IMMUNECARTA

Report
PD-1 and the Immune Exhaustion Paradigm:
Immune Profiling Tools for Drug Discovery and Clinical Monitoring
Yoav Peretz, Ph.D.
Xtalks Webinar
Date: September 20th, 2012
IMMUNECARTATM Services
201 President-Kennedy, Suite PK-3900, Montréal, QC, Canada
[email protected] / T 514-360-3600
www.immunecarta.com
OUTLINE
1. Overview of ImmuneCarta Services
2. Technologies and Applications
a.
PHENOTYPIC ANALYSES
b.
FUNCTIONAL ANALYSES

Epitope Mapping by ELISPOT

Intracellular Cytokine Staining

In Vitro Proliferation
3. Overview of PD-1 and Co-inhibition

Immune Activation/Inhibition/Exhaustion (Is PD-1 sufficient?)
4. Immune Monitoring applied to the analysis of Co-Inhibition and Exhaustion
a.
Vaccine Hyporesponse
b.
Analyzing the Immune Inhibitory Profile (PD-1, TIM3, CD160, CTLA-4, etc.)
c.
Functional Restoration

Intracellular Cytokine Staining (ICS)

CFSE Proliferation
2
IMMUNECARTATM
Services
Advanced Immune Monitoring Services to Support
Vaccine & Drug Development
• Contract Service Business
•




Strategic alliance with Caprion, an exclusive supplier of
ImmuneCarta Services
Flow-based immune monitoring of subjects enrolled in
Phase I-II Clinical Trials in a GLP/GCLP compliant
environment
Immunological profiling and biomarker discovery for
the development of:
 Small molecules
 Biologics/Biosimilars
 Vaccines
In vitro screening of novel immune-modulating drugs
Development and validation of customized assays
3
Flow Cytometry
IMMUNECARTATM
Services
 Technology: Multiparametric single
cell analysis (cell surface, intracytoplasmic, intra-nuclear)
 Enumeration: Specific immune cells in
whole blood
 Phenotyping: Cellular Differentiation, Maturation,
Activation, Inhibition, Apoptosis
 Functionality: Cell Signaling, Cytokine Secretion Profile,
Proliferation, Degranulation
 Antigen-specific responses, Epitope Mapping: Multimer
detection and identification of HLA-restricted stimulatory epitopes by ELISPOT
and FACS
 Serological profiling: Multiplexed detection of soluble inflammatory mediators
in response to immune modulating agents
4
IMMUNECARTATM
Services
Functional Cell-Based Assays that Monitor AntigenSpecific Immune Responses
Flow cytometry is a unique technology that gathers phenotypic and functional data on
single cells from a heterogeneous population found in the blood or tissues.
•
Relative distribution of phenotypic and functional subsets
•
Predictive and/or correlative value with clinical parameters of disease progression
or therapeutic efficacy
5
Epitope Mapping
IMMUNECARTATM
Services
ELISPOT Assay
Detection of IFNγ-secreting lymphocytes
Coating with capture antibodies, αIFN
Day 1
Block plates (PBS-BSA 1%)
Peptide stimulation and incubation of cells (O/N)
Add 2nd antibody, αIFN--ALP conjugate
Day 2
Spot development by adding BCIP/NBT substrate
Spots (IFNγ-secreting T cells) are counted using a CTL
Immunospot analyzer
6
Comprehensive Epitope Mapping using Overlapping Peptide Pools
2760
194
108
87
291
44
151
205
44
POL1
POL2
POL3
POL4
POL5
POL6
POL7
POL8
POL9
POL10
POL11
pol4254
pol4264
pol4274
pol4284
pol4294
pol4304
pol4314
pol4324
pol4334
pol4344
302
POL12
pol4255
pol4265
pol4275
pol4285
pol4295
pol4305
pol4315
pol4325
pol4335
pol4345
399
POL13
pol4256
pol4266
pol4276
pol4286
pol4296
pol4306
pol4316
pol4326
pol4336
pol4346
1725
POL14
pol4257
pol4267
pol4277
pol4287
pol4297
pol4307
pol4317
pol4327
pol4337
pol4347
-20
POL15
pol4258
pol4268
pol4278
pol4288
pol4298
pol4308
pol4318
pol4328
pol4338
pol4348
22
POL16
pol4259
pol4269
pol4279
pol4289
pol4299
pol4309
pol4319
pol4329
pol4339
pol4349
POL17
pol4260
pol4270
pol4280
pol4290
pol4300
pol4310
pol4320
pol4330
pol4340
pol4350
POL18
pol4261
pol4271
pol4281
pol4291
pol4301
pol4311
pol4321
pol4331
pol4341
pol4351
POL19
pol4262
FRDYVDRFYKTLRAE
pol4272
pol4282
pol4292
pol4302
pol4312
pol4322
pol4332
pol4342
pol4352
pol4273
pol4283
pol4293
pol4303
pol4313
pol4323
pol4333
pol4343
pol4353
33
2500
11
65
378
SLYNTVATLYCVHQR
6
6 PBMC)(SFC/10 PBMC)
Cumulative
Magnitude
(SFC/10
Magnitude
IMMUNECARTATM
Services
-9
2250
44
POL20
pol4263
Single IFN-g secretion
2000
Dual IFN-g/IL-2 secretion
1750
1500
Magnitude, Breadth & Specificity
SLYNTVATL
1250
1000
750
500
250
0
Gag
Pol
Nef
Acc
Env
7
IMMUNECARTATM
Services
PD-1 and the Family of Coinhibitory Molecules
 Restore/Enhance immune function (Cancer, Chronic Infection)
 Balance inflammation (Autoimmune Disorders)
8
IMMUNECARTATM
Services
PD-1 Regulates the Delicate Balance between Protective
Immunity and Tolerance
Francisco et al.
Page 38
NIH-PA Author Manuscript
NIH-PA Author Manuscript




Fig. 7. Mechanisms of PD-1-mediated T-cell tolerance
PD-L1 ligation of PD-1 following TCR stimulation results in two possible T-cell fates:
Spontaneous autoimmunity
observed
PD-1iTreg
knockout
mice
diminished T-effector
responses andin
augmented
development,
thus tipping the balance
towards immunologic tolerance.
PD-1 is involved in both central (thymus) and peripheral T cell tolerance
Signaling through PD-1 inhibits CD8 and CD4 T cell effector functions
PD-1 exerts critical inhibitory functions in settings of persistent antigenic stimulation (Selfantigens, Chronic viral infections such as HIV, Oncology)
9
IMMUNECARTATM
Services
Hierarchical Loss of T Cell Function is Associated with Duration of
Antigenic Exposure, Inflammation and Increased Expression of
Inhibitory Molecules (PD-1, CD160, 2B4)
Outstanding Questions:
1.
Is this a reversible process?
2.
Can we distinguish between an activated
and an exhausted antigen-specific T cell?
Adapted from Wherry, J et al. Nature immunology. 2011.
10
IMMUNECARTATM
Services
The Balance Between Co-stimulation and Inhibition is
Critical to Maintaining T Cell Homeostasis and Function
11
Accumulation of Inhibitory Molecules during
Chronic HIV Infection
40
30
20
10
30
20
10
CD160
EC
ST
ic
on
C
ni
90
P = 0.0001
80
P = 0.0003
70
60
50
CMV
HIV
40
30
20
10
P = 0.0001
100
90
P = 0.008
80
70
P = 0.31
60
CMV
HIV
50
40
30
20
10
0
EC
on
ST
ic
e
ut
Ac
d
te
ec
nf
ct
fe
ut
e
0
Un
in
hr
te
d
Ac
ut
e
nf
ec
c
EC
CD160-PD-1+
(SP-PD-1)
100
ed
Frequency of CD160+PD-1- T cells
(% of tetramer)
CD160+PD-1(SP-CD160)
hr
5
CMV
HIV
40
C
10
50
U
4
10
Frequency of CD160-PD-1+ T cells
(% of tetramer)
3
10
CD160
60
ni
2
P = 0.0001
70
U
10
P = 0.0001
80
EC
0
ST
5
c
10
ni
4
ST
ct
fe
in
10
90
0
Un
3
10
Tetramer
P = 0.004
100
0
0
0
Frequency of CD160+PD-1+ T cells
(% of tetramer)
CMV
HIV
50
ed
102
60
ni
0
P = 0.006
ro
3
P = 0.0001
70
e
10
80
ro
3
90
Ch
4
PD-1
10
5
P = 0.0002
Ac
10
PD-1
CD8
104
CD160+PD-1+ (DP)
100
ut
10
5
CD160-PD-1- (DN)
P = 0.0001
Frequency of CD160-PD-1- T cells
(% of tetramer)
10
B
.
B*07 CMV
B*07 Nef
Total CD8
Ch
A
Ac
IMMUNECARTATM
Services
Antigen persistence shifts the phenotype (SP-PD-1 to DP) of antigen-specific
CD8 T cells
Peretz, Y et al. PLOS Pathogens (2012)
12
Longitudinal Analysis of CD160 and PD-1 Expression during
Gag
AcuteA*02
&CMV
Chronic A*03
HIV
Infection
5
10
5
10
4
10
4
10
3
10
3
PD-1
Acute
<6
months
.
B*07 CMV
B*07 Nef
Total CD8
10
PD-1
IMMUNECARTATM
Services
0
0
0
10
4
3
10
Chronic
>12
months
3
0
2
0
0
3
10
Tetramer
10
4
10
5
0
10
2
3
10
CD160
4
10
10
2
3
10
CD160
10
4
10
5
10
5
10
5
10
4
10
4
10
3
0
10
2
10
CD160
3
10
4
10
5
0
10
2
10
CD160
3
10
4
10
5
PD-1
10
10
PD-1
10
5
PD-1
CD8
104
10
PD-1
5
PD-1
10
10
3
0
5
CD160
Peretz, Y et al. PLOS Pathogens (2012)
0
0
10
2
3
10
CD160
10
4
10
5
CD160
13
IMMUNECARTATM
Services
Intracellular Cytokine Staining Measuring
Degranulation (CD107a), IFNγ and TNFα Secretion
# sign represents p < 0.05
when compared to DP
Co-expression of CD160 and PD-1 identifies CD8 T cells at an advanced stage of dysfunction
during chronic HIV infection
Peretz, Y et al. PLOS Pathogens (2012)
14
Case Studies
15
IMMUNECARTATM
Services
I - Vaccine Hyporesponse (VHR) in Healthy Elderly
Subjects
Cohort: 174 healthy subjects of age ≥ 65, HBV seronegative
Hepatitis A/B (Twinrix)
Clinical Sites: 2 recruiting sites
Dukoral (WC/rBS)
Objective: Exploratory study aiming to develop a statistical model to predict VHR
(antibody titers) in the elderly based on a set of phenotypic markers measured by
Flow cytometry.
Tetanus/Diphteria (Td)
Visit 1
Visit 2
Visit 3
Visit 4
Visit 5
SCREENING
VISIT
BASELINE
DAY 7
MONTH 1
MONTH 2
16
IMMUNECARTATM
Services
Serum
aliquoting/storage
II - Sample Management
Ficoll
PBMC
cryopreservation
Other assays
PRIMARY
ENDPOINTS
ELISA (Ab Titers)
Other assays
ImmuKnow
assay
Flow cytometry
T cell panel
Innate panel
Cell pellet
cryopreservation
Paxgene tube
storage
DNA analysis
RNA/mRNA analysis
Flow cytometry
B cell panel
SECONDARY
IMMUNOLOGICAL
ENDPOINTS
174 subjects; 4 TP/subject; cohorts of 20 subjects/shipment; 11 blood tubes/subject
17
IMMUNECARTATM
Services
III - Multidimensional Flow Cytometry Analysis
Using N Parameters
2N Parameters combinations
(512 different populations in CD4+
and CD8+ T cells = 1024 subsets per
sample)
18
IMMUNECARTATM
Services
IV - Reduction of High Dimensionality Immune Markers to
Minimal Parameters
 Boolean analysis of 9 markers in CD4+ and CD8+ T cells (N = 512 subsets)
 Prediction of vaccine hyporesponse at baseline (N = 174 subjects)
Reduce dimensionality:
summing 7 parameters on 2
N = 9 parameters
T Cell phenotype
Ab
Fluor.
FITC
CD38
PerCP-eF710
PD-1
eFluor 450
CD57
V500
CD3
Qdot 605
CD27
eF650 NC
CD8
APC
CD62L
Alexa700
HLA-DR
APC-eF780
CD4
PE
CD28
ECD
CD45RA
PE-Cy7
CCR7
Analysis
Export New Results for
N = 2 parameters
PREDICTIVE
MODELING(combination of 2
Innate phenotype
markers)
! "#$%%"&' $( ) *+&$
No response
Ab
Fluor.
,. %/ ) 01
Vaccine
X:
FITC
Response
CD11c
. 24#
23,
#5 67
#5 <
#5 =>
#5 =;
23B
DE, F5 G
235
! ==;
23K
#5 6;
89: ;
8: ; ;
? 5 ) *@; :
$. @: ; "A#
, C#
, %$HI ">; ;
CJ
CJ F4HG
CJ F#+:
CJ F#+>
CD1c
CD16
CD3
CD19
CD4
CD303
CD56
HLA-DR
CD141
CD14
CD40
PerCP-eF710
+
V450
V500
V500
eF650 NC
#
+
#
+
8
0
2
0
5
4
APC
3
Alexa 700
2
APC-CY7
1
PE
ECD
PE-Cy7
0
5
7 +
+
P
D+
+
(
B
a
r
#
)
S
h
o
w
n
v
a
lu
e
s
:V
is
it=
V
2
;A
g
e
=
6
5
+
;C
D
=
4
#c
and
+:
Stat
Significant
compared
to
group
E
x
lu
d
e
d
v
a
lu
e
s
:D
i=
;D
i=
N
A
/p
;H
=
N
A
/p
;T
=
N
A
/p
“HepB+
Vaccine
Response”
A
v
e
r
a
g
e
d
o
v
e
r
:V
is
it;A
g
e
;D
i;T
;S
u
b
je
c
tI
D
;C
D
S
u
m
m
e
d
o
v
e
r
:R
7
;2
7
;2
8
;3
8
;R
A
;6
2
L
;D
R
p<0.05,
Wilcoxon-Rank
and
Student’s
t-tests
T
h
r
e
s
h
o
ld
=
0
+
(
T
te
s
t)o
r#
(
W
ilc
o
x
o
n
)
:p
<
0
.
0
5
;c
o
m
p
a
r
e
d
to
H
=
H
_
V
A
C
C
+
19
I - Phenotypic Characterization of
Inhibition/Activation/Exhaustion
IMMUNECARTATM
Services
•
METHOD: 16-parameter, 14-color phenotyping cocktail of immune inhibitory markers on
viral-specific CD8+ T cells
20120319_BI_QUALIFICATION
•
Layout
Hierarchical gating scheme identifying the main CD4 and CD8 naïve/memory T cell subsets
Experiment ID:
SUBJECT ID:
Group ID
DATE OF FACS RUN:
Timepoint
95.7
250K
250K
105
105
4
104
27.2
105
1.68
200K
150K
100K
100K
50K
50K
3
10
77.5
CD8
Viability
SSC-A
FSC-H
10
150K
4
A*0201 CMV pp65
10
CD45RA
200K
68.8
103
103
0
0
0
68.7
0
0
0
50K
100K
150K
200K
250K
0
50K
FSC-A
100K
150K
200K
250K
0
FSC-A
250K
103
104
10 5
104
200K
150K
150K
100K
100K
50K
50K
103
104
105
105
4
79.1
105
0
3
10
0
39.1
0
103
104
105
CD27
CD4 Memory Subsets
4.2
28.9
105
105
6.34
0
103
CD27
104
10 5
40.1
10
3
10
0
14.3
0.474
4
10
CCR7
3
10
104
4
10
CCR7
CCR7
CCR7
0.242
4
10
103
CD45RA
CCR7
43.4
14.8
67
0
CD45RA
CD27
Phenotyping Cocktail
0
0
2.75
10 5
FSC
FSC
FSC
200K
0
105
104
Pentamer
250K
33
CD45RA
10 3
0
105
CD4
43
57
103
0
CD3
Live/Dead
Tetramer/Pentamer
CD3
CD4
CD8
CTLA4/CD152
CD45RA
CD27
CCR7
Tim-3/CD
PD-1/CD279
CD160
2B4/CD244
Lag-3/CD223
Negati
CMV te
CMV te
HIV Tet
HIV Tet
HIV Tet
HIV Tet
3
10
0
12.7
54.1
0
103
104
29.4
105
CD27
30.1
0
103
104
10 5
CD27
CD8 Memory Subsets
20
100K
II - Phenotypic Characterization of
Inhibition/Activation/Exhaustion
50K
50K
0
0
0
103
104
105
CD45RA
4.79
20.1
4
105
4
105
3.33
8.75
3.01
105
4
4
10
10
Boolean analysis of 6 parameters quantifying the relative distribution of 64 (26) subsets
with various patterns of inhibitory receptor expression
3
10
0
3
10
0
36.2
3
10
0
38.9
7.96
19.8
104
105
103
0
104
10 5
55.8
103
0
104
PD-1
2B4
CTLA-4
103
0
CD27
CD8 Memory Subsets
LAG-3
TIM-3
CD45RA
CD27
21.5
78.5
C
66
12.7
30.1
3.35
1.24
CD4
0.517
48.8
105
CD27
CD4 Memory Subsets
CD160
3
10
0
32.2
CD27
CD27
Analysis20120319_BI_QUALIFICATION
of CD4, CD8, Pentamer,
and Memory/Naive
subsets
103
0
8.34
0
2
10
10
3
10
4
10
5
0
10
3
10
4
10
5
0
10
3
10
4
5
10
0
3
10
4
5
10
10
0
10
3
10
4
10
5
0
10
3
10
4
10
5
0
10
3
10
4
10
5
0
10
3
10
4
5.7
36.9
14.9
15.5
1.29
10
5
0
55.7
43.3
56.7
CD8
5.11
0 102
10 3
10 4
10 5
0
10 3
10 4
10 5
0
10 3
10 4
105
0
103
104
105
0
10 3
10 4
10 5
0
10 3
10 4
10 5
0
10 3
10 4
10 5
0
10 3
10 4
10 5
0
2.26
Pentamer
•
69.3
10
CCR7
CCR7
•
2.94
105
10
104
CD45RA
CCR7
105
103
0
CCR7
IMMUNECARTATM
Services
100K
8.19
18.1
2
0 10
10
3
10
4
10
5
0
10
3
10
4
10
5
0
10
3
10
4
5
10
14.7
87.3
26.6
85
1.41
0
3
10
4
10
5
10
0
10
3
10
4
10
5
0
10
3
10
4
10
5
0
10
3
10
4
10
5
0
10
3
10
4
10
5
0
21
III - Graphical Presentation of a Phenotypic Analysis
Frequency (% of CD8)
IMMUNECARTATM
Services
# Markers
4
3
2
1
0
Following SEB-stimulation, the relative distribution of CD8 subsets expressing various combinations
of immune inhibitory markers shifts
22
IMMUNECARTATM
Services
I - Intracellular Cytokine Staining
Gating of T cells
17.6
150K
100K
100K
50K
50K
0
0
10
CD8
85.9
0
50K
100K
150K
FSC-A
200K
250K
105
0
50K
100K
150K
FSC-A
200K
250K
5
10
4
10
3
CD27
150K
SSC-A
FSC-H
200K
97.1
60.2
10
4
10
3
10
2
21.5
CD4+ T Cell Subsets
67.1
CM
10
Naive
5
43
48.9
CM
Naive
EM
LD
104
CD27
250K
200K
CD8+ T cell Subsets
CD4+ and CD8+ T cells
CD8+
5
T10cells
Live CD3+ T cells
250K
103
10
4
10
3
<Aqua-A>: Viability
<eFluor 650-A>: CD8
99.9
CD4+
T cells
0
0
69.3
0
EM
7.21
0
10
2
3
4
10
10
<Qdot 605-A>: CD27
10
5
<V450-A>: CD3
0
10
3
10
4
10
5
0
2
10
3
10
4
10
2
0
7.17
4.18
10
5
0
0.869
102
103
104
105
CD45RA
CD45RA
CD4
Aggr- Gate
Event Count: 215893
10
LD
CD4+ T cells
1.53
4.85
62.3
83.7
2.55
71.6
2.68
LD
CD107a
0.766
15.7
80.2
Granzyme B
0.32
27.8
0.0129
55.2
0.142
8.41
0.341
CM
CD107a
0.645
99.5
0.129
Granzyme B
0.806
9.85
2.37
74
59.1
67.2
2.43
EM
CD107a
1.07
32
64.8
Granzyme B
0.252
20.2
6.81e-3
13.9
0.0839
0.361
0.606
Naive
CD107a
0.0681
99.6
0.093
Granzyme B
IL-2
Granzyme B
IL-17
IFNg
CD107a
TNFa
23
II – Analysis of the Distribution of Functional Antigen-Specific
CD4 & CD8 T Cell Subsets
IMMUNECARTATM
Services
Deconvolute
Frequency of CD4 (%)
Total IL-2 secretion
# of Functions
4
Polyfunctional
3
2
1
0
Monofunctional
24
IMMUNECARTATM
Services
III – Analysis of the Distribution of Functional Antigen-Specific
CD4 & CD8 T Cell Subsets
Deconvolute
Frequency of CD8 (%)
Total IFNγ secretion
# of Functions
4
Polyfunctional
3
2
1
0
Monofunctional
25
In vitro Rescue of Proliferation in the
Presence of Compound
IMMUNECARTATM
Services
NS
NS
NS
Pep
de alone
Peptide
Pep
de alone
Isotype
Control
Control
Isotype
Control
B*08 Nef
B*08 Nef
FLKEKGGL
FLKEKGGL
+
+
αPD-L1
αPD-L1
αPD-L1
αHVEM
αHVEM
αHVEM
αHVEM +
αHVEM
+
αPD-L1
+ αHVEM
αPD-L1
αPD-L1
Antigen-specific CD8 T cell proliferation is restored following in vitro blockade
of inhibitory molecule interaction
26
IMMUNECARTATM
Services
Summary
Our Mission is to Accelerate the Development
of Vaccines & Immune-modulating Therapeutics

In settings of persistent antigenic stimulation and chronic immune activation, there is a hierarchical loss
of immune effector cell function.

Functional responses can be restored and enhanced following in vitro blockade of inhibitory molecules

Applications:



Mutiparametric flow cytometry identifies and distinguishes between activated and exhausted
effector subsets
Functional restoration of cytokine secretion and proliferation can be measured in vitro in response
to compounds as well as ex vivo in a clinical setting
Therapeutic areas of interest:
 Oncology
 Infectious Diseases
 Autoimmunity
 Immunosenescence
 Transplantation
27
Acknowledgements
IMMUNECARTATM
Services





Martin Leblanc
Claire Landry
Marylène Fortin
Lina Palmaccio
Benoit Houle





Salim Ahmed Khan
David Favre
Jean-Francois Poulin
Carey Sheu
John Kamins





Geneviève Lévesque
Gilbert Croteau
Nathalie Saha
Caroline Hébert-Benoit
Sasan Ziaie





Karyne Savard
Phyla Kay
Valérie Hébert
Dominic Gagnon
Dominike Sauvé
Thank you!
28

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