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  • 1
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 12_Supplement ( 2022-06-15), p. 1913-1913
    Abstract: Background: The National Cancer Institute's Patient-Derived Models Repository (NCI PDMR; pdmr.cancer.gov) is developing a variety of patient-derived xenograft (PDX) models for pre-clinical drug studies. All NCI PDMR models undergo quality control (QC) processes. Two unique QC challenges are: a) to assess genomic stability across PDX model passages; and b) to confirm the suitability of PDX-derived cancer associated fibroblasts (CAFs) as germline surrogates when blood is not available. Multiple bioinformatics QC assessments have been developed to measure the genomic fidelity in these PDX models using low-pass whole genome sequencing (LP-WGS) and in CAFs using whole exome sequencing (WES). Methods: LP-WGS was performed on 502 PDX samples from 38 models of rare cancer across passages 2 through 9 and WES was performed on 92 CAFs from 32 different histologies. In the QC workflow for estimating the genomic stability of passages within models, BBSplit was used for the assessment of human/mouse DNA content. CNVkit was utilized for copy number (CN) detection. The fraction of genome changed was calculated by comparing the copy numbers of each passage sample to the original patient sample. To evaluate purity of CAFs, three QC steps were constructed: a) plot of SNP variant allele frequency (ideogram); b) variant annotation using OncoKB (www.oncokb.org); c) percentage of genomic loss of heterozygosity (LOH), based on a set of ~800,000 heterozygous SNPs from a population-level genomic database (gnomAD) based on WES data. Results: PDX models showed genomic stability in CN profile when measured by LP-WGS. Human tumor DNA content remains stable ranging from 75-85% across different tiers of PDX passages from Donor +1 to Donor +6 and more. No models showed statistically significant evolution in CN profile, given the average 5 samples per model in each tier of passages. The QC workflow for CAFs generated five categories based on SNP ideograms, the presence/absence of oncogenic variants and LOH. Following observations were made: a) 72.5% CAFs were confirmed as matched diploid CAFs (category 1); b) 6.6% of CAFs were diploid and had & gt;= 1 germline oncogenic variant - classified as category 2. CAFs in category 1 & 2 were suitable as germline surrogates; c) 12% of CAFs (category 3) showed putative polyploidy on SNP ideograms with no oncogenic variants and suitable for somatic variant calling; d) 8.8% of CAFs (category 4) had polyploidy and oncogenic variants present; e) LOH high CAF (category 5) - we identified a CAF with 42% LOH, later confirmed to be a tumor cell line by immunohistochemistry (IHC). Other CAFs (n=91) showed little variance, ranging from 0.6%-1.7% LOH. Conclusions: We developed standard QC workflows to evaluate genomic stability of PDX models during passaging and qualify CAFs as germline surrogates for pre-clinical study. Citation Format: Ting-Chia Chang, Li Chen, Biswajit Das, Yvonne A. Evrard, Chris A. Karlovich, Tomas Vilimas, Alyssa Chapman, Nikitha Nair, Luis Romero, Anna J. Lee Fong, Amanda Peach, Brandie Fullmer, Lindsay Dutko, Kelly Benauer, Gloryvee Rivera, Erin Cantu, Shahanawaz Jiwani, Nastaran Neishaboori, Tomas Forbes, Corinne Camalier, Luke Stockwin, Michael Mullendore, Michelle A. Eugeni, Dianne Newton, Melinda G. Hollingshead, Mickey P. Williams, James H. Doroshow. Quality control workflows developed for the NCI Patient-Derived Models Repository using low pass whole genome sequencing and whole exome sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1913.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
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  • 2
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 1056-1056
    Abstract: Background: Patient-derived tumor xenografts (PDX) are powerful tools to study cancer biology, cancer genomics and developmental therapeutics. A common problem in the development of PDX models is proliferation of atypical lymphocytes at the implantation site, which often overtake or limit the growth of the original tumor. This atypical lymphocyte proliferation has been described as XABLD in our PDX models. In this study, we characterized XABLD cases by morphology, immunophenotyping and genomic profiling. We hypothesize that XABLD tumors are morphologically and phenotypically similar to EBV-driven post-transplant lymphoproliferative disease (PTLD) and diffuse large B cell lymphoma (DLBCL). XABLD is a surrogate model to study EBV-driven PTLD and DLBCL. Materials and Methods: Models were generated from patient tissue collected under NCI Tissue Procurement Protocol (clinicaltrials.gov: NCT00900198) and CIRB Tissue Procurement Protocol 9846 for development of models for NCI’s Patient-Derived Models Repository (https://pdmr.cancer.gov). Specimens were implanted subcutaneously in NOD/SCID/IL2Rg null (NSG) mice and animal health was monitored throughout the study. Tumors in mice with suspected XABLD were harvested and reviewed by histology and immunohistochemical analysis for CD45, B and T cell markers, EBV status, B-cell clonality assay. All samples were also classified by the Lymph2Cx NanoString cell of origin assay and transcriptome profiling. Results: XABLD cases were found to originate from both solid tumor and circulating tumor cell implants. XABLD is a rapidly growing tumor positive for CD45, CD20, and LMP1 stains, 36 of 42 cases are strongly positive for PD-L1 stain. 39 of 42 cases exhibited an activated B cell (ABC) phenotype with evidence of elevated NF-kB signaling. Most cases were monoclonal for IGK/IGH and contained high numbers of tumor infiltrating CD8-positive T-cells with associated high mRNA expression of activated T cell markers. Conclusion: The clinical presentation, morphology and molecular characteristics of XABLD cases were similar to EBV-driven DLBCL. As the XABLD models exhibited frequent PD-L1 expression and marked infiltration of CD8-positive T cells, they may be useful for in vitro evaluation of checkpoint inhibitor response and T cell antitumor activity. Grant Support: This project has been funded in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. Citation Format: Tomas Vilimas, Gloryvee Rivera, Brandie Fullmer, Wiem Lassoued, Lindsay Dutko, Amanda Peach, Corinne Camalier, Li Chen, Rajesh Patidar, Suzanne Borgel, John Carter, Howard Stotler, Raymond Divelbiss, Jesse Stottlemyer, Michelle M. Gottholm-Ahalt, Michelle Crespo-Eugeni, Sean McDermott, William Jacob, Liqiang Xi, Pallavi Galera, Yvonne A. Evrard, Melinda G. Hollingshead, Elaine S. Jaffe, Mark Raffeld, Biswajit Das, Chris Karlovich, Vivekananda Datta, James H. Doroshow, P. Mickey Williams. Xenograft-associated B cell lymphoproliferative disease (XABLD) as a surrogate model to study Epstein-Barr virus (EBV) driven B cell Diseases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1056.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
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  • 3
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 80, No. 16_Supplement ( 2020-08-15), p. 3916-3916
    Abstract: 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) & gt;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 & gt;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.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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  • 4
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 81, No. 13_Supplement ( 2021-07-01), p. 3139-3139
    Abstract: Background: A major set of preclinical models derived from specimens acquired from rapid autopsy patients in the National Cancer Institute Patient-Derived Models Repository (NCI PDMR, https://pdmr.cancer.gov) were from pancreatic adenocarcinoma (PAAD) patients, with metastatic specimens originating from liver, colon, omentum, and lung. Genomic characterization of these preclinical models provides a unique opportunity to study tumor heterogeneity and subclonality associated with the metastatic process and potential treatment resistance. Methods: To date, 30 rapid autopsy patient-derived xenograft (PDX)/patient-derived cell (PDC)/patient-derived organoid (PDOrg ) models derived from pancreatic adenocarcinoma patients (n = 9) have been sequenced using whole-exome sequencing (WES) and RNASeq. Tumor heterogeneity between primary and metastatic sites was studied based on somatic mutation, copy number alteration (CNA) and gene expression data. A bioinformatics workflow was developed to stably infer and visualize the tumor subclonality by integrating the tools of PyClone, SCHISM, and TIMESCAPE, using somatic mutations and site-specific copy number data of multiple samples generated from PDX models in primary and metastatic sites. Results: Among 30 rapid autopsy preclinical models from primary and metastatic sites, liver is the most common metastatic site in PAAD (9/19=47%) compared to other sites. Driver mutations are conserved in all preclinical model specimens derived from a given patient. KRAS p.G12D is present in 28 PDX/PDC/PDOrg models as well as the corresponding patient specimens, and BRAF p.V600E is present in other preclinical models. The fraction of the genome affected by CNA remains stable within a PDX model across passages (n=18, mean=7.63%, sd=5.90%). However, we found that this increased when comparing PDX models derived from metastatic sites versus the primary site (n=16, mean=19.47%, sd=9.69%). This indicates the presence of tumor heterogeneity between metastatic and primary sites. Site-specific subclones were identified in PDX models from two patients (521955 and 485368) and a phylogenetic tree of primary and metastasis sites indicates that one liver metastasis had a unique seeding event compared to the other metastatic sites for both patients. Conclusion: Tumor heterogeneity and subclonality was observed in preclinical models generated from PAAD patients in the NCI PDMR. These models provide a unique resource for preclinical studies in tumor evolution, metastatic spread mediators, and drug resistance. Citation Format: Li Chen, Biswajit Das, Yvonne A. Evrard, Chris A. Karlovich, Tomas Vilimas, Amanda Peach, Chapman Alyssa, Nikitha Nair, Anna L. Fong, Luis Romero, Ting-Chia Chang, Shahanawaz Jiwani, Lindsay Dutko, Kelly Benauer, Marianne Morton, Kelly Dougherty, Michelle A. Eugeni, Dianne Newton, Melinda G. Hollingshead, P. Mickey Williams, James H. Doroshow. Study of tumor heterogeneity and subclonality in primary pancreatic and metastatic sites from rapid autopsy patients in PDMR [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 3139.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
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  • 5
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 4524-4524
    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.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
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  • 6
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 38, No. 15_suppl ( 2020-05-20), p. e13506-e13506
    Abstract: e13506 Background: The National Cancer Institute has developed a repository of preclinical models [Patient-Derived Models Repository (NCI PDMR, https://pdmr.cancer.gov )] including patient derived xenografts (PDXs), organoids (PDOrgs) and in vitro tumor cultures (PDCs) from patients with solid tumor cancer histologies. A subset of these preclinical models is derived from post-mortem collections from rapid autopsies representing the end point in disease progression. Clinical annotations and genomic datasets associated with these models provide a unique opportunity to study tumor evolution, mechanistic insights into the metastatic process, and treatment resistance. Methods: To date, 43 PDXs, 21 PDCs, and 23 PDOrgs using rapid autopsy specimens from 8 primary and 35 metastatic sites of 18 patients have been developed by the Biological Testing Branch (DTP, DCTD, NCI Frederick, MD) for the PDMR. Whole exome (WES) and total transcriptome (RNASeq) data were processed to generate mutation, copy number alteration (CNA) and gene expression data. Multi-model lineage trees were reconstructed based on putative somatic variants for all the models derived from all patients. The fraction of the genome affected by CNA was compared both within and across PDX models. Results: Most of the rapid autopsy PDX models (32/43) are derived from pancreatic adenocarcinoma (PAAD) patients (13/18), with metastatic specimens originating from sites including liver, colon, omentum, and lung. Driver mutations are present in all preclinical model specimens derived from the same patient. For instance, KRAS p.G12D is present in all patient-derived model specimens derived from PAAD patient 521955. The fraction of the genome affected by CNA remains stable within a PDX model across passages (n = 24, mean = 6.39%, sd = 5.90%). However, we found that this increased when comparing PDX models derived from metastatic sites versus the primary site (n = 19, mean = 16.92%, sd = 10.46%). This indicates presence of tumor heterogeneity between metastatic and primary sites. The lineage tree for models from patient 521955 indicates that one liver metastasis has a unique seeding event compared to the other 4 metastatic sites. Unsupervised clustering analysis on gene expression data also confirms the observed tumor site relationships. Conclusions: Our data demonstrate the potential use of these preclinical models available from the NCI PDMR. These models provide a unique resource for preclinical studies in tumor evolution, metastatic spread mediators, and drug resistance.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
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    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2020
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  • 7
    Online Resource
    Online Resource
    Wiley ; 2006
    In:  Immunological Reviews Vol. 209, No. 1 ( 2006-02), p. 159-169
    In: Immunological Reviews, Wiley, Vol. 209, No. 1 ( 2006-02), p. 159-169
    Type of Medium: Online Resource
    ISSN: 0105-2896 , 1600-065X
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2006
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  • 8
    In: Nature Medicine, Springer Science and Business Media LLC, Vol. 13, No. 1 ( 2007-1), p. 70-77
    Type of Medium: Online Resource
    ISSN: 1078-8956 , 1546-170X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2007
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  • 9
    In: Blood, American Society of Hematology, Vol. 107, No. 10 ( 2006-05-15), p. 4115-4121
    Abstract: Loss of E2A transcription factor activity or activation of the intracellular form of Notch1 (ICN) leads to the development of leukemia or lymphoma in humans or mice, respectively. Current models propose that ICN functions by suppressing E2A through a pre–T cell receptor (TCR)–dependent mechanism. Here we show that lymphomas arising in E2A–/– mice require the activation of Notch1 for their survival and have accumulated mutations in, or near, the Notch1 PEST domain, resulting in increased stability and signaling. In contrast, lymphomas arising in p53–/– mice show the activation of Notch1, but no mutations were identified in ICN. The requirement for Notch1 signaling in E2A–/– lymphomas cannot be overcome by ectopic expression of pTα; however, pTα is required for optimal survival and expansion of these cells. Our findings indicate that the activation of Notch1 is an important “second hit” for the transformation of E2A–/– T cell lymphomas and that Notch1 promotes survival through pre–TCR-dependent and -independent mechanisms.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2006
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  • 10
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2015
    In:  Molecular Cancer Therapeutics Vol. 14, No. 12_Supplement_2 ( 2015-12-01), p. A17-A17
    In: Molecular Cancer Therapeutics, American Association for Cancer Research (AACR), Vol. 14, No. 12_Supplement_2 ( 2015-12-01), p. A17-A17
    Abstract: p53 is a well-characterized transcription factor that is mutated in about 50% of human cancers. The majority of p53 genomic alterations are missense mutations which result in expression of p53 protein isoforms with deficient functionality. Such missense mutations cluster in several hotspots, with the most frequent alterations located at amino acids 175, 248 and 273 of human p53 (mouse amino acids 172, 245 and 270). p53 missense mutants disrupt the function of p53 tetramers, thereby behaving similarly to loss of p53. However, there is evidence that p53 missense mutants have additional tumor-promoting functions that differ from p53 deletions: p53 missense mutants can transform p53 null cells in vitro and in mouse models, and the p53 missense mutants induce a different tumor spectrum from that induced by p53 loss or other p53 missense mutants. The information obtained from the engineered murine models featuring p53 missense mutations has greatly elucidated the role of p53 mutagenesis in cancer. However, the currently-available p53 models bear several drawbacks that make them sub-optimal for preclinical studies. These models contain a global p53 haploinsufficiency, potentially impacting the biology of tumor-modifying structures like stroma, the immune system, and the vasculature. Furthermore, activation of the p53 missense mutant alleles results in a transition from a single functional wild-type allele to a combination of a wild-type and a mutant allele. These features substantially deviate from those of observed in human tumorigenesis, where somatic p53 mutagenesis in cells undergoing transformation results in a transition from two wild-type alleles to a combination of a wild-type and a mutant alleles, while tumor-modifying structures retain an unaltered p53 biallelic configuration. Here we describe the molecular and phenotypic characterization of a new allelic series of conditional p53 missense mutant mouse lines in which Cre-mediated recombination converts p53 from a wild-type to a missense mutant (R172H, R270H or R270C) configuration. To characterize the gradual molecular changes induced by expression of R172H and R270H mutants, we derived MEF lines harboring the alleles in a heterozygous conditional (p53-R172H fl/+ or p53-R270H fl/+) configuration. We observed that the wild-type p53 mRNA was lost but p53 protein abundance was increased after Cre-mediated activation of the mutant allele. Interestingly, we found that the R270H mutant allele provided a greater proliferative advantage, a distinct growth pattern and a greater ability to grow in vitro under starvation conditions than a similarly engineered R172H mutant allele. Consistent with published evidence, these observations suggest that the acquired functional changes are dissimilar between different p53 missense mutants. We further characterized the transcriptome profiles in MEF lines harboring R172H and R270H alleles and identified a number of unique and common transcriptional changes that could be causal for gain-of-function phenotypes and informative for uncovering additional mechanisms for carcinogenesis driven by p53 missense mutants. We used the newly-derived p53 mutant alleles to establish improved autochthonous and orthotopic pancreatic cancer models suitable for preclinical efficacy studies and we are currently developing lung cancer, ovarian cancer, and medullary thyroid carcinoma models. Citation Format: Tomas Vilimas, Keith Collins, Theresa Guerin, Roackie Awasthi, Lionel Feigenbaum, Guillermina Lozano, Terry Van Dyke, Serguei Kozlov. p53 missense mutants R172H and R270H exhibit differential effects on tumorigenesis. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr A17.
    Type of Medium: Online Resource
    ISSN: 1535-7163 , 1538-8514
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2015
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