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MESI-STRAT SIGNED

Systems Medicine of Metabolic-Signaling Networks: A New Concept for Breast Cancer Patient Stratification

Total Cost €

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EC-Contrib. €

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Partnership

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 MESI-STRAT project word cloud

Explore the words cloud of the MESI-STRAT project. It provides you a very rough idea of what is the project "MESI-STRAT" about.

cohorts    patient    bioinformaticians    serum    tumors    models    monitoring    stratification    fluids    surgical    prior    mechanisms    quality    disease    risk    reducing    endocrine    clinical    metabolism    co    collection    measured    explored    matched    mesi    ineffective    subgroups    estrogen    prevalence    therapy    predictive    trial    strat    resistant    detection    networks    breast    oncologists    industrial    combination    experimentalists    preclinical    omics    organization    tissue    therapies    explore    gt    closely    signaling    decision    bc    network    receptor    modelers    patients    resistance    er    accelerate    effectiveness    smes    et    translation    interventions    biological    panels    jointly    panel    ending    metabolic    health    cancer    poorly    guide    relapse    medical    metabolite    marker    accounts    data    validation    positive    follow    body    care    treatments    diagnostics    highest    pharmacogenomics    driving    longitudinal    integrate    avoiding    life    computational    team    75    mechanism    recurrence    successful   

Project "MESI-STRAT" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITAET INNSBRUCK 

Organization address
address: INNRAIN 52
city: INNSBRUCK
postcode: 6020
website: http://www.uibk.ac.at

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 Austria [AT]
 Project website http://www.mesi-strat.eu
 Total cost 5˙949˙963 €
 EC max contribution 5˙949˙963 € (100%)
 Programme 1. H2020-EU.3.1.1. (Understanding health, wellbeing and disease)
 Code Call H2020-SC1-2017-Two-Stage-RTD
 Funding Scheme RIA
 Starting year 2018
 Duration (year-month-day) from 2018-01-01   to  2022-09-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITAET INNSBRUCK AT (INNSBRUCK) coordinator 1˙609˙163.00
2    DEUTSCHES KREBSFORSCHUNGSZENTRUM HEIDELBERG DE (HEIDELBERG) participant 870˙100.00
3    UNIVERSITETET I BERGEN NO (BERGEN) participant 679˙520.00
4    CHARITE - UNIVERSITAETSMEDIZIN BERLIN DE (BERLIN) participant 398˙706.00
5    UNIVERSITETET I TROMSOE - NORGES ARKTISKE UNIVERSITET NO (TROMSO) participant 366˙925.00
6    UNIVERSITATSKLINIKUM HEIDELBERG DE (HEIDELBERG) participant 353˙682.00
7    DE DUVE INSTITUTE BE (BRUXELLES) participant 289˙000.00
8    UNIVERSITY OF NEWCASTLE UPON TYNE UK (NEWCASTLE UPON TYNE) participant 258˙687.00
9    STIFTUNG PATIENTS TUMORBANK OF HOPE- DIE PATIENTENEIGENE TUMORGEWEBEBANK DER HOFFNUNG (PATH) DE (AUGSBURG) participant 250˙550.00
10    HITS GGMBH DE (HEIDELBERG) participant 224˙687.00
11    ACADEMISCH ZIEKENHUIS GRONINGEN NL (GRONINGEN) participant 223˙524.00
12    FUNDACIO PRIVADA INSTITUT D'INVESTIGACIO ONCOLOGICA DE VALL-HEBRON ES (BARCELONA) participant 190˙956.00
13    NEUROIMMUN GMBH DE (KARLSRUHE) participant 131˙750.00
14    SYSBIOSIM BV NL (LEIDEN) participant 102˙711.00
15    UNIVERSITY OF DURHAM UK (DURHAM) participant 0.00

Map

 Project objective

Breast cancer (BC) is a complex disease with high prevalence in the EU. 75% of the tumors are estrogen receptor-positive (ER), and are treated with endocrine therapies (ET). MESI-STRAT will develop new concepts for knowledge-based stratification of patients into subgroups with different ET resistance mechanisms. We will establish predictive models for (1) patient stratification prior and during ET; (2) recurrence risk assessment when ending ET; (3) marker panel development to guide targeted therapies for ET-resistant patients; (4) novel ET resistance mechanism-based therapy design.

The unique collection of matched BC tissue, serum, and >10 years follow-up from the patient organization PATH is essential for the longitudinal analysis of ET resistance and relapse. Our team of oncologists, modelers, bioinformaticians and experimentalists will develop new computational models in combination with network analyses and pharmacogenomics, to integrate multi-omics data and explore metabolic and signaling (MESI) networks driving ET resistance. Metabolite marker panels measured in biological fluids will enable patient stratification, resistance monitoring and clinical decision-making. This is a new concept as BC metabolism is poorly explored for diagnostics and therapy. Upon successful validation in preclinical models, the predictive marker panels and related treatments will be jointly investigated by our clinical and industrial partners in clinical studies. Our 3 SMEs will closely co-develop the research, and directly exploit the MESI-STRAT results. BC accounts for the highest cancer-related health-care costs in the EU. Our stratification concepts will increase cost effectiveness and the patients’ quality of life by (1) avoiding ineffective therapies, (2) marker detection in body fluids without surgical interventions, and (3) reducing clinical trial cohorts by improved stratification. This will accelerate the translation of MESI-STRAT results into medical use.

 Deliverables

List of deliverables.
MESI-STRAT website with continuous updates Websites, patent fillings, videos etc. 2020-04-07 22:43:30

Take a look to the deliverables list in detail:  detailed list of MESI-STRAT deliverables.

 Publications

year authors and title journal last update
List of publications.
2019 Mayra Diosa-Toro, Berit Troost, Denise van de Pol, Alexander Martin Heberle, Silvio Urcuqui-Inchima, Kathrin Thedieck, Jolanda M. Smit
Tomatidine, a novel antiviral compound towards dengue virus
published pages: 90-99, ISSN: 0166-3542, DOI: 10.1016/j.antiviral.2018.11.011
Antiviral Research 161 2020-04-07
2018 Mahdi Shafiee Kamalabad, Alexander Martin Heberle, Kathrin Thedieck, Marco Grzegorczyk
Partially non-homogeneous dynamic Bayesian networks based on Bayesian regression models with partitioned design matrices
published pages: 2108-2117, ISSN: 1367-4803, DOI: 10.1093/bioinformatics/bty917
Bioinformatics 35/12 2020-04-07
2019 Michael Platten, Ellen A. A. Nollen, Ute F. Röhrig, Francesca Fallarino, Christiane A. Opitz
Tryptophan metabolism as a common therapeutic target in cancer, neurodegeneration and beyond
published pages: 379-401, ISSN: 1474-1776, DOI: 10.1038/s41573-019-0016-5
Nature Reviews Drug Discovery 18/5 2020-04-07
2019 Alexander Martin Heberle, Patricia Razquin Navas, Miriam Langelaar-Makkinje, Katharina Kasack, Ahmed Sadik, Erik Faessler, Udo Hahn, Philip Marx-Stoelting, Christiane A Opitz, Christine Sers, Ines Heiland, Sascha Schäuble, Kathrin Thedieck
The PI3K and MAPK/p38 pathways control stress granule assembly in a hierarchical manner
published pages: e201800257, ISSN: 2575-1077, DOI: 10.26508/lsa.201800257
Life Science Alliance 2/2 2020-04-07

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