immunogram to decipher pd1/l1 ici resistance: a proof of … · 2019. 12. 21. · 01-01-022....
TRANSCRIPT
Data acquisition and distribution across patients
Patient groups display heterogeneous immune profilesTechnical workflow for immunoprofiling at baseline
Immunogram to decipher PD1/L1 ICI resistance: a proof of concept in advanced NSCLC patients of the PIONeeR ProjectFlorence Monville1, Frédéric Vély3,4, Joseph Ciccolini2,3, Florence Sabatier2,3, Stéphane Garcia2,3, Vanina Leca1, Marion Fabre2, Christelle Piperoglou3, Pernelle Outters1, Laurent Arnaud3, Laurent Vanhille1, Caroline Laugé1, Anna Martirosyan1, Aurélie Collignon1, Marie Roumieux2, Julien Mazières5, Maurice Perol6, Francoise Dignat-George2,3,7, Eric Vivier3,4,8, Fabrice Barlesi2,3, Jacques Fieschi1
1 HalioDx, Marseille/France, 2 Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm U1068 Aix Marseille University, Marseille/France, 3Assistance Publique des Hôpitaux de Marseille (APHM), Marseille/France , 4 Centre d’Immunologie de Marseille-Luminy (CIML), Marseille/France, 5 CHU Toulouse/France, 6 Centre Léon Bérard, Lyon/France, 7 Vascular Research Center (VRCM), Marseille /France, 8 Innate Pharma, Marseille/France.
BackgroundIn the management of advanced Non-Small Cell LungCarcinoma (NSCLC), PD1/L1 Immune CheckpointInhibitors (ICIs) have been shown to increase OverallSurvival (OS) over standard 2nd-line chemotherapy (CT).While this long-term increase in OS is driven by about20% of patients, others display disease progressionduring the first weeks.In clinical practice, high PD-L1 expression in tumor cellsas well as high Tumor Mutational Burden provide with anenriched population of PD(L)1 inhibitors responderswithout being sufficiently precise to exclude patientsfrom treatment.
ChallengeUnderstand biological background behind resistancesto PD1/L1 ICIs through a comprehensive multiparametricbiomarkers strategy (PIONeeR biomarkers program).Identify a relevant predictive algorithm based onbiomarkers combination adaptable to clinical practice.
Reference• Blank CU. et al., Science, 2016
ConclusionThis preliminary profiling highlights immunological heterogeneityacross patients not evaluated in current clinical practice.Such analyses confronted to clinical parameters may highlightbiological mechanisms explaining resistance to anti-PD(L)1 ICIs.These profiles will be expanded to additional biomarkers andoptimized on more than 400 patients to identify reliable predictivebiomarker combinations.
Strategy450 patients prospectively collected with stage IV orrecurrent NSCLC with first line anti-PD1/L1immunotherapy.Preliminary analysis of more than 20 biomarkers on 11patients at baseline as a proof of concept ofImmunogram1 performances to identify relevantcombinations of biomarkers to predict response to ICItreatment.
PIONeeR study sampling workflow
Foreignness : TMB (1/2), TCR clonality (1/2)Immune suppression within the tumor : Treg (1/3), M-MDSC (1/3), PMN-MDSC (1/3)PD-L1+ / Exhaustion : PD-L1+ cell density (1/2), PD1/LAG3/TIM-triple positive Tcells (1/4), PD1/LAG3/TIM-double positive Tcells (1/4).Immune infiltration : Tumor Infiltrating Lymphocytes (1/2) and Tumor Infiltrating Monocytes (1/2)Circulating lymphocytes : Total CD45+ lymphocytes
This work is supported by French National Research Agency (17-RHUS-0007); a partnership of AMU, AP-HM, CNRS, Inserm, Centre Léon Bérard, Institut Paoli-Calmettes, AstraZeneca, HalioDx, Innate Pharma & ImCheck Therapeutics, sponsored by AP-HM and initiated by Marseille Immunopole.Drug supply is funded by Innate Pharma and AstraZeneca.
0102030405060708090
100
Tota
l TCR
βRe
adsC
ount
Immune infiltration
Circulatinglymphocytes
PD-L1 and immune checkpoints
Immuno-suppressive cellsRegulatory T cells (Treg)Myeloid-derived Suppressor Cells:- Monocytic (M-MDSC)- PolyMorphoNuclear (PMN-MDSC)
Foreignness
CD45
SSC
SSC
CD3 CD8
CD4
CD19
CD16/56
M-MDSC
PMN-MDSC
CD3 CD8 CD11bCD4
PDL1 PD1
0
50
100
150
200
250
300
350
0
200
400
600
800
1000
1200
1400
1600
0
50
100
150
200
250
300
350
Cell
dens
ities
(cel
ls/m
m2
0
200
400
600
800
1000
1200
1400
Cell
Dens
ities
(cel
ls/m
m2 )
T Cell clones diversity(each clone represented by one color) bar size representsTCRβ counts and TumorMutational Burden
0
500
1000
1500
2000
2500
3000
Bloo
d Ce
llco
unt (
cells
/µL)Circulating lymphocytes
Immune cells infiltration
T-cells exhaustion
Immuno-suppressive cellsM-MDSC:
CD11b+ CD14+ S100A9+ HLA-DRlow/-
PMN-MDSC:CD11b+ CD15+ S100A9+ LOX1+
HLA-DRlow/-
Treg: CD4+ FOXP3+
T-cell clonality Tumor Mutational BurdenPD-L1 < 1%, TMB > 10
0
20
40
60
80
100
PD-L1+ / Exhaustion
Immune Suppression
Foreignness CirculatingLymphocytes
TumorInfiltration
PD-L1 < 1%, TMB < 10
0
20
40
60
80
100
Immune Suppression
Foreignness CirculatingLymphocytes
TumorInfiltration
PD-L1+ / Exhaustion
S100A9CD14CD11b HLA-DR
S100A9CD15CD11b HLA-DRLOX1
01-0
1-02
2
01-0
1-02
6
01-0
1-02
7
01-0
1-03
3
01-0
1-04
0
01-0
4-00
2
01-0
4-00
6
01-0
5-00
2
02-0
1-00
1
03-0
1-00
2
03-0
2-00
1
Patients IDs
0 17 4,3 6,4 7,1 1,4 13 5 5 9,2 8,5TMBAll events Lymphocytes CD3+ CD3-
Total CD3+ T cellsCytotoxic CD3+CD8+ T cellsHelper CD3+CD4+ T cellsCD3+CD56+ T cellsActivated CD3+ HLA-DR+ T cellsCD19+ B cellsCD3-CD56+ NK cells
CD3+CD8+ T cellsCD3+CD8- T cellsGranulocytesMonocytes Myeloid
Lymphoid
Moderate: 1 checkpointSevere: 2 or 3 checkpoints
PD-L1+ cell density in the tumor
Variables were combined in five biological axes to define an Immunogram; five arbitrary scoreswere calculated:• Each test results were transformed to fit 0 – 100, where 100 = maximum value observed
across the 11 samples• Each normalized result was weighted as indicated in brackets below
Mutations per megabase relative to normal counterpart
TCRβ reads count
LAG3 TIM3
CD4brown
FOXP3pinkV2VS
Post-anti-PD(L)1 treatment samplesPre-anti-PD(L)1 treatment samples
Diag V3 V4 V5V1 V6R R R R
Longitudinal blood sampling
Blood samplePre-tttFFPE
tumor
Pre-tttBlood sample
Pre-tttStool sample
Post-tttFFPE tumor
Post-tttBlood sample
Post-tttStool sample
Tumor biopsy at diagnostic
Blood sampling prior to treatment
20 FFPE slides
DNA/RNA extractionTargeted NGS on DNA
IHC staining + Digital pathology analysisIMMUNOSCORE® CR IC – CD8, PD-L1IMMUNOSCORE® CR TCE – CD3, CD8, PD1, TIM3, LAG3IMMUNOSCORE® CR Treg – CD4, FOXP3IMMUNOSCORE® CR MDSC – CD11b, CD14, CD15, S100A9, LOX1, HLA-DR
Genomics - Targeted sequencingTMB: 7661 exonic regions, 478 genes, 1,41MbT cell clonality: TCRβ sequencing
Immunoprofiling through immunostaining & cytometryCD45, CD3, CD8, CD4, CD19, CD56
Endothelial activation through MACS & cytometry on‐ Circulating endothelial cells (CEC, CD146+)‐ Endothelial MicroParticles (EMP, CD31+CD41-)‐ Circulating Endothelial leukocytes (7AAD, CD45, CD34, KDR)
NA
NA
NA N
A
01-01-02203-02-00101-01-02601-04-00601-04-00203-01-002
PD-L1 > 1 %
0
20
40
60
80
100
PD-L1+ / Exhaustion
Immune Suppression
Foreignness CirculatingLymphocytes
TumorInfiltration
Anti-PD(L)1 respondersenriched population
Anti-PD(L)1 treatmentexcluded population
PD-L1 expression
Poster P117
NKG2A inhibitor (Monalizumab)
+ Durvalumab (N=30)CD73 inhibitor
(MEDI9447) + Durvalumab (N=30)
ATR inhibitor (AZD6738)
+ Durvalumab (N=30)
Stat3 inhibitor*
(AZD9150) + Durvalumab (N=30)
Control arm Docetaxel
monotherapy (N=30)