Mutations In SETBP1 Occur In 3.1% Of De Novo AML and Show a Distinct Genetic Pattern That Highly Resembles Atypical CML
Authors: Meggendorfer Manja , Alpermann Tamara , Sirch Elisabeth , Haferlach Claudia , Kern Wolfgang , Haferlach Torsten , Schnittger Susanne 
Published: October 2019

Introduction

Recently, mutations in SETBP1 (SETBP1mut) have been identified in different myeloid malignancies. We previously determined mutation frequencies in the range of 5-10% in MPN and MDS/MPN overlap, while we found SETBP1 more frequently mutated in atypical CML (32%). SETBP1mut has been shown to associate with CBL and ASXL1 mutations, as well as the cytogenetic abnormalities -7 and i(17)(q10). While SETBP1 mutations have been detected in 3% of s-AML cases, so far no mutations of SETBP1 in de novo AML have been described.

Aim

To analyze the mutation frequency of SETBP1 mutations in de novo AML with corresponding cytogenetic abnormalities and their respective correlation to clinical data and other gene mutations.

Patients and Methods

We investigated 422 adult de novo AML patients, diagnosed by cytomorphology, immunophenotyping and genetic studies following WHO classification. SETBP1 was analyzed by Sanger sequencing of the coding region for amino acids 800 to 935. The cohort comprised 229 males and 193 females, the median age was 65.8 years (range: 19.3 – 89.0). Cytogenetics was available in all 422 cases. Based on the previously described association of SETBP1mut with -7 and i(17)(q10) in other myeloid malignancies there was a selection bias to these karyotypes. Cases were grouped according to cytogenetic abnormalities: normal karyotype (n=88) and aberrant karyotype (n=334), i.e. i(17)(q10) (n=15), +14 (n=20), -7 (n=100), other abnormalities (n=129), and complex karyotype (n=114; 44 contained i(17)(q10), +14 or -7). Within the SETBP1mut cases the following molecular markers were analyzed: ASXL1, CBL, CEBPA, FLT3-ITD, FLT3-TKD, IDH1/2, KRAS, NRAS, NPM1, MLL-PTD, RUNX1, SRSF2, TP53 and WT1 by Sanger sequencing, next generation sequencing, gene scan or melting curve analyses. These data were also available in sub-cohorts of SETBP1 negative cases.

Results

In the total cohort mutations in SETBP1 were detected in 3.1% (13/422) of all cases. SETBP1mut patients were older (median age: 73.5 vs. 65.7 years; p=0.05) and showed a slightly higher white blood cell count (14.5 vs. 13.8x109/L; p<0.001). There was no correlation to gender, hemoglobin level and platelet count. However, analyzing the cytogenetic groups SETBP1mut showed, like in other myeloid malignancies, a strong co-occurrence with -7 and i(17)(q10), since 4/13 SETBP1 positive cases carried a monosomy 7, and 7/13 an i(17)(q10). The two remaining cases showed a trisomy 14 or a complex karyotype that also contained a i(17)(q10). No SETBP1mut was found in any other cytogenetic subgroup. Therefore, SETBP1mut correlated significantly with i(17)(q10) (8/15 i(17)(q10) were SETBP1mut vs. 5/407 in all other karyotypes; p<0.001). Further, we analyzed the association of SETBP1 mutations with other molecular markers. SETBP1mut correlated with ASXL1mut, 9/33 (27%) ASXL1mut patients showed a mutation in SETBP1, while only 2 (1%) showed a SETBP1 mutation in 229 ASXL1 wild type (wt) patients (p<0.001). This was also true for CBLmut, where 4/8 (50%) CBLmut cases were SETBP1mut, while only 8/158 (5%) were SETBP1mut in the group of CBLwt (p=0.001). This was even more prominent in SRSF2mut patients, where all 9 SRSF2mut were also SETBP1mut, while only 4/8 (50%) patients carried a SETBP1 mutation within the SRSF2wt group (p=0.029). In contrast, SETBP1mut were mutually exclusive of mutations in TP53 (0/67 in TP53mut vs. 12/194 in TP53wt; p=0.04), possibly reflecting the exclusiveness of TP53mut in i(17)(q10) patients. There was no correlation to any other analyzed gene mutation. Remarkably, while there was a high coincidence of SETBP1mut, SRSF2mut (9/13) and ASXL1mut (9/11), none of these patients showed mutations in the typical AML markers NPM1, FLT3-ITD, CEBPA, MLL-PTD, or WT1. Comparing the mutational loads of SETBP1, ASXL1 and SRSF2 resulted in SRSF2 having in most cases the highest mutational loads (range: 30-70%) while ASXL1 and SETBP1 showed equal or lower mutational loads (15-50% and 10-50%, respectively), possibly indicating that SRSF2 mutation is a former event followed by ASXL1 and SETBP1 mutation.

Conclusions

1) For the first time we describe, that SETBP1 mutations occur in de novo AML. 2) SETBP1 mutations are correlated with a distinct genetic pattern with high association to i(17)(q10), ASXL1 and SRSF2 mutations and are mutually exclusive of TP53mut. 3) Thus, the genetic pattern of SETBP1 mutated AML highly resembles that of atypical CML.

Disclosures:

Meggendorfer: MLL Munich Leukemia Laboratory: Employment. Alpermann:MLL Munich Leukemia Laboratory: Employment. Sirch:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.