Whole exome sequencing identifies a novel somatic mutation in MMP8 associated with a t(1;22)-acute megakaryoblastic leukemia

Abstract

Letter to the Editor Acute myeloid leukemia (AML) is a clonal hematopoietic disease caused by both inherited and acquired genetic alterations. Conventional cytogenetic analysis reveals chromosomal aberrations in about 50% of AML cases. These chromosomal rearrangements promote leukemia by affecting cell proliferation, differentiation, and/or survival. In addition to these genetic alterations, cooperating mutations are required for leukemogenesis (1–3). Among subtypes of AML, pediatric acute megakaryoblastic leukemia (AMKL) is primarily associated with three cytogenetic subtypes: one with trisomy 21 plus mutation of GATA1, one with the t(1;22) translocation (4, 5), and a third recently reported recurrent cryptic inversion of chromosome 16 (inv(16)(p13.3q24.3)) (6, 7). AMKL with t(1;22) is typically an aggressive disease, presenting in early infancy with a median survival of just 8 months. Translocation between chromosomes 1p13 and 22q13 results in the fusion gene, RBM15-MKL1. The mechanism(s) by which the fusion protein promotes leukemia is unknown. RBM15-MKL1 knock-in mice develop AMKL, but with delayed onset (16–18 months) and incomplete penetrance (8). Induced RBM15-MKL1 overexpression in cell lines causes cell death (9). Together, these findings suggest that RBM15-MKL1 requires cooperating mutations to induce AMKL. To identify potential cooperating mutations in t(1;22) AMKL, we performed whole exome capture followed by next-generation sequencing in diagnostic and remission samples from a t(1;22)-AMKL patient. An 11 week-old boy presented with loss of appetite and fussiness. Samples of bone marrow and peripheral blood were obtained at presentation. Morphological and immunophenotypic analyses were performed at the UC Davis Pathology Department according to standard protocols. FISH and cytogenetic analyses were performed by the Mayo Clinic Laboratory (Children’s Oncology Group designated laboratory). The remaining diagnostic sample was frozen. The blood had a white blood cell count (WBC) of 38,000/mm3, hemoglobin of 6.1g/dL, and platelet count of 99,000/mm3. The peripheral blood smear showed immature blast cells (18% of WBC). Bone marrow examination revealed severe fibrosis (Figure 1A, B). Peripheral blood immunophenotyping showed 15% leukemic blasts based on CD45 expression and SSC profile. These cells expressed CD33 (75%), CD34 (44%), CD41 (63%) and CD61 (79%) and cytogenetic analyses showed 46,XY,t(1;22)(p13;q13) (Figure 1C). Based on the fibrotic marrow, megakaryocytic markers, and translocation, the diagnosis of AMKL was assigned. He responded very well to the treatment with cytarabine, etoposide, daunorubicin, mitoxantrone, L-asparaginase, and Gemtuzumab, the Children’s Oncology Group AAML0531 protocol. Because he did not have an HLA matched family donor, he did not undergo allogeneic hematopoietic stem cell transplantation. He is currently disease free 4 years after completing therapy. Peripheral blood was collected and cryopreserved 6 and 9 months after remission was achieved. The quality of extracted genomic DNA from the fixed cells of the diagnostic sample using the Gentra Puregen kit (Qiagen) was highly comparable to that of freshly thawed peripheral blood of the remission sample (A260/280 = 1.89 vs. 1.86, leukemia and remission, respectively) and no difference in quality was seen in the further analyses, including exome capture, PCR amplification, and sequencing. To delineate the breakpoints on chromosomes 1 and 22, PCR was performed as described (5). Multiplex PCR was performed with combinations of primers (as shown in Figure 1D) to narrow down the breakpoint region. When single primer pairs were then used for individual PCR reactions, no amplification occurred with OTT4 and In4.1-3, but 0.5 kb and 2.2 kb products were amplified with OTT4 and In4.4 and In4.5, respectively (Figure 1E) confirming that the translocation occurred between chromosome 1 and 22 with the breakpoint in intron 1 of OTT and intron 4 of MKL1. To identify potential cooperating mutations in this patient sample, exome capture followed by deep sequencing was performed on the leukemia and remission blood samples from the patient. A total of 88,807,512 and 79,716,978 reads were obtained from the leukemic and remission samples, respectively (Supplementary Table S2). Picard software identified and removed PCR duplicates (14.0% of the leukemia and 9.4% of the blood sample). About 96% of the remaining unique reads from both samples mapped to only one location in the genome with ~ 94% of targeted bases with >10× coverage (Table S2). Varscan identified 97,926 single nucleotide variations (SNVs) with a minimum variant frequency in the sample of >0.02 and minimum average quality score >20. Of these variants, 22,326 were called somatic variations, which were filtered to require <0.2 p-value that the SNV was different in leukemia vs. remission, leaving 4,580. Of the 4,580 SNV, 2,123 were in genic regions and 95.3% were classified as coding variants, with 75.2% being non-synonymous. SIFT predicted 36.0% and 62.9% of the coding variants as damaging and tolerated variations, respectively (Supplementary Table 3). Of 1,956 coding variants, 1,876 were novel SNPs based on dbSNP. Of the 1,956, 377 SNVs remained after further filtering to require <0.05 p-value and damaging/tolerated SIFT predictions, and to exclude known dbSNPs. To overcome the low blast purity (15% of cells), we used a less stringent filter to maximize the chance of detecting variations within the leukemic cells, which resulted in false positive variants from the initial analysis. Therefore, it was necessary to carefully inspect the reads manually using IGV. After the manual inspection of the 377 SNVs for base quality displayed in the Integrated Genomics Viewer (IGV v2.1,(10)), we found 12 variants to be likely candidates and performed further validation for these 12 variants (Table 1). Neither known AML-associated mutations nor mutations in tumor suppressor genes were found. However, small indels would not be detectable in our data due to the low blast percentage. To validate the candidate mutations, Sanger sequencing was performed, but proved to be technically challenging due to the low percentage of blasts. By Sanger sequencing, the expected peak for the variant alleles was not distinguishable except for one in HERC2, which proved to exist in both the leukemic and remission samples at approximately 50%, suggesting a unique SNP in the patient (data not shown). To improve the sensitivity, 10 of the remaining 11 variants were further validated with ddPCR (1 failed in assay design due to repetitive sequences and high GC content). Despite multiple repetitions and assessment using modified primer pairs, of the 10 variants assessed using ddPCR, only MMP8 was validated (Supplementary Figure S1), while the other 9 variants were not detectable in the leukemic sample (Table 1). Given that, for example, a candidate mutation with 7% frequency was found in CDK9 using exome sequencing, we had hypothesized that this was a heterozygous mutation in the leukemic blasts. However, this was not validated with ddPCR even after analysis of over 14,000 molecules of this region from the diagnostic DNA sample (Supplementary Figure S1). While CDK9 is known to play a role in megakaryocyte maturation and to regulate both the cell cycle and transcription, further inspection of the exome data showed that the sequence quality was low at the mutant bases. Other unvalidated variant calls had low number of mutant reads, low mutant base quality, or possible mapping problems. The ddPCR validation demonstrated that more stringent p-value, mutant base quality and read number filtration is necessary when analyzing challenging low blast % samples. The MMP8 mutation in our patient sample, a substitution from C to T on chr11:102592188, resulted in amino acid change MMP8G189D. This mutation is predicted to be damaging and deleterious by SIFT and PROVEAN (11, 12), respectively. This region is universally conserved in all vertebrates except elephant and frog (http://genome.uscs.edu/, (13)). MMP8 encodes matrix metalloproteinase-8, which breaks down type I, II and III collagens in the extracellular matrix, and requires both calcium and zinc ions for activity (14). The variation is located at a calcium ion binding site in the catalytic domain (Figure S2). To determine the effect of this mutation on enzymatic activity, we generated constructs containing either wild-type or mutant MMP8 and expressed them in HEK 293T cells. No difference was observed in expression level between the constructs (Figure 1F). Type 1 collagen substrate gel zymography revealed significantly reduced proteolytic activity of the mutant compared to wildtype MMP8 (Figure 1G and H, p-value=0.017). To further assess whether MMP8 may play a role in AMKL leukemogenesis, we evaluated MMP8 expression in primary AMKL samples. Although RNA was not available from this case, gene expression data from 41 pediatric AML cases including 16 cases of AMKL demonstrated 8 of the 16 AMKL cases to have detectable MMP8 expression (Figure S3) (7). All AMKL samples in this study had >90% purity, an important consideration given that MMP8 is known to be highly expressed in mature myeloid cells. Transcriptome sequencing was available for 14 of these AMKL cases and the sample with the highest signal by exon array also had significant levels of the MMP8 transcript by sequencing. In an independent cohort of 60 AMKL cases also analyzed by gene expression profiling, a subset of patients had evidence of MMP8 expression (15). While the purity of these samples was extremely variable (12–94%), several samples with low purity (M7122, 12%; M7026, 28%) had low levels of MMP8 expression demonstrating that the variability in MMP8 expression cannot solely be due to myeloid cell contamination. Furthermore, there are cases with elevated expression that are relatively pure (M7040, 70%; M7072, 90%). Although the same mutation was not found in any of the samples, MMP8 is aberrantly expressed in a subset of AMKL cases. In addition, MMP8 mRNA is expressed in murine megakaryocyte-erythroid progenitors based on the ENCODE database (GSE40522). Given that MMP8 was the only candidate gene with 14% variation frequency in the exome sequencing, the patient had few cooperating mutations in coding regions, which might explain the excellent response to treatment and survival. In conclusion, we provide the first data identifying a novel somatic mutation that may provide a key insight to understanding the pathogenesis of RBM15-MKL1 in AMKL. Supplementary Material 1 2 3