Drug screening in 3D in vitro tumor models: overcoming current pitfalls of efficacy read-outs

Biotechnology Journal

Volumn 12, Issue 1, 2017, Pages

  Santo, Vítor E ^a,b   Rebelo, Sofia P ^a,b   Estrada, Marta F ^a,b   Alves, Paula M ^a,b   Boghaert, Erwin ^c   Brito, Catarina ^a,b  

^a INSTITUTO DE BIOLOGIA EXPERIMENTAL E TECNOLÓGICA   (Portugal)

^b INSTITUTO DE TECNOLOGIA QUÍMICA E BIOLÓGICA   (Portugal)

^c ABBVIE INC   (United States)

Author keywords

3D cell models; Cancer; Drug discovery; Pre clinical research; Tumor microenvironment

Indexed keywords

AUTOMATION; CELLS; CLINICAL RESEARCH; CYTOLOGY; DIAGNOSIS; DISEASES; ONCOLOGY; TUMORS;

AUTOMATED SYSTEMS; CANCER; CELL MODEL; DRUG DISCOVERY; HIGH THROUGHPUT; INTERPRETATION OF DATA; PREDICTIVE VALUES; TUMOR MICROENVIRONMENT;

PHYSIOLOGICAL MODELS;

ARTICLE; CANCER RESEARCH; CELL CULTURE; CELL LINE; CELL SELECTION; COCULTURE; CONCENTRATION RESPONSE; DRUG EFFECT; DRUG EFFICACY; DRUG SCREENING; EXTRACELLULAR MATRIX; HUMAN; IN VITRO STUDY; MOLECULAR PATHOLOGY; NONHUMAN; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; STROMA CELL; THREE DIMENSIONAL IN VITRO TUMOR MODEL; TUMOR CELL; TUMOR MICROENVIRONMENT; TUMOR MODEL; ANIMAL; CELL CULTURE TECHNIQUE; CYTOLOGY; DEVICES; DRUG DEVELOPMENT; PATHOLOGY; PROCEDURES; TUMOR CELL LINE;

ANTINEOPLASTIC AGENT;

ANIMALS; ANTINEOPLASTIC AGENTS; CELL CULTURE TECHNIQUES; CELL LINE, TUMOR; COCULTURE TECHNIQUES; DRUG DISCOVERY; DRUG SCREENING ASSAYS, ANTITUMOR; HUMANS; STROMAL CELLS; TUMOR MICROENVIRONMENT;

EID: 85006855449     PISSN: 18606768     EISSN: 18607314     Source Type: Journal    
DOI: 10.1002/biot.201600505     Document Type: Article

References (143)

1. Knowlton, S., Onal, S., Yu, C. H., Zhao, J. J., Tasoglu, S., Bioprinting for cancer research. Trends Biotechnol. 2015, 33, 504–513.
2. McKim, J. M., Jr., Building a tiered approach to in vitro predictive toxicity screening: A focus on assays with in vivo relevance. Comb. Chem. High Throughput Screening 2010, 13, 188–206.
3. Unger, C., Kramer, N., Walzl, A., Scherzer, M. et al., Modeling human carcinomas: Physiologically relevant 3D models to improve anti-cancer drug development. Advanced Drug Delivery Rev. 2014, 79, 50–67.
4. Caie, P. D., Walls, R. E., Ingleston-Orme, A., Daya, S. et al., High-content phenotypic profiling of drug response signatures across distinct cancer cells. Mol. Cancer Ther. 2010, 9, 1913–1926.
5. Zanoni, M., Piccinini, F., Arienti, C., Zamagni, A., et al., 3D tumor spheroid models for in vitro therapeutic screening: A systematic approach to enhance the biological relevance of data obtained. Sci. Rep. 2016, 6, 19103.
6. Hoelder, S., Clarke, P. A., Workman, P., Discovery of small molecule cancer drugs: Successes, challenges and opportunities. Mol. Oncol. 2012, 6, 155–176.
7. Day, C. P., Merlino, G., Van Dyke, T., Preclinical mouse cancer models: A maze of opportunities and challenges. Cell 2015, 163, 39–53.
8. Celli, J. P., Rizvi, I., Blanden, A. R., Massodi, I. et al., An imaging-based platform for high-content, quantitative evaluation of therapeutic response in 3D tumour models. Sci. Rep. 2014, 4, 3751.
9. Tanner, K., Gottesman, M. M., Beyond 3D culture models of cancer. Sci. Transl. Med. 2015, 7, 283ps289.
10. Ivanov, D. P., Parker, T. L., Walker, D. A., Alexander, C. et al., Multiplexing spheroid volume, resazurin and acid phosphatase viability assays for high-throughput screening of tumour spheroids and stem cell neurospheres. PLoS One 2014, 9, e103817.
11. Haycock, J. W., 3D Cell culture: A review of current approaches and techniques, in: Haycock, W. J. (Ed.), 3D Cell Culture: Methods and Protocols, Humana Press, Totowa, NJ 2011, pp. 1–15.
12. Lee, G. Y., Kenny, P. A., Lee, E. H., Bissell, M. J., Three-dimensional culture models of normal and malignant breast epithelial cells. Nat. Methods 2007, 4, 359–365.
13. Lovitt, C. J., Shelper, T. B., Avery, V. M., Miniaturized three-dimensional cancer model for drug evaluation. Assay Drug Dev. Technol. 2013, 11, 435–448.
14. Timaner, M., Beyar-Katz, O., Shaked, Y., Analysis of the stromal cellular components of the solid tumor microenvironment using flow cytometry. Curr. Protoc. Cell Biol. 2016, 70, 19.18.11–19.18.2.
15. Pattabiraman, D. R., Weinberg, R. A., Tackling the cancer stem cells – what challenges do they pose. Nat. Rev. Drug Discovery 2014, 13, 497–512.
16. Nath, S., Devi, G. R., Three-dimensional culture systems in cancer research: Focus on tumor spheroid model. Pharmacol. Thera. 2016, 163, 94–108.
17. Thoma, C. R., Zimmermann, M., Agarkova, I., Kelm, J. M., Krek, W., 3D cell culture systems modeling tumor growth determinants in cancer target discovery. Adv. Drug Delivery Rev. 2014, 69, 29–41.
18. Tsai, M. J., Chang, W. A., Huang, M. S., Kuo, P. L., Tumor microenvironment: A new treatment target for cancer. ISRN Biochem. 2014, 2014, 351959.
19. Hay, M. P., Hicks, K. O., Wang, J., Hypoxia-directed drug strategies to target the tumor microenvironment. Adv. Exp. Med. Biol. 2014, 772, 111–145.
20. Hui, L., Chen, Y., Tumor microenvironment: Sanctuary of the devil. Cancer Lett. 2015, 368, 7–13.
21. Razzak, M., Immunotherapy: Engineering a sTrategy for multiple myeloma. Nat. Rev. Cancer 2015, 15, 514.
22. Leavy, O., Immunotherapy: A triple blow for cancer. Nat. Rev. Cancer 2015, 15, 258–259.
23. de Kruijf, E. M., van Nes, J. G., van de Velde, C. J., Putter, H. et al., Tumor-stroma ratio in the primary tumor is a prognostic factor in early breast cancer patients, especially in triple-negative carcinoma patients. Breast Cancer Res. Treat. 2011, 125, 687–696.
24. Jaganathan, H., Gage, J., Leonard, F., Srinivasan, S. et al., Three-dimensional in vitro co-culture model of breast tumor using magnetic levitation. Sci. Rep. 2014, 4, 6468.
25. Estrada, M. F., Rebelo, S. P., Davies, E. J., Pinto, M. T. et al., Modelling the tumour microenvironment in long-term microencapsulated 3D co-cultures recapitulates phenotypic features of disease progression. Biomaterials 2016, 78, 50–61.
26. Kenny, H. A., Lal-Nag, M., White, E. A., Shen, M. et al., Quantitative high throughput screening using a primary human three-dimensional organotypic culture predicts in vivo efficacy. Nat. Commun. 2015, 6, 6220.
27. Miki, Y., Ono, K., Hata, S., Suzuki, T. et al., The advantages of co-culture over mono cell culture in simulating in vivo environment. J. Steroid Biochem. Mol. Biol. 2012, 131, 68–75.
28. Stock, K., Estrada, M. F., Vidic, S., Gjerde, K. et al., Capturing tumor complexity in vitro: Comparative analysis of 2D and 3D tumor models for drug discovery. Sci. Rep. 2016, 6, 28951.
29. Kenny, H. A., Krausz, T., Yamada, S. D., Lengyel, E., Use of a novel 3D culture model to elucidate the role of mesothelial cells, fibroblasts and extra-cellular matrices on adhesion and invasion of ovarian cancer cells to the omentum. Int. J. Cancer 2007, 121, 1463–1472.
30. Akerfelt, M., Bayramoglu, N., Robinson, S., Toriseva, M. et al., Automated tracking of tumor-stroma morphology in microtissues identifies functional targets within the tumor microenvironment for therapeutic intervention. Oncotarget 2015, 6, 30035–30056.
31. Horman, S. R., Hogan, C., Delos Reyes, K., Lo, F., Antczak, C., Challenges and opportunities toward enabling phenotypic screening of complex and 3D cell models. Future Med. Chem. 2015, 7, 513–525.
32. Kenny, P. A., Lee, G. Y., Myers, C. A., Neve, R. M. et al., The morphologies of breast cancer cell lines in three-dimensional assays correlate with their profiles of gene expression. Mol. Oncol. 2007, 1, 84–96.
33. Weaver, V. M., Fischer, A. H., Peterson, O. W., Bissell, M. J., The importance of the microenvironment in breast cancer progression: Recapitulation of mammary tumorigenesis using a unique human mammary epithelial cell model and a three-dimensional culture assay. Biochem. Cell Biol. 1996, 74, 833–851.
34. Debnath, J., Brugge, J. S., Modelling glandular epithelial cancers in three-dimensional cultures. Nat. Rev. Cancer 2005, 5, 675–688.
35. Debnath, J., Muthuswamy, S. K., Brugge, J. S., Morphogenesis and oncogenesis of MCF-10A mammary epithelial acini grown in three-dimensional basement membrane cultures. Methods 2003, 30, 256–268.
36. Shaw, K. R., Wrobel, C. N., Brugge, J. S., Use of three-dimensional basement membrane cultures to model oncogene-induced changes in mammary epithelial morphogenesis. J. Mammary Gland Biol. Neoplasia 2004, 9, 297–310.
37. Schwartz, M. A., Chen, C. S., Cell biology. Deconstructing dimensionality. Science 2013, 339, 402–404.
38. Levental, K. R., Yu, H., Kass, L., Lakins, J. N. et al., Matrix crosslinking forces tumor progression by enhancing integrin signaling. Cell 2009, 139, 891–906.
39. Herrmann, D., Conway, J. R., Vennin, C., Magenau, A. et al., Three-dimensional cancer models mimic cell-matrix interactions in the tumour microenvironment. Carcinogenesis 2014, 35, 1671–1679.
40. Costa, E. C., Gaspar, V. M., Coutinho, P., Correia, I. J., Optimization of liquid overlay technique to formulate heterogenic 3D co-cultures models. Biotechnol. Bioeng. 2014, 111, 1672–1685.
41. Ware, M. J., Colbert, K., Keshishian, V., Ho, J. et al., Generation of homogenous three-dimensional pancreatic cancer cell spheroids using an improved hanging drop technique. Tissue Eng. Part C 2016, 22, 312–321.
42. Gong, X., Lin, C., Cheng, J., Su, J. et al., Generation of multicellular tumor spheroids with microwell-based agarose scaffolds for drug testing. PLoS One 2015, 10, e0130348.
43. Haisler, W. L., Timm, D. M., Gage, J. A., Tseng, H. et al., Three-dimensional cell culturing by magnetic levitation. Nat. Protoc. 2013, 8, 1940–1949.
44. Liang, Y., Jeong, J., DeVolder, R. J., Cha, C. et al., A cell-instructive hydrogel to regulate malignancy of 3D tumor spheroids with matrix rigidity. Biomaterials 2011, 32, 9308–9315.
45. Liu, Z., Vunjak-Novakovic, G., Modeling tumor microenvironments using custom-designed biomaterial scaffolds. Curr. Opin. Chem. Eng. 2016, 11, 94–105.
46. Patra, B., Peng, C.-C., Liao, W.-H., Lee, C.-H., Tung, Y.-C., Drug testing and flow cytometry analysis on a large number of uniform sized tumor spheroids using a microfluidic device. Sci. Rep. 2016, 6, 21061.
47. Santo, V. E., Estrada, M. F., Rebelo, S. P., Abreu, S. et al., Adaptable stirred-tank culture strategies for large scale production of multicellular spheroid-based tumor cell models. J. Biotechnol. 2016, 221, 118–129.
48. Singh, P., Bast, F., Screening and biological evaluation of myricetin as a multiple target inhibitor insulin, epidermal growth factor, and androgen receptor; in silico and in vitro. Invest. New Drugs 2015, 33, 575–593.
49. Eglen, R. M., Randle, D. H., Drug Discovery Goes Three-Dimensional: Goodbye to Flat High-Throughput Screening. Assay Drug Dev. Technol. 2015, 13, 262–265.
50. Xu, X., Farach-Carson, M. C., Jia, X., Three-dimensional in vitro tumor models for cancer research and drug evaluation. Biotechnol. Adv. 2014, 32, 1256–1268.
51. Costachel, O., Fadei, L., Badea, E., Tumor cell suspension culture on non adhesive substratum. Z. Krebsforsch. 1969, 72, 24–31.
52. Sutherland, R. M., Durand, R. E., Radiation response of multicell spheroids--an in vitro tumour model. Curr. Top. Radiat. Res. Quart. 1976, 11, 87–139.
53. Mehta, G., Hsiao, A. Y., Ingram, M., Luker, G. D., Takayama, S., Opportunities and challenges for use of tumor spheroids as models to test drug delivery and efficacy. J. Controlled Release 2012, 164, 192–204.
54. Edmondson, R., Broglie, J. J., Adcock, A. F., Yang, L., Three-dimensional cell culture systems and their applications in drug discovery and cell-based biosensors. Assay Drug Dev. Technol. 2014, 12, 207–218.
55. Hickman, J. A., Graeser, R., de Hoogt, R., Vidic, S. et al., Three-dimensional models of cancer for pharmacology and cancer cell biology: Capturing tumor complexity in vitro/ex vivo. Biotechnol. J. 2014, 9, 1115–1128.
56. Das, V., Bruzzese, F., Konecny, P., Iannelli, F. et al., Pathophysiologically relevant in vitro tumor models for drug screening. Drug Discovery Today 2015, 20, 848–855.
57. Pickl, M., Ries, C. H., Comparison of 3D and 2D tumor models reveals enhanced HER2 activation in 3D associated with an increased response to trastuzumab. Oncogene 2009, 28, 461–468.
58. Xing, H., Wang, S., Hu, K., Tao, W. et al., Effect of the cyclin-dependent kinases inhibitor p27 on resistance of ovarian cancer multicellular spheroids to anticancer chemotherapy. J. Cancer Res. Clin. Oncol. 2005, 131, 511–519.
59. Huanwen, W., Zhiyong, L., Xiaohua, S., Xinyu, R. et al., Intrinsic chemoresistance to gemcitabine is associated with constitutive and laminin-induced phosphorylation of FAK in pancreatic cancer cell lines. Mol. Cancer 2009, 8, 125.
60. Gang, E., Hsieh, Y.-T., Kim, H. N., Duchartre, Y. et al., Overcoming drug resistance of Pre-B ALL cells by targeting integrin alpha6 associated cell-adhesion mediated drug resistance using a novel antibody, P5G10. Blood 2015, 126, 2525–2525.
61. Tan, P. H., Chia, S. S., Toh, S. L., Goh, J. C., Nathan, S. S., Three-dimensional spatial configuration of tumour cells confers resistance to chemotherapy independent of drug delivery. J. Tissue Eng. Regener. Med. 2013.
62. Han, B., Qu, C., Park, K., Konieczny, S. F., Korc, M., Recapitulation of complex transport and action of drugs at the tumor microenvironment using tumor-microenvironment-on-chip. Cancer Lett. 2015.
63. Sirenko, O., Mitlo, T., Hesley, J., Luke, S. et al., High-content assays for characterizing the viability and morphology of 3D cancer spheroid cultures. Assay And Drug Development Technologies 2015, 13, 402–414.
64. Haverty, P. M., Lin, E., Tan, J., Yu, Y. et al., Reproducible pharmacogenomic profiling of cancer cell line panels. Nature 2016, 533, 333–337.
65. Greshock, J., Bachman, K. E., Degenhardt, Y. Y., Jing, J. et al., Molecular target class is predictive of in vitro response profile. Cancer Res. 2010, 70, 3677–3686.
66. Sos, M. L., Michel, K., Zander, T., Weiss, J. et al., Predicting drug susceptibility of non-small cell lung cancers based on genetic lesions. J. Clin. Invest. 2009, 119, 1727–1740.
67. Sachs, N., Clevers, H., Organoid cultures for the analysis of cancer phenotypes. Curr. Opin. Genet. Dev. 2014, 24, 68–73.
68. Lacroix, M., Leclercq, G., Relevance of breast cancer cell lines as models for breast tumours: An update. Breast Cancer Res. Treat. 2004, 83, 249–289.
69. Pereira, J. F., Awatade, N. T., Loureiro, C. A., Matos, P. et al., The third dimension: New developments in cell culture models for colorectal research. Cell. Mol. Life Sci. 2016, 73, 3971–3989.
70. Birgersdotter, A., Sandberg, R., Ernberg, I., Gene expression perturbation in vitro--a growing case for three-dimensional (3D) culture systems. Semin. Cancer Biol. 2005, 15, 405–412.
71. Jaeger, S., Duran-Frigola, M., Aloy, P., Drug sensitivity in cancer cell lines is not tissue-specific. Mol. Cancer 2015, 14, 40.
72. Garnett, M. J., Edelman, E. J., Heidorn, S. J., Greenman, C. D. et al., Systematic identification of genomic markers of drug sensitivity in cancer cells. Nature 2012, 483, 570–575.
73. Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K. et al., The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 2012, 483, 603–607.
74. Fang, C., Man, Y. G., Cuttitta, F., Stetler-Stevenson, W. et al., Novel Phenotypic Fluorescent Three-Dimensional Co-Culture Platforms for Recapitulating Tumor in vivo Progression and for Personalized Therapy. J. Cancer 2013, 4, 755–763.
75. Ruppen, J., Wildhaber, F. D., Strub, C., Hall, S. R. et al., Towards personalized medicine: Chemosensitivity assays of patient lung cancer cell spheroids in a perfused microfluidic platform. Lab Chip 2015, 15, 3076–3085.
76. Davies, E. J., Dong, M., Gutekunst, M., Narhi, K. et al., Capturing complex tumour biology in vitro: Histological and molecular characterisation of precision cut slices. Sci. Rep. 2015, 5, 17187.
77. Song, E. K., Tai, W. M., Messersmith, W. A., Bagby, S. et al., Potent antitumor activity of cabozantinib, a c-MET and VEGFR2 inhibitor, in a colorectal cancer patient-derived tumor explant model. Int. J. Cancer 2015, 136, 1967–1975.
78. Monsma, D. J., Monks, N. R., Cherba, D. M., Dylewski, D. et al., Genomic characterization of explant tumorgraft models derived from fresh patient tumor tissue. J. Transl. Med. 2012, 10, 125.
79. Carranza-Torres, I. E., Guzman-Delgado, N. E., Coronado-Martinez, C., Banuelos-Garcia, J. I. et al., Organotypic culture of breast tumor explants as a multicellular system for the screening of natural compounds with antineoplastic potential. Biomed Res. Int. 2015, 2015, 618021.
80. van der Kuip, H., Murdter, T. E., Sonnenberg, M., McClellan, M. et al., Short term culture of breast cancer tissues to study the activity of the anticancer drug taxol in an intact tumor environment. BMC Cancer 2006, 6, 86.
81. Sato, T., Stange, D. E., Ferrante, M., Vries, R. G. et al., Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma, and Barrett's epithelium. Gastroenterology 2011, 141, 1762–1772.
82. Lancaster, M. A., Knoblich, J. A., Organogenesis in a dish: Modeling development and disease using organoid technologies. Science 2014, 345, 1247125.
83. Fatehullah, A., Tan, S. H., Barker, N., Organoids as an in vitro model of human development and disease. Nat. Cell Biol. 2016, 18, 246–254.
84. Boj, S. F., Hwang, C. I., Baker, L. A., Chio, II et al., Organoid models of human and mouse ductal pancreatic cancer. Cell 2015, 160, 324–338.
85. Huang, L., Holtzinger, A., Jagan, I., BeGora, M. et al., Ductal pancreatic cancer modeling and drug screening using human pluripotent stem cell- and patient-derived tumor organoids. Nat. Med. 2015, 21, 1364–1371.
86. Walsh, A. J., Cook, R. S., Sanders, M. E., Arteaga, C. L., Skala, M. C., Drug response in organoids generated from frozen primary tumor tissues. Sci. Rep. 2016, 6, 18889.
87. Huang, L., Holtzinger, A., Jagan, I., BeGora, M. et al., Ductal pancreatic cancer modeling and drug screening using human pluripotent stem cell- and patient-derived tumor organoids. Nat. Med. 2015, 21, 1364–1371.
88. Dutta, R. C., Dutta, A. K., Cell-interactive 3D-scaffold; advances and applications. Biotechnol. Adv. 2009, 27, 334–339.
89. Pickup, M. W., Mouw, J. K., Weaver, V. M., The extracellular matrix modulates the hallmarks of cancer. EMBO Rep. 2014, 15, 1243–1253.
90. Johnson, K. R., Leight, J. L., Weaver, V. M., Demystifying the effects of a three-dimensional microenvironment in tissue morphogenesis. Methods Cell Biol. 2007, 83, 547–583.
91. Holle, A. W., Young, J. L., Spatz, J. P., In vitro cancer cell–ECM interactions inform in vivo cancer treatment. Adv. Drug Delivery Rev. 2016, 97, 270–279.
92. Pradhan, S., Hassani, I., Clary, J. M., Lipke, E. A., Polymeric Biomaterials for In Vitro Cancer Tissue Engineering and Drug Testing Applications. Tissue Eng. Part B 2016.
93. Emmert, M., Witzel, P., Heinrich, D., Challenges in tissue engineering - towards cell control inside artificial scaffolds. Soft Matter 2016, 12, 4287–4294.
94. Heffernan, J. M., Overstreet, D. J., Srinivasan, S., Le, L. D. et al., Temperature responsive hydrogels enable transient three-dimensional tumor cultures via rapid cell recovery. J. Biomed. Mater. Res. Part A 2016, 104, 17–25.
95. Xu, F., Celli, J., Rizvi, I., Moon, S. et al., A three-dimensional in vitro ovarian cancer coculture model using a high-throughput cell patterning platform. Biotechnol. J. 2011, 6, 204–212.
96. Nash, C. E., Mavria, G., Baxter, E. W., Holliday, D. L. et al., Development and characterisation of a 3D multi-cellular in vitro model of normal human breast: A tool for cancer initiation studies. Oncotarget 2015, 6, 13731–13741.
97. Park, J. I., Lee, J., Kwon, J. L., Park, H. B. et al., Scaffold-free coculture spheroids of human colonic adenocarcinoma cells and normal colonic fibroblasts promote tumorigenicity in nude mice. Transl. Oncol. 2016, 9, 79–88.
98. Rudisch, A., Dewhurst, M. R., Horga, L. G., Kramer, N. et al., High EMT Signature Score of Invasive Non-Small Cell Lung Cancer (NSCLC) Cells Correlates with NFkappaB Driven Colony-Stimulating Factor 2 (CSF2/GM-CSF) Secretion by Neighboring Stromal Fibroblasts. PLoS One 2015, 10, e0124283.
99. Daverey, A., Drain, A. P., Kidambi, S., Physical intimacy of breast cancer cells with mesenchymal stem cells elicits Trastuzumab resistance through Src activation. Sci. Rep. 2015, 5, 13744.
100. Lupo, G., Motta, C., Salmeri, M., Spina-Purrello, V. et al., An in vitro retinoblastoma human triple culture model of angiogenesis: A modulatory effect of TGF-beta. Cancer Lett. 2014, 354, 181–188.
101. Linde, N., Gutschalk, C. M., Hoffmann, C., Yilmaz, D., Mueller, M. M., Integrating macrophages into organotypic co-cultures: A 3D in vitro model to study tumor-associated macrophages. PLoS One 2012, 7, e40058.
102. Rama-Esendagli, D., Esendagli, G., Yilmaz, G., Guc, D., Spheroid formation and invasion capacity are differentially influenced by co-cultures of fibroblast and macrophage cells in breast cancer. Mol. Biol. Rep. 2014, 41, 2885–2892.
103. Liu, X.-q., Kiefl, R., Roskopf, C., Tian, F., Huber, R. M., Interactions among lung cancer cells, fibroblasts, and macrophages in 3D co-cultures and the impact on MMP-1 and VEGF expression. PLoS One 2016, 11, e0156268.
104. Howes, A. L., Richardson, R. D., Finlay, D., Vuori, K., 3-Dimensional culture systems for anti-cancer compound profiling and high-throughput screening reveal increases in EGFR inhibitor-mediated cytotoxicity compared to monolayer culture systems. PLoS One 2014, 9, e108283.
105. Phan-Lai, V., Florczyk, S. J., Kievit, F. M., Wang, K. et al., Three-dimensional scaffolds to evaluate tumor associated fibroblast-mediated suppression of breast tumor specific T cells. Biomacromolecules 2013, 14, 1330–1337.
106. Alonso-Nocelo, M., Abuin, C., Lopez-Lopez, R., de la Fuente, M., Development and characterization of a three-dimensional co-culture model of tumor T cell infiltration. Biofabrication 2016, 8, 025002.
107. Majumder, B., Baraneedharan, U., Thiyagarajan, S., Radhakrishnan, P. et al., Predicting clinical response to anticancer drugs using an ex vivo platform that captures tumour heterogeneity. Nat. Commun. 2015, 6, 6169.
108. Tostoes, R. M., Leite, S. B., Serra, M., Jensen, J. et al., Human liver cell spheroids in extended perfusion bioreactor culture for repeated-dose drug testing. Hepatology 2012, 55, 1227–1236.
109. Serra, M., Brito, C., Correia, C., Alves, P. M., Process engineering of human pluripotent stem cells for clinical application. Trends Biotechnol. 2012, 30, 350–359.
110. Hirt, C., Papadimitropoulos, A., Muraro, M. G., Mele, V. et al., Bioreactor-engineered cancer tissue-like structures mimic phenotypes, gene expression profiles and drug resistance patterns observed ”in vivo“. Biomaterials 2015, 62, 138–146.
111. Bhatia, S. N., Ingber, D. E., Microfluidic organs-on-chips. Nat. Biotechnol. 2014, 32, 760–772.
112. Boussommier-Calleja, A., Li, R., Chen, M. B., Wong, S. C., Kamm, R. D., Microfluidics: A new tool for modeling cancer-immune interactions. Trends Cancer 2016, 2, 6–19.
113. Skardal, A., Shupe, T., Atala, A., Organoid-on-a-chip and body-on-a-chip systems for drug screening and disease modeling. Drug Discovery Today 2016.
114. Materne, E. M., Ramme, A. P., Terrasso, A. P., Serra, M. et al., A multi-organ chip co-culture of neurospheres and liver equivalents for long-term substance testing. J. Biotechnol. 2015, 205, 36–46.
115. Maschmeyer, I., Lorenz, A. K., Schimek, K., Hasenberg, T. et al., A four-organ-chip for interconnected long-term co-culture of human intestine, liver, skin and kidney equivalents. Lab Chip 2015, 15, 2688–2699.
116. Rosa, R., Monteleone, F., Zambrano, N., Bianco, R., In vitro and in vivo models for analysis of resistance to anticancer molecular therapies. Curr. Med. Chem. 2014, 21, 1595–1606.
117. Rebelo, S. P., Costa, R., Sousa, M. F., Brito, C., Alves, P. M., Establishing Liver Bioreactors for In Vitro Research. Methods Mol. Biol. 2015, 1250, 189–202.
118. Schreiber-Brynzak, E., Klapproth, E., Unger, C., Lichtscheidl-Schultz, I. et al., Three-dimensional and co-culture models for preclinical evaluation of metal-based anticancer drugs. Invest. New Drugs 2015, 33, 835–847.
119. Laurent, J., Frongia, C., Cazales, M., Mondesert, O. et al., Multicellular tumor spheroid models to explore cell cycle checkpoints in 3D. BMC Cancer 2013, 13, 1–12.
120. Luca, A. C., Mersch, S., Deenen, R., Schmidt, S. et al., Impact of the 3D microenvironment on phenotype, gene expression, and EGFR inhibition of colorectal cancer cell lines. PLoS One 2013, 8, e59689.
121. Benvenuti, S., Sartore-Bianchi, A., Di Nicolantonio, F., Zanon, C. et al., Oncogenic Activation of the RAS/RAF Signaling pathway impairs the response of metastatic colorectal cancers to anti–epidermal growth factor receptor antibody therapies. Cancer Res. 2007, 67, 2643–2648.
122. Di Nicolantonio, F., Martini, M., Molinari, F., Sartore-Bianchi, A. et al., Wild-Type BRAF Is Required for Response to Panitumumab or Cetuximab in Metastatic Colorectal Cancer. J. Clin. Oncol. 2008, 26, 5705–5712.
123. Thurber, G. M., Schmidt, M. M., Wittrup, K. D., Antibody tumor penetration: Transport opposed by systemic and antigen-mediated clearance. Adv. Drug Delivery Rev. 2008, 60, 1421–1434.
124. Fennema, E., Rivron, N., Rouwkema, J., van Blitterswijk, C., de Boer, J., Spheroid culture as a tool for creating 3D complex tissues. Trends Biotechnol. 2013, 31, 108–115.
125. Horman, S. R., To, J., Orth, A. P., An HTS-compatible 3D colony formation assay to identify tumor-specific chemotherapeutics. J. Biomol. Screening 2013, 18, 1298–1308.
126. Rudin, M., Beckmann, N., Rausch, M., Evaluation of drug candidates: Efficacy readouts during lead optimization. Progr. Drug Res. 2005, 62, 185–255.
127. Ellinger, B., Silber, J., Prashar, A., Landskron, J. et al., A phenotypic screening approach to identify anticancer compounds derived from marine fungi. Assay Drug Dev. Technol. 2014, 12, 162–175.
128. Casey, A., Gargotti, M., Bonnier, F., Byrne, H. J., Chemotherapeutic efficiency of drugs in vitro: Comparison of doxorubicin exposure in 3D and 2D culture matrices. Toxicol. in Vitro 2016, 33, 99–104.
129. Walzl, A., Unger, C., Kramer, N., Unterleuthner, D. et al., The Resazurin reduction assay can distinguish cytotoxic from cytostatic compounds in spheroid screening assays. J. Biomol. Screening 2014, 19, 1047–1059.
130. Lv, D., Ma, Q.-h., Duan, J.-j., Wu, H.-b. et al., Optimized dissociation protocol for isolating human glioma stem cells from tumorspheres via fluorescence-activated cell sorting. Cancer Lett. 2016, 377, 105–115.
131. Li, L., Zhou, Q., Voss, T. C., Quick, K. L., LaBarbera, D. V., High-throughput imaging: Focusing in on drug discovery in 3D. Methods 2016, 96, 97–102.
132. Gualda, E. J., Pereira, H., Vale, T., Estrada, M. F. et al., SPIM-fluid: Open source light-sheet based platform for high-throughput imaging. Biomed. Opt. Express 2015, 6, 4447–4456.
133. Li, C. Y., Wood, D. K., Huang, J. H., Bhatia, S. N., Flow-based pipeline for systematic modulation and analysis of 3D tumor microenvironments. Lab Chip 2013, 13, 1969–1978.
134. Saribudak, A., Kucharavy, H., Hubbard, K., M et al., Spatial heterogeneity analysis in evaluation of cell viability and apoptosis for colorectal cancer cells. IEEE J. Transl. Eng. Health Med. 2016, 4, 1–9.
135. Anbil, S., Rizvi, I., Celli, J. P., Alagic, N. et al., Impact of treatment response metrics on photodynamic therapy planning and outcomes in a three-dimensional model of ovarian cancer. J. Biomed. Opt. 2013, 18, 098004.
136. Loessner, D., Little, J. P., Pettet, G. J., Hutmacher, D. W., A multiscale road map of cancer spheroids--incorporating experimental and mathematical modelling to understand cancer progression. J. Cell Sci. 2013, 126, 2761–2771.
137. Beerenwinkel, N., Schwarz, R. F., Gerstung, M., Markowetz, F., Cancer evolution: Mathematical models and computational inference. Syst. Biol. 2015, 64, e1-e25.
138. Stern, A. M., Schurdak, M. E., Bahar, I., Berg, J. M., Taylor, D. L., A Perspective on Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery and the Advancement of Personalized Medicine. J. Biomol. Screening 2016, 21, 521–534.
139. Gough, A., Shun, T. Y., Taylor, D. L., Schurdak, M., A metric and workflow for quality control in the analysis of heterogeneity in phenotypic profiles and screens. Methods 2016, 96, 12–26.
140. Gough, A. H., Chen, N., Shun, T. Y., Lezon, T. R. et al., Identifying and quantifying heterogeneity in high content analysis: Application of heterogeneity indices to drug discovery. PLoS One 2014, 9, e102678.
141. Glickman, J. F., Lundback, T., Napper, A. D., Niles, W. D. et al., Controversies in ASSAY and drug development technologies: A focus on assessing irreproducibility. Assay Drug Dev. Technol. 2014, 12, 443–451.
142. Trask, O. J., Jr., Johnston, P. A., Standardization of high content imaging and informatics. Assay Drug Dev. Technol. 2015, 13, 341–346.
143. Cortes-Ciriano, I., Bender, A., How consistent are publicly reported cytotoxicity data? Large-scale statistical analysis of the concordance of public independent cytotoxicity measurements. ChemMedChem 2016, 11, 57–71.