Literature DB >> 33666653

Genomic analysis of primary and secondary myelofibrosis redefines the prognostic impact of ASXL1 mutations: a FIM study.

Damien Luque Paz1,2,3, Jérémie Riou4, Emmanuelle Verger5,6, Bruno Cassinat5,6, Aurélie Chauveau7, Jean-Christophe Ianotto8, Brigitte Dupriez9, Françoise Boyer10, Maxime Renard1,2,3, Olivier Mansier11,12, Anne Murati13, Jérôme Rey14, Gabriel Etienne15, Véronique Mansat-De Mas7, Suzanne Tavitian16, Olivier Nibourel17,18, Stéphane Girault19, Yannick Le Bris20,21, François Girodon22, Dana Ranta23, Jean-Claude Chomel24, Pascale Cony-Makhoul25, Pierre Sujobert26, Margot Robles27, Raouf Ben Abdelali28, Olivier Kosmider29, Laurane Cottin1,2,3, Lydia Roy30,31, Ivan Sloma32,33, Fabienne Vacheret34, Mathieu Wemeau35, Pascal Mossuz36, Borhane Slama37, Vincent Cussac38, Guillaume Denis39, Anouk Walter-Petrich40, Barbara Burroni41, Nathalie Jézéquel7, Stéphane Giraudier5,6, Eric Lippert7, Gérard Socié42, Jean-Jacques Kiladjian6,43, Valérie Ugo1,2,3.   

Abstract

We aimed to study the prognostic impact of the mutational landscape in primary and secondary myelofibrosis. The study included 479 patients with myelofibrosis recruited from 24 French Intergroup of Myeloproliferative Neoplasms (FIM) centers. The molecular landscape was studied by high-throughput sequencing of 77 genes. A Bayesian network allowed the identification of genomic groups whose prognostic impact was studied in a multistate model considering transitions from the 3 conditions: myelofibrosis, acute leukemia, and death. Results were validated using an independent, previously published cohort (n = 276). Four genomic groups were identified: patients with TP53 mutation; patients with ≥1 mutation in EZH2, CBL, U2AF1, SRSF2, IDH1, IDH2, NRAS, or KRAS (high-risk group); patients with ASXL1-only mutation (ie, no associated mutation in TP53 or high-risk genes); and other patients. A multistate model found that both TP53 and high-risk groups were associated with leukemic transformation (hazard ratios [HRs] [95% confidence interval], 8.68 [3.32-22.73] and 3.24 [1.58-6.64], respectively) and death from myelofibrosis (HRs, 3.03 [1.66-5.56] and 1.77 [1.18-2.67], respectively). ASXL1-only mutations had no prognostic value that was confirmed in the validation cohort. However, ASXL1 mutations conferred a worse prognosis when associated with a mutation in TP53 or high-risk genes. This study provides a new definition of adverse mutations in myelofibrosis with the addition of TP53, CBL, NRAS, KRAS, and U2AF1 to previously described genes. Furthermore, our results argue that ASXL1 mutations alone cannot be considered detrimental.
© 2021 by The American Society of Hematology.

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Year:  2021        PMID: 33666653      PMCID: PMC7948260          DOI: 10.1182/bloodadvances.2020003444

Source DB:  PubMed          Journal:  Blood Adv        ISSN: 2473-9529


  43 in total

1.  Estimating and comparing time-dependent areas under receiver operating characteristic curves for censored event times with competing risks.

Authors:  Paul Blanche; Jean-François Dartigues; Hélène Jacqmin-Gadda
Journal:  Stat Med       Date:  2013-09-12       Impact factor: 2.373

2.  Impact of genotype on leukaemic transformation in polycythaemia vera and essential thrombocythaemia.

Authors:  Alberto Alvarez-Larrán; Alicia Senín; Concepción Fernández-Rodríguez; Arturo Pereira; Eduardo Arellano-Rodrigo; Montse Gómez; Francisca Ferrer-Marin; Joaquín Martínez-López; Laura Camacho; Dolors Colomer; Anna Angona; Blanca Navarro; Francisco Cervantes; Carlos Besses; Beatriz Bellosillo; Juan Carlos Hernández-Boluda
Journal:  Br J Haematol       Date:  2017-05-23       Impact factor: 6.998

3.  A clinical-molecular prognostic model to predict survival in patients with post polycythemia vera and post essential thrombocythemia myelofibrosis.

Authors:  F Passamonti; T Giorgino; B Mora; P Guglielmelli; E Rumi; M Maffioli; A Rambaldi; M Caramella; R Komrokji; J Gotlib; J J Kiladjian; F Cervantes; T Devos; F Palandri; V De Stefano; M Ruggeri; R T Silver; G Benevolo; F Albano; D Caramazza; M Merli; D Pietra; R Casalone; G Rotunno; T Barbui; M Cazzola; A M Vannucchi
Journal:  Leukemia       Date:  2017-05-31       Impact factor: 11.528

4.  New prognostic scoring system for primary myelofibrosis based on a study of the International Working Group for Myelofibrosis Research and Treatment.

Authors:  Francisco Cervantes; Brigitte Dupriez; Arturo Pereira; Francesco Passamonti; John T Reilly; Enrica Morra; Alessandro M Vannucchi; Ruben A Mesa; Jean-Loup Demory; Giovanni Barosi; Elisa Rumi; Ayalew Tefferi
Journal:  Blood       Date:  2008-11-06       Impact factor: 22.113

5.  Mutations and prognosis in primary myelofibrosis.

Authors:  A M Vannucchi; T L Lasho; P Guglielmelli; F Biamonte; A Pardanani; A Pereira; C Finke; J Score; N Gangat; C Mannarelli; R P Ketterling; G Rotunno; R A Knudson; M C Susini; R R Laborde; A Spolverini; A Pancrazzi; L Pieri; R Manfredini; E Tagliafico; R Zini; A Jones; K Zoi; A Reiter; A Duncombe; D Pietra; E Rumi; F Cervantes; G Barosi; M Cazzola; N C P Cross; A Tefferi
Journal:  Leukemia       Date:  2013-04-26       Impact factor: 11.528

6.  Frequent CBL mutations associated with 11q acquired uniparental disomy in myeloproliferative neoplasms.

Authors:  Francis H Grand; Claire E Hidalgo-Curtis; Thomas Ernst; Katerina Zoi; Christine Zoi; Carolann McGuire; Sebastian Kreil; Amy Jones; Joannah Score; Georgia Metzgeroth; David Oscier; Andrew Hall; Christian Brandts; Hubert Serve; Andreas Reiter; Andrew J Chase; Nicholas C P Cross
Journal:  Blood       Date:  2009-04-22       Impact factor: 22.113

7.  Mutation-enhanced international prognostic systems for essential thrombocythaemia and polycythaemia vera.

Authors:  Ayalew Tefferi; Paola Guglielmelli; Terra L Lasho; Giacomo Coltro; Christy M Finke; Giuseppe G Loscocco; Benedetta Sordi; Natasha Szuber; Giada Rotunno; Annalisa Pacilli; Curtis A Hanson; Rhett P Ketterling; Animesh Pardanani; Naseema Gangat; Alessandro M Vannucchi
Journal:  Br J Haematol       Date:  2020-01-16       Impact factor: 6.998

8.  The evolutionary dynamics and fitness landscape of clonal hematopoiesis.

Authors:  Caroline J Watson; A L Papula; Gladys Y P Poon; Wing H Wong; Andrew L Young; Todd E Druley; Daniel S Fisher; Jamie R Blundell
Journal:  Science       Date:  2020-03-27       Impact factor: 47.728

9.  Prognostic impact of RAS-pathway mutations in patients with myelofibrosis.

Authors:  Fabio P S Santos; Bartlomiej Getta; Lucia Masarova; Christopher Famulare; Jessica Schulman; Tarcila S Datoguia; Renato D Puga; Raquel de Melo Alves Paiva; Maria E Arcila; Nelson Hamerschlak; Hagop M Kantarjian; Ross L Levine; Paulo Vidal Campregher; Raajit K Rampal; Srdan Verstovsek
Journal:  Leukemia       Date:  2019-10-18       Impact factor: 11.528

10.  Expression of mutant Asxl1 perturbs hematopoiesis and promotes susceptibility to leukemic transformation.

Authors:  Reina Nagase; Daichi Inoue; Alessandro Pastore; Takeshi Fujino; Hsin-An Hou; Norimasa Yamasaki; Susumu Goyama; Makoto Saika; Akinori Kanai; Yasuyuki Sera; Sayuri Horikawa; Yasunori Ota; Shuhei Asada; Yasutaka Hayashi; Kimihito Cojin Kawabata; Reina Takeda; Hwei-Fang Tien; Hiroaki Honda; Omar Abdel-Wahab; Toshio Kitamura
Journal:  J Exp Med       Date:  2018-04-11       Impact factor: 14.307

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  7 in total

1.  Mutational spectrum and prognosis in Chinese patients with prefibrotic primary myelofibrosis.

Authors:  Chi-Keung Cheng; Jennifer W Y Lai; Yuk-Lin Yung; Hoi-Yun Chan; Raymond S M Wong; Natalie P H Chan; Joyce S Cheung; Xi Luo; Herbert-Augustus Pitts; Margaret H L Ng
Journal:  EJHaem       Date:  2021-12-30

Review 2.  Molecular Pathogenesis of Myeloproliferative Neoplasms: From Molecular Landscape to Therapeutic Implications.

Authors:  Erika Morsia; Elena Torre; Antonella Poloni; Attilio Olivieri; Serena Rupoli
Journal:  Int J Mol Sci       Date:  2022-04-20       Impact factor: 6.208

Review 3.  Allogeneic haematopoietic cell transplantation for myelofibrosis: proposed definitions and management strategies for graft failure, poor graft function and relapse: best practice recommendations of the EBMT Chronic Malignancies Working Party.

Authors:  Donal P McLornan; Juan Carlos Hernandez Boluda; Tomasz Czerw; Nicholas Cross; H Joachim Deeg; Marcus Ditschkowski; Mufaddal T Moonim; Nicola Polverelli; Marie Robin; Mahmoud Aljurf; Eibhlin Conneally; Patrick Hayden; Ibrahim Yakoub-Agha
Journal:  Leukemia       Date:  2021-05-26       Impact factor: 11.528

4.  A prognostic model to predict survival after 6 months of ruxolitinib in patients with myelofibrosis.

Authors:  Margherita Maffioli; Barbara Mora; Somedeb Ball; Alessandra Iurlo; Elena Maria Elli; Maria Chiara Finazzi; Nicola Polverelli; Elisa Rumi; Marianna Caramella; Maria Cristina Carraro; Mariella D'Adda; Alfredo Molteni; Cinzia Sissa; Francesca Lunghi; Alessandro Vismara; Marta Ubezio; Anna Guidetti; Sabrina Caberlon; Michela Anghilieri; Rami Komrokji; Daniele Cattaneo; Matteo Giovanni Della Porta; Toni Giorgino; Lorenza Bertù; Marco Brociner; Andrew Kuykendall; Francesco Passamonti
Journal:  Blood Adv       Date:  2022-03-22

5.  ASXL1 mutations are prognostically significant in PMF, but not MF following essential thrombocythemia or polycythemia vera.

Authors:  Paola Guglielmelli; Giacomo Coltro; Francesco Mannelli; Giada Rotunno; Giuseppe G Loscocco; Carmela Mannarelli; Chiara Maccari; Chiara Paoli; Simone Romagnoli; Niccolò Bartalucci; Alessandro M Vannucchi
Journal:  Blood Adv       Date:  2022-05-10

Review 6.  Towards a Personalized Definition of Prognosis in Philadelphia-Negative Myeloproliferative Neoplasms.

Authors:  Barbara Mora; Francesco Passamonti
Journal:  Curr Hematol Malig Rep       Date:  2022-09-01       Impact factor: 4.213

Review 7.  Molecular pathogenesis of the myeloproliferative neoplasms.

Authors:  Graeme Greenfield; Mary Frances McMullin; Ken Mills
Journal:  J Hematol Oncol       Date:  2021-06-30       Impact factor: 17.388

  7 in total

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