Objective
Multiple Myeloma is a chronic malignancy characterized by slow progression and recurrences. Currently there is no effective cure since eventually the disease develops resistance to all the available therapeutic approaches. Although recent advances have expanded our understanding of the cellular functions associated with health to disease transition, recurrence and response to therapy, critical aspects of this complex pathology remain to be elucidated.
Application of omics technologies, and bioinformatics approaches on highly annotated samples obtained from all informative states (monoclonal gammopathy of undetermined significance [MGUS], smoldering MM [sMM], active MM [MM]) could identify biological pathways and molecules responsible for the onset, progression and resistance to therapy of Multiple Myeloma. In parallel, particular emphasis will be given to elucidating the health determinants and risk factors associated with progression to active MM from MGUS/sMM by using extensive demographic, lifestyle and exposure datasets.
MGUS is present in 3-5% of the ageing European population and every year, 1% progress to incurable MM that imposes a significant burden on EU societies and health systems. Thus, the best chances of curing MM may be in preventing its progression in the first place. Moreover, there is need of experimental models that recapitulate myeloma progression.
We propose an interdisciplinary approach bringing together clinicians and researchers aiming to integrate epidemiological, clinical and experimental datasets in order to create a molecular model of cellular processes associated with the onset of active MM and response to therapy. The proposed systems medicine approach could yield clinically actionable molecular features that could improve MM patient management. Moreover, the integration of lifestyle, clinical and omics information will provide specific profiles for each patient allowing
personalized diagnosis, prevention, and therapeutic approaches.
This action is part of the Cancer Mission cluster of projects on ''Understanding'.
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 medicineoncology
- medical and health sciencesbasic medicinepathology
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
Programme(s)
- HORIZON.2.1 - Health Main Programme
Call for proposal
(opens in new window) HORIZON-MISS-2021-CANCER-02
See other projects for this callFunding Scheme
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
10561 Athina
Greece