ips cell-derived cardiomyocytes: overcoming barriers to … · 2017. 7. 19. · nature (2004)...
TRANSCRIPT
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iPS cell-derived cardiomyocytes:
overcoming barriers to therapeutic use
Chris GeorgeSwansea University Medical School
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(i) A retrospective look at approaches for heart repair
: autologous bone marrow-derived SC
: cardiac-derived (ckit+) SC
(ii) Contemporary approaches
: ES-derived CM
: iPS-CM
(Direct fibroblast-to-CM conversion)
(v) Systematizing iPS-CM maturation
(iii) Problems with cell type and maturation
(vi) Cellular determinism: towards predicting and
controlling phenotype
(iv) Excitation-contraction coupling and the network
organization of cell signalling
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(i) Repairing the failing heart with bone marrow-derived stem cells (BMSC): the end of the line?
• Just 5/49 trials using BMSC were free from „discrepancies‟ (~10%)
• In those 5, mean EF effect size was zero
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Repairing the failing heart with cardiac-derived SC:
the fall-from-grace of c-kit+ lineage
2001 2017‘03 ‘04 ‘09 ‘10 ‘11 ‘12 ‘14 ‘15 ‘16
Lin-/c-kit+
haematopoietic cells
repair mouse heart
Nature (2001) 410:701-5
Cardiac-resident
c-kit+ cells repair
post-MI rat heart
Cell (2003) 114:763-76
BMSC do not become
cardiomyocytes
Nature (2004) 428:664-8 BMSC contribute to
revascularization of
the damaged heart
Nature (2004) 428:668-73BMSC do not become
cardiomyocytes
Nat. Med. (2004) 10:494-501No evidence of c-kit+
SC myogenesis
PNAS (2009) 106:1808-13
Neonatal, but not adult,
c-kit+ SC can become
cardiomyocytes
Circulation (2010) 121:1992-2000
Lancet (2011) 378:1847-57
Clinical benefit of c-kit+ cell transplantation
Adult c-kit+ SC adopt
vascular fate; neonatal c-kit+
SC can become
cardiomyocytes
PNAS (2012) 109:13380-5
Lancet Expression of concern 2014
Between 2 and 78 y/o human heart is regenerated
8-times from c-kit+-mediated myogenesis
Circulation (2012) 126:1869-81
Retraction of the „8-new-
hearts‟ story
Circulation (2014) 129:e466
Lancet (2014) 60608
Circulation (2013) 128:122-31
c-kit+ SC improve cardiac
function in HF
‘13
Nature (2014) 506:337-41
c-kit+ SC are irrelevant as a source of
new cardiomyocytes in vivo
Nat. Commun (2015) 6:8701
Lineage tracing confirms c-kit+ SC do
not become cardiomyocytes
Circ. Res. (2015) 116:1216-30
Paracrine effects of c-kit+ SCCirc. Res. (2016) 118: 17-19
Drawing a line under things?
Boston Globe
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(ii) Beyond c-kit+ SC - ES-derived cardiomyocytes
Nature (2014) 510:273-7
1x109 cells (suspension, post-freeze
73±12% CM)
Direct myocardial injection
2 weeks 3 month Evidence of CM maturation in situ
2 weeks
x4
Diameter = 43mm
2 mm
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Circ. Res. (2014) 115:335-8
Accentuate the negatives
1. Teratomer risk
2. Long term immunosuppression
3. 100% incidence of arrhythmias
(especially early on)
4. Arrhythmogenic risk increases at
slower heart rates (humans)
5. Is cardiac function improved?
Development of alternans
6. Long term toxicity of pro-survival
cocktail (sarcoma proteins)
1. Risk overplayed; 98% CM in graft;
zero teratomers in > 1000 rats
2. Universal donors / HLA engineering
3. Potentially due to poor coupling from
injecting 1x109 cells (< 1% cells remain);
Human heart may need ~ 8x109
4. Unlikely to see increased risk in humans
5. Further work needed
6. As point 1
The response
Circ. Res. (2014) 115:e28-9
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Beyond ES-derived CM: grafting EHT built from iPS-CM
Sci. Trans. Med. (2016) 8:363ra148
EHT ‘seeded’ at 65% CM (atrial CM)
Day21 : 95% vCM @ 50bpm
2 weeks post-graft
4 weeks
post-graft
IPS-CM in EHT• ‘Immature’• In situ maturation
: sarcomeric extension by ~ 10% but still smaller than GP CM: >95% conversion of MLCA to MLCV isoform
• No arrhythmias reported• Human DNA in spleen (2/7) and lungs (4/7); none in liver or kidney
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(iii) The futility of selecting nodal-, atrial- and ventricular-like cells…....?
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Hallmarks of cardiomyocyte immaturity
Yang and Murry. Circ. Res. (2014) 114:511-523
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Nature (2011) 471:68-73
IPS and epigenetic imprinting: they remember where they came from….....
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iPS-CM ready for the clinic??
A network approach to cellular signalling
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Out
In
Na+ K+
(iv) Excitation-contraction coupling and the entrainment of
surface membrane and intracellular SR „clocks‟
Na/K-
ATPase
NCXNa/K-
ATPasePMCACa2+
Plateau
“Trigger Ca2+”
RyR
SR
SERCA Myofilaments
Mito
Vinogradova et al. (2004) Circ. Res. 94:802-9
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Inhibition of SR clock unmasks an
unusual Ca2+ entrainment in IPS-CM
Out
In
Na+ K+
Na/K-
ATPase
NCX Na/K-
ATPase PMCA Ca2+
“Trigger Ca2+”
RyR
SR
Sarcolemma
SERCA Myofilaments
Mito
X
X
Control
CPA
Edwards (unpub.)
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Building a network….........
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β-AR AC
Adr
ATP cAMP
Multiple downstream effectors
(“Fight or flight” response)
PKA
+
βγ
α
out
in
Activation via the the beta-adrenoceptor pathway
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http://expasy.org/cgi-bin/show_thumbnails.pl
The cell signalling „blueprint‟ – everything linked to
everything else
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///SR
Excitation-
contraction coupling
Ca2+
release
Mitochondria
Surface ion fluxes
Metabolism
Apoptosis
Protein synthesis & degradation
Intra-cellular synchronization
Inter-cellular synchronization
Gene expression
Horizontal and vertical network organization
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out
in
cyto
lumen
Basal
Restore
Restore
Disrupt
Perturbing the homeostatic state : network adaptation
out
in
cyto
lumen
Unstable
Disrupt
Activated
out
in
cyto
lumen
Disrupt
Adapt out
in
cyto
lumen
Pseudo-stable
George et al. (2012) Am. J. Physiol. 303:897-910.
RyR2SERCA
LTCCNCX
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Day
2 3 4 5 6 70
20
40
60
80
100
Tro
po
nin
po
sitiv
e
(%
)
2 3 4 5 6 70
20
40
60
80
100
Day
Ce
llula
r a
lig
nm
en
t (%
)
***
*
Day
Day 2 Day 4 Day 7
DAPI
Troponin-T
Alignment of ES-CM in culture
Lewis et al. J. Biomol. Scr. (2015) 20:30-40
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Maturation-linked refinement of Ca2+ handling
5 sec
ΔC
a2
+
(20 f.u
.)
C
a2
+
(20
f.u
.)
Day 2 Day 3 Day 4 Day 5 Day 6 Day 7
Δ
2 sec
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Temporal heterogeneity index (THI) = σ(int1….intn)
Amplitude heterogeneity index (AHI) = σ(ampa….ampn)
Inter-transient noise (ITN) = Σ(SV1….SVn)
SV1 SV2 SVn
int1 int2 intn
ampa ampb
ampn
Sa Sb Sb Sn
Time (t) Flu
ore
scen
ce
(units)
ampc
Frequency = S s-1
F0
Amplitude* = (ampn-F0) / F0
ka kb kc kn
da db dc dn
Duration = (da + db + dc + dn) / n
Area* = Area under curve / F0
Rate of decay = (ka + kb + kc + kn) / n
a b c n
a b c n
a b c n
a b c n
1
2
3
4
a b c n a b c n a b c n
a 1 1 0
b 0 1 0c 0 0 1
n 0 0 1
a 1 0b 0 1
c 0 0n 1 0
a 0
b 0c 0
n 0
S
Cell no.
1
2
3
2 3 4
= 8/24 (33.3%)
Co-incidence of S Coincidence of S = 33.3% (8/24)
Synchronization = Coincidence (Sa…..Sn)
Cell
S
SALVO-based profiling of cellular Ca2+ : discriminating
signals from noise
George and Edwards (2017) Stem Cell-Derived Methods in Toxicology pp173-90 Humana Press
Intracellular Intercellular
synchronization
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D4 D5 D6 D70.0
0.2
0.4
0.6
0.8
Ra
te (H
z)
****
****
******
**
D4 D5 D6 D70.00
0.05
0.10
0.15
0.20
0.25
0.30
Am
plitu
de
he
tero
ge
ne
ity
in
de
x (A
HI)
****
****
****
D4 D5 D6 D70.0
0.1
0.2
0.3
0.4
0.5
Te
mp
ora
l h
ete
rog
en
eit
y in
de
x (T
HI)
****
****
********
D4 D5 D6 D70.000
0.005
0.010
0.015
0.020
Inte
r-tr
an
sie
nt n
ois
e (
ITN
)
*
****
**
D4 D5 D6 D70
10
20
30
40
50
Sy
nc
hro
niz
atio
n (%
)
Maturation of Ca2+ handling is linked to reduced Ca2+
signalling variability
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Ra
te
Basal C
a2+
ITN
-A
ITN
-B
ITN
-C
Am
pli
tud
e
Du
rati
on
Are
a
Ra
te U
p
Tim
e-t
o-p
ea
k
Ra
te D
ec
ay
Tim
e-t
o-d
ec
ay
No
ise
in
dec
ay
TH
I
AH
I
0
50
100
SALVO parameter
% o
f m
ax
0.6 0.8 1.3 1.2 - 0.5 0.4 0.7 0.6 0.4 0.6 0.4 0.8 1.7 0.8CoV
n=209
Massively variable homeostatic Ca2+ handling
CoV = SD/mean
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Jones et al (2016) Front. Cell Dev. Biol. 3:89
(v) Systematizing iPS-CM maturation : EB vs. monolayer
culture
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EB maturation is not associated
with morphological change
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Increased post-disaggregation clustering from older EBs
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Defining conditions for maximum Ca2+ synchronization
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Unmasking Ca2+ signalling phenotype
Switch [Ca2+]ext from
400μM to 1.8mM [Ca2+]ext
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(vi) Cellular determinism
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1
2
3
4
4
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9
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33
34
35
36
36
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42
43
44
44
45
46
47
48
49
50
51
52
52
53
54
55
56
57
58
59
60
Cause Effect
Cell #
Towards predicting cellular response and heterogeneity
Homeostasis
State 1
State 2
State 3
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Predictably influencing cell-to-
cell coupling in computational
arrays
Variability of
cell-to-cell coupling
Boileau et al. (2015) Ann. Biomed. Engin. 43:1614-25
59
103
Rotors in iPS-CM (Edwards, unpub)
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Progress made
• Maturity of cells
• Maturity of field
• More realistic endpoints
Barriers that still exist
• Transparency / dataset availability /
understanding of „nuisance variables‟
• Reliance on crude end-points of phenotype and function
• High levels of phenotypic variability
• Unpredictability
• Unknown impact of reprogramming / source
What‟s needed?
• New „network‟ approach to cellular variability
and determinism
SUMMARY
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Cardiff
Catrin Williams
David Lloyd
Adrian Porch
Dimitris Parthimos
Nottingham
Chris Denning
Gary Duncan
Divya Mirrington
David Edwards
Aled Jones
Sarah Marsh
Kimberley Lewis
Catherine Hather
Nicole Silvester
Steven Barberini-Jammaers
Phil Ashton
Archana Jayanthi
Alice Mitchell
Jessica Wells
Swansea (Engineering)
Perumal Nithiarasu
Etienne Boileau
Sanjay Pant
Ankush Aggarwal
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SIRPA+/ VCAM+ SIRPA+/ VCAM-0
10
20
30
Pro
po
rtio
n o
f c
ells
(%
) *
102
103
104
105
102 103 104 105
VC
AM
-54
6 (
un
its
)
SIRPA-488 (units)
SIRPA+ / VCAM+
SIRPA+ / VCAM-
Non-e
nrich
ed
SIR
PA+ / V
CAM+
SIR
PA+ / V
CAM-
0
20
40
60
80
100
Tro
po
nin
po
sitiv
e (%
)
********
****
SIRPA+/VCAM-
SIRPA+/VCAM+
Non-enriched
TnT
DAPI
Does CM enrichment improve phenotype?
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5 sec
ΔC
a2
+
(20
f.u
.)
Non-enriched SIRPA+/VCAM+ SIRPA+/VCAM-
Non-enriched SIRPA+/ VCAM+0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
Ra
te
(no
rma
lize
d)
Non-enriched SIRPA+/ VCAM+0.0
0.2
0.4
0.6
0.8
1.0
1.2
AH
I
(no
rma
lize
d)
*
Non-enriched SIRPA+/ VCAM+0.0
0.2
0.4
0.6
0.8
1.0
1.2
TH
I
(no
rma
lize
d)
*
Non-enriched SIRPA+/ VCAM+0.0
0.2
0.4
0.6
0.8
1.0
1.2
ITN
(n
orm
alize
d)
****
Non-enriched SIRPA+/ VCAM+0.0
0.5
1.0
1.5
2.0
Sy
nc
hro
niz
ati
on
(no
rma
lize
d)
*
Non-FACS (Day 7)