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.
