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Functional variant (−1304T>G) in the MKK4 promoter is associated with decreased risk of acute myeloid leukemia in a southern Chinese population

Authors

  • Lan Jiang,

    1. Soochow University Laboratory of Cancer Molecular Genetics, Cyrus Tang Hematology Center, Department of Hematology, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou
    2. Thrombosis and Hemostasis Key Laboratory of the Ministry of Health, Soochow University, Suzhou
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    • These authors contributed equally to this work.

  • Ping Zhou,

    1. The Third Hospital Affiliated to Nantong University, Wuxi
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    • These authors contributed equally to this work.

  • Aining Sun,

    1. Soochow University Laboratory of Cancer Molecular Genetics, Cyrus Tang Hematology Center, Department of Hematology, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou
    2. Thrombosis and Hemostasis Key Laboratory of the Ministry of Health, Soochow University, Suzhou
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    • These authors contributed equally to this work.

  • Jian Zheng,

    1. Soochow University Laboratory of Cancer Molecular Genetics, Cyrus Tang Hematology Center, Department of Hematology, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou
    2. Thrombosis and Hemostasis Key Laboratory of the Ministry of Health, Soochow University, Suzhou
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  • Bin Liu,

    1. The No. 12 Hospital of Guangzhou, Guangzhou, China
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  • Yonghe You,

    1. Soochow University Laboratory of Cancer Molecular Genetics, Cyrus Tang Hematology Center, Department of Hematology, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou
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  • Chun Zhang,

    1. The Third Hospital Affiliated to Nantong University, Wuxi
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  • Depei Wu,

    1. Soochow University Laboratory of Cancer Molecular Genetics, Cyrus Tang Hematology Center, Department of Hematology, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou
    2. Thrombosis and Hemostasis Key Laboratory of the Ministry of Health, Soochow University, Suzhou
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  • Yifeng Zhou

    Corresponding author
    1. Soochow University Laboratory of Cancer Molecular Genetics, Cyrus Tang Hematology Center, Department of Hematology, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou
    2. Thrombosis and Hemostasis Key Laboratory of the Ministry of Health, Soochow University, Suzhou
      To whom correspondence should be addressed. E-mail: zhouyifeng@suda.edu.cn
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To whom correspondence should be addressed. E-mail: zhouyifeng@suda.edu.cn

Abstract

As a member of the MAPK kinase family, mitogen-activated protein kinase kinase (MKK) 4 (NM_003010.2) is know to be involved in the regulation of apoptosis, inflammation, and tumorigenesis. Several polymorphisms have been identified in the promoter region of the MKK4 gene and we hypothesized that genetic variations in this region may alter gene expression, and thus cancer risk. In the present study, we genotyped two polymorphisms in the promoter of the MKK4 gene, namely −1304T>G (rs3826392) and −1044A>T (rs3809728), in 433 patients with AML and 600 controls, and assessed the association between those polymorphisms and the risk of AML. Compared with the −1304TT genotype, patients with the −1304TG genotype had a significantly decreased risk of AML (adjusted odds ratio (OR) 0.67; 95% confidence interval (CI) 0.51−0.87), with the risk decreased even further in those carrying −1304GG (OR 0.56; 95% CI 0.31–0.97). Additional experiments, which focused on reporter gene expression driven by MKK4 promoters, demonstrated that the presence of a −1304G allele led to greater transcriptional activity than the presence of a −1304T allele. However, no significant association was observed between the MKK4−1044A>T polymorphism and the risk of AML. These findings suggest that the functional −1304G>T variant may contribute to the risk of AML by enhancing the transcriptional activity of MKK4. Thus, this polymorphism may be a genetic modifier for the development of AML. (Cancer Sci 2011; 102: 1462–1468)

As the name suggests, AML is a cancer of the myeloid line of blood cells. It is characterized by the rapid growth of abnormal white blood cells, which accumulate in the bone marrow, thus interfering with the production of normal blood cells, and is the most common acute leukemia affecting adults. The incidence of AML increases with age: the median age at diagnosis is 63 years and its incidence is approximately 10-fold greater in people >65 years of age than in those <65 years of age.(1) The incidence of AML is slightly greater in men than in women, with a male:female ratio of 1.3:1.(2) Epidemiological studies have established many etiologic factors for AML, including other blood disorders,(3) chemical exposure,(4,5) ionizing radiation,(6) and genetics.(7) Of these, chemical exposure and ionizing radiation are both cell stressors and are capable of activating MAPK pathways, which are known to participate in the regulation of apoptosis, inflammation, and tumorigenesis.(8)

At least three distinct MAPK signaling pathways have been identified, namely the ERK, p38 kinase, and JNK pathways.(9) All MAPK family members are activated by the phosphorylation of threonine and tyrosine residues within a TXY motif, which is catalysed by the single dual-specificity kinase MAPK kinase (MKK). Two upstream MKK, namely MKK4 and MKK7, are responsible for the phosphorylation and activation of JNK.(9,10) When it is overexpressed in mammalian cells, as well as under in vitro conditions, MKK4 can also phosphorylate and activate different p38 MAPKs, such as p38a, p38b, SAPK3 (p38g) and SAPK4 (p38d).(9)

The MKK4 gene, also known as JNKK1, has been mapped to chromosome 17p11.2 (NM_003010.2). The gene is over 120 kb in size, contains 11 exons, and encodes a 399-amino acid protein in humans.(9,11) It has been found that MKK4 is of vital importance in tumor formation and development because it may act as a tumor suppressor gene.(12–14) It is known that the promoter region determines the transcriptional activity of a gene, so genetic variations in the promoter region may affect gene function. Furthermore, environmental factors that possible contribute to the induction of different cancers, including AML, may cause gene mutations in the promoter region.(8) Therefore, in the present study, we evaluated the hypothesis that polymorphisms in the promoter region of the MMK4 gene are associated with the risk of AML. Four common single nucleotide polymorphisms (SNP; those with a minor allele frequency [MAF] >5%) have been found in the 1.6-kb promoter region of MKK4 according to the GenBank dbSNP database: −1304T>G (rs3826392), −1044A>T (rs3809728), −641C>G (rs2190853), −84T>C (rs9892151). Because Wei et al.(8) had proved, in a Chinese population, that −1044A>T, −641C>G, and −84T>C were in complete linkage disequilibrium (LD) with each other. If −1044 A>T is associated with AML risk, so will the other two sites, conversely, if there is no association between −1044A>T and AML risk, −641C>G and −84T>C will not have association with AML either. So, the selection of −1044A>T is enough for −641C>G and −84T>C.

In the present hospital-based case-control study, we investigated the association between two MKK4 polymorphisms, namely −1304T>G (dbSNP ID: rs3826392) and −1044A>T (dbSNP ID: rs3809728), and the risk of AML. Moreover, we analyzed the correlation between the −1304T>G polymorphism and MKK4 mRNA levels in AML bone marrow. Recombinant reporter plasmids containing −1304T>G and −1044A>T were also constructed to determine their effect on MKK4 gene expression.

Materials and Methods

Study subjects.  The present study included 433 AML patients and 600 healthy controls. All subjects were ethnically homogeneous Han Chinese. Patients with newly diagnosed AML were recruited consecutively from March 2001 to May 2010 at the First Affiliate Hospital of Soochow University (Suzhou, China). All eligible patients diagnosed at the hospital during the study period were invited to participate in the study, with 91% agreeing to do so. There were no restrictions in terms of age, stage of disease, or histology preventing people from participating in the study. The population controls consisted of cancer-free people living in the Suzhou region. Control subjects were selected from a nutritional survey conducted over the same period as the cases were collected.(15,16) The selection criteria for control subjects included no history of cancer and the control population was matched in terms of age and sex with the AML patient group. At the time of recruitment, informed consent was obtained from each subject. This study was approved by the Medical Ethics Committee of The First Affiliate Hospital of Soochow University.

Genotyping analysis.  Genomic DNA was extracted from a 5-mL bone marrow sample, which was obtained from patients before they were given chemotherapy or radiotherapy to avoid any influence of these treatments on outcomes. Genotypes were analyzed using PCR-based methods as described below. Genotyping was performed without knowledge of the subject’s case or control status. A 30% masked random sample of cases and controls was tested twice by different people, and the results were concordant for all masked duplicate sets.

We developed a PCR-RFLP method to determine AML-associated MKK4 polymorphisms. The primer pair designed to amplify the target DNA fragment containing the −1304T>G (rs3826392) polymorphism was 5′-CTT GTT CCA AAC CCA ATT TC-3′ (forward) and 5′-GGG CTA C TG ATT TCC AGA TG-3′ (reverse), which produced a 232-bp fragment. Similarly, the primer pair designed for −1044A>T (rs3809728) was 5′-CTA CGA TTT GTA AGC CAA CCA-3′(forward) and 5′-CCA ACA TGC TGT GAA GAA CTC-3′ (reverse), which produced a 235-bp fragment. The PCR was performed in a 25-μL reaction system containing 5 mM MgCl2, 0.1 mM dNTPs, 3.0 units Taq polymerase and the manufacturer’s buffer (Fermentas, Burlington, VT, Canada). The PCR procedure consisted of an initial melting step at 94°C for 5 min, followed by 35 cycles of 94°C for 45 s, annealing at 58°C for −1304T>G and 60°C for −1044A/T for 45 s and 72°C for 45 s, with a final extension step at 72°C for 7 min. A native endonuclease AflII (Fermentas) site was present in the amplified fragment containing the −1304G>T (rs3826392) polymorphism. After digestion by AflII at 37°C for at least 3 h, the major G allele produced a single 232-bp band, whereas the minor C allele produced two bands (111 and 121 bp). The two bands could be separated easily by 3% agarose gel electrophoresis. The amplified fragment containing the −1044A>T (rs3809728) polymorphism could be cut using Tsp509I (Fermentas) at 65°C for at least 3 h. After digestion, the major A allele produced two bands (129 and106 bp), whereas the minor T allele produced a single 235-bp band. The genotype identification by PCR-RFLP was confirmed by DNA sequencing (Figs 1,2).

Figure 1.

 (a) Representative PCR-RFLP for different genotypes containing the −1304G>T polymorphism site. M, DNA size marker; lanes 1, 3, 4, 5, TT genotype; lanes 2, 7, TG genotype; lane 6, GG genotype. (b) DNA sequencing analysis. The PCR products with different PCR-RFLP profiles were sequenced to confirm the genotypes.

Figure 2.

 (a) Representative PCR-RFLP for different genotypes containing the −1044A>T polymorphism site. M, DNA size marker; lane 1, TT genotype; lanes 2, 4, 5, 6, AA genotype; lanes 3, 7, AT genotype. (b) DNA sequencing analysis. The PCR products with different PCR-RFLP profiles were sequenced to confirm the genotypes.

Construction of reporter plasmids.  Because the MKK4−1304T>G polymorphism was found to be associated with a significantly decreased risk of AML, we then determined whether this polymorphism had an effect on MKK4 gene expression in vitro. The T allelic reporter constructs were prepared by amplifying the 1612-bp MKK4 promoter region (from −1528 to +84 bp relative to the translation start site) from subjects homozygous for the T allele (−1304TT), including the artificial KpnI and HindIII enzyme restriction sites with a forward primer of 5′-gccggtacctaatctgtagtgctgcttcta-3′ and a reverse primer of 5′-tggaagcttcgccggggaccctacggggc-3′. The amplified fragments were then cleaved with the KpnI and HindIII enzymes (New England BioLabs, Ipswich, MA, USA). The pGL3 basic vector (Promega, Madison, WI, USA) was also cleaved with the KpnI and HindIII enzymes, and the fragments and pGL3 basic vector were then ligated by T4 DNA ligase (New England BioLabs). The p1304T–1044T, p1304G–1044A, and p1304G–1044T reporter constructs were obtained from the p1304T–1044A constructs by site-directed mutagenesis using the QuikChange site-directed mutagenesis kit (Stratagene, La Jolla, CA, USA). All constructs were sequenced to confirm the allele, orientation, and integrity of each insert.

Transient transfections and luciferase assays.  Three different cell lines, namely HL-60 (AML-M2 origin), NB4 (AML-M3 origin) and SHI-1 (AML-M5b origin) (China Center for Type Culture Collection, Wuhan University, Hubei, China), were grown in RPMI 1640, supplemented with 10% (v/v) heat-inactivated FCS, 2 mM l-glutamine, 100 units/mL penicillin, and 100 units/mL streptomycin at 37°C and 5% CO2 in a humidified incubator for 2 days. For transient transfection experiments, 5 × 104 cells were plated in 10-mm 24-multiwell plates and grown to 60–70% confluence. Transfection was performed using Lipofectamine Reagent (Life Technologies, Rockville, MD, USA) according to the manufacturer’s instructions. Cells were cotransfected with 0.5 μg reporter plasmid and 0.1 μg pRL-SV40 (Luciferase Assay System; Promega); the latter was used to standardize transfection efficiency.

Luciferase activity was determined using a luciferase assay system (Promega) according to the manufacturer’s instructions. Briefly, cells were scraped into lysis reagent, transferred to microfuge tubes and centrifuged for 30 s at 12 000g. Luciferase activity was measured using a manual luminometer (TD20/20; Turner Designs, Sunnyvale, CA, USA) after mixing 100 μL luciferase assay reagent with 20 μL of 1:10 diluted cell lysate. Measurements for each sample were recorded three times at 10-s intervals. Three independent transfection experiments were performed for each plasmid construct, and each experiment was performed in triplicate. Results are expressed as luciferase activity as a ratio of pRL-SV40.

Real-time analysis of MKK4 mRNA.  Bone marrow samples were obtained from 41 AML patients recruited consecutively over the period February 2008–April 2010 at the First Affiliate Hospital of Soochow University (Suzhou, China). Samples were placed immediately in liquid nitrogen and stored at −80°C until analysis. Total RNA was isolated from bone marrow using TRIzol reagent (Molecular Research Center, Cincinnati, OH, USA). A 2-μg aliquot of total RNA from each specimen was reverse transcribed into single-strand cDNA using oligo primer and SuperscriptII (Invitrogen, Carlsbad, CA, USA). Relative gene expression of MKK4 was determined using β-actin as an internal standard and the ABI Prism 7000 sequence detection system (Applied Biosystems, Foster City, CA, USA) based on the SYBR green method. The primers pairs used in the present study were as follows: for MKK4, 5′-aac aac act ggg att tca ct-3′ (forward) and 5′-tca cta ctc cgc att act aca-3′ (reverse); and for β-actin, 5′-ggc ggc acc acc atg tac cct-3′ (forward) and 5′-agg ggc cgg act cgt cat act-3′ (reverse). The PCR reaction mixture (final volume 20 μL) contained 0.1 μM each primer, 10 μl 1× SYBR Premix EX Taq premix reagent (Perfect Real Time, Takara, Dalian, China), and 50 ng cDNA. The cycling conditions consisted of 95°C for 2 min, followed by 40 cycles of 95°C for 15 s and 60°C for 1 min. Expression of MKK4 in individual samples was normalized against that of β-actin using a modification of the method described by Lehmann and Kreip.(17) All analyses were performed in a blinded fashion, with laboratory personnel unaware of the genotyping results.

Statistical analysis.  Two-sided χ2 tests were used to assess differences in the distribution of age and sex between AML patients and controls, as well as between alleles and genotypes. Hardy–Weinberg equilibrium (HWE) was assessed using a goodness-of-fit χ2 test to compare expected genotype frequencies with the observed genotype frequency (p2 + 2pq + q2 = 1). Associations between the status of the control subjects and each SNP were estimated using an unconditional logistic regression model, with adjustment for age and sex. Logistic regression modeling was also used for the trend test.

Data were further stratified by age, sex, karyotype, and lineage to evaluate the variable-related odds ratios (OR) among the various MKK4 genotypes. Homogeneity within different variable-related ORs levels was tested. Potential multiplicative and additive interactions among gene–gene and gene–environmental factors were also evaluated using logistic regression analysis. The 2LD program and the PROC ALLELE statistical procedure in SAS/Genetics (SAS Institute, Cary, NC, USA) were used to detect the LD of two SNPs. Statistical power was calculated using PS Software (http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/PowerSampleSize, accessed Dec 14, 2010). All tests were two sided and analyses were performed using SAS (version 9.1; SAS Institute). < 0.05 was considered significant.

Results

Characteristics of the study population.  Selected characteristics of AML patients and controls are summarized in Table 1. The average age of patients and controls was 43 and 42 years, respectively (= 0.347). Similarly, there were no significant difference in the proportion of men and women within each of the two groups (= 0.855).

Table 1.   Characteristics of the AML patients and control subjects from the Chinese populations used for the association study
 AML patients (= 433)Control subjects (= 600)
  1. Data show the number of subjects in each group, with percentages given in parentheses.

No. of men240 (55.4)336 (56.0)
No. of women193 (44.6)264 (44.0)
Age at diagnosis (years)
 2047 (10.9)60 (10.0)
 21–40149 (34.4)223 (37.2)
 41–60155 (35.8)220 (36.7)
 ≥6182 (18.9)97 (16.2)
Lineage
 Myeloid308 (71.1) 
 Myeloid and lymphoid118 (27.3) 
 Myeloid and monocytic7 (1.6) 
Classification of diagnosis
 M01 (0.2) 
 M182 (18.9) 
 M2118 (27.3) 
 M373 (16.9) 
 M437 (8.5) 
 M568 (15.7) 
 Unknown54 (12.5) 
Karyotype
 Aberrant207 (47.8) 
 Normal176 (40.6) 
 Unknown50 (11.5) 

MKK4 genotypes and risk of AML.  The genotyping results are given Table 2. The allele frequencies for rs3826392G and rs3809728A were 0.267 and 0.814, respectively, in the control group and 0.204 and 0.800, respectively, in AML patients. The observed genotype frequencies of rs3826392 and rs3809728 polymorphisms in both controls and patients did not deviate from those expected based on HWE (χ2 = 1.003, d.f. = 1, = 0.316 for rs3826392; and χ2 = 1.247, d.f. = 1, = 0.264 for rs3809728).

Table 2.   Genotype frequencies of the two single nucleotide polymorphisms in the MKK4 gene in patients and controls and their associations with AML
 Control subjects (= 600)AML (= 433)OR† (95% CI)P value‡
  1. Unless indicated otherwise, data show the number of subjects in each group, with percentages given in parentheses. OR, odds ratio; CI, confidence interval. †Data were calculated by unconditional logistic regression and adjusted for sex and age status. ‡P values for χ2 analysis or Fisher’s exact test.

−1304G>T
 Genotype
  TT318 (53.0)274 (63.3)1.00 (Reference)0.00097
  GT244 (40.7)141 (32.6)0.67 (0.51–0.87)
  GG38 (6.3)18 (4.1)0.56 (0.31–0.97)
 Allele
  T880 (73.3)689 (79.6)1.00 (Reference)0.001
  G320 (26.7)177 (20.4)0.71 (0.57–0.87)
−1044A>T
 Genotype
  AA402 (67.0)285 (65.8)1.00 (Reference)0.444
  TA173 (28.8)123 (28.4)1.01 (0.76–1.32)
  TT25 (4.2)25 (5.8)1.41 (0.79–2.49)
 Allele
  A977 (81.4)693 (80.0)1.00 (Reference)0.427
  T223 (18.6)173 (20.0)0.91 (0.73–1.14)

The frequencies for the −1304GG, GT, and TT genotypes in AML patients differed significantly from those in the control group (Ptrend = 0.00097). Relative to the −1304GG genotype, −1304GT and −1304TT were both associated with a significantly decreased risk of AML, with an OR of 0.56 (95% confidence interval [CI] = 0.31–0.97) and 0.67 (95% CI = 0.67–0.87), respectively. However, the difference in genotype frequencies at the rs3809728A>T site between AML patients and the control group was not significant (Ptrend = 0.444).

In the control group, LD analysis revealed that the linkage between two loci was relatively weak (D′ = 0.296; r2 = 0.065), suggesting that each may have an independent effect on the risk of AML.

Stratification analysis of MKK4−1304 T>G genotypes and risk of AML.  The risk of AML related to MKK4 genotype was further examined with stratification according to age, sex, lineage, and karyotype. However, as indicated in Table 3, there was no significant association between age, sex, lineage, and karyotype and these two polymorphisms.

Table 3.   Stratification analysis of the MKK4 gene −1304G>T (rs3826392) genotypes by selected variables in AML patients and control subjects
 Patients (= 433)Controls (= 600)Adjusted OR (95% CI)†P value‡
TTGG + GTTTGG + GTCG + CC vs GG
  1. Unless indicated otherwise, data show the number of subjects in each group, with percentages given in parentheses. † Odds ratios (OR) were adjusted for sex and age in a logistic regression model. ‡P values are to test for homogeneity for ORs of MKK4-1304T>G SNP among different strata. CI, confidence interval.

Age (years)
 ≤40125 (28.9)71 (16.4)156 (26.0)127 (21.2)0.71 (0.47–1.05)0.64
 >40149 (34.4)88 (20.3)162 (27.0)155 (25.8)0.62 (0.41–0.86)
Sex
 Male150 (34.7)90 (20.8)171 (28.5)165 (27.5)0.60 (0.44–0.89)0.65
 Female124 (28.6)69 (15.9)147 (24.5)117 (19.5)0.73 (0.45–1.04)
Karyotype
 Aberrant138 (31.9)69 (15.9)318 (53.0)282 (47.0)0.51 (0.37–0.78)0.32
 Normal103 (23.8)73 (16.9)318 (53.0)282 (47.0)0.81 (0.55–1.12)
 Unknown33 (7.6)17 (3.9)318 (53.0)282 (47.0)0.59 (0.30–1.11)
Lineage
 Myeloid190 (43.9)118 (27.2)318 (53.0)282 (47.0)0.72 (0.52–0.93)0.27
 Myeloid and lymphoid77 (17.8)41(9.5)318 (53.0)282 (47.0)0.60 (0.38–0.92)
 Myeloid and monocytic7 (1.6)0 (0.0)318 (53.0)282 (47.0)0.08 (0.01–1.32)

Effects of the MKK4−1304T>G polymorphism on transcriptional activity in AML cell lines.  To determine the transcriptional activity of the native MKK4 promoter in AML cells, two luciferase reporter gene constructs were generated by PCR, spanning −1528 to +84 bp of the MKK4 promoter region, with a T/G or A/T at the −1304 or −1044 polymorphic sites. These constructs were used to transiently transfect three AML cell lines (i.e. HL-60, NB4, and SHI-1 cells). As shown in Fig. 3, we found that −1304G-containing MKK4 promoter resulted in an approximate 1.8–3-fold increase in reporter expression compared with the −1304T-containing promoter in the HL-60, NB4, and SHI-1 cell lines.

Figure 3.

 Transient reporter gene expression assays with constructs containing a full-length MKK4 promoter. (a) Schematic of the reporter gene constructs having a full-length MKK4 promoter. The only difference between the four constructs is a T>G or A>T at the −1304 and −1044 polymorphic sites. (b) Luciferase expression of four constructs in HL-60, NB4, and SHI-1 cells cotransfected with pRL-SV40 to standardize transfection efficiency. Luciferase levels of pGL-3 Basic and pRL-SV40 were determined in triplicate and standardized for transfection efficiency. Fold increases were determined by defining the activity of the empty pGL-3 Basic vector as 1. Data shown are the mean ± SD fold increase from three independent transfection experiments, each performed in triplicate. (□), p1304T–1044T; (bsl00001), p1304G–1044A; (bsl00023), p1304T–1044A; (bsl00025), p1304G–1044T.

Effects of the MKK4−1304T>G SNP on MKK4 mRNA levels.  The effects of the −1304T>G SNP on MKK4 expression were examined by real-time PCR evaluation of MKK4 mRNA in individual samples of AML bone marrow. The results revealed that MKK4 mRNA levels (normalized against β-actin) were significantly greater in patients with the −1304TG and −1304GG genotypes compared with levels in patients with the −1304TT genotype (mean [±SD] expression 0.104 ± 0.043, 0.205 ± 0.133, and 0.064 ± 0.022, respectively; < 0.001; Fig. 4.

Figure 4.

 Expression of MKK4 mRNA in bone marrow samples of individuals who carry different genotypes for the (a) −1304T>G and (b) −1044A>T polymorphisms.

Discussion

In the present study investigating 433 AML patients and 600 cancer-free controls, we found that the −1304G>T polymorphism in the promoter region of MKK4 was associated with the risk of developing AML. The risk of developing AML decreased as the number of −1304G alleles increased. Moreover, we found that the −1304G variant allele significantly increased the transcriptional activity of the MKK4 gene compared with the −1304T allele, both in vitro and in vivo. However, there was no significant difference in the susceptibility to AML between different genotypes of the −1044A>T locus.

All the findings in the present study of the genotyping, real-time PCR, and transient transfection experiments suggest a tumor suppressor role for MKK4. This suppressor function is supported by results from other studies. For example, homozygous deletion of MKK4 that eliminates its coding portions has been identified in pancreatic carcinoma cell lines and lung carcinoma cell lines.(10) Ganiatsas et al.(18) have reported that loss-of-function mutations in the MKK4 gene are present in approximately 5% of tumors from various human tissues. Moreover, MKK4 has been identified as a suppressor of the metastasis of prostate and ovarian cancers,(19,20) and the lack of expression of MKK4 in resected gastric adenocarcinoma was found to be highly associated with poor survival.(21) However, the role of MKK4 in cancer is complex, because several studies have also suggested a pro-oncogenic role for MKK4.(22–25)

In recent years, it has been established that the MAPK signaling pathways play crucial roles in the pathogenesis of various hematologic malignancies.(26) In a recent study, biochemical analysis of 67 primary adult AML patients demonstrated a correlation between the constitutive activity of JNK in leukemic blasts and treatment failure in AML.(27) Importantly, a relationship between JNK activity and increased multidrug resistance-associated protein efflux was also observed.(27) So far, no report has directly demonstrated a role for constitutive activation of the p38 MAPK pathway in the pathophysiology of AML. However, a recent study has shown that p38 and its downstream effector MAPK-activated protein kinase 2 (MAPKAPK2) were activated during treatment of the NB-4 acute promyelocytic leukemia cell line with all-trans retinoic acid (ATRA).(28) Conversely, the MEK inhibitor PD98059 was found to block the induction of differentiation of NB-4 cells(29) and HL-60 cells(30) in response to ATRA. Other studies have shown that, under certain circumstances, the p38 pathway can cooperate with the ERK pathway to mediate cytokine-induced proliferation of AML cells.(31) In summary, the JNK and p38 MAPK pathways both play a functional role in the pathogenesis and pathophysiology of AML. Because MKK4 is a direct activator of both JNK and p38, we hypothesized that dysfunction caused by MKK4 mutations may possibly affect susceptibility to the development of AML. Our hypothesis was supported by the results of our genotyping, real-time PCR, and transient transfection experiments. The present study is the only study thus far to investigate the association between MKK4 mutations and/or expression and susceptibility to AML.

Few studies have investigated the MKK4−1304T>G polymorphism, so only three studies, including our present study, can provide a comparison for the tested frequencies of the allele and genotypes. Wei et al.(8) found that, 723 Chinese control subjects, the frequency of the TT, TG, and GG alleles was 53.8%, 40.8%, and 5.4%, respectively. Similarly, in another study of lung cancer in 1056 controls, the frequency of the TT, TG, and GG alleles was 57.3%, 35.9%, and 6.8%, respectively.(32) These values are similar to the frequency of 53.0%, 40.7%, and 6.3% for the TT, TG, and GG alleles, respectively, determined in the 600 control subjects in the present study. The corresponding figures for these genotypes in the HapMap database (http://hapmap.ncbi.nlm.nih.gov/, accessed Jan 2, 2011; HapMap Genome Browser #27 (Phase 1, 2 and 3–merged genotypes and frequencies) are 63.1%, 33.3%, and 3.6% in 84 Chinese; 74.4%, 23.3%, and 2.3% in 86 Japanese; 54.0%, 41.6%, and 4.4% in 113 European descendents; and 17.0%, 42.9%, and 40.2% in 112 Africans. These data suggest that the role of the MKK4−1304T>G polymorphism in cancer risk may vary with ethnicity, a possibility that warrants further investigation.

Although we found that the MKK4−1304GG/GT genotypes were associated with a decreased risk of AML, our study may have certain limitations because of its design. Selection bias and/or systematic errors may have occurred because the AML patients recruited to the study were recruited from those attending hospital, whereas the control subjects were recruited from the community. Furthermore, some factors that may interact with genotype or act as potential confounders in the analysis, such as information regarding minimal residual disease, were not available in the present case control study. Other limitations may be related to the fact that the present study was a hospital-based case control study that was restricted to a Chinese Han population. However, the genotype frequencies observed in the control group were in agreement with the Hardy–Weinberg disequilibrium law, suggesting that our subject sampling was sufficiently random. We also achieved over 90% study power (two-sided test, α = 0.05) in detecting an OR of 0.65 for the −1304GG + GT genotypes (which occurred at a frequency of 47.0% in the control group), relative to the −1304TT genotype. This evidence suggests that our findings are sound and of note.

In conclusion, the present study indicates that, in the Chinese population, carriers of the −1304GG and GT genotypes have a decreased risk of AML compared with carriers of the MKK4−1304TT genotype. To the best of our knowledge, the present study is the first to demonstrate a significant association between the MKK4−1304G>T polymorphism and the risk of developing AML. Larger, and preferably population-based, case control studies, as well as well-designed mechanistic studies, are warranted to validate our findings.

Acknowledgments

This study was supported in part by the National Natural Scientific Foundation of China (81001278 and 81072366) and the Suzhou Science and Technology Agency (SYS201052). The authors thank Drs Jianying Liang and Mengxing Xue (Department of Hematology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China) for their assistance in recruiting the subjects.

Disclosure Statement

The authors have no conflicts of interest to declare.

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