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Bioinformatic approaches to identify and detect both disease- and drug-related genomic alterations in breast cancer patients

Objective

Breast cancer is the most common cancer among European women showing high clinical and molecular heterogeneity. Current clinical management causes patients overtreatment with implications on both patients’ quality of life and healthcare costs. Moreover, intrinsic or acquired tumor resistance to treatment leads to incurable metastatic progression in a significant proportion of patients.
Advances in cancer genomics highlighted a high inter- and intra-tumor genetic heterogeneity, reinforcing the need for a mutation-based personalized treatment and a way to non-invasively monitor evolving disease. This project will significantly contribute in addressing such unmet challenge aiming 1) to identify altered breast cancer driver pathways, 2) to study their association with drug response and 3) to develop tools for a non-invasive assessment of such alterations.
By integrating multi-dimensional molecular data from more than 3000 cases, driver pathways will be identified and their association with previous breast cancer classifications as well as their prognostic significance will be studied. Their predictive power will be investigated in a matchless bio-bank of Patient Derived Xenografts, a much more reliable pre-clinical model, able to recapitulate inter- and intra-tumor heterogeneity observed in patients. Multi-dimensional molecular data and high throughput drug screenings are available and will be integrated to identify novel pharmacogenomics associations.
Mining of such amount of data will allow defining a portfolio of relevant breast cancer alterations that will be sought in plasma of patients from the DETECT trial, towards a non-invasive monitoring able to guide therapeutic strategy.
Development and application of cutting-edge computational approaches is fundamental to reach above aims and it will constitute a major part of the efforts, considerably expanding Experienced Researcher's know-how in the field of cancer genomics and translational medicine.

Fields of science (EuroSciVoc)

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Programme(s)

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Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MSCA-IF-EF-ST - Standard EF

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-MSCA-IF-2014

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Coordinator

THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 183 454,80
Address
TRINITY LANE THE OLD SCHOOLS
CB2 1TN CAMBRIDGE
United Kingdom

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Region
East of England East Anglia Cambridgeshire CC
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 183 454,80
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