Summary
Cellular interactions are of fundamental importance in life, orchestrating organismal development, tissue homeostasis and immunity. In the immune system, cell-cell interactions act as central hubs for information processing and decision making that collectively determine the outcome of complex immune responses. In leukemias, a cancer originating from immature immune cells, a multilayered network of cellular interactions between immune and leukemic cells underlies effective immune control of the cancer, immune evasion and response to immunotherapies. However, technical limitations in studying cell-cell interactions restrict our understanding into these highly complex and dynamic processes. In order to overcome this limitation, I propose to develop a novel ‘interact-omics’ approach, capable of characterizing millions of cellular interactions across complex organ systems, entire organisms and patient cohorts. Applying the ‘interact-omics’ approach to sophisticated leukemia mouse models will enable us to dissect the dynamic cellular interaction networks between antigen-specific T cells, bystander immune cells and leukemic cells that drive anti-leukemia immunity and immune evasion. In combination with the in vivo perturbation of cellular interactions, this will allow us to systematically decode the cellular logic of how the complex leukemia-immune interplay determines the disease course. Additionally, by making use of leukemia patient cohorts which are either responsive or non-responsive to immunotherapy treatment, we will unravel previously unknown therapy resistance mechanisms and predict therapy response. Together, our approach will set the basis for a comprehensive understanding of the leukemia-immune cell crosstalk underlying immune control, immune escape and therapy response, and may serve as a blueprint to fundamentally expand our insights into other biological processes driven by cellular interactions.
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| Web resources: | https://cordis.europa.eu/project/id/101078713 |
| Start date: | 01-02-2023 |
| End date: | 31-01-2028 |
| Total budget - Public funding: | 1 499 596,00 Euro - 1 499 596,00 Euro |
Cordis data
Original description
Cellular interactions are of fundamental importance in life, orchestrating organismal development, tissue homeostasis and immunity. In the immune system, cell-cell interactions act as central hubs for information processing and decision making that collectively determine the outcome of complex immune responses. In leukemias, a cancer originating from immature immune cells, a multilayered network of cellular interactions between immune and leukemic cells underlies effective immune control of the cancer, immune evasion and response to immunotherapies. However, technical limitations in studying cell-cell interactions restrict our understanding into these highly complex and dynamic processes. In order to overcome this limitation, I propose to develop a novel ‘interact-omics’ approach, capable of characterizing millions of cellular interactions across complex organ systems, entire organisms and patient cohorts. Applying the ‘interact-omics’ approach to sophisticated leukemia mouse models will enable us to dissect the dynamic cellular interaction networks between antigen-specific T cells, bystander immune cells and leukemic cells that drive anti-leukemia immunity and immune evasion. In combination with the in vivo perturbation of cellular interactions, this will allow us to systematically decode the cellular logic of how the complex leukemia-immune interplay determines the disease course. Additionally, by making use of leukemia patient cohorts which are either responsive or non-responsive to immunotherapy treatment, we will unravel previously unknown therapy resistance mechanisms and predict therapy response. Together, our approach will set the basis for a comprehensive understanding of the leukemia-immune cell crosstalk underlying immune control, immune escape and therapy response, and may serve as a blueprint to fundamentally expand our insights into other biological processes driven by cellular interactions.Status
SIGNEDCall topic
ERC-2022-STGUpdate Date
09-02-2023
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