Objective
Owing to advances in sequencing technology, we are now beginning to understand the molecular mechanisms underlying cancer development and evolution. Tumours however are heterogeneous, often containing admixed normal cells and different (sub)clones, confounding interpretation of the massive amounts of data flowing from large initiatives such as the International Cancer Genome Consortium.
To address this issue, I will develop methods that disentangle tumour bulk gene expression (RNA-Seq) and DNA methylation (Bisulphite-Seq) data to accurately reveal the states of the distinct underlying cell populations. The innovative algorithms will derive estimates of the allele-specific expression/methylation rates and tumour copy number profiles from the data and use them to separate the signal coming from the tumour from that of the normal cells. In a second step, the method leverages the wealth of available cancer ‘omics data using a recommender-system approach to complete the deconvolution. Careful validation will come from teasing apart computationally mixed pure samples as well as from ongoing and planned collaborative single-cell sequencing projects. A detailed analysis of tumour expression and DNA methylation heterogeneity on these single-cell datasets will guide further methodological advances. As an intrinsic part of the project, massive pan-cancer datasets will be deconvoluted. Drawing on the pure transcriptomes and epigenomes, I will construct a more comprehensive taxonomy of cancers, laying the basis for significant improvements in clinical prognostic prediction and personalised treatment.
This project will shift the paradigm of genomic tumour heterogeneity to include the more actionable transcriptome and epigenome. In turn this will lead to a better understanding of how (epi)genomic alterations translate into the transcriptomic (and proteomic, interactomic, …) changes driving cancer evolution.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences genetics DNA
- medical and health sciences clinical medicine oncology
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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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.
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.
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.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2015
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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.
NW1 1AT London
United Kingdom
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.