Identification of somatic mutations using whole-exome sequencing in Korean patients with acute myeloid leukemia
© The Author(s). 2017
Received: 24 January 2016
Accepted: 15 February 2017
Published: 1 March 2017
Acute myeloid leukemia (AML) is a biologically and clinically heterogeneous cancer of the bone marrow that is characterized by the rapid growth of abnormal myeloid cells.
We performed a mutational analysis to identify AML somatic mutations using the whole-exome sequencing data of 36 tumor-normal sample pairs from Korean patients with de novo AML. We explored the functional impact of the genes identified in the mutational analyses through an integrated Gene Ontology (GO) and pathway analysis.
A total of 11 genes, including NEFH (p = 6.27 × 10−13 and q = 1.18 × 10−8) and TMPRSS13 (p = 1.40 × 10−10 and q = 1.32 × 10−6), also demonstrated q values less than 0.1 in 36 Korean AML patients. Five out of the 11 novel genes have previously been reported to be associated with other cancers. Two gene mutations, CEBPA (p = 5.22 × 10−5) and ATXN3 (p = 9.75 × 10−4), showed statistical significance exclusively in the M2 and M3 subtypes of the French-American-British classifications, respectively. A total of 501 genes harbored 478 missense, 22 nonsense, 93 frameshift indels, and/or three stop codon deletions and these gene mutations significantly enriched GO terms for signal transduction (GO:0007165, p = 1.77 × 10−3), plasma membrane (GO:0005886, p = 3.07 × 10−4), and scaffold protein binding (GO:0097110, p = 8.65 × 10−4). The mitogen-activated protein kinase (hsa04010, 7.67 × 10−4) was the most enriched Kyoto Encyclopedia of Genes and Genomes pathway.
Morphological AML subtypes may in part reflect subtype specific patterns of genomic alterations. Following validation, future studies to evaluate the usefulness of these genes in genetic testing for the early diagnosis and prognostic prediction of AML patients would be worthwhile.
KeywordsAcute myeloid leukemia Gene ontology Pathway analysis Somatic mutation Subtype-specific mutation Whole-exome sequencing
Acute myeloid leukemia (AML) is a highly malignant cancer of the bone marrow that is characterized by the rapid growth of abnormal myeloid cells. In 2012, leukemia accounted for 2.5% and 3.2% of all new cancer cases and deaths worldwide, respectively . The incidence rate of leukemia increased from 4.7 to 5 cases per 10,000 Koreans from 1999–2010 . AML cytogenetic studies provide important diagnostic and prognostic information for AML patients. However, approximately 50% of AML patients have a normal karyotype (NK-AML). Although Schlenck et al. showed that the combination of the mutations in FLT and NPM1 or CCAAT/enhancer binding protein (C/EBP), alpha (CEBPA) could be used to predict NK-AML prognosis, most patients did not have this mutation set . This finding suggests that AML is a highly heterogeneous disease and that a large number of causal mutations have not yet been uncovered . Two systems, the French-American-British (FAB) classification and the newer World Health Organization (WHO) classification, have been used to classify AML into subtypes. To compare our results with the previous studies, we used the FAB system, the most commonly used classification in previous sequencing studies for AML, including The Cancer Genome Atlas (TCGA) whole genome sequencing (WGS) [5, 6]. AML is classified into eight subtypes (M0 through M7) according to the FAB classification based on its morphological features: early forms in white blood cells (M0-M5), red blood cells (M6), and platelets (M7) .
Next-generation sequencing technologies have extended AML genetic studies to a genome-wide scope at a single-base resolution. Ley et al. (2008) performed the first AML WGS study on one Caucasian woman with the cytogenetically normal AML subtype M1 and reported non-synonymous single nucleotide variants (nsSNVs) in eight genes (i.e., CDH24, PCLKC, GPR123, EBI2, PTPRT, KNDC1, SLC15A1, and GRINL1B) and insertions in the coding regions of the FLT3 and NPM1 genes . Mardis and his colleagues reported that 16% of 80 NK-AML patients had a somatic point mutation in the IDH1 gene . According to a later report by Ley et al. (2010), approximately 22% of 281 AML patients had DNMT3A mutations that were newly discovered using targeted sequencing . In a Chinese study using targeted exome sequencing, the patients with the DNMT3A Arg882 mutation showed poor prognosis among AML-M5 individuals . A WGS study with eight Caucasian AML patients showed clonal evolution patterns and mutations associated with relapsed AML in the genes WAC, SMC3, DIS3, DDX41, and DAXX . Recently, TCGA analyzed 50 and 150 patients with de novo AML using WGS and whole-exome sequencing (WES), respectively. They found 23 significantly mutated genes and 237 gene mutations that recurred in at least two patients, which were grouped into nine categories according to their biological functions .
AML is a clinically and genetically heterogeneous disease, hence discovering subtype-specific mutations may provide additional prognostic information for AML patients. In this study, we aimed to replicate previous findings in the European studies and to characterize the landscape of somatic mutations present in Korean acute myeloid leukemia. We also performed a stratified analysis for FAB M2- and M3-subtypes to investigate if certain mutations have subtype-specific effects. We subsequently evaluated the functional properties of the significantly mutated genes using an integrated systems analysis of Gene Ontology (GO) and biological pathways.
Patients and samples
We included 36 Korean patients with de novo AML who visited the Division of Hematology and Medical Oncology, Seoul National University Hospital, from 1995 to 2013 who had not received a bone marrow transplant prior to sampling. All subjects provided matched tumor-normal sample pairs that passed a DNA quality control (QC) test. The Institutional Review Board for Human Research at Seoul National University approved the study protocol (IRB number 1201-099-396), and all participants signed informed consent forms for WES. A clinician conducted a retrospective medical record review to obtain clinical data including disease status and blood chemistry. An approximately 10-mL bone marrow sample was aspirated from each participant by a clinician in an aseptic environment, and genomic DNA was isolated using the QIAamp DNA Blood Maxi Kit following the manufacturer’s instructions (Qiagen, Inc., Valencia, CA, USA). A 2-ml whole-saliva sample was obtained from the same individuals for the matched normal samples, and the genomic DNA was extracted using the Oragen DNA Self-Collection kit (DNA Genotek, Inc., Ontario, Canada).
We captured the target DNA sample using the Agilent SureSelect Human All Exon 50 Mb Kit (Agilent Technologies Inc., Santa Clara, CA, USA). The entire exome regions for both the tumor and normal samples from 36 AML patients were sequenced using the HiSeq 2000 platform with a 100 bp paired-end read protocol (Illumina, Inc. San Diego, CA, USA). Each the tumor and the normal sample were sequenced to an average read depth of 76X. The fastq quality score and read length cutoff determined by the NGS QC-toolkit were set to 20 and 70, respectively . We aligned the filtered reads to the reference assembly of human_g1k_v37 fasta using BWA-0.7.5  and called somatic SNVs using MuTect v1.1.4 according to the Catalogue of Somatic Mutations in Cancer (COSMIC) v68 database . We used Varscan v2.3.6 to call short indels . We obtained translational effect of variant allele, protein change information, mutation reports in Catalog of Somatic Mutations in Cancer, and predictions of coding non-synonymous variants on protein function using the Oncotator web application . Preliminary reports using six of 36 samples have been previously published elsewhere (Additional file 1: Table S1) [17–19].
We performed a mutation significance test using MutSigCV v1.4 with a significance threshold of a p value less than 0.05. The p value was calculated with the chi-square test to determine whether the observed mutations in a gene significantly exceeded the expected frequency of random background mutations. We additionally considered a q value less than 0.1, which was an analogue of the p value calculated based on the Benjamini-Hochberg false discovery rate (FDR) . To identify subtype-specific mutant genes, we performed the test individually in each of the subgroups as follows: M2-AML, acute myeloblastic leukemia with maturation, and M3-AML, acute promyelocytic leukemia. We screened for mutations that recurred in more than two patients with a p value less than 0.05 in any patient group. We categorized a mutant gene as a subtype-specific gene if the statistical significance of any one subgroup (i.e., M2 or M3) represented exclusively the significance of the total patient group. Finally, we systematically searched the PubMed database (www.ncbi.nlm.nih.gov/pubmed) to review previous studies on the relevance of the genes with p values less than 0.05 and q values less than 0.1 for AML and/or other cancers.
Gene set enrichment analysis and pathway analysis
To investigate the biological relevance of the mutations, we performed a GO enrichment analysis with the Database for Annotation, Visualization, and Integrated Discovery (DAVID 6.8 beta) . We categorized the function of these genes into three classes: ‘biological process’, ‘cellular components’, and ‘molecular function’. We also used the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (http://www.genome.jp/kegg/pathway.html) to identify pathways for the genes that were frequently mutated in AML cells .
Characteristics of the 36 acute myeloid leukemia patients
AML (n = 36)
Age, mean (SE)
Absolute neutrophil count × 103/mm3, mean (SE)
Bone marrow blast (%), mean (SE)
White blood cell count × 103/mm3, Mean (SE)
Platelet count × 103/mm3, Mean (SE)
Overall survival time (months), mean (SE)
Genes identified through mutational analysis in AML in the total, M2, and M3 subtype patient groups
Type of variant (patients, n)
AML (p < 0.01 and q < 0.10)
In Frame Ins(6)/Del(4)
6.27 × 10-13c
1.18 × 10−8
In Frame Del(6), Missense(5)
1.40 × 10-10c
1.32 × 10−6
In Frame Ins(5), Missense(1)
5.07 × 10-8c
3.19 × 10−4
Frame Shift Ins(1)/Del(4)
1.50 × 10-7c
7.09 × 10−4
Intron SNV(1), In Frame Del(5), Silent(1)
3.62 × 10-7c
1.37 × 10−3
In Frame Ins(3)
6.88 × 10-6c
Intron SNV(1), Frame Shift Del(6), 3′UTR Ins(7)/Del(1)
8.50 × 10-6c
Missense(1), In Frame Del(5)
8.88 × 10-6c
In Frame Del(3)
2.09 × 10−5
Intron Ins(2)/Del(2), In Frame Del(4)
2.93 × 10−5
In Frame Ins(2)/Del(4), Silent(3), Intron Del(1)
3.33 × 10−5
AML-M2 (p < 0.01)
In Frame Ins(3)
5.22 × 10−5
Intron Del(1), In Frame Ins(4)/Del(1)
3.45 × 10−4
AML-M3 (p < 0.01)
In Frame Ins(2), Intron Ins(1)
9.75 × 10−4
Subtype-specific somatic mutations
Pathways and biological processes
We identified total of 501 genes harbored 478 missense, 22 nonsense, 93 frameshift indels, and/or three stop codon deletions. We performed GO and KEGG pathway enrichment analyses with the input consisted of the 501 genes. The GO analysis demonstrated that 43 mutated genes could contribute to AML tumorigenesis through the biological processes such as signal transduction (p = 1.77 × 10−3, Fold Enrichment = 1.63). In terms of cellular components, the plasma membrane showed the most significant alteration (p = 3.07 × 10−4, Fold Enrichment = 1.32). Scaffold protein binding was the most significantly altered molecular function (p = 8.65 × 10−4, Fold Enrichment = 6.18). To investigate the pathway-level relationship of the mutated genes, we performed a pathway analysis in the KEGG database (Additional file 1: Table S3). Mitogen-activated protein kinase signaling (p = 7.67 × 10−4, Fold Enrichment = 2.50) and long-term potentiation (p = 2.40 × 10−3, Fold Enrichment = 4.28) pathways were significantly altered in AML.
A total of 11 genes were significantly mutated in 36 AML patients (p < 0.01 and q < 0.1). Specifically, NEFH, hepatitis A virus cellular receptor 1 (HAVCR1, 5q33.2), interferon, alpha-inducible protein 27 (IFI27, 14q32), PCSK5, and the arylsulfatase D gene (ARSD, Xp22.3) have been implicated in a variety of cancers. For instance, the variants of NEFH gene, a tumor suppressor, were suggested as prognostic markers for renal cell carcinoma (RCC) and contributed to susceptibility of esophageal squamous cell and hepatocellular carcinomas [24, 36]. While overexpression of this gene interrupts the development of cell structure and function in normal cells , loss-of-function mutations in this gene activate the Akt/β-catenin pathway and cause increased glycolysis and result in mitochondrial dysfunction in cancer cells . The transmembrane protease, serine 13 gene (TMPRSS13, 11q23), a splice variant of mosaic serine protease large form (MSPL), encodes a family of the type II transmembrane serine proteases which plays critical roles in maintaining homeostasis, infection, and tumorigenesis [38, 39]. The HAVCR1 gene is a biomarker for diagnosing renal cell, ovarian, and colorectal carcinoma [25, 40]. Especially, elevated expression of this gene prevents cancer cell invasion and adhesion in colorectal cancer cells . IFI27, the most highly up-regulated gene in human whole blood, is related with immune response through activation of T lymphocytes and dendritic cells . Furthermore, this gene induces the interferon-alpha and stimulates myeloid dendritic cells . The proprotein convertases (PCs) play important roles in development and metastasis of multiple cancers. The PCSK5 gene (also known as PC5 or PC6) has been reported to be systematically down-regulated in intestinal tumors of the knockout mouse model and human .
The protein encoded by the ARSD gene located on X chromosome is a member of the sulfatase family, which is an essential element for skeletal and cartilage growth. The elevated expression of this protein was suggested to be associated with lipid metabolism such as sphingolipid and development of chronic lymphocytic leukemia . A cluster of Mastermind-like (MAML) genes, including MAML1, MAML2, and MAML3, encodes transcriptional co-activators for various signal pathways such as Notch signaling and tumor suppressor pathway activated in multiple cancers . Specifically, the MAML3 gene regulates the retinoic acid gene, which inhibits growth of human tumor cells . We identified four novel genes, KRTAP4-5, OR2T35, GPRIN1, and MRPL18, of unknown function in tumor progression and metastasis.
The genes mutated exclusively in the patients with the AML subtypes M2 and M3 have been reported more frequently in previous studies to have an association with AML and/or other types of cancers than the genes identified in the total AML patient group. For instance, previous NGS studies for AML evaluated the prognostic impact of the gene CEBPA in AML patients [6, 32]. This gene had the lowest p value in the AML M2 group in the current study. The high proportion of M2-patients in the study subjects may have affected the results of previous studies. The E1A binding protein p400 (EP400, 12q24.33) was reported to be associated with cancers such as RCC and colorectal cancer. All three genes specific to the M3 subtype (ATXN3, thymine-DNA glycosylase (TDG, 12q24.1), and HCLS) also showed possible associations with cancer risks, such as B-cell chronic lymphocytic leukemia (B-CLL).
Gene set enrichment analysis showed that MAPK signaling pathway was significantly enriched in the 36 Korean AMLs. MAPKs play important role in converting extracellular stimuli into cellular responses and are often altered in cancers . The genomic region, Chromosome 11:117789342–117789345, harbor five missense mutations leading to protein changes, p.A77G and p.Q78R, of transmembrane serine proteases that is known to function in tumorigenesis . We additionally investigated the clinical features of patients who share the same recurrent mutations, including age, absolute neutrophil count, bone marrow blast percentage, white blood cell count, platelet count, and overall survival time, however there were no specific clinical features observed among them.
In this study, we replicated multiple gene mutations reported by previous European studies in Korean patients. We also discovered novel genes significantly mutated in AMLs and some mutated genes that showed subtype-specific patterns of mutations. The effects of novel genes and subtype-specific somatic mutations in AML warrant further validation in larger cohorts. Following validation, it would be worthwhile in future studies to evaluate the usefulness of these genes in genetic testing for the early diagnosis and prediction of the prognosis of AML patients.
Acute myeloid leukemia
AML with an abnormal karyotype
Acute promyelocytic leukemia
Cox proportional hazards regression
False discovery rate
Integrative genomics viewer
INO80 complex subunit
Juvenile myelomonocytic leukemia
Mitogen-activated protein kinase
Next-generation sequencing technologies
AML with a normal karyotype
Non-synonymous single nucleotide variants
The Cancer Genome Atlas Research Network
White blood cells
Whole genome sequencing
The authors thank all participants who donated samples and the staff members who were involved in this research. We especially acknowledge the contributions of Young Ki Lee (Syntekabio, Inc., Republic of Korea) who worked on NGS data generation, and Eun Pyo Hong (Hallym University College of Medicine, Republic of Korea) who contributed to the evaluation of the functional importance of the gene mutations.
This research was supported by grant of the Korea Health Industry Development Institute (KHIDI) of the Ministry of Health & Welfare (HI14C0072) and the National Research Foundation (NRF) of the Ministry of Education (2014R1A1A3053168), Republic of Korea.
Availability of data and materials
The data that support the findings are available in this published article and its supplementary information files; and the datasets analysed during the current study are available from the corresponding author on reasonable request.
PJW have made substantial contribution to design of the work, interpretation of data, writing the manuscript and revising it critically for important intellectual content. HSG and KJK participated in the analysis and interpretation of data and drafting the manuscript. KY and YS participated in the study design, data acquisition, and clinical data evaluation. KHL contributed to the design of the study. JJS oversaw generation of sequencing data and participated in writing of the manuscript. All co-authors approved the final version of the manuscript for publication.
The authors declare that they have no competing interests.
Consent for publication
Ethics approval and consent to participate
The Institutional Review Board for Human Research at Seoul National University approved the study protocol (IRB number 1201-099-396), and all participants signed informed consent forms.
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