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1. A sex-informed approach to improve the personalised decision making process in myelodysplastic syndromes: a multicentre, observational cohort study

Author

Maggioni, Giulia, Bersanelli, Matteo, Travaglino, Erica, Alfonso Piérola, Ana, Kasprzak, Annika, Sangerman Montserrat, Arnan, Sauta, Elisabetta, Sala, Claudia, Matteuzzi, Tommaso, Meggendorfer, Manja, Gnocchi, Matteo, Zhao, Lin-Pierre, Tentori, Cristina Astrid, Nachtkamp, Kathrin, Dall'Olio, Daniele, Mosca, Ettore, Ubezio, Marta, Campagna, Alessia, Russo, Antonio, Rivoli, Giulia, Bernardi, Massimo, Borin, Lorenza, Voso, Maria Teresa, Riva, Marta, Oliva, Esther, Zampini, Matteo, Riva, Elena, Saba, Elena, D'Amico, Saverio, Lanino, Luca, Tinterri, Benedetta, Re, Francesca, Bicchieri, Marilena, Giordano, Laura, Angelotti, Giovanni, Morandini, Pierandrea, Kubasch, Anne Sophie, Passamonti, Francesco, Rambaldi, Alessandro, Savevski, Victor, Santoro, Armando, van de Loosdrecht, Arjan A., Brogi, Alice, Santini, Valeria, Kordasti, Shahram, Sanz, Guillermo, Sole, Francesc, Gattermann, Norbert, Kern, Wolfgang, Platzbecker, Uwe, Ades, Lionel, Fenaux, Pierre, Haferlach, Torsten, Castellani, Gastone, Germing, Ulrich, Diez-Campelo, Maria, and Della Porta, Matteo G.

Published
2023
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2. Personalized Timing for Allogeneic Stem-Cell Transplantation in Hematologic Neoplasms: A Target Trial Emulation Approach Using Multistate Modeling and Microsimulation

Author

Gregorio, Caterina, primary, Spreafico, Marta, additional, D'Amico, Saverio, additional, Sauta, Elisabetta, additional, Asti, Gianluca, additional, Lanino, Luca, additional, Tentori, Cristina Astrid, additional, Platzbecker, Uwe, additional, Haferlach, Torsten, additional, Diez-Campelo, Maria, additional, Fenaux, Pierre, additional, Komrokji, Rami, additional, Della Porta, Matteo Giovanni, additional, and Ieva, Francesca, additional

Published
2024
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3. Clinical and Genomic-Based Decision Support System to Define the Optimal Timing of Allogeneic Hematopoietic Stem-Cell Transplantation in Patients With Myelodysplastic Syndromes.

Author

Tentori, Cristina Astrid, Gregorio, Caterina, Robin, Marie, Gagelmann, Nico, Gurnari, Carmelo, Ball, Somedeb, Caballero Berrocal, Juan Carlos, Lanino, Luca, D'Amico, Saverio, Spreafico, Marta, Maggioni, Giulia, Travaglino, Erica, Sauta, Elisabetta, Meggendorfer, Manja, Zhao, Lin-Pierre, Campagna, Alessia, Savevski, Victor, Santoro, Armando, Al Ali, Najla, and Sallman, David

Published
2024
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4. Chronic myelomonocytic leukemia with ring sideroblasts/SF3B1 mutation presents with low monocyte count and resembles myelodysplastic syndromes with-RS/SF3B1 mutation in terms of phenotype and prognosis.

Author

Xicoy, Blanca, Pomares, Helena, Morgades, Mireia, Germing, Ulrich, Arnan, Montserrat, Tormo, Mar, Palomo, Laura, Orna, Elisa, Porta, Matteo Della, Schulz, Felicitas, Díaz-Beya, Marina, Esteban, Ada, Molero, Antonieta, Lanino, Luca, Avendaño, Alejandro, Hernández, Francisca, Roldan, Verónica, Ubezio, Marta, Pineda, Alberto, and Dfez-Campelo, María

Subjects
CHRONIC leukemia, MYELODYSPLASTIC syndromes, PHENOTYPES, ACUTE myeloid leukemia, OVERALL survival, PROGNOSIS
Abstract

Introduction: Chronic myelomonocytic leukemia (CMML) and myelodysplastic syndromes (MDS) with ring sideroblasts (RS) or SF3B1 mutation (MDS-RS/SF3B1) differ in many clinical features, but share others, such as anemia. RS and SF3B1 mutation can also be found in CMML. Methods: We compared CMML with and without RS/SF3B1 and MDS-RS/SF3B1 considering the criteria established by the 2022 World Health Organization classification. Results: A total of 815 patients were included (CMML, n=319, CMML-RS/SF3B1, n=172 and MDS-RS/SF3B1, n=324). The percentage of RS was =15% in almost all CMML-RS/SF3B1 patients (169, 98.3%) and most (125, 72.7%) showed peripheral blood monocyte counts between 0.5 and 0.9 x 109/L and low risk prognostic categories. CMML-RS/SF3B1 differed significantly from classical CMML in the main clinical characteristics, whereas it resembled MDS-RS/SF3B1. At a molecular level, CMML and CMML-RS/SF3B1 had a significantly higher frequency of mutations in TET2 (mostly multi-hit) and ASXL1 (p=0.013) and CMML had a significantly lower frequency of DNMT3A and SF3B1 mutations compared to CMML/MDS-RS/SF3B1. Differences in the median overall survival among the three groups were statistically significant: 6.75 years (95% confidence interval [CI] 5.41-8.09) for CMML-RS/SF3B1 vs. 3.17 years (95% CI 2.56-3.79) for CMML vs. 16.47 years (NA) for MDS-RS/SF3B1, p<0.001. Regarding patients with CMML and MDS, both with SF3B1 mutation, survival did not significantly differ. CMML had a higher risk of transformation to acute myeloid leukemia (24% at 8 years, 95%CI 19%-30%). Discussion: CMML-RS/SF3B1 mutation resembles MDS-RS/SF3B1 in terms of phenotype and clearly differs from CMML. The presence of =15% RS and/or SF3B1 in CMML is associated with a low monocyte count. SF3B1 mutation clearly improves the prognosis of CMML. [ABSTRACT FROM AUTHOR]

Published
2024
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5. MOSAIC: An Artificial Intelligence–Based Framework for Multimodal Analysis, Classification, and Personalized Prognostic Assessment in Rare Cancers.

Author

D'Amico, Saverio, Dall'Olio, Lorenzo, Rollo, Cesare, Alonso, Patricia, Prada-Luengo, Iñigo, Dall'Olio, Daniele, Sala, Claudia, Sauta, Elisabetta, Asti, Gianluca, Lanino, Luca, Maggioni, Giulia, Campagna, Alessia, Zazzetti, Elena, Delleani, Mattia, Bicchieri, Maria Elena, Morandini, Pierandrea, Savevski, Victor, Arroyo, Borja, Parras, Juan, and Zhao, Lin Pierre

Subjects
ARTIFICIAL intelligence, FEDERATED learning, MULTIMODAL user interfaces, CLASSIFICATION, HEMATOLOGIC malignancies, RANDOM forest algorithms, DEEP learning
Abstract

PURPOSE: Rare cancers constitute over 20% of human neoplasms, often affecting patients with unmet medical needs. The development of effective classification and prognostication systems is crucial to improve the decision-making process and drive innovative treatment strategies. We have created and implemented MOSAIC, an artificial intelligence (AI)–based framework designed for multimodal analysis, classification, and personalized prognostic assessment in rare cancers. Clinical validation was performed on myelodysplastic syndrome (MDS), a rare hematologic cancer with clinical and genomic heterogeneities. METHODS: We analyzed 4,427 patients with MDS divided into training and validation cohorts. Deep learning methods were applied to integrate and impute clinical/genomic features. Clustering was performed by combining Uniform Manifold Approximation and Projection for Dimension Reduction + Hierarchical Density-Based Spatial Clustering of Applications with Noise (UMAP + HDBSCAN) methods, compared with the conventional Hierarchical Dirichlet Process (HDP). Linear and AI-based nonlinear approaches were compared for survival prediction. Explainable AI (Shapley Additive Explanations approach [SHAP]) and federated learning were used to improve the interpretation and the performance of the clinical models, integrating them into distributed infrastructure. RESULTS: UMAP + HDBSCAN clustering obtained a more granular patient stratification, achieving a higher average silhouette coefficient (0.16) with respect to HDP (0.01) and higher balanced accuracy in cluster classification by Random Forest (92.7% ± 1.3% and 85.8% ± 0.8%). AI methods for survival prediction outperform conventional statistical techniques and the reference prognostic tool for MDS. Nonlinear Gradient Boosting Survival stands in the internal (Concordance-Index [C-Index], 0.77; SD, 0.01) and external validation (C-Index, 0.74; SD, 0.02). SHAP analysis revealed that similar features drove patients' subgroups and outcomes in both training and validation cohorts. Federated implementation improved the accuracy of developed models. CONCLUSION: MOSAIC provides an explainable and robust framework to optimize classification and prognostic assessment of rare cancers. AI-based approaches demonstrated superior accuracy in capturing genomic similarities and providing individual prognostic information compared with conventional statistical methods. Its federated implementation ensures broad clinical application, guaranteeing high performance and data protection. MOSAIC: AI-based Framework for Multi-Modal Analysis, Classification and Prognostic Assessment in Rare Cancers. [ABSTRACT FROM AUTHOR]

Published
2024
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6. Synthetic Data Generation by Artificial Intelligence to Accelerate Research and Precision Medicine in Hematology

Author

D'Amico, Saverio, primary, Dall’Olio, Daniele, additional, Sala, Claudia, additional, Dall’Olio, Lorenzo, additional, Sauta, Elisabetta, additional, Zampini, Matteo, additional, Asti, Gianluca, additional, Lanino, Luca, additional, Maggioni, Giulia, additional, Campagna, Alessia, additional, Ubezio, Marta, additional, Russo, Antonio, additional, Bicchieri, Maria Elena, additional, Riva, Elena, additional, Tentori, Cristina A., additional, Travaglino, Erica, additional, Morandini, Pierandrea, additional, Savevski, Victor, additional, Santoro, Armando, additional, Prada-Luengo, Iñigo, additional, Krogh, Anders, additional, Santini, Valeria, additional, Kordasti, Shahram, additional, Platzbecker, Uwe, additional, Diez-Campelo, Maria, additional, Fenaux, Pierre, additional, Haferlach, Torsten, additional, Castellani, Gastone, additional, and Della Porta, Matteo Giovanni, additional

Published
2023
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7. Real-World Validation of Molecular International Prognostic Scoring System for Myelodysplastic Syndromes

Author

Sauta, Elisabetta, primary, Robin, Marie, additional, Bersanelli, Matteo, additional, Travaglino, Erica, additional, Meggendorfer, Manja, additional, Zhao, Lin-Pierre, additional, Caballero Berrocal, Juan Carlos, additional, Sala, Claudia, additional, Maggioni, Giulia, additional, Bernardi, Massimo, additional, Di Grazia, Carmen, additional, Vago, Luca, additional, Rivoli, Giulia, additional, Borin, Lorenza, additional, D'Amico, Saverio, additional, Tentori, Cristina Astrid, additional, Ubezio, Marta, additional, Campagna, Alessia, additional, Russo, Antonio, additional, Mannina, Daniele, additional, Lanino, Luca, additional, Chiusolo, Patrizia, additional, Giaccone, Luisa, additional, Voso, Maria Teresa, additional, Riva, Marta, additional, Oliva, Esther Natalie, additional, Zampini, Matteo, additional, Riva, Elena, additional, Nibourel, Olivier, additional, Bicchieri, Marilena, additional, Bolli, Niccolo’, additional, Rambaldi, Alessandro, additional, Passamonti, Francesco, additional, Savevski, Victor, additional, Santoro, Armando, additional, Germing, Ulrich, additional, Kordasti, Shahram, additional, Santini, Valeria, additional, Diez-Campelo, Maria, additional, Sanz, Guillermo, additional, Sole, Francesc, additional, Kern, Wolfgang, additional, Platzbecker, Uwe, additional, Ades, Lionel, additional, Fenaux, Pierre, additional, Haferlach, Torsten, additional, Castellani, Gastone, additional, and Della Porta, Matteo Giovanni, additional

Published
2023
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8. Synthetic Data Generation by Artificial Intelligence to Accelerate Research and Precision Medicine in Hematology

Author

D'Amico, Saverio, Dall'Olio, Daniele, Sala, Claudia, Dall'Olio, Lorenzo, Sauta, Elisabetta, Zampini, Matteo, Asti, Gianluca, Lanino, Luca, Maggioni, Giulia, Campagna, Alessia, Ubezio, Marta, Russo, Antonio, Bicchieri, Maria Elena, Riva, Elena, Tentori, Cristina A., Travaglino, Erica, Morandini, Pierandrea, Savevski, Victor, Santoro, Armando, Prada-Luengo, Iñigo, Krogh, Anders, Santini, Valeria, Kordasti, Shahram, Platzbecker, Uwe, Diez-Campelo, Maria, Fenaux, Pierre, Haferlach, Torsten, Castellani, Gastone, Della Porta, Matteo Giovanni, D'Amico, Saverio, Dall'Olio, Daniele, Sala, Claudia, Dall'Olio, Lorenzo, Sauta, Elisabetta, Zampini, Matteo, Asti, Gianluca, Lanino, Luca, Maggioni, Giulia, Campagna, Alessia, Ubezio, Marta, Russo, Antonio, Bicchieri, Maria Elena, Riva, Elena, Tentori, Cristina A., Travaglino, Erica, Morandini, Pierandrea, Savevski, Victor, Santoro, Armando, Prada-Luengo, Iñigo, Krogh, Anders, Santini, Valeria, Kordasti, Shahram, Platzbecker, Uwe, Diez-Campelo, Maria, Fenaux, Pierre, Haferlach, Torsten, Castellani, Gastone, and Della Porta, Matteo Giovanni

Abstract

PURPOSE: Synthetic data are artificial data generated without including any real patient information by an algorithm trained to learn the characteristics of a real source data set and became widely used to accelerate research in life sciences. We aimed to (1) apply generative artificial intelligence to build synthetic data in different hematologic neoplasms; (2) develop a synthetic validation framework to assess data fidelity and privacy preservability; and (3) test the capability of synthetic data to accelerate clinical/translational research in hematology. METHODS: A conditional generative adversarial network architecture was implemented to generate synthetic data. Use cases were myelodysplastic syndromes (MDS) and AML: 7,133 patients were included. A fully explainable validation framework was created to assess fidelity and privacy preservability of synthetic data. RESULTS: We generated MDS/AML synthetic cohorts (including information on clinical features, genomics, treatment, and outcomes) with high fidelity and privacy performances. This technology allowed resolution of lack/incomplete information and data augmentation. We then assessed the potential value of synthetic data on accelerating research in hematology. Starting from 944 patients with MDS available since 2014, we generated a 300% augmented synthetic cohort and anticipated the development of molecular classification and molecular scoring system obtained many years later from 2,043 to 2,957 real patients, respectively. Moreover, starting from 187 MDS treated with luspatercept into a clinical trial, we generated a synthetic cohort that recapitulated all the clinical end points of the study. Finally, we developed a website to enable clinicians generating high-quality synthetic data from an existing biobank of real patients. CONCLUSION: Synthetic data mimic real clinical-genomic features and outcomes, and anonymize patient information. The implementation of this technology allows to increase the scientif

Published
2023

9. Real-World Validation of Molecular International Prognostic Scoring System for Myelodysplastic Syndromes

Author

Sauta, E, Robin, M, Bersanelli, M, Travaglino, E, Meggendorfer, M, Zhao, L, Caballero Berrocal, J, Sala, C, Maggioni, G, Bernardi, M, Di Grazia, C, Vago, L, Rivoli, G, Borin, L, D'Amico, S, Tentori, C, Ubezio, M, Campagna, A, Russo, A, Mannina, D, Lanino, L, Chiusolo, P, Giaccone, L, Voso, M, Riva, M, Oliva, E, Zampini, M, Riva, E, Nibourel, O, Bicchieri, M, Bolli, N, Rambaldi, A, Passamonti, F, Savevski, V, Santoro, A, Germing, U, Kordasti, S, Santini, V, Diez-Campelo, M, Sanz, G, Sole, F, Kern, W, Platzbecker, U, Ades, L, Fenaux, P, Haferlach, T, Castellani, G, Della Porta, M, Sauta, Elisabetta, Robin, Marie, Bersanelli, Matteo, Travaglino, Erica, Meggendorfer, Manja, Zhao, Lin-Pierre, Caballero Berrocal, Juan Carlos, Sala, Claudia, Maggioni, Giulia, Bernardi, Massimo, Di Grazia, Carmen, Vago, Luca, Rivoli, Giulia, Borin, Lorenza, D'Amico, Saverio, Tentori, Cristina Astrid, Ubezio, Marta, Campagna, Alessia, Russo, Antonio, Mannina, Daniele, Lanino, Luca, Chiusolo, Patrizia, Giaccone, Luisa, Voso, Maria Teresa, Riva, Marta, Oliva, Esther Natalie, Zampini, Matteo, Riva, Elena, Nibourel, Olivier, Bicchieri, Marilena, Bolli, Niccolo', Rambaldi, Alessandro, Passamonti, Francesco, Savevski, Victor, Santoro, Armando, Germing, Ulrich, Kordasti, Shahram, Santini, Valeria, Diez-Campelo, Maria, Sanz, Guillermo, Sole, Francesc, Kern, Wolfgang, Platzbecker, Uwe, Ades, Lionel, Fenaux, Pierre, Haferlach, Torsten, Castellani, Gastone, Della Porta, Matteo Giovanni, Sauta, E, Robin, M, Bersanelli, M, Travaglino, E, Meggendorfer, M, Zhao, L, Caballero Berrocal, J, Sala, C, Maggioni, G, Bernardi, M, Di Grazia, C, Vago, L, Rivoli, G, Borin, L, D'Amico, S, Tentori, C, Ubezio, M, Campagna, A, Russo, A, Mannina, D, Lanino, L, Chiusolo, P, Giaccone, L, Voso, M, Riva, M, Oliva, E, Zampini, M, Riva, E, Nibourel, O, Bicchieri, M, Bolli, N, Rambaldi, A, Passamonti, F, Savevski, V, Santoro, A, Germing, U, Kordasti, S, Santini, V, Diez-Campelo, M, Sanz, G, Sole, F, Kern, W, Platzbecker, U, Ades, L, Fenaux, P, Haferlach, T, Castellani, G, Della Porta, M, Sauta, Elisabetta, Robin, Marie, Bersanelli, Matteo, Travaglino, Erica, Meggendorfer, Manja, Zhao, Lin-Pierre, Caballero Berrocal, Juan Carlos, Sala, Claudia, Maggioni, Giulia, Bernardi, Massimo, Di Grazia, Carmen, Vago, Luca, Rivoli, Giulia, Borin, Lorenza, D'Amico, Saverio, Tentori, Cristina Astrid, Ubezio, Marta, Campagna, Alessia, Russo, Antonio, Mannina, Daniele, Lanino, Luca, Chiusolo, Patrizia, Giaccone, Luisa, Voso, Maria Teresa, Riva, Marta, Oliva, Esther Natalie, Zampini, Matteo, Riva, Elena, Nibourel, Olivier, Bicchieri, Marilena, Bolli, Niccolo', Rambaldi, Alessandro, Passamonti, Francesco, Savevski, Victor, Santoro, Armando, Germing, Ulrich, Kordasti, Shahram, Santini, Valeria, Diez-Campelo, Maria, Sanz, Guillermo, Sole, Francesc, Kern, Wolfgang, Platzbecker, Uwe, Ades, Lionel, Fenaux, Pierre, Haferlach, Torsten, Castellani, Gastone, and Della Porta, Matteo Giovanni

Abstract

Purpose: Myelodysplastic syndromes (MDS) are heterogeneous myeloid neoplasms in which a risk-adapted treatment strategy is needed. Recently, a new clinical-molecular prognostic model, the Molecular International Prognostic Scoring System (IPSS-M) was proposed to improve the prediction of clinical outcome of the currently available tool (Revised International Prognostic Scoring System [IPSS-R]). We aimed to provide an extensive validation of IPSS-M. Methods: A total of 2,876 patients with primary MDS from the GenoMed4All consortium were retrospectively analyzed. Results: IPSS-M improved prognostic discrimination across all clinical end points with respect to IPSS-R (concordance was 0.81 v 0.74 for overall survival and 0.89 v 0.76 for leukemia-free survival, respectively). This was true even in those patients without detectable gene mutations. Compared with the IPSS-R based stratification, the IPSS-M risk group changed in 46% of patients (23.6% and 22.4% of subjects were upstaged and downstaged, respectively).In patients treated with hematopoietic stem cell transplantation (HSCT), IPSS-M significantly improved the prediction of the risk of disease relapse and the probability of post-transplantation survival versus IPSS-R (concordance was 0.76 v 0.60 for overall survival and 0.89 v 0.70 for probability of relapse, respectively). In high-risk patients treated with hypomethylating agents (HMA), IPSS-M failed to stratify individual probability of response; response duration and probability of survival were inversely related to IPSS-M risk.Finally, we tested the accuracy in predicting IPSS-M when molecular information was missed and we defined a minimum set of 15 relevant genes associated with high performance of the score. Conclusion: IPSS-M improves MDS prognostication and might result in a more effective selection of candidates to HSCT. Additional factors other than gene mutations can be involved in determining HMA sensitivity. The definition of a minimum set of relevan

Published
2023

10. Real‐world efficacy and safety of luspatercept and predictive factors of response in patients with lower risk myelodysplastic syndromes with ring sideroblasts.

Author

Lanino, Luca, Restuccia, Francesco, Perego, Alessandra, Ubezio, Marta, Fattizzo, Bruno, Riva, Marta, Consagra, Angela, Musto, Pellegrino, Cilloni, Daniela, Oliva, Esther Natalie, Palmieri, Raffaele, Poloni, Antonella, Califano, Catello, Capodanno, Isabella, Itri, Federico, Elena, Chiara, Fozza, Claudio, Pane, Fabrizio, Pelizzari, Anna Maria, and Breccia, Massimo

Published
2023
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11. Real-World Validation of Molecular International Prognostic Scoring System (IPSS-M) for Myelodysplastic Syndromes

Author

Sauta, Elisabetta, primary, Robin, Marie, additional, Bersanelli, Matteo, additional, Travaglino, Erica, additional, Meggendorfer, Manja, additional, Zhao, Lin-Pierre, additional, Caballero Berrocal, Juan Carlos, additional, Maggioni, Giulia, additional, Tentori, Cristina Astrid, additional, Bernardi, Massimo, additional, Di Grazia, Carmen, additional, Vago, Luca, additional, Rivoli, Giulia, additional, Borin, Lorenza, additional, D'Amico, Saverio, additional, Ubezio, Marta, additional, Campagna, Alessia, additional, Russo, Antonio, additional, Mannina, Daniele, additional, Lanino, Luca, additional, Chiusolo, Patrizia, additional, Giaccone, Luisa, additional, Voso, Maria Teresa, additional, Riva, Marta, additional, Oliva, Esther Natalie, additional, Zampini, Matteo, additional, Riva, Elena, additional, Nibourel, Olivier, additional, Sala, Claudia, additional, Bicchieri, Marilena, additional, Bolli, Niccolò, additional, Rambaldi, Alessandro, additional, Passamonti, Francesco, additional, Savevski, Victor, additional, Santoro, Armando, additional, Germing, Ulrich, additional, Kordasti, Shahram, additional, Santini, Valeria, additional, Diez-Campelo, Maria, additional, Sanz, Guillermo, additional, Solé, Francesc, additional, Kern, Wolfgang, additional, Platzbecker, Uwe, additional, Ades, Lionel, additional, Fenaux, Pierre, additional, Haferlach, Torsten, additional, Gastone, Castellani, additional, and Della Porta, Matteo G., additional

Published
2022
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12. Efficacy and Safety of Luspatercept in Adult Patients with Transfusion-Dependent Anemia Due to Very Low, Low and Intermediate Risk Myelodysplastic Syndromes (MDS) with Ring Sideroblasts, Who Had an Unsatisfactory Response to or Are Ineligible for Erythropoietin-Based Therapy: A Retrospective Multicenter Study By Fondazione Italiana Sindromi Mielodisplastiche (FiSiM ETS)

Author

Lanino, Luca, primary, Salutari, Prassede, additional, Perego, Alessandra, additional, Fattizzo, Bruno, additional, Riva, Marta, additional, Ubezio, Marta, additional, Musto, Pellegrino, additional, Cilloni, Daniela, additional, Oliva, Esther Natalie, additional, Voso, Maria Teresa, additional, Pelizzari, Anna Maria, additional, Poloni, Antonella, additional, Capodanno, Isabella, additional, Elena, Chiara, additional, Fozza, Claudio, additional, Pane, Fabrizio, additional, Breccia, Massimo, additional, De Gobbi, Marco, additional, Di Bassiano, Francesco, additional, Barraco, Daniela, additional, Crisà, Elena, additional, Ferrero, Dario, additional, Frairia, Chiara, additional, Vaccarino, Antonella, additional, Griguolo, Davide, additional, Paolini, Stefania, additional, Quintini, Martina, additional, Sessa, Mariarosaria, additional, Turrini, Mauro, additional, Bocchia, Monica, additional, Di Renzo, Nicola, additional, Diral, Elisa, additional, Foli, Cristina, additional, Molteni, Alfredo, additional, Occhini, Ubaldo, additional, Rivoli, Giulia, additional, Selleri, Carmine, additional, Bono, Roberto, additional, Calvisi, Anna, additional, Castelli, Andrea, additional, Di Bona, Eros, additional, Di Veroli, Ambra, additional, Fianchi, Luana, additional, Galimberti, Sara, additional, Grimaldi, Daniele, additional, Marchetti, Monia, additional, Norata, Marianna, additional, Rambaldi, Alessandro, additional, Tanasi, Ilaria, additional, Tosi, Patrizia, additional, Naldi, Ilaria, additional, Santini, Valeria, additional, and Della Porta, Matteo G., additional

Published
2022
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13. Clinical Implications of p53 Dysfunction in Patients with Myelodysplastic Syndromes

Author

Riva, Elena, primary, Zampini, Matteo, additional, Alberto, Termanini, additional, Dall'Olio, Lorenzo, additional, Merlotti, Alessandra, additional, Kulasekararaj, Austin, additional, Calvi, Michela, additional, Di Vito, Clara, additional, Rahal, Daoud, additional, Bonometti, Arturo, additional, Croci, Giorgio, additional, Boveri, Emanuela, additional, Gianelli, Umberto, additional, Ponzoni, Maurilio, additional, Russo, Antonio, additional, Tinterri, Benedetta, additional, Re, Francesca, additional, Sauta, Elisabetta, additional, Saba, Elena, additional, Travaglino, Erica, additional, Ubezio, Marta, additional, Campagna, Alessia, additional, Lanino, Luca, additional, Maggioni, Giulia, additional, Tentori, Cristina Astrid, additional, Milanesi, Chiara, additional, Manes, Nicla, additional, D'Amico, Saverio, additional, Ficara, Francesca, additional, Crisafulli, Laura, additional, Mavilio, Domenico, additional, Lugli, Enrico, additional, Santoro, Armando, additional, Diez-Campelo, Maria, additional, Sanz, Guillermo, additional, Solé, Francesc, additional, Platzbecker, Uwe, additional, Santini, Valeria, additional, Kordasti, Shahram, additional, Fenaux, Pierre, additional, Haferlach, Torsten, additional, Remondini, Daniel, additional, Gastone, Castellani, additional, and Della Porta, Matteo G., additional

Published
2022
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14. MDS-352 Myelodysplastic syndromes with concomitant SF3B1 mutation and deletion of the long arm of chromosome 5

Author

Schwabkey, Zaker, Komrokji, Rami, Al Ali, Najla, Aguirre, Luis, Stahl, Maximilian, Ball, Somedeb, Mason, Emily, Savona, Michael, Santini, Valeria, Consagra, Angela, Platzbecker, Uwe, Sophie Kubasch, Anne, Madanat, Yazan, Fenaux, Pierre, Zhao, Lin-Pierre, Sekeres, Mikkael, Chandhok, Namrata, Della Porta, Matteo, Lanino, Luca, Dezern, Amy, Sallman, David, Padron, Eric, Xie, Zhuoer, Sasaki, Koji, Takaoka, Kensuke, Jain, Akhil, Del Rey Gonzalez, Monica, Diez Campelo, Maria, and Garcia-Manero, Guillermo

Published
2024
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15. Myelodysplastic Syndromes With Concomitant SF3B1 Mutation and Deletion of the Long Arm of Chromosome 5

Author

Schwabkey, Zaker, Komrokji, Rami, Al Ali, Najla, Aguirre, Luis, Stahl, Maximilian, Ball, Somedeb, Mason, Emily, Savona, Michael, Santini, Valeria, Consagra, Angela, Platzbecker, Uwe, Sophie Kubasch, Anne, Madanat, Yazan, Fenaux, Pierre, Zhao, Lin-Pierre, Sekeres, Mikkael, Chandhok, Namrata, Della Porta, Matteo, Lanino, Luca, Dezern, Amy, Sallman, David, Padron, Eric, Xie, Zhuoer, Sasaki, Koji, Takaoka, Kensuke, Jain, Akhil, Del Rey Gonzalez, Monica, Diez Campelo, Maria, and Garcia-Manero, Guillermo

Published
2024
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16. Case Report: Atypical Manifestations Associated With FOXP3 Mutations. The “Fil Rouge” of Treg Between IPEX Features and Other Clinical Entities?

Author

Gentile, Micaela, primary, Miano, Maurizio, additional, Terranova, Paola, additional, Giardino, Stefano, additional, Faraci, Maura, additional, Pierri, Filomena, additional, Drago, Enrico, additional, Verzola, Daniela, additional, Ghiggeri, Gianmarco, additional, Verrina, Enrico, additional, Angeletti, Andrea, additional, Cafferata, Barbara, additional, Grossi, Alice, additional, Ceccherini, Isabella, additional, Caridi, Gianluca, additional, Lugani, Francesca, additional, Nescis, Lorenzo, additional, Fiaccadori, Enrico, additional, Lanino, Luca, additional, Fenoglio, Daniela, additional, and La Porta, Edoardo, additional

Published
2022
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17. Real-World Efficacy and Safety of Luspatercept in Adult Patients with Transfusion-Dependent Anaemia Due to Lower-Risk Myelodysplastic Syndromes with Ring Sideroblasts (MDS-RS), Who Had an Unsatisfactory Response to or are Ineligible for Erythropoiesis Stimulating Agents: A Retrospective, Multicenter, Cohort Study

Author

Lanino, Luca, primary, Restuccia, Francesco, additional, Perego, Alessandra, additional, Ubezio, Marta, additional, Fattizzo, Bruno, additional, Riva, Marta, additional, Consagra, Angela, additional, Musto, Pellegrino, additional, Cilloni, Daniela, additional, Oliva, Esther Natalie, additional, Palmieri, Raffaele, additional, Poloni, Antonella, additional, Califano, Catello, additional, Capodanno, Isabella, additional, Itri, Federico, additional, Elena, Chiara, additional, Fozza, Claudio, additional, Pane, Fabrizio, additional, Pelizzari, Anna Maria, additional, Breccia, Massimo, additional, Di Bassiano, Francesco, additional, Crisa, Elena, additional, Ferrero, Dario, additional, Giai, Valentina, additional, Barraco, Daniela, additional, Vaccarino, Antonella, additional, Griguolo, Davide, additional, Minetto, Paola, additional, Martina, Quintini, additional, Paolini, Stefania, additional, Sanpaolo, Grazia, additional, Sessa, Mariarosaria, additional, Bocchia, Monica, additional, Di Renzo, Nicola, additional, Diral, Elisa, additional, Leuzzi, Livia, additional, Genua, Angelo, additional, Guarini, Attilio, additional, Molteni, Alfredo, additional, Nicolino, Barbara, additional, Occhini, Ubaldo, additional, Rivoli, Giulia, additional, Bono, Roberto, additional, Calvisi, Anna, additional, Castelli, Andrea, additional, Di Bona, Eros, additional, Di Veroli, Ambra, additional, Ferrara, Felicetto, additional, Fianchi, Luana, additional, Galimberti, Sara, additional, Grimaldi, Daniele, additional, Marchetti, Monia, additional, Norata, Marianna, additional, Frigeni, Marco, additional, Sancetta, Rosaria, additional, Selleri, Carmine, additional, Tanasi, Ilaria, additional, Tosi, Patrizia, additional, Turrini, Mauro, additional, Giordano, Laura, additional, Finelli, Carlo, additional, Pasini, Paolo, additional, Naldi, Ilaria, additional, Santini, Valeria, additional, and Della Porta, Matteo, additional

Published
2022
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18. Combining Gene Mutation with Transcriptomic Data Improves Outcome Prediction in Myelodysplastic Syndromes

Author

Sauta, Elisabetta, Zampini, Matteo, Dall'Olio, Daniele, Sala, Claudia, Todisco, Gabriele, Travaglino, Erica, Lanino, Luca, Tentori, Cristina Astrid, Maggioni, Giulia, D'Amico, Saverio, Asti, Gianluca, Dall'Olio, Lorenzo, Mosca, Ettore, Ubezio, Marta, Campagna, Alessia, Riva, Elena, Bicchieri, Marilena, Savevski, Victor, Santoro, Armando, Kordasti, Shahram, Santini, Valeria, Diez-Campelo, Maria, Kubasch, Anne Sophie, Platzbecker, Uwe, Fenaux, Pierre, Zhao, Lin Pierre, Zeidan, Amer M., Haferlach, Torsten, Castellani, Gastone, and Della Porta, Matteo Giovanni

Published
2023
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20. Fludarabine, High-Dose Cytarabine and Idarubicin-Based Induction May Overcome the Negative Prognostic Impact of FLT3-ITD in NPM1 Mutated AML, Irrespectively of FLT3-ITD Allelic Burden

Author

Minetto, Paola, primary, Candoni, Anna, additional, Guolo, Fabio, additional, Clavio, Marino, additional, Zannier, Maria Elena, additional, Miglino, Maurizio, additional, Dubbini, Maria Vittoria, additional, Carminati, Enrico, additional, Sicuranza, Anna, additional, Ciofini, Sara, additional, Colombo, Nicoletta, additional, Pugliese, Girolamo, additional, Marcolin, Riccardo, additional, Santoni, Adele, additional, Ballerini, Filippo, additional, Lanino, Luca, additional, Cea, Michele, additional, Gobbi, Marco, additional, Bocchia, Monica, additional, Fanin, Renato, additional, and Lemoli, Roberto Massimo, additional

Published
2020
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22. Improved Overall Survival Among Luspatercept Responders and Predictors of Response

Author

Consagra, Angela, Lanino, Luca, Al Ali, Najla H, Aguirre, Luis E., Xie, Zhuoer, Chan, Onyee, Andreossi, Gloria, Rigodanza, Luca, Sanna, Alessandro, Raddi, Marco Gabriele, Walker, Alison R., Kuykendall, Andrew T., Lancet, Jeffrey, Padron, Eric, Sallman, David A, Restuccia, Francesco, Perego, Alessandra, Ubezio, Marta, Fattizzo, Bruno, Riva, Marta, Campagna, Alessia, Della Porta, Matteo Giovanni, Santini, Valeria, and Komrokji, Rami S.

Abstract

Introduction

Published
2023
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23. Data-Driven Harmonization of 2022 Who and ICC Classifications of Myelodysplastic Syndromes/Neoplasms (MDS): A Study By the International Consortium for MDS (icMDS)

Author

Lanino, Luca, Ball, Somedeb, Bewersdorf, Jan Philipp, Marchetti, Monia, Maggioni, Giulia, Travaglino, Erica, Al Ali, Najla H, Fenaux, Pierre, Platzbecker, Uwe, Santini, Valeria, Diez-Campelo, Maria, Singh, Avani M, Jain, Akriti Gupta, Aguirre, Luis E., Tinsley-Vance, Sara M., Schwabkey, Zaker I., Chan, Onyee, Xie, Zhuoer, Brunner, Andrew M., Kuykendall, Andrew T., Bennett, John M., Buckstein, Rena, Bejar, Rafael, Carraway, Hetty E., DeZern, Amy E., Griffiths, Elizabeth A., Halene, Stephanie, Hasserjian, Robert, Lancet, Jeffrey, List, Alan F., Loghavi, Sanam, Odenike, Olatoyosi, Padron, Eric, Patnaik, Mrinal M., Roboz, Gail J., Stahl, Maximilian, Sekeres, Mikkael A., Steensma, David Peter, Savona, Michael R., Taylor, Justin, Xu, Mina, Sweet, Kendra, Sallman, David A, Nimer, Stephen D., Hourigan, Christopher S., Wei, Andrew H., Sauta, Elisabetta, D'Amico, Saverio, Asti, Gianluca, Castellani, Gastone, Borate, Uma M., Sanz, Guillermo, Efficace, Fabio, Gore, Steven D., Kim, Tae Kon, Daver, Naval, Garcia-Manero, Guillermo, Rozman, María, Orfao, Alberto, Wang, Sa A., Foucar, M. Kathy, Germing, Ulrich, Haferlach, Torsten, Scheinberg, Phillip, Miyazaki, Yasushi, Iastrebner, Marcelo, Kulasekararaj, Austin, Cluzeau, Thomas, Kordasti, Shahram, van de Loosdrecht, Arjan A., Ades, Lionel, Zeidan, Amer M., Komrokji, Rami S., and Della Porta, Matteo Giovanni

Abstract

Background.The inclusion of gene mutations and chromosomal abnormalities in the 2022 WHO and ICC Classifications of MDS has enhanced diagnostic precision and is expected to improve clinical decision-making process. Although these two systems share similarities, clinically relevant discrepancies still exist and potentially cause inconsistency in their adoption in a clinical setting. In this study on behalf of the International Consortium for MDS (icMDS), we adopted a data-driven approach to provide a harmonization roadmap between the 2022 WHO and ICC classification for MDS. A modified Delphi Process consensus approach is currently ongoing among icMDS experts to finalize a harmonized MDS classification scheme.

Published
2023
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24. Clinical and Genomic-Based Decision Support System to Define the Optimal Timing of Allogeneic Hematopoietic Stem Cell Transplantation in Patients with Myelodysplastic Syndromes (MDS)

Author

Tentori, Cristina Astrid, Gregorio, Caterina, Robin, Marie, Gagelmann, Nico, Gurnari, Carmelo, Ball, Somedeb, Caballero Berrocal, Juan Carlos, Lanino, Luca, D'Amico, Saverio, Spreafico, Marta, Maggioni, Giulia, Travaglino, Erica, Sauta, Elisabetta, Meggendorfer, Manja, Zhao, Lin-Pierre, Bernardi, Massimo, Di Grazia, Carmen, Vago, Luca, Rivoli, Giulia, Borin, Lorenza Maria, Chiusolo, Patrizia, Giaccone, Luisa, Voso, Maria Teresa, Bewersdorf, Jan Philipp, Nibourel, Olivier, Díaz-Beyá, Marina, Jerez, Andres, Hernandez, Francisca Maria, Velázquez Kennedy, Kyra, Xicoy, Blanca, Ubezio, Marta, Campagna, Alessia, Russo, Antonio, Todisco, Gabriele, Mannina, Daniele, Bramanti, Stefania, Zampini, Matteo, Riva, Elena, Bicchieri, Marilena, Asti, Gianluca, Viviani, Filippo, Buizza, Alessandro, Tinterri, Benedetta, Bacigalupo, Andrea, Rambaldi, Alessandro, Passamonti, Francesco, Ciceri, Fabio, Savevski, Victor, Santoro, Armando, Al Ali, Najla H, Sallman, David A, Sole, Francesc, Garcia-Manero, Guillermo, Germing, Ulrich, Kordasti, Shahram, Santini, Valeria, Sanz, Guillermo, Kern, Wolfgang, Kubasch, Anne Sophie, Platzbecker, Uwe, Diez-Campelo, Maria, Maciejewski, Jaroslaw P., Ades, Lionel, Fenaux, Pierre, Haferlach, Torsten, Zeidan, Amer M., Castellani, Gastone, Komrokji, Rami S., Ieva, Francesca, and Della Porta, Matteo Giovanni

Abstract

Purpose. Allogeneic hematopoietic stem cell transplantation (HSCT) is the only potentially curative treatment for patients with myelodysplastic syndromes (MDS). Several issues must be considered when evaluating the benefits and risks of HSCT for patients with MDS, with the timing of transplantation during the disease course being a crucial question.

Published
2023
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25. Clinical Text Reports to Stratify Patients Affected with Myeloid Neoplasms Using Natural Language Processing

Author

Asti, Gianluca, Sauta, Elisabetta, Curti, Nico, Carlini, Gianluca, Dall'Olio, Lorenzo, Lanino, Luca, Maggioni, Giulia, Campagna, Alessia, Ubezio, Marta, Russo, Antonio, Todisco, Gabriele, Tentori, Cristina Astrid, Morandini, Pierandrea, Bicchieri, Marilena, Grondelli, Maria Chiara, Zampini, Matteo, Travaglino, Erica, Savevski, Victor, Derus, Nicolas Riccardo, Dall'Olio, Daniele, Sala, Claudia, Zhao, Lin-Pierre, Santoro, Armando, Kordasti, Shahram, Santini, Valeria, Kubasch, Anne Sophie, Platzbecker, Uwe, Diez-Campelo, Maria, Fenaux, Pierre, Zeidan, Amer M., Haferlach, Torsten, Castellani, Gastone, Della Porta, Matteo Giovanni, and D'Amico, Saverio

Abstract

Background:The availability of multimodal patient data, such as demographics, clinical, imaging, treatment, quality of life, outcomes and wearables data, as well as genome sequencing, have paved the way for the development of multimodal clinical solutions that introduce personalized or precision medicine. The clinical report is an information layer that contains relevant information about the disease in addition to the patient's point of view. Natural language processing (NLP) is a branch of artificial intelligence (AI) and its pre-trained language models are the key technology for extracting value from this data layer.

Published
2023
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26. Molecular Classification of Chronic Myelomonocytic Leukemia: Results of the Analysis of an International Cohort of 2,471 Patients

Author

Lanino, Luca, Hunter, Anthony M., Sala, Claudia, Dall'Olio, Daniele, Dall'Olio, Lorenzo, Pleyer, Lisa, Xicoy, Blanca, Meggendorfer, Manja, Sauta, Elisabetta, Travaglino, Erica, Robin, Marie, Palomo, Laura, Quintela, David, Jerez, Andres, Cornejo, Elena, Garcia Martin, Paloma, Díaz-Beyá, Marina, Avendaño Pita, Alejandro, Roldan, Veronica, Fiallo Suarez, Dolly Viviana, Cerezo Velasco, Estefania, Calabuig, Marisa, Rivoli, Giulia, Bernardi, Massimo, Onida, Francesco, Borin, Lorenza Maria, Passamonti, Francesco, Campagna, Alessia, Ubezio, Marta, Russo, Antonio, Todisco, Gabriele, Maggioni, Giulia, Tentori, Cristina Astrid, Viviani, Filippo, Buizza, Alessandro, Asti, Gianluca, Zampini, Matteo, Santoro, Armando, Kern, Wolfgang, Platzbecker, Uwe, Sole, Francesc, Diez-Campelo, Maria, Consagra, Angela, Al Ali, Najla H, Sallman, David A, Fenaux, Pierre, Itzykson, Raphael, Fontenay, Michaela, Zeidan, Amer M., Komrokji, Rami S., Santini, Valeria, Haferlach, Torsten, Germing, Ulrich, D'Amico, Saverio, Castellani, Gastone, Solary, Eric, Padron, Eric, and Della Porta, Matteo Giovanni

Abstract

Background.Chronic myelomonocytic leukemia (CMML) is a rare myeloid neoplasm that shares both dysplastic and proliferative features and includes patients with highly heterogeneous clinical manifestations and prognosis. Despite known co-mutation patterns that are suggesting of a CMML diagnosis such as TET2and SRSF2mutations, the current diagnosis and classification schemes rely solely on morphological criteria that fail to capture the genomic heterogeneity of the disease. Here we perform an unsupervised analysis using only genomic features to generate a novel classification schema of CMML patients with unique clinical features.

Published
2023
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27. Fludarabine, High-Dose Cytarabine and Idarubicin-Based Induction May Overcome the Negative Prognostic Impact of FLT3 -ITD in NPM1 Mutated AML, Irrespectively of FLT3 -ITD Allelic Burden.

Author

Minetto, Paola, Candoni, Anna, Guolo, Fabio, Clavio, Marino, Zannier, Maria Elena, Miglino, Maurizio, Dubbini, Maria Vittoria, Carminati, Enrico, Sicuranza, Anna, Ciofini, Sara, Colombo, Nicoletta, Pugliese, Girolamo, Marcolin, Riccardo, Santoni, Adele, Ballerini, Filippo, Lanino, Luca, Cea, Michele, Gobbi, Marco, Bocchia, Monica, and Fanin, Renato

Subjects
RESEARCH, DRUG efficacy, SURVIVAL, GENETIC mutation, GENETICS, MULTIVARIATE analysis, ACUTE myeloid leukemia, ALLELES, MEDICAL cooperation, FLUDARABINE, IDARUBICIN, TREATMENT effectiveness, CYTARABINE, HEMATOPOIETIC stem cell transplantation, LONGITUDINAL method
Abstract

Simple Summary: The prognostic relevance of molecular aberrations in acute myeloid leukemia (AML) has been prevalently tested in patients receiving conventional 3+7 induction. Recently, there has been a renewed interest in intensified inductions, but very few data are available on the impact of the most frequent genetic alterations with these alternative treatments. We analyzed a large multicentric cohort of younger AML patients harboring NPM1 and FLT3-ITD mutations receiving an intensified fludarabine-containing regimen (FLAI). Our data suggest that in NPM1 mut patients, FLAI may overcome the prognostic influence of co-mutated FLT3-ITD. The increased efficacy of this treatment seems to reduce the need for early consolidation with allogeneic transplant in double-mutated patients. Our data strongly support FLAI as an ideal backbone for combination with innovative targeted drugs, in order to further improve patients' outcome. The mutations of NPM1 and FLT3-ITD represent the most frequent genetic aberration in acute myeloid leukemia. Indeed, the presence of an NPM1 mutation reduces the negative prognostic impact of FLT3-ITD in patients treated with conventional "3+7" induction. However, little information is available on their prognostic role with intensified regimens. Here, we investigated the efficacy of a fludarabine, high-dose cytarabine and idarubicin induction (FLAI) in 149 consecutive fit AML patients (median age 52) carrying the NPM1 and/or FLT3-ITD mutation, treated from 2008 to 2018. One-hundred-and-twenty-nine patients achieved CR (86.6%). After a median follow up of 68 months, 3-year overall survival was 58.6%. Multivariate analysis disclosed that both NPM1mut (p < 0.05) and ELN 2017 risk score (p < 0.05) were significant predictors of survival. NPM1-mutated patients had a favorable outcome, with no significant differences between patients with or without concomitant FLT3-ITD (p = 0.372), irrespective of FLT3-ITD allelic burden. Moreover, in landmark analysis, performing allogeneic transplantation (HSCT) in first CR proved to be beneficial only in ELN 2017 high-risk patients. Our data indicate that FLAI exerts a strong anti-leukemic effect in younger AML patients with NPM1mut and question the role of HSCT in 1st CR in NPM1mut patients with concomitant FLT3-ITD. [ABSTRACT FROM AUTHOR]

Published
2021
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28. Data-driven, harmonised classification system for myelodysplastic syndromes: a consensus paper from the International Consortium for Myelodysplastic Syndromes.

Author

Komrokji RS, Lanino L, Ball S, Bewersdorf JP, Marchetti M, Maggioni G, Travaglino E, Al Ali NH, Fenaux P, Platzbecker U, Santini V, Diez-Campelo M, Singh A, Jain AG, Aguirre LE, Tinsley-Vance SM, Schwabkey ZI, Chan O, Xie Z, Brunner AM, Kuykendall AT, Bennett JM, Buckstein R, Bejar R, Carraway HE, DeZern AE, Griffiths EA, Halene S, Hasserjian RP, Lancet J, List AF, Loghavi S, Odenike O, Padron E, Patnaik MM, Roboz GJ, Stahl M, Sekeres MA, Steensma DP, Savona MR, Taylor J, Xu ML, Sweet K, Sallman DA, Nimer SD, Hourigan CS, Wei AH, Sauta E, D'Amico S, Asti G, Castellani G, Delleani M, Campagna A, Borate UM, Sanz G, Efficace F, Gore SD, Kim TK, Daver N, Garcia-Manero G, Rozman M, Orfao A, Wang SA, Foucar MK, Germing U, Haferlach T, Scheinberg P, Miyazaki Y, Iastrebner M, Kulasekararaj A, Cluzeau T, Kordasti S, van de Loosdrecht AA, Ades L, Zeidan AM, and Della Porta MG

Abstract

The WHO and International Consensus Classification 2022 classifications of myelodysplastic syndromes enhance diagnostic precision and refine decision-making processes in these diseases. However, some discrepancies still exist and potentially cause inconsistency in their adoption in a clinical setting. We adopted a data-driven approach to provide a harmonisation between these two classification systems. We investigated the importance of genomic features and their effect on the cluster assignment process to define harmonised entity labels. A panel of expert haematologists, haematopathologists, and data scientists who are members of the International Consortium for Myelodysplastic Syndromes was formed and a modified Delphi consensus process was adopted to harmonise morphologically defined categories without a distinct genomic profile. The panel held regular online meetings and participated in a two-round survey using an online voting tool. We identified nine clusters with distinct genomic features. The cluster of highest hierarchical importance was characterised by biallelic TP53 inactivation. Cluster assignment was irrespective of blast count. Individuals with monoallelic TP53 inactivation were assigned to other clusters. Hierarchically, the second most important group included myelodysplastic syndromes with del(5q). Isolated del(5q) and less than 5% of blast cells in the bone marrow were the most relevant label-defining features. The third most important cluster included myelodysplastic syndromes with mutated SF3B1. The absence of isolated del(5q), del(7q)/-7, abn3q26.2, complex karyotype, RUNX1 mutations, or biallelic TP53 were the basis for a harmonised label of this category. Morphologically defined myelodysplastic syndrome entities showed large genomic heterogeneity that was not efficiently captured by single-lineage versus multilineage dysplasia, marrow blasts, hypocellularity, or fibrosis. We investigated the biological continuum between myelodysplastic syndromes with more than 10% bone marrow blasts and acute myeloid leukaemia, and found only a partial overlap in genetic features. After the survey, myelodysplastic syndromes with low blasts (ie, less than 5%) and myelodysplastic syndromes with increased blasts (ie, 5% or more) were recognised as disease entities. Our data-driven approach can efficiently harmonise current classifications of myelodysplastic syndromes and provide a reference for patient management in a real-world setting., Competing Interests: Declaration of interests UG reports speaker honoraria from Novartis, AbbVie, and BMS; and institutional research support from BMS, AbbVie, and Jazz Pharmaceuticals. FE reports consultancy or advisory roles for AbbVie, Incyte, Syros, Novartis, and Jazz Pharmaceuticals. SH reports research support from STORM Therapeutics and AstraZeneca. EAG reports honoraria from AAMDS, MedscapeLIVE!, MediCom Worldwide, MJH Life Sciences, ASH, MDS International Foundation, and Physicians’ Education Resource; consulting fees from AbbVie, Alexion, Apellis, Takeda Oncology, Astex/Taiho Oncology, Alexion/AstraZeneca Rare Disease, Celgene/BMS, CTI BioPharma, Novartis, Partner Therapeutics, Picnic Health, and Servier; and research funding from Alexion, Apellis, Astex /Otsuka/Taiho Oncology, Blueprint Medicines, Celldex Therapeutics, Genentech, and NextCure. MAS reports participation on advisory boards for BMS, Kurome, Schrödinger, and Karyopharm. MD-C reports participation on a data safety monitoring board or advisory board for BMS, Novartis, Blueprint Medicines, GSK, Agios, Hemavan, Syros, Keros, Curis, and Astex/Otsuka; and payment or honoraria for lectures, presentations, speakers’ bureaus, manuscript writing, or educational events for BMS, Novartis, and Keros. UP reports research support and honoraria from BMS, Geron, Curis, AbbVie, and Janssen. RBe reports employment or equity from Aptose Biosciences; participation on advisory boards for BMS, Servier, NeoGenomics, and Geron; being Data Monitoring Committee Chair for Gilead, Ipsen, and Keros; and consultancy for TenSixteen. YM reports honoraria from Nippon Shinyaku, BMS, Novartis, Sumitomo Pharma, Kyowa Kirin, AbbVie, Daiichi Sankyo, Takeda, Janssen, Astellas, Pfizer, Eisai, and Otsuka; and research funding from Chugai. AED reports participation on advisory boards, consultancy, or honoraria from Celgene/BMS, Agios, Novartis, Astellas, and Gilead; and participation on clinical trial committees or data safety monitoring boards for Novartis, AbbVie, Kura, Geron, Servier, Keros, and Celgene/BMS. DPS reports employment by Ajax Therapeutics; former employment by Novartis; and minor equity in Arrowhead and Bluebird. TKK reports consultancy for Agenus and ImmunoBiome. AK reports research support from Novartis and BMS; consulting fees from Alexion, Novartis, Amgen, Agios, Pfizer, Samsung, Celgene, F Hoffmann-La Roche, and Sobi; honoraria from Alexion, Novartis, Pfizer, Amgen, Samsung, Celgene, F Hoffmann-La Roche, BMS, Sobi, and Silence Therapeutics; and speakers fees from Alexion, Novartis, Amgen, Pfizer, Celgene, F Hoffmann-La Roche, and Sobi. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

Published
2024
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29. Chronic myelomonocytic leukemia with ring sideroblasts/ SF3B1 mutation presents with low monocyte count and resembles myelodysplastic syndromes with-RS/ SF3B1 mutation in terms of phenotype and prognosis.

Author

Xicoy B, Pomares H, Morgades M, Germing U, Arnan M, Tormo M, Palomo L, Orna E, Della Porta M, Schulz F, Díaz-Beya M, Esteban A, Molero A, Lanino L, Avendaño A, Hernández F, Roldan V, Ubezio M, Pineda A, Díez-Campelo M, and Zamora L

Abstract

Introduction: Chronic myelomonocytic leukemia (CMML) and myelodysplastic syndromes (MDS) with ring sideroblasts (RS) or SF3B1 mutation (MDS-RS/ SF3B1 ) differ in many clinical features, but share others, such as anemia. RS and SF3B1 mutation can also be found in CMML., Methods: We compared CMML with and without RS/ SF3B1 and MDS-RS/ SF3B1 considering the criteria established by the 2022 World Health Organization classification., Results: A total of 815 patients were included (CMML, n=319, CMML-RS/ SF3B1 , n=172 and MDS-RS/ SF3B1 , n=324). The percentage of RS was ≥15% in almost all CMML-RS/ SF3B1 patients (169, 98.3%) and most (125, 72.7%) showed peripheral blood monocyte counts between 0.5 and 0.9 x10 9 /L and low risk prognostic categories. CMML-RS/ SF3B1 differed significantly from classical CMML in the main clinical characteristics, whereas it resembled MDS-RS/ SF3B1 . At a molecular level, CMML and CMML-RS/ SF3B1 had a significantly higher frequency of mutations in TET2 (mostly multi-hit) and ASXL1 (p=0.013) and CMML had a significantly lower frequency of DNMT3A and SF3B1 mutations compared to CMML/MDS-RS/ SF3B1 . Differences in the median overall survival among the three groups were statistically significant: 6.75 years (95% confidence interval [CI] 5.41-8.09) for CMML-RS/ SF3B1 vs. 3.17 years (95% CI 2.56-3.79) for CMML vs. 16.47 years (NA) for MDS-RS/ SF3B1 , p<0.001. Regarding patients with CMML and MDS, both with SF3B1 mutation, survival did not significantly differ. CMML had a higher risk of transformation to acute myeloid leukemia (24% at 8 years, 95%CI 19%-30%)., Discussion: CMML-RS/ SF3B1 mutation resembles MDS-RS/ SF3B1 in terms of phenotype and clearly differs from CMML. The presence of ≥15% RS and/or SF3B1 in CMML is associated with a low monocyte count. SF3B1 mutation clearly improves the prognosis of CMML., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Xicoy, Pomares, Morgades, Germing, Arnan, Tormo, Palomo, Orna, Della Porta, Schulz, Díaz-Beya, Esteban, Molero, Lanino, Avendaño, Hernández, Roldan, Ubezio, Pineda, Díez-Campelo and Zamora.)

Published
2024
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