Ivan Civettini, Federica Malighetti, Matteo Villa, Valentina Crippa, Andrea Aroldi, Fabrizio Cavalca, Alex Graudenzi, Luca Lanino, Giulia Maggioni, Torsten Haferlach, Pierre Fenaux, Uwe Platzbecker, María Díez-Campelo, Lorenza Borin, Monica Fumagalli, Arianna Zappaterra, Beatrice Manghisi, Najla H. Al Ali, David A. Sallman, Eric Padron, Zhuoer Xie, Onyee Chan, Amer M. Zeidan, Luca Mologni, Rocco Piazza, Rami S. Komrokji, M Della Porta, Carlo Gambacorti-Passerini, Daniele Ramazzotti
BACKGROUND: Myelodysplastic syndromes are clonal hematopoietic stem cell disorders characterized by multistep molecular evolution and a variable risk of leukemic transformation. Given this prognostic heterogeneity, accurate risk stratification is essential for clinical decision-making. We developed ProgEvo, a proprietary framework that infers molecular evolutionary trajectories and integrates them with clinical data to improve prognostic accuracy. METHODS: ProgEvo was trained on 2519 patients in cBioPortal (https://www.cbioportal.org) and validated using two external cohorts: Genomed4All (2043 patients) and a Moffitt Cancer Center (MCC) cohort (2157 patients). Directional evolutionary routes were inferred and selected for prognostic modeling if they were consistently associated with leukemia-free survival. A multivariable feature selection strategy was applied to integrate evolution-consistent variables into the existing IPSS-M model. RESULTS: ]) were integrated into IPSS-M to generate IPSS-M-Evo. The model with "-Evo" improved discrimination for both leukemia-free survival and overall survival, with over 40% of patients restratified in the Genomed4All data. The performance of the model was further confirmed in the MCC cohort. CONCLUSIONS: ProgEvo enabled inference of a molecular evolution model and integration of evolution-informed covariates into clinical prognostic frameworks, supporting the development of the IPSS-M-Evo model. A free web-based tool allows clinicians to calculate the IPSS-M-Evo score and match individual mutational profiles to cohort-derived evolutionary trajectories (https://evoclin.unimib.it/tools/evolution-graphs.html and https://evoclin.unimib.it/tools/ipssmevo.html). (Funded by the European Union and others.).