Biomarcadores de respuesta inmune
Simposio GEM´13
Miguel F de Sanmamed
Clínica Universidad de Navarra
Tumor
Ganglio drenaje
Aproximación al estudio
1. Especificidad de la respuesta T
2. Cuantificación y caracterización respuesta
3. Estudios de genómica y proteómica
1. Especificidad de la respuesta
Genotyping
FISH
IHC
1. ELISPOT
Array CGH
SNP array
WGS
Figure 18
(b)
(a)
104
1023
Karyotyping
2. TETRÁMEROS
FISH
PCR
Microbial arrays
(CF)
WGS
RNA-Seq
Pentamer APC
enes
plot, gated only on event
within R1, showing Pentamer-stained cells on the
RNASeq
CD8-stained cells on the x-axis. Draw a quadrant t
separates positive cells from negative cells on both
use quadrant statistics to obtain quantitative in
about the frequency of antigen-specific CD
T lymphocytes, figure 18b.
Targ-Seq/WES
SSC-H
ses
Create a second density
2 Targ-Seq/WES
Quadrant Sta
Gate: R1
Gated Events
Total Events:
103
Figure 1. High variability of results for the enzyme-linked
Quadimmu
Even
spot (ELISPOT) immune response assay. IdenticalULperiph2
13
mononuclear cell samples from the same patientUR
were
LL
6107
WGS
R1
different laboratories
experienced with ELISPOT methodo
UL
2544
image shows RNA-Seq
the spot count results in microtiter plates in w
102
101
100
0
0
1023
FSC-H
100
101
102
103
104
CD8 FITC
3. “DEEP SEQUENCING”
ChIP-Seq
protocol details
are reported back for central analysis. Si
Bisulphite sequencing
more than 80 laboratories from 14 countries have pa
methyl-specific PCR
encompassing the academic, nonprofit, biotech, and
on levels RNA microarray
ceutical sectors, and the United States Department o
(20,22).
RNA-Seq
The ELISPOT panel is the longest running program
2. Cuantificación y caracterización respuesta
0·3 mg per kg
3 mg per kg
10 mg per kg
2·6
2·4
2·2
2·0
1·8
Figure 3. Kaplan-Meier survival curves are shown stratified by
the absolute lymphocyte count (ALC) at (A) baseline and after (B) the first and (Ku
(C) second
Gy etipilimumab
al; Cancerdoses.
2010)
original articles
Annals of Oncology
1·6
3
ex
th
re
bi
ad
sy
oc
ici
m
ad
m
im
du
1·4
Cancer
1·2
April 1, 2010
1·0
0
–3
0
3
6
9
12
–3
0
3
6
9
12
–3
0
3
6
9
12
Weeks since first dose
Figure 4: Fitted mean absolute lymphocyte count versus weeks since first dose, by treatment group
Datapoints(Wolchok
include 4 weeks before
to theOncology
end of the induction
dosing period. Thick curves=fitted means.
et al;baseline
Lancet
2010)
Thin curves=pointwise two-sided 95% CI.
Most high-grade events could be managed medically
with treatment guidelines included in the trial protocol,
and they resolved or improved within about 4 weeks.31
(Delyon et al; Annals of oncology 2013)
Downloaded from http://annonc
in
by
by
nd
in
ur
by
Articles
Número absoluto de linfocitos
Fitted mean absolute lymphocyte count (×1000 cells per µL)
w
1c
se
n,
or
se
ed
an
of
rn
s,
es
.30
s,
ce
nd
ed
ur
if
th
or
24
im
we
W
re
(Callahan et al; ASCO 2013)
Fenotipos posibles
Dobles
negativos
Simples
positivos
Dobles
positivos
Triples
positivos
Superficie
PE
CD3
CD11b,c
Linfocitos
CD8
FITC
Mieloides
CD4
NKs
CD56
CD4
CD3+CD4+
CD3
Citometría de Mieloides supresoras
Mieloides supresoras (CD14+HLA-DRneg/low)
(Callahan et al; ASCO 2013)
Caracterizar
PD-1
LAG-3
TIM-3
CD25
CD137
OX40
CD69
ICOS
CTLA-4
CD45R0
Caracterizar
PD-1
LAG-3
TIM-3
CD25
CD137
OX40
CD69
CTLA-4
CD45R0
PB
ICOS
(Callahan et al; ASCO 2013)
(Callahan et al; ASCO 2013)
Fijación
Marcaje
superficial
Permeabilización
Marcaje
intracelular
Intracelular
Fosforilación STAT-5
Caspasa 3
BCL-XL
BIM
P
STAT-5
Granzima
Perforina
Ki-67
FOXP3
Tbet
EOMES
IL-2, IFN-Y, TNF-∝
Intracelular
Fosforilación STAT-5
Caspasa 3
BCL-XL
BIM
P
STAT-5
Granzima
PB
Perforina
Ki-67
FOXP3
Tbet
EOMES
IL-2, IFN-Y, TNF-∝
(Callahan et al; ASCO 2013)
Inmunohistoquímica
7º Congreso Virtual Hispanoamericano de Anatomía Patológica
Pági
Figura 10. Tinci ón inmunohistoquímica del fondo inflamatorio en linfoma de Hodgkin: linfocitos T (CD4 y CD8), c élulas NK (CD56 y CD57) y células citotóxicas (GrB y TIA -1).
Parad ójicamente, un numero elevado de CTL anuncia un curso cl ínico adverso en LH.
A
Baseline
Day 90
B
Baseline
Day 90
C
Baseline
Day 90
Day 322
100
Expresión de PD-L1
101
102
103
Antihuman IgG4
B
Objective Response
No Objective Response
Proportion of Patients
Melanoma
17/17
1.0
0.8
16/25
0.6
0.4
9/25
RCC
0.2
0/17
0.0
Positive
(N=25)
Negative
(N=17)
PD-L1 Status
Association between Pretreatment Tumor PD-L1 Expression and Clinical Response
Response Status
PD-L1–Positive
PD-L1–Negative
Total
Lung Cancer
number (percent)
Objective response
No objective response
All
9 (36)
16 (64)
25
0
17 (100)
17
9 (21)
33 (79)
42
P=0.006 for association by Fisher’s exact test
therapy has been the identification of mechanism- patients with PD-L1–positive
tumors
in none
(Topalian
et al;and
NEJM
2012)
based predictive biomarkers that could be used to of those with PD-L1–negative tumors suggests
(Weber J et al; ASCO 2013)
(Callahan et al; ASCO 2013)
Biomarkers in Immunostimulatory Combina
Tumor
LN
1 mm
100 µm
© 2013 American Association for Cancer Research
aining with anti-FoxP3 and anti-granzyme B. Two opposite cases of lymph node (LN) in different patients with melanoma.
þ
n high expression of FoxP3 cells (red) at margin of melanoma and very low expression of GBþ cells (brown). Granzyme B is
ht, a nonpathologic lymph node with high expression of granzyme B and low expression of FoxP3. The metastatic lymph n
mmunosuppressive cells compared with the negative lymph node.
Inmunocontexto
del
tumor
F O C U S O N T U m O U R I m m U N O lO g y
a
& I m mPU
EN
R SOPTEhCETRI a
V PE y
S
b Immune
Parameters: positive association with survival
contexture
DC
Macrophage
Mast cell
Type
CTLs (CD3+CD8+)
Memory T cells (CD45RO+)
Location
Core of the tumour
Invasive margin
NK cell
Tumour core
Density
1
CD3+CT
CD3+IM
CD8+CT
CD8+IM
CD45RO+CT
CD45RO+IM
MDSC
Immature DC
Invasive margin
Tumour bed
Functional
orientation
FDC
B cell
TFH cell
Number of cells per mm2
10
100 1,000 10,000
TH1 cell-associated factors (IFNγ, IL-12, T-bet and IRF1)
Cytotoxic factors (granzymes, perforin and granulysin)
Chemokines (CX3CL1, CXCL9, CXCL10, CCL5 and CCL2)
CTL
TH17 cells, TReg cells and TH2 cells have a variable
Stroma
TLS
Figure 1 | The immune contexture. a | Tumour anatomy showing the features of the immune contexture, including the tumour core, the invasive
margin, tertiary lymphoid structures (TLS) and the tumour microenvironment. The distribution of different immune cells is also shown. b | Table
depicting the parameters of the immune contexture that predict a good
TLS
Presence and quality
prognosis. CT, core of the tumour; CTL, cytotoxic T lymphocyte; DC,
dendritic cell; FDC, follicular dendritic cell; IFNγ, interferon-γ; IL-12,
interleukin-12; IM, invasive margin; IRF1, interferon regulatory factor 1;
Nature
Reviews
Cancer
MDSC, myeloid-derived suppressor cell; NK cell,
natural
killer |cell;
T H,
T helper; TReg
(Fridman et al; Nat Rev 2012)
on of this
shment
the progts when
nostic
sed on
e populad cytotoxic
he core
ours. For
ancer
and no
metasta-
100
58/60
90
14/15
prognosis
Good
None
Poor
80
70
% articles published
B cells is
s of breast
but corin many
ntigenbe imporndent
control
60
50
4/8
4/8
14/33
40
30
20
10
0
CD8+
CD45RO+
TH1
cell
T H2
cell
TH17
cell
TReg
cell
(Fridman et al; Nat Rev 2012)
3. Estudios masivos
ations in cancer
tations
ions/indels)
mber gains or losses
ements, fusion genes
nic sequences
c modifications
Existing technologies
Capillary (Sanger) sequencing
Pyrosequencing
Genotyping
FISH
IHC
Array CGH
SNP array
Karyotyping
FISH
PCR
Microbial arrays
Bisulphite sequencing
methyl-specific PCR
anscript expression levels RNA microarray
llele-specific expression
RNA microarray
al alternative splicing
RNA microarray
Emerging technologies
Targ-Seq/WES
RNASeq
Targ-Seq/WES
WGS
WGS
RNA-Seq
WGS
RNA-Seq
ChIP-Seq
RNA-Seq
Fig 1. Categories of ge
and technologies for detec
hallmark alterations in can
detected by using a mul
technologies, often in a se
using an appreciable amou
Newer sequencing-based m
capable of interrogating ma
alterations in one compos
CGH, comparative genom
ChIP-Seq, chromatin immu
lowed by massively parallel
fluorescent in situ hybridizat
histochemistry; PCR, polym
tion; RNA-Seq, RNA seque
as transcriptome sequencin
cleotide polymorphism; Targ
quencing; WES, whole-ex
WGS, whole-genome sequ
Predictive Gene Signature for MAGE-A3 Cancer Immunotherapy
No clinical benefit
Clinical benefit
-1
0
1
2
PD
PD
PD
PD
PD
PD
MxR
PD
PD
PD
PD
PD
PD
PD
PD
PD
PD
SD
SD
MxR
PD
PD
MxR
PD
PD
PD
PD
SD
PD
PD
MxR
PD
SD
PD
SD
CR
PD
PD
PD
CR
PD
PR
CR
SD
PD
PD
SD
MxR
PD
MxR
SD
PR
MxR
PD
SD
MxR
-2
HLA-DMA
HLA-DQA1
HLA-DRA
HLA-DRA
PTGER4
LCP1
C1orf162
CD86
SLAMF7
TNFAIP3
TNFAIP3
CYTIP
GPR171
GZMK
CD3D
TRBC1
TRBC1
TRBC1
ITK
TRA@
TRA@
TRA@
SLAMF6
IL2RG
SLA2
ARHGAP15
CXCL2
C4orf7
PPP1R16B
TOX
ITGAL
TNFRSF9
NA
DENND2D
EAF2
JAK2
GBP5
GBP5
IRF1
CD8A
MAP1B
ZNF285A
UTY
USP9Y
HOMER1
MCM10
AP2B1
SLITRK6
SRPX2
C2ORF63
AADAT
DZIP1
KIAA1549
SHROOM3
LOC284757
HILS1
AKR1C2
ITGA3
TMEM56
LONRF2
SLC26A2
Homing
FAM26F
FAM26F
FAM26F
FAM26F
CXCL10
GABBR1; UBD
CXCL9
RARRES3
GBP1
GBP4
EPSTI1
PSMB10
KLRD1
KLRD1
CCL5
ICOS
TARP; TRGV9
TRGC2
NA
TARP
TARP
PSMB9
HCP5
B2M
BTN3A1
STAT1
STAT1
HLA-A;HLA-J
HLA-B
HLA-B
HLA-F
HLA-F
UBASH3B
RNF144B
KLRB1
CDC42SE2
CDC42SE2
GCH1
TC2N
GOLGA7
IFNg
B
100
Disease-Free
Interval (%)
S+
SGS+
GS-
72
hs)
80
60
40
Placebo - GS+
Placebo - GSMAGE-A3 + AS02B - GS+
MAGE-A3 + AS02B - GS-
20
0
No. at risk
MAGE-A3 +AS02B – GS+
MAGE-A3 + AS02B – GSPlacebo – GS+
Placebo – GS-
12
24
36
48
60
72
84
Time Since Surgery (months)
41
65
20
31
34
49
15
20
30
38
11
18
26
32
9
13
24
28
9
12
20
23
8
11
14
11
5
5
3
0
0
1
outcome and irAE
RFS
An analysis of biomarkers at baseline dichotomized by
their medians revealed that a low % of Ki67+EOMES+
CD8+ T cells, and a low % of EOMES+CD8+ T cells were
significantly associated with relapse (p =0.001, and 0.047
with OR = 11.25, and 3.77, respectively; Table 5a). These
pre-treatment biomarkers were also confirmed in a univariate logistic regression analysis to be associated with reWenshi
Wang1*A, Daohai
Yu2, Amod
A Sarnaik1, Bin
lapse (data
not shown).
similar analysis
of dichotomized
baseline Xiuhua
biomarkers
theirJeffrey
medians
showed1 that a low %
Zhaoby2 and
S Weber
of Ki67+EOMES+CD4+ T cells was associated with occurrence of irAE (p =0.008 with OR = 8.00, Table 5b).
Our analysis highlighted the potential importance of
EOMES, a transcription factor in the T-box family and
involved in the regulation of INF-γ, granzyme B and perforin production by CD8+ T cells [43]. To better understand the potential role of EOMES+CD8+ T cells in
ipilimumab treatment, we stratified pre-treatment specimens by the median % of EOMES+CD8+ T cells. Patients
1
3
+
Yu
Hall1, Dawn
Morelli+1CD8
, Yonghong
,
with, Maclean
higher baseline
% of EOMES
T cells Zhang
had a significantly improved relapse-free survival (RFS) compared
to those with a lower basal level of EOMES+CD8+ T cells
(p = 0.02 by log-rank test, Figure 1a). The patients were also
RESEARCH
Open Acce
Biomarkers on melanoma patient T Cells
associated with ipilimumab treatment
Abstract
Proportion
Proportion
a Ipilimumab induces long-lasting clinical
b responses in a minority of patients with metastatic
Background:
1.0
1.0
melanoma. To better understand the mechanism(s) of action and to identify novel biomarkers associated
0.8 baseline characteristics and changes in CD4+ and CD
with the 0.8
clinical benefit and toxicity of ipilimumab,
T cells from
were characterized by gene profiling and flow
0.6 melanoma patients receiving ipilimumab
0.6
cytometry.
0.4
0.4
Methods: Microarray analysis of flow-cytometry purified CD4+ and CD8+ T cells was employed to assess
0.2
0.2
gene profiling
changes induced
by ipilimumab.
Selected
moleculesKi67EOMES
were CD8
further<=2.11
investigated
by flow
(20)
%EOMES_CD8
<=55.6 (27)
Median
>55.6 (27)
>2.11 (19)
Median
0.0183
Log-rank p =0.0004
cytometry0.0onLog-rank
pre,p =3-month
and 6-month post-treatment
specimens.
0.0
0
24
36
48
60
72
84
96
Survival
(Months)
Ipilimumab Relapse-Free
up-regulated
Ki67
and ICOS on
+
12
0
+
12
72
84
96
24
36
48
60
+
Relapse-Free
Survival
CD8
cells at
both(Months)
3- and 6-month
post ipilimumab
Results:
CD4 and
+
+
(pKaplan-Meier
≤ 0.001), decreased
CCR7
andcurves
CD25 comparing
on CD8 at
3-month
≤ 0.02),
and increased
Gata3
Figure 1 a:
relapse-free
survival
patients
with post
(high)ipilimumab
greater than(p
median
baseline
% of EOMES
CD8+in CD4
+ less than median % of EOMES+CD8+. b, Kaplan-Meier relapse-free survival
+ comparing patients
+ high+
to patients
with
(low)
curves
with
and
CD8
cells at 6-month post ipilimumab (p ≤ 0.001). Increased EOMES+CD8
, GranzymeB+EOMES
CD8 and decrea
+
+
+
+
+
+
+ EOMES
baseline %Ki67
of Ki67
/CD8+ Ttocells
patients
low % were
of Ki67significantly
EOMES /CD8associated
.
EOMES+CD4
at 6with
months
with relapse (all p ≤ 0.03). Decreased Ki67+CD8+ T
cells were significantly associated with the development of irAE (p = 0.02). At baseline, low Ki67+EOMES+CD8+ T cells w
associated with relapse (p ≤ 0.001), and low Ki67+EOMES+CD4+ T cells were associated with irAE (p ≤ 0.008).
Conclusions: Up-regulation of proliferation and activation signals in CD4+ and CD8+ T cells were pharmacodynamic
markers for ipilimumab. Ki67+EOMES+CD8+ and Ki67+EOMES+CD4+T cells at baseline merit further testing as biomarker
associated with outcome and irAEs, respectively.
Limitaciones y dificultades
s
or
f
ys
ngs
Figure 1. Challenges of immune monitoring: inter-laboratory variability
Figure 1. Challenges of immune monitoring: inter-laboratory variability
in immune response measurements [8]. Reprinted from Janetzki et al. [8],
wnloaded from http://annonc.oxfordjournals.org/ at Universidad de Navarr
ker
h variability of results for the enzyme-linked immunosorbent
OT) immune response assay. Identical peripheral blood
ar cell samples from the same patient were sent to 36
boratories experienced with ELISPOT methodology. The
s the spot count results in microtiter plates in which each
well represents the result of one laboratory. Some wells
numbers of spots, whereas others are low or negative. Each
assay represents a single T-cell capable of reacting against a de
antigen. These results reflect the outcome of the first ELIS
ciency panel, which identified sources of variability among la
tails are reported back for central analysis. Since 2005,
80 laboratories from 14 countries have participated,
ing the academic, nonprofit, biotech, and pharmactors, and the United States Department of Defense
combined panel results led to initial ELISPOT harm
guidelines (Table 2) (20), which synchronize key varia
laboratories and substantially influence assay outcome
impose standardization of assays on individual laborat
Conclusiones
patients in the combination therapy, ipilimumab-alone and
gp100 treatment groups, respectively [3].
Personalizar-inmunoterapia
CA184-024
Trial CA184-024 evaluated the efficacy and safety of ipilimuma
plus DTIC 850 mg/m2 compared with the DTIC alone group in
502 patients with previously untreated stage IIIC or stage IV
melanoma [5]. The primary end point of the trial was OS, with
response-based and safety secondary end points. The mean age
of patients were similar between the two treatment groups (57.5
years and 56.4 years, respectively) and the majority of patients
had a poor prognosis, with over 50% of patients in both the
treatment groups having stage M1c disease.
OS (Figure 4B) in the ipilimumab plus DTIC group was
significantly longer than in the DTIC alone group: 11.2 months
versus 9.1 months, P = 0.00009, with a 28% reduction in the ris
of death. The estimated 1-year, 2-year and 3-year survival rates
were 47.3%, 28.5% and 20.8% in the ipilimumab plus DTIC
group compared with 36.3%, 17.9% and 12.2% in the DTIC
alone group. PFS was also statistically significantly improved by
the addition of ipilimumab to DTIC, with a 24% reduction in
the risk of disease progression (P = 0.006). The disease control
rates were similar across both the treatment groups (33.2% and
30.2%). The rates of CR and partial responses (PR) were higher
in the ipilimumab plus DTIC group than in the DTIC group,
while the rates of stable and progressive disease were lower. The
durability of response was higher in the ipilimumab plus DTIC
group than in the DTIC group (duration of response: 19.3
months versus 8.1 months, respectively).
The overall AE rates in this trial were similar across both th
treatment groups, although the rate of grade 3 or 4 AEs and
patients in the combination therapy, ipilimumab-alone and
gp100 treatment groups, respectively [3].
Personalizar-inmunoterapia
CA184-024
Trial CA184-024 evaluated the efficacy and safety of ipilimuma
plus DTIC 850 mg/m2 compared with the DTIC alone group in
502 patients with previously untreated stage IIIC or stage IV
melanoma [5]. The primary end point of the trial was OS, with
response-based and safety secondary end points. The mean age
of patients were similar between the two treatment groups (57.5
years and 56.4 years, respectively) and the majority of patients
had a poor prognosis, with over 50% of patients in both the
treatment groups having stage M1c disease.
OS (Figure 4B) in the ipilimumab plus DTIC group was
significantly longer than in the DTIC alone group: 11.2 months
versus 9.1 months, P = 0.00009, with a 28% reduction in the ris
of death. The estimated 1-year, 2-year and 3-year survival rates
were 47.3%, 28.5% and 20.8% in the ipilimumab plus DTIC
group compared with 36.3%, 17.9% and 12.2% in the DTIC
alone group. PFS was also statistically significantly improved by
the addition of ipilimumab to DTIC, with a 24% reduction in
the risk of disease progression (P = 0.006). The disease control
rates were similar across both the treatment groups (33.2% and
30.2%). The rates of CR and partial responses (PR) were higher
in the ipilimumab plus DTIC group than in the DTIC group,
while the rates of stable and progressive disease were lower. The
durability of response was higher in the ipilimumab plus DTIC
group than in the DTIC group (duration of response: 19.3
months versus 8.1 months, respectively).
The overall AE rates in this trial were similar across both th
treatment groups, although the rate of grade 3 or 4 AEs and
?
nlineFirst November 24, 2009; DOI:10.1158/1078-0432.CCR-09-2376
Evaluación-respuesta
Immune Response Criteria for Tumor Immunotherapy?
nlineFirst November 24, 2009; DOI:10.1158/1078-0432.CCR-09-2376
Evaluación-respuesta
Immune Response Criteria for Tumor Immunotherapy?
Tumor
Mecanismo-acción
Ganglio drenaje
Muchas gracias