Molecular-Based Ecosystem to Improve Personalized Medicine in Chronic Myelomonocytic Leukemia

作者：L. Lanino, Anthony M. Hunter, N. Gagelmann, M. Robin, Daniele Dall’Olio, Alice Flamigni, Claudia Sala, C. Gurnari, Yu-Hung Wang, L. Pleyer, Blanca Xicoy, G. Montalban-Bravo, Lee-yung Shih, Ali Alsugair, Saubia Fathima, Caterina Gregorio, C. Rollo, L. Palomo, Anne Sophie Platzbecker, G. Asti, R. Itzykson, D. Sallman, P. Fariselli, W. Kern, G. Garcia-Manero, U. Platzbecker, Francesc Solé, M. Díez-Campelo, J. Maciejewski, R. Bejar, Felicitas R. Thol, N. Kroger, M. Savona, Pierre Fenaux, Guillermo F Sanz, S. Kordasti, V. Santini, Michaela Fontenay, A. Zeidan, R. Komrokji, T. Haferlach, U. Germing, Gastone Castellani, S. D'amico, Mirinal S Patnaik, F. Ieva, E. Solary, A. Tefferi, E. Padron, M. G. Della Porta · 发表于：Journal of Clinical Oncology · 年份：2026 · DOI：10.1200/JCO-25-02116 · 被引用次数：5 · 研究领域：Medicine

PURPOSE Chronic myelomonocytic leukemia (CMML) is a rare myeloid neoplasm characterized by clinical heterogeneity and is associated with poor outcomes. To date, limited molecular information has been incorporated into disease classification and risk stratification. We aimed to integrate genomic features into the clinical decision-making process for CMML. PATIENTS AND METHODS We analyzed a retrospective cohort of 3013 patients with CMML (training set) and a prospective population of 516 patients (validation set). Using an innovative framework for multimodal data analysis, we developed molecular-based disease taxonomy and prognostication. RESULTS Unsupervised clustering identified nine entities with distinct genomic features and outcomes (P < .001), including splicing machinery, transcription factors, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures. Notably, 15% of patients showed molecular/clinical overlap with other myeloid neoplasms. We integrated molecular and clinical information to build the international CMML Prognostic Scoring System (iCPSS), incorporating mutations in nine genes together with hematologic parameters and cytogenetic abnormalities. The iCPSS identified five groups with distinct probability of overall and leukemia-free survival in both training and validation cohorts (P < .001), outperforming existing prognostic models. Importantly, 55% of patients were reassigned to higher or lower risk groups by the iCPSS....