-Sectional Studies ,Socioeconomic Factors ,030220 oncology & carcinogenesis ,Family medicine ,Pediatrics, Perinatology and Child Health ,Ambulatory ,Female ,business ,Social Media - Abstract
Background/objectives Social media use has been suggested to worsen psychiatric health among adolescents, especially those with visible skin lesions including acne. However, little is known about social media's impact on acne treatment. The purpose of the study sought to characterize the influence of social media use on acne treatment. Methods We conducted a cross-sectional survey of West Virginia University ambulatory patients whose chief complaint was acne was conducted. The survey collected sociodemographics and queried whether individuals accessed social media for acne treatment advice or not, whether changes to acne care were made based on social media, and whether these changes aligned with the American Academy of Dermatology (AAD) clinical guidelines for acne management. Results Of 130 respondents, 45% consulted social media for acne treatment advice (54% of women vs 31% of men). 41% of adolescents and 51% of adults consulted social media. The most used platforms were YouTube and Instagram (58% each). Social media users often tried an OTC treatment (81%) or dietary modification (40%). However, only 31% of participants consulting social media made changes fully aligned with AAD clinical guidelines. Conclusions Social media-influenced acne treatment advice is prevalent, especially among women, adolescents, and young adults. This treatment advice frequently does not align with AAD guidelines, with notably 40% of respondents choosing dietary modification for acne management. These results suggest that dermatologists should inquire about social media acne treatment advice and directly address misinformation.
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- 2020
8. Analysis of Cannabinoid-Containing Fluids in Illicit Vaping Cartridges Recovered from Pulmonary Injury Patients: Identification of Vitamin E Acetate as a Major Diluent
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Lingyun Li, David C. Spink, Shijun Lu, Deepika Panawennage, Lorie A. Durocher, Kristen Navarette, David M. LeMaster, Emily Delaney-Baldwin, Bryan C. Duffy, and Mark A Dittmar
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vaping cartridges ,Health, Toxicology and Mutagenesis ,medicine.medical_treatment ,Poison control ,vitamin E acetate ,Lung injury ,Toxicology ,lcsh:Chemical technology ,Diluent ,Article ,03 medical and health sciences ,Cartridge ,cannabinoids ,0302 clinical medicine ,medicine ,lcsh:TP1-1185 ,030212 general & internal medicine ,Vitamin E Acetate ,Adulterant ,Chemical Health and Safety ,Chromatography ,Chemistry ,electronic cigarettes ,030220 oncology & carcinogenesis ,Pulmonary Injury ,Cannabinoid - Abstract
Beginning in June of 2019, there was a marked increase in reported cases of serious pulmonary injury associated with vaping. The condition, referred to as e-cigarette or vaping product use-associated lung injury (EVALI), does not appear to involve an infectious agent, rather, a chemical adulterant or contaminant in vaping fluids is suspected. In August of 2019, the Wadsworth Center began receiving vaporizer cartridges recovered from patients with EVALI for analysis. Having no a priori information of what might be in the cartridges, we employed untargeted analyses using gas chromatography-mass spectrometry and high-resolution mass spectrometry to identify components of concern. Additionally, we employed targeted analyses used for New York medical marijuana products. Here, we report on the analyses of 38 samples from the first 10 New York cases of EVALI for which we obtained cartridges. The illicit fluids had relatively low cannabinoid content, sometimes with unusual &Delta, 9-/&Delta, 8-tetrahydrocannabinol ratios, sometimes containing pesticides and many containing diluents. A notable diluent was &alpha, tocopheryl acetate (vitamin E acetate, VEA), which was found in 64% of the cannabinoid-containing fluids. To investigate potential sources of the VEA, we analyzed six commercial cannabis-oil diluents/thickeners. Three were found to be >, 95% VEA, two were found to be primarily squalane, and one was primarily &alpha, bisabolol. The cause(s) of EVALI is unknown. VEA and squalane are components of some personal care products, however, there is growing concern that vaping large amounts of these compounds is not safe.
- Published
- 2020
9. Around the Board : Boards, Platters, and Plates: Seasonal Cheese and Charcuterie for Year-Round Cel
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Emily Delaney and Emily Delaney
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- Cookbook, cookbooks, recipes, Livres de cuisine, Recettes, Appetizers
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Gather around the board to celebrate all of life's occasions!With a chapter for Winter, Spring, Summer, and Fall, you'll learn to make nearly 50 creative, delicious boards that capitalize on the flavors and festivities of the season. Complete with suggested flavor and beverage pairings, styling tips, ingredient profiles, and more, Around the Board is your guide to year-round entertaining.Celebrate the beauty of winter with the Winter Pairings board, filled with bold, rich flavors and pops of juicy color from pomegranate and citrus. When a beautiful spring day calls for a brunch gathering, Emily walks you through the steps of building a beautiful display of pastries, granola, spreads, fresh fruit and more. As calendars fill up with holidays and celebrations throughout the summer and fall, you'll find recipes for boards to enjoy from the 4th of July to Halloween, all featuring seasonal ingredients, delicious pairing options, and eye-catching yet easy-to-achieve arrangements.Each recipe is accompanied by annotated photography that guides you through the steps to create the board at home, along with helpful tips, product recommendations, and more. The beautiful recipe images are as pleasing to admire as they are to create, making the book the perfect addition to any entertainer's kitchen or coffee table. With an emphasis on honing your own cheese board instincts, Around the Board is a complete resource to mastering one of the year's most popular food trends.
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- 2022
10. Abstract 3012: Patient-derived models of rare cancers in the National Cancer Institute's patient-derived models repository
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Michael Mullendore, Jenna Hull, P. Mickey Williams, Cindy R. Timme, Dianne L. Newton, Tia Shearer, Shahanawaz Jiwani, Li Chen, Chris Karlovich, Michelle Eugeni, Tara Grinnage-Polley, James H. Doroshow, Kristen Cooley, Tom Walsh, Devynn Breen, Emily Delaney, Kimberly Klarmann, Michelle M. Gottholm-Ahalt, Melinda G. Hollingshead, Jesse Stottlemyer, Chelsea McGlynn, Malorie Morris, John Mark Carter, Yvonne A. Evrard, Alice P. Chen, Ting-Chia Chang, Candace Mallow, Sergio Y. Alcoser, Shannon Uzelac, Biswajit Das, and Justine Mills
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Oncology ,Cancer Research ,medicine.medical_specialty ,business.industry ,Internal medicine ,medicine ,Cancer ,business ,medicine.disease - Abstract
There is an unmet need for preclinical models of rare cancers and rare disease sub-types. The National Cancer Institute's Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) is developing quality-controlled, early-passage, clinically-annotated patient-derived tumor xenografts (PDXs), in vitro tumor cell cultures (PDCs), cancer associated fibroblasts (CAFs), and patient-derived organoids (PDOrg) and has focused on addressing unmet needs in the preclinical model space including developing models from adult and pediatric patients with rare cancers. To date, NCI has created and molecularly characterized over 150 preclinical models of rare cancer including indications such as Hurthle cell carcinoma, osteosarcomas, Merkel cell carcinomas, salivary gland cancers, synovial sarcomas, and carcinosarcomas. Rare cancer models developed to date will be reviewed and their histopathologic and molecular characteristics compared to that reported in the clinical setting. A pipeline to identify fusion proteins in these rare cancers such as the Ewing sarcoma EWSR1-FLI1 fusion and NAB2-STAT6 fusions in solitary fibrous tumors (SFT) has been implemented. Four malignant peripheral nerve sheath tumors (MPNST) PDX models are available for researches; these models were developed from patients diagnosed between the ages of 37-68. At the time of model development, two patients were treatment naïve and two had prior radiotherapy. Two of the MPNST PDX models have NF1 oncogenic mutations, three have deep deletions in CDKN2A/B, and three have a mutation in either EED or SUZ12 consistent with the reported molecular characteristics of patients with MPNST. Also of clinical relevance, of two mesothelioma models available, one carries an NF2 driver mutation and the other BAP1 and LATS2 and a PDX model for Hurthle cell carcinoma has wide-spread loss of heterozygosity (LOH 80%). Models for other rare cancers are in development, including four cholangiocarcinoma PDXs with histopathologic confirmation that are currently being expanded for molecular characterization and distribution. Funded by NCI Contract No. HHSN261200800001E Citation Format: Cindy R. Timme, Sergio Y. Alcoser, Devynn Breen, John Carter, Ting-Chia Chang, Alice Chen, Li Chen, Kristen Cooley, Biswajit Das, Emily Delaney, Michelle A. Eugeni, Michelle M. Gottholm-Ahalt, Tara Grinnage-Polley, Jenna Hull, Chris Karlovich, Kimberly Klarmann, Shahanawaz Jiwani, Candace Mallow, Chelsea McGlynn, Justine Mills, Malorie Morris, Michael Mullendore, Dianne Newton, Tia Shearer, Jesse Stottlemyer, Shannon Uzelac, Thomas Walsh, P. Mickey Williams, Yvonne A. Evrard, Melinda G. Hollingshead, James H. Doroshow. Patient-derived models of rare cancers in the National Cancer Institute's patient-derived models repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3012.
- Published
- 2021
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11. Abstract 3015: Applications of immunohistochemistry in characterization of patient derived xenograft models
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Michelle M. Gottholm Ahalt, Kelly Benauer, Jesse Stottlemyer, Vishnuprabha Rahulkannan, Michelle Eugeni, James H. Doroshow, Gloryvee Rivera, Lindsay Dutko, Tiffanie Chase, Erin Cantu, Melinda G. Hollingshead, Yvonne A. Evrard, Biswajit Das, Suzanne Borgel, Mickey Williams, Emily Delaney, Shahanawaz Jiwani, Chris Karlovich, Howard Stotler, Chelsea McGlynn, and John Mark Carter
- Subjects
Cancer Research ,Pathology ,medicine.medical_specialty ,Oncology ,business.industry ,medicine ,Immunohistochemistry ,business ,Tumor xenograft - 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.
- Published
- 2021
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12. 17480 The influence of social media on acne treatment: A cross-sectional survey
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Ahmed Yousaf, Emily Delaney, Rachael Hagan, and Zachary Zinn
- Subjects
medicine.medical_specialty ,Cross-sectional study ,business.industry ,Family medicine ,medicine ,Social media ,Dermatology ,Acne treatment ,business - Published
- 2020
- Full Text
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13. Abstract 3554: Genomic landscape of acquired uniparental disomy in NCI PDMR patient derived xenograft models
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Li Chen, Yvonne A. Evrard, Michelle Eugeni, Kelly Benauer, Amanda Peach, Michelle M. Gottholm Ahalt, James H. Doroshow, Shahanawaz Jiwani, Biswajit Das, Chris Karlovich, John Carter, Candace Mallow, Tara Grinnage-Pulley, Lindsay Dutko, Tiffanie L. Miner, Sergio Y. Alcoser, Dianne L. Newton, Devynn Breen, Thomas Forbes, Emily Delaney, Alyssa K. Chapman, Marianne Radzyminski, Anna J. Lee Fong, Shannon Uzelac, Chelsea McGlynn, Tomas Vilimas, Brandie A. Fullmer, Luis E. Romero, Gloryvee Rivera, Suzanne Borgel, Robin D. Harrington, Justine N. McCutcheon, Rajesh Patidar, Jesse Stottlemyer, Vishnuprabha R. Kannan, Nikitha Nair, Erin Cantu, Peng Wang, Melinda G. Hollingshead, Kelsey A. Conley, and Paul Williams
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Cancer Research ,Haplotype ,Chromosome ,Cancer ,Biology ,medicine.disease ,Uniparental disomy ,Loss of heterozygosity ,Clear cell renal cell carcinoma ,Oncology ,Cancer research ,Carcinoma ,medicine ,Exome sequencing - 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.
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- 2020
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14. Abstract 5056: 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)
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John Carter, Dianne L. Newton, Shannon Uzelac, Gloryvee Rivera, Michael Mullendore, Malorie Morris, Abigail Walke, Lily Chen, Thomas Forbes, Kyle Georgius, Emily Delaney, Sergio . Y. Alcoser, Debbie Trail, Tom Walsh, Raymond Divelbiss, Tara Grinnage-Pulley, Shahanawaz Jiwani, Chris Karlovich, Yvonne A. Evrard, Lyndsay Dutko, Sierra Hoffman, Devynn Breen, Biswajit Das, Howard Stotler, Rajesh Patidar, Thomas Vilimas, Peng Wang, Justine Mills, Suzanne Borgel, Nicole Walters, Melinda G. Hollingshead, James Doroshow, Savanna Styers, Jesse Stottlemyer, Tiffanie Chase, Michelle M. Gottholm-Ahalt, Alice P. Chen, Kristen Cooley, and P. Mickey Williams
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Cancer Research ,medicine.medical_specialty ,Scale (ratio) ,business.industry ,media_common.quotation_subject ,Cancer ,medicine.disease ,Rare cancer ,Oncology ,Medicine ,Quality (business) ,Medical physics ,business ,media_common - 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.
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- 2020
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15. Abstract 4524: Comparison of PDX, PDC, and PDOrg models from the National Cancer Institute’s Patient-Derived Models Repository (PDMR)
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Jenna Moyer, Howard Stotler, James H. Doroshow, Tom Walsh, Lily Chen, Abigail Walke, Mike Mullendore, Matt Murphy, Tara Grinnage-Pulley, Luke H. Stockwin, Marion Gibson, Yvonne A. Evrard, John Mark Carter, Wiem Lassoued, Suzanne Borgel, Carrie Bonomi, Kelly Dougherty, Kevin Plater, Biswajit Das, Raymond Divelbiss, Joe Geraghty, Vivekananda Datta, Nikki E. Craig, Emily Delaney, Marianne Radzyminski, Alice P. Chen, Kaitlyn Arthur, Mariah Baldwin, Rajesh Patidar, Dianne L. Newton, Sergio Y. Alcoser, Debbie Trail, Kyle Georgius, Shahanawaz Jiwani, Chris Karlovich, Tiffany Chase, Candace Mallow, Mallorie Morris, Sierra Hoffman, Thomas P. Forbes, P. Mickey Williams, Nicki Scott, Savanna Styers, Anna Wade, Jesse Stottlemyer, Chelsea McGlynn, Tomas Vilimas, Melinda G. Hollingshead, Michelle M. Gottholm-Ahalt, and Kelly Hedger
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Cancer Research ,Research use ,Extramural ,Genetic stability ,Cancer ,medicine.disease ,Rare cancer ,Genealogy ,Unmet needs ,Data sequences ,Oncology ,Multiple criteria ,medicine ,Psychology - Abstract
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.
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- 2019
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16. Abstract 986: The National Cancer Institute's patient-derived models repository (PDMR)
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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, and James H. Doroshow
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Cancer Research ,Oncology - Abstract
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.
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- 2018
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17. Abstract 3840: The National Cancer Institute’s patient-derived models repository (PDMR)
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Michael E. Mullendore, Carrie Bonomi, Michelle M. Gottholm Ahalt, Michelle Eugeni, Tiffanie Chase, Dianne L. Newton, Elizabeth Bradtke, Margaret R. DeFreytas, Lilia Ileva, Sergio . Y. Alcoser, Donna W. Coakley, Suzanne Borgel, Raymond Divelbiss, Franklyn Jimenez, Biswajit Das, Alice P. Chen, Paula M. Jacobs, Nimit L. Patel, Mickey Williams, Marianne Radzyminski, James H. Doroshow, Catherine Karangwa, Tara Grinnage-Pulley, Chelsea McGlynn, Nicole E. Craig, Jordyn Davidson, Chris Karlovich, Palmer Fliss, Sierra Hoffman, Yvonne A. Evrard, Luke H. Stockwin, Emily Delaney, Thomas Forbes, Vivekananda Datta, Mariah Baldwin, Lily Chen, Lisa A. Riffle, Kaitlyn Arthur, Jenna Moyer, Joseph D. Kalen, Linda L. Blumenauer, Kevin Plater, Candace Mallow, Larry Rubinstein, Marion Gibson, Melinda G. Hollingshead, John Carter, Rajesh Patidar, and Corinne Camalier
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0301 basic medicine ,Cancer Research ,Direct response ,Cancer ,Library science ,medicine.disease ,Tumor heterogeneity ,Clinical trial ,03 medical and health sciences ,030104 developmental biology ,Oncology ,medicine ,Subcutaneous implantation ,Sociology ,Citation ,National laboratory ,Web site - Abstract
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.
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- 2017
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18. Rodents
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Emily Delaney and Hopi Hoekstra
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Male ,Agricultural and Biological Sciences(all) ,Biochemistry, Genetics and Molecular Biology(all) ,Terminology as Topic ,Animals ,Humans ,Female ,Rodentia ,Biodiversity ,General Agricultural and Biological Sciences ,Biological Evolution ,General Biochemistry, Genetics and Molecular Biology - Full Text
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