Prognostic Score for Myelodysplastic Syndromes Based on Molecular Evolution.

Civettini, Ivan; Malighetti, Federica; Villa, Matteo; Crippa, Valentina; Aroldi, Andrea; Cavalca, Fabrizio; Graudenzi, Alex; Lanino, Luca et al. · NEJM Evid · 2026

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Abstract

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. 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. ProgEvo identified 1765 gene co-occurrences aggregated into 45 directional evolutionary routes. Of these, 18 were validated in the Genomed4All cohort. Five evolution-informed variables, two directional routes (Additional Sex Combs-Like 1 [<i>ASXL1</i>]→KRAS Proto-Oncogene [<i>KRAS</i>] and Serine and Arginine-Rich Splicing Factor 2 [<i>SRSF2</i>]→NRAS Proto-Oncogene [<i>NRAS</i>]), one co-occurrence (<i>NRAS/</i>RUNX Family Transcription Factor 1 [<i>RUNX1</i>]), and two early mutations (<i>ATRX</i> [ATRX Chromatin Remodeler] and Janus Kinase 2 [<i>JAK2</i>]) 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. 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.).

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