DrugComb SIGNED
Informatics approaches for the rational selection of personalized cancer drug combinations
Total Cost €
0EC-Contrib. €
0Partnership
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0DrugComb project word cloud
Explore the words cloud of the DrugComb project. It provides you a very rough idea of what is the project "DrugComb" about.
Project "DrugComb" data sheet
The following table provides information about the project.
| Coordinator |
HELSINGIN YLIOPISTO
Organization address contact info |
| Coordinator Country | Finland [FI] |
| Project website | https://drugcomb.fimm.fi/ |
| Total cost | 1˙500˙000 € |
| EC max contribution | 1˙500˙000 € (100%) |
| Programme |
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC)) |
| Code Call | ERC-2016-STG |
| Funding Scheme | ERC-STG |
| Starting year | 2017 |
| Duration (year-month-day) | from 2017-06-01 to 2022-05-31 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | HELSINGIN YLIOPISTO | FI (HELSINGIN YLIOPISTO) | coordinator | 1˙500˙000.00 |
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Project objective
Making cancer treatment more personalized and effective is one of the grand challenges in our health care system. However, many drugs have entered clinical trials but so far showed limited efficacy or induced rapid development of resistance. We critically need multi-targeted drug combinations, which shall selectively inhibit the cancer cells and block the emergence of drug resistance. This project will develop mathematical and computational tools to identify drug combinations that can be used to provide personalized and more effective therapeutic strategies that may prevent acquired resistance. Utilizing molecular profiling and pharmacological screening data from patient-derived leukaemia and ovarian cancer samples, I will develop model-based clustering methods for identification of patient subgroups that are differentially responsive to first-line chemotherapy. For patients resistant to chemotherapy, I will develop network modelling approaches to predict the most potential drug combinations by understanding the underlying drug target interactions. The drug combination prediction will be made for each patient and will be validated using a preclinical drug testing platform on patient samples. I will explore the drug combination screen data to identify significant synergy at the therapeutically relevant doses. The drug combination hits will be mapped into signalling networks to infer their mechanisms. Drug combinations with selective efficacy in individual patient samples or in sample subgroups will be further translated into in treatment options by clinical collaborators. This will lead to novel and personalized strategies to treat cancer patients.
Publications
| year | authors and title | journal | last update |
|---|---|---|---|
| 2017 |
Ulla-Maija Haltia, Noora Andersson, Bhagwan Yadav, Anniina Färkkilä, Evgeny Kulesskiy, Matti Kankainen, Jing Tang, Ralf Bützow, Annika Riska, Arto Leminen, Markku Heikinheimo, Olli Kallioniemi, Leila Unkila-Kallio, Krister Wennerberg, Tero Aittokallio, Mikko Anttonen Systematic drug sensitivity testing reveals synergistic growth inhibition by dasatinib or mTOR inhibitors with paclitaxel in ovarian granulosa cell tumor cells published pages: 621-630, ISSN: 0090-8258, DOI: 10.1016/j.ygyno.2016.12.016 |
Gynecologic Oncology 144/3 | 2020-02-20 |
| 2017 |
Aleksandr Ianevski, Liye He, Tero Aittokallio, Jing Tang SynergyFinder: a web application for analyzing drug combination dose–response matrix data published pages: 2413-2415, ISSN: 1367-4803, DOI: 10.1093/bioinformatics/btx162 |
Bioinformatics 33/15 | 2020-02-20 |
| 2019 |
Michael P. Menden, Dennis Wang, Mike J. Mason, Bence Szalai, Krishna C. Bulusu, Yuanfang Guan, Thomas Yu, Jaewoo Kang, Minji Jeon, Russ Wolfinger, Tin Nguyen, Mikhail Zaslavskiy, In Sock Jang, Zara Ghazoui, Mehmet Eren Ahsen, Robert Vogel, Elias Chaibub Neto, Thea Norman, Eric K. Y. Tang, Mathew J. Garnett, Giovanni Y. Di Veroli, Stephen Fawell, Gustavo Stolovitzky, Justin Guinney, Jonathan R. Dry Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen published pages: , ISSN: 2041-1723, DOI: 10.1038/s41467-019-09799-2 |
Nature Communications 10/1 | 2020-02-20 |
| 2018 |
E I Andersson, S Pützer, B Yadav, O Dufva, S Khan, L He, L Sellner, A Schrader, G Crispatzu, M Oleś, H Zhang, S Adnan-Awad, S Lagström, D Bellanger, J P Mpindi, S Eldfors, T Pemovska, P Pietarinen, A Lauhio, K Tomska, C Cuesta-Mateos, E Faber, S Koschmieder, T H Brümmendorf, S Kytölä, E-R Savolainen, T Siitonen, P Ellonen, O Kallioniemi, K Wennerberg, W Ding, M-H Stern, W Huber, S Anders, J Discovery of novel drug sensitivities in T-PLL by high-throughput ex vivo drug testing and mutation profiling published pages: 774-787, ISSN: 0887-6924, DOI: 10.1038/leu.2017.252 |
Leukemia 32/3 | 2020-02-20 |
| 2019 |
Alina Malyutina, Muntasir Mamun Majumder, Wenyu Wang, Alberto Pessia, Caroline A. Heckman, Jing Tang Drug combination sensitivity scoring facilitates the discovery of synergistic and efficacious drug combinations in cancer published pages: e1006752, ISSN: 1553-7358, DOI: 10.1371/journal.pcbi.1006752 |
PLOS Computational Biology 15/5 | 2019-09-04 |
| 2019 |
Bulat Zagidullin, Jehad Aldahdooh, Shuyu Zheng, Wenyu Wang, Yinyin Wang, Joseph Saad, Alina Malyutina, Mohieddin Jafari, Ziaurrehman Tanoli, Alberto Pessia, Jing Tang DrugComb: an integrative cancer drug combination data portal published pages: W43-W51, ISSN: 0305-1048, DOI: 10.1093/nar/gkz337 |
Nucleic Acids Research 47/W1 | 2019-09-04 |
| 2018 |
Jing Tang, Zia-ur-Rehman Tanoli, Balaguru Ravikumar, Zaid Alam, Anni Rebane, Markus Vähä-Koskela, Gopal Peddinti, Arjan J. van Adrichem, Janica Wakkinen, Alok Jaiswal, Ella Karjalainen, Prson Gautam, Liye He, Elina Parri, Suleiman Khan, Abhishekh Gupta, Mehreen Ali, Laxman Yetukuri, Anna-Lena Gustavsson, Brinton Seashore-Ludlow, Anne Hersey, Andrew R. Leach, John P. Overington, Gretchen Repasky, Krister Wennerberg, Tero Aittokallio Drug Target Commons: A Community Effort to Build a Consensus Knowledge Base for Drug-Target Interactions published pages: 224-229.e2, ISSN: 2451-9456, DOI: 10.1016/j.chembiol.2017.11.009 |
Cell Chemical Biology 25/2 | 2019-06-13 |
| 2017 |
Aleksandr Ianevski, Liye He, Tero Aittokallio, Jing Tang SynergyFinder: a web application for analyzing drug combination dose–response matrix data published pages: 2413-2415, ISSN: 1367-4803, DOI: 10.1093/bioinformatics/btx162 |
Bioinformatics 33/15 | 2019-06-13 |
| 2019 |
Emma Cazaly, Joseph Saad, Wenyu Wang, Caroline Heckman, Miina Ollikainen, Jing Tang Making Sense of the Epigenome Using Data Integration Approaches published pages: , ISSN: 1663-9812, DOI: 10.3389/fphar.2019.00126 |
Frontiers in Pharmacology 10 | 2019-05-28 |
| 2018 |
Liye He, Jing Tang, Emma I. Andersson, Sanna Timonen, Steffen Koschmieder, Krister Wennerberg, Satu Mustjoki, Tero Aittokallio Patient-Customized Drug Combination Prediction and Testing for T-cell Prolymphocytic Leukemia Patients published pages: 2407-2418, ISSN: 0008-5472, DOI: 10.1158/0008-5472.can-17-3644 |
Cancer Research 78/9 | 2019-05-28 |
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