NCT04174547 - An European Platform for Translational Research in Myelodysplastic Syndromes
An European Platform for Translational Research in Myelodysplastic Syndromes
Istituto Clinico Humanitas
Rationale Myelodysplastic syndromes (MDS) are rare cancers with unmet medical needs.
Study of MDS has been rapidly transformed by genome characterization.
The investigators hypothesize that comprehensive analyses of large patient population
will allow to correctly estimate the effect of each mutation on clinical outcomes, and
that niche factors and immune dysfunctions may influence the development of MDS, clonal
evolution and response to treatments
Aims
1- Investigate gene mutations, niche factors and immune dysfunctions influencing the
development of MDS, and define biomarkers for early identification of individuals at
risk; 2- Develop prognostic models for MDS patients through integration of comprehensive
genomic/clinical information; 3- Define biomarkers to better stratify the individual
probability of response to specific treatments
Methods EuroBloodNet, the European Reference Network in rare hematological diseases, will
provide a basis for research activities. Study of genomic features of clonal dominance in
elderly subjects enrolled in large population-based studies and description of the
dynamics of clonal establishment and evolution; study of bone marrow microenvironment to
identify immune dysfunctions influencing MDS development. Development of inclusive
statistical models to accurately predict clinical outcome at individual level, based on
large MDS populations with comprehensive genomic/clinical data. Finally, analysis of
mutational screening and immune profiles from patients enrolled in prospective trials, to
provide evidence on genetic/immunologic profiles associated with probability of response
to specific compounds
Expected results To characterize how clonal hematopoiesis relates to the induction of MDS
clinical phenotype, and to test the utility of gene sequencing to detect subjects at risk
of developing MDS. To define effective prognostic systems and biomarkers to stratify the
individual probability of response to treatment