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HERCULES SIGNED

Comprehensive characterization and effective combinatorial targeting of high-grade serous ovarian cancer via single-cell analysis

Total Cost €

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EC-Contrib. €

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Partnership

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 HERCULES project word cloud

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

levels    efforts    treatment    retrospective    health    longitudinally    models    marked    strategy    translated    treatments    transcriptomics    care    patients    validated    lack    combination    predictive    comprehensively    metastatic    regimens    vivo    lasting    advantage    deaths    trial    drug    hgs    multiple    expensive    diagnostic    collected    predict    regimen    modalities    experiments    benefit    clinical    sorting    pharmaceutical    mass    hercules    biomarker    ex    cell    breakthrough    followed    prediction    fresh    industry    tumors    therapeutic    screening    error    takes    tools    populations    network    data    suggestions    kill    cancer    anatomic    combinatorial    paves    reduce    actionable    characterise    serous    prospective    multidisciplinary    fluorescence    inefficient    stratified    disease    clinically    decrease    single    combinations    patient    specimens    cohorts    right    commercialise    activated    toward    prospectively    genetic    individual    subpopulations    trials    kills    innovative    kit    cytometry    sites    grade    move    suggest    medicine    ovarian    ovca    systematic    women   

Project "HERCULES" data sheet

The following table provides information about the project.

Coordinator
HELSINGIN YLIOPISTO 

Organization address
address: YLIOPISTONKATU 3
city: HELSINGIN YLIOPISTO
postcode: 14
website: www.helsinki.fi

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 Finland [FI]
 Project website http://project-hercules.eu/
 Total cost 5˙994˙868 €
 EC max contribution 5˙994˙868 € (100%)
 Programme 1. H2020-EU.3.1.1. (Understanding health, wellbeing and disease)
 Code Call H2020-PHC-2015-two-stage
 Funding Scheme RIA
 Starting year 2016
 Duration (year-month-day) from 2016-01-01   to  2020-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    HELSINGIN YLIOPISTO FI (HELSINGIN YLIOPISTO) coordinator 2˙444˙812.00
2    TURUN YLIOPISTO FI (Turku) participant 999˙211.00
3    THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE UK (CAMBRIDGE) participant 566˙969.00
4    INSTITUT PASTEUR FR (PARIS CEDEX 15) participant 360˙101.00
5    ISTITUTO SUPERIORE DI SANITA IT (ROMA) participant 356˙250.00
6    UNIVERSITA DEGLI STUDI DI TRIESTE IT (TRIESTE) participant 350˙000.00
7    KAROLINSKA INSTITUTET SE (STOCKHOLM) participant 332˙712.00
8    VARSINAIS-SUOMEN SAIRAANHOITOPIIRIN KUNTAYHTYMA FI (TURKU) participant 297˙312.00
9    AB ANALITICA SRL IT (PADOVA) participant 287˙500.00

Map

 Project objective

The goal of this multidisciplinary project is to comprehensively characterise high-grade serous ovarian cancer (HGS-OvCa) at single-cell level, identify the best combination of drug combination to kill HGS-OvCa populations and commercialise a predictive biomarker kit for finding the right therapeutic regimen to the right patient.

This project takes an advantage on prospectively and longitudinally collected fresh sample specimens from multiple anatomic sites of HGS-OvCa patients with metastatic disease. Fluorescence activated cell sorting and recently developed mass cytometry are used to identify subpopulations in HGS-OvCa tumors. This is followed by single-cell analysis at genetic and transcriptomics levels, and ex vivo drug screening experiments. These data will be used to establish network models to predict the most effective combinatorial treatments. The key results will be validated with existing HGS-OvCa data together with prospective and retrospective cohorts and in vivo models. The clinically most actionable treatment suggestions from our modelling efforts will be translated to HGS-OvCa patient care.

Ovarian cancer kills more than 40,000 women in Europe every year due to lack of effective and long-lasting therapeutic regimens. HERCULES presents an innovative strategy to suggest effective treatments that lead to a marked decrease in ovarian cancer deaths and reduce the number of expensive but inefficient treatments. Our approach paves the way to move beyond the current trial-and-error clinical assessment of drug combinations toward more systematic prediction of the most effective drug combinations for each patient. The proposed approach will be a major breakthrough in systems medicine and will benefit individual ovarian cancer patients and the health-care system through more effective treatments, and the diagnostic and pharmaceutical industry through tools for better stratified clinical trials, and novel treatment and diagnostic modalities.

 Deliverables

List of deliverables.
Evaluation of flow cytometry and imaging-based clonal drug response assays Demonstrators, pilots, prototypes 2019-05-28 17:19:33
One or more software components that automate import and integration of modelling data into Cytoscape Other 2019-05-24 19:13:12
Project presentation produced Documents, reports 2019-05-24 16:49:29
Knowledge Management System up and running Websites, patent fillings, videos etc. 2019-05-24 16:49:28
Project Office with Operational Project Manager in place and Project Management Committee Websites, patent fillings, videos etc. 2019-05-24 16:49:28
A workflow for obtaining consents from advanced HGS-OvCa patients, and for collecting samples from the patients Documents, reports 2019-05-24 16:49:29
Data Management Plan Open Research Data Pilot 2019-05-24 16:49:28

Take a look to the deliverables list in detail:  detailed list of HERCULES deliverables.

 Publications

year authors and title journal last update
List of publications.
2018 Emilia Kozłowska, Anniina Färkkilä, Tuulia Vallius, Olli Carpén, Jukka Kemppainen, Seija Grénman, Rainer Lehtonen, Johanna Hynninen, Sakari Hietanen, Sampsa Hautaniemi
Mathematical Modeling Predicts Response to Chemotherapy and Drug Combinations in Ovarian Cancer
published pages: 4036-4044, ISSN: 0008-5472, DOI: 10.1158/0008-5472.can-17-3746
Cancer Research 78/14 2019-05-22
2018 J. Hynninen, M. Laasik, T. Vallius, J. Kemppainen, S. Grönroos, J. Virtanen, J. Casado, S. Hautaniemi, S. Grenman, M. Seppänen, A. Auranen
Clinical Value of 18 F-fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in Response Evaluation after Primary Treatment of Advanced Epithelial Ovarian Cancer
published pages: 507-514, ISSN: 0936-6555, DOI: 10.1016/j.clon.2018.04.007
Clinical Oncology 30/8 2019-05-22
2018 Antti Häkkinen, Amjad Alkodsi, Chiara Facciotto, Kaiyang Zhang, Katja Kaipio, Sirpa Leppä, Olli Carpén, Seija Grénman, Johanna Hynninen, Sakari Hietanen, Rainer Lehtonen, Sampsa Hautaniemi
Identifying differentially methylated sites in samples with varying tumor purity
published pages: 3078-3085, ISSN: 1367-4803, DOI: 10.1093/bioinformatics/bty310
Bioinformatics 34/18 2019-05-22
2018 Iryna Nikolayeva, Oriol Guitart Pla, Benno Schwikowski
Network module identification—A widespread theoretical bias and best practices
published pages: 19-25, ISSN: 1046-2023, DOI: 10.1016/j.ymeth.2017.08.008
Methods 132 2019-05-22

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

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