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      Applications of patient-derived tumor xenograft models and tumor organoids

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          Abstract

          Patient-derived tumor xenografts (PDXs), in which tumor fragments surgically dissected from cancer patients are directly transplanted into immunodeficient mice, have emerged as a useful model for translational research aimed at facilitating precision medicine. PDX susceptibility to anti-cancer drugs is closely correlated with clinical data in patients, from whom PDX models have been derived. Accumulating evidence suggests that PDX models are highly effective in predicting the efficacy of both conventional and novel anti-cancer therapeutics. This also allows “co-clinical trials,” in which pre-clinical investigations in vivo and clinical trials could be performed in parallel or sequentially to assess drug efficacy in patients and PDXs. However, tumor heterogeneity present in PDX models and in the original tumor samples constitutes an obstacle for application of PDX models. Moreover, human stromal cells originally present in tumors dissected from patients are gradually replaced by host stromal cells as the xenograft grows. This replacement by murine stroma could preclude analysis of human tumor-stroma interactions, as some mouse stromal cytokines might not affect human carcinoma cells in PDX models. The present review highlights the biological and clinical significance of PDX models and three-dimensional patient-derived tumor organoid cultures of several kinds of solid tumors, such as those of the colon, pancreas, brain, breast, lung, skin, and ovary.

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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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            Personalized In Vitro and In Vivo Cancer Models to Guide Precision Medicine.

            Precision medicine is an approach that takes into account the influence of individuals' genes, environment, and lifestyle exposures to tailor interventions. Here, we describe the development of a robust precision cancer care platform that integrates whole-exome sequencing with a living biobank that enables high-throughput drug screens on patient-derived tumor organoids. To date, 56 tumor-derived organoid cultures and 19 patient-derived xenograft (PDX) models have been established from the 769 patients enrolled in an Institutional Review Board-approved clinical trial. Because genomics alone was insufficient to identify therapeutic options for the majority of patients with advanced disease, we used high-throughput drug screening to discover effective treatment strategies. Analysis of tumor-derived cells from four cases, two uterine malignancies and two colon cancers, identified effective drugs and drug combinations that were subsequently validated using 3-D cultures and PDX models. This platform thereby promotes the discovery of novel therapeutic approaches that can be assessed in clinical trials and provides personalized therapeutic options for individual patients where standard clinical options have been exhausted.Significance: Integration of genomic data with drug screening from personalized in vitro and in vivo cancer models guides precision cancer care and fuels next-generation research. Cancer Discov; 7(5); 462-77. ©2017 AACR.See related commentary by Picco and Garnett, p. 456This article is highlighted in the In This Issue feature, p. 443.
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              Acquired resistance to TKIs in solid tumours: learning from lung cancer.

              The use of advanced molecular profiling to direct the use of targeted therapy, such as tyrosine kinase inhibitors (TKIs) for patients with advanced-stage non-small-cell lung cancer (NSCLC), has revolutionized the treatment of this disease. However, acquired resistance, defined as progression after initial benefit, to targeted therapies inevitably occurs. This Review explores breakthroughs in the understanding and treatment of acquired resistance in NSCLC, focusing on EGFR mutant and ALK rearrangement-positive disease, which may be relevant across multiple different solid malignancies with oncogene-addicted subtypes. Mechanisms of acquired resistance may be pharmacological (that is, failure of delivery of the drug to its target) or biological, resulting from evolutionary selection on molecularly diverse tumours. A number of clinical approaches can maintain control of the disease in the acquired resistance setting, including the use of radiation to treat isolated areas of progression and adding or switching to cytotoxic chemotherapy. Furthermore, novel approaches that have already proven successful include the development of second-generation and third-generation inhibitors and the combination of some of these inhibitors with antibodies directed against the same target. With our increased understanding of the spectrum of acquired resistance, major changes in how we conduct clinical research in this setting are now underway.
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                Author and article information

                Contributors
                go-yoshida@juntendo.ac.jp
                Journal
                J Hematol Oncol
                J Hematol Oncol
                Journal of Hematology & Oncology
                BioMed Central (London )
                1756-8722
                7 January 2020
                7 January 2020
                2020
                : 13
                : 4
                Affiliations
                [1 ]ISNI 0000 0004 1762 2738, GRID grid.258269.2, Department of Pathology and Oncology, , Juntendo University School of Medicine, ; 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-8412 Japan
                [2 ]ISNI 0000 0004 1762 2738, GRID grid.258269.2, Present Address: Department of Immunological Diagnosis, , Juntendo University Graduate School of Medicine, ; 2-1-1, Hongo, Bunkyo-ku, Tokyo, 113-8412 Japan
                Author information
                http://orcid.org/0000-0002-1472-892X
                Article
                829
                10.1186/s13045-019-0829-z
                6947974
                31910904
                ddf4cd7f-0548-4f96-9190-aa36b832845c
                © The Author(s). 2020

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 17 October 2019
                : 13 November 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001691, Japan Society for the Promotion of Science;
                Award ID: 19K23898
                Award Recipient :
                Categories
                Review
                Custom metadata
                © The Author(s) 2020

                Oncology & Radiotherapy
                acquired resistance,avatar models,carcinoma-associated fibroblasts,co-clinical trials,heterogeneity,immunodeficient mice,organoids,pdx models,translational research,tumor microenvironment

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