Patient-Specific Induced Pluripotent Stem Cells for Disease

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Perspective

Patient-specific Induced Pluripotent Stem Cells for Disease Modeling and Phenotypic Drug Discovery Shibing Tang, Min Xie, Nan Cao, and Sheng Ding J. Med. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jmedchem.5b00789 • Publication Date (Web): 31 Aug 2015 Downloaded from http://pubs.acs.org on September 1, 2015

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Journal of Medicinal Chemistry

Patient-specific Induced Pluripotent Stem Cells for Disease Modeling and Phenotypic Drug Discovery Shibing Tang,† Min Xie,† Nan Cao, Sheng Ding* Gladstone Institutes, 1650 Owens Street, San Francisco, California 94158, United States

ABSTRACT: In vitro cell models are invaluable tools for studying diseases and discovering drugs. Human induced pluripotent stem cells, particularly derived from patients, are an advantageous resource for generating ample supplies of cells to create unique platforms that model disease. This perspective will review recent developments in modeling a variety of diseases—including their cellular phenotypes—with induced pluripotent stem cells derived from patients. It will also describe how researchers have exploited these models to validate drugs as potential therapeutics for these devastating diseases.

INTRODUCTION Phenotypic drug discovery. Modern efforts for drug discovery search for therapeutics that cure or alleviate disease. In preclinical settings, drug discovery involves routinely testing chemical entities in disease models and evaluating their pharmacological effects. To find these entities, drug candidates are screened through two fundamentally different approaches—target-based drug discovery (TDD) and phenotypic drug discovery (PDD). TDD measures the interactions between drug candidates and a single, well-defined drug target, usually with biochemical assays. TDD has tremendous merit; however, it can be limited by incomplete knowledge of the molecular mechanisms underlying a disease. Because TDD is intended for only one drug target, it could miss a significant off-target and/or polypharmacological effect of the drug.1 PDD, however, is not limited to a specific drug target. Instead, it relies on phenotypes of organisms, tissues, or living cells—such as their morphology, functions, and/or biomarkers—to model the specific phenotypic parameters of a disorder. Thus, PDD can measure phenotypic readouts to reveal drug candidates that induce changes in pathological hallmarks, such as a switch from a pathological to healthy state, and their pharmacological and biological effects. PDD is an

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advantageous pathological and physiological approach that has arguably achieved a higher success rate in the launch of novel classes of drugs for treating diseases.2 Human induced pluripotent stem cells. Living cells can reflect an organism’s essential physiological activities and invaluably support modeling diseases and screening for potential drugs in vitro. Human cells are undoubtedly the most relevant platform for these models, because they avoid concerns about interspecies differences in physiology, pharmacology, and cellular processes. However, how disease-relevant human cells are applied depends on their accessibility. For example, human lines of cancer cells are readily available and have been widely used in oncology studies and anticancer therapies.3 Nonetheless, researchers must consider how difficulties in harvesting and propagating large varieties of disease-relevant human cells can restrict their applications in modeling diseases and discovering drugs. Fortunately, cell-reprogramming technology has substantially expanded the availability of human cells. 4,5 This technology can be used to convert human somatic cells into induced pluripotent stem cells (iPSCs) by forcing expression of a group of transcription factors.6 Human iPSCs closely resemble human embryonic stem cells (ESCs), because they can proliferate indefinitely and differentiate into all cell types found in a human body,4,5 including neurons,7 cardiomyocytes (CMs),8 hepatocytes (HCs),9 and chondrocytes.10 Thus, iPSCs can serve as an unlimited source of human cells for modeling disease. Reprogramming iPSCs from cells taken from patients opens many possibilities in disease modeling and PDD (Figure 1). For example, iPSCs retain the genetic characteristics of their donors, which enables genotypedependent pathophysiology to manifest at the cellular level to recapitulate pathological biomarkers and, thereby, support studies of genetic disorders. In recent years, patient-derived iPSCs have been used to study a number of devastating diseases, 11 , 12 which have shed new light on their phenotypic traits and cellular mechanisms. Therefore, human iPSCs have tremendous potential in discovering drugs through phenotypic approaches. In this perspective, we will review recent developments in applying patient-derived iPSCs to disease modeling and PDD, with a particular focus on neurological disorders and heart disease that greatly burden healthcare and urgently call for effective therapies.


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Figure 1. Process for generating induced pluripotent stem cells derived from patients and using them for disease modeling and phenotypic drug discovery. Induced pluripotent stem cells (iPSCs) can be generated from patient-specific somatic cells and then transformed into desired cell types by directed differentiation. Control cells can be either derived from healthy donors or generated by genetically correcting patient-specific iPSCs through targeted genome editing. These model cells can be used to study and compare phenotypes between control and diseased cells in a dish and to perform screening assays for phenotypic drug discovery. These approaches can enrich our knowledge of diseases and reveal drugs that effectively benefit patients. NEUROLOGICAL DISEASE Primary neural cells from humans are accessible only through surgical resection or postmortem biopsies and, thus, are too scarce to be widely used to study neurological disease. Alternatively, iPSCs are an abundant source of human neural cells. While generating specific types of neural cells from iPSCs can be challenging, methods to generate these cells are improving7—iPSCs can now be differentiated into neural cells and used to model neurological disorders.13,14,15 Here, we will review recent studies of neurological diseases, focusing on those that use patient-derived iPSCs to model disease and pharmacologically rescue cellular-disease phenotypes. We will also discuss how researchers validated the relevance of the cellular phenotypes seen in the iPSCs to the actual diseases, and we will highlight strategies for robustly inducing these phenotypes to provide readouts for PDD. Familial dysautonomia. Familial dysautonomia (FD) is a rare, but fatal, degenerative disease caused by mutations in the IKBKAP gene, 16 which primarily affects the neural crest (NC) lineage. Specifically, these


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mutations cause defects in the splicing of IKBKAP in peripheral neurons, which causes them to die or lose motility. To model FD with human cells, researchers from the Studer Lab generated iPSCs from fibroblasts isolated from FD patients (FD-iPSCs) and differentiated them into NC (FD-NC) precursor cells.17 In these cells, the ratio of wild-type to mutant IKBKAP (WT- versus MU-IKBKAP) transcripts was much lower than control cells derived from healthy individuals (Table 1). The FD-NC precursors also exhibited reduced neurogenesis and migration, further demonstrating that FD-NC precursors recapitulated the pathogenesis of FD. Interestingly, treating FD-NC precursors with kinentin, a plant cytokinin known to rescue defects in IKBKAP splicing, significantly increased normal splicing and decreased mutant splicing of IKBKAP (Table 1). Continuously treating these cells with kinentin also improved the neurogenesis of these precursors, but not their migratory propensity. Nonetheless, these findings support that FD-associated pathological phenotypes could be partially rescued with a pharmacological treatment. More recently, this same group successfully applied iPSC-based PDD to a high-throughput system that they developed to screen for compounds that rescue defects in the expression of IKBKAP in the FD-NC model.18 Specifically, with quantitative reverse transcription polymerase chain reaction (qRT-PCR), they measured the IKBKAP level in reference to the 18S internal control. To achieve high reproducibility, they optimized the experimental parameters against the density of cells in each well. With this system, the authors screened a library of 6,912 compounds and identified 43 hits that increased wild-type IKBKAP. Among these hits, seven compounds rescued IKBKAP expression in the FD-NC model and similar cell lines. Most notably, 6-Chloro2,3,4,5-tetrahydro-3-methyl-1H-3-benzazepine (SKF-86466, Figure 2)18 and yohimbine, two known antagonists of the α2-adrenergic receptor, rescued defects in IKBKAP splicing, supporting that the α2-adrenergic receptor affects the expression of IKBKAP (Table 1). Unfortunately, none of these compounds rescued the migratory defects of FD-NC precursors. Nonetheless, the authors demonstrated the feasibility of screening phenotypes and the value of confirming chemical compounds with an iPSC-derived model of disease with a defined genetic cause but unknown molecular mechanism. With this approach, researchers also evaluated active compounds with known molecular mechanisms to discover potential therapeutic targets for treating FD.


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Spinal muscular atrophy. Spinal muscular atropy (SMA) is characterized by progressive muscle weakness caused by mutations in the SMN1 gene. This mutation reduces the production of survival of motor neuron (SMN) protein to cause the selective loss of motor neurons (MNs) in the anterior horn of the spinal cord.19 Ebert et al. successfully modeled SMA with patient-derived iPSCs (SMA-iPSCs) deficient in SMN protein.20 They confirmed that while both control and SMA-iPSCs could generate MNs, the number of MNs in the SMA-iPSC culture significantly decreased over time, mimicking the death of MNs and the neurodegeneration process in vitro (Table 1). By immunostaining, they found that the nuclear gems that contain SMN proteins were present in control iPSCs but not in SMA-iPSCs. Furthermore, they found that valproic acid (VPA), a histone deacetylase inhibitor, and tobramycin, an aminoglycoside antibiotic, enhanced the production of SMN in SMAiPSCs (Table 1). These findings support that patient-derived iPSCs can recapitulate the pathology and phenotypes of SMA. Rett syndrome. Rett syndrome (RTT), a progressive neurodevelopmental disorder, is caused by mutations in the MECP2 gene that lead to a loss of function methyl-CpG-binding protein 2 (MeCP2).21 In a mouse model of RTT, Chao et al. found that altering MeCP2 affects the formation of glutamatergic synapses.22 Marchetto et al. then confirmed the role of MeCP2 in the pathology of RTT with neurons generated from iPSCs derived from RTT patients (RTT-neurons). 23 Marchetto et al. observed decreased densities of synaptic puncta in RTTneurons, which reflected a decrease in the number of glutamatergic synapses compared to control neurons (Table 1). They also found that knocking down MeCP2 in neurons from wild-type human iPSCs reduced the number of glutamatergic synapses, mimicking the consequences of the loss of function of MeCP2. Gentamicin, an aminoglycoside antibiotic, was found to increase the number of glutamatergic synapses in RTT-neurons (Table 1). These results support that RTT-neurons represent a valuable model for studying RTT. Machado-Joseph disease. Machado-Joseph disease (MJD) is a rare, hereditary cerebral ataxia caused by the expansion of polyglutamine (polyQ)-encoding CAG repeats in the MJD1gene, which produces polyQ-expanded ataxin-3 protein. Aberrant proteolysis of this protein generates aggregates that initiate MJD. In iPSC-derived neurons from MJD patients (MJD-neurons), Koch et al. stimulated the excitatory transmitter L-glutamate and observed an increased cleavage of polyQ-expanded ataxin-3 and a dose-dependent aggregation of its ACS Paragon Plus Environment

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fragments (Table 1).24 These aggregates were reduced by inhibiting caspases (with Ac-YVAD-CHO, Z-DEVDFMK, or Z-VAD-FMK) and calpain (with ALLN, or calpeptin). Depleting calcium (Ca2+) (with EDTA) and blocking Ca2+ influx (with D-APV, NBQX, or tetrodotoxin) also reduced the ataxin-3 aggregates (Table 1). In this study, the authors confirmed the known pathogenesis of the MJD. Further investigations into the molecular pathways that influence the pathological cleavage and aggregation of the mutant ataxin-3 may bring about new therapeutic strategies to treat MJD. The authors also established an iPSC-based model of MJD dependent on the mutant ataxin-3, which will be useful to explore new entities to treat this disease. Schizophrenia. Schizophrenia (SCZD) is a psychocognitive disorder that affects 1% of the population.25 SCZD patients are currently treated with antipsychotic drugs that target dopamine receptor D2, but they still suffer from inadequate efficacies and side effects.26 Thus, we need more effective treatments for this disease. The pathology of SCZD is largely affected by disrupted neural connectivity.27 By developing an in vitro cellular model that recapitulates this disrupted connectivity, researchers can further study the molecular mechanisms that underlie this disease and explore new medications to treat it with PDD. Brennand et al. have already reported a successful in vitro model of SCZD that uses iPSCs.28 Here, they traced the monosynaptic connections among neurons generated from SCZD iPSCs (SCZD-neurons) with a rabies virus and found that these neurons displayed decreased neuronal connectivity, which they rescued with loxapine, an antipsychotic drug (Table 1). This study illustrated that neurons derived from patient-specific iPSCs can recapitulate, at the cellular level, a typical disease phenotype of SCZD, which has strong and convoluted genetic risk factors.29 This study also demonstrated the alteration of the disease phenotype by an established anti-psychotic drug. Although neural cells alone are unlikely to perfectly model a complicated psychocognitive disease or fully reveal the side effects of anti-psychotics, a cellular model will nonetheless be useful for the early stage of discovery of novel, antipsychotic drugs. Amyotrophic lateral sclerosis. Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the loss of MNs.30 A number of genetic factors have been linked to ALS. For example, a subset of ALS patients carries mutations in the TARDBP gene, which generally leads to aggregation of TAR DNAbinding protein-43 (TDP-43). 31 To recapitulate TDP-43-associated proteinopathies in vitro, Egawa et al. ACS Paragon Plus Environment

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generated iPSC lines from ALS patients (ALS-iPSC) with mutations in TARDBP. 32 From these lines, they derived neural populations containing MNs (ALS-MNs), which contained higher levels of detergent-insoluble TDP-43 aggregates (Table 1). They also found that these cells expressed lower levels of medium polypeptide neurofilament (NEFM), similar to that observed in the spinal motor neurons from ALS patients.33 The authors further challenged these cells with arsenite, which is widely used to model oxidative stress associated with ALS, and then screened the cells for compounds that protect them from the oxidative stress. They found that anacardic acid improved survival, reduced insoluble TDP-43, and increased NEFM expression in ALS-MNs (Table 1). These findings suggest that an MN survival assay could be used to evaluate therapeutics for ALS. Similarly, Yang et al. established another survival assay in which MNs were subjected to stress induced by removing tropic factors from the culture medium (Table 1).34 They found that kenpaullone, a glycogen synthase kinase (GSK)-3β inhibitor, promoted the survival of both ALS-MNs and their control counterparts (Table 1). Interestingly, in the absence of additional stressors, Burkhart et al. established a screening assay based on readouts of TDP-43 aggregation in patient-derived MNs.35 They reprogrammed fibroblasts from three sporadicALS patients with unknown genetic etiology, one of whom was confirmed with TDP-43 pathology by autopsy. In contrast to control MNs, ALS-MNs stained positive for TDP-43 aggregates (Table 1). Burkhart et al. then set up an automated, imaged-based system to screen compounds for their effects on TDP-43 aggregates in ALSMNs. Out of 1757 compounds, 38 reduced the percentage of cells positive for TDP-43 aggregates. This study demonstrated that even when the genetic cause and molecular basis of a disease are unknown, researchers can still rely on a phenotypic approach to search for therapeutics. Furthermore, it supports that a high-throughput system that screens for phenotypic drugs can be built upon a platform provided by patient-derived iPSCs. Glutamate-induced excitotoxicity has been implicated to damage the MNs in ALS patients. 36 Improperly stimulated, hyperexcited MNs fire excessively and die. 37 Wainger et al. successfully recapitulated the hyperexcitability of ALS-MNs in vitro (Table 1).38 They derived MNs from ALS patients with three separate genetic etiologies and employed multielectrode arrays (MEAs) to monitor the firing of MNs and the currents generated by MNs. MEAs recorded higher spontaneous firing rates of all three classes of ALS-MNs than MNs derived from control donors. The hyperexcitability of ALS-MNs was rigorously confirmed in whole-cell ACS Paragon Plus Environment

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patch-clamp assays, which recorded greater number of action potentials generated by ALS-MNs (with SOD1 mutations) than control MNs during ramp depolarization. With the whole-cell patch-clamp technique, Wainger et al. recorded decreased amplitude of the outward delayed-rectifier potassium current generated by the ALSMNs with SOD1 (A4V/+) mutation compared to the genetically corrected controls. Retigabine (an anticonvulsant) and flupirtine (an analgesic), both known to open the voltage-gated potassium channel Kv7, were found to prevent ALS-MNs from exhibiting hyperexcitibility (Table 1). Retigabine also partially rescued the death of ALS-MNs with SOD1 mutations. This study not only uncovered that potassium channel openers can protect MNs from excitotoxicity in familial ALS, it also demonstrated that electrophysiological behaviors of neurons can be useful phenotypes for PDD. Parkinson’s disease. Parkinson’s disease (PD) is characterized by motor symptoms and dementia and is the second-most common neurodegenerative disorder. 39 Although drugs that effectively control Parkinsonian symptoms already exist, their side effects still warrant new and more effective therapeutics.40 PD involves a major loss of dopaminergic (DA) neurons and damage to non-DA neurons.41 Mitochondrial dysfunction42 and oxidative stress43 have also been implicated as major contributors to PD pathogenesis. While most cases of PD are sporadic, a number of genetic factors have been linked to familial PD (fPD).44 To study PD, Copper et al. generated iPSC-derived neural cells from patient donors harboring mutations in PINK or LRRK2, which have been associated with fPD. These cells displayed changes in mitochondrial function and were more vulnerable to mitochondrial toxins, such as valinomycin and concanamycin A (Table 1). 45 Coenzyme Q10 (CoQ10), rapamycin, and 3-(3,5-Dibromo-4-hydroxy-benzylidene)-5-iodo-1,3-dihydro-indol-2one (GW5074, Figure 2)45 protected against the effects of mitochondrial toxins on these neural cells; however, the exact cellular responses varied depending on the mutations, toxins, and rescue agents (Table 1). Nonetheless, this study supports that therapeutics that rescue dysfunctional mitochondrial phenotypes may benefit patients suffering from PD. Another group applied targeted gene editing and cell reprogramming to establish a number of cellular phenotypes of PD caused by the LRRK2 (G2019S) mutation. 46 Here, Reinhardt et al. generated iPSC lines carrying the LRRK2 (G2019S) mutation and differentiated them into midbrain DA neurons. They then ACS Paragon Plus Environment

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corrected the mutation in these lines to create the corresponding isogenic controls. They also generated a wildtype iPSC line and an isogenic, gene-edited line with targeted insertion of mutant LRRK2. In the midbrain DA (mDA) neurons differentiated from these iPSC lines, the authors clearly identified a number of PD-associated biomarkers induced by the LRRK2 (G2019S) mutation (Table 1). They also confirmed that mutant LRRK2 produced PD-associated cellular phenotypes that were previously reported, such as shortened neurites, defective autophagy, increased sensitivities to neurotoxins, and elevated oxidative stress. They also observed increased levels of pathological markers of PD, such as tau protein, phosphorylated tau (p-tau), and alpha-synuclein (αSyn), in mDA neurons expressing mutant LRRK2. They then profiled the gene expression in these neurons and found that mutant LRRK2 upregulated novel genes. To confirm the contributions of these genes, the authors knocked them down while inducing oxidative stress to the mDA neurons by withdrawing the B27 supplement, and/or exposing the cells to the Parkinsonian neurotoxin rotenone. They found that knocking down these genes improved the survival of mutant mDA neurons under stresses, implicating that these genes could be new therapeutic

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pharmacologically inhibiting the phosphorylation of extracellular signal-regulated kinase (ERK) and/or the LRRK kinase ameliorated the DA neurons’ increased vulnerabilities to oxidative stress and neurotoxins (Table 1). This study highlights that by combining targeted gene editing and cell reprogramming, researchers can more easily establish reliable disease phenotypes, elucidate the genetic and/or molecular contributors to a disease, and, ultimately, search for novel therapeutic strategies and agents. α-Syn is a strong contributor to PD, which is largely influenced by nitrosative stress. 47 ,48 Chung et al. confirmed that nitrosative stress correlates with α-Syn toxicity in both yeast and rat models involving cortical neurons.49 Based on these findings, they developed an iPSC-based assay to screen for compounds that rescue αSyn toxicity. They obtained neurons differentiated from iPSCs derived from PD patients (PD-neurons) harboring SNCAA53T and from isogenic, mutant-corrected iPSCs. Using a copper complex as a fluorescent-based sensor, they confirmed that the intraneuronal nitric oxide (NO) level was higher in PD-neurons compared to isogenic controls, indicating that mutant SNCA induces α-Syn toxicity (Table 1). They also showed that N-(2chlorobenzyl)-1-(2,5-dimethylphenyl)-1H-benzo[d]imidazole-5-carboxamide (NAB2), ACS Paragon Plus Environment

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found to rescue yeast from α-Syn toxicity, reduced the NO level in PD-neurons (Table 1). This study is an inspiring example of creating robust and disease-relevant cellular phenotypes suitable for screening drugs. Table 1. Compound Screening in Neurological Diseases With Patient iPSC-based Cell Models Disease Genetic etiology DiseaseDisease-relevant Rescue agent(s) relevant phenotype(s) cells FD IKBKAP mutations NC Decreased expression of Kinentin; SKF-86466; precursors WT IKBKAP compared to Yohimbine MU IKBKAP; reduced neurogenesis SMA SMN1 mutations iPSCs Reduced SMN protein VPA; Tobramycin RTT MECP2 mutations Neurons Reduced number of Gentamicin glutamatergic synapses MJD Expanded CAG Neurons Fragmentation and Caspase inhibitors; repeats in MJD1 aggregation of ataxin-3 Calpine inhibitors; EDTA; D-APV; NBQX; Tetrodotoxin SCZD Undetermined Neurons Reduced neuronal Loxapine connectivity TARDBP MNs Increased cell death Anacardic acid mutations SOD1 (L144F); MNs Increased cell death Kenpaullone TARDBP (M337V) ALS Undetermined MNs Intracellular TDP-43 Digoxin; Lanatoside C; aggregation Proscillaridin A, etc. SOD1 mutations; MNs Hyperexcitability; Retigabine; Flupirtine C9orf72 mutations; increased cell death FUS mutations PINK (Q456X); Neural cells Increased cell death CoQ10; GW5074; LRRK2 (G2019S); Rapamycin LRRK2 (R1441C) PD LRRK2 (G2019S) mDA Increased apoptosis; LRRK2-IN-1; neurons increased phosporylated PD0325901 ERK1/2 SNCA (A53T) Neurons Increased NO production NAB2 PSEN1 (A246E); Neurons Increased Aβ42 / Aβ40 Compound E PSEN2 (N141I) ratio APP (Dp) Neurons Increased p-tau/t-tau; β-Secretase Inhibitor fAD activated GSK-3β II; OM99-2 APP (E693) Neurons Elevated Aβ oligomers, β-Secretase Inhibitor BIP, PRDX4, ROS; IV; DHA cleaved caspase-4

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Alzheimer’s disease. Alzheimer’s disease (AD) is characterized by progressive dementia and cognitive deficits and is the most prevalent neurodegenerative disorder. Yet, there is still no effective treatment for this


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devastating disease,51 and its multifactorial pathogenesis has yet to be fully elucidated.52 Familial AD (fAD) is caused by mutations in PSEN1, PSEN2, and APP,53 while sporadic AD (sAD)—the more common form—has been linked to a prominent genetic risk factor, APOE, although patients with sAD are genetically heterogeneous. Unfortunately, modeling sAD in vitro is also confounded by the complex genetic and environmental factors that contribute to the disease. Despite these challenges, researchers have identified and validated a number of molecular hallmarks of AD pathology, paving the way for modeling phenotypes of AD and discovering drugs that combat the disease.54 Below, we will describe several studies that have illustrated the possibility of using neurons generated from patient-derived iPSCs to recapitulate and pharmacologically alter the pathological features of AD. In fAD, mutations in PSEN1 and PSEN2 lead to increased production of β-amyloid (Aβ) peptides.55 These peptides are secreted from neurons and aggregate to form pathological fibrils and plaques in the brain, a known pathogenetic mechanism of AD. The 42-amino-acid Aβ peptide (Aβ42) is more prone to aggregate and, therefore, more toxic than the most abundant 40-amino-acid form (Aβ40). The ratio of Aβ42 to Aβ40 has been used as a biomarker for AD. For example, Tagi et al. observed that Aβ42/Aβ40 ratios increased in the medium of iPSC-derived neurons from the fAD patients (fAD-neurons) (Table 1),56 and were dose-dependently reduced by the γ-secretase inhibitors Compound E and Compound W (Table 1). Another prominent pathological feature of AD involves neurofibrillary tangles composed of p-tau.57 Indeed, an important biomarker for AD is an increased ratio of p-tau to total tau (t-tau). In a cellular model of AD, Israel et al. recapitulated elevated p-tau in neurons differentiated from iPSCs derived from patients carrying a duplication of the APP gene, aka APP (Dp).58 Compared to control neurons derived from healthy donors, the fAD-neurons secreted more Aβ, maintained a higher p-tau/t-tau ratio (Table 1), and expressed more activated GSK-3β, a kinase that phosphorylates tau. The authors also found that while both β-secretase inhibitors (βSecretase Inhibitor II, OM99-2) and γ-secretase inhibitors (Compound E, DAPT) suppressed Aβ secretion in fAD-neurons, only β-secretase inhibitors reduced the p-tau/t-tau ratio and the level of activated GSK-3β (Table 1). In this same study, Israel et al. also generated iPSC-derived neurons from two sAD patients (sAD-neurons).


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Interestingly, sAD-neurons from only one patient exhibited increased Aβ, p-tau/t-tau, and activated GSK-3β, implicating disease heterogeneity between these patients. H N O Br

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Figure 2. Kondo et al. reported a study in which they modeled a rare case of fAD with an APP (E693) mutation.59 AD patients with this particular mutation exhibit early-onset symptoms without Aβ deposits; however, the APP (E693) mutation gave rise to a special form of Aβ that is prone to oligomerize. In their study, Kondo et al. established relevant disease biomarkers and demonstrated the possibility of alleviating these phenotypes in neurons. Here, the authors generated fAD-neurons from patients with APP (E693) and confirmed their elevated levels of intracellular Aβ oligomers with specific antibodies (Table 1). In these fAD-neurons, they found elevated levels of four biomarkers associated with endoplasmic reticulum (ER) stress, including binding immunoglobulin protein (BIP), peroxiredoxin-4 (PRDX4), reactive oxygen species (ROS), and cleaved caspase4. These findings implicate that Aβ oligomers contribute to fAD pathology. When the fAD-neurons were ACS Paragon Plus Environment

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treated with β-Secretase Inhibitor IV, these biomarkers decreased as Aβ oligomers gradually disappeared (Table 1). Interestingly, docosahexaenoic acid (DHA) reduced the biomarkers of ER stress without changing the amount of Aβ oligomers (Table 1). The studies on fAD discussed above clearly demonstrate that patient-derived iPSCs are excellent platforms for the modeling of this disease with well defined genetic causes. Established pathological hallmarks of AD can serve as valuable phenotypic readouts in cellular models. CARDIAC DISEASE Primary human CMs are difficult to obtain in adequate quantities and maintain in vitro for a long period. Fortunately, with advanced iPSC technology and differentiation methods, human CMs can now be obtained in large quantities from iPSC (iPSC-CMs).60 Human CMs display unique electrophysiological characteristics, such as beating and ion-channel activities, which can be conveniently evaluated by well-developed techniques, including multi-electrode arrays and patch-clamp recordings. Based on their availability and the technical convenience to monitor their behaviors, iPSC-CMs have served as useful surrogates to model heart disease in vitro and discover potential drugs to treat it.61 Since an early study of LEOPARD syndrome in 2010,62 many researchers have focused on modeling heart disease in vitro with patient-derived iPSC-CMs.61,63 Additionally, researchers have used iPSC-CMs to screen cardiotoxicities related to pharmaceuticals in drug development. 64,65 For the purpose of this article, we will focus on the significant progress made in modeling cardiac disorders with patient-specific iPSC-CMs. We will also highlight examples that replicate and pharmacologically alleviate the phenotypes of these disorders at a cellular level. Long QT Syndrome. Heart function largely depends on its electrical activity, which can be measured by electrocardiogram. When evaluating the heart’s electrical cycle with this approach, the QT interval is the time between the start of the Q wave and the end of the T wave, which represents the time needed for electrical depolarization and repolarization of the ventricles. An abnormally prolonged QT interval indicates an increased risk of arrhythmia that may cause sudden cardiac death. Inherited long QT syndrome (LQTS) is a genetically ACS Paragon Plus Environment

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heterogeneous disorder mainly caused by mutations in genes that encode critical subunits of the cardiac ionchannels that orchestrate cardiac action potentials.66 In patients with inherited LQTS, dysfunction of these ion channels prolongs action potential duration (APD) in CMs, which underlies the abnormal electrical activities in LQTS hearts.67 LQTS Type 1 and Type 2 (LQT1 and LQT2) are characterized by a prolonged ventricular repolarization and a propensity to arrhythmias. They are caused by mutations in KCNQ1 and KCNH2, respectively, both of which encode for cardiac potassium (K+) channels.66 The iPSC-CMs derived from LQT1 and LQT2 patients showed longer APD, reduced the delayed rectifier K+ current (IKr (rapid) or IKs (slow)), and developed arrhythmias after β-adrenergic stimulation (Table 2).68,69,70 These abnormal effects were reversed after treating cells with either a β-blocker (propranolol), an ATP-sensitive K+-channel (KATP) opener (pinacidil), or an experimental K+-channel opener (2-[[4-[2-(3,4-Dichlorophenyl)ethyl]phenyl]amino]benzoic acid (PD118057), Figure 2) 69 (Table 2). LQTS Type 3 (LQT3) is caused by gain-of-function mutations in SCN5A, which encodes the cardiac sodium (Na+) channel.66 iPSC-CMs from patients carrying a hereditary missense mutation in SCN5A replicated the disease phenotypes, including prolonged APD and aberrant behaviors of Na+-channel gating (Table 2). 71,72 These abnormal functions can be ameliorated by mexiletine, a Na+-channel blocker and anti-arrhythmic drug (Table 2). LQTS Type 8 (LQT8), or Timothy syndrome, is induced by a missense mutation in the gene CACNA1C, which encodes the L-type Ca2+ channel CaV1.2 in humans.73 LQT8 is a rare congenital disorder that often causes death in early childhood. Yazawa et al. modeled this disease with iPSC-CMs generated from patients with Timothy syndrome, and then recapitulated the disease phenotypes in vitro. 74 Indeed, they observed prolonged APD, excess Ca2+ influx, irregular contraction, and impaired Ca2+-channel gating in these iPSC-CMs (Table 2). They also rescued these phenotypes with roscovitine, a cyclin-dependent kinase (CDK) inhibitor that enhances CaV1.2 signaling (Table 2). Overall, LQTS is the most studied cardiac disease using patient-derived iPSC-CMs. Although iPSC-CMs in the dish are more similar to fetal CMs rather than adult CMs, these studies have demonstrated that iPSC-CMs


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can model LQTS and predict drug’s response in vitro. iPSC-CMs therefore represent a distinctive platform to understand the mechanisms and discover drugs to treat LQTS. Table 2. Modeling Cardiac Diseases and Screening Compounds with iPSC-derived Cardiomyocytes from Diseased Patients Disease Genetic etiology Disease-relevant Rescue agent(s) References phenotypes LQT1

KCNQ1 (R190Q)

LQT2

KCNH2 (G1681A)

LQT3

KCNH2 (A614V) SCN5A (F1473C) SCN5A (V1763M)

LQT8 (Timothy CACNA1C syndrome) (G406R)

Prolonged APD; reduced IKs current; increased susceptibility with βadrenergic stimulation Prolonged APD; increased susceptibility to arrhythmogenic chemicals Prolonged APD; reduced IKr current; arrhythmias Prolonged APD; aberrant Na+ channel gating Prolonged APD; irregular behaviors of Na+ channel gating Prolonged APD; irregular behaviors of Ca2+-channel gating Irregular Ca2+ signaling; increased susceptibility to DADs and arrhythmia

CPVT1

RYR2 (S406L); RYR2 (M4109R)

DCM

TNNT2 (R173W) Decreased contractility; aberrant Ca2+ signaling; abnormal distribution of sarcomeric α-actinin MYH7 (R663H) Enlarged cell; contractile arrhythmia; aberrant Ca2+ homeostasis

HCM

Barth syndrome

TAZ (517delG); TAZ (T328C)

Diabetic Undetermined Cardiomyopathy

Mitochondrial dysfunction; abnormal organization of sarcomeres; impaired contractile function Cellular hypertrophy; sarcomeric disarray; altered Ca2+ transient; increased arrhythmia and oxidative stress

Propranolol

68

Propranolol; Nadolol; Nicorandil; PD118057

69

Nifedipine; Pinacidil; Ranolazine Mexiletine

70 71

Mexiletine

72

Roscovitine

74

Dantrolene; Flecainide; Thapsigargin; Propranolol

75, 76

Metoprolol

78

Propranolol; Verapamil; Nifedipin; Diltiazem; Lidocaine; Mexiletine; Ranolazine Linoleic acid; mitoTEMPO

81

28 compounds, including fluspirilene and thapsigargin

85


84

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Catecholaminergic polymorphic ventricular tachycardia. Catecholaminergic polymorphic ventricular tachycardia type 1 (CPVT1) can cause ventricular arrhythmias and sudden cardiac death in young people.75 CPVT1 is a familial disorder caused by mutations in the gene RYR2 that encodes the cardiac ryanodine–receptor channel that handles the storage of Ca2+ in the sarcoplasmic reticulum (SR). The mutation in the RYR2 gene causes an irregular concentration of diastolic Ca2+ in CMs. Two research groups generated iPSC-CMs from CPVT1 patients and then challenged them with the adrenergic agonist isoproterenol to successfully recapitulate CPTV1 phenotypes in vitro,75,76 such as elevated concentrations of diastolic Ca2+, an increased propensity to delayed afterdepolarizations (DADs), and arrhythmia (Table 2). These phenotypes were abolished by compounds such as dantrolene and flecainide, and completely rescued by thapsigargin, a potent intracellular Ca2+ releaser (Table 2). Thus, cardiomyocytes derived from iPSCs isolated from CPVT1 patients could provide an approach for researchers to discover effective therapeutics for this disease. Dilated cardiomyopathy. Cardiomyopathies are disorders linked to impaired structure and function of heart muscle that result in heart failure or sudden cardiac death.77 The most common form of cardiomyopathy is dilated cardiomyopathy (DCM), which is characterized by left ventricular dilatation and global systolic dysfunction. In a family with inherited DCM, researchers discovered a point mutation in the gene TNNT2 that encodes the sarcomeric protein cardiac troponin T. 78 They then derived iPSC-CMs from patients of this family, which exhibited reduced contractility, abnormal sarcomeric organization, aberrant Ca2+ flux, and increased susceptibility to stress compared to control iPSC-CMs derived from healthy individuals (Table 2). Interestingly, these phenotypes were ameliorated by the clinical drug metoprolol, a β-adrenergic blocker (Table 2). This study indicates that iPSC-CMs could be used as a valuable platform for investigating DCM and for screening phenotypes while developing new drugs. Hypertrophic cardiomyopathy. Hypertrophic cardiomyopathy (HCM) is another type of hereditary cardiomyopathy that is estimated to be the most prevalent congenital heart dysfunction worldwide.79 HCM is caused by mutations in genes that encode proteins in the cardiac sarcomere. 80 These mutations lead to hypertrophic CMs with disorganized sarcomere structure and abnormal electrophysiological properties, ultimately leading to thickening of the myocardium of the left ventricle. Recently, Lan et al. generated iPSCACS Paragon Plus Environment

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CMs from HCM patients and studied the molecular mechanisms underlying the disease.81 Here, they generated iPSC-CMs from a ten-member family carrying a missense mutation (R663H) in the gene MYH7. These iPSCCMs replicated many phenotypes of the disease, including enlarged cell bodies, contractile arrhythmias, and aberrant Ca2+-handling activities (Table 2). CMs derived from human ESCs overexpressing the mutant MYH7 exhibited similar abnormal Ca2+ transients and arrhythmias, confirming the significance of this particular mutation to HCM. Importantly, with a pharmaceutical screen for clinical drugs, researchers found that either βadrenergic blockers (e.g., propranolol) or Ca2+-channel blockers (e.g., verapamil) can abolish cellular abnormalities in patient-derived iPSC-CMs, validating that Ca2+ homeostasis affects the development of HCM at the cellular level (Table 2). These findings support that iPSC-CMs can be effectively used to elucidate the pathophysiology of cardiomyopathy and screen for drug candidates that target this disease. Barth syndrome. Barth syndrome (BTHS) is a multi-system mitochondrial myopathy mainly characterized by cardiac and skeletal dysfunctions.82 BTHS is caused by mutations in the gene TAZ, which encodes tafazzin, an acyltransferase responsible for the normal structure of cardiolipin, a key phospholipid protein in the inner membrane of mitochondria.

83

When TAZ is mutated, an immature form of cardiolipin, called

monolysocardiolipin, accumulates and causes structural and functional abnormalities of mitochondria. Recently, Wang et al. modeled BTHS disease with patient-derived iPSC-CMs.84 Consistent with the clinical manifestation of the disease, patient iPSC-CMs showed metabolic abnormalities caused by impaired mitochondrial function, contractile deficits, and elevated ROS in mitochondria despite normal ATP levels in the whole cell (Table 2). Importantly, the authors validated that the single mutation causes these disease phenotypes in CMs by combining state-of-the-art techniques in three independent approaches. They found that knocking down TAZ in primary neonatal rat CMs with shRNAs replicated abnormalities; transfecting BTHS iPSC-CMs with modified RNA that encodes wild-type TAZ rescued abnormalities; and performing targeted mutation of TAZ with Cas9 in control iPSC-CMs reproduced abnormalities. Furthermore, they found that they could correct cellular defects in sacomeric organization and function with either linoleic acid, a precursor of mature cardiolipin and ROS scavenger, or mitoTEMPO, a mitochondria-targeted ROS scavenger (Table 2). Therefore, these results strongly


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implicate that mitochondrial ROS is a critical intermediate that links TAZ mutations to cardiomyopathy, thereby providing new insights into the pathophysiology of BTHS with CMs derived from iPSCs. Diabetic cardiomyopathy. The cases using patient-specific iPSC-CMs for disease modeling and chemical screening discussed so far share several common characteristics: the diseases are usually monogenic disorders with known genetic causes; the etiologies of disease are congenital and symptoms are early-onset; and protocols to obtain CMs are available. Most cardiac disorders in newborns or adults, however, are polygenic, from complex origins, and late in onset. Therefore, researchers would benefit from iPSC-CM models that recapitulate these more complicated disorders. Drawnel et al., from the pharmaceutical company Roche, showed that these complex disorders could be modeled with iPSC-CMs in vitro. 85 In their report, they studied diabetic cardiomyopathy, which develops from metabolic dysfunction in diabetes and progresses to DCM and heart failure. It is the leading cause of death in people with type 2 diabetes mellitus (T2DM). Despite the tremendous need, there is no cure or specific treatment available for diabetic cardiomyopathy, because of its complex pathology and the lack of practical assays for drug discovery. To model this disease, researchers need CMs with higher maturity. Drawnel et al. developed a maturation medium (MM) by adding insulin and fatty acids to standard medium. When CMs were cultured in this MM, they showed more matured phenotypes, such as upregulated expression of α-actinin, a contractile marker that represents mature sarcomeric integrity. After incubating MM-treated CMs in a diabetic milieu (DM) containing glucose and two diabetic stressors, endothelin 1 and cortisol, matured CMs produced from normal iPSCs displayed structural and functional abnormalities similar to that seen in diabetic cardiomyopathy, such as sarcomeric disarray, increased oxidative stress, and arrhythmia (Table 2). These phenotypes were confirmed in iPSC-CMs generated from T2DM patients. When the patient-derived iPSC-CMs were incubated in only the MM condition without glucose and diabetic stressors, they exhibited similar disease phenotypes as healthy CMs cultured in DM medium. Based on these findings, the authors successfully reproduced diabetic cardiomyopathy in vitro with iPSC-CMs by either environmentally or genetically driven models. With these cells, the authors completed a high-content phenotypic screen of 480 compounds using several screenable readouts, i.e. the levels of actinin-α, the size of the cell nucleus and the production of B-type natriuretic peptide. Of these, 28 dose-dependently improved the ACS Paragon Plus Environment

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outcome of the disease phenotypes (Table 2). These results implicate that iPSC-CMs can model disorders with unknown genetic bases and complex origins, which can be used as a powerful platform for PDD. OTHER DISEASES Since iPSC technology emerged, it has enabled researchers to model a number of diseases in vitro. Below, we will summarize recent progress in hepatic, hematological, and skeletal diseases, with a particular focus on designing phenotypic cell assays and chemical screens. Hepatic Disease. A few research groups have developed patient-derived HCs from iPSCs (iPSC-HCs) to recapitulate phenotypes and reflect pharmalogical responses in vitro for a variety of liver diseases. 86 For example, Wilson’s disease (WD) is caused by mutations in the liver transport gene ATP7B, which results in progressive liver damage caused by an accumulation of copper ions (Cu2+) in HCs.87 Zhang et al. generated iPSC-HCs from a WD patient (WD-HCs), 88 which showed abnormal cytoplasmic localization of mutated ATP7B protein and defective Cu2+ transport when compared with primary human HCs (Table 3). These phenotypes were partially reversed by a natural product, curcumin. Another group evaluated α-1 antitrypsin deficiency (AATD), a condition characterized by accumulation of misfolded α-1 antitrypsin (AAT) in HCs.89 Here, the authors optimized a procedure to differentiate HCs from patient iPSCs and screened phenotypes based on the intracellular levels of the AAT protein. In a library of 2,800 clinical chemicals (FDA-approved or passed a phase 1 clinical trial), the authors identified five compounds as promising hits, which each showed positive effects in many iPSC-HCs lines (Table 3). Because these compounds have already been used in clinical trials, they can bypass the early stages of drug discovery and potentially be repositioned as drugs to treat hepatic diseases. This study provides a good example of how to align iPSC technique in PDD. Hematological Disease. Shwachman-Diamond syndrome (SDS) is an inherited pediatric disorder characterized by hematologic abnormalities and exocrine pancreatic insufficiency. SDS is caused by mutations in the SBDS gene,90 which reduces expression of SBDS protein in patients; however, the link between mutations in SBDS and pathology within the hematopoietic and pancreatic lineages remains unknown. Tulpile et al. modeled SDS by obtaining iPSCs from patients with SDS (SDS-iPSCs). 91 They overexpressed normal SBDS protein in these lines to create gene-corrected controls. When differentiated into target cells, SDS-iPSCs, but ACS Paragon Plus Environment

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not gene-corrected controls, showed the defects of hematopoietic and pancreatic differentiation observed in patients (Table 3). The authors also compared the cellular phenotypes and biochemical features of culture medium and found that elevated protease levels that kill myeloid and pancreatic-acinar cells was a molecular mechanism of SDS. Aprotinin, a protease inhibitor, effectively rescued the abnormalities in culture (Table 3). This work demonstrates the potential impact of iPSCs for modeling disease and discovering pharmacological methods to target the disease mechanism. In another study, Liu et al. modeled Fanconi anaemia (FA) with iPSCs.92 FA is caused by mutations in any of the 16 FANC genes and is characterized by genomic instability, progressive failure of bone marrow, and endocrine defects.93 FA cells have defective mechanisms to repair DNA and are genomically unstable, which creates challenges in generating iPSCs from FA patients, even under fine-tuned conditions such as hypoxia.94 Nevertheless, Liu et al. reprogrammed iPSCs from FA-patient fibroblasts with a FANCA mutation (FA-iPSCs) with an integration-free method. These cells recapitulated FA defects at the cellular level, such as defective abilities of DNA repair and hematopoietic differentiation (Table 3). Importantly, the authors validated that the FANCA mutation caused the cellular abnormalities in two independent lines of isogenic cells: targeted correction of FANCA gene in FA-iPSCs reversed defects and precise mutation of FANCA gene in human ESCs resulted in similar defects. Interestingly, to further explore the pathology of FA, they differentiated two types of adult stem/progenitor cells from FA iPSCs, i.e. mesenchymal stem cells (MSCs) and neural stem cells (NSCs), which manifested various abnormalities. For example, MSCs showed characteristics of premature senescence, which might represent part of the molecular mechanism of the disease. In addition, several compounds were identified as hits that can promote hematopoietic differentiation of FA-iPSCs (Table 3), which validates the model as a valuable platform for small-molecule screening. Skeletal Disease. Marfan syndrome (MFS) is a heritable connective–tissue disorder caused by a mutation in the FBN1 gene, which encodes fibrillin-1, an extracellular matrix protein.95 Quarto et al.96 modeled MFS by generating iPSCs from MFS-patient dermal cells (MFS-iPSCs) and found that these cells manifested impaired osteogenic differentiation in vitro because of an enhanced transforming growth factor (TGF)-β signaling (Table 3). This finding was supported by results showing that a TGF-β signaling inhibitor (4-[4-(1,3-benzodioxol-5ACS Paragon Plus Environment

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yl)-5-pyridin-2-yl-1H-imidazol-2-yl]benzamide (SB-431542), Figure 2)96 rescued the deficits of skeletogenesis in MFS-iPSCs, while a BMP-signaling inhibitor (noggin) did not. Fibrodysplasia ossificans progressiva (FOP) is a rare, but debilitating, genetic disease caused by hyperactive mutations in ACVR1 gene.97 It has also been modeled by reprogramming patient fibroblasts into iPSCs (FOPiPSCs).98 Activating the ACVR1 gene leads to increased mineralization that causes abnormal endochondral bone formation in patient’s soft tissues. Remarkably, FOP-iPSCs similarly exhibited enhanced mineralization and increased chondrogenesis in vitro compared to healthy controls (Table 3). Interestingly these disease phenotypes were blocked by DMH1, a small-molecule inhibitor of BMP signaling, which could be interesting for further drug development for this disease. Table 3. Modeling Miscellaneous Diseases and Screening Compounds with Patient iPSCs or iPSC-derived Cells Disease-relevant Rescue molecule(s) Referenc Disease Genetic etiology Diseaserelevant cells phenotypes es WD

ATP7B (R778L)

HCs

AATD

AAT (E342K)

HCs

SDS

SBDS mutations

iPSCs

FA

FANCA mutations

iPSCs

MFS

FBN1 (G 3839– iPSCs 1T); FBN1 (1642del3ins20b p) ACVR1 (R206H) iPSCs

FOP TD1; ACH

FGFR3 (R248C); FGFR3 (G380R)

iPSCs

Irregular cellular localization of mutated ATP7B; aberrant Cu2+ transport Intracellular accumulation of misfolded mutant α1antitrypsin

Curcumin

88

Carbamazepine; Lithium salt; Valproic acid; Glipizide; Thiamine

89

Impaired abilities of hematopoietic and pancreatic differentiation Defective abilities of DNA repair and hematopoietic differentiation Impaired ability of osteogenic differentiation

Aprotinin

91

Doramapimod; Tremulacin

92

SB-431542

96

DMH1

98

Statins

99

Enhanced chondrogenesis; increased mineralization Impaired ability of Chondrogenic differentiation

Recently, Yamashita et al. studied the skeletal disorders of achondroplasia (ACH) and thanatophoric


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dysplasia type 1 (TD1) and provided another good example of how to use iPSCs to model bone disease and reposition drugs.99 Both ACH and TD1 are caused by gain-of-function mutations in the gene FGFR3, 100 which encodes a transmembrane tyrosine receptor. When FGFR3 protein accumulates, it affects downstream pathways to suppress the differentiation and proliferation of cartilage cells, chondrocytes. Similarly, the authors found that iPSCs derived from patients showed higher expression of FGFR3 protein compared with control iPSCs. Importantly, the patient-derived iPSCs manifested abnormal cartilage formation when differentiated towards chondrocytes, and displayed decreased proliferation and increased apoptosis after chondrogenic differentiation, which well recapitulated the abnormalities of the diseases in vitro (Table 3). Treating patient iPSCs with statins, such as lovastatin, led to degradation of mutated FGFR3 protein and restored normal chondrogenic differentiation (Table 3). Notably, statins also promoted bone growth in a mouse model that harbored the ACH mutation, but not wild-type mice. Despite these encouraging findings, extensive evaluation is still needed before using statins to treat the skeletal dysplasias in patients, particularly children, because statins inhibit cholesterol, which is critical for development. The results of this study demonstrate that iPSCs can effectively model skeletal disorders and support chemical screening in the search for clinical drugs. SUMMARY AND OUTLOOK Since its discovery, the technique for cell reprogramming has continued to improve and support growing applications of human iPSCs in disease modeling and PDD. For example, non-integrative approaches have enabled researchers to generate transgene-free iPSCs that are genetically identical to their donors—a significant advantage for building cell models.101 Nonetheless, a number of technical challenges need to be overcome to unleash the great potential of human iPSCs in disease modeling and drug discovery (Table 4).102 Many disease-relevant cell types are currently inaccessible through the directed differentiation of iPSCs. Fortunately, the toolbox of cell reprogramming and cell differentiation will continue to expand, thereby increasing the varieties of cells types accessible. As illustrated by a number of studies previously discussed, even in cases where researchers cannot easily obtain a specific cell type affected by a disease, they can rely on the readily available patient-derived iPSCs to model the disease, provided that the iPSCs exhibit the diseaserelevant phenotypes responsive to pharmacological treatments. ACS Paragon Plus Environment

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Many existing methods for the differentiation of human iPSCs are still complex, laborious, and costinefficient. Sub-optimal differentiation methods often generate heterogeneous cellular compositions which can impede the investigation of a specific cell type of interest. Some current differentiation methods can only produce immature cells that inadequately resemble the functional, mature cells in the human body.103 Improved methods for cell differentiation and/or cell culturing may overcome these obstacles that restrict the application of human iPSCs. For example, a recent study reported that highly pure CMs in good yields can be produced from human iPSCs in simple, chemically defined conditions.104 Table 4. Current Limitations of Human iPSC-based Cell Models and Emerging Solutions Current limitations

Emerging solutions

Limited, inefficient differentiation methods to Invention produce

disease-relevant

cells;

and/or

improvement

of

heterogeneous differentiation protocols and/or cell culture

compositions of differentiated cells; immaturity of conditions target cells Confounding variations in genetic background Targeted genome editing technology among cell sources Difficulties in modeling disorders without a strong Proper genetic background

pathogenic

stimuli

to

induce

phenotypes

Difficulties in modeling disorders at the tissue level 3D organoid models

Patient-derived iPSCs retain the genetic predispositions of the diseases of interest and are particularly useful for studying disorders with strong genetic components. By comparing patient-derived cells with control cells derived from healthy donors, researchers can identify disease-related phenotypes; however, they must consider that the difference in phenotypes may be an artifact that merely reflects the genetic heterogeneity among donors. Fortunately, isogenic control cells can be created by genetically correcting patient-derived iPSCs with targeted genome editing techniques. This approach can help researchers easily identify phenotypes caused by the


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disease-related mutations. Alternatively, researchers can introduce precise mutations into iPSC lines through targeted genome editing so that the exact contributions of a genetic risk factor can be stringently evaluated. Thus, targeted genome editing can uniquely tailor human iPSCs and will continue to be widely used to create cell models of diseases.105 By understanding the pathophysiology underlying diseases, researchers can apply effective strategies that evoke and/or enhance disease-relevant phenotypes in cell models and, hopefully, discover drugs by phenotypic screening.106 In many studies discussed above, disease-relevant phenotypes were induced by pathogenic stresses, which could be used to recapitulate the phenotypes of diseases that are linked with age, environmental factors, and/or epigenetic components. Future efforts may build on three-dimensional (3D), organoid models with in vitro cell cultures, an important field where human iPSCs have already set firm roots.107 Researchers have already generated 3D cardiac tissues from human iPSCs that successfully model the human heart.108 Recently, they also developed organoids with iPSCs that mimic the cerebrum. 109 Compared with conventional two-dimensional cell cultures, 3D models incorporate the spatial and structural features of tissues and/or organs affected by diseases and thereby could reveal more relevant information. For example, one study recapitulated the pathological phenotypes of AD with a 3D model.110 Here, the authors used a 3D culture of neurons that presumably better resembled the structural and pathophysiological microenvironment in a brain affected by AD. With this model, they showed, for the first time in a disease model of AD, the causative link between Aβ pathology and tauopathy. These findings support that researchers will continue to develop effective 3D models to reveal more relevant disease mechanism.111 Cell models are widely used to model diseases and elucidate their mechanisms, which benefits PDD. After validating the pathophysiology of a disease with these cell models, researchers can then select relevant and robust phenotypic readouts for specific drug screening assays. Strategies and methods to design cell-based, high-throughput screening assays have been comprehensively reviewed elsewhere.112 PPD is useful not only for finding therapeutically useful entities, but also for exploring disease mechanisms. For example, researchers can use compounds with established biological functions to tested phenotypic, cellular models to learn the mechanisms and/or drug targets in diseases. When novel compounds without known functions are discovered ACS Paragon Plus Environment

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in phenotypic assays, researchers can use them to identify their molecular target(s) and potentially uncover new insights into the disease of interest.113 In summary, human iPSCs supply ample cells as fundamental tools for researchers to study diseases. By coupling patient-derived iPSCs with techniques such as targeted genome editing, researchers have drastically enhanced their ability to build in vitro models of diseases and investigate their mechanisms. These models can also be used for cell-based, phenotypic assays to discover drug candidates, and, hopefully, lead to the discovery and development of drugs that effectively treat or cure devastating diseases.

AUTHOR INFORMATION Corresponding Author *Phone: (415) 734-2717. Fax: (415) 355-0141. E-mail: [email protected]. Author Contributions †

S.T. and M.X. contributed equally to this Perspective.

Notes The authors declare no competing financial interest. Biographies Shibing Tang received his B.Sc. in Chemistry from Jilin University in 2006 and his Ph.D. in Organic Chemistry from Lanzhou University in 2011. Since 2011, he has been a postdoctoral fellow at the Gladstone Institutes under the supervision of Prof. Sheng Ding. His current research focuses on discovering novel small molecules that control cell fates and functions, elucidating their molecular targets, and examining their therapeutic potential in disease models. Min Xie received his B.Sc. in Chemistry from Peking University in 2003. After obtaining his Ph.D. in Organic Chemistry from the University of Illinois at Urbana-Champaign in 2010, he joined Dr. Sheng Ding’s lab as a postdoctoral fellow. Currently at the Gladstone Institutes, he is participating in the discovery and preclinical development of small-molecule drugs for the treatment of cancers, neurodegenerative diseases, and metabolic diseases. ACS Paragon Plus Environment

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Nan Cao is currently a postdoctoral fellow at the Gladstone Institutes. He received his Ph.D. degree in Cell Biology from the Key Laboratory of Stem Cell Biology, Chinese Academy of Science. His research mainly focuses on conversion of non-cardiac cells into cardiac progenitors and/or cardiomyocytes by chemical strategies and exploring the underlying mechanisms. Sheng Ding is currently William K. Bowes, Jr. Distinguished Investigator and Professor at Gladstone Institutes, and Department of Pharmaceutical Chemistry, UCSF. He obtained his B.S. in chemistry from Caltech in 1999, and a Ph.D. in chemistry from The Scripps Research Institute in 2003. Before moving to Gladstone in 2011, Dr. Ding was an Assistant Professor and then Associate Professor of Chemistry at Scripps from 2003 to 2011. Dr. Ding has pioneered in developing and applying innovative chemical approaches to stem cell biology and regeneration, with a focus on discovering and characterizing small molecules that control cell fate/function, including stem cell maintenance, differentiation and reprogramming. Ding has published over 100 research articles and reviews, and made several seminal contributions to the stem cell field.

ACKNOWLEDGMENTS Sheng Ding is supported by funding from National Institute of Child Health and Human Development, National Heart, Lung, and Blood Institute, and National Eye Institute/National Institute of Health, California Institute for Regenerative Medicine, and the Gladstone Institutes. We thank Crystal Herron from the Gladstone Institutes for critical reading and editing of this manuscript. The authors apologize to all scientists whose research could not be properly discussed and cited in this review owing to space limitations. ABBREVIATIONS USED 3D, three-dimensional; α-Syn , alpha-synuclein; AAT, α-1 antitrypsin; AATD, α-1 antitrypsin deficiency; Aβ, β-amyloid; ACH, achondroplasia; AD, Alzheimer’s disease; ALS, Amyotrophic lateral sclerosis; APD, action potential duration; Aβ, beta-amyloid; BIP, binding immunoglobulin protein; BMP, bone morphogenetic protein; BTHS, Barth syndrome; CDK, cyclin-dependent kinase; CM, cardiomyocyte; CoQ10, Coenzyme Q10; CPVT1, catecholaminergic polymorphic ventricular tachycardia type 1; DA, dopaminergic; DAD, delayed ACS Paragon Plus Environment

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afterdepolarizations; DCM, dilated cardiomyopathy; DHA, docosahexaenoic acid; DM, diabetic milieu; ER, endoplasmic reticulum; ERK, extracellular signal-regulated kinase; FA, Fanconi anaemia; fA, familial Alzheimer’s disease; FD, familial dysautonomia; FOP, Fibrodysplasia ossificans progressive; fPD, familial Parkinson’s disease; GSK, glycogen synthase kinase; HC, hepatocyte; HCM, hypertrophic cardiomyopathy; iPSC, induced pluripotent stem cell; LQTS, long QT syndrome; LQT1, long QT syndrome type 1; mDA, midbrain dopaminergic; MEA, multielectrode array; MeCP2, methyl-CpG-binding protein 2; MFS, Marfan syndrome; MJD, Machado-Joseph disease; MM, maturation medium; MN, motor neuron; MSC, mesenchymal stem cell; MU, mutant; NC, neural crest; NEFM, medium polypeptide neurofilament; NO, nitric oxide; NSC, neural stem cell; PD, Parkinson’s disease; PDD, phenotypic drug discovery; polyQ, polyglutamine; PRDX4, eroxiredoxin-4; p-tau, phosphorylated tau; qRT-PCR, quantitative reverse transcription polymerase chain reaction; ROS, reactive oxygen species; RTT, Rett syndrome; sAD, sporadic Alzheimer’s disease; SCZD, schizophrenia; SDS, Shwachman-Diamond syndrome; SMA, Spinal muscular atropy; SMN, survival of motor neuron; SR, sarcoplasmic reticulum; t-tau, total tau; T2DM, type 2 diabetes mellitus; TD1, thanatophoric dysplasia type 1; TDD, target-based drug discovery; TDP-43, TAR DNA-binding protein-43; TGF, transforming growth factor; VPA, valproic acid; WD, Wilson’s disease; WT, wild-type

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Table of Contents graphic.

Treatment

Somatic cell reprogramming

Patient

Patient-specific iPSCs

Drugs

Directed differentiation

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Phenotypic drug discovery Cellular models of diseases


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Patient-Specific Induced Pluripotent Stem Cells for Disease

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