Zebrafish patient avatars in cancer biology and precision cancer therapy.
Journal
Nature reviews. Cancer
ISSN: 1474-1768
Titre abrégé: Nat Rev Cancer
Pays: England
ID NLM: 101124168
Informations de publication
Date de publication:
05 2020
05 2020
Historique:
accepted:
05
03
2020
pubmed:
7
4
2020
medline:
25
7
2020
entrez:
7
4
2020
Statut:
ppublish
Résumé
In precision oncology, two major strategies are being pursued for predicting clinically relevant tumour behaviours, such as treatment response and emergence of drug resistance: inference based on genomic, transcriptomic, epigenomic and/or proteomic analysis of patient samples, and phenotypic assays in personalized cancer avatars. The latter approach has historically relied on in vivo mouse xenografts and in vitro organoids or 2D cell cultures. Recent progress in rapid combinatorial genetic modelling, the development of a genetically immunocompromised strain for xenotransplantation of human patient samples in adult zebrafish and the first clinical trial using xenotransplantation in zebrafish larvae for phenotypic testing of drug response bring this tiny vertebrate to the forefront of the precision medicine arena. In this Review, we discuss advances in transgenic and transplantation-based zebrafish cancer avatars, and how these models compare with and complement mouse xenografts and human organoids. We also outline the unique opportunities that these different models present for prediction studies and current challenges they face for future clinical deployment.
Identifiants
pubmed: 32251397
doi: 10.1038/s41568-020-0252-3
pii: 10.1038/s41568-020-0252-3
pmc: PMC8011456
mid: NIHMS1683766
doi:
Substances chimiques
Antineoplastic Agents
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
263-273Subventions
Organisme : NIH HHS
ID : R24 OD016761
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA154923
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA215118
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA103846
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA211734
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA226926
Pays : United States
Organisme : Howard Hughes Medical Institute
Pays : United States
Organisme : NCI NIH HHS
ID : P01 CA163222
Pays : United States
Références
National Cancer Institute. Targeted cancer therapies. NCI https://www.cancer.gov/about-cancer/treatment/types/targeted-therapies/targeted-therapies-fact-sheet (2020).
Morrison, C. Fresh from the biotech pipeline — 2018. Nat. Biotechnol. 37, 118–123 (2019).
doi: 10.1038/s41587-019-0021-6
pubmed: 30718867
Friedman, A. A., Letai, A., Fisher, D. E. & Flaherty, K. T. Precision medicine for cancer with next-generation functional diagnostics. Nat. Rev. Cancer 15, 747–756 (2015).
pubmed: 4970460
pmcid: 4970460
doi: 10.1038/nrc4015
Hyman, D. M., Taylor, B. S. & Baselga, J. Implementing genome-driven oncology. Cell 168, 584–599 (2017).
pubmed: 5463457
pmcid: 5463457
doi: 10.1016/j.cell.2016.12.015
Clohessy, J. G. & Pandolfi, P. P. Mouse hospital and co-clinical trial project — from bench to bedside. Nat. Rev. Clin. Oncol. 12, 491 (2015). This review discusses mouse co-clinical trials for precision cancer therapy.
doi: 10.1038/nrclinonc.2015.62
pubmed: 25895610
Drost, J. & Clevers, H. Organoids in cancer research. Nat. Rev. Cancer 18, 407–418 (2018).
doi: 10.1038/s41568-018-0007-6
pubmed: 29692415
Tuveson, D. & Clevers, H. Cancer modeling meets human organoid technology. Science 364, 952–955 (2019).
doi: 10.1126/science.aaw6985
pubmed: 31171691
Schwartzberg, L., Kim, E. S., Liu, D. & Schrag, D. Precision oncology: who, how, what, when, and when not? Am. Soc. Clin. Oncol. Educ. Book 37, 160–169 (2017).
doi: 10.14694/EDBK_174176
pubmed: 28561651
Strauss, D. G. & Blinova, K. Clinical trials in a dish. Trends Pharmacol. Sci. 38, 4–7 (2017).
doi: 10.1016/j.tips.2016.10.009
pubmed: 27876286
Aparicio, S., Hidalgo, M. & Kung, A. L. Examining the utility of patient-derived xenograft mouse models. Nat. Rev. Cancer 15, 311 (2015).
pubmed: 25907221
doi: 10.1038/nrc3944
pmcid: 25907221
Tentler, J. J. et al. Patient-derived tumour xenografts as models for oncology drug development. Nat. Rev. Clin. Oncol. 9, 338 (2012).
pubmed: 22508028
pmcid: 3928688
doi: 10.1038/nrclinonc.2012.61
Ablain, J. et al. Human tumor genomics and zebrafish modeling identify SPRED1 loss as a driver of mucosal melanoma. Science 362, 1055–1060 (2018). This article shows rapid generation of genetic avatars in zebrafish using combinatorial mosaic transgenesis.
pubmed: 30385465
pmcid: 6475924
doi: 10.1126/science.aau6509
Fior, R. et al. Single-cell functional and chemosensitive profiling of combinatorial colorectal therapy in zebrafish xenografts. Proc. Natl Acad. Sci. USA 114, E8234–E8243 (2017). This study conducts phenotypic drug response testing and migration scoring of PDXs in zebrafish larvae.
pubmed: 28835536
doi: 10.1073/pnas.1618389114
pmcid: 28835536
Yan, C. et al. Visualizing engrafted human cancer and therapy responses in immunodeficient zebrafish. Cell 177, 1903–1914 (2019). This article demonstrates establishment of PDXs in adult zebrafish.
pubmed: 31031007
doi: 10.1016/j.cell.2019.04.004
pmcid: 31031007
White, R., Rose, K. & Zon, L. Zebrafish cancer: the state of the art and the path forward. Nat. Rev. Cancer 13, 624–636 (2013).
pubmed: 23969693
pmcid: 6040891
doi: 10.1038/nrc3589
Pulak, R. Tools for automating the imaging of zebrafish larvae. Methods 96, 118–126 (2016).
pubmed: 26631716
doi: 10.1016/j.ymeth.2015.11.021
pmcid: 26631716
Zhao, Y. et al. A review of automated microinjection of zebrafish embryos. Micromachines 10, 7 (2018).
doi: 10.3390/mi10010007
pmcid: 6357019
Ablain, J., Durand, E. M., Yang, S., Zhou, Y. & Zon, L. I. A CRISPR/Cas9 vector system for tissue-specific gene disruption in zebrafish. Dev. Cell 32, 756–764 (2015).
pubmed: 25752963
pmcid: 25752963
doi: 10.1016/j.devcel.2015.01.032
Gengenbacher, N., Singhal, M. & Augustin, H. G. Preclinical mouse solid tumour models: status quo, challenges and perspectives. Nat. Rev. Cancer 17, 751 (2017).
pubmed: 29077691
pmcid: 29077691
doi: 10.1038/nrc.2017.92
Howe, K. et al. The zebrafish reference genome sequence and its relationship to the human genome. Nature 496, 498–503 (2013).
pubmed: 23594743
pmcid: 3703927
doi: 10.1038/nature12111
Carneiro, M. C., de Castro, I. P. & Ferreira, M. G. Telomeres in aging and disease: lessons from zebrafish. Dis. Model. Mech. 9, 737–748 (2016).
pubmed: 27482813
pmcid: 4958310
doi: 10.1242/dmm.025130
Berghmans, S. et al. Making waves in cancer research: new models in the zebrafish. Biotechniques 39, 227–237 (2005).
pubmed: 16116796
doi: 10.2144/05392RV02
pmcid: 16116796
Langenau, D. M. et al. Myc-induced T cell leukemia in transgenic zebrafish. Science 299, 887–890 (2003). This article reports the first transgenic cancer model in zebrafish.
pubmed: 12574629
doi: 10.1126/science.1080280
pmcid: 12574629
Yang, H. W. et al. Targeted expression of human MYCN selectively causes pancreatic neuroendocrine tumors in transgenic zebrafish. Cancer Res. 64, 7256–7262 (2004).
pubmed: 15492244
doi: 10.1158/0008-5472.CAN-04-0931
pmcid: 15492244
Patton, E. E. et al. BRAF mutations are sufficient to promote nevi formation and cooperate with p53 in the genesis of melanoma. Curr. Biol. 15, 249–254 (2005).
pubmed: 15694309
doi: 10.1016/j.cub.2005.01.031
pmcid: 15694309
Cagan, R. L., Zon, L. I. & White, R. M. Modeling cancer with flies and fish. Dev. Cell 49, 317–324 (2019).
pubmed: 31063751
doi: 10.1016/j.devcel.2019.04.013
pmcid: 31063751
Kirchberger, S., Sturtzel, C., Pascoal, S. & Distel, M. Quo natas, Danio? — Recent progress in modeling cancer in zebrafish. Front. Oncol. 7, 186 (2017).
pubmed: 28894696
pmcid: 5581328
doi: 10.3389/fonc.2017.00186
Letrado, P., de Miguel, I., Lamberto, I., Diez-Martinez, R. & Oyarzabal, J. Zebrafish: speeding up the cancer drug discovery process. Cancer Res. 78, 6048–6058 (2018).
pubmed: 30327381
doi: 10.1158/0008-5472.CAN-18-1029
pmcid: 30327381
Vogelstein, B. et al. Cancer genome landscapes. Science 339, 1546–1558 (2013).
pubmed: 23539594
pmcid: 3749880
doi: 10.1126/science.1235122
Vogelstein, B. & Kinzler, K. W. The path to cancer –three strikes and you’re out. N. Engl. J. Med. 373, 1895–1898 (2015).
pubmed: 26559569
pmcid: 26559569
doi: 10.1056/NEJMp1508811
McConnell, A. M. et al. Neural crest state activation in NRAS driven melanoma, but not in NRAS-driven melanocyte expansion. Dev. Biol. 449, 107–114 (2019).
doi: 10.1016/j.ydbio.2018.05.026
pubmed: 29883661
Pea, A., Hruban, R. H. & Wood, L. D. Genetics of pancreatic neuroendocrine tumors: implications for the clinic. Expert Rev. Gastroenterol. Hepatol. 9, 1407–1419 (2015).
pubmed: 26413978
pmcid: 26413978
doi: 10.1586/17474124.2015.1092383
Berghmans, S. et al. tp53 mutant zebrafish develop malignant peripheral nerve sheath tumors. Proc. Natl Acad. Sci. USA 102, 407–412 (2005).
doi: 10.1073/pnas.0406252102
pubmed: 15630097
Ceol, C. J. et al. The histone methyltransferase SETDB1 is recurrently amplified in melanoma and accelerates its onset. Nature 471, 513–517 (2011).
pubmed: 21430779
pmcid: 21430779
doi: 10.1038/nature09806
Kendall, G. C. et al. PAX3-FOXO1 transgenic zebrafish models identify HES3 as a mediator of rhabdomyosarcoma tumorigenesis. eLife 7, e33800 (2018).
pubmed: 5988421
pmcid: 5988421
doi: 10.7554/eLife.33800
Langenau, D. M. et al. Effects of RAS on the genesis of embryonal rhabdomyosarcoma. Genes Dev. 21, 1382–1395 (2007).
pubmed: 17510286
pmcid: 17510286
doi: 10.1101/gad.1545007
Sanchez-Rivera, F. J. & Jacks, T. Applications of the CRISPR-Cas9 system in cancer biology. Nat. Rev. Cancer 15, 387–395 (2015).
pubmed: 4530801
pmcid: 4530801
doi: 10.1038/nrc3950
Hwang, W. Y. et al. Efficient genome editing in zebrafish using a CRISPR-Cas system. Nat. Biotechnol. 31, 227–229 (2013). This study reports the first use of CRISPR in zebrafish.
pubmed: 23360964
pmcid: 23360964
doi: 10.1038/nbt.2501
Kawakami, K. et al. A transposon-mediated gene trap approach identifies developmentally regulated genes in zebrafish. Dev. Cell 7, 133–144 (2004).
pubmed: 15239961
pmcid: 15239961
doi: 10.1016/j.devcel.2004.06.005
Heppt, M. V. et al. Prognostic significance of BRAF and NRAS mutations in melanoma: a German study from routine care. BMC Cancer 17, 536 (2017).
pubmed: 28797232
pmcid: 28797232
doi: 10.1186/s12885-017-3529-5
Shain, A. H. et al. The genetic evolution of melanoma from precursor lesions. N. Engl. J. Med. 373, 1926–1936 (2015).
pubmed: 26559571
pmcid: 26559571
doi: 10.1056/NEJMoa1502583
Burns, M. A. et al. Hedgehog pathway mutations drive oncogenic transformation in high-risk T-cell acute lymphoblastic leukemia. Leukemia 32, 2126–2137 (2018).
pubmed: 29654263
pmcid: 29654263
doi: 10.1038/s41375-018-0097-x
Callahan, S. J. et al. Cancer modeling by transgene electroporation in adult zebrafish (TEAZ). Dis. Model. Mech. 11, (2018). This article shows mosaic transgenesis in adult zebrafish through electroporation of plasmid DNA.
White, R. M. et al. Transparent adult zebrafish as a tool for in vivo transplantation analysis. Cell Stem Cell 2, 183–189 (2008). This article reports development of the optically clear casper zebrafish strain often used for transplantation studies.
pubmed: 18371439
pmcid: 18371439
doi: 10.1016/j.stem.2007.11.002
Weintraub, A. All eyes on zebrafish. Lab. Anim. 46, 323–326 (2017).
doi: 10.1038/laban.1321
Smith, A. C. et al. High-throughput cell transplantation establishes that tumor-initiating cells are abundant in zebrafish T-cell acute lymphoblastic leukemia. Blood 115, 3296–3303 (2010).
pubmed: 20056790
pmcid: 20056790
doi: 10.1182/blood-2009-10-246488
Blackburn, J. S. et al. Clonal evolution enhances leukemia-propagating cell frequency in T cell acute lymphoblastic leukemia through Akt/mTORC1 pathway activation. Cancer Cell 25, 366–378 (2014).
pubmed: 3992437
pmcid: 3992437
doi: 10.1016/j.ccr.2014.01.032
Tang, Q. et al. Optimized cell transplantation using adult rag2 mutant zebrafish. Nat. Methods 11, 821–824 (2014). This article reports allotransplantation of zebrafish tumours in immunocompromised recipients.
pubmed: 25042784
pmcid: 25042784
doi: 10.1038/nmeth.3031
Tang, Q. et al. Imaging tumour cell heterogeneity following cell transplantation into optically clear immune-deficient zebrafish. Nat. Commun. 7, 10358 (2016).
pubmed: 4735845
pmcid: 4735845
doi: 10.1038/ncomms10358
Hayes, M. N. et al. Vangl2/RhoA signaling pathway regulates stem cell self-renewal programs and growth in rhabdomyosarcoma. Cell Stem Cell 22, 414–427.e6 (2018).
pubmed: 29499154
pmcid: 29499154
doi: 10.1016/j.stem.2018.02.002
Ignatius, M. S. et al. The NOTCH1/SNAIL1/MEF2C pathway regulates growth and self-renewal in embryonal rhabdomyosarcoma. Cell Rep. 19, 2304–2318 (2017).
pubmed: 28614716
pmcid: 28614716
doi: 10.1016/j.celrep.2017.05.061
Moore, J. C. et al. Single-cell imaging of normal and malignant cell engraftment into optically clear prkdc-null SCID zebrafish. J. Exp. Med. 213, 2575–2589 (2016).
pubmed: 27810924
pmcid: 27810924
doi: 10.1084/jem.20160378
Tenente, I. M. et al. Myogenic regulatory transcription factors regulate growth in rhabdomyosarcoma. eLife 6, e19214 (2017).
pubmed: 28080960
pmcid: 28080960
doi: 10.7554/eLife.19214
Li, P. et al. Epoxyeicosatrienoic acids enhance embryonic haematopoiesis and adult marrow engraftment. Nature 523, 468–471 (2015).
pubmed: 26201599
pmcid: 26201599
doi: 10.1038/nature14569
Tamplin, O. J. et al. Hematopoietic stem cell arrival triggers dynamic remodeling of the perivascular niche. Cell 160, 241–252 (2015).
pubmed: 25594182
pmcid: 25594182
doi: 10.1016/j.cell.2014.12.032
Heilmann, S. et al. A quantitative system for studying metastasis using transparent zebrafish. Cancer Res. 75, 4272–4282 (2015).
pubmed: 26282170
pmcid: 26282170
doi: 10.1158/0008-5472.CAN-14-3319
Zhang, M. et al. Adipocyte-derived lipids mediate melanoma progression via FATP proteins. Cancer Discov. 8, 1006–1025 (2018).
pubmed: 29903879
pmcid: 29903879
doi: 10.1158/2159-8290.CD-17-1371
Nicoli, S., Ribatti, D., Cotelli, F. & Presta, M. Mammalian tumor xenografts induce neovascularization in zebrafish embryos. Cancer Res. 67, 2927–2931 (2007).
pubmed: 17409396
pmcid: 17409396
doi: 10.1158/0008-5472.CAN-06-4268
Haldi, M., Ton, C., Seng, W. L. & McGrath, P. Human melanoma cells transplanted into zebrafish proliferate, migrate, produce melanin, form masses and stimulate angiogenesis in zebrafish. Angiogenesis 9, 139–151 (2006).
pubmed: 17051341
pmcid: 17051341
doi: 10.1007/s10456-006-9040-2
Topczewska, J. M. et al. Embryonic and tumorigenic pathways converge via Nodal signaling: role in melanoma aggressiveness. Nat. Med. 12, 925–932 (2006).
doi: 10.1038/nm1448
pubmed: 16892036
Mercatali, L. et al. Development of a patient-derived xenograft (PDX) of breast cancer bone metastasis in a zebrafish model. Int. J. Mol. Sci. 17, 1375 (2016).
pubmed: 5000770
pmcid: 5000770
doi: 10.3390/ijms17081375
Bentley, V. L. et al. Focused chemical genomics using zebrafish xenotransplantation as a pre-clinical therapeutic platform for T-cell acute lymphoblastic leukemia. Haematologica 100, 70–76 (2015).
pubmed: 4281315
pmcid: 4281315
doi: 10.3324/haematol.2014.110742
Lin, J. et al. A clinically relevant in vivo zebrafish model of human multiple myeloma to study preclinical therapeutic efficacy. Blood 128, 249–252 (2016).
pubmed: 4946203
pmcid: 4946203
doi: 10.1182/blood-2016-03-704460
Chapman, A. et al. Heterogeneous tumor subpopulations cooperate to drive invasion. Cell Rep. 8, 688–695 (2014).
pubmed: 4542310
pmcid: 4542310
doi: 10.1016/j.celrep.2014.06.045
Renshaw, S. A. & Trede, N. S. A model 450 million years in the making: zebrafish and vertebrate immunity. Dis. Model. Mech. 5, 38–47 (2012).
pubmed: 3255542
pmcid: 3255542
doi: 10.1242/dmm.007138
Langenau, D. M. et al. In vivo tracking of T cell development, ablation, and engraftment in transgenic zebrafish. Proc. Natl Acad. Sci. USA 101, 7369–7374 (2004).
doi: 10.1073/pnas.0402248101
pubmed: 15123839
Tang, Q. et al. Dissecting hematopoietic and renal cell heterogeneity in adult zebrafish at single-cell resolution using RNA sequencing. J. Exp. Med. 214, 2875–2887 (2017).
pubmed: 5626406
pmcid: 5626406
doi: 10.1084/jem.20170976
Trede, N. S., Langenau, D. M., Traver, D., Look, A. T. & Zon, L. I. The use of zebrafish to understand immunity. Immunity 20, 367–379 (2004).
pubmed: 15084267
pmcid: 15084267
doi: 10.1016/S1074-7613(04)00084-6
Willett, C. E., Cortes, A., Zuasti, A. & Zapata, A. G. Early hematopoiesis and developing lymphoid organs in the zebrafish. Dev. Dyn. 214, 323–336 (1999).
pubmed: 10213388
pmcid: 10213388
doi: 10.1002/(SICI)1097-0177(199904)214:4<323::AID-AJA5>3.0.CO;2-3
Konantz, M. et al. Zebrafish xenografts as a tool for in vivo studies on human cancer. Ann. NY Acad. Sci. 1266, 124–137 (2012).
doi: 10.1111/j.1749-6632.2012.06575.x
pubmed: 22901264
He, S. et al. Neutrophil-mediated experimental metastasis is enhanced by VEGFR inhibition in a zebrafish xenograft model. J. Pathol. 227, 431–445 (2012).
pubmed: 3504093
pmcid: 3504093
doi: 10.1002/path.4013
Visvader, J. E. & Lindeman, G. J. Cancer stem cells: current status and evolving complexities. Cell Stem Cell 10, 717–728 (2012).
doi: 10.1016/j.stem.2012.05.007
pubmed: 22704512
Stoletov, K., Montel, V., Lester, R. D., Gonias, S. L. & Klemke, R. High-resolution imaging of the dynamic tumor cell vascular interface in transparent zebrafish. Proc. Natl Acad. Sci. USA 104, 17406–17411 (2007).
doi: 10.1073/pnas.0703446104
pubmed: 17954920
Traver, D. et al. Transplantation and in vivo imaging of multilineage engraftment in zebrafish bloodless mutants. Nat. Immunol. 4, 1238–1246 (2003).
doi: 10.1038/ni1007
pubmed: 14608381
Traver, D. et al. Effects of lethal irradiation in zebrafish and rescue by hematopoietic cell transplantation. Blood 104, 1298–1305 (2004).
doi: 10.1182/blood-2004-01-0100
pubmed: 15142873
Larsen, E. C. et al. Dexamethasone and high-dose methotrexate improve outcome for children and young adults with high-risk B-acute lymphoblastic leukemia: a report from Children’s Oncology Group Study AALL0232. J. Clin. Oncol. 34, 2380–2388 (2016).
pubmed: 4981974
pmcid: 4981974
doi: 10.1200/JCO.2015.62.4544
Matsuda, M. et al. Human NK cell development in hIL-7 and hIL-15 knockin NOD/SCID/IL2rgKO mice. Life Sci. Alliance 2, 201800195 (2019).
doi: 10.26508/lsa.201800195
Herndler-Brandstetter, D. et al. Humanized mouse model supports development, function, and tissue residency of human natural killer cells. Proc. Natl Acad. Sci. USA 114, E9626–E9634 (2017). This article reports engineering of NSG mice towards humanized models and more robust PDX support.
doi: 10.1073/pnas.1705301114
pubmed: 29078283
Dang, M., Henderson, R. E., Garraway, L. A. & Zon, L. I. Long-term drug administration in the adult zebrafish using oral gavage for cancer preclinical studies. Dis. Model. Mech. 9, 811–820 (2016). This study administers a drug in adult zebrafish through intraperitoneal injection and oral gavage.
pubmed: 4958307
pmcid: 4958307
doi: 10.1242/dmm.024166
Samaee, S. M., Seyedin, S. & Varga, Z. M. An affordable intraperitoneal injection setup for juvenile and adult zebrafish. Zebrafish 14, 77–79 (2017).
pubmed: 27841973
pmcid: 27841973
doi: 10.1089/zeb.2016.1322
Usai, A. et al. A model of zebrafish avatar for co-clinical trials. Cancers 12, 677 (2019). This article reports preliminary results of zebrafish co-clinical trial NCT03668418.
doi: 10.3390/cancers12030677
Eisenhauer, E. A. et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur. J. Cancer 45, 228–247 (2009).
pubmed: 19097774
pmcid: 19097774
doi: 10.1016/j.ejca.2008.10.026
Goessling, W., North, T. E. & Zon, L. I. Ultrasound biomicroscopy permits in vivo characterization of zebrafish liver tumors. Nat. Methods 4, 551–553 (2007).
pubmed: 17572681
pmcid: 17572681
doi: 10.1038/nmeth1059
Jin, Y. et al. Comparison of efficacy and toxicity of bevacizumab, endostar and apatinib in transgenic and human lung cancer xenograft zebrafish model. Sci. Rep. 8, 15837 (2018).
pubmed: 30367145
pmcid: 30367145
doi: 10.1038/s41598-018-34030-5
Chen, C. et al. A multiplex preclinical model for adenoid cystic carcinoma of the salivary gland identifies regorafenib as a potential therapeutic drug. Sci. Rep. 7, 11410 (2017).
pubmed: 28900283
pmcid: 28900283
doi: 10.1038/s41598-017-11764-2
Wu, J. Q. et al. Patient-derived xenograft in zebrafish embryos: a new platform for translational research in gastric cancer. J. Exp. Clin. Cancer Res. 36, 160 (2017).
pubmed: 5688753
pmcid: 5688753
doi: 10.1186/s13046-017-0631-0
Wang, L. et al. Patient-derived heterogeneous xenograft model of pancreatic cancer using zebrafish larvae as hosts for comparative drug assessment. J. Vis. Exp. 146, e59507 (2019). This is a method guide for the drug testing of zPDXs in larvae.
Ikonomopoulou, M. P. et al. Gomesin inhibits melanoma growth by manipulating key signaling cascades that control cell death and proliferation. Sci. Rep. 8, 11519 (2018).
pubmed: 6070509
pmcid: 6070509
doi: 10.1038/s41598-018-29826-4
Wang, G. et al. The novel autophagy inhibitor elaiophylin exerts antitumor activity against multiple myeloma with mutant TP53 in part through endoplasmic reticulum stress-induced apoptosis. Cancer Biol. Ther. 18, 584–595 (2017).
pubmed: 5653199
pmcid: 5653199
doi: 10.1080/15384047.2017.1345386
von Massenhausen, A. et al. Targeting DDR2 in head and neck squamous cell carcinoma with dasatinib. Int. J. Cancer 139, 2359–2369 (2016).
doi: 10.1002/ijc.30279
Ochoa-Alvarez, J. A. et al. Antibody and lectin target podoplanin to inhibit oral squamous carcinoma cell migration and viability by distinct mechanisms. Oncotarget 6, 9045–9060 (2015).
pubmed: 25826087
pmcid: 4496201
doi: 10.18632/oncotarget.3515
Ghotra, V. P. et al. SYK is a candidate kinase target for the treatment of advanced prostate cancer. Cancer Res. 75, 230–240 (2015).
pubmed: 25388286
doi: 10.1158/0008-5472.CAN-14-0629
pmcid: 25388286
van der Ent, W. et al. Ewing sarcoma inhibition by disruption of EWSR1-FLI1 transcriptional activity and reactivation of p53. J. Pathol. 233, 415–424 (2014).
pubmed: 24974828
doi: 10.1002/path.4378
pmcid: 24974828
Tan, D. S. et al. Bosutinib inhibits migration and invasion via ACK1 in KRAS mutant non-small cell lung cancer. Mol. Cancer 13, 13 (2014).
pubmed: 24461128
pmcid: 3930897
doi: 10.1186/1476-4598-13-13
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT01858168 (2013).
Liu, P. H. et al. An IRAK1-PIN1 signalling axis drives intrinsic tumour resistance to radiation therapy. Nat. Cell Biol. 21, 203–213 (2019).
pubmed: 30664786
pmcid: 6428421
doi: 10.1038/s41556-018-0260-7
Smith, M. P. et al. Effect of SMURF2 targeting on susceptibility to MEK inhibitors in melanoma. J. Natl Cancer Inst. 105, 33–46 (2013).
pubmed: 23250956
doi: 10.1093/jnci/djs471
pmcid: 23250956
Yoganantharjah, P. & Gibert, Y. The use of the zebrafish model to aid in drug discovery and target validation. Curr. Top. Med. Chem. 17, 2041–2055 (2017).
pubmed: 28137236
doi: 10.2174/1568026617666170130112109
pmcid: 28137236
Sarmah, S. & Marrs, J. A. Zebrafish as a vertebrate model system to evaluate effects of environmental toxicants on cardiac development and function. Int. J. Mol. Sci. 17, 2123 (2016).
pmcid: 5187923
doi: 10.3390/ijms17122123
Chakraborty, C., Sharma, A. R., Sharma, G. & Lee, S. S. Zebrafish: a complete animal model to enumerate the nanoparticle toxicity. J. Nanobiotech. 14, 65 (2016).
doi: 10.1186/s12951-016-0217-6
Kanungo, J., Cuevas, E., Ali, S. F. & Paule, M. G. Zebrafish model in drug safety assessment. Curr. Pharm. Des. 20, 5416–5429 (2014).
pubmed: 24502596
doi: 10.2174/1381612820666140205145658
pmcid: 24502596
Chakravarthy, S., Sadagopan, S., Nair, A. & Sukumaran, S. K. Zebrafish as an in vivo high-throughput model for genotoxicity. Zebrafish 11, 154–166 (2014).
pubmed: 24428353
doi: 10.1089/zeb.2013.0924
pmcid: 24428353
Peterson, R. T. & Macrae, C. A. Systematic approaches to toxicology in the zebrafish. Annu. Rev. Pharmacol. Toxicol. 52, 433–453 (2012).
pubmed: 22017682
doi: 10.1146/annurev-pharmtox-010611-134751
pmcid: 22017682
Boumahdi, S. & de Sauvage, F. J. The great escape: tumour cell plasticity in resistance to targeted therapy. Nat. Rev. Drug Discov. 19, 39–56 (2020).
pubmed: 31601994
doi: 10.1038/s41573-019-0044-1
pmcid: 31601994
Yao, Y. et al. Patient-derived organoids predict chemoradiation responses of locally advanced rectal cancer. Cell Stem Cell 26, 17–26.e6 (2020). This article reports the use of organoids to assess drug response in the neoadjuvant setting.
pubmed: 31761724
doi: 10.1016/j.stem.2019.10.010
pmcid: 31761724
Fazio, M. & Zon, L. I. Fishing for answers in precision cancer medicine. Proc. Natl Acad. Sci. USA 114, 10306–10308 (2017).
pubmed: 28916734
doi: 10.1073/pnas.1713769114
pmcid: 28916734
Baeten, J. T. & de Jong, J. L. O. Genetic models of leukemia in zebrafish. Front. Cell Dev. Biol. 6, 115 (2018).
pubmed: 30294597
pmcid: 6158309
doi: 10.3389/fcell.2018.00115
Kurata, M. et al. Highly multiplexed genome engineering using CRISPR/Cas9 gRNA arrays. PLoS one 13, e0198714 (2018).
pubmed: 30222773
pmcid: 6141065
doi: 10.1371/journal.pone.0198714
Zhang, Y. et al. A gRNA-tRNA array for CRISPR-Cas9 based rapid multiplexed genome editing in Saccharomyces cerevisiae. Nat. Commun. 10, 1053 (2019).
pubmed: 30837474
pmcid: 6400946
doi: 10.1038/s41467-019-09005-3
Kuzu, O. F., Nguyen, F. D., Noory, M. A. & Sharma, A. Current state of animal (mouse) modeling in melanoma research. Cancer Growth Metastasis 8 (Suppl. 1), 81–94 (2015).
pubmed: 4597587
pmcid: 4597587
Xue, W. et al. CRISPR-mediated direct mutation of cancer genes in the mouse liver. Nature 514, 380–384 (2014).
pubmed: 4199937
pmcid: 4199937
doi: 10.1038/nature13589
Sanchez-Rivera, F. J. et al. Rapid modelling of cooperating genetic events in cancer through somatic genome editing. Nature 516, 428–431 (2014). This article reports mosaic transgenesis in mouse cancer models.
pubmed: 4292871
pmcid: 4292871
doi: 10.1038/nature13906
National Research Council. Guide for the Care and Use of Laboratory Animals 8th edn (National Academies Press, 2011)
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT03668418 (2018).
Vlachogiannis, G. et al. Patient-derived organoids model treatment response of metastatic gastrointestinal cancers. Science 359, 920–926 (2018).
pubmed: 6112415
pmcid: 6112415
doi: 10.1126/science.aao2774
Tiriac, H. et al. Organoid profiling identifies common responders to chemotherapy in pancreatic cancer. Cancer Discov. 8, 1112–1129 (2018).
pubmed: 6125219
pmcid: 6125219
doi: 10.1158/2159-8290.CD-18-0349
Ganesh, K. et al. A rectal cancer organoid platform to study individual responses to chemoradiation. Nat. Med. 25, 1607–1614 (2019).
doi: 10.1038/s41591-019-0584-2
pubmed: 31591597
Ben-David, U., Beroukhim, R. & Golub, T. R. Genomic evolution of cancer models: perils and opportunities. Nat. Rev. Cancer 19, 97–109 (2019).
pubmed: 30578414
pmcid: 30578414
doi: 10.1038/s41568-018-0095-3
Wang, K. et al. Patient-derived xenotransplants can recapitulate the genetic driver landscape of acute leukemias. Leukemia 31, 151–158 (2017).
doi: 10.1038/leu.2016.166
pubmed: 27363283
Ben-David, U. et al. Patient-derived xenografts undergo mouse-specific tumor evolution. Nat. Genet. 49, 1567–1575 (2017). This article shows the evolution of mouse PDXs compared with donor patients.
pubmed: 28991255
pmcid: 28991255
doi: 10.1038/ng.3967
Ooft, S. N. et al. Patient-derived organoids can predict response to chemotherapy in metastatic colorectal cancer patients. Sci. Transl Med. 11, eaay2574 (2019).
pubmed: 31597751
pmcid: 31597751
doi: 10.1126/scitranslmed.aay2574
Hirata, E. & Sahai, E. Tumor microenvironment and differential responses to therapy. Cold Spring Harb. Perspect. Med. https://doi.org/10.1101/cshperspect.a026781 (2017).
doi: 10.1101/cshperspect.a026781
pubmed: 28213438
pmcid: 28213438
Binnewies, M. et al. Understanding the tumor immune microenvironment (TIME) for effective therapy. Nat. Med. 24, 541–550 (2018).
pubmed: 5998822
pmcid: 5998822
doi: 10.1038/s41591-018-0014-x
Vargas, R. et al. Case study: patient-derived clear cell adenocarcinoma xenograft model longitudinally predicts treatment response. NPJ Precis. Oncol. 2, 14 (2018).
pubmed: 30202792
pmcid: 30202792
doi: 10.1038/s41698-018-0060-3
Nardella, C., Lunardi, A., Patnaik, A., Cantley, L. C. & Pandolfi, P. P. The APL paradigm and the ‘co-clinical trial’ project. Cancer Discov. 1, 108–116 (2011).
pubmed: 22116793
pmcid: 22116793
doi: 10.1158/2159-8290.CD-11-0061