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Preclinical Organotypic Models for the Assessment of Novel Cancer Therapeutics and Treatment

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Three Dimensional Human Organotypic Models for Biomedical Research

Part of the book series: Current Topics in Microbiology and Immunology ((CT MICROBIOLOGY,volume 430))

Abstract

The immense costs in both financial terms and preclinical research effort that occur in the development of anticancer drugs are unfortunately not matched by a substantial increase in improved clinical therapies due to the high rate of failure during clinical trials. This may be due to issues with toxicity or lack of clinical effectiveness when the drug is evaluated in patients. Currently, much cancer research is driven by the need to develop therapies that can exploit cancer cell adaptations to conditions in the tumor microenvironment such as acidosis and hypoxia, the requirement for more-specific, targeted treatments, or the exploitation of ‘precision medicine’ that can target known genomic changes in patient DNA. The high attrition rate for novel anticancer therapies suggests that the preclinical methods used in screening anticancer drugs need improvement. This chapter considers the advantages and disadvantages of 3D organotypic models in both cancer research and cancer drug screening, particularly in the areas of targeted drugs and the exploitation of genomic changes that can be used for therapeutic advantage in precision medicine.

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References

  • Aparicio S, Hidalgo M, Kung AL (2015) Examining the utility of patient-derived xenograft mouse models. Nat Rev Cancer 15:311–316

    CAS  PubMed  Google Scholar 

  • Arrowsmith J (2011) Trial watch: phase II failures: 2008–2010. Nat Rev Drug Discov 10:328–329

    CAS  PubMed  Google Scholar 

  • Bayin NS et al (2016) Patient-specific screening using high-grade glioma explants to determine potential radiosensitization by a TGF-β small molecule inhibitor. Neoplasia 18:795–805

    CAS  PubMed  PubMed Central  Google Scholar 

  • Bazou D, Maimon N, Gruionu G, Munn LL (2016) Self-assembly of vascularized tissue to support tumor explants in vitro. Integr Biol 8:1301–1311

    CAS  Google Scholar 

  • Bell-McGuinn KM, Garfall AL, Bogyo M, Hanahan D, Joyce JA (2007) Inhibition of cysteine cathepsin protease activity enhances chemotherapy regimens by decreasing tumor growth and invasiveness in a mouse model of multistage cancer. Cancer Res 67:7378–7385

    CAS  PubMed  Google Scholar 

  • Bellmunt J et al (2010) Activity of a multitargeted chemo-switch regimen (sorafenib, gemcitabine and metronomic capecitabine) in metastatic renal-cell carcinoma: a phase 2 study (ISOGUG-02-06). Lancet Oncol 11:350–357

    CAS  PubMed  Google Scholar 

  • Beloribi-Djefaflia S, Siret C, Lombardo D (2015) Exosomal lipids induce human pancreatic tumoral MiaPaCa-2 cells resistance through the CXCR4-SDF-1α signaling axis. Oncoscience 2:15–30

    PubMed  Google Scholar 

  • Belteki G et al (2005) Conditional and inducible transgene expression in mice through the combinatorial use of Cre-mediated recombination and tetracycline induction. Nucl Acids Res 33:e51

    PubMed  PubMed Central  Google Scholar 

  • Ben-David U et al (2017) Patient-derived xenografts undergo mouse-specific tumor evolution. Nat Genet 49:1567–1575

    CAS  PubMed  PubMed Central  Google Scholar 

  • Bhattacharyya S et al (2017) CDKN2A-p53 mediated antitumor effect of Lupeol in head and neck cancer. Cell Oncol 40:145–155

    CAS  Google Scholar 

  • Boedigheimer MJ, Freeman DJ, Kiaei P, Damore MA, Radinsky R (2013) Gene expression profiles can predict panitumumab monoterapy responsiveness in human tumor xenograft models. Neoplasia 15:125–132

    CAS  PubMed  PubMed Central  Google Scholar 

  • Boehnke K et al (2016) Assay establishment and validation of a high-throughput screening platform for three-dimensional patient-derived colon cancer organoid cultures. J Biomol Screen 21:931–941

    CAS  PubMed  PubMed Central  Google Scholar 

  • Boj SF et al (2015) Organoid models of human and mouse ductal pancreatic cancer. Cell 160:324–338

    CAS  PubMed  Google Scholar 

  • Boj SF et al (2016) Model organoids provide new research opportunities for ductal pancreatic cancer. Mol Cell Oncology 3(1):e1014757

    Google Scholar 

  • Bolenz C et al (2009) Topical chemotherapy in human urothelial carcinoma explants: a novel translational tool for preclinical evaluation of experimental intravesical therapies. Eur Urol 56:504–511

    CAS  PubMed  Google Scholar 

  • Bomken S, Fiser K, Heidenreich O, Vormoor J (2010) Understanding the cancer stem cell. Br J Cancer 103:439–445

    CAS  PubMed  PubMed Central  Google Scholar 

  • Broutier et al (2017) Human primary liver cancer-derived organoid cultures for disease modeling and drug screening. Nature Med 23:1424–1435

    CAS  PubMed  Google Scholar 

  • Bruna A et al (2016) A biobank of breast cancer explants with preserved intra-tumor heterogeneity to screen anticancer compounds. Cell 167:260–274

    CAS  PubMed  PubMed Central  Google Scholar 

  • Burdall SE, Hanby AM, Lansdown MR, Speirs V (2003) Breast cancer cell lines: friend or foe? Breast Cancer Res 5:89–95

    PubMed  PubMed Central  Google Scholar 

  • Byrne AT et al (2017) Interrogating open issues in cancer precision medicine with patient-derived xenografts. Nature Rev Cancer 17:254–268

    CAS  Google Scholar 

  • Capodanno Y et al (2018) Notch pathway inhibition targets chemoresistant insulinoma cancer stem cells. Endocr Relat Cancer 25:131–144

    CAS  PubMed  Google Scholar 

  • Caponigro G, Sellers WR (2011) Advances in the preclinical testing of cancer therapeutic hypotheses. Nat Rev Drug Discov 10:179–187

    CAS  PubMed  Google Scholar 

  • Chen Z et al (2012) A murine lung cancer co-clinical trial identifies genetic modifiers of therapeutic response. Nature 485:613–617

    Google Scholar 

  • Cheung KJ, Gabrielson E, Werb Z, Ewald AJ (2013) Collective invasion in breast cancer requires a conserved basal epithelial program. Cell 155:1639–1651

    CAS  PubMed  PubMed Central  Google Scholar 

  • Clark AK et al (2013) A bioengineered microenvironment to quantitatively measure the tumorigenic properties of cancer-associated fibroblasts in human prostate cancer. Biomaterials 34:4777–4785

    CAS  PubMed  Google Scholar 

  • Cornel KMC et al (2012) Overexpression of 17β-hydroxysteroid dehydrogenase type 1 increases the exposure of endometrial cancer to 17β-estradiol. J Clin Endocrinol Metab 97:E591–E601

    CAS  PubMed  Google Scholar 

  • Correia AL, Bissell MJ (2012) The tumor microenvironment is a dominant force in multidrug resistance. Drug Resist Update 15:39–49

    CAS  Google Scholar 

  • Crawford Y et al (2009) PDGF-C mediates the angiogenic and tumorigenic properties of fibroblasts associated with tumors refractory to anti-VEGF treatment. Cancer Cell 15:21–34

    CAS  PubMed  Google Scholar 

  • Daniel VC et al (2009) A primary xenograft model of small-cell lung cancer reveals irreversible changes in gene expression imposed by culture in vitro. Cancer Res 69:3364–3373

    CAS  PubMed  PubMed Central  Google Scholar 

  • Dean JL et al (2012) Therapeutic response to CDK4/6 inhibition in breast cancer defined by ex vivo analyses of human tumors. Cell Cycle 11:2756–2761

    CAS  PubMed  PubMed Central  Google Scholar 

  • Dekkers JF et al (2013) A functional CFTR assay using primary cystic fibrosis intestinal organoids. Nat Med 19:939–945

    CAS  PubMed  Google Scholar 

  • Delitto D et al (2015) Downstream mediators of the intratumoral interferon response suppress antitumor immunity, induce gemcitabine resistance and associate with poor survival in human pancreatic cancer. Cancer Immunol Immunother 64:1553–1563

    CAS  PubMed  PubMed Central  Google Scholar 

  • DeRose YS et al (2011) Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes. Nat Med 17:1514–1520

    CAS  PubMed  PubMed Central  Google Scholar 

  • dit Faute MA et al (2002) Distinctive alterations of invasiveness, drug resistance and cell-cell organization in 3D-cultures of MCF-7, a human breast cancer cell line, and its multidrug resistant variant. Clin Exp Metastasis 19:161–168

    PubMed  Google Scholar 

  • Drost J et al (2017) Use of CRISPR-modified human stem cell organoids to study the origin of mutational signatures in cancer. Science 358:234–238

    CAS  PubMed  PubMed Central  Google Scholar 

  • Ekert JE et al (2014) Three-dimensional lung tumor microenvironment modulates therapeutic compound responsiveness in vitro—implication for drug development. PLoS ONE 9(3):e92248. https://doi.org/10.1372/journal.pone.0092248

    Article  PubMed  PubMed Central  Google Scholar 

  • Faca VM et al (2008) A mouse to human search for plasma proteome changes associated with pancreatic tumor development. PLoS Med 5:e123

    PubMed  PubMed Central  Google Scholar 

  • Fournier MV et al (2006) Gene expression signature in organized and growth-arrested mammary acini predicts good outcome in breast cancer. Cancer Res 66:7095–7102

    CAS  PubMed  PubMed Central  Google Scholar 

  • Freidrich J, Seidel C, Ebner R, Kunz-Schughart LA (2009) Spheroid-based drug screen: considerations and practical approach. Nat Protoc 4:309–324

    Google Scholar 

  • Fujii M et al (2016) A colorectal tumor organoid library demonstrates progressive loss of niche factor requirements during tumorigenesis. Cell Stem Cell 18:827–838

    CAS  PubMed  Google Scholar 

  • Gao D et al (2014) Organoid cultures derived from patients with advanced prostate cancer. Cell 159:176–187

    CAS  PubMed  PubMed Central  Google Scholar 

  • Gao D, Chen Y (2015) Organoid development in cancer genome discovery. Curr Opin Gen Develop 30:42–48

    CAS  Google Scholar 

  • Gao H et al (2015) High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response. Nat Med 21:1318–1325

    CAS  PubMed  Google Scholar 

  • Gatenby RA et al (2007) Cellular adaptations to hypoxia and acidosis during somatic evolution of breast cancer. Br J Cancer 97:646–653

    CAS  PubMed  PubMed Central  Google Scholar 

  • Ghajar CM et al (2013) The perivascular niche regulates breast tumour dormancy. Nat Cell Biol 15:807–817

    CAS  PubMed  PubMed Central  Google Scholar 

  • Graves EE et al (2010) Hypoxia in models of lung cancer: implications for targeted therapeutics. Clin Cancer Res 16:4843–4852

    CAS  PubMed  PubMed Central  Google Scholar 

  • Gu L, Liao Z, McCue P, Trabulsi EJ, Nevalainen MT (2013a) Ex vivo prostate cancer explant organ culture model system for targeted drug development in prostate cancer. J Clin Oncol Abstract https://doi.org/10.1200/jco.2013.31.6-suppl.110.a

  • Gu L et al (2013b) Pharmacologic inhibition of Jak2-Stat5 signaling by Jak2 inhibitor AZD1480 potently suppresses growth of both primary and castrate-resistant prostate cancer. Clin Cancer Res 19:5658–5674

    CAS  PubMed  PubMed Central  Google Scholar 

  • Guillaumond F et al (2013) Strengthened glycolysis under hypoxia supports tumor symbiosis and hexosamine biosynthesis in pancreatic adenocarcinoma. PNAS USA 110:3919–3924

    CAS  PubMed  PubMed Central  Google Scholar 

  • Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144:646–674

    CAS  PubMed  Google Scholar 

  • Havas KM et al (2017) Metabolic shifts in residual breast cancer drive tumor recurrence. J Clin Invest 127:2091–2105

    PubMed  PubMed Central  Google Scholar 

  • Heneweer M et al (2005) Co-culture of primary human mammary fibroblasts and MCF-7 cells as an in vitro breast cancer model. Toxicol Sci 83:257–263

    CAS  PubMed  Google Scholar 

  • Hensley CT et al (2016) Metabolic heterogeneity in human lung tumors. Cell 164:681–694

    CAS  PubMed  PubMed Central  Google Scholar 

  • Herrmann D et al (2014) Three-dimensional cancer models mimic cell-matrix interactions in the tumour microenvironment. Carcinogenesis 35:1671–1679

    CAS  PubMed  Google Scholar 

  • Hesami P et al (2014) A humanized tissue-engineered in vivo model to dissect interactions between human prostate cancer cells and human bone. Clin Exp Metastasis 31:435–446

    CAS  PubMed  Google Scholar 

  • Hidalgo M et al (2011) A pilot clinical study of treatment guided by personalized tumorgrafts in patients with advanced cancer. Mol Cancer Therapeut 10:1311–1316

    CAS  Google Scholar 

  • Holzapfel BM et al (2014) Species-specific homing mechanisms of human prostate cancer metastasis in tissue engineered bone. Biomaterials 35:4108–4115

    CAS  PubMed  Google Scholar 

  • Horie M et al (2012) Characterization of human lung cancer-associated fibroblasts in three-dimensional in vitro co-culture model. Biochem Biophys Res Commun 423:158–163

    CAS  PubMed  Google Scholar 

  • Hsiao AY et al (2009) Microfluidic system for formation of PC-3 prostate cancer co-culture spheroids. Biomaterials 30:3020–3027

    CAS  PubMed  PubMed Central  Google Scholar 

  • Huang L et al (2015) Ductal pancreatic cancer modeling and drug screening using human pluripotent stem cell- and patient-derived tumor organoids. Nat Med 21:364–1371

    CAS  Google Scholar 

  • Huang M, Shen A, Ding J, Geng M (2014) Molecularly targeted cancer therapy: some lessons from the past decade. Trends Pharmacol Sci 35:41–50

    PubMed  Google Scholar 

  • Hubert CG et al (2016) A three-dimensional organoid culture system derived from human glioblastomas recapitulates the hypoxic gradients and cancer stem cell heterogeneity of tumors found in vivo. Cancer Res 76:2465–2477

    CAS  PubMed  PubMed Central  Google Scholar 

  • Infanger DW et al (2013) Glioblastoma stem cells are regulated by interleukin-8 signaling in a tumoral perivascular niche. Cancer Res 73:7079–7089

    CAS  PubMed  Google Scholar 

  • Ingram M et al (2010) Tissue engineered tumor models. Biotech Histochem 85:213–229

    CAS  PubMed  Google Scholar 

  • Ishiguro T (2017) Tumor-derived spheroids: relevance to cancer stem cells and clinical applications. Cancer Sci 108:283–289

    CAS  PubMed  PubMed Central  Google Scholar 

  • Jaganathan H et al (2014) Three-dimensional in vitro co-culture model of breast tumor using magnetic levitation. Sci Rep 4:6468. https://doi.org/10.1038/srep06468

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Julien S et al (2012) Characterization of a large panel of patient-derived tumor xenografts representing the clinical heterogeneity of human colorectal cancer. Clin Cancer Res 18:5314–5328

    CAS  PubMed  Google Scholar 

  • Kamb A (2005) What’s wrong with our cancer models? Nat Rev Drug Dis 4:161–165

    CAS  Google Scholar 

  • Karar J, Maity A (2009) Modulating the tumor microenvironment to increase radiation responsiveness. Cancer Biol Ther 8:1994–2001

    CAS  PubMed  Google Scholar 

  • Karekla E et al (2017) Ex vivo explant cultures of non-small cell lung carcinoma enable evaluation of primary tumor responses to anticancer therapy. Cancer Res 77:2029–2039

    CAS  PubMed  Google Scholar 

  • Katz E et al (2012) Targeting of Rac GTPases blocks the spread of intact human breast cancer. Oncotarget 3:608–613

    PubMed  PubMed Central  Google Scholar 

  • Kim S, Lee EK, Kuh H (2015) Co-culture of 3D tumor spheroids with fibroblasts as a model for epithelial-mesenchymal transition in vitro. Exper Cell Res 335:187–196

    CAS  Google Scholar 

  • Klco JM et al (2014) Functional heterogeneity of genetically defined subclones in acute myeloid leukemia. Cancer Cell 25:379–392

    CAS  PubMed  PubMed Central  Google Scholar 

  • Kopetz S, Lemos R, Powis G (2012) The promise of patient-derived xenografts: the best laid plans of mice and men. Clin Cancer Res 18:5160–5162

    PubMed  PubMed Central  Google Scholar 

  • Lancaster MA, Knoblich JA (2014) Organogenesis in a dish: Modeling development and disease using organoid technologies. Science 345. https://doi.org/10.1126/science.1247125

  • Lane AN, Higashi RM, Fan TW (2016) Preclincal models for interrogating drug action in human cancers using stable isotope resolved metabolomics (SIRM). Metabolomics 12:118. https://doi.org/10.1007/s11306-016-1065-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Langdon SP (2004) Isolation and culture of ovarian cancer cell lines. Method Mol Med 88:133–139

    Google Scholar 

  • Lawrence MG et al (2013) A preclinical xenograft model of prostate cancer using human tumors. Nat Protoc 8:836–848

    CAS  PubMed  Google Scholar 

  • Ledford H (2011) 4 ways to fix the clinical trial. Nature 477:526–528

    CAS  PubMed  Google Scholar 

  • Ledford H (2015) CRISPR, the disruptor. Nature 522:20–24

    CAS  PubMed  Google Scholar 

  • Ledford H (2016) US cancer institute to overhaul tumour cell lines. Nature 530:391

    PubMed  Google Scholar 

  • Leeper AD et al (2011) Long-term culture of human breast cancer specimens and their analysis using optical projection tomography. J Vis Exp pii3085

    Google Scholar 

  • Leeper AD et al (2012) Determining tamoxifen sensitivity using primary breast cancer tissue in collagen-based three-dimensional culture. Biomaterials 33:907–915

    CAS  PubMed  Google Scholar 

  • Li L, Lu Y (2011) Optimizing a 3D culture system to study the interaction between epithelial breast cancer and its surrounding fibroblasts. J Cancer 2:458–466

    PubMed  PubMed Central  Google Scholar 

  • Liao Z et al (2015) Structure-based screen identifies a potent small molecule inhibitor of Stat5a/b with therapeutic potential for prostate cancer and chronic myeloid leukaemia. Mol Cancer Ther 14:1777–1793

    CAS  PubMed  PubMed Central  Google Scholar 

  • Loessner D et al (2010) Bioengineered 3D platform to explore cell–ECM interactions and drug resistance of epithelial ovarian cancer cells. Biomaterials 31:8494–8506

    CAS  PubMed  Google Scholar 

  • Longati P et al (2013) 3D pancreatic carcinoma spheroids induce a matrix-rich, chemoresistant phenotype offering a better model for drug testing. BMC Cancer 13:95

    CAS  PubMed  PubMed Central  Google Scholar 

  • Mariette C et al (2008) Activation of MUC1 mucin expression by bile acids in human esophaeal adenocarcinomatous cells and tissues in mediated by the phosphatidylinositol 3-kinase. Surgery 143:58–71

    PubMed  Google Scholar 

  • Martin JK, Patrick DR, Bissell MJ, Fournier MV (2008) Prognostic breast cancer signature identified from 3D culture model accurately predictes clinical outcome across independent datasets. PLoS ONE 3:e2994. https://doi.org/10.1371/journal.pone.0002994

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Martinez-Garcia R et al (2014) Transcriptional dissection of pancreatic tumors engrafted in mice. Genome Medicine 6:27

    PubMed  PubMed Central  Google Scholar 

  • Matano M et al (2015) Modeling colorectal cancer using CRISPR-Cas9-mediated engineering of human intestinal organoids. Nat Med 21:256–262

    CAS  PubMed  Google Scholar 

  • McAllister SS, Weinberg RA (2010) Tumor-host interactions: a far-reaching relationship. J Clin Oncol 28:4022–4028

    PubMed  Google Scholar 

  • McCracken KW et al (2014) Modelling human development and disease in pluripotent stem-cell-derived gastric organoids. Nature 516:400–404

    CAS  PubMed  PubMed Central  Google Scholar 

  • Minchinton AI, Tannock IF (2006) Drug penetration in solid tumours. Nat Rev Cancer 6:583–592

    CAS  PubMed  Google Scholar 

  • Mitra A, Mishra L, Li S (2015) EMT, CTCs and CSCs in tumor relapse and drug-resistance. Oncotarget 6:10697–10711

    PubMed  PubMed Central  Google Scholar 

  • Moore CB, Guthrie EH, Huang MTH, Taxman DJ (2010) Short hairpin RNA (shRNA): design, delivery, and assessment of gene knockdown. Methods Mol Biol 629:141–158

    PubMed  PubMed Central  Google Scholar 

  • Morton JJ, Bird G, Refaeli Y, Jimeno A (2016) Humanized mouse xenograft models: narrowing the tumor-microenvironment gap. Cancer Res 76:6153–6158

    CAS  PubMed  PubMed Central  Google Scholar 

  • Muller CR et al (2007) Potential for treatment of liposarcomas with the MDM2 antagonist Nutlin-3A. Int J Cancer 121:199–205

    CAS  PubMed  Google Scholar 

  • Muthuswamy R, Corman JM, Dahl K, Chatta GS, Kalinski P (2016) Functional reprogramming of human prostate cancer to promote local attraction of effector CD8(+) T cells. Prostate 76:1095–1105

    CAS  PubMed  Google Scholar 

  • Nadauld LD et al (2014) Metastatic tumor evolution and organoid modeling implicate TGFBR2 as a cancer driver in diffuse gastric cancer. Genome Biol 428 http://genomebiology.com/2014/15/8/428

  • Nardella C, Lunardi A, Patnaik A, Cantley LC, Pandolfi PP (2011) The APL paradigm and the “co-clinical trial” project. Cancer Dis 1:108–116

    Google Scholar 

  • Nozaki K et al (2016) Co-culture with intestinal epithelial organoids allows efficient expansion and motility analysis of intraepithelial lymphocytes. J Gastroenterol 51:206–213

    CAS  PubMed  PubMed Central  Google Scholar 

  • Ocana A, Pandiella A, Siu LL, Tannock IF (2011) Preclinical development of molecular-targeted agents for cancer. Nat Rev Clin Oncol 8:200–209

    CAS  Google Scholar 

  • Olive KP et al (2009) Inhibition of Hedgehog signalling enhances delivery of chemotherapy in a mouse model of pancreatic cancer. Science 324:1457–1461

    CAS  PubMed  PubMed Central  Google Scholar 

  • Pajic A et al (2000) Cell cycle activation by c-myc in a burkitt lymphoma model cell line. Int J Cancer 87:787–793

    CAS  PubMed  Google Scholar 

  • Pauli C et al (2017) Personalized in vitro and in vivo cancer models to guide precision medicine. Cancer Discov 7:462–477

    PubMed  PubMed Central  Google Scholar 

  • Petsko GA (2010) When failure should be the option. BMC Biol 8:61

    PubMed  PubMed Central  Google Scholar 

  • Pettersen EO et al (2015) Targeting tumour hypoxia to prevent cancer metastasis. From biology, biosensing and technology to drug development: the METOXIA consortium. J Enzyme Inhib Med Chem 30(5):689–721

    CAS  PubMed  Google Scholar 

  • Phelan JJ et al (2016) Examining the connectivity between different cellular processes in the Barrett tissue microenvironment. Cancer Lett 371:334–346

    CAS  PubMed  Google Scholar 

  • Pickl M, Ries CH (2009) Comparison of 3D and 2D tumor models reveals enhanced HER2 activation in 3D associated with an increased response to trastuzumab. Oncogene 28:461–468

    CAS  PubMed  Google Scholar 

  • Pietras K, Hanahan D (2005) A multitargeted, metronomic, and maximum-tolerated dose “chemoswitch” regimen is antiangeogenic, producing objective responses and survival benefit in a mouse model of cancer. J Clin Oncol 23:939–952

    CAS  PubMed  Google Scholar 

  • Pishas KI et al (2014) Nutlin-3a efficacy in sarcoma predicted by transcriptomic and epigenetic profiling. Cancer Res 74:921–931

    CAS  PubMed  Google Scholar 

  • Pitteri SJ et al (2009) Integrated proteomic analysis of human cancer cells and plasma from tumor bearing mice for ovarian cancer biomarker discovery. PLoS ONE 4:e7916

    PubMed  PubMed Central  Google Scholar 

  • Politi K, Fan PD, Shen R, Zakowski M, Varmus H et al (2010) Erlotinib resistance in mouse models of epidermal growth factor receptor-induced lung adenocarcinoma. Dis Model Mech 3:111–119

    CAS  PubMed  Google Scholar 

  • Politi K, Pao W (2011) How genetically engineered mouse tumour models provide insights into human cancers. J Clin Oncol 29:2273–2281

    CAS  PubMed  PubMed Central  Google Scholar 

  • Pouyssegur J, Dayan F, Mazure NM (2006) Hypoxia signalling in cancer and approaches to enforce tumour regression. Nature 441:437–443

    CAS  PubMed  Google Scholar 

  • Proia DA, Kuperwasser C (2006) Reconstruction of human mammary tissues in a mouse model. Nat Protoc 1:206–214

    CAS  PubMed  Google Scholar 

  • Ravi M, Paramesh V, Kaviya SR, Anuradha E, Paul Solomon FDP (2014) 3D cell culture systems: advantages and applications. J Cell Physiol 230:16–26

    Google Scholar 

  • Rayal F et al (2012) Molecular profiling of patient-derived breast cancer xenografts. Breast Cancer Res 14:R11

    Google Scholar 

  • Ray-Coquard I et al (2012) Effect of the MDM2 antagonist R7112 on the P53 pathway in patients with MDM2-amplified, well-differentiated or dedifferentiated liposarcoma; an exploratory proof-of-mechanism study. Lancet Oncology 13:1133–1140

    CAS  PubMed  Google Scholar 

  • Riemer P et al (2017) Oncogenic β-catenin and PIK3CA instruct network states and cancer phenotypes in intestinal organoids. J Cell Biol 216:1567–1577

    CAS  PubMed  PubMed Central  Google Scholar 

  • Riffle S, Naresh P, Albert M, Hegde RS (2017) Linking hypoxia, DNA damage and proliferation in multicellular tumor spheroids. BMC Cancer 17:338. https://doi.org/10.1186/s12885-017-3319-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Roper J et al (2017) In vivo genome editing and organoid transplantation models of colorectal cancer and metastasis. Nature Biotechnol 35:569–576

    CAS  Google Scholar 

  • Ruben JM et al (2014) In situ loading of skin dendritic cells with apoptotic bleb-derived antigen for the induction of tumor-directed immunity. Oncoimmunology 3:7e946360,https://doi.org/10.4161/21624011.2014.946360

  • Sachs N, Clevers H (2014) Organoid cultures for the analysis of cancer phenotypes. Curr Opin Gen Develop 24:68–73

    CAS  Google Scholar 

  • Sachs N et al (2018) A living biobank of breast cancer organoids captures disease heterogeneity. Cell 172:1–14

    Google Scholar 

  • Sander JD, Joung JK (2014) CRISPR-Cas systems for editing, regulating and targeting genomes. Nature Biotechnol 32:347–355

    CAS  Google Scholar 

  • Sato T et al (2011) Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma and Barrett’s epithelium. Gastroent 141:1762–1772

    CAS  Google Scholar 

  • Saunders T (2011) Inducible transgenic mouse models. Methods Mol Biol 693:103–115

    CAS  PubMed  Google Scholar 

  • Sausville EA, Burger AM (2006) Contribution of human tumor xenografts to anticancer drug development. Cancer Res 66:3351–3354

    CAS  PubMed  Google Scholar 

  • Schmeichel KL, Bissell MJ (2003) Modeling tissue-specific signalling and organ function in three dimensions. J Cell Sci 116:2377–2388

    CAS  PubMed  Google Scholar 

  • Schutte M et al (2017) Molecular dissection of colorectal cancer in pre-clinical models identifies biomarkers predicting sensitivity to EGFR inhibitors. Nat Commun 8:14262

    PubMed  PubMed Central  Google Scholar 

  • Schwank G et al (2013) Functional repair of CFTR by CRISPR/Cas9 in intestinal stem cell organoids of cystic fibrosis patients. Cell Stem Cell 13:653–658

    CAS  PubMed  Google Scholar 

  • Sethi T et al (1999) Extracellular matrix proteins protect small cell lung cancer cells against apoptosis: a mechanism for small cell lung cancer growth and drug resistance in vivo. Nat Med 5:662–668

    CAS  PubMed  Google Scholar 

  • Sharpless NE, Depinho RA (2006) The mighty mouse: genetically engineered mouse models in cancer drug development. Nature Rev Drug Discov 5:741–754

    CAS  Google Scholar 

  • Simian M, Bissell MJ (2017) Organoids: a historical perspective of thinking in three dimensions. J Cell Biol 216:31–40

    CAS  PubMed  PubMed Central  Google Scholar 

  • Singh M et al (2010) Assessing therapeutic responses in Kras mutant cancers using genetically engineered mouse models. Nat Biotechnol 28:585–593

    CAS  PubMed  Google Scholar 

  • Singh M, Ferrara N (2012) Modeling and predicting clinical efficacy for drugs targeting the tumor milieu. Nat Biotechnol 30:648–657

    CAS  PubMed  Google Scholar 

  • Singh M, Close DA, Mukundan S, Johnston PA, Sant S (2015) Production of uniform 3D microtumors in hydrogel microwell arrays for measurement of viability, morphology and signalling pathway activation. Assay Drug Dev Techol 13:570–583

    CAS  Google Scholar 

  • Singh M, Mukundan S, Jaramillo M, Oesterreich S, Sant S (2016) Three-dimensional breast cancer models mimic hallmarks of size-induced tumor progression. Cancer Res 76:3732–3743

    CAS  PubMed  PubMed Central  Google Scholar 

  • Siolas D, Hannon GJ (2013) Patient derived tumor xenografts: transforming clinical samples into mouse models. Cancer Res 73:5315–5319

    CAS  PubMed  PubMed Central  Google Scholar 

  • Stewart E et al (2017) Orthotopic patient-derived xenografts of paediatric solid tumours. Nature 549:96–100

    CAS  PubMed  PubMed Central  Google Scholar 

  • Straussman R et al (2012) Tumour micro-environment elicits innate resistance to RAF inhibitors through HGF secretion. Nature 487:500–504

    CAS  PubMed  PubMed Central  Google Scholar 

  • Tentler JJ et al (2012) Patient-derived tumour xenografts as models for oncology drug development. Nat Rev Clin Oncol 9:338–350

    CAS  PubMed  PubMed Central  Google Scholar 

  • Thibaudeau L et al (2014) A tissue-engineered humanized xenograft model of human breast cancer metastasis to bone. Dis Model Mech 7:299–309

    CAS  PubMed  PubMed Central  Google Scholar 

  • Timpson P et al (2011) Spatial regulation of RhoA activity during pancreatic cancer cell invasion driven by mutant p53. Cancer Res 71:747–757

    CAS  PubMed  PubMed Central  Google Scholar 

  • Toledo F, Wahl GM (2006) Regulating the p53 pathway: in vitro hypotheses, in vivo veritas. Nat Rev Cancer 6:909–923

    CAS  PubMed  Google Scholar 

  • Townsend EC et al (2016) The public repository of xenografts enables discovery and randomized phase II-like trials in mice. Cancer Cell 29:574–586

    CAS  PubMed  PubMed Central  Google Scholar 

  • van der Kuip H et al (2006) Short term culture of breast cancer tissues to study the activity of the anticancer drug taxol in an intact tumor enviroment. BMC Cancer 6:86. https://doi.org/10.1186/1471-2407-6-86

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • van de Wetering M et al (2015) Prospective derivation of a ‘Living Organoid Biobank’ of colorectal cancer patients. Cell 161:933–945

    PubMed  PubMed Central  Google Scholar 

  • Verissimo CS et al (2015) Targeting mutant RAS in patient-derived colorectal cancer organoids by combinatorial drug screening eLife, 5. https://doi.org/10.7554/elife.18489

  • Verjans E, Doijen J, Luyten W, Landuyt B, Schoofs L (2017) Three-dimensional cell culture models for anticancer drug screening: worth the effort? J Cell Physiol 1–11 doi.org/https://doi.org/10.1002/jcp26052

  • Vudattu NK et al (2014) Humanized mice as a model for aberrant responses in human T cell immunotherapy. J Immunol 193:587–596

    CAS  PubMed  Google Scholar 

  • Wang J et al (2010) A novel orthotopic and metastatic mouse model of breast cancer in human mammary microenvironment. Breast Cancer Res Treat 120:337–344

    PubMed  Google Scholar 

  • Wang X et al (2018) Enrichment of glioma stem cell-like cells on 3D porous scaffolds composed of different extracellular matrix. Biochem Biophys Res Comm 498:1052–1057

    CAS  PubMed  Google Scholar 

  • Ward C et al (2013) New strategies for targeting the hypoxic tumour microenvironment in breast cancer. Cancer Treat Rev 39:171–179

    CAS  PubMed  Google Scholar 

  • Ward C et al (2015) Evaluation of carbonic anhydrase IX as a therapeutic target for inhibition of breast cancer invasion and metastasis using a series of in vitro breast cancer models. Oncotarget 6:24856–2485670

    PubMed  PubMed Central  Google Scholar 

  • Ware MJ et al (2016) Generation of an in vitro 3D PDAC stromal rich spheroid model. Biomaterials 108:129–142

    CAS  PubMed  PubMed Central  Google Scholar 

  • Weeber F et al (2015) Preserved genomic diversity in organoids cultured from biopsies of colorectal cancer metastases PNAS USA 112:13308–13311

    Google Scholar 

  • Werner-Klein M et al (2014) Immune humanization of immunodeficient mice using diagnostic bone marrow aspirates from carcinoma patients. PLoS ONE 9(e97860):6158

    Google Scholar 

  • Witkiewicz AK et al (2015) Selective impact of CDK4/6 suppression of patient-derived models of pancreatic cancer. Oncotarget 6:15788–15801

    PubMed  PubMed Central  Google Scholar 

  • Xie H et al (2014) Targeting lactate dehydrogenase—a inhibits tumorigenesis and tumor progression in mouse models of lung cancer and impacts tumor initiating cells. Cell Metabolism 19:795–780

    Google Scholar 

  • Yamada KM, Cukierman E (2007) Modeling tissue morphogenesis and cancer in 3D. Cell 130:601–610

    CAS  PubMed  Google Scholar 

  • Yu M (2014) Ex vivo culture of circulating breast tumor cells for individualized testing of drug susceptibility. Science 345:216–220

    CAS  PubMed  PubMed Central  Google Scholar 

  • Zamboni WC et al (2012) Best practices in cancer nanotechnology: perspective from NCI nanotechnology alliance. Clin Cancer Res 18:3229–3241

    CAS  PubMed  PubMed Central  Google Scholar 

  • Zhang X et al (2013) A renewable tissue resource of phenotypically stable, biologically and ethnically diverse, patient-derived human breast cancer xenograft models. Cancer Res 73:4885–4897

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors MG, JM, CW, IK, AM, and DA are supported by funding from the UK Engineering and Physical Sciences Research Council, through the Implantable Microsystems for Personalised Anti-Cancer Therapy (IMPACT) program grant (EP/K-34510/1).

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Authors and Affiliations

  1. The Royal (Dick) School of Veterinary Studies and Roslin Institute, University of Edinburgh, Easter Bush, Roslin, Midlothian, EH25 9RG, Edinburgh, UK

    Carol Ward, Mark Gray & David Argyle

  2. Cancer Research UK Edinburgh Centre and Division of Pathology Laboratories, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road South, EH4 2XU, Edinburgh, UK

    Carol Ward, James Meehan, Mark Gray, Ian H. Kunkler & Simon P. Langdon

  3. School of Engineering and Physical Sciences, Institute of Sensors, Signals and Systems, Heriot-Watt University, EH14 4AS, Edinburgh, UK

    James Meehan

  4. School of Engineering, Faraday Building, The King’s Buildings, Mayfield Road, EH9 3JL, Edinburgh, UK

    Alan Murray

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  1. Carol Ward
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Correspondence to Carol Ward .

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  1. GSK Vaccines Research, Siena, Italy

    Fabio Bagnoli

  2. GSK Vaccines Research, Siena, Italy

    Rino Rappuoli

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Ward, C. et al. (2019). Preclinical Organotypic Models for the Assessment of Novel Cancer Therapeutics and Treatment. In: Bagnoli, F., Rappuoli, R. (eds) Three Dimensional Human Organotypic Models for Biomedical Research. Current Topics in Microbiology and Immunology, vol 430. Springer, Cham. https://doi.org/10.1007/82_2019_159

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