Network Biology for Immuno-oncology
OF OUR RESEARCH AXIS
Our lab studies the relationship between patients and cancer, focusing on how the immune system and the tumour interact. We aim to improve therapies that exploit this interaction. Currently such therapies only work on some patients and, often, for a limited time before patients develop resistance against the therapy.
Our goal is to understand how variability in the patients, in the tumours, and in their interactions affects the efficacy of these therapies. We use computational approaches including data science, simulations, modeling and especially network theory.
Networks are a useful framework to represent systems in which relationships such as interactions or similarity between objects are important. All networks share some common properties and a vast literature exists on how to measure them. The beauty is that our understanding of one type of network can help us better understand a completely different one.
We apply network models to study such diverse systems as networks of patient-patient similarity, networks of interactions between different cell types in a tumour, and 3D interactions of genes in the nucleus.
In the same healthy organism, two cells of the same type, sharing the same DNA, can still display some variability, due to the organization of more than two meters of DNA in a tiny nucleus. These changes in DNA configuration impact the characteristics and behavior of the cells.
The important common factor characterising these systems is variability.
Variability pervades biological systems. On one side, the difference between patients is thwarting our successes in medicine and calls for personalised medicine approaches, especially in oncology. On the other side, there are many contexts within the body characterised by a heterogeneous mix of cell types; for example the gut, the bone marrow or the tissue surrounding a tumour. Complex relationships between cell types establish ‘ecological networks’ whose properties reflect the equilibria that define health against disease.
The variety of cell types in the tumor and their relationships:
Determining the cellular composition and organization of a tumour sample remains the priority in cancer research. Our team integrates omics data to estimate the proportions of different cell types and their spatial relationships in the tumor.
Simulating the complex interactions of these cells in our computers, both at the molecular and intercellular level, offers the possibility to study these systems in a multitude of scenarios. This is an excellent way to formulate new hypotheses and allows better use of our experimental resources.
Since 2020 we have launched collaborative projects with other CRCT teams with the co-supervision of 4 theses:
Rüçhan Ekren (Labex Toucan grant), with Ludovic Martinet. Study of T cell depletion mechanisms and NK cell biology in multiple myeloma, using single cell approaches on proteomic and transcriptomic (CITEseq) datasets (human or mouse).
Matthieu Genais (BSB doctoral school grant), with Bruno Segui. Artificial intelligence approaches to determine the impact of TNFa on the response to immune checkpoint inhibitors (ICB) in melanoma. Use of clinical, CITEseq and metabolomic data.
Alexis Hucteau (Labex Toucan grant), with J.E Sarry. Study of acute myeloid leukemia and specific metabolic resistances by combining RNAseq, DNA methylation, histone modifications, metabolic connections, epigenomics and reprogramming approaches.
Jacobo Solorzano (scholarship from Occitanie region and Fondation Toulouse Cancer Santé ), with Yvan Martineau and Corinne Bousquet. Translation and role of stromal cells (particularly CAFs) in the emergence of cancer cells activating the integrated stress response (ISR) in pancreatic cancers.
Heterogeneity and Tumour Microenvironment
Spatial and single cell transcriptomics
Deconvolution: description of the composition of the tumour microenvironment, towards personalised medicine
PARTNERSHIPS & funding
Centre de Recherches en Cancérologie de Toulouse (Oncopole)
Toulouse – FR
05 82 74 15 75
Envie de rejoindre
L’équipe du CRCT ?