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Unified platforM for a Better integRal Evaluation of MyeLodyspLastic Syndromes in SpAin-Strategy for Unraveling Personalized genoMic Medicine in Public heAlth System (UMBRELLA-SUMMA)

Sponsor: Instituto de Investigación Biomédica de Salamanca

Summary

Myelodysplastic Syndromes (MDS) are heterogeneous clonal diseases characterized by difficult diagnosis, complex prognostic stratification and unsatisfactory treatment. Based on that, UMBRELLA SUMMA aims to provide better clinical management and personalized medicine to MDS patients in Spain through improving diagnosis (1), prognosis (2 and 3), and treatment (2), and facilitating future investigations (4) of the disease. More concretely, we propose: 1. The application of new technologies such as Optical Genome Mapping (OGM) in the diagnosis of those MDS cases whose cytogenetic alterations cannot be identify by other methods, as well as the implementation of this technology using peripheral blood avoiding more invasive methods for patients. 2. To provide all Spanish Group of MDS (GESMD) members who require it with the newly prognostic stratification of their patients (IPSS-M) by making Next Generation Sequencing (NGS) accessible for all of them. 3. Validate and improve a new prognostic system (AIPSS-MDS) previously developed within the GESMD, thanks to artificial intelligence, one of the tools with the most projection in the field of medicine currently. 4. To build and register ISCIII collections of cells, genetic material and/or plasma from all prospective MDS patients. On the other hand, the dynamics of coexisting mutations in a specific context of chromosomal abnormalities could be defining the clinical fate of each patient. Based on that, the IBSAL team recently proposed three models of MDS evolution based on NGS data from three different cytogenetic subgroups: normal karyotype, trisomy 8 and 5q deletion. The IBSAL proposal aims to deepen into the pathophysiological mechanisms of MDS evolution in these three models through in vitro and in vivo functional studies and single-cell multiomics approaches.

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