Blake Anson, PhDMarch 16, 2016
Symposium Session: Pat ient -
Speci f ic Stem Cel ls as Models for
Gene, Drug, and Environment
Interact ions in Disease
Use of Human iPSC-derived Cells as a Means to
Investigate the Relationship Between Genes and Disease
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Agenda and Disclaimer
I. The potential of iPSC technology and requirements for successful utilization
II. Case studies of IPSC use (and potential use) in understanding genetic factors underlying disease
Disclaimer:
The speaker is an employee of Cellular Dynamics International
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Induced pluripotent stem cell (iPSC) technologyMoving from somatic cells to stem cells to tissue cells of choice
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New horizons
iPSC technology is enabling new pathways toward
understanding human biology, pathology, and therapy
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Current pre-clinical modelsUseful with impactful limitations
Primary Human Cells Transformed Cell Lines Animal Models
• Donor variability
• Variable quality
• Limited availability
• Limited characterization
• Inaccessible biology
• Phenotypic instability
• May not recapitulate relevant
cell/tissue biology
• May lack key functional
characteristics
• Cannot adequately represent
human diversity
• May not represent relevant
human biology
• Resource intensive
($ and labor)
• Require significant quantities
of compound
• Animal welfare issues
Induced pluripotent stem cell (iPSC) technology overcomes limitations of
existing cell models - Availability, Functionality, Reproducibility, Translatability
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iPSC technologyProviding human biology from cells to populations
iPSC technology is providing relevant material richer content from targeted populations
Endoderm
Mesoderm
Ectoderm
Terminally differentiated
human cells
…from multiple organs
across the body
…expanding across
diverse populations
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“Disease in a Dish”Using iPSCs to move from Bedside to Bench to Bedside
iPSC technology can be used to
model human innate, induced,
and infectious diseases that
cannot be interrogated using
conventional cell lines, primary
cells or animal models
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iPS Cell TechnologyRevolutionary Access to Human Biology
Differentiate into any cell
type in the human body
208 C
ell
Typ
es
Represent any
individual genotype6 Billion People
Edit any gene in
the genome
Reprogramming
Dif
fere
nti
ati
on
an
d
Man
ufa
tcu
re
To revolutionize life-science
research and medicine,
mastery of all three
technology platforms is
required: reprogramming,
differentiation, and
engineering.
Mastery of one or two is
evolutionary, not
revolutionary
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Contextual Relevance is KeyFunctional cell types provides translatable answers
Neuronal Endpoints
• Developmental,
• Electrical / synaptic
• Degeneration
• Toxicity and DiscoverySynapse formation
Neurite Outgrowth Electrical Activity
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iCell CardiomyocytesContextual Relevance
Cell Signaling• Ca2+ signaling (EC coupling)
• Kinases, transcription factors, etc
• Energetics
Electrical / Membrane
Ion channels, ECM, GPCRs, etc
MechanicalContraction and relaxation
iPSC-Cardiomyocytes can exhibit many
aspects of native human behavior with the
appropriate biological pathways and may
provide more meaningful test substrate.
Cardiac Endpoints
• Electrical
• Biochemical
• Contractile
• Cardiomyopathy
• Toxicity and Discovery
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Why bother?
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Predictive Screens for Functional ToxicityLabel Free Impedance Measurements
Contextual relevance of human iPSC cardiomyocytes provide a more predictive tool for detecting
functional toxicity
Proarrhythmiascreening in 96 wells
> 90% -- QT prolongation> 80% -- Proarrhythmia
• >120 compounds
• ~equal positives and negatives
• beat rate, atypical beats, irregularity
Guo et al., 2013
C. Scott Tox Sci 2014
Contractility screening in
> 96 wells
1 AR Harmer Tox App Pharm (2012)2, A. Pointon Tox Sci (2014)3, C. Scott Tox. Sci (2014)
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KI-induced CardiotoxicityDeconvoluting the problem
FDA approved SMKI show cardiac liabilities
• Preclinical assays were insufficient
• Toxicities arose in late development / clinic
• Difficult to ascribe mechanism
Prediction hindered by :
• Highly conserved site of action-ATP-binding pocket
(on vs off target effects)
• Multiple effects on overlapping endpoints
Model can:
• Determine on-target vs off-target KI toxicity (MARK vs Chk KI)
• Identify KI-related toxicity with p<0.05
(>160 cmpds via Ambit and AZ-proprietary datasets)M. Peters CDI UGM 2014
Contextual relevance provides a predictive
tool for detecting KI toxicity
See also Cohen et al, 2013, Doherty 2013, Talbert 2014, Peters et al, 2015
S. Lamore SOT 2014
Cellular impedance assays with iCell
CMs can predict KI toxicity
Altered beat
phenotype indicates
upstream interaction
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Disease Modeling
Reprogramming to iPSCs
iPSCDifferentiation
INNATE
Healthy DonorDonor with
Genetic Disease
INDUCED
Healthy Conditions
Disease-inducing Conditions
Healthy Donor
ENGINEERED
Healthy DonorDonor with
Genetic Disease
Controls
Engineer Genome
PHENOTYPIC ANDFUNCTIONALANALYSIS
Disease Modeling and Assay DevelopmentDisease in a Dish
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Normal
Diseased
Native Phenotype
Cellular and Molecular Hallmarks
• Increased cell size
• Sarcomeric re-organization
• Increased fetal gene expression
-14 -13 -12 -11 -10 -9 -81000
1100
1200
1300
1400
1500
Log [ET-1] (M)
To
tal A
rea (
m2)
Control
+ET-1 (10 nM)
Control
+ET-1 (10 nM)
Control
ET-1 (10 nM)
Cell Size Cytoskeletal
RearrangementsFetal Gene
Expression
iPSC Cardiomyocytes exhibit classic hallmarks of cardiac
hypertrophy
iPSC Cardiomyocyte Recapitulation
Induced Disease Models – iPSC CardiomyocytesCardiac Hypertrophy
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Case Study #1: Induced Cardiac HypertrophyIn-vitro condition reflects native phenotype
Zhi et al, Front in Genetics, 2012
Aggarwal et al., Plos One 2014
Principal Component Analysis (Expression Array) of Human LV Biopsy
vs iPSC Cardiomyocytes
iPSC Cardiomyocytes provide a relevant inducible model of cardiac
hypertrophy
Biopsy
PC1; Biopsy vs iCell Cardiomyocytes- Difference attributed to heterogeneous
tissue sample vs. pure cardiomyocytes
iCell CM
PC2; control vs hypertrophy- Shift along the axis indicative of pathology
Control
Hypertrophy
Similar location of hypertrophic
samples along PC2 indicates
common pathology components
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NHLBI Next Generation Genetic
Association Studies (RFA-HL-11-066)
250 patient samples – HyperGEN cohort
GWAS – Left Ventricular Hypertrophy (LVH)
Derive iPS cells and cardiomyocytes
Induce hypertrophy, perform molecular analyses
Correlate GWAS findings with in vitro phenotype
Case study #2: Innate disease modelsPopulation and disease diversity
All donors reprogrammed
Optimized differentiation protocol
iPSC Cardiomyocytes in the hands of the PI
Population studies from clinical samples;
Feasible, on-going, and valuable
Identify common and unique pathways across clinical diagnoses
Enable diversity driven drug discovery
Preliminary findings include
Unique and common phenotypes across
disease CMs
Correlation between in-vitro phenotype and
disease progression (Uli Broeckel, MCoW)
Consistent IPSC material
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Case Study #3: Induced Disease ModelDiabetic cardiomyopathy (DCM)
Diabetic media induces DCM disease phenotype in iCell CMs
Functional E-C pathology
Diabetic media induced disease phenotype:
• Sarcomeric disorganization
• Ultrastructural disruption
• Lipid accumulation
• Oxidative stress
• Altered gene expression
• Cellular hypertrophy
• Altered EC functionality
Drawnel et al, Cell Reports, 2014
iPSC Cardiomyocytes model diabetic
cardiomyopathy through environmental induction.
Myofilament remodeling
DM; endothelin, cortisol, glucose)
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Screening with iPSC-CardiomyocytesInduced DCM-disease pathology enables unbiased screen
Diverse set of hits
from iPSC CMs• Lipid synthesis
• DNA synthesis
• Protein control
• PDE inhibitor
• Kinase inhibitors
• Ca2+ signaling
iPSC Cardiomyocytes initial Screen• 480 compounds
• 47 hits
• 28 confirmed DR
• Across a wide MOA
Phenotypic screen enabled large
diversity of hits
iCell DCM Screening Phenotype
Endpoints• Increased CM score
• Decreased BNP secretion
• Decreased nuclear area
iCell DCM Screening Strategy
Drawnel et al, Cell Reports, 2014
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Case Study #4: Innate Disease ModelsPatient derived cardiomyocytes show innate disease phenotypes
• Patient derived CMs show
baseline pathology
• In-vitro phenotype mirrors
clinical presentation
Non-Clinical and Clinical Samples DCM CMs Functional Pathology
Altered EC
function
Increased lipids
Increased ROS
Drawnel et al, Cell Reports, 2014
MyCell-DCM CMs Cellular Morphology
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Screening with clinically-derived CardiomyocytesPhenotype trends with clinical phenotype
Drawnel et al, Cell Reports, 2014
Clinical DCM screening strategy
Source
induced
Innate
Cmpds
14/18
MyCell screening results - Rescue DCM phenotype to control phenotype)
10/18
Clinical DCM - Cardiomyocytes:
• Screen against innate pathology
(no induction)
• Verifies hits across clinical
diversity
• Practical method for bringing the
clinic into screening
Assay Range
MM; control condition
BM = positive control
(rescues baseline pathology)
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MYH7 R403Q iPSC Cardiomyocytes• Show innate and induced signs of cardiac
hypertrophy
• Hypertrophic phenotype can be rescued
Provide another model/example of innate
disease models suitable for discovery
and screening
Case study #5: Innate disease modelsMYH7-R403Q linked hypertrophic cardiomyopathy
MyCell MYH7 R403Q CMFamilial Cardiac Hypertrophy
Baseline Pathology
NPPB 5
ACTA1 4
DUSP4 3
ACTC1 2
ACTN1 1
CREB5 0
MYH7 -1
NPPA -2
MYH6 -3
TRIM63 -4
ADM -5
FBXO32
PDCD4
Relative Expression
ET-1
induced
iCell CM
MyCell
MYH7
R403Q CM
Expression levels normalized
to uninduced iCell CMs
iCell CM
MYH7 R403Q CM
BNP / DAPI 384-well plate.
Phenotype induction and rescue
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Case Study #6: iPSC Neurons and Chemotherapy induced Peripheral Neuropathy (CiPN)
Chemotherapy-induced peripheral neuropathy (CIPN)
• Most common non-hematological side-effect
• Estimated 12 million cancer survivors in 2012
• CIPN can affect 20-40% of patients
• Limits therapeutic options
Can iPSC neurons used as a model to understand the genetics of CiPN?
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Chemotherapeutic-induced NeuropathiesConsistent Material Enables Phenotype Assays
Stem Cell Res, 2016
Different batches of iPSC-Neurons derived from a single iPSC clone showed:
• No significant differences in transcriptomic profiling
• Consistency in gene expression, cytosine modifications, neurite growth
• No significant differences in sensitivities to paclitaxel, vincristine, and
cisplatin
Effect of chemotherapeutic agents on neuronal
outgrowth compared between neuron batches
Profiling of iPSC
differentiated neurons
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iPSC Neurons and Chemotherapy induced Peripheral Neuropathy (CIPN)
Chemotherapeutics affect neurite outgrowth of iPSC neurons
Can this be used as an endpoint to understand the genetics of CIPN?
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Proof of concept for iPSC neurons and CiPN
Paclitaxel changes
neurite morphology siRNA knockdown of the Paciltaxel target
TUBB2A disrupts neurite outgrowth
Target knockdown mimics effect, thus the model
passes the POC assessment
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Proof of concept for iPSC neurons and CiPN (#2)
JAMA, 2015
• Inherited polymorphism in CEP72 is associated with risk and severity
of vincristine-induced neuropathy in children with ALL.
• Polymorphism reduces CEP72 expression
• Knock-down of CEP72 expression in iCell Neurons results in increased
sensitivity to vincristine compared to control iCell Neurons.
POC #2 passed
Can this be extended to
the clinical population?
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Chemotherapeutic-induced Neuropathies Layering in Diversity: Associating population genetics with function
Mean most sensitive: NA12892 and NA12814
Mean most resistant: NA07022 and NA12752
Observed reproducible
differences in morphological
characteristics among different
drugs and genetically diverse
neurons for each drug
Establishes a framework for
functional studies of genes
contributing to CIPN and
identifying drugs to treat or
prevent CIPN
iPSC-Neurons from 4 different unrelated LCLs
with varying degrees of chemotherapeutic toxicity
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Case Study #7: APP Protective and Pathogenic StudiesMyCell Neurons
Maloney JA, et al. (2014) J Biol Chem
Relevant Neuronal Model for Alzheimer’s Disease -
Mechanism of A673T variant of APP for protection against AD
◄ Differentiated cells from
three isogenic lines
appeared morphologically
similar to each other, and
uniformly expressed APP.
▲BACE cleavage of endogenous APP in MyCell
cortical neurons resulted in lower levels of Ab peptides
and sAPPb/sAPPα ratio in the A673T APP variant.
A B C
Disease Modeling using iPSC-Neurons
Induced model: Engineered APP mutations
Disease phenotype: The protective variant
resulted in lower levels of Aβ production and
improved neuronal activity.
Insight to pathology: Opportunity to
discover disease modifying (prevention,
arrest, reverse) targets
▲A673T APP showed improved
electrical and network activity.
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First disease iPSC banked
~800 donor-derived iPSCs banked
~8000 donor-derived iPSCs banked
~2000 donor-derived iPSCs banked
Democratizing access to iPSCs for disease Modeling
2010
2015
2018
2016
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Upcoming Disease and Diversity ProductsDeveloping Banks of Human iPS cells
Jump start your research–Order the differentiated cells you want from newly opened iPSC Banks
CIRM Bank currently contains iPS cell lines from 259 affected donors and 41
control: complete bank will be 3000 donor samples
Neurodevelopment (22 affected, 6 controls*)
Autism (22)
Cerebral Palsy (2)
Epilepsy (2) *
Intellectual disabilities (coming)
Alzheimer’s Disease (1 affected, 16 controls)
Liver Diseases (27 affected, 7 controls)
HCV (17)
NASH (9)
Steatosis (1)
Idiopathic Pulmonary Fibrosis (55 affected. 21 controls)
Blinding Diseases (55 affected, 11 controls*)
AMD (37)
POAG (7)
Diabetic Retinopathy (11)
Cardiomyopathies (102 affected, 0 controls)
LV non-compact CM (2)
HCM (17)
DCM (63)
Other (20)
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Thank-you
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