Explore the words cloud of the MicroC project. It provides you a very rough idea of what is the project "MicroC" about.
The following table provides information about the project.
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
|Coordinator Country||United Kingdom [UK]|
|Total cost||1˙996˙325 €|
|EC max contribution||1˙996˙325 € (100%)|
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
|Duration (year-month-day)||from 2018-06-01 to 2023-05-31|
Take a look of project's partnership.
|1||THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD||UK (OXFORD)||coordinator||1˙996˙325.00|
The occurrence of therapeutic resistance is a major cause for the small effect on overall survival showed by targeted cancer therapies. Whilst experimental strategies to evaluate available treatments have been faced by an ever increasing number of possible combinations, computational approaches have been challenged by the lack of a framework able to model the multiple interactions encompassed by the three major factors affecting therapeutic resistance: selection of resistant clones, adaptability of gene signalling networks, and a protective and hypoxic tumour microenvironment.
Here I propose a novel modelling framework, Agent-Based Modelling of Gene Networks, which brings together powerful computational modelling techniques and gene networks. This combination allows biological hypotheses to be tested in a controlled stepwise fashion, and it lends itself naturally to model a heterogeneous population of cells acting and evolving in a dynamic microenvironment, which is needed to predict therapeutic resistance and guide effective treatment selection.
Using triple negative breast cancer (TNBC) as a testing case (15% of breast cancers, lacks validated), I propose to:
1. Develop a computational model of the TNBC tumour microenvironment using in-vitro and in-vivo, including patient-derived, models and data from clinical samples. 2. Validate the ability of the model to predict driver genes conferring a survival advantage to cancer cells in a hypoxic microenvironment. 3. Predict combinations of druggable targets to tackle TNBC therapeutic resistance. 4. Select most effective drug combinations and validate pre-clinically.
This project will deliver pre-clinically validated drug combinations, new therapeutic targets and a virtual environment to study individual tumours and predict therapeutic resistance. Complementing and empowering experimental models and assays, microC will offer a new powerful tool for diagnosis and therapy.
|year||authors and title||journal||last update|
Simon R. Lord, Jennifer M. Collins, Wei-Chen Cheng, Syed Haider, Simon Wigfield, Edoardo Gaude, Barbara A. Fielding, Katherine E. Pinnick, Ulrike Harjes, Ashvina Segaran, Pooja Jha, Gerald Hoefler, Michael N. Pollak, Alastair M. Thompson, Pankaj G. Roy, Ruth. English, Rosie F. Adams, Christian Frezza, Francesca M. Buffa, Fredrik Karpe, Adrian L. Harris
Transcriptomic analysis of human primary breast cancer identifies fatty acid oxidation as a target for metformin
published pages: 258-265, ISSN: 0007-0920, DOI: 10.1038/s41416-019-0665-5
|British Journal of Cancer 122/2||2020-02-05|
Dimitrios Voukantsis, Kenneth Kahn, Martin Hadley, Rowan Wilson, Francesca M Buffa
Modeling genotypes in their microenvironment to predict single- and multi-cellular behavior
published pages: , ISSN: 2047-217X, DOI: 10.1093/gigascience/giz010
Simon R. Lord, Wei-Chen Cheng, Dan Liu, Edoardo Gaude, Syed Haider, Tom Metcalf, Neel Patel, Eugene J. Teoh, Fergus Gleeson, Kevin Bradley, Simon Wigfield, Christos Zois, Daniel R. McGowan, Mei-Lin Ah-See, Alastair M. Thompson, Anand Sharma, Luc Bidaut, Michael Pollak, Pankaj G. Roy, Fredrik Karpe, Tim James, Ruth English, Rosie F. Adams, Leticia Campo, Lisa Ayers, Cameron Snell, Ioannis Roxanis,
Integrated Pharmacodynamic Analysis Identifies Two Metabolic Adaption Pathways to Metformin in Breast Cancer
published pages: 679-688.e4, ISSN: 1550-4131, DOI: 10.1016/j.cmet.2018.08.021
|Cell Metabolism 28/5||2020-02-05|
Andrew Dhawan, Jacob G. Scott, Adrian L. Harris, Francesca M. Buffa
Pan-cancer characterisation of microRNA across cancer hallmarks reveals microRNA-mediated downregulation of tumour suppressors
published pages: , ISSN: 2041-1723, DOI: 10.1038/s41467-018-07657-1
|Nature Communications 9/1||2020-02-05|
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The information about "MICROC" are provided by the European Opendata Portal: CORDIS opendata.
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