Literature DB >> 23558523

SETBP1 mutations in 415 patients with primary myelofibrosis or chronic myelomonocytic leukemia: independent prognostic impact in CMML.

R R Laborde1, M M Patnaik, T L Lasho, C M Finke, C A Hanson, R A Knudson, R P Ketterling, A Pardanani, A Tefferi.   

Abstract

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Year:  2013        PMID: 23558523      PMCID: PMC3806243          DOI: 10.1038/leu.2013.97

Source DB:  PubMed          Journal:  Leukemia        ISSN: 0887-6924            Impact factor:   11.528


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SETBP1 encodes SET-binding protein 1, a binding partner for the multi-function SET protein. This protein is encoded by the SET nuclear oncogene and is involved in apoptosis, transcription and nucleosome assembly.[1] The proposed functional outcome of this interaction is based on in vitro studies that demonstrate a protection of SET protein from protease cleavage that results in inhibition of protein phosphatase 2A activity, leading to higher rates of cell proliferation.[1] Initial identification of germline SETBP1 alterations affecting amino-acid residues between 858 and 871 have been described in patients with Schinzel–Giedion syndrome, associated with a congenital phenotype including mental retardation and facial deformities.[2] Recently, analysis of exome sequencing data from eight cases of atypical chronic myelogenous leukemia (aCML) led to the identification of recurrent somatic mutations involving SETBP1.[3] Mutational frequency was 24% among 70 patients with aCML, and 4% among 82 patients with chronic myelomonocytic leukemia (CMML). The investigators were not able to detect similar mutations among 106 patients with acute myeloid leukemia (AML), 100 with myelodysplastic syndromes (MDS), 42 with chronic myeloid leukemia, 33 with primary myelofibrosis (PMF), 42 with polycythemia vera and 36 with essential thrombocythemia.[3] A more recent study identified SETBP1 mutations with an overall prevalence of 3.2% in a total of 658 cases consisting of 195 patients with CMML, 222 with MDS and 241 with secondary acute myeloid leukemia (sAML). SETBP1 mutations were identified in 6.2% of CMML patients, 2.2% of MDS patients and 1.7% of patients with sAML.[4] In an effort to further investigate the prevalence and prognostic value of SETBP1 mutations in PMF and CMML, we studied a total of 415 patients with either PMF (n=236) or CMML (n=179). PCR and Sanger sequencing was used for mutation screening in PMF patients (forward primer 5′-ATGCACCCACTTTCAACACA-3′ and Reverse primer 5′-AAAAGGCACCTTTGTCATGG-3′ to generate sequence for amino-acid region 825–1013). For the CMML cohort, we used the ViiA7 quantitative RT-PCR platform (qPCR) and MeltDoctor high-resolution melting assay (Life Technologies, Grand Island, NY, USA) using forward primer 5′-GCGAGATTGGCTCCCTAAAG-3′ and reverse primer 5′-CCAGGGAGCAGAAATCAAAA-3′ to generate sequence for amino-acid region 860–1000. Targeted cases in the CMML cohort were validated using Sanger sequencing to confirm the presence of a mutation. Among the 236 patients with PMF (median age 63 years; 63% males), Dynamic International Prognostic Scoring System (DIPSS)-plus[5] risk distributions were high in 30%, intermediate-2 in 37%, intermediate-1 in 20% and low in 13%. Only six (2.5%) patients displayed SETBP1 mutations including three with D868N, two with G870S and one with I871T (Table 1). These mutations have all been previously described in other myeloid malignancies but not in PMF.[3] We found no significant correlations between the presence of SETBP1 mutations and age (P=0.74), sex (P=0.5), DIPSS-plus risk category (P=0.38), red cell transfusion need (P=0.3), hemoglobin <10 g/dl (P=0.34) or karyotype (P=0.48; three normal and three abnormal karyotype). SETBP1 mutations significantly correlated with higher leukocyte count (P=0.047), and borderline significance was seen with lower platelet count (P=0.08). Among 234 patients with concomitant JAK2V617F analysis, SETBP1 mutations were seen in 3 of 136 JAK2V617F-mutated and 3 of 98 unmutated cases (P=0.68). Table 1 outlines the patterns of concomitant mutations in other genes, including MPL, ASXL1, EZH2, SRSF2 and IDH, for all six SETBP1-mutated cases. Three of the six SETBP1-mutated patients were also screened for SF3B1 mutations and were all negative (P=0.61). At a median follow-up of 47 months, 129 (55%) deaths and 22 (9%) leukemic transformations were documented. Although the number of informative cases were too small to be definitive, the differences in either overall (hazard ratio (HR) 1.9; 95% confidence interval (CI) 0.7–5.2) or leukemia-free survival (HR 2.6; 95% CI 0.34–19.4) did not reach statistical significance.
Table 1

SETBP1 mutational frequency and distribution in PMF and CMML

SETBP1 mutationsPMFn=236CMMLn=179 
SETBP1 mutated6/236 (2.5%)8/179 (4.5%) 
D868N3/2365/179 
D868Y0/2361/179 
G870S2/2361/179 
I871T
1/236
1/179
 
SETBP1 with concomitant mutations
PMF
P-value
CMML
JAK2V617F mutated3/1360.68a
JAK2V617F unmutated3/98 
MPL0/6a
ASXL12/60.76/8
EZH20/60.52a
SRSF21/60.653/8
IDH0/60.6a
SF3B10/30.610/8
U2AF35aa2/8

Abbreviations: CMML, chronic myelomonocytic leukemia; PMF, primary myelofibrosis.

Not tested in this patient group.

Among the 179 study patients with CMML, median age was 70 years and 122 (68%) were males. Distribution of patients based on the Mayo CMML prognostic model were: 93 (52%) low risk, 45 (25%) intermediate risk and 41 (23%) high risk.[6] Eight (4.5%) patients with CMML displayed SETBP1 mutations. These included previously described mutations in seven patients (five with D868N, one with G870S and one with I871T) and a previously undescribed variant affecting amino-acid 868 (D868Y; Table 1). We found no significant correlations between the presence of SETBP1 mutations and age (P=0.4), sex (P=0.6), absolute monocyte count (P=0.77), hemoglobin (P=0.4), platelet count (P=0.34), bone marrow blasts (P=0.8), distribution across the Spanish cytogenetic risk stratification system (P=0.17),[7] MD Anderson prognostic scoring system (MDAPS) (P=0.19),[8] Mayo prognostic scoring system (P=0.65) and the global MDAPS (P=0.56).[9] SETBP1 mutations significantly correlated with higher circulating immature myeloid cells (P=0.03) and circulating blasts (P=0.032), and a borderline significance was noted for leukocyte count (P=0.08). SETBP1-mutated patients with CMML coexpressed mutations involving ASXL1 in six cases (75%), SRSF2 in three (38%), U2AF35 in two (25%) and SF3B1 in none; there was no statistically significant difference between SETBP1-mutated and unmutated cases in their coexpression frequencies. At a median follow-up of 17 months, 134 (75%) deaths and 24 (13%) leukemic transformations were documented. In univariate analysis, SETBP1 mutations were found to have a negative impact on overall survival (P=0.01, HR; 95% CI) (Figure 1). In multivariable analysis, SETBP1 mutations retained their negative prognostic impact against other parameters of prognostic importance that are listed in conventional prognostic models for CMML. Low number of events did not allow accurate statistical evaluation for leukemia-free survival.
Figure 1

Overall survival of 179 CMML patients stratified by SETBP1 mutational status.

Increased expression of SETBP1 has been reported occurring in 27% of patients with AML.[1] Similarly, increased expression of SETBP1 has been associated with decreased expression of SETBP1-embedded regulatory micro-RNA miR_4319 in a patient with PMF progressing to AML.[10] Accordingly, using published primer sets[11] and GAPDH controls, we measured levels of gene expression using qPCR and the SYBR green mastermix (Life Technologies) in 20 PMF patients who were studied for the presence of SETBP1 mutations, including 4 who harbored the mutation. SETBP1 expression levels in 19 of the 20 PMF patients were similar to normal controls (n=4) and the single patient with >5-fold increased expression of SETBP1 was wild-type for SETBP1. The role of SETBP1 in disease progression, including leukemic transformation, is currently poorly understood, although it was recently reported that constitutive expression of SETBP1 in an in vivo murine system may be involved in conferring self-renewal properties to leukemic stem cells.[12] Regardless, the strong prognostic value of the particular mutation in CMML, as suggested by the current study as well as that of Damm et al., raises the possibility of its incorporation into current prognostic models.
  12 in total

1.  De novo mutations of SETBP1 cause Schinzel-Giedion syndrome.

Authors:  Alexander Hoischen; Bregje W M van Bon; Christian Gilissen; Peer Arts; Bart van Lier; Marloes Steehouwer; Petra de Vries; Rick de Reuver; Nienke Wieskamp; Geert Mortier; Koen Devriendt; Marta Z Amorim; Nicole Revencu; Alexa Kidd; Mafalda Barbosa; Anne Turner; Janine Smith; Christina Oley; Alex Henderson; Ian M Hayes; Elizabeth M Thompson; Han G Brunner; Bert B A de Vries; Joris A Veltman
Journal:  Nat Genet       Date:  2010-05-02       Impact factor: 38.330

2.  Reduced expression by SETBP1 haploinsufficiency causes developmental and expressive language delay indicating a phenotype distinct from Schinzel-Giedion syndrome.

Authors:  Isabel Filges; Keiko Shimojima; Nobuhiko Okamoto; Benno Röthlisberger; Peter Weber; Andreas R Huber; Tsutomu Nishizawa; Alexandre N Datta; Peter Miny; Toshiyuki Yamamoto
Journal:  J Med Genet       Date:  2010-10-30       Impact factor: 6.318

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

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

4.  Cytogenetic risk stratification in chronic myelomonocytic leukemia.

Authors:  Esperanza Such; José Cervera; Dolors Costa; Francesc Solé; Teresa Vallespí; Elisa Luño; Rosa Collado; María J Calasanz; Jesús M Hernández-Rivas; Juan C Cigudosa; Benet Nomdedeu; Mar Mallo; Felix Carbonell; Javier Bueno; María T Ardanaz; Fernando Ramos; Mar Tormo; Reyes Sancho-Tello; Consuelo del Cañizo; Valle Gómez; Victor Marco; Blanca Xicoy; Santiago Bonanad; Carmen Pedro; Teresa Bernal; Guillermo F Sanz
Journal:  Haematologica       Date:  2010-11-25       Impact factor: 9.941

5.  Recurrent SETBP1 mutations in atypical chronic myeloid leukemia.

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

6.  SETBP1 overexpression is a novel leukemogenic mechanism that predicts adverse outcome in elderly patients with acute myeloid leukemia.

Authors:  Ion Cristóbal; Francisco J Blanco; Laura Garcia-Orti; Nerea Marcotegui; Carmen Vicente; José Rifon; Francisco J Novo; Eva Bandres; María J Calasanz; Carmelo Bernabeu; María D Odero
Journal:  Blood       Date:  2009-11-16       Impact factor: 22.113

7.  Mayo prognostic model for WHO-defined chronic myelomonocytic leukemia: ASXL1 and spliceosome component mutations and outcomes.

Authors:  M M Patnaik; E Padron; R R LaBorde; T L Lasho; C M Finke; C A Hanson; J M Hodnefield; R A Knudson; R P Ketterling; A Al-kali; A Pardanani; N A Ali; R S Komrokji; R S Komroji; A Tefferi
Journal:  Leukemia       Date:  2013-03-27       Impact factor: 11.528

8.  Proposal for a new risk model in myelodysplastic syndrome that accounts for events not considered in the original International Prognostic Scoring System.

Authors:  Hagop Kantarjian; Susan O'Brien; Farhad Ravandi; Jorge Cortes; Jianqin Shan; John M Bennett; Alan List; Pierre Fenaux; Guillermo Sanz; Jean-Pierre Issa; Emil J Freireich; Guillermo Garcia-Manero
Journal:  Cancer       Date:  2008-09-15       Impact factor: 6.860

9.  Setbp1 promotes the self-renewal of murine myeloid progenitors via activation of Hoxa9 and Hoxa10.

Authors:  Kevin Oakley; Yufen Han; Bandana A Vishwakarma; Su Chu; Ravi Bhatia; Kristbjorn O Gudmundsson; Jonathan Keller; Xiongfong Chen; Vasyl Vasko; Nancy A Jenkins; Neal G Copeland; Yang Du
Journal:  Blood       Date:  2012-05-07       Impact factor: 22.113

10.  SETBP1 and miR_4319 dysregulation in primary myelofibrosis progression to acute myeloid leukemia.

Authors:  Francesco Albano; Luisa Anelli; Antonella Zagaria; Nicoletta Coccaro; Paola Casieri; Angela Minervini; Giorgina Specchia
Journal:  J Hematol Oncol       Date:  2012-08-08       Impact factor: 17.388

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  42 in total

Review 1.  Somatic SETBP1 mutations in myeloid neoplasms.

Authors:  Hideki Makishima
Journal:  Int J Hematol       Date:  2017-04-26       Impact factor: 2.490

2.  I walk the line: how to tell MDS from other bone marrow failure conditions.

Authors:  Lukasz P Gondek; Amy E DeZern
Journal:  Curr Hematol Malig Rep       Date:  2014-12       Impact factor: 3.952

3.  Only SETBP1 hotspot mutations are associated with refractory disease in myeloid malignancies.

Authors:  Nils Winkelmann; Vivien Schäfer; Jenny Rinke; Alexander Kaiser; Philipp Ernst; Sebastian Scholl; Andreas Hochhaus; Thomas Ernst
Journal:  J Cancer Res Clin Oncol       Date:  2017-09-14       Impact factor: 4.553

4.  Exome sequencing identifies secondary mutations of SETBP1 and JAK3 in juvenile myelomonocytic leukemia.

Authors:  Hirotoshi Sakaguchi; Yusuke Okuno; Hideki Muramatsu; Kenichi Yoshida; Yuichi Shiraishi; Mariko Takahashi; Ayana Kon; Masashi Sanada; Kenichi Chiba; Hiroko Tanaka; Hideki Makishima; Xinan Wang; Yinyan Xu; Sayoko Doisaki; Asahito Hama; Koji Nakanishi; Yoshiyuki Takahashi; Nao Yoshida; Jaroslaw P Maciejewski; Satoru Miyano; Seishi Ogawa; Seiji Kojima
Journal:  Nat Genet       Date:  2013-07-07       Impact factor: 38.330

Review 5.  Chronic Myelomonocytic Leukemia: a Genetic and Clinical Update.

Authors:  Kristen B McCullough; Mrinal M Patnaik
Journal:  Curr Hematol Malig Rep       Date:  2015-09       Impact factor: 3.952

Review 6.  Chronic myelomonocytic leukemia: Forefront of the field in 2015.

Authors:  Christopher B Benton; Aziz Nazha; Naveen Pemmaraju; Guillermo Garcia-Manero
Journal:  Crit Rev Oncol Hematol       Date:  2015-03-14       Impact factor: 6.312

Review 7.  Chronic myelomonocytic leukemia: 2018 update on diagnosis, risk stratification and management.

Authors:  Mrinal M Patnaik; Ayalew Tefferi
Journal:  Am J Hematol       Date:  2018-06       Impact factor: 10.047

8.  Antagonism of SET using OP449 enhances the efficacy of tyrosine kinase inhibitors and overcomes drug resistance in myeloid leukemia.

Authors:  Anupriya Agarwal; Ryan J MacKenzie; Raffaella Pippa; Christopher A Eide; Jessica Oddo; Jeffrey W Tyner; Rosalie Sears; Michael P Vitek; María D Odero; Dale J Christensen; Brian J Druker
Journal:  Clin Cancer Res       Date:  2014-01-16       Impact factor: 12.531

9.  Neutrophilic leukocytosis in advanced stage polycythemia vera: hematopathologic features and prognostic implications.

Authors:  Leonardo Boiocchi; Umberto Gianelli; Alessandra Iurlo; Falko Fend; Irina Bonzheim; Daniele Cattaneo; Daniel M Knowles; Attilio Orazi
Journal:  Mod Pathol       Date:  2015-09-04       Impact factor: 7.842

10.  CSF3R T618I is a highly prevalent and specific mutation in chronic neutrophilic leukemia.

Authors:  A Pardanani; T L Lasho; R R Laborde; M Elliott; C A Hanson; R A Knudson; R P Ketterling; J E Maxson; J W Tyner; A Tefferi
Journal:  Leukemia       Date:  2013-04-22       Impact factor: 11.528

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