Abstract
The success rate from investigational new drug filing to drug approval has remained low for decades despite major scientific and technological advances, and a steady increase of funding and investment. The failure to demonstrate drug efficacy has been the major reason that drug development does not progress beyond phase II and III clinical trials. The combination of two-dimensional (2D) cellular in vitro and animal models has been the gold standard for basic science research and preclinical drug development studies. However, most findings from these systems fail to translate into human trials because these models only partly recapitulate human physiology and pathology. The lack of a dynamic three-dimensional microenvironment in 2D cellular models reduces the physiological relevance, and for these reasons, 3D and microfluidic model systems are now being developed as more native-like biological assay platforms. 3D cellular in vitro systems, microfluidics, self-organized organoids, and 3D biofabrication are the most promising technologies to mimic human physiology because they provide mechanical cues and a 3D microenvironment to the multicellular components. With the advent of human-induced pluripotent stem cell (iPSC) technology, the 3D dynamic in vitro systems further enable extensive access to human-like tissue models. As increasingly complex 3D cellular systems are produced, the use of current visualization technologies is limited due to the thickness and opaqueness of 3D tissues. Tissue-clearing techniques improve light penetration deep into tissues by matching refractive indices among the 3D components. 3D segmentation enables quantitative measurements based on 3D tissue images. Using these state-of-the-art technologies, high-throughput screening (HTS) of thousands of drug compounds in 3D tissue models is slowly becoming a reality. In order to screen thousands of compounds, machine learning will need to be applied to help maximize outcomes from the use of cheminformatics and phenotypic approaches to drug screening. In this chapter, we discuss the current 3D ocular models recapitulating physiology and pathology of the back of the eye and further discuss visualization and quantification techniques that can be implemented for drug screening in ocular diseases.
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Scannell JW, Blanckley A, Boldon H, Warrington B (2012) Diagnosing the decline in pharmaceutical R&D efficiency. Nat Rev Drug Discov 11(3):191–200
Hay M, Thomas DW, Craighead JL, Economides C, Rosenthal J (2014) Clinical development success rates for investigational drugs. Nat Biotechnol 32(1):40–51
BIO BaA (2016) Clinical development success rates 2006-2015. BIO, Washington
Harrison RK (2016) Phase II and phase III failures: 2013-2015. Nat Rev Drug Discov 15(12):817–818
Repetto G, del Peso A, Zurita JL (2008) Neutral red uptake assay for the estimation of cell viability/cytotoxicity. Nat Protoc 3(7):1125–1131
Trapnell C et al (2010) Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 28(5):511–515
Potter H (2003) Transfection by electroporation. Curr Protoc Mol Biol Chapter 9:Unit 9 3
Connor KM et al (2009) Quantification of oxygen-induced retinopathy in the mouse: a model of vessel loss, vessel regrowth and pathological angiogenesis. Nat Protoc 4(11):1565–1573
McAvoy JW, Chamberlain CG, de Iongh RU, Hales AM, Lovicu FJ (1999) Lens development. Eye (Lond) 13(Pt 3b):425–437
Ferrara N, Hillan KJ, Gerber HP, Novotny W (2004) Discovery and development of bevacizumab, an anti-VEGF antibody for treating cancer. Nat Rev Drug Discov 3(5):391–400
Rongvaux A et al (2014) Development and function of human innate immune cells in a humanized mouse model. Nat Biotechnol 32(4):364–372
Chiu JJ, Chien S (2011) Effects of disturbed flow on vascular endothelium: pathophysiological basis and clinical perspectives. Physiol Rev 91(1):327–387
Li YS, Haga JH, Chien S (2005) Molecular basis of the effects of shear stress on vascular endothelial cells. J Biomech 38(10):1949–1971
Huh D et al (2010) Reconstituting organ-level lung functions on a chip. Science 328(5986):1662–1668
Huh D, Torisawa YS, Hamilton GA, Kim HJ, Ingber DE (2012) Microengineered physiological biomimicry: organs-on-chips. Lab Chip 12(12):2156–2164
Newman AC, Nakatsu MN, Chou W, Gershon PD, Hughes CC (2011) The requirement for fibroblasts in angiogenesis: fibroblast-derived matrix proteins are essential for endothelial cell lumen formation. Mol Biol Cell 22(20):3791–3800
Chen JX, Stinnett A (2008) Disruption of Ang-1/Tie-2 signaling contributes to the impaired myocardial vascular maturation and angiogenesis in type II diabetic mice. Arterioscler Thromb Vasc Biol 28(9):1606–1613
Wakui S et al (2006) Localization of Ang-1, -2, Tie-2, and VEGF expression at endothelial-pericyte interdigitation in rat angiogenesis. Lab Invest 86(11):1172–1184
Moya ML, Alonzo LF, George SC (2014) Microfluidic device to culture 3D in vitro human capillary networks. Methods Mol Biol 1202:21–27
Wang X, Phan DTT, George SC, Hughes CCW, Lee AP (2017) 3D anastomosed microvascular network model with living capillary networks and endothelial cell-lined microfluidic channels. Methods Mol Biol 1612:325–344
Jeon JS et al (2015) Human 3D vascularized organotypic microfluidic assays to study breast cancer cell extravasation. Proc Natl Acad Sci U S A 112(1):214–219
Kim S, Lee H, Chung M, Jeon NL (2013) Engineering of functional, perfusable 3D microvascular networks on a chip. Lab Chip 13(8):1489–1500
Chung M et al (2018) Wet-AMD on a chip: modeling outer blood-retinal barrier in vitro. Adv Healthc Mater 7(2)
Becerra SP et al (2004) Pigment epithelium-derived factor in the monkey retinal pigment epithelium and interphotoreceptor matrix: apical secretion and distribution. Exp Eye Res 78(2):223–234
Saint-Geniez M, Kurihara T, Sekiyama E, Maldonado AE, D’Amore PA (2009) An essential role for RPE-derived soluble VEGF in the maintenance of the choriocapillaris. Proc Natl Acad Sci U S A 106(44):18751–18756
Sonoda S et al (2009) Attainment of polarity promotes growth factor secretion by retinal pigment epithelial cells: relevance to age-related macular degeneration. Aging 2(1):28–42
Bailey TA et al (2004) Oxidative stress affects the junctional integrity of retinal pigment epithelial cells. Invest Ophthalmol Vis Sci 45(2):675–684
Hamilton RD, Foss AJ, Leach L (2007) Establishment of a human in vitro model of the outer blood-retinal barrier. J Anat 211(6):707–716
Song MJ, Quinn R, Dejene R, Bharti K (2017) 3D tissue engineered RPE/“choroid” to identify mechanism of AMD-disease initiation and progression. Assoc Res Vis Ophthalmol 58(8):3760–3760
Song MJ, Bharti K (2016) Looking into the future: using induced pluripotent stem cells to build two and three dimensional ocular tissue for cell therapy and disease modeling. Brain Res 1638(Pt A):2–14
Hampton C et al (2018) Hypoxia of retina pigment epithelium induces type 1 CNV-like morphology within 3D engineered iPSC-RPE/“Choroid” tissues. Invest Ophthalmol Vis Sci 59(9):3272–3272
Hotaling NA et al (2016) Nanofiber scaffold-based tissue-engineered retinal pigment epithelium to treat degenerative eye diseases. J Ocul Pharmacol Ther 32(5):272–285
Ablonczy Z, Crosson CE (2007) VEGF modulation of retinal pigment epithelium resistance. Exp Eye Res 85(6):762–771
Curcio CA, Johnson M (2012) Structure, function, and pathology of Bruch’s membrane. Elastic:465–481
Baba T et al (2009) Maturation of the fetal human choriocapillaris. Invest Ophthalmol Vis Sci 50(7):3503–3511
Takahashi K et al (2007) Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell 131(5):861–872
Reh TA (2017) The development of the retina. Ryan’s Retina. Elsevier, Amsterdam
Zuber ME, Gestri G, Viczian AS, Barsacchi G, Harris WA (2003) Specification of the vertebrate eye by a network of eye field transcription factors. Development 130(21):5155–5167
Lamba DA, Karl MO, Ware CB, Reh TA (2006) Efficient generation of retinal progenitor cells from human embryonic stem cells. Proc Natl Acad Sci U S A 103(34):12769–12774
Osakada F et al (2008) Toward the generation of rod and cone photoreceptors from mouse, monkey and human embryonic stem cells. Nat Biotechnol 26(2):215–224
Mellough CB, Sernagor E, Moreno-Gimeno I, Steel DH, Lako M (2012) Efficient stage-specific differentiation of human pluripotent stem cells toward retinal photoreceptor cells. Stem Cells 30(4):673–686
Hunt NC et al (2017) 3D culture of human pluripotent stem cells in RGD-alginate hydrogel improves retinal tissue development. Acta Biomater 49:329–343
Eiraku M et al (2011) Self-organizing optic-cup morphogenesis in three-dimensional culture. Nature 472(7341):51–56
Nakano T et al (2012) Self-formation of optic cups and storable stratified neural retina from human ESCs. Cell Stem Cell 10(6):771–785
Kuwahara A et al (2015) Generation of a ciliary margin-like stem cell niche from self-organizing human retinal tissue. Nat Commun 6:6286
Wahlin KJ et al (2017) Photoreceptor outer segment-like structures in long-term 3D retinas from human pluripotent stem cells. Sci Rep 7(1):766
Volkner M et al (2016) Retinal organoids from pluripotent stem cells efficiently recapitulate retinogenesis. Stem Cell Rep 6(4):525–538
Gonzalez-Cordero A et al (2013) Photoreceptor precursors derived from three-dimensional embryonic stem cell cultures integrate and mature within adult degenerate retina. Nat Biotechnol 31(8):741–747
Meyer JS et al (2009) Modeling early retinal development with human embryonic and induced pluripotent stem cells. Proc Natl Acad Sci U S A 106(39):16698–16703
Meyer JS et al (2011) Optic vesicle-like structures derived from human pluripotent stem cells facilitate a customized approach to retinal disease treatment. Stem Cells 29(8):1206–1218
Zhong X et al (2014) Generation of three-dimensional retinal tissue with functional photoreceptors from human iPSCs. Nat Commun 5:4047
Luo Z et al (2018) An optimized system for effective derivation of three-dimensional retinal tissue via wnt signaling regulation. Stem Cells 36:1709
Zhu Y et al (2013) Three-dimensional neuroepithelial culture from human embryonic stem cells and its use for quantitative conversion to retinal pigment epithelium. PLoS One 8(1):e54552
Lowe A, Harris R, Bhansali P, Cvekl A, Liu W (2016) Intercellular adhesion-dependent cell survival and ROCK-regulated actomyosin-driven forces mediate self-formation of a retinal organoid. Stem Cell Rep 6(5):743–756
Shirai H et al (2016) Transplantation of human embryonic stem cell-derived retinal tissue in two primate models of retinal degeneration. Proc Natl Acad Sci U S A 113(1):E81–E90
Mandai M et al (2017) Autologous induced stem-cell-derived retinal cells for macular degeneration. N Engl J Med 376(11):1038–1046
Dorrie J, Wellner V, Kampgen E, Schuler G, Schaft N (2006) An improved method for RNA isolation and removal of melanin contamination from melanoma tissue: implications for tumor antigen detection and amplification. J Immunol Methods 313(1-2):119–128
Eckhart L, Bach J, Ban J, Tschachler E (2000) Melanin binds reversibly to thermostable DNA polymerase and inhibits its activity. Biochem Biophys Res Commun 271(3):726–730
Chung JY et al (2016) A melanin-bleaching methodology for molecular and histopathological analysis of formalin-fixed paraffin-embedded tissue. Lab Invest 96(10):1116–1127
Liu CH et al (2013) Melanin bleaching with dilute hydrogen peroxide: a simple and rapid method. Appl Immunohistochem Mol Morphol 21(3):275–279
Kim SY, Assawachananont J (2016) A new method to visualize the intact subretina from retinal pigment epithelium to retinal tissue in whole mount of pigmented mouse eyes. Transl Vis Sci Technol 5(1):6
Thanos A et al (2012) Evidence for baseline retinal pigment epithelium pathology in the Trp1-Cre mouse. Am J Pathol 180(5):1917–1927
Tainaka K, Kuno A, Kubota SI, Murakami T, Ueda HR (2016) Chemical principles in tissue clearing and staining protocols for whole-body cell profiling. Annu Rev Cell Dev Biol 32:713–741
Silvestri L, Costantini I, Sacconi L, Pavone FS (2016) Clearing of fixed tissue: a review from a microscopist’s perspective. J Biomed Opt 21(8):081205
Jacques SL (2013) Optical properties of biological tissues: a review. Phys Med Biol 58(11):R37–R61
Spalteholz W (1914) Über das Durchsichtigmachen von menschlichen und tierischen Präparaten und seine theoretischen Bedingungen, nebst Anhang: Über Knochenfärbung. S. Hirzel, Leipzig
Erturk A et al (2012) Three-dimensional imaging of solvent-cleared organs using 3DISCO. Nat Protoc 7(11):1983–1995
Ke MT, Fujimoto S, Imai T (2013) SeeDB: a simple and morphology-preserving optical clearing agent for neuronal circuit reconstruction. Nat Neurosci 16(8):1154–1161
Hama H et al (2011) Scale: a chemical approach for fluorescence imaging and reconstruction of transparent mouse brain. Nat Neurosci 14(11):1481–1488
Hama H et al (2015) ScaleS: an optical clearing palette for biological imaging. Nat Neurosci 18(10):1518–1529
Susaki EA, Ueda HR (2016) Whole-body and whole-organ clearing and imaging techniques with single-cell resolution: toward organism-level systems biology in mammals. Cell Chem Biol 23(1):137–157
Chung K et al (2013) Structural and molecular interrogation of intact biological systems. Nature 497(7449):332–337
Yang B et al (2014) Single-cell phenotyping within transparent intact tissue through whole-body clearing. Cell 158(4):945–958
Murray E et al (2015) Simple, scalable proteomic imaging for high-dimensional profiling of intact systems. Cell 163(6):1500–1514
Zheng H, Rinaman L (2016) Simplified CLARITY for visualizing immunofluorescence labeling in the developing rat brain. Brain Struct Funct 221(4):2375–2383
Phillips J et al (2016) Development of passive CLARITY and immunofluorescent labelling of multiple proteins in human cerebellum: understanding mechanisms of neurodegeneration in mitochondrial disease. Sci Rep 6:26013
Kuwajima T et al (2013) ClearT: a detergent- and solvent-free clearing method for neuronal and non-neuronal tissue. Development 140(6):1364–1368
Boutin ME et al (2018) A high-throughput imaging and nuclear segmentation analysis protocol for cleared 3D culture models. Sci Rep 8(1):11135
Grist SM, Nasseri SS, Poon T, Roskelley C, Cheung KC (2016) On-chip clearing of arrays of 3-D cell cultures and micro-tissues. Biomicrofluidics 10(4):044107
Silva Santisteban T, Rabajania O, Kalinina I, Robinson S, Meier M (2017) Rapid spheroid clearing on a microfluidic chip. Lab Chip 18(1):153–161
Rajasekaran B, Uriu K, Valentin G, Tinevez JY, Oates AC (2016) Object segmentation and ground truth in 3D embryonic imaging. PLoS One 11(6):e0150853
Li L, Zhou Q, Voss TC, Quick KL, LaBarbera DV (2016) High-throughput imaging: focusing in on drug discovery in 3D. Methods 96:97–102
Schmitz A, Fischer SC, Mattheyer C, Pampaloni F, Stelzer EH (2017) Multiscale image analysis reveals structural heterogeneity of the cell microenvironment in homotypic spheroids. Sci Rep 7:43693
Jones TR et al (2009) Scoring diverse cellular morphologies in image-based screens with iterative feedback and machine learning. Proc Natl Acad Sci U S A 106(6):1826–1831
Inglese J et al (2007) High-throughput screening assays for the identification of chemical probes. Nat Chem Biol 3(8):466–479
Ko HC, Gelb BD (2014) Concise review: drug discovery in the age of the induced pluripotent stem cell. Stem Cells Transl Med 3(4):500–509
Haasen D et al (2017) How phenotypic screening influenced drug discovery: lessons from five years of practice. Assay Drug Dev Technol 15(6):239–246
Ursu A, Scholer HR, Waldmann H (2017) Small-molecule phenotypic screening with stem cells. Nat Chem Biol 13(6):560–563
Smith K et al (2018) Phenotypic image analysis software tools for exploring and understanding big image data from cell-based assays. Cell Syst 6(6):636–653
Kaewkhaw R et al (2016) Treatment paradigms for retinal and macular diseases using 3-D retina cultures derived from human reporter pluripotent stem cell lines. Invest Ophthalmol Vis Sci 57(5):ORSFl1
Fuller JA et al (2014) A high content screening approach to identify molecules neuroprotective for photoreceptor cells. Adv Exp Med Biol 801:773–781
Chang YC et al (2014) The generation of induced pluripotent stem cells for macular degeneration as a drug screening platform: identification of curcumin as a protective agent for retinal pigment epithelial cells against oxidative stress. Front Aging Neurosci 6:191
Ito SI, Onishi A, Takahashi M (2017) Chemically-induced photoreceptor degeneration and protection in mouse iPSC-derived three-dimensional retinal organoids. Stem Cell Res 24:94–101
Vergara MN et al (2017) Three-dimensional automated reporter quantification (3D-ARQ) technology enables quantitative screening in retinal organoids. Development 144(20):3698–3705
Parfitt DA et al (2016) Identification and correction of mechanisms underlying inherited blindness in human iPSC-derived optic cups. Cell Stem Cell 18(6):769–781
Zhou T et al (2017) High-content screening in hPSC-neural progenitors identifies drug candidates that inhibit zika virus infection in fetal-like organoids and adult brain. Cell Stem Cell 21(2):274–283. e275
Mathews Griner LA et al (2016) Large-scale pharmacological profiling of 3D tumor models of cancer cells. Cell Death Dis 7(12):e2492
Hou S et al (2018) Advanced development of primary pancreatic organoid tumor models for high-throughput phenotypic drug screening. SLAS Discov 23(6):574–584
Carragher N et al (2018) Concerns, challenges and promises of high-content analysis of 3D cellular models. Nat Rev Drug Discov 17:606
Fujitani M et al (2017) Morphology-based non-invasive quantitative prediction of the differentiation status of neural stem cells. J Biosci Bioeng 124(3):351–358
Kobayashi H et al (2017) Label-free detection of cellular drug responses by high-throughput bright-field imaging and machine learning. Sci Rep 7(1):12454
Matsuoka F et al (2013) Morphology-based prediction of osteogenic differentiation potential of human mesenchymal stem cells. PLoS One 8(2):e55082
Sasaki H et al (2014) Label-free morphology-based prediction of multiple differentiation potentials of human mesenchymal stem cells for early evaluation of intact cells. PLoS One 9(4):e93952
Anderson DM et al (2014) High resolution MALDI imaging mass spectrometry of retinal tissue lipids. J Am Soc Mass Spectrom 25(8):1394–1403
Deutskens F, Yang J, Caprioli RM (2011) High spatial resolution imaging mass spectrometry and classical histology on a single tissue section. J Mass Spectrom 46(6):568–571
Seeley EH, Schwamborn K, Caprioli RM (2011) Imaging of intact tissue sections: moving beyond the microscope. J Biol Chem 286(29):25459–25466
Srinivasan B et al (2015) TEER measurement techniques for in vitro barrier model systems. J Lab Autom 20(2):107–126
Ferrer M et al (2014) A multiplex high-throughput gene expression assay to simultaneously detect disease and functional markers in induced pluripotent stem cell-derived retinal pigment epithelium. Stem Cells Transl Med 3(8):911–922
Lo YC, Rensi SE, Torng W, Altman RB (2018) Machine learning in chemoinformatics and drug discovery. Drug Discov Today 23:1538
Horvath P, Wild T, Kutay U, Csucs G (2011) Machine learning improves the precision and robustness of high-content screens: using nonlinear multiparametric methods to analyze screening results. J Biomol Screen 16(9):1059–1067
O’Duibhir E et al (2018) Machine learning enables live label-free phenotypic screening in three dimensions. Assay Drug Dev Technol 16(1):51–63
Piccinini F et al (2017) Advanced cell classifier: user-friendly machine-learning-based software for discovering phenotypes in high-content imaging data. Cell Syst 4(6):651–655. e655
Smith K, Horvath P (2014) Active learning strategies for phenotypic profiling of high-content screens. J Biomol Screen 19(5):685–695
Strang BL et al (2018) Identification of lead anti-human cytomegalovirus compounds targeting MAP4K4 via machine learning analysis of kinase inhibitor screening data. PLoS One 13(7):e0201321
Fuller JA, Berlinicke CA, Inglese J, Zack DJ (2016) Use of a machine learning-based high content analysis approach to identify photoreceptor neurite promoting molecules. Adv Exp Med Biol 854:597–603
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Boutin, M.E., Hampton, C., Quinn, R., Ferrer, M., Song, M.J. (2019). 3D Engineering of Ocular Tissues for Disease Modeling and Drug Testing. In: Bharti, K. (eds) Pluripotent Stem Cells in Eye Disease Therapy. Advances in Experimental Medicine and Biology, vol 1186. Springer, Cham. https://doi.org/10.1007/978-3-030-28471-8_7
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