Programme d’analyse globale et intégrative du micro-environnement tumoral - Vassili SOUMELIS, MD, PhD Laboratoire d’Immunologie Clinique et Inserm U932

1. Geneviève Almouzni, PhD
Directeur(e) du Centre de Recherche
Marc Estève , MD
Directeur de l’Hôpital

2. Programme d’analyse globale et intégrative du
micro-environnement tumoral
Vassili SOUMELIS, MD, PhD
Laboratoire d’Immunologie Clinique
et
Inserm U932

3. L’organisation hiérarchique des systèmes vivants

4. Réseaux de communication intercellulaire dans les
tissus inflammatoires

5. Oncogénèse: vision centrée sur la cellule tumorale
Oncogene Tumor supressor geneNormal Tumor

6. Oncogene Tumor supressor geneNormal Tumor
Normal epithelial cells Neoplastic cells
Extra-cellular Matrix
Fibroblasts/Myofibroblasts
CAFs
Lymphatic vessels
Blood vessels
Lymphocytes
Macrophages/TAM
Dentritic cells
Micro-environnement tumoral: une écologie complexe

7. Oncogene Tumor supressor geneNormal Tumor
Influence du micro-environnement sur l’évolution du cancer

8. Le micro-environnement: nouvelle cible thérapeutique?
1/ Rôle dans la progression tumorale
2/ Implication dans la résistance à la chimiothérapie
3/ Eficacité de nouvelles thérapies ciblant le micro-environnement
(exemple: immunothérapie)

9. Normal epithelial cells Neoplastic cells
Extra-cellular Matrix
Fibroblasts/Myofibroblasts
CAFs
Lymphatic vessels
Blood vessels
Lymphocytes
Macrophages/TAM
Dentritic cells
Comment étudier le micro-environnement
tumoral?

10. T-MEGA: Tumor MicroEnvironment Global Analysis
Hospital partners:
Surgery Dpt: Fabien Reyal, Pascale Mariani
Pathology Dpt: Xavier Sastre-Garau, Anne Vincent-
Salomon, Eliane Padoy, Jean-Marie Pléau
Centre de ressources biologiques (CRB) : Odette Mariani
Bioinformatic and biostatistic:
Bioinformatic Unit U900
Biostatistic Unit
Technological Platforms:
Cytometry Platform
Experimental Pathology Platform
Preclinical Investigation Laboratories
High throughput RTqPCR Platform
Affymetrix Platform
T-MEGA people:
Fatima Mechta-Grigoriou, PhD: Coordinator
Vassili Soumelis, MD-PhD: Coordinator
Alix Scholer-Dahirel: Project Manager
Philemon Sirven: Bioengineer
Melissa Cardon: Bioengineer
Gerome Jules-Clement: Data Manager
Yann Kieffer: Bioinformatician
Marine Jeanmougin: Bioinformatician
Sofia Honorio-Grand: CRA
Researchers involved in T-MEGA initiative:
Fatima Mechta-Grigoriou
Vassili Soumelis
François Radvanyi
Fabien Reyal
Danijela Vignjevic
Arturo Londoño-Vallejo
Marc-Henri Stern
Marie Dutreix
Marie Fernet
Janet Hall
Virginie Dangles-Marie
Didier Decaudin
Rosette Lidereau
Ivan Bieche
Didier Meseure
Clotilde Thery
Ana-Maria Lennon-Duménil
Matthieu Piel

11. Schéma expérimental: comment générer le maximum de
données à partir d’un petit échantilon tumoral (résidu)
Macrodissection
Transcriptome
Histology
Molecular Studies
TMA
Functional Experiments
Methylation profiles
Labs
Patient
Frozen
(CRB)
Fresh Tissue
Supernatant Cells
MAP
dissociationculture
FACS
T-MEGABioengineer
FFPE
(PIC BIM)
Macrodissection
Transcriptome
Functional Experiments
Methylation profiles
Histology
Molecular Studies
TMA
Frozen
(CRB)
FFPE
(PIC BIM)
Fresh Tissue
Supernatant Cells
MAP
dissociationculture
FACS
Patient
Clinical Research Associate
(T-MEGA)

12. De l’échantillon clinique aux données biologiques: approche
modulaire
Clinical sample
Cellular TME:
- ImmunoHistoChemistry
- FACS, 3 Ab panels
Soluble TME:
- Multiple Analyte Profiling
- Tumor infiltrating lymphocyte
secretion profiles
- Functional effect of tumor-derived
supernatants
Clinical data
Diagnosis / Follow-up
Extracellular Matrix
composition :
ImmunoHistoChemistry
Glucose
Metabolism
Oxidative stress
Transcriptomic:
Epithelial and Stromal
compartments
Human breast or ovarian cancer
450 patients included to date

13. Clinical sample
Cellular TME:
- ImmunoHistoChemistry
- FACS, 3 Ab panels
Soluble TME:
- Multiple Analyte Profiling
- Tumor infiltrating lymphocyte
secretion profiles
- Functional effect of tumor-derived
supernatants
Clinical data
Diagnosis / Follow-up
Extracellular Matrix
composition :
ImmunoHistoChemistry
Glucose
Metabolism
Oxidative stress
Transcriptomic:
Epithelial and Stromal
compartments
Human breast or ovarian cancer
450 patients included to date
De l’échantillon clinique aux données biologiques: approche
modulaire

14. Analyse “multi-process” du micro-environnement sécrété
Tumor
Juxtatumor fragment no treatment
RPMI 10% FCS
24h
Pro-/Anti-Inflammatory
Invasion/MetastasisAngiogenesis
Growth factors
Metabolism Immune infiltrate, Th subsets
Fibroblast infiltrate
Oxidative stress
Drug sensitivity
SASP
Apoptosis
ECM remodeling
Oxidativestress
ImmuneInfiltrate
Fibroblastinfiltrate
Drugsensitivity
Pro-Inflammatory
Anti-Inflammatory
Invasion/Metastasis
ECMremodeling
Angiogenesis
SASP
Apoptosis
Metabolism
GrowthFactors
0
10
20
30
40
50
60
Numberofwantedanalytes

15. De l’échantillon clinique aux données biologiques: approche
modulaire
Clinical sample
Cellular TME:
- ImmunoHistoChemistry
- FACS, 3 Ab panels
Soluble TME:
- Multiple Analyte Profiling
- Tumor infiltrating lymphocyte
secretion profiles
- Functional effect of tumor-derived
supernatants
Clinical data
Diagnosis / Follow-up
Extracellular Matrix
composition :
ImmunoHistoChemistry
Glucose
Metabolism
Oxidative stress
Transcriptomic:
Epithelial and Stromal
compartments
Human breast or ovarian cancer
450 patients included to date

16. Caractérisation de la diversité du microenvironnement
cellulaire
DC
CD4+ T cells, CD8+ T cells, B cells, NK cells
Joyce et al. Nat Rev Cancer 2009
+ T
BMDC
Macrophage
Neutrophil
Mast cell
MDSC
MSC Fibroblast
Lymphocyte
TEM Endothelial cell
Pericyte
Blood vessel
LyLymphocyLy
Normal epithelial cell
Tumor epithelial cell
Lymphatic endothelial cell

17. De l’échantillon clinique aux données biologiques: approche
modulaire
Clinical sample
Cellular TME:
- ImmunoHistoChemistry
- FACS, 3 Ab panels
Soluble TME:
- Multiple Analyte Profiling
- Tumor infiltrating lymphocyte
secretion profiles
- Functional effect of tumor-derived
supernatants
Clinical data
Diagnosis / Follow-up
Extracellular Matrix
composition :
ImmunoHistoChemistry
Glucose
Metabolism
Oxidative stress
Transcriptomic:
Epithelial and Stromal
compartments
Human breast or ovarian cancer
450 patients included to date

18. INTEGRATIVE ANALYSIS
DATA INTEGRATION
1
2
3
5
4
55
DATA QUERY
Sam ple Type
+
Pathology
+
Biotechnology
+
Gene A
Scientist / Clinician
KDI core
system
Detection of new target
6
DATAPRE-PROCESSING
Web applications
m odules
Sam ple
Patient
Clinical data
Low throughput
biotechnological
platform
High-throughput
biotechnological
platform
Low-throughput
biotechnological
platform
Analysis pipelines
SaSS m ple TyTT pe
+
PaPP thology
+
Biotechnology
+
Gene A
KDDDI core
syyyyysssssttttteeeeemmmmm
Detection of new
66
Anal
WEBSERVICES(SOAP)
Clinical data
Alteration data
- DNA copy number
- mutations
Expression data
- gene expression
« ClinicalDB »
« BIRD »
« Bioinfo-Portal »
Biological data
- Histological Analyzis
- Cellular phenotyping
- Supernatant Analysis
- Functional Experiments
«Algebra»
«Gersimi»
De l’échantillon tumoral à l’intégration des données:
un circuit “haute fidélité”

19. Apply T-MEGA datasetTheoritical modeling
Antonio Cappucio
2/ Modeling
Today
1/ Biostatistical analysis
Prognostic/Predictive
Biomarkers
3/ Biomarkers and therapeutic targets
T-MEGA: état d’avancement des analyses de données
LE.*RE LE.*RS
LS.*RE
LS.*RS
SE
Co-segregation of biological parameters
Yann Kieffer, Marine Jeanmougin

20. T-MEGA people:
Fatima Mechta-Grigoriou, PhD: Coordinator
Vassili Soumelis, MD-PhD: Coordinator
Alix Scholer-Dahirel: Project Manager
Philemon Sirven: Bioengineer
Melissa Cardon: Bioengineer (SIRIC)
Gerome Jules-Clement: Data Manager
Yann Kieffer: Bioinformatician
Marine Jeanmougin: Bioinformatician
Sofia Honorio-Grand: CRA
Sponsors:
T-MEGA: ressources humaines et financières
INCAPIC
Industrial
Partner
ARC
ITMO
PIC
ARC
Industrial
Partner
INCA
SIRIC ICGEX FRM

21. Importance du soutien financier: dynamiser et péréniser
Ø Personnel: la plupart en CDD financé par des contrats de recherche de
durée limitée
Ø Analyses biologiques modulaires: financer des modules déjà
plannifiés ou ajouter de nouveaux modules
Ø Etendre le programme à d’autres tumeurs: cancer du sein, ovaire
Ø Permettre la pérénisation pour répondre à des questions cliniques sur
l’évolution des cancers
Ø Initier le développement de nouvelles thérapeutiques ciblant le micro-
environnement
Clinical sample
Cellular TME:
- ImmunoHistoChemistry
- FACS, 3 Ab panels
Soluble TME:
- Multiple Analyte Profiling
- Tumor infiltrating
lymphocyte secretion profiles
- Functional effect of tumor-
derived supernatants
Clinical data
Diagnosis / Follow-up
Extracellular Matrix
composition :
ImmunoHistoChemistry
Glucose
Metabolism
Oxidative
stresssupernatants
Transcriptomic:
Epithelial and Stromal
compartments

22. Merci Fatima

23. Merci à toutes et à tous pour votre intérêt et
votre soutien