Objective
Intra-tumor genetic heterogeneity imposes a great challenge on cancer therapy. Resistance to molecularly targeted therapies and chemotherapy can arise from selective growth of pre-existing sub-clones that carries drug-resistance mutations, altered metabolic and/or epigenomic states, providing a survival advantages. Early detection of these subclonal states can thus significantly aid cancer therapy. However, attempts to profile various types of primary cancer cells using single-cell techniques are relatively poor. One of the major limitations is the significant dropout rate (i.e. loss of alleles) observed in single-cell RNA-seq. It severely affects our ability to leverage single cell RNA-seq to accurately profile somatic mutation, to reveal cancer driver mutation and even extract low/mid-level expressed genes and splicing. For that reason, most of the efforts to expose mutations that are critical for cancer growth and can subsequently lead to more effective treatment are based on the sequencing of bulk populations. However, due to the noise introduced by PCR, sequencing and alignment processes, bulk sequencing is limited to identify mutations with a frequency higher than 5%. Here we propose to develop a novel 3D clone-based full-length RNA-seq profiling technology. A preliminary version of this technology for digital profiling of mRNA, already allowed us to significantly improve sensitivity comparing to gold-standard single-cell RNA-seq methods. Using this preliminary version on clones of lung adenocarcinoma, we revealed novel cancer stem like subpopulation that could not be detected using regular single cell RNA-seq maps. Altogether, improving the ability to detect rare mutations (<5%), splicing events and transcriptional variation between cancer cells, will be an extremely powerful tool for early diagnosis of cancer and effective means to improve personalized based drug treatment decision making.
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.
- medical and health sciences clinical medicine oncology prostate cancer
- medical and health sciences basic medicine pharmacology and pharmacy drug resistance
- natural sciences biological sciences genetics mutation
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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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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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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.
HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants
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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) ERC-2022-POC2
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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.
91904 JERUSALEM
Israel
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.