Anthony Hunter1, Eric Padron2. 1. Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA, USA. 2. Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA. eric.padron@moffitt.org.
Abstract
PURPOSE: The advent of next-generation sequencing has allowed for the annotation of a vast array of recurrent somatic mutations across human malignancies, ushering in a new era of precision oncology. Chronic myelomonocytic leukemia is recognized as a myelodysplastic/myeloproliferative neoplasm and displays heterogenous clinical and genetic features. Herein, we review what is currently understood regarding the genomic landscape of this disease and discuss how somatic mutations have impacted current risk stratification methods. RECENT FINDINGS: Genomic studies in chronic myelomonocytic leukemia have identified a characteristic spectrum of cytogenetic and molecular abnormalities. Chromosomal abnormalities are detected in ~30% of patients and somatic gene mutations in up to 90% of patients, most commonly in TET2, SRSF2, and ASXL1. While cytogenetic abnormalities have long been known to impact the prognosis of myeloid neoplasms, recent studies have identified that somatic mutations impact prognosis independent of cytogenetic and clinical variables. This is best exemplified by mutations in ASXL1, which have been uniformly associated with inferior survival. These findings have led to the development of three molecularly inspired prognostic models, in an attempt to more accurately prognosticate in the disease. Our understanding of the genomic landscape of chronic myelomonocytic leukemia continues to evolve, with somatic mutations demonstrating an expanding role in diagnosis, risk stratification, and therapeutic decision-making. Given these findings, molecular profiling by next-generation sequencing should be considered standard of care in all patients.
PURPOSE: The advent of next-generation sequencing has allowed for the annotation of a vast array of recurrent somatic mutations across humanmalignancies, ushering in a new era of precision oncology. Chronic myelomonocytic leukemia is recognized as a myelodysplastic/myeloproliferative neoplasm and displays heterogenous clinical and genetic features. Herein, we review what is currently understood regarding the genomic landscape of this disease and discuss how somatic mutations have impacted current risk stratification methods. RECENT FINDINGS: Genomic studies in chronic myelomonocytic leukemia have identified a characteristic spectrum of cytogenetic and molecular abnormalities. Chromosomal abnormalities are detected in ~30% of patients and somatic gene mutations in up to 90% of patients, most commonly in TET2, SRSF2, and ASXL1. While cytogenetic abnormalities have long been known to impact the prognosis of myeloid neoplasms, recent studies have identified that somatic mutations impact prognosis independent of cytogenetic and clinical variables. This is best exemplified by mutations in ASXL1, which have been uniformly associated with inferior survival. These findings have led to the development of three molecularly inspired prognostic models, in an attempt to more accurately prognosticate in the disease. Our understanding of the genomic landscape of chronic myelomonocytic leukemia continues to evolve, with somatic mutations demonstrating an expanding role in diagnosis, risk stratification, and therapeutic decision-making. Given these findings, molecular profiling by next-generation sequencing should be considered standard of care in all patients.
Authors: Esperanza Such; José Cervera; Dolors Costa; Francesc Solé; Teresa Vallespí; Elisa Luño; Rosa Collado; María J Calasanz; Jesús M Hernández-Rivas; Juan C Cigudosa; Benet Nomdedeu; Mar Mallo; Felix Carbonell; Javier Bueno; María T Ardanaz; Fernando Ramos; Mar Tormo; Reyes Sancho-Tello; Consuelo del Cañizo; Valle Gómez; Victor Marco; Blanca Xicoy; Santiago Bonanad; Carmen Pedro; Teresa Bernal; Guillermo F Sanz Journal: Haematologica Date: 2010-11-25 Impact factor: 9.941
Authors: F Solé; B Espinet; G F Sanz; J Cervera; M J Calasanz; E Luño; F Prieto; I Granada; J M Hernández; J C Cigudosa; J L Diez; E Bureo; M L Marqués; E Arranz; R Ríos; J A Martínez Climent; T Vallespí; L Florensa; S Woessner Journal: Br J Haematol Date: 2000-02 Impact factor: 6.998
Authors: Daniel A Arber; Attilio Orazi; Robert Hasserjian; Jürgen Thiele; Michael J Borowitz; Michelle M Le Beau; Clara D Bloomfield; Mario Cazzola; James W Vardiman Journal: Blood Date: 2016-04-11 Impact factor: 22.113
Authors: Emnet A Wassie; Raphael Itzykson; Terra L Lasho; Olivier Kosmider; Christy M Finke; Curtis A Hanson; Rhett P Ketterling; Eric Solary; Ayalew Tefferi; Mrinal M Patnaik Journal: Am J Hematol Date: 2014-09-26 Impact factor: 10.047
Authors: Elli Papaemmanuil; Moritz Gerstung; Luca Malcovati; Sudhir Tauro; Gunes Gundem; Peter Van Loo; Chris J Yoon; Peter Ellis; David C Wedge; Andrea Pellagatti; Adam Shlien; Michael John Groves; Simon A Forbes; Keiran Raine; Jon Hinton; Laura J Mudie; Stuart McLaren; Claire Hardy; Calli Latimer; Matteo G Della Porta; Sarah O'Meara; Ilaria Ambaglio; Anna Galli; Adam P Butler; Gunilla Walldin; Jon W Teague; Lynn Quek; Alex Sternberg; Carlo Gambacorti-Passerini; Nicholas C P Cross; Anthony R Green; Jacqueline Boultwood; Paresh Vyas; Eva Hellstrom-Lindberg; David Bowen; Mario Cazzola; Michael R Stratton; Peter J Campbell Journal: Blood Date: 2013-09-12 Impact factor: 22.113
Authors: E Padron; G Garcia-Manero; M M Patnaik; R Itzykson; T Lasho; A Nazha; R K Rampal; M E Sanchez; E Jabbour; N H Al Ali; Z Thompson; S Colla; P Fenaux; H M Kantarjian; S Killick; M A Sekeres; A F List; F Onida; R S Komrokji; A Tefferi; E Solary Journal: Blood Cancer J Date: 2015-07-31 Impact factor: 11.037