Objective
Melanoma is the most aggressive form of skin cancer and one of the most invasive tumor types. Melanoma incidence keeps increasing worldwide and the therapeutic choices are limited. The lack of treatments with durable responses may be due, at least in part, to an incomplete understanding of the molecular mechanisms that regulate tumor initiation and/or progression to metastasis. Therefore, there is an urgent need to find new strategies to expand our knowledge of melanomagenesis.
We propose a new approach to unravel the complexity of melanoma: To use a cellular differentiation model to decipher the role of epigenetic regulation during melanocyte differentiation and its contribution to melanoma progression. Melanoma cells often express developmental genes, display multi-differentiation potential, and seem to recapitulate the migratory nature of neural crest stem cells from which melanocytes arise. We reasoned that studying a model of differentiation of melanocytes from neural crest stem cells could be useful to identify the mechanisms that modulate melanoma stem-like properties, probably among the most significant contributing features to the tumor aggressiveness. The plasticity and reversibility of the epigenetic mechanisms make them ideal orchestrators of these dynamic processes. Then, we hypothesize that epigenetically controlled miRNAs could be involved in normal differentiation and in tumorigenesis when altered. Thus, aberrant epigenetic modifications could be responsible for reactivation (or retention) of stem-like properties in melanoma cells. The identification of epigenetically regulated miRNAs involved in melanoma progression will be useful not only as prognosis biomarkers in order to stratify patients for more rigorous follow-up and aggressive therapy, but also by their potential as therapeutic targets considering the reversibility of epigenetic changes.
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: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- medical and health sciencesclinical medicineoncologyskin cancermelanoma
- medical and health sciencesmedical biotechnologycells technologiesstem cells
- natural sciencesbiological sciencesgeneticsepigenetics
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Call for proposal
FP7-PEOPLE-2013-IOF
See other projects for this call
Funding Scheme
MC-IOF - International Outgoing Fellowships (IOF)Coordinator
08908 L'Hospitalet De Llobregat
Spain