Towards novel approaches for Myelodysplastic Syndromes diagnosis to Strengthen Research Human Capital with Cross-Sectoral and Interdisciplinary Staff mobility

The DiagMDS project aims to enhance training and lifelong learning opportunities for research and innovation staff by providing structured, cross-sectoral and interdisciplinary exchanges for mobility-driven skill development. Myelodysplastic syndrome (MDS) is a heterogeneous group of hematopoietic disorders characterised by dysplasia of blood cell lineages, cytopenia, functional abnormalities, and stem cell-derived defects in differentiation, proliferation, and maturation of myeloid lineages. Despite various advances in the field, early and accurate diagnosis remains challenging, as peripheral blood (PB) counts and morphological features overlap with those of anemias. Current diagnostics rely on an integration of PB, bone marrow (BM) findings, karyotyping, and detection of specific mutations via next-generation sequencing. DiagMDS will address this unmet clinical need by developing novel, non-invasive methods for accurate MDS diagnosis in the PB. DiagMDS will study the immune microenvironment, genome architecture, chromatin accessibility, methylation, EVs cargo, mitochondrial DNA and metabolome in PB of MDS patients. The project will then develop novel in silico approaches to obtain patient-specific omic signatures and chromosomal scaffolds. It will utilise AI-based methods for integrating imaging, omics, and clinical data. Following validation of key findings, diagnostic biomarkers/profiles are expected to be defined. The application of such cutting-edge experimental, computational and clinically relevant approaches will significantly contribute to MDS diagnosis, while strengthening staff skills, knowledge transfer, and research excellence.