- Open Access
Metallothionein III (MT3) is a putative tumor suppressor gene that is frequently inactivated in pediatric acute myeloid leukemia by promoter hypermethylation
- Yan-Fang Tao†1,
- Li-Xiao Xu†1,
- Jun Lu1,
- Lan Cao1,
- Zhi-Heng Li1,
- Shao-Yan Hu1,
- Na-Na Wang1,
- Xiao-Juan Du2,
- Li-Chao Sun3,
- Wen-Li Zhao1,
- Pei-Fang Xiao1,
- Fang Fang1,
- Yan-Hong Li1,
- Gang Li1,
- He Zhao1,
- Yi-Ping Li1,
- Yun-Yun Xu1,
- Jian Ni4,
- Jian Wang1,
- Xing Feng1Email author and
- Jian Pan1Email author
© Tao et al.; licensee BioMed Central Ltd. 2014
- Received: 29 April 2014
- Accepted: 20 June 2014
- Published: 25 June 2014
Acute myeloid leukemia (AML) is the second most common form of leukemia in children. Aberrant DNA methylation patterns are a characteristic feature in various tumors, including AML. Metallothionein III (MT3) is a tumor suppresser reported to show promoter hypermethylated in various cancers. However, the expression and molecular function of MT3 in pediatric AML is unclear.
Eleven human leukemia cell lines and 41 pediatric AML samples and 20 NBM/ITP (Norma bone marrow/Idiopathic thrombocytopenic purpura) control samples were analyzed. Transcription levels of MT3 were evaluated by semi-quantitative and real-time PCR. MT3 methylation status was determined by methylation specific PCR (MSP) and bisulfite genomic sequencing (BSG). The molecular mechanism of MT3 was investigated by apoptosis assays and PCR array analysis.
The MT3 promoter was hypermethylated in leukemia cell lines. More CpG’s methylated of MT3 was observed 39.0% pediatric AML samples compared to 10.0% NBM controls. Transcription of MT3 was also significantly decreased in AML samples compared to NBM/ITP controls (P < 0.001); patients with methylated MT3 exhibited lower levels of MT3 expression compared to those with unmethylated MT3 (P = 0.049). After transfection with MT3 lentivirus, proliferation was significantly inhibited in AML cells in a dose-dependent manner (P < 0.05). Annexin V assay showed that apoptosis was significantly upregulated MT3-overexpressing AML cells compared to controls. Real-time PCR array analysis revealed 34 dysregulated genes that may be implicated in MT3 overexpression and apoptosis in AML, including FOXO1.
MT3 may be a putative tumor suppressor gene in pediatric AML. Epigenetic inactivation of MT3 via promoter hypermethylation was observed in both AML cell lines and pediatric AML samples. Overexpression of MT3 may inhibit proliferation and induce apoptosis in AML cells. FOXO1 was dysregulated in MT3-overexpressing cells, offering an insight into the mechanism of MT3-induced apoptosis. However, further research is required to determine the underlying molecular details.
- Metallothionein III
- Pediatric acute myeloid leukemia
- Tumor suppressor
Acute myeloid leukemia (AML) is a type of cancer in the myeloid cell. It is the most common form of acute leukemia in adults and the second most common form of leukemia in children after acute lymphoblastic leukemia (ALL) [1, 2].The incidence of AML increases with age and is characterized by the rapid growth of abnormal white blood cells which accumulate in the bone marrow and interfere with the production of normal blood cells .
DNA methylation is an important regulator of gene transcription. It is an epigenetic modification that typically occurs at CpG (cytosine-phosphate-guanine) sites in mamalian cells. It is catalyzed by DNA methyltransferase which results in the conversion of the cytosine residue to 5-methylcytosine, leading to the formation of Me-CpG . Alterations in DNA methylation frequently occur during cell development and are common in tumors. Aberrant DNA methylation patterns have been reported in a variety of cancers including AML [5, 6]. Hypermethylation within the promoter regions of tumor suppressor genes leads to gene silencing, and global hypomethylation has also been recognized as a cause of oncogenesis [7, 8]. As such, the role of methylation in carcinogenesis has been the focus of considerable research. However, the mechanisms leading to aberrant DNA methylation are poorly understood.
Genome-wide studies have been performed to obtain details on the genome and epigenome in various solid tumors. Examination of clonal evolution patterns have suggested that these may shape epigenetic dysregulation in AML. Investigations on genome-wide methylation in AML have shown variations in methylation patterns between AML and normal healthy tissues [9–11]. Although several studies have found that molecular subtypes in AML can exhibit highly distinct DNA methylation profiles [12, 13], a small set of common genes have also been shown to exhibit consistent aberrant methylation across several hundred cases of AML [14, 15], such as PML-RARα and AML1-ETO[12, 13, 16]. Together, these findings implicate distinct aberrant DNA methylation patterns in the pathogenetic processes in cancer, rather than evolving homogeneously across cancer types,
Deep sequencing of patients with different myeloid malignancies has revealed recurrent mutations in epigenetic regulator proteins, such as DNMT3A and TET2, and several major driver mutations in normal karyotype AML [17, 18]. Functional studies of these mutations have revealed specific methylation signatures. These mutations carry prognostic relevance and are likely to be contributors to AML pathogenesis.
Metallothionein (MT) is a family of cysteine-rich, low molecular weight (500–14,000 Da) proteins . Ten functional isoforms of MTs have been identified, which are divided into four classes (MT1–4) based on small differences in protein sequences and characteristics. MTs have been proposed to play important roles in protecting against DNA damage, apoptosis and oxidative stress. MT3 was first identified as a neuronal growth inhibitory factor . In vitro studies have demonstrated that MT3 can inhibit neurite formation and survival in neurons . It has been shown to protect against apoptotic neuronal death in the brains of patients with Alzheimer’s disease and in the hippocampus of SAMP8 mice, suggesting that MT3 may inhibit the development of neurodegeneration and may influence neuronal regeneration during the recovery process [21, 22]. Its endogenous overexpression in glial and tumor cells stably transfected with MT3 was found to inhibit cell growth. In addition, MT3 plays a role in regulating lysosomal functions; in the absence of MT3, reductions in specific lysosomal enzymes associated with decreased autophagic flux have been reported .
In relation to cancer, downregulation of MT3 has been reported as one of 17 changes in gene expression which are associated with metastasis and poor clinical outcome in a range of solid tumors, including gastric cancer  and primary esophageal squamous cell carcinoma (SCC) . This was supported by the observation that treatment with 5-aza-2'-deoxycytidine, an inhibitor of DNA methylation reduced the degree of methylation and increase the level of MT3 expression, in esophageal SCC cell lines . Significant downregulation of MT3 has been most frequently reported in tumors that exhibiting MT3 methylation, suggesting that MT3 may act as a tumor suppresser via promoter hypermethylation .
However, reports on the methylation status of MT3 in the blood system are rare, and its expression and role in pediatric AML remains unclear. The aim of this study was to analyze the methylation profile and molecular function of MT3 in pediatric AML.
Leukemia cell lines HL-60, MV4-11, U937, DAMI and K562 were obtained from the American Type Culture Collection (ATCC). CCRF, Raji, Jurkat, 697 and SHI-1 cell lines (gifts from Professor Wang Jian-Rong, The Cyrus Tang Hematology center of Soochow University). All cell lines were maintained at 37°C in the RPMI 1640 (GibcoR, Life Technologies, Carlsbad, CA) supplemented with 10% fetal bovine serum (Invitrogen, Life Technologies, Carlsbad, CA).
Patients and samples
Correlation between MT3 methylation status and clinicopathological features in pediatric AML patients
Clinical and pathologic features
Methylated (n = 16)
Unmethylated (n = 25)
Total patients (n = 41)
Gender (male/female ratio)
WBC: median; range (109/L)
Hemoglobin: median; range (g/L)
Platelet count: median; range (109/L)
FAB subtype (n = number of patients)
CD34 + cell purification
For CD34 +cell selection, the Miltenyi immunoaffinity device (VarioMACS 130-046-703) was used according to the manufacturer’s instructions (Miltenyi Biotech, Auburn, CA). Briefly, the CD34+ cells are magnetically labeled with CD34 MicroBeads. Then, the cell suspension is loaded onto a MACSR Column which is placed in the magnetic field of a MACS Separator. The magnetically labeled CD34+ cells are retained within the column. The unlabeled cells run through; CD34+ cells were adsorbed on the magnetic poles. After removing the column from the magnetic field, the magnetically retained CD34+ cells can be eluted as the positively selected cell fraction.
Sodium bisulfite modification of genomic DNA
High-molecular-weight genomic DNA was extracted from cell lines and biopsies by a conventional phenol/chloroform method. The sodium bisulphite modification procedure was as described  with slight modification. In brief, 600 ng of genomic DNA was denatured in 3 M NaOH for 15 min at 37°C, then mixed with 2 volumes of 2% low-melting-point agarose. Agarose/DNA mixtures were then pipetted into chilled mineral oil to form agarose beads. Aliquots of 200 μl of 5 M bisulphite solution (2.5 M sodium metabisulphite, 100 mM hydroquinone, both Sigma, USA) were added into each tube containing a single bead. The bisulphite reaction was then carried out by incubating the reaction mixture for 4 h at 50°C in the dark. Treatments were stopped by equilibration against 1 ml of TE buffer, followed by desulphonation in 500 μl of 0.2 M NaOH. Finally, the beads were washed with 1 ml of TE buffer and directly used for PCR.
The methylation status of the MT-3 promoter region was determined by methylation-specific PCR. Primers distinguishing unmethylated (U) and methylated (M) alleles were designed to amplify the sequence:
MT-3 M-forward: 5- TTAAGCGTATAAACGGAAAGAGC -3;
MT-3 M-reverse: 5- AAAACAAATCTCAAAATCCATATCG -3;
MT-3 U-forward: 5- TTTAAGTGTATAAATGGAAAGAGTGG -3;
MT-3 U-reverse: 5- AACAAATCTCAAAATCCATATCAAA -3.
Each PCR reaction contained 20 ng of sodium bisulphite-modified DNA, 250 pmol of each primer, 250 pmol deoxynucleoside triphosphate, 1 × PCR buffer, and one unit of ExTaq HS polymerase (Takara, Tokyo) in a final reaction volume of 20 μl. Cycling conditions were initial denaturation at 95°C for 3 min, 40 cycles of 94°C for 30 s, 60°C (M) or 58°C (U) for 30 s, and 72°C for 30 s. For each set of methylation-specific PCR reactions, in vitro-methylated genomic DNA treated with sodium bisulphite served as a positive methylation control. PCR products were separated on 4% agarose gels, stained with ethidium bromide and visualized under UV illumination. For cases with borderline results, PCR analyses were repeated.
Bisulfite genomic sequencing
Bisulfite genomic sequencing (BGS) was performed as previously described . BGS primers were from +427 to +672 including 15 CpGs. MT-3 F: 5- AGGGAGATTTGGTATTTTATTTTTT-3 and MT-3 R: 5- ACCTAACTATCTCTCCACATCCTAC-3. Amplified BGS products were TA-cloned; and five to six randomly chosen colonies were sequenced. DNA sequences were analyzed with QUMA Analyzer. (http://quma.cdb.riken.jp/).
Leukemia cell cells treated with 5-aza-2'-deoxycytidine
De-methylation was induced with 5-aza-dC (5-Aza, Sigma-Aldrich, St Louis, MO, USA) treatment at a concentration that induced de-methylation of the DNA without killing the cells. Culture media for HL-60 and MV4-11 cells contained 5 μM 5-Aza. DNA and RNA were extracted after 72 hours of 5-Aza treatment for the following analysis.
Quantitative reverse-transcription PCR for MT-3
Quantitative real-time PCR was performed to determine the expression levels of MT-3 genes. Total RNA was reverse transcribed using the Reverse Transcription Kit, according to the manufacturer’s protocol (Applied Biosystems Inc., Foster City, CA). The real time PCR primers used to quantify GAPDH expression were: F: 5′-AGAAGGCTGGGGCTCATTTG-3′ and R: 5′-AGGGGCCATCCACAGTCTTC-3′ and for MT-3 were: F: 5′-ACACACAGTCCTTGGCACAC-3′ and R: 5′-AAGTGCGAGGGATGCAAAT-3′. Expression of MT-3 was normalized to endogenous GAPDH expression.
MT-3 lentiviral expression constructs and lentivirus production
Briefly, an approximately 250 bp fragment containing the human MT-3 gene was directly synthesized, and cloned into the pMD18-T vector. Positive clones were confirmed by sequencing and subcloned into the pLVX-IRES-ZsGreen vector (Clontech). The vector plasmids, pLVX-IRES-ZsGreen1, pLP1, pLP2 and pLP/VSVG were amplified in E.Coli and purified using the Endofree Maxiprep Kit (Qiagen). 270 μg of transfer vector, 176 μg of pLP1, 95 μg of pLP/VSVG and 68 μg of pLP2 was mixed with 0.25 M CaCl2 (Sigma) and added to same volume of 2 × HEPES (Sigma) and mixed while bubbling for 20 min to allow a precipitate to form. This was then added to a 175 cm2 flask of approximately 60% confluent 293 T cells containing 20 mL DMEM supplemented with 10% fetal calf serum, 100 U/mL penicillin, 100 μg/mL streptomycin and 2 mM glutamine and incubated for 48 h at 37°C in 5% CO2. The supernatant was centrifuged at 1,700 g for 10 min to pellet cell debris, and ultracentrifuged at 121,603 g for 2 h. The pellet containing concentrated virus was resuspended in DMEM without supplements and stored at -80°C.
Cell proliferation analysis
Acute myeloid leukemia cells were seeded in 96-well plates at 2 × 104 cells per well. 20 ul CCK-8(Dojindo Molecular Technologies, Japan) was added to each well and incubated at 37°C for a further 4 hours. The optical density (OD) values were measured at 450 nm on a scanning multi-well spectrophotometer (BioRad Model 550, USA). Compared with the control group, Cell proliferation was calculated as proliferation values. All experiments were performed in triplicate and repeated twice. The results were analyzed using ANOVA and the Student-Newman-Keuls tests, p < 0.05 were considered significant.
Apoptosis assay was according to the manual operation of BD Annexin V Staining Kit (Cat: 556420, BD Biosciences, Franklin Lakes and NJ USA). Briefly, wash cells twice with cold PBS and then resuspend cells in 1 × Binding Buffer at a concentration of ~1 × 106 cells/ml. Transfer 100 μl of the solution (~1 × 105 cells) to a 5 ml culture tube. Add Annexin V and PI 5 μl/test. Gently mix the cells and incubate for 15 min at RT in the dark. Add 400 μl of 1 × Binding Buffer to each tube. Analyze by flow cytometry as soon as possible (within 1 hour).
Western blot analysis
For western blot analysis, cellular proteins were extracted in 40 mM Tris–HCl (pH 7.4) containing 150 mM NaCl and 1% (v/v) Triton X-100, supplemented with a cocktail of protease inhibitors. Equal amounts of protein were resolved on 12% SDS-PAGE gels, and then transferred to a PVDF membrane (Millipore, Bedford, MA). Blots were blocked and then probed with antibodies against MT-3(1:1000, Abcam, Cambridge, MA Office, USA), PARP (1:1000, Cell Signaling Technology, Inc. Danvers, MA), FOXO1 (1:1000, Cell Signaling Technology, Inc. Danvers, MA), CDKN1A (1:1000, Cell Signaling Technology, Inc. Danvers, MA), GAPDH (1:5000, Sigma, St. Louis, MO). After washing, the blots were incubated with horseradish peroxidase-conjugated secondary antibodies and visualized by enhanced chemiluminescence kit (Pierce, Rockford, IL). Protein bands were visualized after exposure of the membrane to Kodak X-ray film.
Real-time PCR array analysis
For RNA extraction, cells were immediately submerged in 2 ml Trizol (Invitrogen Co., NY, USA), stored at -80°C until further processed. A volume of 1 ml of each sample was spun at 4°C for 15 min at 12,000 g to remove debris and DNA, 1 ml of supernatant was mixed with 200 ul chloroform, shaken for 15 seconds, incubated at Room Temperature for 2–3 minutes and spun for 10 minutes at 12,000 g at 4°C. RNA was precipitated by adding 500 ul of the aqueous phase to an equal volume of isopropanol and spun at 14,000 g at 4°C for 10 minutes. RNA was washed with 75% ethanol, spun at 14,000 g at 4°C for 10 minutes, dried and resuspended in 40 ul DEPC-treated H2O. The final RNA concentration was determined using a spectrophotometer (Nanodrop 2000) and the purity was assessed by agarose gel electrophoresis. cDNA synthesis was performed on 4 ug of RNA in a 10 ul sample volume using SuperScript II reverse transcriptase (Invitrogen Co., NY, USA) as recommended by the manufacturer. The RNA was incubated with 0.5 ug of oligo (dT)12–18mers primers (Invitrogen Co., NY, USA) for 7 minutes at 70°C and then transferred onto ice. Then, 9 ul of a master mix containing 4 ul of SuperScript II buffer, 2 ul of 0.1 M DTT, and 1 ul each of dNTPs stock (10 mM), Rnasin (40 UI) and SuperScript II were added to the RNA sample, spun and incubated at 42°C for 60 min followed by 5 min at 70°C to inactivate the enzyme. cDNA was stored at -20°C. Real-time PCR array (SABioscience Human Apoptosis PCR Array PAHS-3012) analysis was performed in a total volume of 20 ul including 2ul of cDNA, primers (0.2 mM each) and 10 ul of SYBR Green mix (Roche Co., Basel, Switzerland). Reactions were run on an Light cycler 480 using the universal thermal cycling parameters (95°C 5 min, 45 cycles of 10 sec at 95°C, 20 sec at 60°C and 15 sec at 72°C; melting curve: 10 sec at 95°C, 60 sec at 60°C and continues melting). Results were obtained using the sequence detection software Light cycler 480 and analyzed using Microsoft Excel. For all samples melting curves were acquired for quality control purposes. For gene expression quantification, we used the comparative Ct method. First, gene expression levels for each sample were normalized to the expression level of the housekeeping gene encoding Glyceraldehydes 3-phosphate dehydrogenase (GAPDH) within a given sample (-⊿Ct); the relative expression of each gene was calculated with 105 *Log2(-⊿Ct). The difference between the MT-3 over-expression samples compared to the control samples was used to determine the 106 *Log2(-⊿Ct). Statistical significance of the gene expression difference between the MT-3 over-expression and the control samples was calculated with the T-test using SPSS 11.5 software.
SPSS v11.5 (SPSS Inc., Chicago, IL) was used for statistical analysis. Data are presented as means ± standard deviation. Group t-test was used to compare the expression of MT-3 between DMSO group and 5-Aza group. Statistical significance between methylated sample data and clinical pathological features of AML patients were analyzed by Pearson chi-square test or Fisher’s exact test. Statistical significance of MT-3 expression among NBM and pediatric AML groups was determined using one-way ANOVA. A p < 0.05 was considered statistically significant.
The MT3 promoter is hypermethylated in AML cells
The MT3 promoter was methylated in patients with pediatric AML
Examination of the clinicopathologic characteristics in patients with pediatric AML revealed that there were no significant differences in clinical features, such as sex, age, initial hemoglobin level, white blood cell counts, platelet counts and chromosomal abnormalities between those with methylated MT3 and those with unmethylated MT3 (Table 1).
Real-time qPCR was employed to examine the transcript levels of MT3 in the 41 pediatric AML samples and 20 NBM/ITP control samples (Figure 3C; Table 1). MT3 expression was found to be significantly decreased in the AML samples compared to the control samples (16.37 ± 15.09 vs. 55.25 ± 18.34; P < 0.001). Further analysis of the AML samples showed that 16/41 patients with pediatric AML displayed methylated MT3 compared to 25/41 patients with unmethylated MT3 (Table 1). Furthermore, those with methylated MT3 showed significantly lower levels of MT3 expression compared to those with unmethylated MT3 (10.65 ± 10.19 vs. 19.23 ± 16.93; P = 0.049; Figure 3D). In summary the hypermethylation status of the MT3 promoter in samples from patients with pediatric AML was consistent with results in human myeloid leukemia cell lines.
Overexpression of MT3 inhibited proliferation and induced apoptosis in leukemia cells
To determine whether MT3 induced apoptosis in leukemia cells, we performed an Annexin V assay in HL-60 and MV4-11 leukemia cells following transfection (Figure 4C and D). The results showed that the proportion of apoptotic cells in the MT3-overexpressing cells (PLVX-MT3) was significantly greater than that in the control group (PLVX-Ve): HL-60 (8.40% ± 1.04% vs. 0.5% ± 0.3%, respectively; P = 0.003); and MV4-11 (7.53% ± 1.49% vs. 0.73 ± 0.21%, respectively; P = 0.014).To further investigate the apoptotic effect of MT3 in HL-60 and MV4-11 cells, we investigated the expression levels of cleaved PARP, a marker of apoptosis, by Western blotting. The results were consistent with the Annexin V data, confirming that MT3 induced apoptosis in leukemia cells (Figure 4A).
Dysregulation of apoptosis-related genes in HL-60 cells overexpressing MT3
Genes up regulated in HL-60 cells treated with PLVX-MT-3 compared with control group
forkhead box O1
immediate early response 3
NADH dehydrogenase (ubiquinone) Fe-S protein 3
tumor necrosis factor, alpha-induced protein 3
tumor necrosis factor
DNA-damage-inducible transcript 3
CASP2 and RIPK1 domain containing adaptor with death domain
BCL2/adenovirus E1B 19 kDa interacting protein 1
BCL2 binding component 3
NADPH oxidase, EF-hand calcium binding domain 5
caspase 7, apoptosis-related cysteine peptidase
CCAAT/enhancer binding protein (C/EBP), gamma
suppressor of cytokine signaling 2
cyclin-dependent kinase inhibitor 1A
Genes down regulated in HL-60 cells treated with PLVX-MT-3 compared with control group
mitogen-activated protein kinase 8 interacting protein 2
chemokine (C-C motif) ligand 2
heat shock 70 kDa protein 1B
protein kinase C, alpha
arachidonate 15-lipoxygenase, type B
sema domain, immunoglobulin domain 4D
caspase recruitment domain family, member 18
NLR family, apoptosis inhibitory protein
Fas (TNFRSF6)-associated via death domain
Fas apoptotic inhibitory molecule 2
caspase recruitment domain family, member 9
caspase recruitment domain family, member 8
caspase 10, apoptosis-related cysteine peptidase
In this study, we found that the MT3 promoter was hypermethylated in pediatric AML. Our results showed that the MT3 promoter was hypermethylated in seven out of eleven human myeloid leukemia cell lines. Furthermore, in agreement with reports in esophageal SCC, treatment with 5-Aza, a specific inhibitor of DNA methylation, led to a significant increase in MT3 expression in AML cells (39.8 fold in HL-60 and 26.8 fold in MV4-11; P < 0.05 and P < 0.01, respectively). These results demonstrated that the MT3 promoter was consistently significantly methylated in human myeloid leukemia cells, suggesting that the MT3 promoter may also be methylated in pediatric AML.
Consistent with the cell line results, we found that the MT3 promoter was methylated in samples obtained from patients with pediatric AML. Aberrant methylation of MT3 was observed 39.0% (16/41) of pediatric AML samples compared to 6.7% (2/30) of NBM control samples. In addition, MT3 was significantly downregulated in the pediatric AML samples compared to the control samples. Further analysis revealed that patients with pediatric AML exhibiting methylated MT3 showed lower levels of MT3 expression compared to those with unmethylated MT3. These results confirmed that hypermethylation of the MT3 promoter occurs with high frequency in both AML cell lines and pediatric AML samples. However, comparisons between the two groups of patients showed no significant differences in MT3 methylation status and patient characteristics, including sex, age, initial hemoglobin level, white blood cell counts, platelet counts, and chromosomal abnormalities. Together, these results implied that various mechanisms may be involved in the downregulation of MT3 in pediatric AML, such as different post-transcriptional modifications, gene deletions, copy number reductions and histone code modifications. Further research will be required to elucidate the details of the underlying mechanisms.
A previous study in prostate cancer PC-3 cells revealed that overexpression of MT3 significantly increased cell proliferation, invasion and tumorigenic activities both in vitro and in vivo. However, there were no reports on the role of MT3 in leukemia cells. In this study, we demonstrated that HL-60 and MV4-11 leukemia cells overexpressing MT3 inhibited cell proliferation in a dose-dependent manner. Further analysis by Annexin V assay revealed that there were a greater proportion of apoptotic cells in MT3-overexpressing leukemia cells compared to mock transfected cells. The apoptotic effect of MT3 in leukemia cells was confirmed by Western blot analysis which showed that MT3 overexpression led to enhanced expression of cleaved PARP, a marker of apoptosis. These findings suggested that MT3 may possess promising antitumor activity in AML cells.
Real-time PCR array analysis is an effective technique for quantifying the expression of a focused panel of genes [32, 33]. Therefore, in order to explore the underlying mechanisms of MT3 antitumor activity, we carried out a real-time PCR array assay on 370 apoptosis-related genes in order to identify those genes that were dysregulated in AML following MT3 overexpression. The findings showed that 17 of the genes were significantly upregulated and 17 genes were significantly downregulated in MT3-overexpressing cells relative to control cells. The gene that was most significantly upregulated was found to be FOXO1, which belongs to the family of forkhead box transcription factors. These are downstream targets in the serine/threonine protein kinase B (PKB)/Akt pathway which is involved in the regulation of cell proliferation and survival [34–36]. It has been shown that withdrawal of growth factors leads to inactivation of the PI3K-Akt pathway, FOXO1 dephosphorylation at its Akt sites, nuclear translocation and activation of FOXO target genes [35–37]. FOXO1 plays a central role in initiating apoptosis by inducing expression of death genes, such as FASL. In the nucleus, FOXO1 is a key mediator of tumor suppression downstream of PTEN. Exogenous expression of PTEN induces FOXO1 to relocate to the nucleus, restoring its transcriptional activation. In addition, a constitutively active form of FOXO1 that cannot be phosphorylated by Akt has been found to induce apoptosis in PTEN-null cells, indicating that it has the same effect as reconstitution of PTEN. Our results indicated that FOXO1 is a downstream target of MT3 in pediatric AML. A study in prostate cancer cells suggested that overexpression of FOXO1 resulted in apoptosis via increased expression of TRAIL (TNF-Related Apoptosis-Inducing Ligand) . However, the mechanism and the role of these genes in MT3-induced apoptosis in AML remain to be elucidated.
In this study, we identified epigenetic inactivation of MT3 in both AML cell lines and pediatric AML samples via hypermethylation of the MT3 promoter. Our findings also showed that transcriptional overexpression of MT3 could inhibit proliferation and induce apoptosis in AML cells. We identified 34 dysregulated apoptosis-related genes in MT3-overexpressing, including FOXO1. These results may provide new insights into the molecular mechanism of MT3-induced apoptosis; however, further research will be required to determine the underlying details. Together, our findings suggest that MT3 may act as a putative tumor suppressor gene in pediatric AML.
This work was supported by grants from the National Key Basic Research Program (No. 2010CB933902), the Key Medical Subjects of Jiangsu Province (XK201120), the Innovative Team of Jiangsu Province ( LJ201114, LJ201126 ), the Special Clinical Medical Science and Technology of Jiangsu Province (BL2012050, BL2013014), the Key Laboratory of Suzhou (SZS201108, SZS201307), the National Natural Science Foundation (81100371, 81370627, 81300423, 81272143), the Natural Science Foundation of Jiangsu Province (No. BK2011308), the Universities Natural Science Foundation of Jiangsu Province (No. 11KJB320014), the Talent’s Subsidy Project in Science and Education of Department of Public Health of Suzhou City (No. SWKQ1020), and the Major Scientific and Technological Special Project for “Significant New Drugs Creation” (No. 2012ZX09103301-040).
- Appelbaum FR, Baer MR, Carabasi MH, Coutre SE, Erba HP, Estey E, Glenn MJ, Kraut EH, Maslak P, Millenson M, Miller CB, Saba HI, Stone R, Tallman MS: NCCN practice guidelines for Acute Myelogenous Leukemia. Oncology (Williston Park). 2000, 14: 53-61.Google Scholar
- Sanz GF, Sanz MA, Vallespi T, Canizo MC, Torrabadella M, Garcia S, Irriguible D, San Miguel JF: Two regression models and a scoring system for predicting survival and planning treatment in myelodysplastic syndromes: a multivariate analysis of prognostic factors in 370 patients. Blood. 1989, 74: 395-408.PubMedGoogle Scholar
- Basu I, Cordovano G, Das I, Belbin TJ, Guha C, Schramm VL: A transition state analogue of 5′-methylthioadenosine phosphorylase induces apoptosis in head and neck cancers. J Biol Chem. 2007, 282: 21477-21486.View ArticlePubMedGoogle Scholar
- Mann MR, Bartolomei MS: Epigenetic reprogramming in the mammalian embryo: struggle of the clones. Genome Biol. 2002, 3: 2-REVIEWS1003View ArticleGoogle Scholar
- Agrawal S, Unterberg M, Koschmieder S, ZurStadt U, Brunnberg U, Verbeek W, Buchner T, Berdel WE, Serve H, Muller-Tidow C: DNA methylation of tumor suppressor genes in clinical remission predicts the relapse risk in acute myeloid leukemia. Cancer Res. 2007, 67: 1370-1377.View ArticlePubMedGoogle Scholar
- Akhavan-Niaki H, Samadani AA: DNA methylation and cancer development: molecular mechanism. Cell Biochem Biophys. 2013, 67: 501-513.View ArticlePubMedGoogle Scholar
- Gaudet F, Hodgson JG, Eden A, Jackson-Grusby L, Dausman J, Gray JW, Leonhardt H, Jaenisch R: Induction of tumors in mice by genomic hypomethylation. Science. 2003, 300: 489-492.View ArticlePubMedGoogle Scholar
- Chen RZ, Pettersson U, Beard C, Jackson-Grusby L, Jaenisch R: DNA hypomethylation leads to elevated mutation rates. Nature. 1998, 395: 89-93.View ArticlePubMedGoogle Scholar
- Worm J, Aggerholm A, Guldberg P: In-tube DNA methylation profiling by fluorescence melting curve analysis. Clin Chem. 2001, 47: 1183-1189.PubMedGoogle Scholar
- Willman CL: Targeted AML therapy: new biologic paradigms and therapeutic opportunities. Leukemia. 2001, 15: 690-694.View ArticlePubMedGoogle Scholar
- Toyota M, Kopecky KJ, Toyota MO, Jair KW, Willman CL, Issa JP: Methylation profiling in acute myeloid leukemia. Blood. 2001, 97: 2823-2829.View ArticlePubMedGoogle Scholar
- Miftakhova R, Sandberg T, Hedblom A, Nevzorova T, Persson JL, Bredberg A: DNA methylation in ATRA-treated leukemia cell lines lacking a PML-RAR chromosome translocation. Anticancer Res. 2012, 32: 4715-4722.PubMedGoogle Scholar
- Fu L, Huang W, Jing Y, Jiang M, Zhao Y, Shi J, Huang S, Xue X, Zhang Q, Tang J, Dou L, Wang L, Nervi C, Li Y, Yu L: AML1-ETO triggers epigenetic activation of early growth response gene l, inducing apoptosis in t (8;21) acute myeloid leukemia. Febs J. 2013, 281: 1123-1131.View ArticleGoogle Scholar
- Deshpande AJ, Bradner J, Armstrong SA: Chromatin modifications as therapeutic targets in MLL-rearranged leukemia. Trends Immunol. 2012, 33: 563-570.PubMed CentralView ArticlePubMedGoogle Scholar
- Bernt KM, Armstrong SA: Targeting epigenetic programs in MLL-rearranged leukemias. Hematology Am Soc Hematol Educ Program. 2011, 2011: 354-360.View ArticlePubMedGoogle Scholar
- Tabe Y, Konopleva M, Kondo Y, Contractor R, Jin L, Ruvolo V, Tsutsumi-Ishii Y, Miyake K, Miyake N, Ohsaka A, Nagaoka I, Issa JP, Andreeff M: PML-RARalpha and AML1-ETO translocations are rarely associated with methylation of the RARbeta2 promoter. Ann Hematol. 2006, 85: 689-704.View ArticlePubMedGoogle Scholar
- Haferlach T, Nagata Y, Grossmann V, Okuno Y, Bacher U, Nagae G, Schnittger S, Sanada M, Kon A, Alpermann T, Yoshida K, Roller A, Nadarajah N, Shiraishi Y, Shiozawa Y, Chiba K, Tanaka H, Koeffler HP, Klein HU, Dugas M, Aburatani H, Kohlmann A, Miyano S, Haferlach C, Kern W, Ogawa S: Landscape of genetic lesions in 944 patients with myelodysplastic syndromes. Leukemia. 2014, 28: 241-247.PubMed CentralView ArticlePubMedGoogle Scholar
- Weissmann S, Alpermann T, Grossmann V, Kowarsch A, Nadarajah N, Eder C, Dicker F, Fasan A, Haferlach C, Haferlach T, Kern W, Schnittger S, Kohlmann A: Landscape of TET2 mutations in acute myeloid leukemia. Leukemia. 2012, 26: 934-942.View ArticlePubMedGoogle Scholar
- Ajjimaporn A, Swinscoe J, Shavali S, Govitrapong P, Ebadi M: Metallothionein provides zinc-mediated protective effects against methamphetamine toxicity in SK-N-SH cells. Brain Res Bull. 2005, 67: 466-475.View ArticlePubMedGoogle Scholar
- Howells C, West AK, Chung RS: Neuronal growth-inhibitory factor (metallothionein-3): evaluation of the biological function of growth-inhibitory factor in the injured and neurodegenerative brain. Febs J. 2010, 277: 2931-2939.View ArticlePubMedGoogle Scholar
- Ma F, Wang H, Chen B, Wang F, Xu H: Metallothionein 3 attenuated the apoptosis of neurons in the CA1 region of the hippocampus in the senescence-accelerated mouse/PRONE8 (SAMP8). Arq Neuropsiquiatr. 2011, 69: 105-111.View ArticlePubMedGoogle Scholar
- Carrasco J, Penkowa M, Giralt M, Camats J, Molinero A, Campbell IL, Palmiter RD, Hidalgo J: Role of metallothionein-III following central nervous system damage. Neurobiol Dis. 2003, 13: 22-36.View ArticlePubMedGoogle Scholar
- Lee SJ, Koh JY: Roles of zinc and metallothionein-3 in oxidative stress-induced lysosomal dysfunction, cell death, and autophagy in neurons and astrocytes. Mol Brain. 2010, 3: 30-PubMed CentralView ArticlePubMedGoogle Scholar
- Lowy AM, Clements WM, Bishop J, Kong L, Bonney T, Sisco K, Aronow B, Fenoglio-Preiser C, Groden J: beta-Catenin/Wnt signaling regulates expression of the membrane type 3 matrix metalloproteinase in gastric cancer. Cancer Res. 2006, 66: 4734-4741.View ArticlePubMedGoogle Scholar
- Smith E, Drew PA, Tian ZQ, De Young NJ, Liu JF, Mayne GC, Ruszkiewicz AR, Watson DI, Jamieson GG: Metallothionien 3 expression is frequently down-regulated in oesophageal squamous cell carcinoma by DNA methylation. Mol Cancer. 2005, 4: 42-PubMed CentralView ArticlePubMedGoogle Scholar
- Deng D, El-Rifai W, Ji J, Zhu B, Trampont P, Li J, Smith MF, Powel SM: Hypermethylation of metallothionein-3 CpG island in gastric carcinoma. Carcinogenesis. 2003, 24: 25-29.View ArticlePubMedGoogle Scholar
- Olek A, Oswald J, Walter J: A modified and improved method for bisulphite based cytosine methylation analysis. Nucleic Acids Res. 1996, 24: 5064-5066.PubMed CentralView ArticlePubMedGoogle Scholar
- Cheng Y, Geng H, Cheng SH, Liang P, Bai Y, Li J, Srivastava G, Ng MH, Fukagawa T, Wu X, Chan AT, Tao Q: KRAB zinc finger protein ZNF382 is a proapoptotic tumor suppressor that represses multiple oncogenes and is commonly silenced in multiple carcinomas. Cancer Res. 2010, 70: 6516-6526.View ArticlePubMedGoogle Scholar
- Yan-Fang T, Jian N, Jun L, Na W, Pei-Fang X, Wen-Li Z, Dong W, Li P, Jian W, Xing F, Jian P: The promoter of miR-663 is hypermethylated in Chinese pediatric acute myeloid leukemia (AML). BMC medical genetics. 2013, 14: 74-PubMed CentralView ArticlePubMedGoogle Scholar
- Jian P, Li ZW, Fang TY, Jian W, Zhuan Z, Mei LX, Yan WS, Jian N: Retinoic acid induces HL-60 cell differentiation via the upregulation of miR-663. J Hematol Oncol. 2011, 4: 20-PubMed CentralView ArticlePubMedGoogle Scholar
- Juang HH, Chung LC, Sung HC, Feng TH, Lee YH, Chang PL, Tsui KH: Metallothionein 3: an androgen-upregulated gene enhances cell invasion and tumorigenesis of prostate carcinoma cells. Prostate. 2013, 73: 1495-1506.View ArticlePubMedGoogle Scholar
- Yan-Fang T, Dong W, Li P, Wen-Li Z, Jun L, Na W, Jian W, Xing F, Yan-Hong L, Jian N, Jian P: Analyzing the gene expression profile of pediatric acute myeloid leukemia with real-time PCR arrays. Cancer Cell Int. 2012, 12: 40-PubMed CentralView ArticlePubMedGoogle Scholar
- Tao YF, Lu J, Du XJ, Sun LC, Zhao X, Peng L, Cao L, Xiao PF, Pang L, Wu D, Wang N, Feng X, Li YH, Ni J, Wang J, Pan J: Survivin selective inhibitor YM155 induce apoptosis in SK-NEP-1 Wilms tumor cells. BMC Cancer. 2012, 12: 619-PubMed CentralView ArticlePubMedGoogle Scholar
- Zhang X, Tang N, Hadden TJ, Rishi AK: Akt, FoxO and regulation of apoptosis. Biochim Biophys Acta. 1813, 2011: 1978-1986.Google Scholar
- Lu H, Huang H: FOXO1: a potential target for human diseases. Curr Drug Targets. 2011, 12: 1235-1244.PubMed CentralView ArticlePubMedGoogle Scholar
- Monsalve M, Olmos Y: The complex biology of FOXO. Curr Drug Targets. 2011, 12: 1322-1350.View ArticlePubMedGoogle Scholar
- Fu Z, Tindall DJ: FOXOs, cancer and regulation of apoptosis. Oncogene. 2008, 27: 2312-2319.PubMed CentralView ArticlePubMedGoogle Scholar
- Modur V, Nagarajan R, Evers BM, Milbrandt J: FOXO proteins regulate tumor necrosis factor-related apoptosis inducing ligand expression. Implications for PTEN mutation in prostate cancer. J Biol Chem. 2002, 277: 47928-47937.View ArticlePubMedGoogle Scholar
- Nakamura N, Ramaswamy S, Vazquez F, Signoretti S, Loda M, Sellers WR: Forkhead transcription factors are critical effectors of cell death and cell cycle arrest downstream of PTEN. Mol Cell Biol. 2000, 20: 8969-8982.PubMed CentralView ArticlePubMedGoogle Scholar
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