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Visual Proteomics SIGNED

Biomarker discovery by AI-guided, image based single-cell isolation proteomics

Total Cost €

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EC-Contrib. €

0

Partnership

0

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 Visual Proteomics project word cloud

Explore the words cloud of the Visual Proteomics project. It provides you a very rough idea of what is the project "Visual Proteomics" about.

prediction    profiling    career    impede    individually    receive    ubiquitous    cell    patient    disease    isolated    early    biomarkers    exploits    attempt    proteome    me    heterogeneity    stimulate    perform    expression    class    cells    collaborative    cellular    proteins    tumor    individual    identity    unresolved    cutting    form    samples    protein    tissue    microscopy    biobank    learning    training    optimize    machine    microdissection    populations    sensitivity    averaged    edge    critical    ground    diagnosis    diseases    workflow    tissues    ffpe    expertise    outcome    molecular    critically    clinical    personalized    pipeline    cancer    techniques    intelligence    severe    acquisition    fertile    complement    detection    laser    solid    competitive    world    niche    map    discoveries    correlate    pathology    therapies    host    retrospective    artificial    image    guided    morphology    array    followed    composition    inspire    automated    laboratory    shown    prospective    limited    descriptions    archival    treatment    outside    candidates    resolution    microscopic    biomarker    survival    malignancies    proteomics    unprecedented   

Project "Visual Proteomics" data sheet

The following table provides information about the project.

Coordinator
KOBENHAVNS UNIVERSITET 

Organization address
address: NORREGADE 10
city: KOBENHAVN
postcode: 1165
website: www.ku.dk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Denmark [DK]
 Total cost 207˙312 €
 EC max contribution 207˙312 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2018
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2019
 Duration (year-month-day) from 2019-04-01   to  2021-03-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    KOBENHAVNS UNIVERSITET DK (KOBENHAVN) coordinator 207˙312.00

Map

 Project objective

Early detection of severe malignancies such as cancer is the most effective way to increase patient survival, but early diagnosis and prediction of treatment outcome critically depend on disease-specific biomarkers. However, molecular and cellular disease heterogeneity provide a ubiquitous and unresolved challenge to this important task, and therefore impede any attempt to develop personalized therapies. Past and current approaches provide “averaged” descriptions of the tumor composition and have shown very limited success to identify biomarkers. This is likely due to the failure of these methods to identify the critical disease promoting cell populations within the tumor. Therefore, I will develop a new workflow that exploits automated microscopic image acquisition and artificial-intelligence-guided image analysis to identify specific cell populations in patient samples. These cells are then individually isolated by laser microdissection, followed by high-sensitivity proteome profiling, to identify proteins that define the identity of individual cells in a given tumor and thus represent the most promising biomarker candidates. To apply my approach to wide array of diseases, I will optimize it for archival biobank tissues (FFPE), the most common form of solid tissues in pathology. Applied to FFPE samples, my approach will allow me to perform both prospective and retrospective studies, correlate disease state and tissue morphology to protein expression and clinical outcome, and map tumor heterogeneity with unprecedented resolution. To achieve this, I will receive world-class training in cutting-edge microscopy and machine learning techniques in my host laboratory, which I complement with my expertise in high-sensitivity proteomics. My new pipeline will offer a highly fertile ground for new biomarker discoveries, inspire and stimulate collaborative research within and outside the host institute and allow me to establish a highly competitive niche for my future career.

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The information about "VISUAL PROTEOMICS" are provided by the European Opendata Portal: CORDIS opendata.

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