MoP-MiP | Molecular Programming for MicroRNA profiling

Summary
MicroRNAs, a class of transcript responsible for the fine regulation of gene expression, are emerging as promising biomarkers for cancer monitoring (diagnostic, prognostic and prediction of therapy response. The concentration profiling of – stably present – microRNAs from liquid biopsies represents a hopeful opportunity to fight these diseases, enabling large population screening for early cancer appearance and monitoring in real-time the treatment response. However, current microRNA detection methods do not meet performances in term of sensitivity, multiplexing and practicability to bring microRNA signatures in the front line of clinical applications.
The objective of this research proposal is to develop novel approaches for microRNA profiling using concepts of molecular programming (MP). MP deals with the design of artificial DNA reaction networks capable of information-processing, including complex biosensing tasks. The team will investigate two major strategies: 1) the development of a digital and multiplex assay (Digiplex), where each microRNA is accurately quantified independently at the single molecule level using target-specific molecular program; 2) the exploration of molecular neural network (MolNNet) for concentration pattern recognition. It involves the conception of sophisticated molecular program architectures performing the integration of multiple microRNA concentrations, signal processing and reporting of the sample type (e.g. “healthy” or “diseased”).
This project is highly interdisciplinary, gathering expertise in DNA nanotechnology, microfluidics, surface chemistry and machine learning. The expected outcomes include the advance of cutting-edge microRNA quantification technology combining single-molecule amplification with a multiplex readout (up to 100 targets). On the long term, the exploration of in moleculo neural networks is foreseen to trigger a whole new field of research, providing a ground-breaking approach for molecular diagnostics.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/949493
Start date: 01-02-2021
End date: 31-01-2026
Total budget - Public funding: 1 499 326,00 Euro - 1 499 326,00 Euro
Cordis data

Original description

MicroRNAs, a class of transcript responsible for the fine regulation of gene expression, are emerging as promising biomarkers for cancer monitoring (diagnostic, prognostic and prediction of therapy response. The concentration profiling of – stably present – microRNAs from liquid biopsies represents a hopeful opportunity to fight these diseases, enabling large population screening for early cancer appearance and monitoring in real-time the treatment response. However, current microRNA detection methods do not meet performances in term of sensitivity, multiplexing and practicability to bring microRNA signatures in the front line of clinical applications.
The objective of this research proposal is to develop novel approaches for microRNA profiling using concepts of molecular programming (MP). MP deals with the design of artificial DNA reaction networks capable of information-processing, including complex biosensing tasks. The team will investigate two major strategies: 1) the development of a digital and multiplex assay (Digiplex), where each microRNA is accurately quantified independently at the single molecule level using target-specific molecular program; 2) the exploration of molecular neural network (MolNNet) for concentration pattern recognition. It involves the conception of sophisticated molecular program architectures performing the integration of multiple microRNA concentrations, signal processing and reporting of the sample type (e.g. “healthy” or “diseased”).
This project is highly interdisciplinary, gathering expertise in DNA nanotechnology, microfluidics, surface chemistry and machine learning. The expected outcomes include the advance of cutting-edge microRNA quantification technology combining single-molecule amplification with a multiplex readout (up to 100 targets). On the long term, the exploration of in moleculo neural networks is foreseen to trigger a whole new field of research, providing a ground-breaking approach for molecular diagnostics.

Status

SIGNED

Call topic

ERC-2020-STG

Update Date

27-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.1. EXCELLENT SCIENCE - European Research Council (ERC)
ERC-2020
ERC-2020-STG