Classification and Personalized Prognostic Assessment on the Basis of Clinical and Genomic Features in Myelodysplastic Syndromes
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- Matteo Bersanelli
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy
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- Erica Travaglino
- Humanitas Clinical and Research Center—IRCCS, Rozzano, Milan, Italy
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- Manja Meggendorfer
- MLL Munich Leukemia Laboratory, Munich, Germany
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- Tommaso Matteuzzi
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy
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- Claudia Sala
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy
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- Ettore Mosca
- Institute of Biomedical Technologies, National Research Council (CNR), Segrate, Milan, Italy
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- Chiara Chiereghin
- Humanitas Clinical and Research Center—IRCCS, Rozzano, Milan, Italy
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- Noemi Di Nanni
- Institute of Biomedical Technologies, National Research Council (CNR), Segrate, Milan, Italy
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- Matteo Gnocchi
- Institute of Biomedical Technologies, National Research Council (CNR), Segrate, Milan, Italy
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- Matteo Zampini
- Humanitas Clinical and Research Center—IRCCS, Rozzano, Milan, Italy
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- Marianna Rossi
- Humanitas Clinical and Research Center—IRCCS, Rozzano, Milan, Italy
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- Giulia Maggioni
- Humanitas Clinical and Research Center—IRCCS, Rozzano, Milan, Italy
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- Alberto Termanini
- Humanitas Clinical and Research Center—IRCCS, Rozzano, Milan, Italy
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- Emanuele Angelucci
- Hematology and Transplant Center, IRCCS Ospedale Policlinico San Martino, Genova, Italy
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- Massimo Bernardi
- Hematology and Bone Marrow Transplantation, IRCCS San Raffaele Scientific Institute, & University Vita-Salute San Raffaele, Milan, Italy
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- Lorenza Borin
- Hematology, Ospedale San Gerardo, Monza, Italy
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- Benedetto Bruno
- Stem Cell Transplant Program, Department of Oncology, A.O.U. Città della Salute e della Scienza di Torino
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- Francesca Bonifazi
- Hematology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
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- Valeria Santini
- Hematology, Azienda Ospedaliero-Universitaria Careggi & University of Florence, Florence Italy
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- Andrea Bacigalupo
- Hematology, IRCCS Fondazione Policlinico Universitario Gemelli & Università Cattolica del Sacro Cuore, Rome, Italy
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- Maria Teresa Voso
- Hematology, Policlinico Tor Vergata & Department of Biomedicine and Prevention, Tor Vergata University, Rome, Italy
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- Esther Oliva
- Hematology, Grande Ospedale Metropolitano Bianchi Melacrino Morelli, Reggio Calabria, Italy
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- Marta Riva
- Hematology, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
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- Marta Ubezio
- Humanitas Clinical and Research Center—IRCCS, Rozzano, Milan, Italy
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- Lucio Morabito
- Humanitas Clinical and Research Center—IRCCS, Rozzano, Milan, Italy
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- Alessia Campagna
- Humanitas Clinical and Research Center—IRCCS, Rozzano, Milan, Italy
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- Claudia Saitta
- Department of Medicine and Surgery, University of Milano-Bicocca, Monza Italy
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- Victor Savevski
- Humanitas Clinical and Research Center—IRCCS, Rozzano, Milan, Italy
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- Enrico Giampieri
- National Institute of Nuclear Physics (INFN), Bologna, Italy
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- Daniel Remondini
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy
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- Francesco Passamonti
- Hematology, ASST Sette Laghi, Ospedale di Circolo of Varese & Department of Medicine and Surgery, University of Insubria, Varese, Italy
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- Fabio Ciceri
- Hematology and Bone Marrow Transplantation, IRCCS San Raffaele Scientific Institute, & University Vita-Salute San Raffaele, Milan, Italy
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- Niccolò Bolli
- Hematology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
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- Alessandro Rambaldi
- Hematology, Azienda Ospedaliera Papa Giovanni XXIII, Bergamo, Italy
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- Wolfgang Kern
- MLL Munich Leukemia Laboratory, Munich, Germany
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- Shahram Kordasti
- Haematology, Guy's Hospital & Comprehensive Cancer Centre, King's College, London, United Kingdom
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- Francesc Sole
- Institut de Recerca Contra la Leucèmia Josep Carreras, Ctra de Can Ruti, Badalona-Barcelona, Spain
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- Laura Palomo
- Institut de Recerca Contra la Leucèmia Josep Carreras, Ctra de Can Ruti, Badalona-Barcelona, Spain
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- Guillermo Sanz
- Hematology, Hospital Universitario La Fe, Valencia, Spain
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- Armando Santoro
- Humanitas Clinical and Research Center—IRCCS, Rozzano, Milan, Italy
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- Uwe Platzbecker
- Medical Clinic and Policlinic 1, Hematology and Cellular Therapy, University Hospital Leipzig, Leipzig, Germany
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- Pierre Fenaux
- Service d'Hématologie Séniors, Hôpital Saint-Louis, Assistance Publique-Hôpitaux de Paris and Université Paris, Paris, France
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- Luciano Milanesi
- Institute of Biomedical Technologies, National Research Council (CNR), Segrate, Milan, Italy
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- Torsten Haferlach
- MLL Munich Leukemia Laboratory, Munich, Germany
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- Gastone Castellani
- National Institute of Nuclear Physics (INFN), Bologna, Italy
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- Matteo G. Della Porta
- Humanitas Clinical and Research Center—IRCCS, Rozzano, Milan, Italy
抄録
<jats:sec><jats:title>PURPOSE</jats:title><jats:p> 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. </jats:p></jats:sec><jats:sec><jats:title>METHODS</jats:title><jats:p> 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. </jats:p></jats:sec><jats:sec><jats:title>RESULTS</jats:title><jats:p> 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. </jats:p></jats:sec><jats:sec><jats:title>CONCLUSION</jats:title><jats:p> 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. </jats:p></jats:sec>
収録刊行物
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- Journal of Clinical Oncology
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Journal of Clinical Oncology 39 (11), 1223-1233, 2021-04-10
American Society of Clinical Oncology (ASCO)