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      Genetic characterization of a unique neuroendocrine transdifferentiation prostate circulating tumor cell-derived eXplant model

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          Abstract

          Transformation of castration-resistant prostate cancer (CRPC) into an aggressive neuroendocrine disease (CRPC-NE) represents a major clinical challenge and experimental models are lacking. A CTC-derived eXplant (CDX) and a CDX-derived cell line are established using circulating tumor cells (CTCs) obtained by diagnostic leukapheresis from a CRPC patient resistant to enzalutamide. The CDX and the derived-cell line conserve 16% of primary tumor (PT) and 56% of CTC mutations, as well as 83% of PT copy-number aberrations including clonal TMPRSS2-ERG fusion and NKX3.1 loss. Both harbor an androgen receptor-null neuroendocrine phenotype, TP53, PTEN and RB1 loss. While PTEN and RB1 loss are acquired in CTCs, evolutionary analysis suggest that a PT subclone harboring TP53 loss is the driver of the metastatic event leading to the CDX. This CDX model provides insights on the sequential acquisition of key drivers of neuroendocrine transdifferentiation and offers a unique tool for effective drug screening in CRPC-NE management.

          Abstract

          Better tumor models are needed for the neuroendocrine subtype of castration resistant prostate cancer (CRPC-NE). Here, the authors develop patient-derived model from circulating tumor cells of a CRPC-NE patient, and provide insights on the sequential acquisition of driver gene mutations promoting NE transdifferentiation.

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          Most cited references25

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          Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

          The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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            Circulating tumor cells predict survival benefit from treatment in metastatic castration-resistant prostate cancer.

            A method for enumerating circulating tumor cells (CTC) has received regulatory clearance. The primary objective of this prospective study was to establish the relationship between posttreatment CTC count and overall survival (OS) in castration-resistant prostate cancer (CRPC). Secondary objectives included determining the prognostic utility of CTC measurement before initiating therapy, and the relationship of CTC to prostate-specific antigen (PSA) changes and OS at these and other time points. Blood was drawn from CRPC patients with progressive disease starting a new line of chemotherapy before treatment and monthly thereafter. Patients were stratified into predetermined Favorable or Unfavorable groups ( or =5 CTC/7.5mL). Two hundred thirty-one of 276 enrolled patients (84%) were evaluable. Patients with Unfavorable pretreatment CTC (57%) had shorter OS (median OS, 11.5 versus 21.7 months; Cox hazard ratio, 3.3; P 26 to 9.3 months). CTC are the most accurate and independent predictor of OS in CRPC. These data led to Food and Drug Administration clearance of this assay for the evaluation of CRPC.
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              Organoid cultures derived from patients with advanced prostate cancer.

              The lack of in vitro prostate cancer models that recapitulate the diversity of human prostate cancer has hampered progress in understanding disease pathogenesis and therapy response. Using a 3D organoid system, we report success in long-term culture of prostate cancer from biopsy specimens and circulating tumor cells. The first seven fully characterized organoid lines recapitulate the molecular diversity of prostate cancer subtypes, including TMPRSS2-ERG fusion, SPOP mutation, SPINK1 overexpression, and CHD1 loss. Whole-exome sequencing shows a low mutational burden, consistent with genomics studies, but with mutations in FOXA1 and PIK3R1, as well as in DNA repair and chromatin modifier pathways that have been reported in advanced disease. Loss of p53 and RB tumor suppressor pathway function are the most common feature shared across the organoid lines. The methodology described here should enable the generation of a large repertoire of patient-derived prostate cancer lines amenable to genetic and pharmacologic studies. Copyright © 2014 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Yohann.loriot@gustaveroussy.fr
                francoise.farace@gustaveroussy.fr
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                20 April 2020
                20 April 2020
                2020
                : 11
                : 1884
                Affiliations
                [1 ]GRID grid.457369.a, INSERM, U981 “Identification of Molecular Predictors and new Targets for Cancer Treatment”, ; 94805 Villejuif, France
                [2 ]Gustave Roussy, Université Paris-Saclay, “Circulating Tumor Cells” Translational Platform, CNRS UMS3655—INSERM US23 AMMICA, 94805 Villejuif, France
                [3 ]XenTech, 91000 Evry, France
                [4 ]Gustave Roussy, Université Paris-Saclay, Experimental and Translational Pathology Platform, CNRS UMS3655–INSERM US23 AMMICA, 94805 Villejuif, France
                [5 ]Gustave Roussy, Université Paris-Saclay, Department of Cell Therapy, 94805 Villejuif, France
                [6 ]ISNI 0000 0004 0399 8953, GRID grid.6214.1, Medical Cell Biophysics Group, Technical Medical Centre, Faculty of Science and Technology, , University of Twente, ; 7522 NB Enschede, The Netherlands
                [7 ]ISNI 0000 0001 2176 9917, GRID grid.411327.2, Department of General, Visceral and Pediatric Surgery, Medical Faculty, , University Hospital of the Heinrich-Heine-University Düsseldorf, ; Düsseldorf, Germany
                [8 ]Gustave Roussy, Université Paris-Saclay, Department of Cancer Medicine, 94805 Villejuif, France
                [9 ]Menarini Silicon Biosystems S.p.A, 40013 Bologna, Italy
                Author information
                http://orcid.org/0000-0002-7329-7429
                http://orcid.org/0000-0003-3371-2496
                http://orcid.org/0000-0002-7807-6289
                http://orcid.org/0000-0002-3412-594X
                http://orcid.org/0000-0002-4725-5970
                http://orcid.org/0000-0001-5944-3787
                http://orcid.org/0000-0002-1681-7037
                http://orcid.org/0000-0003-1604-6823
                http://orcid.org/0000-0001-8563-160X
                Article
                15426
                10.1038/s41467-020-15426-2
                7171138
                32313004
                01280c9c-3c0e-4dee-ad1b-356fc604d698
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 11 January 2019
                : 4 March 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001665, Agence Nationale de la Recherche (French National Research Agency);
                Award ID: ANR-15-CE17-0006-01
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100011272, EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health);
                Award ID: #305341
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100002915, Fondation pour la Recherche Médicale (Foundation for Medical Research in France);
                Award ID: FDT20160435543
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100004097, Fondation ARC pour la Recherche sur le Cancer (ARC Foundation for Cancer Research);
                Award ID: PJA20171206530
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                cancer models,prostate cancer
                Uncategorized
                cancer models, prostate cancer

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