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Clinical Significance of DNA Variants in Chronic Myeloid Neoplasms
Accepted Manuscript Clinical Significance of DNA Variants in Chronic Myeloid Neoplasms (CMNs): A Report of the Association for Molecular Pathology Rebecca F. McClure, Mark D. Ewalt, Jennifer Crow, Robyn L. Temple-Smolkin, Mrudula Pullambhatla, Rachel Sargent, Annette S. Kim PII:
S1525-1578(17)30409-9
DOI:
10.1016/j.jmoldx.2018.07.002
Reference:
JMDI 722
To appear in:
The Journal of Molecular Diagnostics
Received Date: 22 August 2017 Revised Date:
7 June 2018
Accepted Date: 19 July 2018
Please cite this article as: McClure RF, Ewalt MD, Crow J, Temple-Smolkin RL, Pullambhatla M, Sargent R, Kim AS, Clinical Significance of DNA Variants in Chronic Myeloid Neoplasms (CMNs): A Report of the Association for Molecular Pathology, The Journal of Molecular Diagnostics (2018), doi: 10.1016/ j.jmoldx.2018.07.002. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Clinical Significance of DNA Variants in Chronic Myeloid Neoplasms (CMNs): A Report of the Association for Molecular Pathology
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Rebecca F. McClure,*† Mark D. Ewalt,*‡ Jennifer Crow,*§ Robyn L. Temple-Smolkin,¶ Mrudula Pullambhatla,¶ Rachel Sargent,*ǁ and Annette S. Kim*,**
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From the The Chronic Myeloid Neoplasms Working Group of the Clinical Practice Committee,*
Association for Molecular Pathology,¶ Bethesda, Maryland; the Department of Pathology,† Health
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Sciences North/Horizon Santé-Nord, Sudbury, Ontario, Canada; the Department of Pathology,‡ University of Colorado School of Medicine, Aurora, Colorado; the Huguley Memorial Medical Center,§ Burleson, Texas; the University of Pennsylvania Perelman School of Medicine,ǁ Philadelphia, Pennsylvania; and the Department of Pathology, Brigham and Women’s Hospital, Harvard Medical
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School, Boston, Massachusetts
Short running title: DNA variants in Chronic Myeloid Neoplasms
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The AMP 2015 -2017 Clinical Practice Committee consisted of Marina N. Nikiforova (2016 Chair), Antonia Sepulveda (2017 Chair), Monica J. Basehore, Mark Boguski, Susan Butler-Wu, Christopher
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Coldren, Linda Cook, Jennifer Crow, Birgit Funke, Meera R. Hameed, Lawrence J. Jennings, Arivarasan Karunamurthy, Annette S. Kim, Bryan Krock, Mary Lowery-Nordberg, Melissa Miller, Keyur Patel, Jess Friedrich Peterson, Benjamin Pinsky, Carolyn S. Richards, Somak Roy, Mark J. Routbort, Kandelaria Rumilla, Ryan Schmidt, and David S. Viswanatha.
Footnote: R.F.McC. and M.D.E. contributed equally.
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Disclosures: A.K. received consulting or advisory fees from Aushon Biosystems, and Papgene, Inc., as well as speaker fees, consulting or advisory fees from LabCorp, Inc. M.D.E. has received speaker fees/honoraria from Invivoscribe. R.S. has received consulting or advisory fees from Janssen Global
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Services LLC and The Double Hit Lymphoma Foundation, and provided voluntary consulting or advisory services to Curis.
Standard of practice is not defined by this article and there may be alternatives. See Disclaimer for
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further details.
Funding: Supported by the Association for Molecular Pathology.
Corresponding author:
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Annette S. Kim, MD, PhD 75 Francis Street, Thorn 613A Boston, MA 02115
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United States
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Email: [email protected]
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ABSTRACT To address the clinical relevance of small DNA variants in chronic myeloid neoplasms (CMNs), an
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Association for Molecular Pathology (AMP) Working Group comprehensively reviewed published literature, summarized key findings that support clinical utility, and defined critical gene inclusions for high-throughput sequencing testing panels. This review highlights the biological complexity of CMNs (including myelodysplastic syndromes, myeloproliferative neoplasms, entities with overlapping features
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(myelodysplastic syndromes/myeloproliferative neoplasms), and systemic mastocytosis), the genetic heterogeneity within diagnostic categories, and similarities between apparently disparate diagnostic
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entities. The founding variant’s hematopoietic differentiation compartment, specific genes and variants present, order of variant appearance, individual subclone dynamics, and therapeutic intervention all contribute to the clinicopathologic features of CMNs. Selection and efficacy of targeted therapies are increasingly based on DNA variant profiles present at various time points; therefore, high-throughput
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sequencing remains critical for patient management. The following genes are a minimum recommended list to provide relevant clinical information for the management of most CMNs: ASXL1, BCOR, BCORL1, CALR, CBL, CEBPA, CSF3R, DNMT3A, ETV6, EZH2, FLT3, IDH1, IDH2, JAK2, KIT, KRAS, MPL, NF1, NPM1,
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NRAS, PHF6, PPM1D, PTPN11, RAD21, RUNX1, SETBP1, SF3B1, SMC3, SRSF2, STAG2, TET2, TP53, U2AF1, and ZRSR2. This list is not comprehensive for all myeloid neoplasms and will evolve as insights into effects
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of combinations of relevant biomarkers on specific clinicopathologic characteristics of CMNs accumulate.
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INTRODUCTION Chronic myeloid neoplasms (CMNs) are a heterogeneous group of hematopoietic disorders that
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are currently classified using predominantly non-specific clinicopathologic features. We use the term CMNs to include myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPNs), those myeloid neoplasms with overlapping features (MDS/MPNs), and systemic mastocytosis, thereby
distinguishing these chronic entities from acute myeloid leukemia (AML) that has been sufficiently
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reviewed in numerous other papers. This heterogeneity of CMNs complicates the ability to make an accurate diagnosis, provide reliable prognostic information, and select appropriate therapy. Single
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genetic variants already feature prominently in the diagnosis and management of a few MPNs, notably BCR/ABL1 in chronic myelogenous leukemia (CML), FIP1L1/PDGFRA in one type of myeloid/lymphoid neoplasm with eosinophilia, KIT variants in systemic mastocytosis (SM), and JAK2, CALR, and MPL variants in the classic MPNs, including polycythemia vera (PV), essential thrombocythemia (ET), and
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primary myelofibrosis (PMF). Introduction of high-throughput sequencing technology, however, has generated a recent explosion of literature pertaining to DNA variants and their relevance with respect to diagnosis, prognosis, and the therapeutic management of CMNs. For most adult non-CML CMNs, which
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is the focus of this review, the cataloging of specific variants is well underway and has yielded new insights into which cellular processes are disrupted within the myeloid neoplasms as a group, and
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highlighted the genomic complexity underlying current diagnostic categories. In the 2016 World Health Organization (WHO), most diagnostic categories for CMNs lack a single variant as a common driver for the group.1,2 In contrast, each neoplasm contains one or more variants in genes that have been identified as altered in myeloid neoplasms as a whole (so-called "myeloid genes"). It has recently been discovered that variants in myeloid genes can be present in hematopoietic cells of individuals showing no clinical features of a myeloid neoplasm.3–5 This phenomenon is known as clonal hematopoiesis of indeterminate potential (CHIP) in individuals who lack any evidence of a myeloid neoplasm, and clonal
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cytopenia(s) of undetermined significance (CCUS), in individuals who have one or more cytopenia but lack sufficient clinicopathologic features to fulfill WHO criteria for a myeloid neoplasm. The incidence of CHIP and CCUS increases with age and both are associated with an increased risk of a subsequent
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hematopoietic neoplasm. Although these categories are not formally recognized in the current WHO classification, they are included in this review, as they represent pre-malignant conditions similar to others that are routinely considered worthy of identification and monitoring (eg, monoclonal
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gammopathy of undetermined significance and clonal B-cell lymphocytosis).
Initial variant characterization studies in CMNs seemed to merely underscore the heterogeneity
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already known to exist, without providing much practical clarification as to how the variants might be integrated into clinical practice. However, recent investigations, particularly those evaluating clonal architecture in individual CMNs, have provided a more comprehensive picture of clonal evolution. These evaluations are already providing clinically useful genomic biomarker information and promise to not
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only clarify the underlying biology of this heterogeneous group of neoplasms but also to allow for more accurate, and perhaps even truly individualized, diagnoses, prognoses, and therapies. The goal of the Association for Molecular Pathology (AMP) CMN Working Group is to review and
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summarize the current state of the literature regarding small DNA variants in adult, non-CML CMNs, and to provide education and guidance regarding the practical clinical relevance of variants in this group of
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neoplasms. Although it is clear that relevant literature continues to accumulate, it is the opinion of the authors that a “current” collation of genomic biomarker information in CMNs, would be beneficial for those involved in the clinical laboratory evaluation and management of such patients.
MATERIALS AND METHODS From November 2015 through November 2016, the AMP CMN Working Group performed a review of articles (>600 published in the English language literature) pertaining to DNA variants in adult
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CMNs with a focus on small somatic variants that might have sufficient clinical relevance to be included in testing panels for the management of these neoplasms. Essentially all of the studies were retrospective association studies, not clinical trials. Diseases primarily driven by a single recurrent
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translocation were excluded from this study, such as CML and neoplasms associated with eosinophils and abnormalities of PDGFRA, PDGFRB, or FGFR1. Aplastic anemia, a disease that shows
clinicopathologic overlap with MDS, and juvenile myelomonocytic leukemia (JMML), a pediatric disease
excluded due to their distinct pathogenesis from other CMNs.
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that has some overlapping features with adult chronic myelomonocytic leukemia (CMML), were also
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A master database was created to relate genes with reported variants to WHO disease categories and to discrete facts felt to be of diagnostic, prognostic, or therapeutic relevance. The database matrix included the clinically relevant fact, WHO disease category, gene name, gene relevance in cell biological processes, gene associations (genes with variants identified together or appearing
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mutually exclusive), specific variant when applicable, incidence (number of patients in the study with the feature being evaluated), total number of patients in the study, and data source. Only gene symbols are used in this text and readers are referred to the HUGO Gene Nomenclature Committee
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(http://www.genenames.org, last accessed 4/14/17) for full gene designations. A review of relevant basic cell processes, focusing on the normal role of each gene in the
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database, was performed and is summarized graphically in Figures 1, 2, and 36 (also Supplemental Figures S17,8 and S29) to provide an aid for data analysis and discussion. From the database, Supplemental Tables S1, S2, S3, S4, S5.10-140 were created to summarize the most clinically relevant data in a form that could be more easily viewed. In the text, only genes that were found in greater than 10% of cases were listed, but genes mutated at lower frequencies in specific diseases are noted in the Supplemental Tables S1, S2, S3, S4, and S5 and organized by cell process. However, these latter tables are not meant to be comprehensive, and it is possible that infrequent drivers may have been missed by
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this study. Prognostic data was further analyzed to be presented as a heatmap (Figure 4) representing a synthesized, overall view of the clinical value of variants in each gene. To create the heatmap, key
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prognostic matrix points [progression, including fibrosis, transformation to acute leukemia, leukemiafree survival (LFS), and overall survival (OS)] were given a score from 1 to 3 as follows: Unclear- no convincing reports OR contradictory reports OR <5 patients reported (labeled as “unclear”
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prognostically); Score 1 - ≤2 papers OR multiple contradictory reports OR <25 patients reported; Score 2 - ≥2 papers AND no contradictory reports AND ≥25 patients reported; Score 3 - ≥4 papers AND no
RESULTS COMMON PATHWAYS ALTERED IN CMNs
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contradictory reports AND ≥100 patients reported.
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The majority of genes commonly containing variants in CMNs may be classified into several key pathways that span the breadth of cellular functions. The four most significant pathways are: i) receptor kinase signaling transduction (Figure 1 and Supplemental Table S1); ii) transcription via transcription
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factors (Figure 1 and Supplemental Table S2); iii) epigenetic modification (Figure 2 and Supplemental Table S3); and iv) RNA splicing (Figure 3 and Supplemental Table S4).
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Activity through these key pathways, which are all critically implicated in CMNs, regulates cell cycle progression, apoptosis, and protein degradation. Other pathways with fewer components containing gene variants are shown in Supplemental Figures S1 and S2 and Supplemental Table S5. DNA variants may occur from several types of sequence alterations (single nucleotide changes,
insertions, deletions, and inversions) resulting in a variety of mutations (missense, nonsense, frameshift, and splice site alteration) that lead to altered RNA and/or protein levels and/or functions. Variants are frequently described as showing gain of function (GOF), loss of function (LOF), or alteration of
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function (AOF), based on the final functional result for the protein encoded. Missense and in-frame insertion/deletion variants are typically associated with GOF or AOF while nonsense and frameshift variants are typically associated with LOF or AOF. In many genes (eg, CALR, JAK2, MPL, SF3B1, SRSF2,
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and U2AF1), there are variant hotspots, whereas in other genes (eg, TP53), variants may be found
throughout the gene. Variant locations for each gene and the most common corresponding changes in protein function are denoted in Supplemental Table S6. It should be noted that not all somatic variants
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identified in CMNs are pathogenic drivers.
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CATEGORIZATION OF VARIANTS BY WHO DISEASE CLASSIFICATIONS
DNA variants reported in WHO categories of CMNs were further cataloged based on variant diagnostic specificity, prognostic utility, and therapeutic implications (Supplemental Tables S1, S2, S3, S4, S5). Although gene sets vary between studies, there is general consensus regarding the most
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commonly identified genes containing variants implicated in CMNs and those genes are included here. The broad range of reported incidences for variants in most genes likely resulted from study differences with respect to the number of cases, groupings of cases, sequencing targets (focused panels versus
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whole exome), sequencing analytic sensitivity, sample type, and processing. All diagnostic categories have reported variants in genes representing multiple cellular pathways. Though some variants appear
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to have prognostic utility for specific categories, others show utility across many/all diagnostic categories. However, for most reported gene variants, there was either minimal or absent available prognostic information, conflicting prognostic information, or an absence of prognostic significance. Studies also varied widely with respect to which prognostic features were evaluated and the subgroupings of patients reported. The most commonly reported prognostic endpoints were risk for progression (fibrosis and/or acute leukemia, almost exclusively AML), leukemia-free survival (LFS), and overall survival (OS). Most articles reported each particular prognostic feature as a comparison between
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the diagnostic group with the variant and the diagnostic group without the variant. Unless otherwise specified, these methods of reporting were assumed for the purposes of this review. For ease of visualization this complex and often incomplete data, genes with variants reported as having prognostic
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significance were weighted for clinical relevance based on a scoring system that was designed to reflect the strength of the prognostic correlation and presented in a heatmap (Figure 4).
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Clonal hematopoiesis (CHIP and CCUS)
With the recent description of CHIP and CCUS,3–5,141 the list of genes that may be clinically
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relevant for myeloid neoplasms has expanded.The most common CHIP genes (accounting for 63% to 78% of somatic variants found in clonal hematopoiesis) are also commonly found in myeloid neoplasms (DNMT3A, ASXL1, TET2, JAK2, PPM1D, SF3B1, and TP53).3–5,141 These genes predominantly define the clinical implications of CHIP. In addition, clonal hematopoiesis may also be seen with a large number of
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other genes less frequently, including SRSF2, TP53, CBL, U2AF1, IDH2, ATM, TET2, GNAS, GNB1, BCOR, CUX1, SETD2, SETBP1, and BCORL1. Overall, when compared with age-matched controls, the presence of clonal hematopoiesis at or greater than 2% variant allele fraction (VAF) has been associated with an
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increased risk of a subsequent hematopoietic neoplasm (hazard ratio 11 to 12), death (hazard ratio 1.4), and an overall rate of progression of 0.5% to 1% per year.4,142,143 Interestingly, these patients also have
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an increased risk of cardiovascular disease.4,144 Highly sensitive sequencing methods, such as can be achieved by molecular barcoding, have detected very small clones sizes (VAF 0.03% t0 2%) that reveal clonal hematopoiesis may be found in 95% of 50- to 70-year–olds, although the clinical significance of these smaller clones has not been studied to date.145 Variants in spliceosome genes appear to arise almost exclusively in individuals >70 yo and these variants do not appear to provide a proliferative advantage to normal hematopoietic stem and progenitor cells.146 Studies have suggested that higher VAF (>10%), and an increased number of variants (>2), presence of spliceosome gene variants, and
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comutation patterns involving TET2, DNMT3A, or ASXL1 may identify CHIP patients at increased risk of subsequent myeloid neoplasm.147 The clinical relevance of most individual variants has not yet been
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determined due to the low frequency of any individual variant in the available studies.
Myelodysplastic syndrome (MDS)
Reported series of DNA variants in MDS typically lump together many of the WHO MDS
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subcategories and even include entities from the mixed MDS/MPN categories, such as CMML. Thus, conclusive data for individual MDS categories is difficult to obtain. As such, the following summarizes
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the data for the inclusive category of MDS.
Genes reported to show variants in ≥10% of cases in at least one series included: SF3B1 (10% to 33%),12,22,24,25,31,84,90,108,130-132 TET2 (13% to 37%),124 ASXL1 (5% to 46%),22-25,84,89,99–105 TP53 (5% to 18%),22,23,25,31 U2AF1 (5% to 17%),22,24,91,103,131,132,135,136 SRSF2 (12% to 33%),12,22,24,25,90-92,103,105,131,132 STAG2 (5% to 15%),24,31,138 RUNX1 (8% to 20%),22–25,83,84 DNMT3A (3% to 13%),22,24,25,84,88,89,100,101,103-105 EZH2 (3%
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to 11%),22-25,84,89,100,105,112,113 ZRSR2 (3% to 11%),24,89,91,92,103,131,132,135 IDH1/2 (4% to 12%),23,24,89,104,114,115,117 cohesins as a group (8% to 15%),24,25,89,92,133,137,138 KIT (1% to 10%),24,25,31 NRAS (3% to 10%),22,23,25,26,31 and
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KRAS (<1% to 10%).22-25,31 Genes from all major cell process categories were represented. Although no single gene or gene category aligned exclusively with MDS or any of its subcategories, SF3B1 variants are
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highly correlated with the dysplastic feature of ring sideroblasts (RS). This association is so robust that the WHO 2016 revision requires only 5% RS in the presence of a pathologic SF3B1 variant for a diagnosis of MDS-RS compared to the at least 15% RS required for cases without an SF3B1 variant.2 Variants in some genes appear to have prognostic utility for patients with MDS (Figure 4 and
Supplemental Tables S1, S2, S3, S4, and S5). Variants in the following genes are the most significant poor prognostic markers: ASXL1 (increased progression, decreased LFS and OS, poor overall),3,23-25,84,102– 104
CBL (decreased OS, poor overall),23,24,26 BCOR (decreased OS),24,105 cohesins as a group (increased
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progression, decreased OS, poor overall),24,92,133 ETV6 (decreased OS,23–25 poor overall), EZH2 (decreased OS, poor overall),22–25,84,89,105,100,112,113 FLT3 (increased progression),40,41 KRAS (increased progression, poor overall),24,41 NRAS (decreased OS, poor overall),22–25 PHF6 (poor overall),24 PPM1D (increased risk
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of therapy-related myeloid neoplasms),82 PTPN11 (decreased OS),79 RUNX1 (increased progression, decreased LFs and OS, poor overall),22–25,83 SETBP1 (increased progression, decreased OS, poor overall), 86–88
SRSF2 (increased progression, decreased LFS and OS, poor overall),22,26,91,103,132,135 STAG2 (increased
25,79,84,139,140
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progression, decreased OS),24,31,92,133 TP53 (increased progression, decreased OS, poor overall),22–
and U2AF1 (decreased OS, poor overall).22,26,136,137 In addition, patients with more pathogenic
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variants fair worse than patients with fewer variants.148 Only SF3B1 variants have been associated with better prognosis (increased LFS and OS so long as not associated with variants in RUNX1 or TP53),12,25,84,104,130,132 the effect being independent of the categorization of MDS-RS.12 The following genes had ambiguous data with respect to variant status and prognosis: DNMT3A,22,24,31,104,110 IDH1,23,24,100,103,105,114-118IDH2,24,105,114,115,117,118 IDH1/2,104,117 NPM1,22-24, 40 TET2,23,31,40,42,3,101,105,107,124–126 and
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ZRSR2.103,135 Variants in the remaining genes either had no impact on prognosis or no data identified. Haferlach et al recently proposed a new prognostic predictor for MDS based only on the variant status
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of 14 myeloid genes (ASXL1, CBL, ETV6, EZH2, KRAS, LAMB4, NF1, NPM1, NRAS, PRPF8, RUNX1, STAG2, TET2, and TP53).24 This was shown to outperform the Revised International Prognostic Scoring System
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(IPSS-R). In the transplant setting, TP53 (especially truncating variants) and RAS variants are associated with high rates of relapse and poor survival post transplantation.82 TP53 and PPM1D variants are commonly found in therapy-related MDS (38% and 15% of cases, respectively) and are associated with poor prognosis. In therapy-related MDS lacking a TP53 mutation, the prognosis is similar to nontherapy–related MDS.82 Specific therapeutic responses in MDS have been associated with variants in the following genes: STAG2 and RAD21 (better response to DNA methyl transferase (DNMT) inhibitors),133 SF3B1 (increased response to DNMT inhibitors),104 TET2 (increased response to DNMT inhibitors when
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ASXL1 wildtype),101 and TP53 (decreased response to lenalidomide).149 However, small molecule therapeutics that specifically target proteins that are altered due to known gene variants are not yet commonly used in MDS patients.
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Clonal architecture studies in individual MDS patients have provided interesting insights into the pathogenesis and dynamic nature of MDS clones.24,25,60,89,148,150 Mossner et al reported the
reconstruction of variant hierarchies in serial samples from 30 cases, including many pre- and post-
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therapy samplings.148 The results showed that each patient's clone is unique with respect to founding variants and to those appearing throughout the disease course. In all cases, variants in genes involved in
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methylation and/or splicing were identified as the earliest events in 90% of the cases. Interestingly, the remaining 10% of the cases had TP53 variants initially identified, followed by the appearance of variants in methylation (especially ASXL1, TET2, and DNMT3A) or splicing genes and/or del(5q). Variants in genes involved in signaling pathways were not identified early, but rather later in clonal progression, as was
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the case for large variants, detected using classic cytogenetic techniques. This study also clearly confirmed that founding clones frequently involve lymphocytes (both B-cells and T-cells) further highlighting that clonal initiation occurs in pluripotent hematopoietic stem cells, and underscoring the
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importance of using non-hematopoietic cells as internal germline controls for these types of studies. This study also demonstrated that clonal progression may be linear, branching, or a combination of
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both, occurring with or without therapy. Following therapy, relapses may arise from the original founding clone, from re-emergence of subclones that were insensitive to therapy, or as outgrowth of apparently new subclones. Although specific clinicopathologic features appeared to track with overall clonal burden (eg, hemoglobin, white blood cell count, platelet count) or specific subclones (eg., ring sideroblasts with SF3B1 variants), other distinct associations of clonal patterns with WHO subclassifications were not clearly identified. There was also a direct correlation between the complexity of clonal architecture and clone aggressiveness, with death frequently occurring shortly after the
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emergence of additional variant complexity. The data from this detailed clonal architecture study aligns well with reports of variant gene frequencies in MDS and apparent order of identification of variants in prior reports.24,108,132,136 Overall, the data from clonal architecture studies support the hypothesis that
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MDS likely arises from CHIP in essentially all cases and that the clinicopathologic features are dictated by the emergence of subsequent variants. Spliceosome component variants which, as mentioned above, are identified in CHIP essentially exclusively in individuals >70 years old, are also seen predominantly in
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MDS patients >70 years old.24,25 This suggests a specific component of age-induced development.
Spliceosome gene variants also appear associated with dysplastic features since they are enriched in
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CMNs with prominent dysplasia.
Myelodysplastic/myeloproliferative neoplasms (MDS/MPN)
Reporting on the clinical significance of DNA variants in each of these neoplasms is variable and
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consists of predominantly small series or the inclusion of these cases within larger general groups. Thus, accurate data extraction is difficult. However, as might be expected from their clinicopathologic
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similarities to MDS and MPN, there is significant genetic overlap among these entities.
Chronic myelomonocytic leukemia (CMML)
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Genes reported to show variants in ≥10% of cases in at least one series included: TET2 (22% to 61%),28,29,32–34,42,43,107,124,127 SRSF2 (28% to 52%),28,32–34,43,73,132 ASXL1 (22% to 60%),25,29-34,42,43,73,99,105-107 RUNX1 (7% to 37%),31,32,34,35,42,43,85 CBL (10% to 22%),27–34 CEBPA (4% to 20%),31,80,81 JAK2 (1% to 10%),28,29,31–34,43,44 KRAS (7% to 18%),25,28,29,31–34,43 NRAS (4% to 16%),28,29,31–34,43 SETBP1 (4% to 16%),3133,90–93
EZH2 (6% to 13%),25,28–34,106,112 DNMT3A (2% to 13%),25,29,31–34,105 KIT (<1% to 11%),34,69 IDH2 (0% to
11%),32–34,43,118 SF3B1 (4% to 10%),31,32,34,43,108 U2AF1 (5% to 15%),31–34 STAG2 (10%),31 ZRSFR2 (8% to 10%),31,32,34,43 and cohesins in general (6% to 10%).31,138 Genes from all major cell process categories
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were represented with no single gene or gene category aligned specifically with CMML or any of its subcategories. Variant identification in some genes appears to have prognostic utility for CMML patients (Figure 4 and Supplemental Tables S1, S2, S3, S4, and S5). Variants in the following genes are the most
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significant poor prognostic markers: ASXL1 (increased progression to AML, decreased LFS and OS, poor overall),28,31,34,42,43,96,99 CBL (decreased OS, poor overall),23,24,27,29,34 DNMT3A (decreased overall survival, poor overall),29,31 EZH2 (increased progression, decreased OS, poor overall),28–31,33,43,112,113 MPL
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(decreased OS),33 NPM1 (increased progression, decreased OS),31,81,98 NRAS (decreased OS, poor
overall),33,34 and SETBP1 (increased progression to AML).86,87,94,95 Variants in the following genes had
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ambiguous data with respect to prognosis: CEBPA,80,81 FLT3,39-41 IDH2,34,43,118 RUNX1,28,31,81 SETBP1 (overall survival),86,87,94-97 SF3B1, SRSF2,28,31,34 and TET2.12,22-24,28,31,34,42,43,90,101,105,107,124 Variants in the remaining genes either had no impact on prognosis or no data identified. No gene variants were identified as being predictive of response to therapies currently available for the treatment of CMML.
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However, rare tumors containing activating FLT3 variants have been treated with FLT3 inhibitors.151,152 Other signaling pathway components such as JAK2, KRAS/NRAS, MAPK, and MEK as well as methylation pathway components IDH1/2 have been the focus of targeted therapy development.153
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Clonal architecture studies in CMML have shown very similar findings to those identified in MDS as discussed above: variants in genes involved in methylation or RNA splicing, in particular ASXL1, TET2,
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and SRSF2, are identified early and variants in genes encoding transcription factors and signaling/other pathway components appear later in clonal progression.32 At this time, gene variants aligning specifically with monocytic differentiation, the hallmark feature of CMML, have not been clearly identified. It remains unclear whether prominent monocytic differentiation is due to a specific combination and/or order of acquisition of known myeloid genes, or whether the key driver variant(s) remain to be discovered in other genes. Of note, a study using whole-exome sequencing revealed greater than 10% of CMML cases contain variants in several genes not among those currently described as recurring variants
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in CMNs.33 CBL variants are enriched in CMML compared with other CMNs and it has been proposed that the presence of a CBL variant should suggest the diagnosis of CMML in the correct clinical context.73 Not surprisingly, when compared with MDS, CMML as a group shows a higher percentage of cases
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containing variants in signaling genes associated with proliferative features (eg, JAK2, MPL, KIT, KRAS, and NRAS).
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Atypical CML (aCML)
Genes reported to show variants in ≥10% of cases in at least one series included: ASXL1 (20% to
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66%),31,73 TET2 (30% to 41%),31,73 SRSF2 (40%),73 SETBP1 (24% to 32%),31,77,93,97,98 NRAS (27% to 30%),31,77 U2AF1 (13%)77, EZH2 (13% to 20%),31,77,112 and KRAS (10%).31 Genes from all major cell process categories were represented but no single gene or gene category aligned specifically with aCML. Variant identification in some genes appears to have prognostic utility for patients with aCML (Figure 4). Variants in SETBP1 are enriched in aCML and are the most significant poor prognostic markers
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(decreased OS).86,93 Rare studies show EZH2 is also associated with inferior prognosis.31,112 The following genes were suggested to be associated with poor prognosis in at least one study: ASXL1,
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DNMT3A, IDH1/2, FLT3, and NPM1.31 No gene variants were identified as good prognostic markers. The remainder either had no impact on prognosis, contradictory data, or no data identified. No gene variants
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were identified as having implications for targeted therapy.
MDS/MPN with ring sideroblasts and thrombocytosis (MDS/MPN-RS-T, formerly refractory anemia with ring sideroblasts and thrombocytosis, RARS-T) Genes reported to show variants in ≥10% of cases in at least one series included: SF3B1 (72% to 87%),12,31,45,46,130 JAK2 (50% to 100%),45–49 MPL (1% to 23%),31,41,45,46,48 EZH2 (12% to 25%),25,112 BCOR (24%),25 DNMT3A (12% to 17%),31,44 CALR (13% to 15%),11,12 TET2 (26%),47 and ASXL1 (10%).45,108 Variants
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in SF3B1 are associated with ring sideroblasts, as discussed above, explaining the high incidence of these variants identified in MDS/MPN-RS-T. However, as in other CMNs, variants in epigenetic genes, such as EZH2, BCOR, DNMT3A, TET2, and ASXL1, are also present in most cases and likely represent initial
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events. Acquisition of an SF3B1 variant may precede or follow the appearance of variants in JAK2, CALR, or MPL which give the clone proliferative features, including thrombocytosis.
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Myeloproliferative Neoplasms (MPNs) Essential thrombocythemia (ET)
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Genes reported to show variants in ≥10% of cases in at least one series included: JAK2 (2% to 75%),10,13,15,18,35,44,49-54 CALR (16% to 73%),10,11,13–17 ASXL1 (4% to 25%),31,35,61 TET2 (5% to 21% and 13% to 30% in post-ET-MF),13,35,123,127,128 MPL (1% to 8% and 11% in post-ET MF),10,11,13,16,17,36,44,49,52,67 and SF3B1 (2% to 3% and 10% in post-ET-MF).35,108 Approximately 90% of ET clones acquire a variant in one of JAK2 (~60%), CALR (~25%), or MPL (~5%) at some point, with these being virtually mutually exclusive in
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any given cell/clone.15 No single gene or gene category aligned exclusively with ET. Variant identification in some genes appears to have prognostic utility for patients with ET (Figure 4 and Supplemental Tables
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S1, S2, S3, S4, and S5). Variants in the following genes are the most significant poor prognostic markers: ASXL1 (increased fibrosis),35 JAK2 (increased thrombosis, rare transformation to PV with very high VAF,
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increased fibrosis),11,14,15,50,51,53,57 MPL (increased thrombosis, poorer OS),11,52 TET2 (increased progression to AML and poorer OS),13 and TP53 (particularly biallelic loss of function leading to rapid transformation to AML, decreased OS).13 In addition, patients with more variants carry a worse prognosis than patients with fewer variants.13 Variants in CALR are associated with increased platelet counts but decreased thrombosis.11,13,14,15,17,18 There is no clear association of JAK2, CALR, or MPL variant status with major bleeding events, risk of transformation to AML, or OS. The remainder of the gene variants reported either had no impact on prognosis or no data identified. However, lack of an
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identifiable variant in JAK2, CALR, or MPL (triple negative cases) appears to be a poor prognostic feature in ET.13 Evaluations of DNA variants, including single case clonal architecture studies,13 have provided
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new insight into the pathogenesis of ET. As for other CMNs, variants in genes coding for components of methylation or splicing are identified early in the majority of cases studied. Variants in genes coding for components of signaling and other pathways (including JAK2, MPL, and possibly CALR) typically appear
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secondarily but contribute to the proliferative clinicopathologic features.18
It has been suggested that ET with JAK2 variants and PV are a spectrum of the same disease,15 as
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both entities show a direct correlation between the JAK2 VAF and the level of erythrocytosis.50 Additionally, the rare cases of ET that progress to PV show an apparent, direct relationship to the JAK2 VAF at diagnosis.15 Rare neoplasms with low JAK2 VAF, that initially present as ET, can later lose the unmutated JAK2 allele (through loss of heterozygosity at chromosome 9p), resulting in increased JAK2
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VAF, progression to a PV phenotype, and rapid progression to fibrosis.15 Very high JAK2 VAF (>75%, sometimes referred to as "homozygous") has only been described in ET with secondary fibrosis and PV.15,154 Reports of PV transforming to ET were not found and PV does not ever appear to develop from
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ET containing CALR or MPL variants.15
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Polycythemia vera (PV)
Genes reported to show variants in ≥10% of cases in at least one series included: JAK2
(essentially 100% with good sensitivity assay and all exons evaluated),10,13,15,18,35,36,44,50-54,56,57 ASXL1 (7% and 22% to 50% in post-PV MF),35,109 TET2 (7% to 36% and 7% to 33% in post-PV MF).13,28,35,127,128 Although JAK2 variants are not specific for PV, essentially all PVs contain a JAK2 variant and do not contain variants in either CALR or MPL.10,11 Variant identification in some genes appears to have prognostic utility for patients with PV (Figure 4 and Supplemental Tables S1, S2, S3, S4, and S5).
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Variants in the following genes are the most significant poor prognostic markers: ASXL1 (increased fibrosis),35 JAK2 (very high VAF associated with increased thrombosis and fibrosis and poor overall prognosis),15,50,51,54,57–59 TET2 (increased progression to AML and poorer OS),13 and TP53 (particularly
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biallelic loss of function leading to rapid transformation to AML).13 In addition, patients with more
variants carry a worse prognosis than patients with fewer variants.13 Variants in the remaining genes either had no impact on prognosis or no data identified.
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Individual patient clonal hierarchy studies13 and others studies18 indicate that, as for other
CMNs, variants in genes coding for components of methylation or splicing can appear early in PV with
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the secondary appearance of the JAK2 variant, although “JAK2-first” cases (where mutations in JAK2 occur first and epigenetic or splicing second) are more likely to present as PV.155 Variants in genes of signaling and alternate cell processes may also appear secondarily. Erythrocytosis is the hallmark of PV
Primary myelofibrosis (PMF)
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and is closely associated with a high level of JAK2 activity.15,50
Genes reported to show variants in ≥10% of cases in at least one series included: ASXL1 (12% to
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75%),20,35,61,76,106,109 JAK2 (25% to 79%),13,15,17,35,56,61CALR (23% to 60%),10,11,13,15,17,19 TET2 (10% to 50%),13,35,61,76,106,127,129 SRSF2 (9% to 17%),76,122 EZH2 (6% to 13%),18,36,76,106,112 and DNMT3A (3% to
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7%).18,35,76,106,111 Among genes with variants present in <10% of cases, MPL (3% to 9%) is highlighted here, as it has been reported as a recurrent gene in PMF in many series.11,13,35,36,44,52,66,76,74,75 Approximately 90% of PMF clones are identified as having a variant in one of JAK2 (~60%), CALR (~25%), or MPL (~5%) at some point, with these being virtually mutually exclusive in the same cell/clone.10,11,15,156 No single gene or gene category aligned specifically with the diagnosis of PMF. Variant identification in some genes appears to have prognostic utility for patients with PMF (Figure 4 and Supplemental Tables S1, S2, S3, S4, and S5). Variants in the following genes are the most significant poor prognostic markers:
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ASXL1 (increased fibrosis, increased progression, decreased OS, poor overall),14,19,20,31,76,104 EZH2 (increased progression, decreased LFS and OS),14,36,76,112 IDH1 (decreased LFS, decreased OS),76 JAK2 (need for splenectomy, increased progression, poor overall),32,55,57,58 MPL (when compared with PMF-
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CALR and PMF-JAK2 – increased risk of transfusion dependency, poorer OS),11,52,60,74 NRAS (poor
overall),56 and SRSF2 (increased progression, decreased LFS and OS, poor overall).14,66,116 As in the other CMNs, patients with more variants carry a worse prognosis than patients with fewer variants,13 and
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PMF lacking detectable variants in any of the main three genes (JAK2, CALR, or MPL) has a particularly poor overall prognosis.11,16,56 The following are the most significant good prognostic markers: CALR
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(lower risk of thrombosis11 and increased OS11,18,20 when compared with those with variants in JAK2 and/or MPL). The following had ambiguous data with respect to prognosis: IDH275,76,120 and MPL (when compared with PMF-JAK2).66,67 Variants in the remaining genes either had no impact on prognosis or no data identified.
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Individual clonal hierarchy studies indicate that, as for other CMNs, variants in genes coding for components of methylation or splicing appear early in PMF in the majority of cases and variants in genes coding for components of signaling and alternate cell processes occur secondarily.13,76,157 Although there
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are few clinicopathologic features specifically associated with secondary gene variants in PMF, it appears that clones containing CALR variants are associated with higher platelet counts, but lower
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thrombotic events and lower total white blood cell counts than clones containing JAK2 variants.11 Additional insight into the pathogenesis of ET, PV, and PMF has been gained by detailed analysis
of DNA variants with respect to clonal architecture. Regardless of JAK2, CALR, or MPL status, the final phenotype and natural history is affected by the presence and order of appearance of variants in a variety of other myeloid genes.155,158 For example, Ortmann et al demonstrated that although variants of JAK2, TET2, or both may appear in all of ET, PV and PMF, clones acquiring JAK2 p.V617F prior to emergence of a TET2 variant (JAK2-first) behave differently than those acquiring TET2 variants prior to
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emergence of JAK2 p.V617F (TET2-first).155 JAK2-1st stem and progenitor cells can undergo erythroid/megakaryocyte differentiation but do not themselves expand until they subsequently acquire a TET2 variant. This correlates to the observation that these patients are more likely to present as PV
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and have thrombocytosis. In contrast, TET2-1st stem and progenitor cells show clonal expansion, but do not undergo erythroid/megakaryocyte differentiation until they subsequently acquire a JAK2 variant. As such, these MPNs are not as likely to show erythrocytosis and/or thrombocytosis at initial presentation.
number of variants present (clone complexity).155
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As in MDS, the clinical aggressiveness of all MPN clones generally appears to be directly related to the
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Because it appears that signaling through various tyrosine kinase pathways is a common feature of these diseases, many small molecule therapeutics that target a variety of components in several key pathways are being utilized or evaluated (eg, inhibitors of JAK, PI3K, AKT, MTOR, TORC, histone deacetylase). It remains to be seen whether gene variant data will be informative for guiding therapy
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further in classic MPNs. Several recent reviews of this topic are available.159,160
Chronic neutrophilic leukemia (CNL)
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When strict WHO criteria are applied, essentially 100% of these extremely rare cases have a variant in CSF3R.161–163 The p.T618I mutation is highly specific and correlates with sensitivity to
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ruxolitinib.163,164 Clones containing the p.S783fs* mutation, and possibly other c-terminal truncating variants, show inhibition by dasatinib.164 SETBP1 variants are reported in the range of 15% to 55%, but some reports that have taken a more rigid classification of aCML and CNL have suggested that the percentage may be closer to 1%.1,73,161,162
Chronic eosinophilic leukemia (CEL)
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Chronic eosinophilic leukemia, not otherwise specified (CEL-NOS), is a clonal proliferation of eosinophils that does not contain translocations of PDGFRA, PDGFRB, or FGFR1. In addition to cytogenetic aberrations, clonality may be demonstrated by detection of small, somatic DNA variants in
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myeloid genes, the most common being: ASXL1 (43%), TET2 (36%), EZH2 (29%), SETBP1 (22%), CBL (14%), NOTCH1 (14%), and rarely DNMT3A, NRAS, JAK2 (non-p.V617F), and GATA2.165 DNA variant
evaluation now allows for a diagnosis of CEL in many cases that would have previously been considered
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idiopathic hypereosinophilic syndrome.1,2 Further studies will be required to clarify what underlying
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pattern of clonal architecture and progression of variants gives this CMN its clinicopathologic features.
Systemic Mastocytosis (SM)
Genes reported to show variants in ≥10% in at least one series included: KIT (essentially 100%),38,68,70,71 TET2 (20% to 47%),37,38,72,129 SRSF2 (36% to 43%),38,68 ASXL1 (12% to 29%),37,38,68 RUNX1 (23%),38,68 JAK2 (5% to 16%),38,68 KRAS/NRAS (14%),38,68 CBL (4% to 13%),37,38 DNMT3A (12%),37 EZH2 (5%
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to 10%),38,68 and KRAS (10%).68 For the following genes, the highest incidence was reported in systemic mastocytosis with an associated hematopoietic neoplasm (SM-AHN): ASXL1, CBL, JAK2, KRAS/NRAS, and
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TET2. Genes from all major cell process categories were represented, but no single gene or gene category aligned exclusively with SM or any of its subcategories. However, the outgrowth of mature
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mast cells seen in mastocytosis is strongly associated with KIT variants and essentially all cases have a KIT variant in the mature mast cell component, with variable presence in other hematopoietic compartments.69,71 It should be noted that increased mast cells may be seen in other hematologic malignancies as either reactive (eg, in lymphoplasmacytic lymphoma) or as part of the neoplastic clone due to increased KIT activation without mutation (eg, in FIP1L1/PDGFRA myeloid/lymphoid neoplasm with eosinophilia). Variant identification in some genes appears to have prognostic utility for patients with SM. Variants in the following genes were the most significant poor prognostic markers: ASXL1
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(decreased OS, especially if present with variants in one or more of RUNX1, SRSF2, DNMT3A),37,38,68 DNMT3A (decreased OS, especially if present with variants of one or more of TET2 or ASXL1),37 KIT (poor overall if present in multiple lineages),70,71 RUNX1 (decreased OS, especially if present with variants in
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one or more of ASXL1 and SRSF2),38 and SRSF2 (decreased OS, especially if present with variants in one or more of ASXL1 and RUNX1).38 A KIT variant identified only in mast cells is a good prognostic marker. Variants in the remaining genes either had no impact on prognosis or no data were identified.
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Tyrosine kinase inhibitors with inhibitory activity for KIT may be used for therapy in systemic mastocytosis, although each drug has a unique profile with respect to activity on protein derived from
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the wild-type gene and from KIT with the various known variants.166–168 For example, KIT p.D816V is associated with resistance to the tyrosine kinase inhibitor, imatinib, but has been associated with responses to other inhibitors including midostaurin.
Clonal architecture studies in SM have shown that SM-AHN clones, including those designated
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as aggressive (ASM-AHN), have initiating variants in non-KIT genes.38,69 Similar to other CMNs, these variants found in SM-AHN are most common in genes found in the associated hematologic neoplasm involved in epigenetics (TET2, ASXL1, and EZH2) or RNA splicing (SRSF2). In these cases, the KIT variants
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appear to arise within a subclone in a similar manner to other CMNs where variants in signaling pathway genes appear secondarily.68 The non-KIT gene variant patterns identified in these cases parallel the
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patterns seen in the associated non-SM CMNs (eg, SM-AHNs in which the AHN resembles CMML have clonal variant architecture similar to CMML in addition to the KIT variant). Interestingly, within the broader group of neoplasms classified as mastocytosis, the following features directly correlate with aggressiveness: presence and number of non-KIT gene variants, acquisition of the KIT variant within early hematopoietic compartments (HSC or early myeloid progenitor compartments) and higher KIT VAF within the compartment. Clinically indolent SM clones rarely contain non-KIT variants and only rarely contain the KIT variant in an early hematopoietic compartment (when presentat low VAF). The most
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indolent forms of mastocytosis (non-systemic/localized to skin and mucosa) appear to have KIT variants that are found only in mature mast cells, without variants identified in additional myeloid genes.69
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DISCUSSION
This review was initiated following AMP member discussions that yielded a consensus that the recent explosion of literature regarding the clinical relevance of small DNA variants in CMNs, driven by
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the use of high-throughput sequencing, was ripe for comprehensive review. This led to the formation of the AMP CMN Working Group. This group was charged with the challenging task of comprehensively
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reviewing the literature, summarizing key findings that support clinical utility, and defining the need for gene inclusion in high-throughput sequencing testing panels. It was evident, early in the process, that there was a need to clearly place the commonly reported genes within the context of their normal cell biology to clarify the discussion of the extensive literature. A second challenge was the ever-increasing
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volume of detailed literature pertaining to the topic. Thus, the Working Group's summary of relevant published data attempts to pull findings into a readily accessible format that identifies clinically relevant biomarkers, provides insight into basic biology, and establishes easy access to key references. This
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exercise was helpful to identify a list of "myeloid genes" that appear to be the most important biomarkers based on our current understanding of CMNs. The exercise also highlighted not only the
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complexity of the underlying biology of these neoplasms but also the genetic heterogeneity within diagnostic categories and the similarities between apparently disparate diagnostic entities. Recent meticulous studies evaluating the architecture of individual patient clones over time and through therapy have begun to provide clarity on the pathogenesis of CMNs. They have shown that each neoplasm is unique but that there is an overarching theme (Figure 5). In nearly all cases, the founding variant is in a gene involved in either epigenetic regulation or RNA splicing, the latter being particularly common in patients >70 years old. Variants in genes of other cell processes are often identified as later
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events. It is these later-appearing variants and their relative dominance within the total neoplastic population that appears to determine the heterogeneous clinicopathologic features currently used for sub-classification of CMNs. This relative dominance also appears to have the potential to drive
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progression toward more aggressive behavior. The hematopoietic differentiation compartment in which the founding variant is identified, the specific genes and specific variants that are present, the order of variant appearance, individual subclone dynamics, and therapeutic intervention, all contribute to the
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clinicopathologic features of any individual CMN at any point in time. Insight into the effect that
combinations of relevant biomarkers have on the specific clinicopathologic characteristics of CMNs
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continues to accumulate.
As more targeted therapies become available, their selection and efficacy will likely be based on the profile of DNA variants present in each patient's clone at various time points. Several inhibitors targeting elements of signaling pathways are already in clinical use. Therapies targeting spliceosome
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components and epigenetic modulators will soon become available. Thus, sequencing for DNA variants, remains critical for patient management at all levels (diagnosis, prognosis, therapy, monitoring). For the time being, genomic diagnostic laboratories must be capable of identifying variants in a large list of
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myeloid genes, with optimal sensitivity, and be able to aid in diagnosis and reliably evaluate and report clonal architecture throughout the course of disease.
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Based on this review, the following core 34-gene set (including the core CHIP gene set) is recommended to provide relevant clinical information for the management of most CMNs at this time (Supplemental Table S6): ASXL1, BCOR, BCORL1, CALR, CBL, CEBPA, CSF3R, DNMT3A, ETV6, EZH2, FLT3, IDH1, IDH2, JAK2, KIT, KRAS, MPL, NF1, NPM1, NRAS, PHF6, PPM1D, PTPN11, RAD21, RUNX1, SETBP1, SF3B1, SMC3, SRSF2, STAG2, TET2, TP53, U2AF1, and ZRSR2. For utilization of some CMN prognostic scoring systems, other genes may be required, and this list does not include all of the variants that may be seen in CHIP or other myeloid neoplasms, such as AML or aplastic anemia. As a result, laboratories
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endeavoring to develop a pan-myeloid panel should consider these recommendations as a minimum recommended list to provide relevant diagnostic and prognostic information in CMNs and enable
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monitoring of clonal architecture.
DISCLAIMER
The AMP Clinical Practice Guidelines and Reports are developed to be of assistance to laboratory and
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other healthcare professionals by providing guidance and recommendations for particular areas of practice. The Guidelines or Report should not be considered inclusive of all proper approaches or
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methods, or exclusive of others. The Guidelines or Report cannot guarantee any specific outcome, nor do they establish a standard of care. The Guidelines or Report are not intended to dictate the treatment of a particular patient. Treatment decisions must be made based on the independent judgment of healthcare providers and each patient’s individual circumstances. AMP makes no warranty, express or
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implied, regarding the Guidelines or Report and specifically excludes any warranties of merchantability and fitness for a particular use or purpose. AMP shall not be liable for direct, indirect, special, incidental,
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or consequential damages related to the use of the information contained herein.
ACKNOWLEDGMENTS
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We thank Norman Cyr for his expert graphic design contributions to this manuscript; Dr. R. Coleman Lindsley for helpful discussions; and multiple colleagues for their primary literature contributions to the field which have been referenced within reviews due to journal limitations.
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Greenberg PL: The multifaceted nature of myelodysplastic syndromes: Clinical, molecular, and
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Gu J, Wang Z, Xiao M, Mao X, Zhu L, Wang Y, Huang W: Chronic myelomonocytic leukemia with
double-mutations in DNMT3A and FLT3-ITD treated with decitabine and sorafenib. Cancer Biol Ther 2017, 4047:00–00.
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myelomonocytic leukemia. Curr Opin Oncol 2017, 29:79–87.
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Papaemmanuil E, Menon S, Godfrey AL, Dimitropoulou D, Guglielmelli P, Bellosillo B, Besses C, Döhner K,
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Harrison CN, Vassiliou GS, Vannucchi A, Campbell PJ, Green AR: Effect of mutation order on myeloproliferative neoplasms. N Engl J Med 2015, 372:601–612. Campbell PJ, Scott LM, Buck G, Wheatley K, East CL, Marsden JT, Duffy A, Boyd EM, Bench AJ,
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Scott MA, Vassiliou GS, Milligan DW, Smith SR, Erber WN, Bareford D, Wilkins BS, Reilly JT, Harrison CN,
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Green AR, United Kingdom Myeloproliferative Disorders Study Group, Medical Research Council Adult Leukaemia Working Party, Australasian Leukaemia and Lymphoma Group: Definition of subtypes of essential thrombocythaemia and relation to polycythaemia vera based on JAK2 V617F mutation status: a prospective study. Lancet (London, England) 2005, 366:1945–1953. 157.
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signaling. Cancer Cell 2010, 18:524–535. Pandey R, Kapur R: Targeting phosphatidylinositol-3-kinase pathway for the treatment of
Philadelphia-negative myeloproliferative neoplasms. Mol Cancer, Molecular Cancer, 2015, 14:118. Geyer HL, Mesa RA: Therapy for myeloproliferative neoplasms: when, which agent, and how?
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features similar to chronic eosinophilic leukemia, not otherwise specified. Mod Pathol 2016, 29:854– 864. Shah NP, Lee FY, Luo R, Jiang Y, Donker M, Akin C: Dasatinib (BMS-354825) inhibits KIT D816V ,
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Verstovsek S: Advanced systemic mastocytosis: the impact of KIT mutations in diagnosis,
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treatment, and progression. Eur J Haematol 2012, 90:89–98.
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FIGURE LEGENDS Figure 1: Overview of cellular processes with components reported to have coding gene variants in
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chronic myeloid neoplasms (CMNs). External growth factors and cytokines bind and activate their respective transmembrane receptors, triggering activation of pathways (predominantly composed of kinase cascade proteins) leading to activated key intermediaries such as ERK, AKT1, TP53, and
mTORC1or2. These intermediaries interact with many targets located throughout the cell until signals
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reach effectors (such a transcription factors, mitochondrial proteins, structural and transport proteins) that ultimately facilitate the major cell functions of proliferation, differentiation, survival, or apoptosis.
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Signaling through JAK/STAT/ERK is most commonly used by the three main cytokine receptors known to be important for normal myeloid hematopoiesis; erythropoietin receptor (EPOR), predominantly for development of erythrocytes, thrombopoetin receptor (TPOR) (gene called MPL), predominantly for development of megakaryocytes, and colony stimulating factor 3 receptor (CSF3R), predominantly for
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development of neutrophils. RUNX1 is a master hematopoietic transcriptional regulator, involved both in the formation of hematopoietic stem cells and differentiation, the latter with fine-tuning assistance by CEBPA. Core binding factor beta (CBFB) binds RUNX1 to enhance its DNA affinity but does not directly
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interact with the DNA. ETV6 is a strong transcriptional repressor, and is also implicated in interactions with corepressors that recruit histone deacetylases, such as NCOR2. TP53 is activated by diverse forms
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of stress (cytokine deprivation, DNA damage, others) and is the main pro-apoptotic proponent in the cell’s continual balance of pro-apoptotic and anti-apoptotic factors. TP53 induces the expression of PPM1D (not shown), a phosphatase that negatively regulates the MAPK pathway and consequently p53mediated transcription and apoptosis. It initiates cell cycle arrest and activates pro-apoptotic members of the BCL2 family in the mitochondria through direct and indirect mechanisms, the latter through its role as a transcription factor, whereby it increases transcription of pro-apoptotic BCL2 family members and directly represses transcription of anti-apoptotic family members. The cohesion complex (SMC1,
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SMC3, RAD21, STAG) forms a ring-like structure that encircles DNA without directly binding it, providing sister chromatid cohesion during processes that require DNA looping such as transcription, meiosis, mitosis, recombination, and ribosomal biogenesis (Supplemental Figure S1). Nucleophosmin (NPM1)
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shuttles proteins between the nucleus and cytoplasm, playing a key role in ribosomal biogenesis, cell cycle regulation (such as maintaining the stability and function of p53), activation of cyclin-dependent kinases, and regulation of the mitotic spindle. Old or dysfunctional proteins may be disposed off through
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ubiquitin tagging (Supplemental Figure S2) followed by degradation, either in the proteasome or
through autophagy. The protein substrates affected by the CBL family include a wide range of tyrosine
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kinases acting in signal transduction pathways, including KIT, FLT3, and JAK2. SET and its binding partner, SETBP1, play poorly elucidated roles in hematopoiesis, although both are known to have oncogenic properties when functionally abnormal. Similarly, the role of PHF6 (not shown) is poorly understood but appears to act as a tumor suppressor, regulating transcription of signaling genes and rRNA. CALR is a
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multi-compartmental protein (extracellular matrix, outer cell surface, cytosol, endoplasmic reticulum (ER), nucleus) that regulates a wide array of cellular processes including, among others, normal and abnormal protein movement through the ER, calcium signaling, and transcription modulation. However,
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variant CALR (CALRv) functions in a different manner than the wildtype, traveling with TPOR from the ER to the cell surface and activating the JAK/STAT pathway. For detailed information on the alterations
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noted in this figure in myeloid neoplasia, see Supplemental Tables S1, S2, and S5.
Figure 2: Epigenetic modification of DNA and histones with an emphasis on components reported to have coding gene variants in chronic myeloid neoplasms (CMNs). Epigenetics broadly encompasses processes that impact gene expression without altering the underlying DNA sequence and includes methylation of both DNA and histones. DNA methylation is mediated by DNA methyltransferases (DNMTs) and occurs at cytosine residues of CpG dinucleotides located within CG-rich regions of gene
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promoters. DNMT1 is responsible for maintaining patterns of methylation during DNA replication whereas DNMT3A and DNMT3B are de novo methyltransferases, both of which are expressed in hematopoietic stem cells and involved in self-renewal and differentiation, though only DNMT3A is
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expressed in more mature elements. Cytosine methylation results in recruitment of transcriptional repressors and gene silencing. Cyotsine methylation marks can be lost during DNA replication or
actively removed by the TET family proteins, including TET2. TET enzyme activity is inhibited by 2-
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hydroxyglutarate (2-HG) which is generated by the variant form of isocitrate dehydrogenase (IDH), either from the cytosolic gene IDH1, or the mitochondrial homolog, IDH2. Histone methylation alters
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chromatin structure, directly affecting accessibility to transcriptional activators and repressors and allowing recruitment of additional epigenetic regulators such as DNMTs. The polycomb repressor complex 2 (PRC2) consists of four core members (JARID2, EED, SUZ12, and EZH1 or EXH2) and silences chromatin by methylating histone H3 with activity further augmented by ASXL1. BCOR is another
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polycomb repressor complex (comprised of BCOR, BCORL1, and others), which represses transcription by ubiquitylating histone H2A. Opposing the action of the polycomb repressor complexes are a variety of histone deubiquitinases and histone demethylases, including KDM6A. For detailed information on the
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alterations noted in this figure in myeloid neoplasia, see Supplemental Table S3.
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Figure 3: Spliceosome mechanisms with an emphasis on components reported to have coding gene variants in chronic myeloid neoplasms (CMNs). For genes containing more than one exon (>90% of all genes), excision of introns through splicing of mRNA is required prior to translation. The primary machinery required for this process is a complex of five small nuclear RNAs (snRNAs) coupled with over 150 small nuclear ribonucleic proteins (snRNPs), collectively termed the spliceosome.6 Two basic types of splice site sequences are known that recruit slightly different versions of spliceosome: The major splice sequence (used for approximately 99% of splices) recruits the major spliceosome (comprised of
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snRNPs U1, U2, U4, U5, U6). Intronic material to be excised is bookended by splice sites at their 5' and 3' ends (5'ss and 3'ss, respectively). The 5'ss is characterize by a GU sequence whereas the 3' by AG. Between these sites are two additional key recognition sequences, a conserved adenosine, the branch
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point site (BPS) located between the two ends, and a polypyrimidine tract (PPT) located just 5' of the 3'ss. The initial step in the splicing process is the recognition of the 5'ss by U1 snRNP. Simultaneously, there is recognition of the PPT by the serine-arginine (SR)-rich splicing factors SRSF1 or SFSR2 as well as
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the U2 auxiliary factor, U2AF2 (formerly U2AF65). In addition, U2AF1 (formerly U2AF35) recognizes the AG of the 3'ss along with ZRSR2, an SR factor with zinc finger activity. Together these form the early (E)
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complex. The U2 auxiliary factors guide the U2 snRNP to the BPS to form complex A. Binding of the U2 snRNA to the BPS, regulated by the SF3a (subunits 1 to 3) and SF3b (subunits 1 to 6) complexes, creates a bulge by a single base non-complementarity that exposes the 2'-hydroxyl of the conserved adenosine for the transesterification to the 5'-phosphate of the guanosine adjacent to the end of the 5' exon. The
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complex U4/U5/U6 tri-snRNP is then recruited through interaction of U5 to the 3'ss, resulting in an initial B complex, and ultimately forming B* complex, the active spliceosome, with loss of U1 and U4. After the first catalytic step, the entirety is termed the C complex. The final transesterification results in
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fusion of the two exons and release of the intron in a lariat configuration. For detailed information on
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the alterations noted in this figure in myeloid neoplasia, see Supplemental Table S4.
Figure 4: Heat map of incidence and prognostic significance of gene variants by chronic myeloid neoplasms (CMNs) entity (heatmap meant to be viewed in color). Commonly mutated genes in CMNs are listed with their overall incidence as the number in each box. The color-coding represents a synthesized, overall view of the clinical value of variants in each gene. Acccordingly, the figure is best viewed in color. To create the heatmap, key prognostic matrix points (progression, including fibrosis and transformation to acute leukemia, leukemia-free survival (LFS), overall survival (OS)) were given a score
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from 1 to 3 as follows: Unclear- no convincing reports OR contradictory reports OR <5 patients reported (labeled as “unclear” prognostically); Score 1 - ≤2 papers OR multiple contradictory reports OR <25 patients reported; Score 2 - ≥2 papers AND no contradictory reports AND ≥25 patients reported; Score 3
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- ≥4 papers AND no contradictory reports AND ≥100 patients reported. Of note, the papers used to generate the score could not all be referenced in this manuscript due to space limitations. *Several studies reviewed IDH1 and IDH2 mutations together and their conclusions are listed here. †The
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percentages for CMML and aCML may reflect the inclusion of cases of CNL whereas other references have suggested that CSF3R may be highly sensitive and specific for CNL. ‡These ranges for JAK2
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incidence in PV reflect the incidence of the JAK2 p.V617F mutation only. In addition, the prognostic designation for JAK2 in PV, ET, and PMF is related largely to high VAF JAK2 mutations, not the presence of a JAK2 mutation itself. §The incidence of KIT mutations in SM reflects the incidence in mast cells and not necessarily the incidence in all marrow compartments; particularly in SM with an associated
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hematopoietic neoplasm. ¶SF3B1 mutations are found in 10% to 33% of cases of MDS overall, but are ǁ
present in 50% to 83% of cases of MDS with ring sideroblasts. PPM1D prognosis (shaded for MDS only) and frequency is only related to the high incidence of PPM1D mutations found in CHIP that is associated
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with therapy-related myeloid neoplasms, in general, after autologous stem cell transplantation. MDS - myelodysplastic syndrome; CMML - chronic myelomonocytic leukemia; aCML - atypical chronic
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myelogenous leukemia; MDS/MPN-RS-T - myelodysplastic/myeloproliferative neoplasm with ring sideroblasts and thrombocytosis; ET - essential thrombocythemia; PV - polycythemia vera; PMF primary myelofibrosis; SM - systemic mastocytosis.
Figure 5: Schematic of common changes acquired in the differentiation and progression of chronic myeloid neoplasms (CMNs). Although many and varied passenger variants are evident at the time of development of CMNs, the founder mutations in CMNs are enriched for variants in genes involved with
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epigenetic regulation and the spliceosome. TET2 and ASXL1 are particularly prevalent in the former category. In the latter category, the four main spliceosome genes (SRSF2, SF3B1, U2AF1, and ZRSR2) are commonly recurrent in MDS whereas only SRSF2 is particularly prevalent in all CMNs and SF3B1 in
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entities involving ring sideroblasts. Although this base appears to characterize MDS, in other CMNs additional secondary variants are recurrently identified and confer the disease-defining features of those entities, such as CSF3R in CNL or JAK2 and CALR in the non-CML MPNs. Finally, during disease
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progression, many CMNs acquire additional variants in TP53 or SETBP1. Specifically, in MDS, additional variants in signal transduction pathway members (such as NRAS, KRAS, FLT3, and KIT), myeloid
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transcription regulators (such as RUNX1 or ETV6), or additional epigenetic regulators (such as IDH1/2, DNMT3A, and EZH2) are common findings in more high-risk disease or secondary AML. In the non-CML MPNs, biallelic or LOH of the JAK2 lead to high VAFs in association with progressive polycythemia and fibrosis. x, variable number of passenger mutations; y, founder mutation(s); z, secondary mutation(s); n,
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progression nutation(s).
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Signaling
Splicing
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Other
PPM1Dll RUNX1 SETBP1 TP53 NPM1
7 3‐10 1‐2 10‐33¶ 12‐33 5‐17 3‐11 <1 2‐3 2‐3 15 8‐20 2‐4 5‐18 1‐4
20‐66
10 24
Rare 13‐20
12‐17 12‐25 0‐6
Rare 30‐41 3 8 † <5 4‐8
26 13‐15
50‐100
ET
PV
PMF
SM
4‐25
7
12‐75
21‐29
<1 <1 5‐21 16‐73 2
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MDS/MPN‐ RS‐T
3‐7 3 <1 2
7‐36 0
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10 22‐60 3‐7 2 2‐13 6‐13 <1‐3 1‐10 0‐11 22‐61 3 10‐22 † 0‐8 1‐10 <1‐11 7‐18 6 1‐7 4‐16 1 4‐10 28‐52 5‐15 8‐10 4‐20
aCML
3‐7 6‐13 0.5‐5 3‐5 0‐4 10‐50 23‐60 6
2‐75
23‐100‡
25‐79
1‐8
0
3‐9 7 3‐5
10
1‐23
27‐30 Rare
72‐87
1
2‐3
2‐7 9‐17
40 13
12 5‐10
0‐4 20‐29 4
5 100§ 10
5 3 36‐43 4‐5
4
3‐4
4
7‐37 4‐16 <1‐4 1‐6
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Transcription Factor
0‐2 3‐4 1‐10 <1‐10
CMML 6‐10
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Epigenetics
MDS 8‐15 <1 1 5‐15 5‐46 4‐6 <1‐3 3‐13 3‐11 1‐3 4‐12 3‐9 13‐37 8 2‐5
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Cohesin
Gene Cohesins RAD21 SMC3 STAG2 ASXL1 BCOR BCORL1 DNMT3A EZH2 IDH1 IDH1/2* IDH2 TET2 CALR CBL CSF3R FLT3 JAK2 KIT KRAS MPL NF1 NRAS PTPN11 SF3B1 SRSF2 U2AF1 ZRSR2 CEBPA ETV6 PHF6
6 24‐32 9 <1
Good 3 2 1 Unclear
Bad
No Change
1
3 3
23 3
S1525-1578(17)30409-9
DOI:
10.1016/j.jmoldx.2018.07.002
Reference:
JMDI 722
To appear in:
The Journal of Molecular Diagnostics
Received Date: 22 August 2017 Revised Date:
7 June 2018
Accepted Date: 19 July 2018
Please cite this article as: McClure RF, Ewalt MD, Crow J, Temple-Smolkin RL, Pullambhatla M, Sargent R, Kim AS, Clinical Significance of DNA Variants in Chronic Myeloid Neoplasms (CMNs): A Report of the Association for Molecular Pathology, The Journal of Molecular Diagnostics (2018), doi: 10.1016/ j.jmoldx.2018.07.002. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Clinical Significance of DNA Variants in Chronic Myeloid Neoplasms (CMNs): A Report of the Association for Molecular Pathology
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Rebecca F. McClure,*† Mark D. Ewalt,*‡ Jennifer Crow,*§ Robyn L. Temple-Smolkin,¶ Mrudula Pullambhatla,¶ Rachel Sargent,*ǁ and Annette S. Kim*,**
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From the The Chronic Myeloid Neoplasms Working Group of the Clinical Practice Committee,*
Association for Molecular Pathology,¶ Bethesda, Maryland; the Department of Pathology,† Health
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Sciences North/Horizon Santé-Nord, Sudbury, Ontario, Canada; the Department of Pathology,‡ University of Colorado School of Medicine, Aurora, Colorado; the Huguley Memorial Medical Center,§ Burleson, Texas; the University of Pennsylvania Perelman School of Medicine,ǁ Philadelphia, Pennsylvania; and the Department of Pathology, Brigham and Women’s Hospital, Harvard Medical
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School, Boston, Massachusetts
Short running title: DNA variants in Chronic Myeloid Neoplasms
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The AMP 2015 -2017 Clinical Practice Committee consisted of Marina N. Nikiforova (2016 Chair), Antonia Sepulveda (2017 Chair), Monica J. Basehore, Mark Boguski, Susan Butler-Wu, Christopher
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Coldren, Linda Cook, Jennifer Crow, Birgit Funke, Meera R. Hameed, Lawrence J. Jennings, Arivarasan Karunamurthy, Annette S. Kim, Bryan Krock, Mary Lowery-Nordberg, Melissa Miller, Keyur Patel, Jess Friedrich Peterson, Benjamin Pinsky, Carolyn S. Richards, Somak Roy, Mark J. Routbort, Kandelaria Rumilla, Ryan Schmidt, and David S. Viswanatha.
Footnote: R.F.McC. and M.D.E. contributed equally.
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Disclosures: A.K. received consulting or advisory fees from Aushon Biosystems, and Papgene, Inc., as well as speaker fees, consulting or advisory fees from LabCorp, Inc. M.D.E. has received speaker fees/honoraria from Invivoscribe. R.S. has received consulting or advisory fees from Janssen Global
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Services LLC and The Double Hit Lymphoma Foundation, and provided voluntary consulting or advisory services to Curis.
Standard of practice is not defined by this article and there may be alternatives. See Disclaimer for
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further details.
Funding: Supported by the Association for Molecular Pathology.
Corresponding author:
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Annette S. Kim, MD, PhD 75 Francis Street, Thorn 613A Boston, MA 02115
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United States
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Email: [email protected]
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ABSTRACT To address the clinical relevance of small DNA variants in chronic myeloid neoplasms (CMNs), an
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Association for Molecular Pathology (AMP) Working Group comprehensively reviewed published literature, summarized key findings that support clinical utility, and defined critical gene inclusions for high-throughput sequencing testing panels. This review highlights the biological complexity of CMNs (including myelodysplastic syndromes, myeloproliferative neoplasms, entities with overlapping features
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(myelodysplastic syndromes/myeloproliferative neoplasms), and systemic mastocytosis), the genetic heterogeneity within diagnostic categories, and similarities between apparently disparate diagnostic
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entities. The founding variant’s hematopoietic differentiation compartment, specific genes and variants present, order of variant appearance, individual subclone dynamics, and therapeutic intervention all contribute to the clinicopathologic features of CMNs. Selection and efficacy of targeted therapies are increasingly based on DNA variant profiles present at various time points; therefore, high-throughput
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sequencing remains critical for patient management. The following genes are a minimum recommended list to provide relevant clinical information for the management of most CMNs: ASXL1, BCOR, BCORL1, CALR, CBL, CEBPA, CSF3R, DNMT3A, ETV6, EZH2, FLT3, IDH1, IDH2, JAK2, KIT, KRAS, MPL, NF1, NPM1,
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NRAS, PHF6, PPM1D, PTPN11, RAD21, RUNX1, SETBP1, SF3B1, SMC3, SRSF2, STAG2, TET2, TP53, U2AF1, and ZRSR2. This list is not comprehensive for all myeloid neoplasms and will evolve as insights into effects
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of combinations of relevant biomarkers on specific clinicopathologic characteristics of CMNs accumulate.
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INTRODUCTION Chronic myeloid neoplasms (CMNs) are a heterogeneous group of hematopoietic disorders that
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are currently classified using predominantly non-specific clinicopathologic features. We use the term CMNs to include myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPNs), those myeloid neoplasms with overlapping features (MDS/MPNs), and systemic mastocytosis, thereby
distinguishing these chronic entities from acute myeloid leukemia (AML) that has been sufficiently
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reviewed in numerous other papers. This heterogeneity of CMNs complicates the ability to make an accurate diagnosis, provide reliable prognostic information, and select appropriate therapy. Single
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genetic variants already feature prominently in the diagnosis and management of a few MPNs, notably BCR/ABL1 in chronic myelogenous leukemia (CML), FIP1L1/PDGFRA in one type of myeloid/lymphoid neoplasm with eosinophilia, KIT variants in systemic mastocytosis (SM), and JAK2, CALR, and MPL variants in the classic MPNs, including polycythemia vera (PV), essential thrombocythemia (ET), and
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primary myelofibrosis (PMF). Introduction of high-throughput sequencing technology, however, has generated a recent explosion of literature pertaining to DNA variants and their relevance with respect to diagnosis, prognosis, and the therapeutic management of CMNs. For most adult non-CML CMNs, which
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is the focus of this review, the cataloging of specific variants is well underway and has yielded new insights into which cellular processes are disrupted within the myeloid neoplasms as a group, and
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highlighted the genomic complexity underlying current diagnostic categories. In the 2016 World Health Organization (WHO), most diagnostic categories for CMNs lack a single variant as a common driver for the group.1,2 In contrast, each neoplasm contains one or more variants in genes that have been identified as altered in myeloid neoplasms as a whole (so-called "myeloid genes"). It has recently been discovered that variants in myeloid genes can be present in hematopoietic cells of individuals showing no clinical features of a myeloid neoplasm.3–5 This phenomenon is known as clonal hematopoiesis of indeterminate potential (CHIP) in individuals who lack any evidence of a myeloid neoplasm, and clonal
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cytopenia(s) of undetermined significance (CCUS), in individuals who have one or more cytopenia but lack sufficient clinicopathologic features to fulfill WHO criteria for a myeloid neoplasm. The incidence of CHIP and CCUS increases with age and both are associated with an increased risk of a subsequent
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hematopoietic neoplasm. Although these categories are not formally recognized in the current WHO classification, they are included in this review, as they represent pre-malignant conditions similar to others that are routinely considered worthy of identification and monitoring (eg, monoclonal
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gammopathy of undetermined significance and clonal B-cell lymphocytosis).
Initial variant characterization studies in CMNs seemed to merely underscore the heterogeneity
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already known to exist, without providing much practical clarification as to how the variants might be integrated into clinical practice. However, recent investigations, particularly those evaluating clonal architecture in individual CMNs, have provided a more comprehensive picture of clonal evolution. These evaluations are already providing clinically useful genomic biomarker information and promise to not
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only clarify the underlying biology of this heterogeneous group of neoplasms but also to allow for more accurate, and perhaps even truly individualized, diagnoses, prognoses, and therapies. The goal of the Association for Molecular Pathology (AMP) CMN Working Group is to review and
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summarize the current state of the literature regarding small DNA variants in adult, non-CML CMNs, and to provide education and guidance regarding the practical clinical relevance of variants in this group of
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neoplasms. Although it is clear that relevant literature continues to accumulate, it is the opinion of the authors that a “current” collation of genomic biomarker information in CMNs, would be beneficial for those involved in the clinical laboratory evaluation and management of such patients.
MATERIALS AND METHODS From November 2015 through November 2016, the AMP CMN Working Group performed a review of articles (>600 published in the English language literature) pertaining to DNA variants in adult
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CMNs with a focus on small somatic variants that might have sufficient clinical relevance to be included in testing panels for the management of these neoplasms. Essentially all of the studies were retrospective association studies, not clinical trials. Diseases primarily driven by a single recurrent
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translocation were excluded from this study, such as CML and neoplasms associated with eosinophils and abnormalities of PDGFRA, PDGFRB, or FGFR1. Aplastic anemia, a disease that shows
clinicopathologic overlap with MDS, and juvenile myelomonocytic leukemia (JMML), a pediatric disease
excluded due to their distinct pathogenesis from other CMNs.
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that has some overlapping features with adult chronic myelomonocytic leukemia (CMML), were also
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A master database was created to relate genes with reported variants to WHO disease categories and to discrete facts felt to be of diagnostic, prognostic, or therapeutic relevance. The database matrix included the clinically relevant fact, WHO disease category, gene name, gene relevance in cell biological processes, gene associations (genes with variants identified together or appearing
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mutually exclusive), specific variant when applicable, incidence (number of patients in the study with the feature being evaluated), total number of patients in the study, and data source. Only gene symbols are used in this text and readers are referred to the HUGO Gene Nomenclature Committee
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(http://www.genenames.org, last accessed 4/14/17) for full gene designations. A review of relevant basic cell processes, focusing on the normal role of each gene in the
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database, was performed and is summarized graphically in Figures 1, 2, and 36 (also Supplemental Figures S17,8 and S29) to provide an aid for data analysis and discussion. From the database, Supplemental Tables S1, S2, S3, S4, S5.10-140 were created to summarize the most clinically relevant data in a form that could be more easily viewed. In the text, only genes that were found in greater than 10% of cases were listed, but genes mutated at lower frequencies in specific diseases are noted in the Supplemental Tables S1, S2, S3, S4, and S5 and organized by cell process. However, these latter tables are not meant to be comprehensive, and it is possible that infrequent drivers may have been missed by
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this study. Prognostic data was further analyzed to be presented as a heatmap (Figure 4) representing a synthesized, overall view of the clinical value of variants in each gene. To create the heatmap, key
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prognostic matrix points [progression, including fibrosis, transformation to acute leukemia, leukemiafree survival (LFS), and overall survival (OS)] were given a score from 1 to 3 as follows: Unclear- no convincing reports OR contradictory reports OR <5 patients reported (labeled as “unclear”
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prognostically); Score 1 - ≤2 papers OR multiple contradictory reports OR <25 patients reported; Score 2 - ≥2 papers AND no contradictory reports AND ≥25 patients reported; Score 3 - ≥4 papers AND no
RESULTS COMMON PATHWAYS ALTERED IN CMNs
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contradictory reports AND ≥100 patients reported.
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The majority of genes commonly containing variants in CMNs may be classified into several key pathways that span the breadth of cellular functions. The four most significant pathways are: i) receptor kinase signaling transduction (Figure 1 and Supplemental Table S1); ii) transcription via transcription
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factors (Figure 1 and Supplemental Table S2); iii) epigenetic modification (Figure 2 and Supplemental Table S3); and iv) RNA splicing (Figure 3 and Supplemental Table S4).
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Activity through these key pathways, which are all critically implicated in CMNs, regulates cell cycle progression, apoptosis, and protein degradation. Other pathways with fewer components containing gene variants are shown in Supplemental Figures S1 and S2 and Supplemental Table S5. DNA variants may occur from several types of sequence alterations (single nucleotide changes,
insertions, deletions, and inversions) resulting in a variety of mutations (missense, nonsense, frameshift, and splice site alteration) that lead to altered RNA and/or protein levels and/or functions. Variants are frequently described as showing gain of function (GOF), loss of function (LOF), or alteration of
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function (AOF), based on the final functional result for the protein encoded. Missense and in-frame insertion/deletion variants are typically associated with GOF or AOF while nonsense and frameshift variants are typically associated with LOF or AOF. In many genes (eg, CALR, JAK2, MPL, SF3B1, SRSF2,
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and U2AF1), there are variant hotspots, whereas in other genes (eg, TP53), variants may be found
throughout the gene. Variant locations for each gene and the most common corresponding changes in protein function are denoted in Supplemental Table S6. It should be noted that not all somatic variants
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identified in CMNs are pathogenic drivers.
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CATEGORIZATION OF VARIANTS BY WHO DISEASE CLASSIFICATIONS
DNA variants reported in WHO categories of CMNs were further cataloged based on variant diagnostic specificity, prognostic utility, and therapeutic implications (Supplemental Tables S1, S2, S3, S4, S5). Although gene sets vary between studies, there is general consensus regarding the most
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commonly identified genes containing variants implicated in CMNs and those genes are included here. The broad range of reported incidences for variants in most genes likely resulted from study differences with respect to the number of cases, groupings of cases, sequencing targets (focused panels versus
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whole exome), sequencing analytic sensitivity, sample type, and processing. All diagnostic categories have reported variants in genes representing multiple cellular pathways. Though some variants appear
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to have prognostic utility for specific categories, others show utility across many/all diagnostic categories. However, for most reported gene variants, there was either minimal or absent available prognostic information, conflicting prognostic information, or an absence of prognostic significance. Studies also varied widely with respect to which prognostic features were evaluated and the subgroupings of patients reported. The most commonly reported prognostic endpoints were risk for progression (fibrosis and/or acute leukemia, almost exclusively AML), leukemia-free survival (LFS), and overall survival (OS). Most articles reported each particular prognostic feature as a comparison between
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the diagnostic group with the variant and the diagnostic group without the variant. Unless otherwise specified, these methods of reporting were assumed for the purposes of this review. For ease of visualization this complex and often incomplete data, genes with variants reported as having prognostic
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significance were weighted for clinical relevance based on a scoring system that was designed to reflect the strength of the prognostic correlation and presented in a heatmap (Figure 4).
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Clonal hematopoiesis (CHIP and CCUS)
With the recent description of CHIP and CCUS,3–5,141 the list of genes that may be clinically
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relevant for myeloid neoplasms has expanded.The most common CHIP genes (accounting for 63% to 78% of somatic variants found in clonal hematopoiesis) are also commonly found in myeloid neoplasms (DNMT3A, ASXL1, TET2, JAK2, PPM1D, SF3B1, and TP53).3–5,141 These genes predominantly define the clinical implications of CHIP. In addition, clonal hematopoiesis may also be seen with a large number of
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other genes less frequently, including SRSF2, TP53, CBL, U2AF1, IDH2, ATM, TET2, GNAS, GNB1, BCOR, CUX1, SETD2, SETBP1, and BCORL1. Overall, when compared with age-matched controls, the presence of clonal hematopoiesis at or greater than 2% variant allele fraction (VAF) has been associated with an
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increased risk of a subsequent hematopoietic neoplasm (hazard ratio 11 to 12), death (hazard ratio 1.4), and an overall rate of progression of 0.5% to 1% per year.4,142,143 Interestingly, these patients also have
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an increased risk of cardiovascular disease.4,144 Highly sensitive sequencing methods, such as can be achieved by molecular barcoding, have detected very small clones sizes (VAF 0.03% t0 2%) that reveal clonal hematopoiesis may be found in 95% of 50- to 70-year–olds, although the clinical significance of these smaller clones has not been studied to date.145 Variants in spliceosome genes appear to arise almost exclusively in individuals >70 yo and these variants do not appear to provide a proliferative advantage to normal hematopoietic stem and progenitor cells.146 Studies have suggested that higher VAF (>10%), and an increased number of variants (>2), presence of spliceosome gene variants, and
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comutation patterns involving TET2, DNMT3A, or ASXL1 may identify CHIP patients at increased risk of subsequent myeloid neoplasm.147 The clinical relevance of most individual variants has not yet been
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determined due to the low frequency of any individual variant in the available studies.
Myelodysplastic syndrome (MDS)
Reported series of DNA variants in MDS typically lump together many of the WHO MDS
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subcategories and even include entities from the mixed MDS/MPN categories, such as CMML. Thus, conclusive data for individual MDS categories is difficult to obtain. As such, the following summarizes
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the data for the inclusive category of MDS.
Genes reported to show variants in ≥10% of cases in at least one series included: SF3B1 (10% to 33%),12,22,24,25,31,84,90,108,130-132 TET2 (13% to 37%),124 ASXL1 (5% to 46%),22-25,84,89,99–105 TP53 (5% to 18%),22,23,25,31 U2AF1 (5% to 17%),22,24,91,103,131,132,135,136 SRSF2 (12% to 33%),12,22,24,25,90-92,103,105,131,132 STAG2 (5% to 15%),24,31,138 RUNX1 (8% to 20%),22–25,83,84 DNMT3A (3% to 13%),22,24,25,84,88,89,100,101,103-105 EZH2 (3%
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to 11%),22-25,84,89,100,105,112,113 ZRSR2 (3% to 11%),24,89,91,92,103,131,132,135 IDH1/2 (4% to 12%),23,24,89,104,114,115,117 cohesins as a group (8% to 15%),24,25,89,92,133,137,138 KIT (1% to 10%),24,25,31 NRAS (3% to 10%),22,23,25,26,31 and
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KRAS (<1% to 10%).22-25,31 Genes from all major cell process categories were represented. Although no single gene or gene category aligned exclusively with MDS or any of its subcategories, SF3B1 variants are
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highly correlated with the dysplastic feature of ring sideroblasts (RS). This association is so robust that the WHO 2016 revision requires only 5% RS in the presence of a pathologic SF3B1 variant for a diagnosis of MDS-RS compared to the at least 15% RS required for cases without an SF3B1 variant.2 Variants in some genes appear to have prognostic utility for patients with MDS (Figure 4 and
Supplemental Tables S1, S2, S3, S4, and S5). Variants in the following genes are the most significant poor prognostic markers: ASXL1 (increased progression, decreased LFS and OS, poor overall),3,23-25,84,102– 104
CBL (decreased OS, poor overall),23,24,26 BCOR (decreased OS),24,105 cohesins as a group (increased
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progression, decreased OS, poor overall),24,92,133 ETV6 (decreased OS,23–25 poor overall), EZH2 (decreased OS, poor overall),22–25,84,89,105,100,112,113 FLT3 (increased progression),40,41 KRAS (increased progression, poor overall),24,41 NRAS (decreased OS, poor overall),22–25 PHF6 (poor overall),24 PPM1D (increased risk
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of therapy-related myeloid neoplasms),82 PTPN11 (decreased OS),79 RUNX1 (increased progression, decreased LFs and OS, poor overall),22–25,83 SETBP1 (increased progression, decreased OS, poor overall), 86–88
SRSF2 (increased progression, decreased LFS and OS, poor overall),22,26,91,103,132,135 STAG2 (increased
25,79,84,139,140
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progression, decreased OS),24,31,92,133 TP53 (increased progression, decreased OS, poor overall),22–
and U2AF1 (decreased OS, poor overall).22,26,136,137 In addition, patients with more pathogenic
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variants fair worse than patients with fewer variants.148 Only SF3B1 variants have been associated with better prognosis (increased LFS and OS so long as not associated with variants in RUNX1 or TP53),12,25,84,104,130,132 the effect being independent of the categorization of MDS-RS.12 The following genes had ambiguous data with respect to variant status and prognosis: DNMT3A,22,24,31,104,110 IDH1,23,24,100,103,105,114-118IDH2,24,105,114,115,117,118 IDH1/2,104,117 NPM1,22-24, 40 TET2,23,31,40,42,3,101,105,107,124–126 and
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ZRSR2.103,135 Variants in the remaining genes either had no impact on prognosis or no data identified. Haferlach et al recently proposed a new prognostic predictor for MDS based only on the variant status
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of 14 myeloid genes (ASXL1, CBL, ETV6, EZH2, KRAS, LAMB4, NF1, NPM1, NRAS, PRPF8, RUNX1, STAG2, TET2, and TP53).24 This was shown to outperform the Revised International Prognostic Scoring System
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(IPSS-R). In the transplant setting, TP53 (especially truncating variants) and RAS variants are associated with high rates of relapse and poor survival post transplantation.82 TP53 and PPM1D variants are commonly found in therapy-related MDS (38% and 15% of cases, respectively) and are associated with poor prognosis. In therapy-related MDS lacking a TP53 mutation, the prognosis is similar to nontherapy–related MDS.82 Specific therapeutic responses in MDS have been associated with variants in the following genes: STAG2 and RAD21 (better response to DNA methyl transferase (DNMT) inhibitors),133 SF3B1 (increased response to DNMT inhibitors),104 TET2 (increased response to DNMT inhibitors when
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ASXL1 wildtype),101 and TP53 (decreased response to lenalidomide).149 However, small molecule therapeutics that specifically target proteins that are altered due to known gene variants are not yet commonly used in MDS patients.
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Clonal architecture studies in individual MDS patients have provided interesting insights into the pathogenesis and dynamic nature of MDS clones.24,25,60,89,148,150 Mossner et al reported the
reconstruction of variant hierarchies in serial samples from 30 cases, including many pre- and post-
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therapy samplings.148 The results showed that each patient's clone is unique with respect to founding variants and to those appearing throughout the disease course. In all cases, variants in genes involved in
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methylation and/or splicing were identified as the earliest events in 90% of the cases. Interestingly, the remaining 10% of the cases had TP53 variants initially identified, followed by the appearance of variants in methylation (especially ASXL1, TET2, and DNMT3A) or splicing genes and/or del(5q). Variants in genes involved in signaling pathways were not identified early, but rather later in clonal progression, as was
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the case for large variants, detected using classic cytogenetic techniques. This study also clearly confirmed that founding clones frequently involve lymphocytes (both B-cells and T-cells) further highlighting that clonal initiation occurs in pluripotent hematopoietic stem cells, and underscoring the
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importance of using non-hematopoietic cells as internal germline controls for these types of studies. This study also demonstrated that clonal progression may be linear, branching, or a combination of
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both, occurring with or without therapy. Following therapy, relapses may arise from the original founding clone, from re-emergence of subclones that were insensitive to therapy, or as outgrowth of apparently new subclones. Although specific clinicopathologic features appeared to track with overall clonal burden (eg, hemoglobin, white blood cell count, platelet count) or specific subclones (eg., ring sideroblasts with SF3B1 variants), other distinct associations of clonal patterns with WHO subclassifications were not clearly identified. There was also a direct correlation between the complexity of clonal architecture and clone aggressiveness, with death frequently occurring shortly after the
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emergence of additional variant complexity. The data from this detailed clonal architecture study aligns well with reports of variant gene frequencies in MDS and apparent order of identification of variants in prior reports.24,108,132,136 Overall, the data from clonal architecture studies support the hypothesis that
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MDS likely arises from CHIP in essentially all cases and that the clinicopathologic features are dictated by the emergence of subsequent variants. Spliceosome component variants which, as mentioned above, are identified in CHIP essentially exclusively in individuals >70 years old, are also seen predominantly in
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MDS patients >70 years old.24,25 This suggests a specific component of age-induced development.
Spliceosome gene variants also appear associated with dysplastic features since they are enriched in
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CMNs with prominent dysplasia.
Myelodysplastic/myeloproliferative neoplasms (MDS/MPN)
Reporting on the clinical significance of DNA variants in each of these neoplasms is variable and
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consists of predominantly small series or the inclusion of these cases within larger general groups. Thus, accurate data extraction is difficult. However, as might be expected from their clinicopathologic
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similarities to MDS and MPN, there is significant genetic overlap among these entities.
Chronic myelomonocytic leukemia (CMML)
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Genes reported to show variants in ≥10% of cases in at least one series included: TET2 (22% to 61%),28,29,32–34,42,43,107,124,127 SRSF2 (28% to 52%),28,32–34,43,73,132 ASXL1 (22% to 60%),25,29-34,42,43,73,99,105-107 RUNX1 (7% to 37%),31,32,34,35,42,43,85 CBL (10% to 22%),27–34 CEBPA (4% to 20%),31,80,81 JAK2 (1% to 10%),28,29,31–34,43,44 KRAS (7% to 18%),25,28,29,31–34,43 NRAS (4% to 16%),28,29,31–34,43 SETBP1 (4% to 16%),3133,90–93
EZH2 (6% to 13%),25,28–34,106,112 DNMT3A (2% to 13%),25,29,31–34,105 KIT (<1% to 11%),34,69 IDH2 (0% to
11%),32–34,43,118 SF3B1 (4% to 10%),31,32,34,43,108 U2AF1 (5% to 15%),31–34 STAG2 (10%),31 ZRSFR2 (8% to 10%),31,32,34,43 and cohesins in general (6% to 10%).31,138 Genes from all major cell process categories
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were represented with no single gene or gene category aligned specifically with CMML or any of its subcategories. Variant identification in some genes appears to have prognostic utility for CMML patients (Figure 4 and Supplemental Tables S1, S2, S3, S4, and S5). Variants in the following genes are the most
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significant poor prognostic markers: ASXL1 (increased progression to AML, decreased LFS and OS, poor overall),28,31,34,42,43,96,99 CBL (decreased OS, poor overall),23,24,27,29,34 DNMT3A (decreased overall survival, poor overall),29,31 EZH2 (increased progression, decreased OS, poor overall),28–31,33,43,112,113 MPL
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(decreased OS),33 NPM1 (increased progression, decreased OS),31,81,98 NRAS (decreased OS, poor
overall),33,34 and SETBP1 (increased progression to AML).86,87,94,95 Variants in the following genes had
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ambiguous data with respect to prognosis: CEBPA,80,81 FLT3,39-41 IDH2,34,43,118 RUNX1,28,31,81 SETBP1 (overall survival),86,87,94-97 SF3B1, SRSF2,28,31,34 and TET2.12,22-24,28,31,34,42,43,90,101,105,107,124 Variants in the remaining genes either had no impact on prognosis or no data identified. No gene variants were identified as being predictive of response to therapies currently available for the treatment of CMML.
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However, rare tumors containing activating FLT3 variants have been treated with FLT3 inhibitors.151,152 Other signaling pathway components such as JAK2, KRAS/NRAS, MAPK, and MEK as well as methylation pathway components IDH1/2 have been the focus of targeted therapy development.153
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Clonal architecture studies in CMML have shown very similar findings to those identified in MDS as discussed above: variants in genes involved in methylation or RNA splicing, in particular ASXL1, TET2,
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and SRSF2, are identified early and variants in genes encoding transcription factors and signaling/other pathway components appear later in clonal progression.32 At this time, gene variants aligning specifically with monocytic differentiation, the hallmark feature of CMML, have not been clearly identified. It remains unclear whether prominent monocytic differentiation is due to a specific combination and/or order of acquisition of known myeloid genes, or whether the key driver variant(s) remain to be discovered in other genes. Of note, a study using whole-exome sequencing revealed greater than 10% of CMML cases contain variants in several genes not among those currently described as recurring variants
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in CMNs.33 CBL variants are enriched in CMML compared with other CMNs and it has been proposed that the presence of a CBL variant should suggest the diagnosis of CMML in the correct clinical context.73 Not surprisingly, when compared with MDS, CMML as a group shows a higher percentage of cases
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containing variants in signaling genes associated with proliferative features (eg, JAK2, MPL, KIT, KRAS, and NRAS).
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Atypical CML (aCML)
Genes reported to show variants in ≥10% of cases in at least one series included: ASXL1 (20% to
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66%),31,73 TET2 (30% to 41%),31,73 SRSF2 (40%),73 SETBP1 (24% to 32%),31,77,93,97,98 NRAS (27% to 30%),31,77 U2AF1 (13%)77, EZH2 (13% to 20%),31,77,112 and KRAS (10%).31 Genes from all major cell process categories were represented but no single gene or gene category aligned specifically with aCML. Variant identification in some genes appears to have prognostic utility for patients with aCML (Figure 4). Variants in SETBP1 are enriched in aCML and are the most significant poor prognostic markers
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(decreased OS).86,93 Rare studies show EZH2 is also associated with inferior prognosis.31,112 The following genes were suggested to be associated with poor prognosis in at least one study: ASXL1,
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DNMT3A, IDH1/2, FLT3, and NPM1.31 No gene variants were identified as good prognostic markers. The remainder either had no impact on prognosis, contradictory data, or no data identified. No gene variants
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were identified as having implications for targeted therapy.
MDS/MPN with ring sideroblasts and thrombocytosis (MDS/MPN-RS-T, formerly refractory anemia with ring sideroblasts and thrombocytosis, RARS-T) Genes reported to show variants in ≥10% of cases in at least one series included: SF3B1 (72% to 87%),12,31,45,46,130 JAK2 (50% to 100%),45–49 MPL (1% to 23%),31,41,45,46,48 EZH2 (12% to 25%),25,112 BCOR (24%),25 DNMT3A (12% to 17%),31,44 CALR (13% to 15%),11,12 TET2 (26%),47 and ASXL1 (10%).45,108 Variants
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in SF3B1 are associated with ring sideroblasts, as discussed above, explaining the high incidence of these variants identified in MDS/MPN-RS-T. However, as in other CMNs, variants in epigenetic genes, such as EZH2, BCOR, DNMT3A, TET2, and ASXL1, are also present in most cases and likely represent initial
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events. Acquisition of an SF3B1 variant may precede or follow the appearance of variants in JAK2, CALR, or MPL which give the clone proliferative features, including thrombocytosis.
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Myeloproliferative Neoplasms (MPNs) Essential thrombocythemia (ET)
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Genes reported to show variants in ≥10% of cases in at least one series included: JAK2 (2% to 75%),10,13,15,18,35,44,49-54 CALR (16% to 73%),10,11,13–17 ASXL1 (4% to 25%),31,35,61 TET2 (5% to 21% and 13% to 30% in post-ET-MF),13,35,123,127,128 MPL (1% to 8% and 11% in post-ET MF),10,11,13,16,17,36,44,49,52,67 and SF3B1 (2% to 3% and 10% in post-ET-MF).35,108 Approximately 90% of ET clones acquire a variant in one of JAK2 (~60%), CALR (~25%), or MPL (~5%) at some point, with these being virtually mutually exclusive in
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any given cell/clone.15 No single gene or gene category aligned exclusively with ET. Variant identification in some genes appears to have prognostic utility for patients with ET (Figure 4 and Supplemental Tables
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S1, S2, S3, S4, and S5). Variants in the following genes are the most significant poor prognostic markers: ASXL1 (increased fibrosis),35 JAK2 (increased thrombosis, rare transformation to PV with very high VAF,
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increased fibrosis),11,14,15,50,51,53,57 MPL (increased thrombosis, poorer OS),11,52 TET2 (increased progression to AML and poorer OS),13 and TP53 (particularly biallelic loss of function leading to rapid transformation to AML, decreased OS).13 In addition, patients with more variants carry a worse prognosis than patients with fewer variants.13 Variants in CALR are associated with increased platelet counts but decreased thrombosis.11,13,14,15,17,18 There is no clear association of JAK2, CALR, or MPL variant status with major bleeding events, risk of transformation to AML, or OS. The remainder of the gene variants reported either had no impact on prognosis or no data identified. However, lack of an
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identifiable variant in JAK2, CALR, or MPL (triple negative cases) appears to be a poor prognostic feature in ET.13 Evaluations of DNA variants, including single case clonal architecture studies,13 have provided
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new insight into the pathogenesis of ET. As for other CMNs, variants in genes coding for components of methylation or splicing are identified early in the majority of cases studied. Variants in genes coding for components of signaling and other pathways (including JAK2, MPL, and possibly CALR) typically appear
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secondarily but contribute to the proliferative clinicopathologic features.18
It has been suggested that ET with JAK2 variants and PV are a spectrum of the same disease,15 as
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both entities show a direct correlation between the JAK2 VAF and the level of erythrocytosis.50 Additionally, the rare cases of ET that progress to PV show an apparent, direct relationship to the JAK2 VAF at diagnosis.15 Rare neoplasms with low JAK2 VAF, that initially present as ET, can later lose the unmutated JAK2 allele (through loss of heterozygosity at chromosome 9p), resulting in increased JAK2
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VAF, progression to a PV phenotype, and rapid progression to fibrosis.15 Very high JAK2 VAF (>75%, sometimes referred to as "homozygous") has only been described in ET with secondary fibrosis and PV.15,154 Reports of PV transforming to ET were not found and PV does not ever appear to develop from
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ET containing CALR or MPL variants.15
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Polycythemia vera (PV)
Genes reported to show variants in ≥10% of cases in at least one series included: JAK2
(essentially 100% with good sensitivity assay and all exons evaluated),10,13,15,18,35,36,44,50-54,56,57 ASXL1 (7% and 22% to 50% in post-PV MF),35,109 TET2 (7% to 36% and 7% to 33% in post-PV MF).13,28,35,127,128 Although JAK2 variants are not specific for PV, essentially all PVs contain a JAK2 variant and do not contain variants in either CALR or MPL.10,11 Variant identification in some genes appears to have prognostic utility for patients with PV (Figure 4 and Supplemental Tables S1, S2, S3, S4, and S5).
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Variants in the following genes are the most significant poor prognostic markers: ASXL1 (increased fibrosis),35 JAK2 (very high VAF associated with increased thrombosis and fibrosis and poor overall prognosis),15,50,51,54,57–59 TET2 (increased progression to AML and poorer OS),13 and TP53 (particularly
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biallelic loss of function leading to rapid transformation to AML).13 In addition, patients with more
variants carry a worse prognosis than patients with fewer variants.13 Variants in the remaining genes either had no impact on prognosis or no data identified.
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Individual patient clonal hierarchy studies13 and others studies18 indicate that, as for other
CMNs, variants in genes coding for components of methylation or splicing can appear early in PV with
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the secondary appearance of the JAK2 variant, although “JAK2-first” cases (where mutations in JAK2 occur first and epigenetic or splicing second) are more likely to present as PV.155 Variants in genes of signaling and alternate cell processes may also appear secondarily. Erythrocytosis is the hallmark of PV
Primary myelofibrosis (PMF)
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and is closely associated with a high level of JAK2 activity.15,50
Genes reported to show variants in ≥10% of cases in at least one series included: ASXL1 (12% to
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75%),20,35,61,76,106,109 JAK2 (25% to 79%),13,15,17,35,56,61CALR (23% to 60%),10,11,13,15,17,19 TET2 (10% to 50%),13,35,61,76,106,127,129 SRSF2 (9% to 17%),76,122 EZH2 (6% to 13%),18,36,76,106,112 and DNMT3A (3% to
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7%).18,35,76,106,111 Among genes with variants present in <10% of cases, MPL (3% to 9%) is highlighted here, as it has been reported as a recurrent gene in PMF in many series.11,13,35,36,44,52,66,76,74,75 Approximately 90% of PMF clones are identified as having a variant in one of JAK2 (~60%), CALR (~25%), or MPL (~5%) at some point, with these being virtually mutually exclusive in the same cell/clone.10,11,15,156 No single gene or gene category aligned specifically with the diagnosis of PMF. Variant identification in some genes appears to have prognostic utility for patients with PMF (Figure 4 and Supplemental Tables S1, S2, S3, S4, and S5). Variants in the following genes are the most significant poor prognostic markers:
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ASXL1 (increased fibrosis, increased progression, decreased OS, poor overall),14,19,20,31,76,104 EZH2 (increased progression, decreased LFS and OS),14,36,76,112 IDH1 (decreased LFS, decreased OS),76 JAK2 (need for splenectomy, increased progression, poor overall),32,55,57,58 MPL (when compared with PMF-
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CALR and PMF-JAK2 – increased risk of transfusion dependency, poorer OS),11,52,60,74 NRAS (poor
overall),56 and SRSF2 (increased progression, decreased LFS and OS, poor overall).14,66,116 As in the other CMNs, patients with more variants carry a worse prognosis than patients with fewer variants,13 and
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PMF lacking detectable variants in any of the main three genes (JAK2, CALR, or MPL) has a particularly poor overall prognosis.11,16,56 The following are the most significant good prognostic markers: CALR
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(lower risk of thrombosis11 and increased OS11,18,20 when compared with those with variants in JAK2 and/or MPL). The following had ambiguous data with respect to prognosis: IDH275,76,120 and MPL (when compared with PMF-JAK2).66,67 Variants in the remaining genes either had no impact on prognosis or no data identified.
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Individual clonal hierarchy studies indicate that, as for other CMNs, variants in genes coding for components of methylation or splicing appear early in PMF in the majority of cases and variants in genes coding for components of signaling and alternate cell processes occur secondarily.13,76,157 Although there
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are few clinicopathologic features specifically associated with secondary gene variants in PMF, it appears that clones containing CALR variants are associated with higher platelet counts, but lower
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thrombotic events and lower total white blood cell counts than clones containing JAK2 variants.11 Additional insight into the pathogenesis of ET, PV, and PMF has been gained by detailed analysis
of DNA variants with respect to clonal architecture. Regardless of JAK2, CALR, or MPL status, the final phenotype and natural history is affected by the presence and order of appearance of variants in a variety of other myeloid genes.155,158 For example, Ortmann et al demonstrated that although variants of JAK2, TET2, or both may appear in all of ET, PV and PMF, clones acquiring JAK2 p.V617F prior to emergence of a TET2 variant (JAK2-first) behave differently than those acquiring TET2 variants prior to
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emergence of JAK2 p.V617F (TET2-first).155 JAK2-1st stem and progenitor cells can undergo erythroid/megakaryocyte differentiation but do not themselves expand until they subsequently acquire a TET2 variant. This correlates to the observation that these patients are more likely to present as PV
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and have thrombocytosis. In contrast, TET2-1st stem and progenitor cells show clonal expansion, but do not undergo erythroid/megakaryocyte differentiation until they subsequently acquire a JAK2 variant. As such, these MPNs are not as likely to show erythrocytosis and/or thrombocytosis at initial presentation.
number of variants present (clone complexity).155
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As in MDS, the clinical aggressiveness of all MPN clones generally appears to be directly related to the
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Because it appears that signaling through various tyrosine kinase pathways is a common feature of these diseases, many small molecule therapeutics that target a variety of components in several key pathways are being utilized or evaluated (eg, inhibitors of JAK, PI3K, AKT, MTOR, TORC, histone deacetylase). It remains to be seen whether gene variant data will be informative for guiding therapy
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further in classic MPNs. Several recent reviews of this topic are available.159,160
Chronic neutrophilic leukemia (CNL)
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When strict WHO criteria are applied, essentially 100% of these extremely rare cases have a variant in CSF3R.161–163 The p.T618I mutation is highly specific and correlates with sensitivity to
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ruxolitinib.163,164 Clones containing the p.S783fs* mutation, and possibly other c-terminal truncating variants, show inhibition by dasatinib.164 SETBP1 variants are reported in the range of 15% to 55%, but some reports that have taken a more rigid classification of aCML and CNL have suggested that the percentage may be closer to 1%.1,73,161,162
Chronic eosinophilic leukemia (CEL)
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Chronic eosinophilic leukemia, not otherwise specified (CEL-NOS), is a clonal proliferation of eosinophils that does not contain translocations of PDGFRA, PDGFRB, or FGFR1. In addition to cytogenetic aberrations, clonality may be demonstrated by detection of small, somatic DNA variants in
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myeloid genes, the most common being: ASXL1 (43%), TET2 (36%), EZH2 (29%), SETBP1 (22%), CBL (14%), NOTCH1 (14%), and rarely DNMT3A, NRAS, JAK2 (non-p.V617F), and GATA2.165 DNA variant
evaluation now allows for a diagnosis of CEL in many cases that would have previously been considered
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idiopathic hypereosinophilic syndrome.1,2 Further studies will be required to clarify what underlying
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pattern of clonal architecture and progression of variants gives this CMN its clinicopathologic features.
Systemic Mastocytosis (SM)
Genes reported to show variants in ≥10% in at least one series included: KIT (essentially 100%),38,68,70,71 TET2 (20% to 47%),37,38,72,129 SRSF2 (36% to 43%),38,68 ASXL1 (12% to 29%),37,38,68 RUNX1 (23%),38,68 JAK2 (5% to 16%),38,68 KRAS/NRAS (14%),38,68 CBL (4% to 13%),37,38 DNMT3A (12%),37 EZH2 (5%
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to 10%),38,68 and KRAS (10%).68 For the following genes, the highest incidence was reported in systemic mastocytosis with an associated hematopoietic neoplasm (SM-AHN): ASXL1, CBL, JAK2, KRAS/NRAS, and
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TET2. Genes from all major cell process categories were represented, but no single gene or gene category aligned exclusively with SM or any of its subcategories. However, the outgrowth of mature
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mast cells seen in mastocytosis is strongly associated with KIT variants and essentially all cases have a KIT variant in the mature mast cell component, with variable presence in other hematopoietic compartments.69,71 It should be noted that increased mast cells may be seen in other hematologic malignancies as either reactive (eg, in lymphoplasmacytic lymphoma) or as part of the neoplastic clone due to increased KIT activation without mutation (eg, in FIP1L1/PDGFRA myeloid/lymphoid neoplasm with eosinophilia). Variant identification in some genes appears to have prognostic utility for patients with SM. Variants in the following genes were the most significant poor prognostic markers: ASXL1
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(decreased OS, especially if present with variants in one or more of RUNX1, SRSF2, DNMT3A),37,38,68 DNMT3A (decreased OS, especially if present with variants of one or more of TET2 or ASXL1),37 KIT (poor overall if present in multiple lineages),70,71 RUNX1 (decreased OS, especially if present with variants in
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one or more of ASXL1 and SRSF2),38 and SRSF2 (decreased OS, especially if present with variants in one or more of ASXL1 and RUNX1).38 A KIT variant identified only in mast cells is a good prognostic marker. Variants in the remaining genes either had no impact on prognosis or no data were identified.
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Tyrosine kinase inhibitors with inhibitory activity for KIT may be used for therapy in systemic mastocytosis, although each drug has a unique profile with respect to activity on protein derived from
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the wild-type gene and from KIT with the various known variants.166–168 For example, KIT p.D816V is associated with resistance to the tyrosine kinase inhibitor, imatinib, but has been associated with responses to other inhibitors including midostaurin.
Clonal architecture studies in SM have shown that SM-AHN clones, including those designated
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as aggressive (ASM-AHN), have initiating variants in non-KIT genes.38,69 Similar to other CMNs, these variants found in SM-AHN are most common in genes found in the associated hematologic neoplasm involved in epigenetics (TET2, ASXL1, and EZH2) or RNA splicing (SRSF2). In these cases, the KIT variants
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appear to arise within a subclone in a similar manner to other CMNs where variants in signaling pathway genes appear secondarily.68 The non-KIT gene variant patterns identified in these cases parallel the
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patterns seen in the associated non-SM CMNs (eg, SM-AHNs in which the AHN resembles CMML have clonal variant architecture similar to CMML in addition to the KIT variant). Interestingly, within the broader group of neoplasms classified as mastocytosis, the following features directly correlate with aggressiveness: presence and number of non-KIT gene variants, acquisition of the KIT variant within early hematopoietic compartments (HSC or early myeloid progenitor compartments) and higher KIT VAF within the compartment. Clinically indolent SM clones rarely contain non-KIT variants and only rarely contain the KIT variant in an early hematopoietic compartment (when presentat low VAF). The most
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indolent forms of mastocytosis (non-systemic/localized to skin and mucosa) appear to have KIT variants that are found only in mature mast cells, without variants identified in additional myeloid genes.69
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DISCUSSION
This review was initiated following AMP member discussions that yielded a consensus that the recent explosion of literature regarding the clinical relevance of small DNA variants in CMNs, driven by
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the use of high-throughput sequencing, was ripe for comprehensive review. This led to the formation of the AMP CMN Working Group. This group was charged with the challenging task of comprehensively
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reviewing the literature, summarizing key findings that support clinical utility, and defining the need for gene inclusion in high-throughput sequencing testing panels. It was evident, early in the process, that there was a need to clearly place the commonly reported genes within the context of their normal cell biology to clarify the discussion of the extensive literature. A second challenge was the ever-increasing
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volume of detailed literature pertaining to the topic. Thus, the Working Group's summary of relevant published data attempts to pull findings into a readily accessible format that identifies clinically relevant biomarkers, provides insight into basic biology, and establishes easy access to key references. This
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exercise was helpful to identify a list of "myeloid genes" that appear to be the most important biomarkers based on our current understanding of CMNs. The exercise also highlighted not only the
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complexity of the underlying biology of these neoplasms but also the genetic heterogeneity within diagnostic categories and the similarities between apparently disparate diagnostic entities. Recent meticulous studies evaluating the architecture of individual patient clones over time and through therapy have begun to provide clarity on the pathogenesis of CMNs. They have shown that each neoplasm is unique but that there is an overarching theme (Figure 5). In nearly all cases, the founding variant is in a gene involved in either epigenetic regulation or RNA splicing, the latter being particularly common in patients >70 years old. Variants in genes of other cell processes are often identified as later
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events. It is these later-appearing variants and their relative dominance within the total neoplastic population that appears to determine the heterogeneous clinicopathologic features currently used for sub-classification of CMNs. This relative dominance also appears to have the potential to drive
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progression toward more aggressive behavior. The hematopoietic differentiation compartment in which the founding variant is identified, the specific genes and specific variants that are present, the order of variant appearance, individual subclone dynamics, and therapeutic intervention, all contribute to the
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clinicopathologic features of any individual CMN at any point in time. Insight into the effect that
combinations of relevant biomarkers have on the specific clinicopathologic characteristics of CMNs
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continues to accumulate.
As more targeted therapies become available, their selection and efficacy will likely be based on the profile of DNA variants present in each patient's clone at various time points. Several inhibitors targeting elements of signaling pathways are already in clinical use. Therapies targeting spliceosome
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components and epigenetic modulators will soon become available. Thus, sequencing for DNA variants, remains critical for patient management at all levels (diagnosis, prognosis, therapy, monitoring). For the time being, genomic diagnostic laboratories must be capable of identifying variants in a large list of
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myeloid genes, with optimal sensitivity, and be able to aid in diagnosis and reliably evaluate and report clonal architecture throughout the course of disease.
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Based on this review, the following core 34-gene set (including the core CHIP gene set) is recommended to provide relevant clinical information for the management of most CMNs at this time (Supplemental Table S6): ASXL1, BCOR, BCORL1, CALR, CBL, CEBPA, CSF3R, DNMT3A, ETV6, EZH2, FLT3, IDH1, IDH2, JAK2, KIT, KRAS, MPL, NF1, NPM1, NRAS, PHF6, PPM1D, PTPN11, RAD21, RUNX1, SETBP1, SF3B1, SMC3, SRSF2, STAG2, TET2, TP53, U2AF1, and ZRSR2. For utilization of some CMN prognostic scoring systems, other genes may be required, and this list does not include all of the variants that may be seen in CHIP or other myeloid neoplasms, such as AML or aplastic anemia. As a result, laboratories
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endeavoring to develop a pan-myeloid panel should consider these recommendations as a minimum recommended list to provide relevant diagnostic and prognostic information in CMNs and enable
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monitoring of clonal architecture.
DISCLAIMER
The AMP Clinical Practice Guidelines and Reports are developed to be of assistance to laboratory and
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other healthcare professionals by providing guidance and recommendations for particular areas of practice. The Guidelines or Report should not be considered inclusive of all proper approaches or
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methods, or exclusive of others. The Guidelines or Report cannot guarantee any specific outcome, nor do they establish a standard of care. The Guidelines or Report are not intended to dictate the treatment of a particular patient. Treatment decisions must be made based on the independent judgment of healthcare providers and each patient’s individual circumstances. AMP makes no warranty, express or
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implied, regarding the Guidelines or Report and specifically excludes any warranties of merchantability and fitness for a particular use or purpose. AMP shall not be liable for direct, indirect, special, incidental,
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or consequential damages related to the use of the information contained herein.
ACKNOWLEDGMENTS
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We thank Norman Cyr for his expert graphic design contributions to this manuscript; Dr. R. Coleman Lindsley for helpful discussions; and multiple colleagues for their primary literature contributions to the field which have been referenced within reviews due to journal limitations.
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FIGURE LEGENDS Figure 1: Overview of cellular processes with components reported to have coding gene variants in
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chronic myeloid neoplasms (CMNs). External growth factors and cytokines bind and activate their respective transmembrane receptors, triggering activation of pathways (predominantly composed of kinase cascade proteins) leading to activated key intermediaries such as ERK, AKT1, TP53, and
mTORC1or2. These intermediaries interact with many targets located throughout the cell until signals
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reach effectors (such a transcription factors, mitochondrial proteins, structural and transport proteins) that ultimately facilitate the major cell functions of proliferation, differentiation, survival, or apoptosis.
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Signaling through JAK/STAT/ERK is most commonly used by the three main cytokine receptors known to be important for normal myeloid hematopoiesis; erythropoietin receptor (EPOR), predominantly for development of erythrocytes, thrombopoetin receptor (TPOR) (gene called MPL), predominantly for development of megakaryocytes, and colony stimulating factor 3 receptor (CSF3R), predominantly for
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development of neutrophils. RUNX1 is a master hematopoietic transcriptional regulator, involved both in the formation of hematopoietic stem cells and differentiation, the latter with fine-tuning assistance by CEBPA. Core binding factor beta (CBFB) binds RUNX1 to enhance its DNA affinity but does not directly
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interact with the DNA. ETV6 is a strong transcriptional repressor, and is also implicated in interactions with corepressors that recruit histone deacetylases, such as NCOR2. TP53 is activated by diverse forms
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of stress (cytokine deprivation, DNA damage, others) and is the main pro-apoptotic proponent in the cell’s continual balance of pro-apoptotic and anti-apoptotic factors. TP53 induces the expression of PPM1D (not shown), a phosphatase that negatively regulates the MAPK pathway and consequently p53mediated transcription and apoptosis. It initiates cell cycle arrest and activates pro-apoptotic members of the BCL2 family in the mitochondria through direct and indirect mechanisms, the latter through its role as a transcription factor, whereby it increases transcription of pro-apoptotic BCL2 family members and directly represses transcription of anti-apoptotic family members. The cohesion complex (SMC1,
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SMC3, RAD21, STAG) forms a ring-like structure that encircles DNA without directly binding it, providing sister chromatid cohesion during processes that require DNA looping such as transcription, meiosis, mitosis, recombination, and ribosomal biogenesis (Supplemental Figure S1). Nucleophosmin (NPM1)
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shuttles proteins between the nucleus and cytoplasm, playing a key role in ribosomal biogenesis, cell cycle regulation (such as maintaining the stability and function of p53), activation of cyclin-dependent kinases, and regulation of the mitotic spindle. Old or dysfunctional proteins may be disposed off through
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ubiquitin tagging (Supplemental Figure S2) followed by degradation, either in the proteasome or
through autophagy. The protein substrates affected by the CBL family include a wide range of tyrosine
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kinases acting in signal transduction pathways, including KIT, FLT3, and JAK2. SET and its binding partner, SETBP1, play poorly elucidated roles in hematopoiesis, although both are known to have oncogenic properties when functionally abnormal. Similarly, the role of PHF6 (not shown) is poorly understood but appears to act as a tumor suppressor, regulating transcription of signaling genes and rRNA. CALR is a
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multi-compartmental protein (extracellular matrix, outer cell surface, cytosol, endoplasmic reticulum (ER), nucleus) that regulates a wide array of cellular processes including, among others, normal and abnormal protein movement through the ER, calcium signaling, and transcription modulation. However,
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variant CALR (CALRv) functions in a different manner than the wildtype, traveling with TPOR from the ER to the cell surface and activating the JAK/STAT pathway. For detailed information on the alterations
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noted in this figure in myeloid neoplasia, see Supplemental Tables S1, S2, and S5.
Figure 2: Epigenetic modification of DNA and histones with an emphasis on components reported to have coding gene variants in chronic myeloid neoplasms (CMNs). Epigenetics broadly encompasses processes that impact gene expression without altering the underlying DNA sequence and includes methylation of both DNA and histones. DNA methylation is mediated by DNA methyltransferases (DNMTs) and occurs at cytosine residues of CpG dinucleotides located within CG-rich regions of gene
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promoters. DNMT1 is responsible for maintaining patterns of methylation during DNA replication whereas DNMT3A and DNMT3B are de novo methyltransferases, both of which are expressed in hematopoietic stem cells and involved in self-renewal and differentiation, though only DNMT3A is
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expressed in more mature elements. Cytosine methylation results in recruitment of transcriptional repressors and gene silencing. Cyotsine methylation marks can be lost during DNA replication or
actively removed by the TET family proteins, including TET2. TET enzyme activity is inhibited by 2-
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hydroxyglutarate (2-HG) which is generated by the variant form of isocitrate dehydrogenase (IDH), either from the cytosolic gene IDH1, or the mitochondrial homolog, IDH2. Histone methylation alters
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chromatin structure, directly affecting accessibility to transcriptional activators and repressors and allowing recruitment of additional epigenetic regulators such as DNMTs. The polycomb repressor complex 2 (PRC2) consists of four core members (JARID2, EED, SUZ12, and EZH1 or EXH2) and silences chromatin by methylating histone H3 with activity further augmented by ASXL1. BCOR is another
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polycomb repressor complex (comprised of BCOR, BCORL1, and others), which represses transcription by ubiquitylating histone H2A. Opposing the action of the polycomb repressor complexes are a variety of histone deubiquitinases and histone demethylases, including KDM6A. For detailed information on the
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alterations noted in this figure in myeloid neoplasia, see Supplemental Table S3.
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Figure 3: Spliceosome mechanisms with an emphasis on components reported to have coding gene variants in chronic myeloid neoplasms (CMNs). For genes containing more than one exon (>90% of all genes), excision of introns through splicing of mRNA is required prior to translation. The primary machinery required for this process is a complex of five small nuclear RNAs (snRNAs) coupled with over 150 small nuclear ribonucleic proteins (snRNPs), collectively termed the spliceosome.6 Two basic types of splice site sequences are known that recruit slightly different versions of spliceosome: The major splice sequence (used for approximately 99% of splices) recruits the major spliceosome (comprised of
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snRNPs U1, U2, U4, U5, U6). Intronic material to be excised is bookended by splice sites at their 5' and 3' ends (5'ss and 3'ss, respectively). The 5'ss is characterize by a GU sequence whereas the 3' by AG. Between these sites are two additional key recognition sequences, a conserved adenosine, the branch
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point site (BPS) located between the two ends, and a polypyrimidine tract (PPT) located just 5' of the 3'ss. The initial step in the splicing process is the recognition of the 5'ss by U1 snRNP. Simultaneously, there is recognition of the PPT by the serine-arginine (SR)-rich splicing factors SRSF1 or SFSR2 as well as
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the U2 auxiliary factor, U2AF2 (formerly U2AF65). In addition, U2AF1 (formerly U2AF35) recognizes the AG of the 3'ss along with ZRSR2, an SR factor with zinc finger activity. Together these form the early (E)
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complex. The U2 auxiliary factors guide the U2 snRNP to the BPS to form complex A. Binding of the U2 snRNA to the BPS, regulated by the SF3a (subunits 1 to 3) and SF3b (subunits 1 to 6) complexes, creates a bulge by a single base non-complementarity that exposes the 2'-hydroxyl of the conserved adenosine for the transesterification to the 5'-phosphate of the guanosine adjacent to the end of the 5' exon. The
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complex U4/U5/U6 tri-snRNP is then recruited through interaction of U5 to the 3'ss, resulting in an initial B complex, and ultimately forming B* complex, the active spliceosome, with loss of U1 and U4. After the first catalytic step, the entirety is termed the C complex. The final transesterification results in
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fusion of the two exons and release of the intron in a lariat configuration. For detailed information on
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the alterations noted in this figure in myeloid neoplasia, see Supplemental Table S4.
Figure 4: Heat map of incidence and prognostic significance of gene variants by chronic myeloid neoplasms (CMNs) entity (heatmap meant to be viewed in color). Commonly mutated genes in CMNs are listed with their overall incidence as the number in each box. The color-coding represents a synthesized, overall view of the clinical value of variants in each gene. Acccordingly, the figure is best viewed in color. To create the heatmap, key prognostic matrix points (progression, including fibrosis and transformation to acute leukemia, leukemia-free survival (LFS), overall survival (OS)) were given a score
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from 1 to 3 as follows: Unclear- no convincing reports OR contradictory reports OR <5 patients reported (labeled as “unclear” prognostically); Score 1 - ≤2 papers OR multiple contradictory reports OR <25 patients reported; Score 2 - ≥2 papers AND no contradictory reports AND ≥25 patients reported; Score 3
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- ≥4 papers AND no contradictory reports AND ≥100 patients reported. Of note, the papers used to generate the score could not all be referenced in this manuscript due to space limitations. *Several studies reviewed IDH1 and IDH2 mutations together and their conclusions are listed here. †The
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percentages for CMML and aCML may reflect the inclusion of cases of CNL whereas other references have suggested that CSF3R may be highly sensitive and specific for CNL. ‡These ranges for JAK2
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incidence in PV reflect the incidence of the JAK2 p.V617F mutation only. In addition, the prognostic designation for JAK2 in PV, ET, and PMF is related largely to high VAF JAK2 mutations, not the presence of a JAK2 mutation itself. §The incidence of KIT mutations in SM reflects the incidence in mast cells and not necessarily the incidence in all marrow compartments; particularly in SM with an associated
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hematopoietic neoplasm. ¶SF3B1 mutations are found in 10% to 33% of cases of MDS overall, but are ǁ
present in 50% to 83% of cases of MDS with ring sideroblasts. PPM1D prognosis (shaded for MDS only) and frequency is only related to the high incidence of PPM1D mutations found in CHIP that is associated
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with therapy-related myeloid neoplasms, in general, after autologous stem cell transplantation. MDS - myelodysplastic syndrome; CMML - chronic myelomonocytic leukemia; aCML - atypical chronic
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myelogenous leukemia; MDS/MPN-RS-T - myelodysplastic/myeloproliferative neoplasm with ring sideroblasts and thrombocytosis; ET - essential thrombocythemia; PV - polycythemia vera; PMF primary myelofibrosis; SM - systemic mastocytosis.
Figure 5: Schematic of common changes acquired in the differentiation and progression of chronic myeloid neoplasms (CMNs). Although many and varied passenger variants are evident at the time of development of CMNs, the founder mutations in CMNs are enriched for variants in genes involved with
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epigenetic regulation and the spliceosome. TET2 and ASXL1 are particularly prevalent in the former category. In the latter category, the four main spliceosome genes (SRSF2, SF3B1, U2AF1, and ZRSR2) are commonly recurrent in MDS whereas only SRSF2 is particularly prevalent in all CMNs and SF3B1 in
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entities involving ring sideroblasts. Although this base appears to characterize MDS, in other CMNs additional secondary variants are recurrently identified and confer the disease-defining features of those entities, such as CSF3R in CNL or JAK2 and CALR in the non-CML MPNs. Finally, during disease
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progression, many CMNs acquire additional variants in TP53 or SETBP1. Specifically, in MDS, additional variants in signal transduction pathway members (such as NRAS, KRAS, FLT3, and KIT), myeloid
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transcription regulators (such as RUNX1 or ETV6), or additional epigenetic regulators (such as IDH1/2, DNMT3A, and EZH2) are common findings in more high-risk disease or secondary AML. In the non-CML MPNs, biallelic or LOH of the JAK2 lead to high VAFs in association with progressive polycythemia and fibrosis. x, variable number of passenger mutations; y, founder mutation(s); z, secondary mutation(s); n,
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progression nutation(s).
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Signaling
Splicing
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Other
PPM1Dll RUNX1 SETBP1 TP53 NPM1
7 3‐10 1‐2 10‐33¶ 12‐33 5‐17 3‐11 <1 2‐3 2‐3 15 8‐20 2‐4 5‐18 1‐4
20‐66
10 24
Rare 13‐20
12‐17 12‐25 0‐6
Rare 30‐41 3 8 † <5 4‐8
26 13‐15
50‐100
ET
PV
PMF
SM
4‐25
7
12‐75
21‐29
<1 <1 5‐21 16‐73 2
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MDS/MPN‐ RS‐T
3‐7 3 <1 2
7‐36 0
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10 22‐60 3‐7 2 2‐13 6‐13 <1‐3 1‐10 0‐11 22‐61 3 10‐22 † 0‐8 1‐10 <1‐11 7‐18 6 1‐7 4‐16 1 4‐10 28‐52 5‐15 8‐10 4‐20
aCML
3‐7 6‐13 0.5‐5 3‐5 0‐4 10‐50 23‐60 6
2‐75
23‐100‡
25‐79
1‐8
0
3‐9 7 3‐5
10
1‐23
27‐30 Rare
72‐87
1
2‐3
2‐7 9‐17
40 13
12 5‐10
0‐4 20‐29 4
5 100§ 10
5 3 36‐43 4‐5
4
3‐4
4
7‐37 4‐16 <1‐4 1‐6
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Transcription Factor
0‐2 3‐4 1‐10 <1‐10
CMML 6‐10
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Epigenetics
MDS 8‐15 <1 1 5‐15 5‐46 4‐6 <1‐3 3‐13 3‐11 1‐3 4‐12 3‐9 13‐37 8 2‐5
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Cohesin
Gene Cohesins RAD21 SMC3 STAG2 ASXL1 BCOR BCORL1 DNMT3A EZH2 IDH1 IDH1/2* IDH2 TET2 CALR CBL CSF3R FLT3 JAK2 KIT KRAS MPL NF1 NRAS PTPN11 SF3B1 SRSF2 U2AF1 ZRSR2 CEBPA ETV6 PHF6
6 24‐32 9 <1
Good 3 2 1 Unclear
Bad
No Change
1
3 3
23 3