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34 results on '"Maggioni, Giulia"'

2. Mutations in the splicing factor SF3B1 are linked to frequent emergence of HLA-DRlow/neg monocytes in lower-risk myelodysplastic neoplasms

Author

Winter, Susann, Schneider, Marie, Oelschlaegel, Uta, Maggioni, Giulia, Riva, Elena, Raddi, Marco Gabriele, Bencini, Sara, Peruzzi, Benedetta, Choy, Desmond, Antunes Dos Reis, Rita, Güse, Esther, Lischer, Christopher, Vera, Julio, Timms, Jessica A., Sompairac, Nicolas, Sockel, Katja, Poloni, Antonella, Tunger, Antje, Della Porta, Matteo Giovanni, Santini, Valeria, Schmitz, Marc, Platzbecker, Uwe, and Kordasti, Shahram

Published
2024
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3. Data-driven, harmonised classification system for myelodysplastic syndromes: a consensus paper from the International Consortium for Myelodysplastic Syndromes

Author

Komrokji, Rami S, Lanino, Luca, Ball, Somedeb, Bewersdorf, Jan P, Marchetti, Monia, Maggioni, Giulia, Travaglino, Erica, Al Ali, Najla H, Fenaux, Pierre, Platzbecker, Uwe, Santini, Valeria, Diez-Campelo, Maria, Singh, Avani, Jain, Akriti G, Aguirre, Luis E, Tinsley-Vance, Sarah M, Schwabkey, Zaker I, Chan, Onyee, Xie, Zhouer, 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 P, Lancet, Jeffrey, List, Alan F, Loghavi, Sanam, Odenike, Olatoyosi, Padron, Eric, Patnaik, Mrinal M, Roboz, Gail J, Stahl, Maximilian, Sekeres, Mikkael A, Steensma, David P, Savona, Michael R, Taylor, Justin, Xu, Mina L, Sweet, Kendra, Sallman, David A, Nimer, Stephen D, Hourigan, Christopher S, Wei, Andrew H, Sauta, Elisabetta, D’Amico, Saverio, Asti, Gianluca, Castellani, Gastone, Delleani, Mattia, Campagna, Alessia, Borate, Uma M, Sanz, Guillermo, Efficace, Fabio, Gore, Steven D, Kim, Tae Kon, Daver, Navel, Garcia-Manero, Guillermo, Rozman, Maria, Orfao, Alberto, Wang, Sa A, Foucar, M Kathryn, 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, and Della Porta, Matteo G

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

Author

DʼAmico, 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, Zhao, Lin Pierre, Platzbecker, Uwe, Diez-Campelo, Maria, Santini, Valeria, Fenaux, Pierre, Haferlach, Torsten, Krogh, Anders, Zazo, Santiago, Fariselli, Piero, Sanavia, Tiziana, Della Porta, Matteo Giovanni, and Castellani, Gastone

Published
2024
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6. 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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8. 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
FEDERATED learning, ARTIFICIAL intelligence, HEMATOLOGIC malignancies, RANDOM forest algorithms, MYELODYSPLASTIC syndromes
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. [ABSTRACT FROM AUTHOR]

Published
2024
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9. 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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10. Thyroid dysfunction in children and adolescents affected by undernourished and overnourished eating disorders

Author

Calcaterra, Valeria, primary, Magenes, Vittoria Carlotta, additional, Siccardo, Francesca, additional, Hruby, Chiara, additional, Basso, Martina, additional, Conte, Veronica, additional, Maggioni, Giulia, additional, Fabiano, Valentina, additional, Russo, Susanna, additional, Veggiotti, Pierangelo, additional, and Zuccotti, Gianvincenzo, additional

Published
2023
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11. S170: MYELODYSPLASTIC NEOPLASMS (MDS) CLASSIFICATION FROM WHO 2017 TO WHO 2022 AND ICC 2022): AN EXPANDED ANALYSIS OF 7017 PATIENTS ON BEHALF OF THE INTERNATIONAL CONSORTIUM FOR MDS (ICMDS)

Author

Komrokji, Rami S., primary, Ball, Somdeb, additional, Maggioni, Giulia, additional, Travaglino, Erica, additional, Al Ali, Najla, additional, Fenaux, Pierre, additional, Platzbecker, Uwe, additional, Santini, Valeria, additional, Díez Campelo, María, additional, Haferlach, Torsten, additional, Singh, Avani, additional, Jain, Akriti, additional, Aguirre, Luis E., additional, Tinsley, Sara, additional, Schwabkey, Zaker, additional, Chan, Onyee, additional, Xie, Zhuoer, additional, Brunner, Andrew, additional, Kuykendall, Andrew, additional, Bennett, John, additional, Buckstein, Rena, additional, Bejar, Rafael, additional, Bewersdorf, Jan, additional, Carraway, Hetty, additional, Dezern, Amy, additional, Griffiths, Elizabeth A., additional, Halene, Stephanie, additional, Hasserjian, Robert Paul, additional, Loghavi, Sanam, additional, Odenike, Olatoyosi, additional, Patnaik, Mrinal, additional, Roboz, Gail, additional, Stahl, Maximillian, additional, Sekeres, Mikkael, additional, Steensma, David, additional, Savona, Michael Robert, additional, Taylor, Justin, additional, Xu, Mina, additional, Sweet, Kendra, additional, Lancet, Jeffrey, additional, List, Alan, additional, Padron, Eric, additional, Sallman, David, additional, Zeidan, Amer M., additional, and Della Porta, Matteo Giovanni, additional

Published
2023
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12. 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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13. 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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14. 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

15. 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

16. Mutations in the splicing factor SF3B1are linked to frequent emergence of HLA-DRlow/negmonocytes in lower-risk myelodysplastic neoplasms

Author

Winter, Susann, Schneider, Marie, Oelschlaegel, Uta, Maggioni, Giulia, Riva, Elena, Raddi, Marco Gabriele, Bencini, Sara, Peruzzi, Benedetta, Choy, Desmond, Antunes Dos Reis, Rita, Güse, Esther, Lischer, Christopher, Vera, Julio, Timms, Jessica A., Sompairac, Nicolas, Sockel, Katja, Poloni, Antonella, Tunger, Antje, Della Porta, Matteo Giovanni, Santini, Valeria, Schmitz, Marc, Platzbecker, Uwe, and Kordasti, Shahram

Published
2024
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18. 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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19. 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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20. A Population-Based Study on Survival of Higher Risks Myelofibrosis Patients Treated with Ruxolitinib in the Italian Lombardy Region

Author

Mora, Barbara, primary, Pellegrini, Giacomo, additional, Franchi, Matteo, additional, Maffioli, Margherita, additional, Brociner, Marco, additional, Guglielmelli, Paola, additional, Voso, Maria Teresa, additional, Ottone, Tiziana, additional, Ubezio, Marta, additional, Maggioni, Giulia, additional, Merli, Michele, additional, Vannucchi, Alessandro M., additional, Della Porta, Matteo G., additional, Corrao, Giovanni, additional, and Passamonti, Francesco, additional

Published
2022
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22. Clinical relevance of clonal hematopoiesis in persons aged ≥80 years

Author

Rossi, Marianna, primary, Meggendorfer, Manja, additional, Zampini, Matteo, additional, Tettamanti, Mauro, additional, Riva, Emma, additional, Travaglino, Erica, additional, Bersanelli, Matteo, additional, Mandelli, Sara, additional, Antonella Galbussera, Alessia, additional, Mosca, Ettore, additional, Saba, Elena, additional, Chiereghin, Chiara, additional, Manes, Nicla, additional, Milanesi, Chiara, additional, Ubezio, Marta, additional, Morabito, Lucio, additional, Peano, Clelia, additional, Soldà, Giulia, additional, Asselta, Rosanna, additional, Duga, Stefano, additional, Selmi, Carlo, additional, De Santis, Maria, additional, Malik, Karolina, additional, Maggioni, Giulia, additional, Bicchieri, Marilena, additional, Campagna, Alessia, additional, Tentori, Cristina A., additional, Russo, Antonio, additional, Civilini, Efrem, additional, Allavena, Paola, additional, Piazza, Rocco, additional, Corrao, Giovanni, additional, Sala, Claudia, additional, Termanini, Alberto, additional, Giordano, Laura, additional, Detoma, Paolo, additional, Malabaila, Aurelio, additional, Sala, Luca, additional, Rosso, Stefano, additional, Zanetti, Roberto, additional, Saitta, Claudia, additional, Riva, Elena, additional, Condorelli, Gianluigi, additional, Passamonti, Francesco, additional, Santoro, Armando, additional, Sole, Francesc, additional, Platzbecker, Uwe, additional, Fenaux, Pierre, additional, Bolli, Niccolò, additional, Castellani, Gastone, additional, Kern, Wolfgang, additional, Vassiliou, George S., additional, Haferlach, Torsten, additional, Lucca, Ugo, additional, and Della Porta, Matteo G., additional

Published
2021
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23. Clinical relevance of clonal hematopoiesis in persons aged ≥80 years

Author

Rossi, M, Meggendorfer, M, Zampini, M, Tettamanti, M, Riva, E, Travaglino, E, Bersanelli, M, Mandelli, S, Galbussera, A, Mosca, E, Saba, E, Chiereghin, C, Manes, N, Milanesi, C, Ubezio, M, Morabito, L, Peano, C, Soldà, G, Asselta, R, Duga, S, Selmi, C, De Santis, M, Malik, K, Maggioni, G, Bicchieri, M, Campagna, A, Tentori, C, Russo, A, Civilini, E, Allavena, P, Piazza, R, Corrao, G, Sala, C, Termanini, A, Giordano, L, Detoma, P, Malabaila, A, Sala, L, Rosso, S, Zanetti, R, Saitta, C, Condorelli, G, Passamonti, F, Santoro, A, Sole, F, Platzbecker, U, Fenaux, P, Bolli, N, Castellani, G, Kern, W, Vassiliou, G, Haferlach, T, Lucca, U, Della Porta, M, Rossi, Marianna, Meggendorfer, Manja, Zampini, Matteo, Tettamanti, Mauro, Riva, Emma, Travaglino, Erica, Bersanelli, Matteo, Mandelli, Sara, Galbussera, Alessia Antonella, Mosca, Ettore, Saba, Elena, Chiereghin, Chiara, Manes, Nicla, Milanesi, Chiara, Ubezio, Marta, Morabito, Lucio, Peano, Clelia, Soldà, Giulia, Asselta, Rosanna, Duga, Stefano, Selmi, Carlo, De Santis, Maria, Malik, Karolina, Maggioni, Giulia, Bicchieri, Maria Elena, Campagna, Alessia, Tentori, Cristina Astrid, Russo, Antonio, Civilini, Efrem, Allavena, Paola, Piazza, Rocco, Corrao, Giovanni, Sala, Claudia, Termanini, Alberto, Giordano, Laura, Detoma, Paolo, Malabaila, Aurelio, Sala, Luca, Rosso, Stefano, Zanetti, Roberto, Saitta, Claudia, Riva, Elena, Condorelli, Gianluigi, Passamonti, Francesco, Santoro, Armando, Sole, Francesc, Platzbecker, Uwe, Fenaux, Pierre, Bolli, Niccolo, Castellani, Gastone, Kern, Wolfgang, Vassiliou, George, Haferlach, Torsten, Lucca, Ugo, Della Porta, Matteo G, Rossi, M, Meggendorfer, M, Zampini, M, Tettamanti, M, Riva, E, Travaglino, E, Bersanelli, M, Mandelli, S, Galbussera, A, Mosca, E, Saba, E, Chiereghin, C, Manes, N, Milanesi, C, Ubezio, M, Morabito, L, Peano, C, Soldà, G, Asselta, R, Duga, S, Selmi, C, De Santis, M, Malik, K, Maggioni, G, Bicchieri, M, Campagna, A, Tentori, C, Russo, A, Civilini, E, Allavena, P, Piazza, R, Corrao, G, Sala, C, Termanini, A, Giordano, L, Detoma, P, Malabaila, A, Sala, L, Rosso, S, Zanetti, R, Saitta, C, Condorelli, G, Passamonti, F, Santoro, A, Sole, F, Platzbecker, U, Fenaux, P, Bolli, N, Castellani, G, Kern, W, Vassiliou, G, Haferlach, T, Lucca, U, Della Porta, M, Rossi, Marianna, Meggendorfer, Manja, Zampini, Matteo, Tettamanti, Mauro, Riva, Emma, Travaglino, Erica, Bersanelli, Matteo, Mandelli, Sara, Galbussera, Alessia Antonella, Mosca, Ettore, Saba, Elena, Chiereghin, Chiara, Manes, Nicla, Milanesi, Chiara, Ubezio, Marta, Morabito, Lucio, Peano, Clelia, Soldà, Giulia, Asselta, Rosanna, Duga, Stefano, Selmi, Carlo, De Santis, Maria, Malik, Karolina, Maggioni, Giulia, Bicchieri, Maria Elena, Campagna, Alessia, Tentori, Cristina Astrid, Russo, Antonio, Civilini, Efrem, Allavena, Paola, Piazza, Rocco, Corrao, Giovanni, Sala, Claudia, Termanini, Alberto, Giordano, Laura, Detoma, Paolo, Malabaila, Aurelio, Sala, Luca, Rosso, Stefano, Zanetti, Roberto, Saitta, Claudia, Riva, Elena, Condorelli, Gianluigi, Passamonti, Francesco, Santoro, Armando, Sole, Francesc, Platzbecker, Uwe, Fenaux, Pierre, Bolli, Niccolo, Castellani, Gastone, Kern, Wolfgang, Vassiliou, George, Haferlach, Torsten, Lucca, Ugo, and Della Porta, Matteo G

Abstract

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with increased risk of cancers and inflammation-related diseases. This phenomenon becomes common in persons aged ≥80 years, in whom the implications of CHIP are not well defined. We performed a mutational screening in 1794 persons aged ≥80 years and investigated the relationships between CHIP and associated pathologies. Mutations were observed in one-third of persons aged ≥80 years and were associated with reduced survival. Mutations in JAK2 and splicing genes, multiple mutations (DNMT3A, TET2, and ASXL1 with additional genetic lesions), and variant allele frequency ≥0.096 had positive predictive value for myeloid neoplasms. Combining mutation profiles with abnormalities in red blood cell indices improved the ability of myeloid neoplasm prediction. On this basis, we defined a predictive model that identifies 3 risk groups with different probabilities of developing myeloid neoplasms. Mutations in DNMT3A, TET2, ASXL1, or JAK2 were associated with coronary heart disease and rheumatoid arthritis. Cytopenia was common in persons aged ≥80 years, with the underlying cause remaining unexplained in 30% of cases. Among individuals with unexplained cytopenia, the presence of highly specific mutation patterns was associated with myelodysplastic-like phenotype and a probability of survival comparable to that of myeloid neoplasms. Accordingly, 7.5% of subjects aged ≥80 years with cytopenia had presumptive evidence of myeloid neoplasm. In summary, specific mutational patterns define different risk of developing myeloid neoplasms vs inflammatory-associated diseases in persons aged ≥80 years. In individuals with unexplained cytopenia, mutational status may identify those subjects with presumptive evidence of myeloid neoplasms.

Published
2021

24. 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

Published
2023
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25. 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

Published
2023
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26. 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

Published
2023
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27. 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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28. Classification and Personalized Prognostic Assessment on the Basis of Clinical and Genomic Features in Myelodysplastic Syndromes

Author

Bersanelli, Matteo, primary, Travaglino, Erica, additional, Meggendorfer, Manja, additional, Matteuzzi, Tommaso, additional, Sala, Claudia, additional, Mosca, Ettore, additional, Chiereghin, Chiara, additional, Di Nanni, Noemi, additional, Gnocchi, Matteo, additional, Zampini, Matteo, additional, Rossi, Marianna, additional, Maggioni, Giulia, additional, Termanini, Alberto, additional, Angelucci, Emanuele, additional, Bernardi, Massimo, additional, Borin, Lorenza, additional, Bruno, Benedetto, additional, Bonifazi, Francesca, additional, Santini, Valeria, additional, Bacigalupo, Andrea, additional, Voso, Maria Teresa, additional, Oliva, Esther, additional, Riva, Marta, additional, Ubezio, Marta, additional, Morabito, Lucio, additional, Campagna, Alessia, additional, Saitta, Claudia, additional, Savevski, Victor, additional, Giampieri, Enrico, additional, Remondini, Daniel, additional, Passamonti, Francesco, additional, Ciceri, Fabio, additional, Bolli, Niccolò, additional, Rambaldi, Alessandro, additional, Kern, Wolfgang, additional, Kordasti, Shahram, additional, Sole, Francesc, additional, Palomo, Laura, additional, Sanz, Guillermo, additional, Santoro, Armando, additional, Platzbecker, Uwe, additional, Fenaux, Pierre, additional, Milanesi, Luciano, additional, Haferlach, Torsten, additional, Castellani, Gastone, additional, and Della Porta, Matteo G., additional

Published
2021
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29. Acute Myeloid Leukemia with Isocitrate Dehydrogenases (IDH) 1 and 2 Mutations. a Real-World Study from the European IDH Research Group

Author

Maggioni, Giulia, primary, Tentori, Cristina Astrid, additional, Voso, Maria Teresa, additional, Heibl, Sonja, additional, Metzeler, Klaus H., additional, Middeke, Jan Moritz, additional, Desterro, Joana, additional, Carmo-Fonseca, Maria, additional, Travaglino, Erica, additional, Fazi, Paola, additional, Piciocchi, Alfonso, additional, Dufour, Annika Maria, additional, Esteve, Jordi, additional, Pratcorona, Marta, additional, Mancini, Valentina, additional, Lussana, Federico, additional, Spiekermann, Karsten, additional, Thiede, Christian, additional, Stolzel, Friedrich, additional, Botelho de Sousa, Aida, additional, Tormo, Mar, additional, Acha, Pamela, additional, Arnan, Montserrat, additional, Fracchiolla, Nicola, additional, Hentrich, Marcus, additional, Sippel, Christoph, additional, Heilmeier, Bernhard, additional, Lemos, Marcos, additional, Nunes, Albertina, additional, Matos, Sonia, additional, Diaz, Marina, additional, Garrido, Ana, additional, Gallardo, David, additional, Vives, Susana, additional, Salamero, Olga, additional, Todisco, Elisabetta, additional, Basilico, Claudia, additional, Passamonti, Francesco, additional, Machherndl-Spandl, Sigrid, additional, Pleyer, Lisa, additional, Sierra, Jorge, additional, Solé, Francesc, additional, and Della Porta, Matteo Giovanni, additional

Published
2020
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30. A Sex-Informed Approach to Improve Prognostication and Personalized Decision-Making Process in Myelodysplastic Syndromes. a European Study of 11.878 Patients

Author

Maggioni, Giulia, primary, Travaglino, Erica, additional, Alfonso Pierola, Ana, additional, Kaivers, Jennifer, additional, Arnan, Montserrat, additional, Meggendorfer, Manja, additional, Giordano, Laura, additional, Bersanelli, Matteo, additional, Tentori, Cristina Astrid, additional, Ubezio, Marta, additional, Morabito, Lucio, additional, Campagna, Alessia, additional, Angelucci, Emanuele, additional, Bernardi, Massimo, additional, Borin, Lorenza Maria, additional, Voso, Maria Teresa, additional, Passamonti, Francesco, additional, Santoro, Armando, additional, Santini, Valeria, additional, Sanz, Guillermo F, additional, Haferlach, Torsten, additional, Germing, Ulrich, additional, Diez-Campelo, Maria, additional, and Della Porta, Matteo Giovanni, additional

Published
2020
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31. Clinical Relevance of Clonal Hematopoiesis in the Oldest-Old Population

Author

Rossi, Marianna, primary, Meggendorfer, Manja, additional, Zampini, Matteo, additional, Tettamanti, Mauro, additional, Riva, Emma, additional, Travaglino, Erica, additional, Mandelli, Sara, additional, Galbussera, Alessia Antonella, additional, Saba, Elena, additional, Manes, Nicla, additional, Milanesi, Chiara, additional, Ubezio, Marta, additional, Morabito, Lucio, additional, Chiereghin, Chiara, additional, Peano, Clelia, additional, Solda, Giulia, additional, Asselta, Rosanna, additional, Duga, Stefano, additional, Selmi, Carlo, additional, De Santis, Maria, additional, Malik, Karolina, additional, Maggioni, Giulia, additional, Bicchieri, Marilena, additional, Campagna, Alessia, additional, Civilini, Efrem, additional, Allavena, Paola, additional, Piazza, Rocco, additional, Bersanelli, Matteo, additional, Mosca, Ettore, additional, Corrao, Giovanni, additional, Castellani, Gastone C., additional, Sala, Claudia, additional, Termanini, Alberto, additional, Giordano, Laura, additional, Detoma, Paolo, additional, Malabaila, Aurelio, additional, Sala, Luca, additional, Rosso, Stefano, additional, Zanetti, Roberto, additional, Saitta, Claudia, additional, Condorelli, Gianluigi, additional, Passamonti, Francesco, additional, Santoro, Armando, additional, Sole, Francesc, additional, Platzbecker, Uwe, additional, Fenaux, Pierre, additional, Bolli, Niccolo, additional, Kern, Wolfgang, additional, Vassiliou, George S., additional, Haferlach, Torsten, additional, Lucca, Ugo, additional, and Della Porta, Matteo, additional

Published
2020
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32. 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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33. Clinical relevance of clonal hematopoiesis in the oldest-old population

Author

Rossi, Marianna, Meggendorfer, Manja, Zampini, Matteo, Tettamanti, Mauro, Riva, Emma, Travaglino, Erica, Bersanelli, Matteo, Mandelli, Sara, Galbussera, Alessia Antonella, Mosca, Ettore, Saba, Elena, Chiereghin, Chiara, Manes, Nicla, Milanesi, Chiara, Ubezio, Marta, Morabito, Lucio, Peano, Clelia, Soldà, Giulia, Asselta, Rosanna, Duga, Stefano, Selmi, Carlo, De Santis, Maria, Malik, Karolina, Maggioni, Giulia, Bicchieri, Marilena, Campagna, Alessia, Tentori, Cristina A, Russo, Antonio, Civilini, Efrem, Allavena, Paola, Piazza, Rocco, Corrao, Giovanni, Sala, Claudia, Termanini, Alberto, Giordano, Laura, Detoma, Paolo, Malabaila, Aurelio, Sala, Luca, Rosso, Stefano, Zanetti, Roberto, Saitta, Claudia, Riva, Elena, Condorelli, Gianluigi, Passamonti, Francesco, Santoro, Armando, Sole, Francesc, Platzbecker, Uwe, Fenaux, Pierre, Bolli, Niccolo', Castellani, Gastone, Kern, Wolfgang, Vassiliou, George S, Haferlach, Torsten, Lucca, Ugo, and Porta, Matteo G Della

Abstract

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with increased risk of cancers and inflammation-related diseases. This phenomenon becomes very common in oldest-old individuals, in whom the implications of CHIP are not well defined. We performed a mutational screening in 1794 oldest-old individuals enrolled in two population-based studies and investigate the relationships between CHIP and associated pathologies. Clonal mutations were observed in one third of oldest-old individuals and were associated with reduced survival. Mutations in JAK2and splicing genes, multiple mutations (DNMT3A, TET2, ASXL1with additional genetic lesions) and variant allele frequency ≥0.096 had positive predictive value for myeloid neoplasms. Combining mutation profiles with abnormalities in red blood cell indices improved the ability of myeloid neoplasm prediction. On this basis, we defined a predictive model that identifies 3 risk groups with different probabilities of developing myeloid neoplasms. Mutations in DNMT3A, TET2, ASXL1or JAK2(most occurring as single lesion) were associated with coronary heart disease and rheumatoid arthritis. Cytopenia was a common finding in oldest-old population, the underlying cause remaining unexplained in 30% of cases. Among individuals with unexplained cytopenia, the presence of highly-specific mutation patterns was associated with myelodysplastic-like phenotype and a probability of survival comparable to that of myeloid neoplasms. Accordingly, 7.5% of oldest-old subjects with cytopenia had presumptive evidence of myeloid neoplasm. In conclusion, specific mutational patterns define different risk of developing myeloid neoplasms vs.inflammatory-associated diseases in oldest-old population. In individuals with unexplained cytopenia, mutational status may identify those subjects with presumptive evidence of myeloid neoplasms.

Published
2021
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34. Classification and Personalized Prognostic Assessment on the Basis of Clinical and Genomic Features in Myelodysplastic Syndromes

Author

Andrea Bacigalupo, Pierre Fenaux, Alberto Termanini, Marianna Rossi, Lucio Morabito, Niccolo Bolli, Massimo Bernardi, Victor Savevski, Manja Meggendorfer, Daniel Remondini, Tommaso Matteuzzi, Torsten Haferlach, Luciano Milanesi, Matteo G. Della Porta, Ettore Mosca, Gastone Castellani, Valeria Santini, Alessandro Rambaldi, Giulia Maggioni, Guillermo Sanz, Claudia Sala, Wolfgang Kern, Marta Ubezio, Matteo Zampini, Emanuele Angelucci, Armando Santoro, Laura Palomo, Noemi Di Nanni, Lorenza Borin, Erica Travaglino, Alessia Campagna, Maria Teresa Voso, Francesc Solé, Francesca Bonifazi, Shahram Kordasti, Uwe Platzbecker, Matteo Bersanelli, Matteo Gnocchi, Esther Oliva, Marta Riva, Benedetto Bruno, Fabio Ciceri, Francesco Passamonti, Claudia Saitta, Enrico Giampieri, Chiara Chiereghin, Bersanelli, Matteo, Travaglino, Erica, Meggendorfer, Manja, Matteuzzi, Tommaso, Sala, Claudia, Mosca, Ettore, Chiereghin, Chiara, Di Nanni, Noemi, Gnocchi, Matteo, Zampini, Matteo, Rossi, Marianna, Maggioni, Giulia, Termanini, Alberto, Angelucci, Emanuele, Bernardi, Massimo, Borin, Lorenza, Bruno, Benedetto, Bonifazi, Francesca, Santini, Valeria, Bacigalupo, Andrea, Voso, Maria Teresa, Oliva, Esther, Riva, Marta, Ubezio, Marta, Morabito, Lucio, Campagna, Alessia, Saitta, Claudia, Savevski, Victor, Giampieri, Enrico, Remondini, Daniel, Passamonti, Francesco, Ciceri, Fabio, Bolli, Niccolò, Rambaldi, Alessandro, Kern, Wolfgang, Kordasti, Shahram, Sole, Francesc, Palomo, Laura, Sanz, Guillermo, Santoro, Armando, Platzbecker, Uwe, Fenaux, Pierre, Milanesi, Luciano, Haferlach, Torsten, Castellani, Gastone, and Della Porta, Matteo G

Subjects
Male, Cancer Research, SCORING SYSTEM, MODELS, disease classification, MEDLINE, ACUTE MYELOID-LEUKEMIA, Computational biology, 03 medical and health sciences, 0302 clinical medicine, Text mining, hemic and lymphatic diseases, MDS, medicine, CRITERIA, Humans, NGS, somatic mutations, myelodysplastic syndromes, prognosis, 030304 developmental biology, Retrospective Studies, 0303 health sciences, GENETIC LESIONS, business.industry, Myelodysplastic syndromes, Disease classification, Retrospective cohort study, SOMATIC MUTATIONS, Genomics, MDS, Artificial Intekkìlligence, machine learning, Settore MED/15, medicine.disease, Prognosis, 3. Good health, Oncology, 030220 oncology & carcinogenesis, Myelodysplastic Syndromes, Female, prognostication, business
Abstract

PURPOSE Recurrently mutated genes and chromosomal abnormalities have been identified in myelodysplastic syndromes (MDS). We aim to integrate these genomic features into disease classification and prognostication. METHODS We retrospectively enrolled 2,043 patients. Using Bayesian networks and Dirichlet processes, we combined mutations in 47 genes with cytogenetic abnormalities to identify genetic associations and subgroups. Random-effects Cox proportional hazards multistate modeling was used for developing prognostic models. An independent validation on 318 cases was performed. RESULTS We identify eight MDS groups (clusters) according to specific genomic features. In five groups, dominant genomic features include splicing gene mutations ( SF3B1, SRSF2, and U2AF1) that occur early in disease history, determine specific phenotypes, and drive disease evolution. These groups display different prognosis (groups with SF3B1 mutations being associated with better survival). Specific co-mutation patterns account for clinical heterogeneity within SF3B1- and SRSF2-related MDS. MDS with complex karyotype and/or TP53 gene abnormalities and MDS with acute leukemia–like mutations show poorest prognosis. MDS with 5q deletion are clustered into two distinct groups according to the number of mutated genes and/or presence of TP53 mutations. By integrating 63 clinical and genomic variables, we define a novel prognostic model that generates personally tailored predictions of survival. The predicted and observed outcomes correlate well in internal cross-validation and in an independent external cohort. This model substantially improves predictive accuracy of currently available prognostic tools. We have created a Web portal that allows outcome predictions to be generated for user-defined constellations of genomic and clinical features. CONCLUSION Genomic landscape in MDS reveals distinct subgroups associated with specific clinical features and discrete patterns of evolution, providing a proof of concept for next-generation disease classification and prognosis.

Published
2021
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