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DrugComb SIGNED

Informatics approaches for the rational selection of personalized cancer drug combinations

Total Cost €

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EC-Contrib. €

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Partnership

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Project "DrugComb" 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 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.

# participants  country  role  EC contrib. [€] 
1    HELSINGIN YLIOPISTO FI (HELSINGIN YLIOPISTO) coordinator 1˙500˙000.00

Map

 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
List of publications.
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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