Project description
Cell-level prediction of drug resistance in cancer
Cancer is a clonal heterogeneous disorder that starts with a single mutated cell that proliferates, creating a population of cells with genetic variations. This clonal expansion leads to a diverse array of subclonal populations within the tumour, each with distinct mutations and characteristics. This not only contributes to the complexity of the disease but also presents major challenges in treatment. Identifying rare mutations associated with drug resistance and correlating these with RNA expression levels is critical for effective cancer diagnosis and treatment. The ERC-funded MultiCloneSeq project aims to develop a novel multiomics tool for cost-effective analysis of single cells. This tool overcomes technical limitations of existing solutions and promises comprehensive multi-omics profiling with high resolution.
Objective
Cancer led to one in six death worlds wildly. By nature, cancer is characterized by abnormal and uncontrolled cellular growth caused primarily by genetic mutations. Despite of the high cellular heterogeneity, only a small number of somatic mutations shown to be directly associated with tumorigenesis, hence driving cancer growth. The first hurdle in the cancer diagnosis is to identify these rare populations that have the potential to develop drug resistance. A second hurdle is to be able to associate mutations in the genetic level to the RNA expression level, which will improve the chance of pinpointing a specific mutation with the relevant activity. Therefore, it is of crucial importance to develop a single-cell multi-omics sequencing tool to simultaneously study the heterogeneity of expression and DNA-based regulation of cancer-associated genes. Recently, several multi-omics tools have emerged that allow for the interrogation of both gene expression and open chromatin regions. However, there are some notable limitations constrain the capability and applicability of these tools: 1) The expensive and disposable apparatuses and reagents of these methods is extremely expensive, and thus limits their extensive application and potential as a diagnosis tool; 2) The transcriptome derived from all these technologies only captures the 3 ' RNA termini of polyadenylated transcripts. It excludes the capture of non-polyadenylated transcripts which plays a vital role in cancer development, and the interrogation of somatic mutation from full length RNA. (3) The low input of single-cell material leads to the sparse data. To overcome these hurdles, our novel technology is based on three methods that we have developed leveraging the power of microfluidics: 1. single-clone sequencing, 2.Full-length RNA, and 3. A cost efffective open chromatin extraction method. MultiCloneSeq will be the first method providing low-cost and full-scale multiomic profiling with high resolution.
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.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesphysical sciencesclassical mechanicsfluid mechanicsmicrofluidics
- natural sciencesbiological sciencesgeneticsmutation
- medical and health sciencesclinical medicineoncology
- natural sciencesbiological sciencesgeneticsRNA
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Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Funding Scheme
HORIZON-ERC-POC - HORIZON ERC Proof of Concept GrantsHost institution
91904 Jerusalem
Israel