Literature DB >> 32573691

Molecular landscape and clonal architecture of adult myelodysplastic/myeloproliferative neoplasms.

Laura Palomo1, Manja Meggendorfer2, Stephan Hutter2, Sven Twardziok2, Vera Ademà3, Irene Fuhrmann2, Francisco Fuster-Tormo1, Blanca Xicoy4, Lurdes Zamora4, Pamela Acha1, Cassandra M Kerr3, Wolfgang Kern2, Jaroslaw P Maciejewski3, Francesc Solé1, Claudia Haferlach2, Torsten Haferlach2.   

Abstract

More than 90% of patients with myelodysplastic/myeloproliferative neoplasms (MDSs/MPNs) harbor somatic mutations in myeloid-related genes, but still, current diagnostic criteria do not include molecular data. We performed genome-wide sequencing techniques to characterize the mutational landscape of a large and clinically well-characterized cohort including 367 adults with MDS/MPN subtypes, including chronic myelomonocytic leukemia (CMML; n = 119), atypical chronic myeloid leukemia (aCML; n = 71), MDS/MPN with ring sideroblasts and thrombocytosis (MDS/MPN-RS-T; n = 71), and MDS/MPN unclassifiable (MDS/MPN-U; n = 106). A total of 30 genes were recurrently mutated in ≥3% of the cohort. Distribution of recurrently mutated genes and clonal architecture differed among MDS/MPN subtypes. Statistical analysis revealed significant correlations between recurrently mutated genes, as well as genotype-phenotype associations. We identified specific gene combinations that were associated with distinct MDS/MPN subtypes and that were mutually exclusive with most of the other MDSs/MPNs (eg, TET2-SRSF2 in CMML, ASXL1-SETBP1 in aCML, and SF3B1-JAK2 in MDS/MPN-RS-T). Patients with MDS/MPN-U were the most heterogeneous and displayed different molecular profiles that mimicked the ones observed in other MDS/MPN subtypes and that had an impact on the outcome of the patients. Specific gene mutations also had an impact on the outcome of the different MDS/MPN subtypes, which may be relevant for clinical decision-making. Overall, the results of this study help to elucidate the heterogeneity found in these neoplasms, which can be of use in the clinical setting of MDS/MPN.
© 2020 by The American Society of Hematology.

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Year:  2020        PMID: 32573691      PMCID: PMC7645608          DOI: 10.1182/blood.2019004229

Source DB:  PubMed          Journal:  Blood        ISSN: 0006-4971            Impact factor:   22.113


  48 in total

1.  Clinical features and course of refractory anemia with ring sideroblasts associated with marked thrombocytosis.

Authors:  Julien Broseus; Lourdes Florensa; Esther Zipperer; Susanne Schnittger; Luca Malcovati; Steven Richebourg; Eric Lippert; Jaroslav Cermak; Jyoti Evans; Morgane Mounier; José Maria Raya; François Bailly; Norbert Gattermann; Torsten Haferlach; Richard Garand; Kaoutar Allou; Carlos Besses; Ulrich Germing; Claudia Haferlach; Erica Travaglino; Elisa Luno; Maria Angeles Pinan; Leonor Arenillas; Maria Rozman; Maria Luz Perez Sirvent; Bernardine Favre; Julien Guy; Esther Alonso; Nuhri Ahwij; Andrés Jerez; Sylvie Hermouet; Marc Maynadié; Mario Cazzola; François Girodon
Journal:  Haematologica       Date:  2012-04-24       Impact factor: 9.941

2.  Prognostic factors and scoring systems in chronic myelomonocytic leukemia: a retrospective analysis of 213 patients.

Authors:  Francesco Onida; Hagop M Kantarjian; Terry L Smith; Greg Ball; Michael J Keating; Elihu H Estey; Armand B Glassman; Maher Albitar; Monica I Kwari; Miloslav Beran
Journal:  Blood       Date:  2002-02-01       Impact factor: 22.113

3.  Recurrent SETBP1 mutations in atypical chronic myeloid leukemia.

Authors:  Rocco Piazza; Simona Valletta; Nils Winkelmann; Sara Redaelli; Roberta Spinelli; Alessandra Pirola; Laura Antolini; Luca Mologni; Carla Donadoni; Elli Papaemmanuil; Susanne Schnittger; Dong-Wook Kim; Jacqueline Boultwood; Fabio Rossi; Giuseppe Gaipa; Greta P De Martini; Paola Francia di Celle; Hyun Gyung Jang; Valeria Fantin; Graham R Bignell; Vera Magistroni; Torsten Haferlach; Enrico Maria Pogliani; Peter J Campbell; Andrew J Chase; William J Tapper; Nicholas C P Cross; Carlo Gambacorti-Passerini
Journal:  Nat Genet       Date:  2012-12-09       Impact factor: 38.330

4.  Age, JAK2(V617F) and SF3B1 mutations are the main predicting factors for survival in refractory anaemia with ring sideroblasts and marked thrombocytosis.

Authors:  J Broséus; T Alpermann; M Wulfert; L Florensa Brichs; S Jeromin; E Lippert; M Rozman; F Lifermann; V Grossmann; T Haferlach; U Germing; E Luño; F Girodon; S Schnittger
Journal:  Leukemia       Date:  2013-04-18       Impact factor: 11.528

5.  Characteristics and outcome of patients with Philadelphia chromosome negative, bcr/abl negative chronic myelogenous leukemia.

Authors:  Francesco Onida; Greg Ball; Hagop M Kantarjian; Terry L Smith; Armand Glassman; Maher Albitar; Barbara Scappini; Mary Beth Rios; Michael J Keating; Miloslav Beran
Journal:  Cancer       Date:  2002-10-15       Impact factor: 6.860

6.  ASXL1 and SETBP1 mutations and their prognostic contribution in chronic myelomonocytic leukemia: a two-center study of 466 patients.

Authors:  M M Patnaik; R Itzykson; T L Lasho; O Kosmider; C M Finke; C A Hanson; R A Knudson; R P Ketterling; A Tefferi; E Solary
Journal:  Leukemia       Date:  2014-04-03       Impact factor: 11.528

7.  Integrating clinical features and genetic lesions in the risk assessment of patients with chronic myelomonocytic leukemia.

Authors:  Chiara Elena; Anna Gallì; Esperanza Such; Manja Meggendorfer; Ulrich Germing; Ettore Rizzo; Jose Cervera; Elisabetta Molteni; Annette Fasan; Esther Schuler; Ilaria Ambaglio; Maria Lopez-Pavia; Silvia Zibellini; Andrea Kuendgen; Erica Travaglino; Reyes Sancho-Tello; Silvia Catricalà; Ana I Vicente; Torsten Haferlach; Claudia Haferlach; Guillermo F Sanz; Luca Malcovati; Mario Cazzola
Journal:  Blood       Date:  2016-07-06       Impact factor: 22.113

8.  Oncogenic CSF3R mutations in chronic neutrophilic leukemia and atypical CML.

Authors:  Julia E Maxson; Jason Gotlib; Daniel A Pollyea; Angela G Fleischman; Anupriya Agarwal; Christopher A Eide; Daniel Bottomly; Beth Wilmot; Shannon K McWeeney; Cristina E Tognon; J Blake Pond; Robert H Collins; Basem Goueli; Stephen T Oh; Michael W Deininger; Bill H Chang; Marc M Loriaux; Brian J Druker; Jeffrey W Tyner
Journal:  N Engl J Med       Date:  2013-05-09       Impact factor: 91.245

9.  Clonal evolution in myelodysplastic syndromes.

Authors:  Pedro da Silva-Coelho; Leonie I Kroeze; Kenichi Yoshida; Theresia N Koorenhof-Scheele; Ruth Knops; Louis T van de Locht; Aniek O de Graaf; Marion Massop; Sarah Sandmann; Martin Dugas; Marian J Stevens-Kroef; Jaroslav Cermak; Yuichi Shiraishi; Kenichi Chiba; Hiroko Tanaka; Satoru Miyano; Theo de Witte; Nicole M A Blijlevens; Petra Muus; Gerwin Huls; Bert A van der Reijden; Seishi Ogawa; Joop H Jansen
Journal:  Nat Commun       Date:  2017-04-21       Impact factor: 14.919

10.  Myelodysplastic/myeloproliferative neoplasms, unclassifiable (MDS/MPN, U): natural history and clinical outcome by treatment strategy.

Authors:  C D DiNardo; N Daver; N Jain; N Pemmaraju; C Bueso-Ramos; C C Yin; S Pierce; E Jabbour; J E Cortes; H M Kantarjian; G Garcia-Manero; S Verstovsek
Journal:  Leukemia       Date:  2014-01-10       Impact factor: 11.528

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  27 in total

1.  MDS/MPN-Unclassifiable with t(X;17)(q28;q21) and KANSL1-MTCP1/CMC4 Fusion Gene.

Authors:  Peter Molony; Adam C Smith; Shamini Selvarajah; Ali Sakhdari
Journal:  Cytogenet Genome Res       Date:  2022-01-17       Impact factor: 1.636

2.  SLIT2 promoter hypermethylation-mediated SLIT2-IT1/miR-218 repression drives leukemogenesis and predicts adverse prognosis in myelodysplastic neoplasm.

Authors:  Ting-Juan Zhang; Zi-Jun Xu; Xiang-Mei Wen; Yu Gu; Ji-Chun Ma; Qian Yuan; Jiang Lin; Jing-Dong Zhou; Jun Qian
Journal:  Leukemia       Date:  2022-07-29       Impact factor: 12.883

3.  CSF3R T618I mutant myelodysplastic/myeloproliferative neoplasm in the elderly: An age-related disease with unfavorable prognosis.

Authors:  Xinmin Zhang; Cristina Ghiuzeli; Erin Jou; Peihong Hsu; Jonathan Kolitz; Judith P Brody
Journal:  Leuk Res Rep       Date:  2022-06-25

Review 4.  Clonal Hematopoiesis Analyses in Clinical, Epidemiologic, and Genetic Aging Studies to Unravel Underlying Mechanisms of Age-Related Dysfunction in Humans.

Authors:  Kenneth Walsh; Nalini Raghavachari; Candace Kerr; Alexander G Bick; Steven R Cummings; Todd Druley; Cynthia E Dunbar; Giulio Genovese; Margaret A Goodell; Siddhartha Jaiswal; Jaroslaw Maciejewski; Pradeep Natarajan; Anastasia V Shindyapina; Alan R Shuldiner; Erik B Van Den Akker; Jan Vijg
Journal:  Front Aging       Date:  2022-03-08

5.  A phase 1b study of glasdegib + azacitidine in patients with untreated acute myeloid leukemia and higher-risk myelodysplastic syndromes.

Authors:  Mikkael A Sekeres; Michael Schuster; Magalie Joris; Jürgen Krauter; Johan Maertens; Dimitri Breems; Emmanuel Gyan; Tibor Kovacsovics; Amit Verma; Paresh Vyas; Eunice S Wang; Keith Ching; Thomas O'Brien; Corrado Gallo Stampino; Weidong Wendy Ma; Arthur Kudla; Geoffrey Chan; Amer M Zeidan
Journal:  Ann Hematol       Date:  2022-04-30       Impact factor: 4.030

Review 6.  TET-dioxygenase deficiency in oncogenesis and its targeting for tumor-selective therapeutics.

Authors:  Yihong Guan; Metis Hasipek; Anand D Tiwari; Jaroslaw P Maciejewski; Babal K Jha
Journal:  Semin Hematol       Date:  2020-12-28       Impact factor: 3.851

Review 7.  Genetic Aspects of Myelodysplastic/Myeloproliferative Neoplasms.

Authors:  Laura Palomo; Pamela Acha; Francesc Solé
Journal:  Cancers (Basel)       Date:  2021-04-27       Impact factor: 6.639

8.  Gender-related differences in the outcomes and genomic landscape of patients with myelodysplastic syndrome/myeloproliferative neoplasm overlap syndromes.

Authors:  Theodoros Karantanos; Lukasz P Gondek; Ravi Varadhan; Alison R Moliterno; Amy E DeZern; Richard J Jones; Tania Jain
Journal:  Br J Haematol       Date:  2021-05-24       Impact factor: 8.615

9.  Enhancer Hijacking Drives Oncogenic BCL11B Expression in Lineage-Ambiguous Stem Cell Leukemia.

Authors:  Lindsey E Montefiori; Sonja Bendig; Zhaohui Gu; Xiaolong Chen; Petri Pölönen; Xiaotu Ma; Alex Murison; Andy Zeng; Laura Garcia-Prat; Kirsten Dickerson; Ilaria Iacobucci; Sherif Abdelhamed; Ryan Hiltenbrand; Paul E Mead; Cyrus M Mehr; Beisi Xu; Zhongshan Cheng; Ti-Cheng Chang; Tamara Westover; Jing Ma; Anna Stengel; Shunsuke Kimura; Chunxu Qu; Marcus B Valentine; Marissa Rashkovan; Selina Luger; Mark R Litzow; Jacob M Rowe; Monique L den Boer; Victoria Wang; Jun Yin; Steven M Kornblau; Stephen P Hunger; Mignon L Loh; Ching-Hon Pui; Wenjian Yang; Kristine R Crews; Kathryn G Roberts; Jun J Yang; Mary V Relling; William E Evans; Wendy Stock; Elisabeth M Paietta; Adolfo A Ferrando; Jinghui Zhang; Wolfgang Kern; Torsten Haferlach; Gang Wu; John E Dick; Jeffery M Klco; Claudia Haferlach; Charles G Mullighan
Journal:  Cancer Discov       Date:  2021-06-08       Impact factor: 39.397

10.  Machine learning integrates genomic signatures for subclassification beyond primary and secondary acute myeloid leukemia.

Authors:  Hassan Awada; Arda Durmaz; Carmelo Gurnari; Ashwin Kishtagari; Manja Meggendorfer; Cassandra M Kerr; Teodora Kuzmanovic; Jibran Durrani; Jacob Shreve; Yasunobu Nagata; Tomas Radivoyevitch; Anjali S Advani; Farhad Ravandi; Hetty E Carraway; Aziz Nazha; Claudia Haferlach; Yogen Saunthararajah; Jacob Scott; Valeria Visconte; Hagop Kantarjian; Tapan Kadia; Mikkael A Sekeres; Torsten Haferlach; Jaroslaw P Maciejewski
Journal:  Blood       Date:  2021-11-11       Impact factor: 25.476

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