cmiRCan | Circulating microRNAs in lynch syndrome

Summary
Blood-based cancer biomarkers have become important research targets and together with the recent development of liquid biopsy methods and analysis, they have become interesting future tools for cancer diagnosis. The cell-free small non-coding circulating RNA particles, namely microRNAs (c-miRs) that associate with cancer development, have been identified and tested to be used for cancer screening, diagnosis, tumor subtype classification, chemo- or radio-resistance monitoring, and outcome prognosis. Here we use whole serum c-miR clusters from patients with hereditary cancer syndrome, called Lynch syndrome, as a biomarker and we develop machine learning-based algorithms to diagnose and predict cancer occurrence in this patient cohort. We also functionally test how these c-miR clusters effect lynch syndrome linked to tumor growth.
This interdisciplinary project combines clinical, cell biological and bioinformatic research and it will reciprocally transfer knowledge between research, Tiina Jokela and host institute, University of Jyväskylä and secondment institutes; University of Helsinki and Helsinki University Hospital. The proposed project support researcher Tiina Jokela to also gain transferable independent research skills and support her future career goal to become the leader of her own academic research group in the cancer research field.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101026706
Start date: 01-03-2022
End date: 29-02-2024
Total budget - Public funding: 202 680,96 Euro - 202 680,00 Euro
Cordis data

Original description

Blood-based cancer biomarkers have become important research targets and together with the recent development of liquid biopsy methods and analysis, they have become interesting future tools for cancer diagnosis. The cell-free small non-coding circulating RNA particles, namely microRNAs (c-miRs) that associate with cancer development, have been identified and tested to be used for cancer screening, diagnosis, tumor subtype classification, chemo- or radio-resistance monitoring, and outcome prognosis. Here we use whole serum c-miR clusters from patients with hereditary cancer syndrome, called Lynch syndrome, as a biomarker and we develop machine learning-based algorithms to diagnose and predict cancer occurrence in this patient cohort. We also functionally test how these c-miR clusters effect lynch syndrome linked to tumor growth.
This interdisciplinary project combines clinical, cell biological and bioinformatic research and it will reciprocally transfer knowledge between research, Tiina Jokela and host institute, University of Jyväskylä and secondment institutes; University of Helsinki and Helsinki University Hospital. The proposed project support researcher Tiina Jokela to also gain transferable independent research skills and support her future career goal to become the leader of her own academic research group in the cancer research field.

Status

CLOSED

Call topic

MSCA-IF-2020

Update Date

28-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.3. EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions (MSCA)
H2020-EU.1.3.2. Nurturing excellence by means of cross-border and cross-sector mobility
H2020-MSCA-IF-2020
MSCA-IF-2020 Individual Fellowships