Decoding leukemia-immune cell dynamics by organism-wide cellular interaction mapping

Projektinformationen

InteractOmics

ID Finanzhilfevereinbarung: 101078713

DOI

10.3030/101078713

EK-Unterschriftsdatum 30 Januar 2023

Startdatum 1 Februar 2023

Enddatum 31 Januar 2028

Finanziert unter

• European Research Council (ERC)

Gesamtkosten

€ 1 499 596,00

EU-Beitrag

€ 1 499 596,00

Koordiniert durch

CHARITE - UNIVERSITAETSMEDIZIN BERLIN
Germany

Periodic Reporting for period 1 - InteractOmics (Decoding leukemia-immune cell dynamics by organism-wide cellular interaction mapping)

Berichtszeitraum: 2023-02-01 bis 2025-07-31

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

Cells in our body constantly communicate with each other to keep us healthy. This is especially true for the immune system, which helps protect us from infections and diseases, including cancer. In leukemia—a type of blood cancer—immune cells and cancer cells interact in complex ways. Some of these interactions help the immune system fight the cancer, while others allow the cancer to escape and keep growing. Understanding these interactions is key to improving treatments.
Right now, scientists have limited tools to study these complex cell-to-cell interactions in a detailed way. This makes it difficult to fully understand how immune cells and leukemia cells interact and why some patients respond well to immunotherapy (a treatment that helps the immune system fight cancer) while others do not.
To address this, we are developing a new approach called “interact-omics”. This method will allow us to study cell interactions across entire organs, organisms, and groups of patients. By applying this approach we aim to improve our understanding of how immune and leukemia cells communicate and lay the groud for predicting therapy response to immunotherapies in a personalized manner.
Overall, our work aims at providing a deeper understanding of how leukemia interacts with the immune system. This knowledge can help develop better immunotherapies, improve treatment strategies, and serve as a model for studying other diseases.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

In the first phase of our funding period, we successfully developed the “interact-omics” technological framework, enabling the mapping of cellular interactions at an ultra-high scale. We rigorously benchmarked this approach and demonstrated its wide applicability across various model systems and research areas (see Scientific Reporting PDF for details).

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

Our preliminary results suggest that “interact-omics” can help uncover the mechanisms behind therapy response to bispecific antibodies, a widely used immunotherapy, and may even predict personalized treatment outcomes. We are now expanding and validating these findings in larger patient groups. Ultimately, our goal is to develop a response prediction tool that could guide personalized treatment decisions. To advance this, we are currently exploring its potential within the framework of an ERC Proof-of-Concept grant.