Project description
Innovative screening platform for personalised cancer treatment
Successful cancer treatment requires an understanding of the molecular and cellular systems that define response to medication, and the development of specific assays that predict patient responses to treatments. The EU-funded SCIPER project aims to identify the mechanisms creating the drug response variability among cancer patients and develop assays to accurately predict treatment responses of late-stage cancer patients. The project is developing a platform that measures ex vivo drug responses from patient biopsies by immunofluorescence, automated confocal microscopy, single-cell image analysis, and machine learning. The state-of-the-art Pharmacoscopy assay platform combines image-based drug screening of patient biopsies and their molecular profiling and patient data in a series of clinical studies, ensuring the applicability of the technology.
Objective
The cellular and molecular systems that determine drug responses in cancer are complex, highly individual, and incompletely understood. As a result, many cancer patients receive ineffective or even harmful therapies, which endangers lives, burdens healthcare systems, and prevents new therapies from reaching clinical approval.
To address this problem, we are developing a platform that measures hundreds of ex vivo drug responses from small patient biopsies by immunofluorescence, automated confocal microscopy, single-cell image analysis, and machine learning. We preserve cellular memory and maximize physiological relevance by not culturing or sorting cells prior to drug exposure. Sub-cellular, single-cell, and cell population-wide image analysis reveals on-target drug responses and disentangles multicellular ones. In a first interventional clinical trial, this phenotypic information alone led to strongly improved treatment of patients with aggressive hematologic malignancies.
Enabled by this high-throughput, predictive, and phenotypic information, I here propose to identify the molecular and cellular systems that govern treatment response individuality in cancer. (Aim 1) We will combine drug response profiling with RNA sequencing and proteomic measurements of malignant and healthy cells from the same biopsies. Critically, the patient-internal comparisons in both screening and OMICs allow neutralizing complex confounding factors. (Aim 2) New multiplexed immunofluorescence and convolutional neural network-based analyses will identify multiclass cell-types and -states, and quantify non-cell-autonomous responses. (Aim 3) Computational integration and causal inference will identify the molecular determinants and governing principles of drug response individuality in cancer, amenable to further validation. This proposal will thus improve our mechanistic understanding of cancer individuality and develop powerful new tools for OMICs-based precision medicine.
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
- medical and health sciences health sciences personalized medicine
- natural sciences physical sciences optics microscopy confocal microscopy
- natural sciences biological sciences genetics RNA
- natural sciences computer and information sciences artificial intelligence machine learning
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
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.1.1. - EXCELLENT SCIENCE - 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.
ERC-STG - Starting Grant
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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-2018-STG
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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.
8092 Zuerich
Switzerland
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.