Literature DB >> 27521306

Prognosis of Primary Myelofibrosis in the Genomic Era.

Prithviraj Bose1, Srdan Verstovsek2.   

Abstract

Currently, prognostication in primary myelofibrosis (PMF) relies on the International Prognostic Scoring System (IPSS), dynamic IPSS (DIPSS), and DIPSS-plus, which incorporate age, blood counts, constitutional symptoms, circulating blasts, red cell transfusion need, and karyotype. Although the JAK2 V617F mutation was discovered a decade ago and MPL mutations shortly thereafter, it was the recent discovery of CALR mutations in the vast majority of JAK2/MPL-unmutated patients and recognition of the powerful impact of CALR mutations and triple-negative (JAK2/MPL/CALR-negative) status on outcome that set the stage for revision of traditional prognostic models to include molecular information. Additionally, the advent of next-generation sequencing has identified a host of previously unrecognized somatic mutations across hematologic malignancies. As in the myelodysplastic syndromes, the majority of common and prognostically informative mutations in PMF affect epigenetic regulation and mRNA splicing. Thus, a need has arisen to incorporate mutational information on genes such as ASXL1 and SRSF2 into risk stratification systems. Mutations in yet other genes appear to be important players in leukemic transformation, and new insights into disease pathogenesis are emerging. Finally, the number of prognostically detrimental mutations may affect both survival and response to ruxolitinib, which has significant implications for clinical decision making. In this review, we briefly summarize the prognostic models in use today and discuss in detail the somatic mutations commonly encountered in patients with PMF, along with their prognostic implications and role in leukemic transformation. Emerging prognostic models that incorporate new molecular information into existing systems or exclude clinical variables are also presented.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Leukemic transformation; Mutations; Primary myelofibrosis; Prognosis; Survival

Mesh:

Year:  2016        PMID: 27521306      PMCID: PMC4987499          DOI: 10.1016/j.clml.2016.02.031

Source DB:  PubMed          Journal:  Clin Lymphoma Myeloma Leuk        ISSN: 2152-2669


  158 in total

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Review 3.  Life expectancy and prognostic factors in the classic BCR/ABL-negative myeloproliferative disorders.

Authors:  F Cervantes; F Passamonti; G Barosi
Journal:  Leukemia       Date:  2008-04-03       Impact factor: 11.528

4.  A pooled analysis of overall survival in COMFORT-I and COMFORT-II, 2 randomized phase III trials of ruxolitinib for the treatment of myelofibrosis.

Authors:  Alessandro M Vannucchi; Hagop M Kantarjian; Jean-Jacques Kiladjian; Jason Gotlib; Francisco Cervantes; Ruben A Mesa; Nicholas J Sarlis; Wei Peng; Victor Sandor; Prashanth Gopalakrishna; Abdel Hmissi; Viktoriya Stalbovskaya; Vikas Gupta; Claire Harrison; Srdan Verstovsek
Journal:  Haematologica       Date:  2015-06-11       Impact factor: 9.941

5.  Genome integrity of myeloproliferative neoplasms in chronic phase and during disease progression.

Authors:  Thorsten Klampfl; Ashot Harutyunyan; Tiina Berg; Bettina Gisslinger; Martin Schalling; Klaudia Bagienski; Damla Olcaydu; Francesco Passamonti; Elisa Rumi; Daniela Pietra; Roland Jäger; Lisa Pieri; Paola Guglielmelli; Ilaria Iacobucci; Giovanni Martinelli; Mario Cazzola; Alessandro M Vannucchi; Heinz Gisslinger; Robert Kralovics
Journal:  Blood       Date:  2011-04-29       Impact factor: 22.113

6.  Disease burden at the progenitor level is a feature of primary myelofibrosis: a multivariable analysis of 164 JAK2 V617F-positive myeloproliferative neoplasm patients.

Authors:  Brady L Stein; Donna M Williams; Ophelia Rogers; Mary Ann Isaacs; Jerry L Spivak; Alison R Moliterno
Journal:  Exp Hematol       Date:  2010-10-01       Impact factor: 3.084

7.  Novel mutations in the inhibitory adaptor protein LNK drive JAK-STAT signaling in patients with myeloproliferative neoplasms.

Authors:  Stephen T Oh; Erin F Simonds; Carol Jones; Matthew B Hale; Yury Goltsev; Kenneth D Gibbs; Jason D Merker; James L Zehnder; Garry P Nolan; Jason Gotlib
Journal:  Blood       Date:  2010-04-19       Impact factor: 22.113

8.  DNMT3A mutations in acute myeloid leukemia.

Authors:  Timothy J Ley; Li Ding; Matthew J Walter; Michael D McLellan; Tamara Lamprecht; David E Larson; Cyriac Kandoth; Jacqueline E Payton; Jack Baty; John Welch; Christopher C Harris; Cheryl F Lichti; R Reid Townsend; Robert S Fulton; David J Dooling; Daniel C Koboldt; Heather Schmidt; Qunyuan Zhang; John R Osborne; Ling Lin; Michelle O'Laughlin; Joshua F McMichael; Kim D Delehaunty; Sean D McGrath; Lucinda A Fulton; Vincent J Magrini; Tammi L Vickery; Jasreet Hundal; Lisa L Cook; Joshua J Conyers; Gary W Swift; Jerry P Reed; Patricia A Alldredge; Todd Wylie; Jason Walker; Joelle Kalicki; Mark A Watson; Sharon Heath; William D Shannon; Nobish Varghese; Rakesh Nagarajan; Peter Westervelt; Michael H Tomasson; Daniel C Link; Timothy A Graubert; John F DiPersio; Elaine R Mardis; Richard K Wilson
Journal:  N Engl J Med       Date:  2010-11-10       Impact factor: 91.245

9.  JAK2 V617F mutational status predicts progression to large splenomegaly and leukemic transformation in primary myelofibrosis.

Authors:  Giovanni Barosi; Gaetano Bergamaschi; Monia Marchetti; Alessandro M Vannucchi; Paola Guglielmelli; Elisabetta Antonioli; Margherita Massa; Vittorio Rosti; Rita Campanelli; Laura Villani; Gianluca Viarengo; Elisabetta Gattoni; Giancarla Gerli; Giorgina Specchia; Carmine Tinelli; Alessandro Rambaldi; Tiziano Barbui
Journal:  Blood       Date:  2007-08-21       Impact factor: 22.113

10.  Transgenic expression of JAK2V617F causes myeloproliferative disorders in mice.

Authors:  Shu Xing; Tina Ho Wanting; Wanming Zhao; Junfeng Ma; Shaofeng Wang; Xuesong Xu; Qingshan Li; Xueqi Fu; Mingjiang Xu; Zhizhuang Joe Zhao
Journal:  Blood       Date:  2008-03-11       Impact factor: 22.113

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Review 2.  The New Genomics: What Molecular Databases Can Tell Us About Human Population Variation and Endocrine Disease.

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Journal:  Endocrinology       Date:  2017-07-01       Impact factor: 4.736

3.  Splenomegaly impacts prognosis in essential thrombocythemia and polycythemia vera: A single center study.

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Review 4.  Next Generation Sequencing in MPNs. Lessons from the Past and Prospects for Use as Predictors of Prognosis and Treatment Responses.

Authors:  Vibe Skov
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