Explore the words cloud of the HERCULES project. It provides you a very rough idea of what is the project "HERCULES" about.
The following table provides information about the project.
|Coordinator Country||Finland [FI]|
|Total cost||5˙994˙868 €|
|EC max contribution||5˙994˙868 € (100%)|
1. H2020-EU.3.1.1. (Understanding health, wellbeing and disease)
|Duration (year-month-day)||from 2016-01-01 to 2020-12-31|
Take a look of project's partnership.
|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|
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.
|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.
|year||authors and title||journal||last update|
Emilia KozÅ‚owska, Anniina FÃ¤rkkilÃ¤, Tuulia Vallius, Olli CarpÃ©n, Jukka Kemppainen, Seija GrÃ©nman, 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|
J. Hynninen, M. Laasik, T. Vallius, J. Kemppainen, S. GrÃ¶nroos, J. Virtanen, J. Casado, S. Hautaniemi, S. Grenman, M. SeppÃ¤nen, 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|
Antti HÃ¤kkinen, Amjad Alkodsi, Chiara Facciotto, Kaiyang Zhang, Katja Kaipio, Sirpa LeppÃ¤, Olli CarpÃ©n, Seija GrÃ©nman, 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
Iryna Nikolayeva, Oriol Guitart Pla, Benno Schwikowski
Network module identificationâ€”A widespread theoretical bias and best practices
published pages: 19-25, ISSN: 1046-2023, DOI: 10.1016/j.ymeth.2017.08.008
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The information about "HERCULES" are provided by the European Opendata Portal: CORDIS opendata.