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Deep Spatial Proteomics: connecting cellular neighbourhoods to functional states

Project description

Linking subcellar proteomes with cell function

Cells carry out biochemical reactions in distinct subcellular regions, ensuring efficiency and regulation of cellular functions. Understanding how these spatially defined interactions influence health and disease is crucial, since disruptions can drive pathological conditions like cancer. However, systematic analysis of these interactions at the proteome level remains challenging. The ERC-funded Spatial Proteomics project aims to develop a multimodal strategy that integrates immunofluorescence imaging, machine learning and single-cell mass spectrometry to delineate proteomic states in subcellular compartments. Researchers will employ this approach to investigate cells critical for immunotherapy response, uncover resistance mechanisms and identify predictive biomarkers. This technology has the potential to extend beyond cancer in other proteomics applications.

Objective

Health and disease states result from dynamic cellular interactions within spatially defined regions in tissues and organs. In diseases such as cancer, these interactions are often disturbed, but their systematic analysis with respect to their impact on the proteome, a close proxy for cellular function, has so far remained elusive. To overcome this major bottleneck in molecular biosciences, I propose to develop and apply Deep Spatial Proteomics (DSP), a multimodal strategy, which for the first time will link distinct cellular neighbourhoods within biological samples to functional proteome states. DSP will combine multiplex immunofluorescence imaging and machine-learning driven cellular neighbourhood profiling with single-cell sensitivity mass spectrometry (MS) based proteomics. Our preliminary data support the feasibility and strong potential of DSP to uncover novel disease mechanisms, drug targets and predictive biomarkers. After development and rigorous benchmarking, we will apply DSP to an already available retrospective cohort of advanced head and neck squamous cell carcinoma, where response rates for anti-cancer immunotherapy are only below twenty percent. The correlation of cell states and spatial neighbourhoods with clinical outcomes will allow us to identify cell communities of highest likelihood to be critical for treatment response and hence patient survival. Through their functional characterisation by deep MS based proteomics, we will not only gain unique biological insights into immunotherapy resistance and potential therapeutic targets, but also identify predictive candidate markers to improve patient stratification. This new concept will have strong implications for basic and translational research, far beyond the study of cancer immunotherapy. DSP could pave the way for a plethora of spatial proteomics applications with countless opportunities for discovery-driven biomedical research.

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Programme(s)

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Topic(s)

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2023-STG

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Host institution

MAX DELBRUECK CENTRUM FUER MOLEKULARE MEDIZIN IN DER HELMHOLTZ-GEMEINSCHAFT (MDC)
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 470 851,00
Address
ROBERT ROSSLE STRASSE 10
13125 Berlin
Germany

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Region
Berlin Berlin Berlin
Activity type
Research Organisations
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 470 851,00

Beneficiaries (1)

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