Decoding leukemia-immune cell dynamics by organism-wide cellular interaction mapping
Develop a novel 'interact-omics' approach to analyze cellular interactions in leukemia, aiming to enhance understanding of immune responses and therapy resistance mechanisms.
Projectdetails
Introduction
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.
Importance in Leukemias
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 of these highly complex and dynamic processes.
Proposed Approach
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.
Application of the Approach
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, systematically decode the cellular logic of how the complex leukemia-immune interplay determines the disease course.
Understanding Therapy Resistance
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.
- Predict therapy response.
Conclusion
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. It may serve as a blueprint to fundamentally expand our insights into other biological processes driven by cellular interactions.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.499.596 |
Totale projectbegroting | € 1.499.596 |
Tijdlijn
Startdatum | 1-2-2023 |
Einddatum | 31-1-2028 |
Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- CHARITE - UNIVERSITAETSMEDIZIN BERLINpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
Mechanistic models of leukemia-niche interaction using multimodal single cell profilingThis project aims to uncover AML's interactions with the bone marrow niche through advanced single-cell sequencing and modeling, potentially transforming treatment strategies for hematological malignancies. | ERC Consolid... | € 2.000.000 | 2022 | Details |
Elucidating the networks of immune stromal connections by Perturbation of Immunity in Cancer - towards developing novel therapeutic strategiesThis project aims to map immune and stromal cell interactions in the tumor microenvironment to develop targeted therapies that enhance immunotherapy efficacy against cancer. | ERC Starting... | € 1.500.000 | 2025 | Details |
Elucidating the Spatial and Temporal Dynamics of Acute Myeloid Leukemia Progression Using Functional Omics and High-Throughput In Vivo ScreeningThis project aims to explore the spatial and temporal dynamics of tumor progression in Acute Myeloid Leukemia to identify critical factors influencing cancer pathogenicity and potential therapeutic targets. | ERC Consolid... | € 1.994.500 | 2024 | Details |
Understanding the functional role of Immune-related Intercellular Signalling Networks during tissue Development and CancerThis project aims to uncover immune-related intercellular crosstalk in tissue development and cancer using single-cell RNA-sequencing and functional assays to identify novel therapeutic targets. | ERC Starting... | € 2.025.000 | 2022 | Details |
Unmasking the dynamic influence of the hematopoietic niche as an oncogenic path to myeloid neoplasms evolutionThis project aims to explore hematopoietic-niche interactions across myeloid neoplasm stages to develop innovative therapies that prevent acute myeloid leukemia and improve patient outcomes. | ERC Starting... | € 1.911.428 | 2024 | Details |
Mechanistic models of leukemia-niche interaction using multimodal single cell profiling
This project aims to uncover AML's interactions with the bone marrow niche through advanced single-cell sequencing and modeling, potentially transforming treatment strategies for hematological malignancies.
Elucidating the networks of immune stromal connections by Perturbation of Immunity in Cancer - towards developing novel therapeutic strategies
This project aims to map immune and stromal cell interactions in the tumor microenvironment to develop targeted therapies that enhance immunotherapy efficacy against cancer.
Elucidating the Spatial and Temporal Dynamics of Acute Myeloid Leukemia Progression Using Functional Omics and High-Throughput In Vivo Screening
This project aims to explore the spatial and temporal dynamics of tumor progression in Acute Myeloid Leukemia to identify critical factors influencing cancer pathogenicity and potential therapeutic targets.
Understanding the functional role of Immune-related Intercellular Signalling Networks during tissue Development and Cancer
This project aims to uncover immune-related intercellular crosstalk in tissue development and cancer using single-cell RNA-sequencing and functional assays to identify novel therapeutic targets.
Unmasking the dynamic influence of the hematopoietic niche as an oncogenic path to myeloid neoplasms evolution
This project aims to explore hematopoietic-niche interactions across myeloid neoplasm stages to develop innovative therapies that prevent acute myeloid leukemia and improve patient outcomes.