Literature DB >> 32337016

Transcriptomic Profiles of MV4-11 and Kasumi 1 Acute Myeloid Leukemia Cell Lines Modulated by Epigenetic Modifiers Trichostatin A and 5-Azacytidine.

Mat Jusoh Siti Asmaa1,2,3,4,5,6,7, Hamid Ali Al-Jamal1,2,3,4,5,6,7, Abdul Rahim Hussein1,2,3,4,5,6,7, Badrul Hisham Yahaya1,2,3,4,5,6,7, Roslin Hassan1, Faezahtul Arbaeyah Hussain5, Shaharum Shamsuddin6,7, Muhammad Farid Johan1.   

Abstract

Background: Acute myeloid leukemia (AML) is the most common form of acute leukemias in adults which is clinically and molecularly heterogeneous. Several risk and genetic factors have been widely investigated to characterize AML. However, the concomitant epigenetic factors in controlling the gene expression lead to AML transformation was not fully understood. This study was aimed to identify epigenetically regulated genes in AML cell lines induced by epigenetic modulating agents, Trichostatin A (TSA) and 5-Azacytidine (5-Aza). Materials and
Methods: MV4-11 and Kasumi 1 were treated with TSA and/or 5-Aza at IC50 concentration. Gene expression profiling by microarray was utilized using SurePrint G3 Human Gene Expression v3. Gene ontology and KEGG pathway annotations were analyzed by DAVID bioinformatics software using EASE enrichment score. mRNA expression of the differentially expressed genes were verified by quantitative real time PCR.
Results: Gene expression analysis revealed a significant changes in the expression of 24,822, 15,720, 15,654 genes in MV4-11 and 12,598, 8828, 18,026 genes in Kasumi 1, in response to TSA, 5-Aza and combination treatments, respectively, compared to non-treated (p<0.05). 7 genes (SOCS3, TUBA1C, CCNA1, MAP3K6, PTPRC, STAT6 and RUNX1) and 4 genes (ANGPTL4, TUBB2A, ADAM12 and PTPN6) shown to be predominantly expressed in MV4-11 and Kasumi 1, respectively (EASE<0.1). The analysis also revealed phagosome pathway commonly activated in both cell lines.
Conclusion: Our data showed a distinct optimal biological characteristic and pathway in different types of leukemic cell lines. These finding may help in the identification of cell-specific epigenetic biomarker in the pathogenesis of AML. Copyright : © International Journal of Hematology-Oncology and Stem Cell Research & Tehran University of Medical Sciences.

Entities:  

Keywords:  5-Azacytidine; Acute myeloid leukemia; Epigenetics* Histone deacetylase inhibitors; Gene expression

Year:  2020        PMID: 32337016      PMCID: PMC7167603     

Source DB:  PubMed          Journal:  Int J Hematol Oncol Stem Cell Res        ISSN: 2008-2207


Introduction

Acute myeloid leukemia (AML) is characterized by a block in early progenitor differentiation leading to accumulation of immature and highly proliferative leukemic stem cells (LSCs) in the bone marrow and peripheral blood[   1 ]. The 2017 World Health Organization (WHO) has provided guidelines on the cut-off value of blast percentage of AML by; 200 and 500 cells-leukocytes differential counts in the peripheral blood and in the bone marrow, respectively[   2 ]. For a diagnosis of AML, a marrow or blood blast count of 20% or more is required, except for AML with t(15;17), t(8;21), inv(16) or t(16;16), and some cases of erythroleukemia. AML is the most common form of acute leukemias in adults which affected 32% adults. Although the overall mortality rate has decreased by 1.0% each year from 2001 to 2010, the overall incidence rate was increased by 0.2% each year. In 2018, the American Cancer Society estimated that 19,520 of new cases and 10,670 deaths from AML. The 5-years overall survival rate was also poor with only 24%[   3 ]. For many years, gene expression profiling by microarray was used as a traditional method to search abnormalities in cancers, including in AML[   4 ]. These presented data was invaluable and accessible to the identification of disease’s class discovery, class prediction, and class comparison. Class discovery refers to the identification of a new subgroup, that later was class predicted by gene expression data. The first and second class already had a diagnostic implication. While the third class, which is class comparison refer to the identification of genes that were deregulated in certain subgroups, that may address biological function[   5 ]. It has long established that AML is clinically heterogeneous disease characterized by an accumulation of continuous genetic abnormalities[   6 ] and prior epigenetic lesions[   7 ] resulting in clonal evolution and expansion. The considerable complexities disrupt the genetic and epigenetic landscapes by changes in gene expression[   8 ] which profoundly affecting treatment response and patients’ survival. Earlier epigenetic alteration established cellular identities initiating tumorigenesis by inappropriate activation or inhibition of cellular signaling pathways[   9 ]. For example, promoter hypermethylation of a tumor suppressor genes is commonly implicated in cancer[   10 ], involving genes controlling the cell cycle and DNA repair[   11 ]. On the other hand, modification to histone protein in nucleosome modulates the transcriptional burst frequency specifically through histone acetylation[   12 ]. Both epigenetic mechanisms endow the regulation in gene expression. Hence, targeting the epigenetically-regulated genes in the control of AML licensed a promising outcome. In this study, high-throughput microarray technique was used to analyze epigenetic-derived molecular mechanism by modulating gene expression using a classical DNA methyltransferase (DNMT) inhibitor; 5-Azacytidine (5-Aza) and a histone deacetylase (HDAC) inhibitor, Trichostatin A (TSA). The aim of this study was to induce the epigenetic response via gene re-expression or down-expression in two types of AML cell lines; MV4-11 and Kasumi 1. It was hypothesized that the silencing of a tumor suppressor gene and the activation of oncogenes in AML were due to epigenetic mechanisms of DNA hypermethylation and histone deacetylation.

MATERIALS AND METHODS

MV4-11 and Kasumi 1 cell culture MV4-11 is a human AML cell line established from blasts cells of 10 years old male with biphenotypic B-myelomonocytic leukemia (AML FAB M5) that carry translocation t(4;11) and a FLT3-ITD mutation. Kasumi 1 is a human AML cell line established from peripheral blast cells from 7 years old juvenile male Japanese that carry translocation t(8;21) and AML1-ETO (also known as RUNX1-CBF2T1) fusion genes. The AML cell lines were originally purchased from the American Type Culture Collection (ATCC, VA, USA). Both AML cell lines were cultured in RPMI-1640 (Gibco®, CA, USA) supplemented with 10% Fetal bovine serum (Sigma-Aldrich, MO, USA) and 0.1% penicillin/streptomycin (Invitrogen, CA, USA) in humidified temperature containing 5% carbon dioxide (CO2) at 37°C. TSA and/or 5-Aza treatment TSA (Sigma-Aldrich, MO, USA) and 5-Aza (Sigma-Aldrich, MO, USA) were dissolved in DMSO (Sigma-Aldrich, MO, USA) and RPMI-1640, respectively to a stock concentration of 500 µM, and further diluted to the desired working concentrations. MV4-11 and Kasumi 1 were seeded in 6-wells plate to 80-90% confluency at the initial cell number of 1 x 105 cells/mL prior to the drug treatment for 24 hours. The cell lines were treated with varying concentration of TSA (0, 1.25, 2.5, 5.0, 10.0 µM) and 5-Aza (0, 5.0, 10.0, 20.0, 50, 100 µM) and incubated for 24 hours under humidified temperature. Cell Viability Assay Percentage viability of non-treated and treated MV4-11 and Kasumi 1 after the 24 hours exposure to TSA and 5-Aza treatments were measured by Trypan Blue Exclusion Assay (Life Technologies, CA, USA). The half maximal inhibitory concentration (IC50) was determined by GraphPad Prism 6.0 (GraphPad, CA, USA). Total RNA extraction and quality control Total RNA was extracted from treated and untreated MV4-11 and Kasumi 1 using Total RNA Isolation Kit (Promega, SA, USA) according to the manufacturer’s protocol. The final elution step was performed using 30 µl of elution buffer for a highly concentrated RNAs. The isolated RNA concentration and purity were determined by Nanodrop ND-1000 spectrophotometer (Thermo-Fisher Scientific, WA, USA). Prior to the gene expression profiling, the RNA integrity was assessed by 1.5% agarose gel electrophoresis and their RIN (RNA integrity number) values were determine by Agilent 2100 Bioanalyzer (Agilent, CA, USA). The qualified RNAs (absorbance 280/260 1.8-2.1 ratio; highly intact 28S and 18S ribosomal RNA and RIN above 7) were stored at -80 ºC until further analysis. Microarray analysis Whole genome expression profiling was performed using One-Color SurePrint G3 Human Gene Expression v3, 8 x 60K slides contained array probe (Agilent Technologies, CA, USA). Prior to Cyanine 3 (Cy3) labeling, RNA spiked-In dilution was prepared using RNA spiked-In Kit (Agilent Technologies, CA, USA) to each sample using T7 RNA polymerase (RNA reference target) for normalization. Cy3-labeled cRNA was generated from 25 ng input total RNA using Low Input Quick Amp Labeling Kit (Agilent Technologies, CA, USA). The fluorescent-labeled cRNA was purified by RNAeasy Mini Kit and RNAase-free DNAase Set (Qiagen, CA, USA) and quantified by Nanodrop ND-1000 spectrophotometer. 25 ng of fluorescein-labeled and amplified cRNA was hybridized into array slides containing 60,000 probes (Agilent Technologies, CA, USA) at 65 degree Celsius for 17 hours. After hybridization and washing steps, the array slides were scanned using SureCan Microarray Scanner (Agilent Technologies, CA, USA) to measure the fluorescence intensity of Cy3 labeled RNA bound to the microarray slide. The resulted images were processed using the Feature Extraction (FE) software v.12 (Agilent Technologies, CA, USA) for data filtering. Raw data obtained was analyzed by Genespring GX v12.6 software (Agilent Technologies, CA, USA). Database screening Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis annotations were utilized by the Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resources v6.8 (https://david.ncifcrf.gov/) to characterize and predict epigenetically regulated genes in treated AML cell lines. The Enhanced AL Scoring Engine (EASE) scoring system (a modified Fisher Exact p-value, p<0.1) was implemented for statistical analysis to provide enriched GO terms and pathways annotation within gene lists. EASE analysis produces a consistent and similar functional annotation with numerous analytical methods[   13 ], and Venn diagram was constructed to analyze genes with differential expression pattern after TSA and 5-Aza treatment in MV4-11 and Kasumi 1. The analysis was conducted by the Venny 2.1 software (http://bioinfogp.cnb.csic.es/tools/venny/). Quantitative Real-time PCR (qRT-PCR) To validate microarray data, qRT-PCR analysis on selected up-regulated and down-regulated genes was performed by Taqman gene expression assays and analyzed using Applied Biosystem (ABI)® 7500 Real-Time PCR Machine (Applied Biosystem, CA, USA). Total RNAs from untreated and treated cell lines were reverse transcribed using High-Capacity cDNA Reverse Transcription Kit (Applied Biosystem, CA, USA). Pre-designed assays (PrimeTime® Pre-designed Assays) (IDT Inc., IA, USA) [ANGPTL4 (assay ID: Hs.PT58.25480012), TUBB2A (assay ID: Hs.PT58.40767003), PTPN6 (assay ID: Hs.PT58.23073507) and ADAM12 (assay ID: Hs.PT58.26423628)], and custom-designed primers and probes (SOCS3, TUBA1C, CCNA1, MAP3K6, STAT6, PTPRC and RUNX1 genes) were amplified by PrimeTime® Gene Expression Master Mix (IDT Inc., IA, USA). Assay sequences were confirmed using web Basic Local Alignment Search Tool (BLAST) by the National Center for Biotechnology Information (NCBI) (U.S. National Library of Medicine, MD, USA). The qRT-PCR amplification conditions were: 95°C for 3 min for enzyme activation, 40 cycles of denaturation at 95°C for 15 s and 60°C for 1 min for annealing and extension. B2M and GAPDH were used as endogenous control genes and expression levels were estimated using relative quantitation (RQ) of duplicated samples calculated by 2-∆∆CT method (∆∆CT=∆CTTreated–∆CTUntreated, ∆CT=CtSelected Genes –CtB2M/GAPDH).

Results

A significant decrease in cell viability was observed after the TSA and 5-Aza treatments (One-way ANOVA, p<0.05). The half maximal inhibitory concentration (IC50) was acquired at 2.2 µM and 2.3 µM for MV4-11 and; 6.25 µM and 6.95 µM for Kasumi 1 in TSA and 5-Aza, respectively. TSA and 5-Aza treatments have higher potency in MV4-11 due to their lower IC50 value compared to Kasumi 1 (Figure 1).
Figure 1

Effect of TSA and 5-Aza treatment on cell viability by percentage (%) inhibition of MV4-11 and Kasumi 1 cell lines relative to non-treated cell lines. Significant inhibition of MV4-11 after (a) TSA and (b) 5-Aza treatment at increasing concentration (0.0, 1.25, 2.5, 5.0 and 10.0 µM) for 24 h. Significant inhibition of Kasumi 1 after (c) TSA treatment at increasing concentration (0.0, 1.25, 2.5, 5.0 and 10.0 µM) and (d) 5-Aza (0.0, 5.0, 10.0, 20.0, 50.0 and 100.0 µM) for 24 h calculated by Trypan Blue Exclusion Assay (TBEA) (One-Way ANOVA, LSD multiple comparison, p<0.05).

Effect of TSA and 5-Aza treatment on cell viability by percentage (%) inhibition of MV4-11 and Kasumi 1 cell lines relative to non-treated cell lines. Significant inhibition of MV4-11 after (a) TSA and (b) 5-Aza treatment at increasing concentration (0.0, 1.25, 2.5, 5.0 and 10.0 µM) for 24 h. Significant inhibition of Kasumi 1 after (c) TSA treatment at increasing concentration (0.0, 1.25, 2.5, 5.0 and 10.0 µM) and (d) 5-Aza (0.0, 5.0, 10.0, 20.0, 50.0 and 100.0 µM) for 24 h calculated by Trypan Blue Exclusion Assay (TBEA) (One-Way ANOVA, LSD multiple comparison, p<0.05). Gene expression profile of MV4-11 and Kasumi 1 in response to TSA and 5-Aza The gene expression profile of MV4-11 and Kasumi 1 after 24 hours of TSA, 5-Aza and combination (TSA+5-Aza) treatments at IC50 concentration. The exploratory microarray analysis was carried out to short-list the differentially expressed genes induced by the drug treatments analyzed by GeneSpring software 12.1 (the cut-off value; fold change ≥ 2.0, significance level, Pearson, P <0.05). 33,150 and 24,668 genes passed the FE filtering in MV4-11 and Kasumi 1, respectively. In MV4-11, 24,822 genes’ expressions were altered (either up or down-regulated) in TSA, 15,720 in 5-Aza and 15,654 in TSA+5-Aza. Whereas in Kasumi 1, 12,598 genes were altered in TSA, 8828 genes in 5-Aza and 18,026 genes in TSA+5-Aza treatments, normalized to non-treated cells (Figure 2). The most up-regulated and down-regulated genes in TSA, 5-Aza and TSA+5-Aza treatments and their folds change were listed in Tables 1 and 2. Genes were selected according to these three criteria: 1. Relevant genes with the highest fold-change different and commonly regulated across all treatments, 2. Relevant genes reported having an association with AML and other myeloid neoplasms from the previous study and/or Pubmed literature, 3. Genes with not otherwise classified under both criteria but could be interesting due to their implication in pathways in cancer.
Figure 2

Microarray gene expression analysis for MV4-11 and Kasumi 1 treated with TSA, 5-Aza and TSA+5-Aza. Number of up-regulated and down-regulated genes was created by Genespring software analysis. Further analysis to obtain gene entities were performed using Moderated T-test with multiple correction (Benjamini Hochberg FDR) with p-value <0.05 and fold change of >2.0 as a significant.

Microarray gene expression analysis for MV4-11 and Kasumi 1 treated with TSA, 5-Aza and TSA+5-Aza. Number of up-regulated and down-regulated genes was created by Genespring software analysis. Further analysis to obtain gene entities were performed using Moderated T-test with multiple correction (Benjamini Hochberg FDR) with p-value <0.05 and fold change of >2.0 as a significant. Most up- and down-regulated genes in TSA treated MV4-11 *Folds-change of treatment group compared to control analyzed by Genespring software analysis, Moderated T-test, p<0.05) Most up- and down-regulated genes in 5-Aza treated MV4-11 Most up- and down-regulated genes in TSA+5-Aza treated MV4-11 *Folds-change of treatment group compared to control analyzed by Genespring software analysis, Moderated T-test, p<0.05) Most up- and down-regulated genes in TSA treated Kasumi 1 *Folds-change of treatment group compared to control analyzed by Genespring software analysis, Moderated T-test, p<0.05) Most up- and down-regulated genes in 5-Aza treated Kasumi 1 *Folds-change of treatment group compared to control analyzed by Genespring software analysis, Moderated T-test, p<0.05) Most up- and down-regulated genes in TSA+5-Aza treated Kasumi 1 *Folds-change of treatment group compared to control analyzed by Genespring software analysis, Moderated T-test, p<0.05) Identification of an optimal Gene Ontology (GO) and KEGG pathway by DAVID software GO analysis identified 13 optimal GO terms in MV4-11 after TSA, 5-Aza and TSA+5-Aza treatments constituted of 7 highly enriched biological processes (BP); Actin filament organization, Cytoskeleton organization, JAK-STAT, Blood coagulation, Positive regulation of activated T cell proliferation, Positive regulation of MAPK cascade and Cytoskeleton-dependent intracellular transport, related to 6 enriched molecular function (MF); GTPase activity, GTP binding, Structural constituent of cytoskeleton, Signal transducer activity, Polysaccharide binding, and Insulin-like growth factor receptor binding. The transduced GO terms were correspondent to 4 enriched KEGG pathway, which was Viral carcinogenesis, Hepatitis B, JAK-STAT and Phagosome (Table 3a).
Table 3(a)

Gene ontology (GO) profile after TSA, 5-Aza and TSA+5-Aza treatments in MV4-11

GO IDs
GO term
Genes
p-value
Biological processes
GO:0007015 Actin filamen organization ARHGAP6, SPTA1, TPM2, TMSB15A 0.0084
GO:0007010 Cytoskeleton organization ABLIM3, TUBA1C, ANK1, TSPAN32, TUBB3 0.014
GO:0007259 JAK-STAT cascade NMI, STAT5A, SOCS3 0.015
GO:0007596 Blood coagulation CYP4F2, HBD, NFE2, THBD, TFPI 0.022
GO:0042102 Positive regulation of activated T cell proliferation CD24, IGF2, IL6 0.047
GO:0043410 positive regulation of MAPK cascade TIMP2, IGF2, IL6 0.080
GO:0030705 Cytoskeleton-dependent intracellular transport KIF5C, TUBA1C 0.099
Molecular Functions
GO:0003924 GTPase activity GNG11, GNG8, RHEB, RAB3A, TUBA1C, TUBB3 0.010
GO:0005525 GTP binding GIMAP2, GIMAP6, RAB12, RAB3A, RHEB, TUBA1C, TUBB3 0.021
GO:0005200 Structural constituent of cytoskeleton ANK1, SPTA1, TUBA1C, TUBB3 0.024
GO:0004871 Signal transducer activity CD24, GNG11, GNG8, STAT5A, STAT6 0.028
GO:0030247 Polysaccharide binding ENPP3, PRG4 0.076
GO:0005159 Insulin-like growth factor receptor binding IGF2, REN 0.081
Pathways
Viral carcinogenesis CCNA1, HDAC7, HIST1H2BN, STAT5A 0.069
Hepatitis B CCNA1, IL6, STAT5A, STAT6 0.084
JAK-STAT SOCS3, IL6, STAT5A, STAT6 0.084
Phagosome STX12, TUBA1C, TUBB3 0.10

(DAVID software analysis, EASE score 0.1, Benjamini p<0.1)

Gene ontology (GO) profile after TSA, 5-Aza and TSA+5-Aza treatments in MV4-11 (DAVID software analysis, EASE score 0.1, Benjamini p<0.1) In Kasumi 1, 16 optimal GO terms by BP were identified; Cell adhesion, Leukocyte migration, Bone mineralization, Regulation of G-protein coupled receptor protein signaling pathway, Positive regulation of cell motility, phagocytosis, Peptidyl-tyrosine dephosphorylation, Protein localization to cell surface, Negative regulation of apoptotic process, Protein phosphorylation, Negative regulation of cell death, Hematopoiesis, Negative regulation of cell proliferation, Response to drug, Angiogenesis and Microtubule-based process, related to 8 MF; Protein tyrosine phosphatase activity, Transmembrane receptor protein tyrosine phosphatase activity, Carbohydrate-binding, Protein kinase activity, Heparin-binding, Protein serine/threonine kinase activity, Beta-catenin binding and Transcription factor binding. The most optimal KEGG pathway induced in Kasumi 1 were; Transcriptional misregulation in cancer, MAPK signaling pathway, PI3K-Akt signaling pathway, Pathways in cancer, Hippo signaling pathway, Proteoglycans in cancer, Ras signaling and Phagosome (Table 3b).
Table 3(b)

Gene ontology (GO) profile after TSA, 5-Aza and TSA+5-Aza treatments in Kasumi 1

GO IDs
GO term
Genes
P-value
Biological processes
GO:0007155 Cell adhesion ADAM12, CDH15, COL1A1, PTPRK, PTPRF, DSC2, ATP1B2, CD96, DSC2, COL1A1, MCAM 0.00093
GO:0050900 Leukocyte migration ANGPTL1, COL1A1, ATP1B2, PECAM1, PTPN6, DOK2 0.0013
GO:0030282 Bone mineralization CLEC3B, WNT11, FGFR3, TUFT1 0.0014
GO:0008277Regulation of G-protein coupled receptor protein signaling pathway GNG4, RGS18, RGS9, RAMP1 0.0022
GO:2000147Positive regulation of cell motility CCR7, CSF1R, TWIST1 0.0037
GO:0006909Phagocytosis CEBPE, CD93, ELANE, PECAM1 0.0039
GO:0035335 Peptidyl-tyrosine dephosphorylation PTPN6, PTPN7, PTPRK,PTPRF, DUSP6 0.0042
GO:0034394Protein localization to cell surface WNT11, ANGPTL1, PTPRK 0.0051
GO:0043066 Negative regulation of apoptotic process GLI3, WNT11, ANGPTL1, ANGPTL4, CSF1R, DHRS2, TWIST1, MYC 0.0068
GO:0006468 Protein phosphorylation FES, MOK, WNT11, CDK14, LMTK3, TRIB3, RPS6KA4 0.024
GO:0060548 Negative regulation of cell death WNT11, CST3, MYC 0.030
GO:0030097 Hematopoiesis ANGPTL1, CSF1R, GFI1 0.034
GO:0008285 Negative regulation of cell proliferation PTPN6, PTPRK, GL13, CSF1R, DHRS2, DLG3CBFA2T3 0.048
GO:0042493 Response to drug FOS, COL1A1, CST3, HDAC5, MYC 0.062
GO:0001525 Angiogenesis ANGPTL1, ANGPTL4, PECAM1, RAMP1, MCAM 0.096
GO:0007017 Microtubule-based process TUBB2A, TUBB3 0.10
Molecular Functions
GO:0004725 Protein tyrosine phosphatase activity PTPN6, PTPN7, PTPRF, PTPRK, DUSP6 0.0038
GO:0005001 Transmembrane receptor protein tyrosine phosphatase activity PTPN6, PTPRF, PTPRK 0.0051
GO:0030246 Carbohydrate binding CLEC3B, CLEC4B, PRG2, LGALS12 0.036
GO:0004672 Protein kinase activity MOK, TRIB3, CDK14, LMTK3, STK33, MAP3K9 0.078
GO:0008201 Heparin binding CLEC3B, ELANE, PTPRF, PRG2 0.081
GO:0004674 protein serine/threonine kinase activity MOK, SBK1, LMTK3, MAP3K9, RPS6KA4, STK33 0.091
GO:0008013 Beta-catenin binding GLI3, DACT3, PTPRK 0.095
GO:0003700 Transcription factor binding FOS, PBX2, HDAC5, TWIST1, MYC 0.100
Pathways
Transcriptional misregulation in cancer CEBPE, LMO2, CSF1R, CDK14, MYC, ELANE 0.0014
MAPK signaling pathway FOS, PTPN7, MYC, RPS6KA4 0.010
PI3K-Akt signaling pathway DDIT4, GNG4, ANGPTL1, COL1A1, CSF1R, FGFR3, MYC 0.041
Pathway in cancer FOS, GNG4, GLI3, WNT11, CSF1R, FGFR3, MYC 0.069
Hippo signaling pathway WWCI, WNT11, MYC, DLG3 0.10
Proteoglycans in cancer WNT11, PTPN6, TWIST1, MYC 0.18
Ras signaling GNG4, ANGPTL4, CSF1R, FGFR3 0.23
Phagosome TUBB2A, TUBB3 0.10

(DAVID software analysis, EASE score, p< 0.1)

Gene ontology (GO) profile after TSA, 5-Aza and TSA+5-Aza treatments in Kasumi 1 (DAVID software analysis, EASE score, p< 0.1) Identification of Differentially Expressed Genes by Venn Diagram Configuration In MV4-11, out of 9 common differentially expressed genes between TSA, 5-Aza and TSA+5-Aza treatments, 8 genes (DEF8, GUSBP1, TUBA1C, NDUFC2, ARIH2, STX12, MAP3K6, and RAB12) were commonly up-regulated, while HEMGN was commonly down-regulated in all treatments. Between TSA and 5-Aza treatments, SOCS3 and HIST1H2BN were commonly up-regulated, but PTPRC, GIMAP2, TPM2, CASP4, RUNX1-IT1, and STAT6 were commonly down-regulated. 16 genes were commonly up-regulated in both 5-Aza and TSA+5-Aza treatments (FAM200B, RBM17, C1orf50, TMEM120A, SETX, NAGPA, MCUR1, BBS4, ATG4A, SUGP2, and RHEB). 5 down-regulated genes in 5-Aza (FAM133A, GPR125, GNG11, REN, and HBD) shared common down-regulation with TSA+5-Aza treatments. No gene in common was differentially expressed between TSA and TSA+5-Aza treatments. 25, 16 and 38 genes were exclusively expressed in TSA, 5-Aza and TSA+5-Aza, respectively as shown in Figure 3(a) (p<0.05).
Figure 3(a)

Venn diagram illustrating the genes commonly and exclusively expressed after TSA, 5-Aza and TSA+5-Aza treatments in MV4-11 (adhered to gene selection criteria).

In Kasumi 1, there were 3 common differentially expressed genes across all treatments; 2 genes (ANGPTL4 and TUBB2A) and 1 gene (ADAM12) were commonly up-regulated and down-regulated, respectively. Whereas PTPN6 was either up-regulated in 5-Aza treatment or down-regulated in TSA. VSTM1 and KIF1A were commonly down-regulated in 5-Aza and TSA+5-Aza treatments. There were 36 genes commonly expressed in TSA and TSA+5-Aza treatments with 20 up-regulated and 16 down-regulated genes. 7, 41 and 31 genes were exclusively expressed in TSA, 5-Aza and TSA+5-Aza, respectively as shown in Figure 3(b) (p<0.05).
Figure 3(b)

Venn diagram illustrating the genes commonly and exclusively expressed after TSA, 5-Aza and TSA+5-Aza treatments in Kasumi 1(adhered to gene selection criteria).

Venn diagram illustrating the genes commonly and exclusively expressed after TSA, 5-Aza and TSA+5-Aza treatments in MV4-11 (adhered to gene selection criteria). Venn diagram illustrating the genes commonly and exclusively expressed after TSA, 5-Aza and TSA+5-Aza treatments in Kasumi 1(adhered to gene selection criteria). Quantitative real-time PCR (qRT-PCR) To verify the expression of genes, commonly up-regulated genes; SOCS3, TUBA1C, CCNA1, and MAP3K6 in MV4-11; ANGPTL4 and TUBB2A in Kasumi-1, and commonly down-regulated genes; STAT6, PTPRC and RUNX1 in MV4-11, ADAM12 and differentially expressed gene, PTPN6 in Kasumi 1 were selected for validation by qRT-PCR. The results were consistent with that of microarray in both MV4-11 and Kasumi 1 cell lines except for MAP3K6 in MV4-11 (Figure 4).
Figure 4

Validation of expression levels of selected genes by qRT- PCR

Validation of expression levels of selected genes by qRT- PCR The qRT-PCR results revealed a significant up- and down regulation of several genes in MV4-11 and Kasumi 1 treated with TSA and 5-Aza compared to non-treated cell lines. GAPDH and B2M were used as endogenous controls to which the expression was normalized. Shown in the bar graph is the standard error (SE) of duplicated samples.

Discussion

It was recognized that epigenetic changes serve as a mediator in cancer progression by the changes of gene expression. Epigenetic alterations are reported to concurrently disrupt the essential signaling pathway predisposed cell to uncontrolled growth, longer survival, and metastasis[   14 ]. Histone modifications and DNA hypermethylation are two known epigenetic mechanisms that largely impact the regulation of gene transcription. Histone modification by acetylation has been found to be significantly deficient in acute leukemia patients, compared with the normal individual[   15 ]. In this study, TSA acts by increasing the acetylation level by inhibiting HDAC activity in human leukemic cell lines. Histone acetylation is known to enhance the expression of specific genes that elicit extensive cellular morphology and metabolic changes, such as growth arrest, differentiation, and apoptosis[   16 ]. Aberrant DNA methylation was the most common epigenetic alteration in leukemia in which an increased level of DNA methylation was observed in AML at remission[        17 ]. 5-Aza reverts DNA methylation to induce antineoplastic activity either by global hypomethylation and direct cytotoxicity on abnormal hematopoietic cells in the bone marrow[   18 ]. 5-Aza inhibits DNMT thus to induce re-expression of the silenced genes to halt tumor growth, and to cause modest differentiation in transformed leukemic cell lines and primary AML[   19 ]. The current study found that both TSA and 5-Aza inhibit the growth of MV4-11 and Kasumi 1 cell lines in a dose-dependent manner. The IC50 of both treatments at 24 hours were lower in MV4-11, compared to Kasumi 1 which could suggest the inhibitory effect of the drugs were less sensitive in Kasumi 1 harboring t(8;21) than in MV4-11 with FLT3-ITD mutation. The variation in the IC50 values would also represent different expression signature in response to TSA and 5-Aza treatments. It is proposed that the genes which were commonly expressed within TSA, 5-Aza and TSA+5-Aza treatments were epigenetically regulated and involved in the pathogenesis of AML and may serve as candidates for potential biomarkers although they did not share similar GO profile and targeted different signaling pathways. DEF8, NDUFC2, GUSBP1, ARIH2, STX12 and HIST1H2BN were highly re-expressed (more than 100 folds) in either treatment of MV4-11, have not been previously discussed on their role in cancer except for HIST1H2BN. DEP8 is located at chromosome 16 encodes for an activator of intracellular signal transduction reported to carry single nucleotide polymorphism (SNP) rs4268748 at 16q24 with significantly associated with cell cycle regulator, CDK10 expression[   20 ]. GUSBP1 which was located at chromosome 5 were involved in transcriptional regulation by putative alternative promoters (PAPs)[        21 ]. ARIH2 primarily functions in neuronal differentiation was found to be tumor-specific in Glioblastoma multiforme (GBM) correlated with growth suppression in GBM cell lines[   22 ]. Treatment with 5-aza-2′-deoxycytidine resulted in gene re-expression of HIST1H2BN in malignant ovarian cancer[   23 ]. Differential down-regulation of HIST1H2BN was observed in meningiomas was associated with malignant progression[   24 ]. RAB12 is a member of RAS oncogene family, function as small GTPase for intracellular protein transport, activated in stimulus-dependent pattern and promote microtubules-dependent of the cell secretary-granule in mast cell[   25 ] and its up-regulation has been linked with colorectal cancer[   26 ]. The most optimal GO in MV4-11 were Cytoskeleton organization involving TUBA1C, JAK-STAT cascade involving SOCS3 and STAT6 and the cell cycle involving CCNA1, associated with Phagosome, JAK-STAT pathway and Viral carcinogenesis, respectively, CCNA1 was expressed after TSA treatment with high fold-change (298.44) in MV4-11, but was slightly re-expressed at a low level in 5-Aza and combination treatment (fold-change: 5.67 and 2.81, respectively) (results not shown). CCNA1, located at chromosome 13, encodes for activating regulatory subunit which binds to cyclin-dependent kinases 2 (CDK2) and cell division cycle 2 (CDC2) for the cell cycle machinery to progress into S phase[   27 ]. In normal cells, CCNA1 was prominently expressed in testes, hematopoietic cells, and brain[   28 ]. CCNA1 acts as tumor suppressor gene (TSG) which is epigenetically silenced by hypermethylation in cervical cancer[   29 ], ovarian, renal and lung carcinoma[        30 ]. In AML, CCNA1 was found to be overexpressed especially in M3 and M2 AML with significant worse overall survival[   31 ]. In addition, upregulation of CCNA1 was observed in leukemic cells in response to DNA damaging agents by increasing DNA repair process[   32 ]. SOCS3, located at chromosome 17 is the known mediators in the JAK-STAT pathway which is strongly related to AML pathogenesis due to its function in blood lineage differentiation, apoptosis, and proliferation[        33 ]. SOCS1, SOCS2 and SOCS3 negatively regulate JAK-STAT signaling in AML patients carrying a FLT3-ITD mutation[        34 ]. SOCS3 has been extensively studied for over 20 years for their role in various diseases, especially in cancer. The most widely reported in SOCS3 was aberrant methylation affecting gene expression and protein function. Hypermethylation of promoter region of SOCS3 resulted in gene silencing implicated in cancer pathogenesis including hematological malignancies[   35 ], prostate cancer[   36 ], pancreatic cancer[   37 ], endometrial carcinoma[   38 ], hepatocellular carcinoma[   39 ] and breast cancer[        40 ]. Other candidate genes convoluted in the JAK-STAT pathway associated with hematological malignancies are STAT6 and RUNX1. TUBA1C, located at chromosome 12 is a member of tubulin family of microtubules ubiquitously expressed in the esophagus, bone marrow, appendix, brain, colon, bladder and placenta[   41 ]. TUBA1C expression was significantly increased in hepatocellular carcinoma (HCC) on both mRNA and protein level, which predict a poor prognosis[   42 ], reduced expression in breast cancer associated invasive stage[   43 ] and their expression was susceptible to colorectal cancer risk [   44 ]. Cytochrome P450 (CYP4F2) was the highest re-expressed gene in TSA treatment with more than 1000 fold-change in MV4-11. CYP4F2 is a drug-metabolizing enzyme gene reported to have an epigenetic regulatory role with clinical implication[   45 ]. Inhibition of DNMT and histone deacetylase (HDAC) by 5-Aza and TSA induced the demethylation of CYP1A1 and CYP1A2 leading to their up-regulation[   46 ]. In Kasumi 1, three common differentially expressed genes in either treatments were ANGPTL4, TUBB2A, and ADAM12 associated with angiogenesis, microtubule-based process, and cell-adhesion, respectively. ANGPTL4, located at chromosome 19 encodes a glycosylated, secreted protein containing a fibrinogen-like C-terminal domain, mainly induced by a nuclear receptor protein, peroxisome-proliferator-activated receptor (PPAR)[   47 ]. It is the most studied among ANGPLT family, functions primarily in the regulation of lipid metabolism, glucose homeostasis, and insulin sensitivity[   48 ]. ANGPTL4 has not been previously discussed in the context of AML. However previous studies have reported ANGPTL4 in various cancer types, including breast cancer, colorectal cancer, prostate cancer, hepatocarcinoma, and renal cell carcinoma, suggesting its important roles in cancer cell growth and progression[   49 ]. In the current study, ANGPTL4 was mutually up-regulated in TSA treatment in both MV4-11 and Kasumi 1 cell lines, thus has wide potential for gene-specific therapy in AML. TUBB2A, located at chromosome 6 is another putative gene in AML with cell-specific expression. It forms a class ll beta-tubulin from six families of tubulins, including, alpha, gamma, delta, epsilon and zeta, and their protein may localize in extracellular exosome, cytoplasm and nucleus, involved in small GTPase activity, GTP binding, nucleotide binding acetylation and methylation[   50 ]. Alpha and beta tubulin sub-families were studied for mutational analysis in human brain tumor and malformations was found in TUBB2A affecting the spectrum of "tubulinopathy" phenotypes[51], [52]. Mutations in TUBB2A were also explored in epilepsy[   51 ], gastric carcinoma and lung cancer[   53 ] but not hematological malignancies. ADAM12, located at chromosome 10 was over-expression in non-Hodgkin’s lymphoma that lead to accelerate of proliferation and cell-adhesion[   54 ] and was commonly methylated in chronic lymphocytic leukemia[        55 ]. The roles of ADAM12 in leukemia pathogenesis is still obscure and need further study since the expression of this gene was similarly down-regulated in both treatments. PTPN6 (or SHP1) located at chromosome 12 was differentially regulated in TSA and 5-Aza treatments (re-expressed only in 5-Aza but not TSA). Our previous study showed a positive correlation of PTPN6 re-activation due to hypomethylation in MV4-11 that carry a FLT3-ITD mutation after the 5-Aza treatment[   56 ]. PTPN6 expression has been studied in lymphoma, leukemia and other cancers such as breast cancer, ovarian cancer, prostate cancer, and pancreatic cancer[        57 ], and in hepatocellular carcinoma[   58 ]. PTPN6 is a downstream mediator in the JAK-STAT pathway, and together with SOCS3 they potentially serve as molecular indicators for pathway-targeted therapy in AML. Another example of the methylation-related gene is PRG2. In the Venn diagram, PRG2 was exclusively expressed in 5-Aza treatment, but not in TSA treatment. The differentially expressed PRG2 was reported in three human leukemic cell lines (K562, THP1, and HL-60)[   59 ]. We also previously reported that the expression of PRG2 was restored after 5-Aza treatment in PKC-412 (Midostaurin) resistant leukemic cell line[   56 ]. DHRS2 and LMTK3 were another highly up-regulated genes in TSA treatment in Kasumi 1 with up to 500 fold change. Their up-regulation was due to histone acetylation. Finally, despite thousands of genes generated by microarray expression profiling, the highly re-expressed and down-expressed genes perceived in this study were thought to be convoluted with epigenetic regulation of gene transcription in AML. Although only several genes were selected for validation by qRT-PCR, there were many other genes as discussed earlier that may have important roles in cancer pathogenesis.

CONCLUSION

In conclusion, we have identified common differently expressed genes that are importants in epigenetic regulation of AML. Our finding also revealed that Phagosome pathway was the most optimal and common in both MV4-11 and Kasumi 1 AML cell lines. Although MV4-11 and Kasumi 1 transduced different optimal signaling pathways in response to drug treatment, it was shown that MV4-11 mainly targeted the genes in the JAK-STAT signaling, while Kasumi 1 targeted the genes in transcriptional misregulation in cancer, PI3K-Akt and MAPK signaling, which are all critical pathways in oncogenesis. These were due to their different molecular characteristics (FLT3-ITD vs t(8;21) AML1-ETO). The data presented here may serve as a preliminary finding and are useful for further study to explore epigenetic involvement in the pathogenesis of AML.
Table 1(a)

Most up- and down-regulated genes in TSA treated MV4-11

Gene Bank Accession Gene symbol Gene description ( Homo sapiens) *Folds Change
NM_001082 CYP4F2 Cytochrome P450, family 4, subfamily F, polypeptide 21094.05
NM_014971 EFR3B EFR3 homolog B (S. cerevisiae) 360.59
NM_006569 CGREF1 Cell growth regulator with EF-hand domain 1348.85
NM_017702 DEF8 Differentially expressed in FDCP 8 325.92
NM_003914 CCNA1 Cyclin A1 298.44
NM_003255 TIMP2 TIMP metallopeptidase inhibitor 2281.56
NM_031313 ALPPL2 Alkaline phosphatase, placental-like 2250.36
NM_032704 TUBA1C Tubulin, alpha 1c234.14
NM_003955 SOCS3 Suppressor of cytokine signaling 3176.76
NM_001204054NDUFC2NADH dehydrogenase (ubiquinone) 1, subcomplex unknown 2166.94
NR_027028 GUSBP1 Glucuronidase, beta pseudogene 1153.18
NM_004522 KIF5C Kinesin family member 5C153.59
NM_003520 HIST1H2BN Histone cluster 1, H2bn150.13
NM_006321 ARIH2 Ariadne RBR E3 ubiquitin protein ligase 2133.61
NM_000612 IGF2 Insulin-like growth factor 2 131.09
NM_177424 STX12 Syntaxin 12103.73
NM_006086 TUBB3 Tubulin, beta 3 class III80.38
NM_004672 MAP3K6 Mitogen-activated protein kinase kinase kinase 639.50
NM_001025300RAB12member RAS oncogene family 38.83
NM_139314 ANGPTL4 Angiopoietin-like 426.79
NM_018437 HEMGN Hemogen-518.75
NM_024913 CPED1 Cadherin-like and PC-esterase domain containing 1-243.96
NM_003152 STAT5A Signal transducer and activator of transcription 5A-159.83
NM_002838 PTPRC Protein tyrosine phosphatase, receptor type C -138.75
NM_080612 GAB3 GRB2-associated binding protein 3-117.26
NM_003126 SPTA1 Spectrin, alpha, erythrocytic 1 -107.30
NM_015401 HDAC7 Histone deacetylase 7-88.16
NM_006563 KLF1 Kruppel-like factor 1 (erythroid)-85.08
NM_015660 GIMAP2 GTPase, IMAP family member 2-73.83
NM_006163 NFE2 Nuclear factor, erythroid 2-69.24
NM_213674 TPM2 Tropomyosin 2 (beta)-57.76
NM_006287 TFPI Tissue factor pathway inhibitor-55.30
NM_005021 ENPP3 pyrophosphatase/phosphodiesterase 3-49.49
NM_004688 NMI N-myc (and STAT) interactor-47.85
NM_000037 ANK1 Ankyrin 1, erythrocytic, transcript variant 3-46.78
NM_013427 ARHGAP6 Rho GTPase activating protein 6-42.54
NM_006546 IGF2BP1 Insulin-like growth factor 2 mRNA binding protein 1-42.54
NM_033306 CASP4 Caspase 4, apoptosis-related cysteine peptidase-42.42
NM_080588 PTPN7 Protein tyrosine phosphatase, non-receptor type 7-39.69
NM_004753 DHRS3 dehydrogenase/reductase (SDR family) member 3-36.59
NR_026812RUNX1-IT1RUNX1 intronic transcript 1 -22.05
NM_003153 STAT6 signal transducer and activator of transcription 6-10.04

*Folds-change of treatment group compared to control analyzed by Genespring software analysis, Moderated T-test, p<0.05)

Table 1(b)

Most up- and down-regulated genes in 5-Aza treated MV4-11

Gene Bank Accession Gene symbol Gene description ( Homo sapiens) *Folds change
NM_001145191 FAM200B family with sequence similarity 200, member B 461.79
NM_032905 RBM17 RNA binding motif protein 17336.98
NM_017702 DEF8 differentially expressed in FDCP 8 homolog 277.69
NM_024097 C1orf50 chromosome 1 open reading frame 50207.14
NM_001204054 NDUFC2 NADH dehydrogenase 185.92
NM_006321 ARIH2 ariadne RBR E3 ubiquitin protein ligase 2 158.81
NR_027028 GUSBP1 glucuronidase, beta pseudogene 1, non-coding RNA157.88
NM_032704 TUBA1C tubulin, alpha 1c 154.28
NM_031925 TMEM120A transmembrane protein 120A 135.01
NM_003955 SOCS3 suppressor of cytokine signaling 3 120.31
NM_015046 SETX Homo sapiens senataxin 95.04
NM_016256] NAGPA N-acetylglucosamine-1-phosphodiester alpha-N-acetylglucosaminidase 93.98
NM_001031713 MCUR1 mitochondrial calcium uniporter regulator 1 92.49
NM_033028 BBS4 Bardet-Biedl syndrome 490.09
NM_177424 STX12 syntaxin 12 89.59
NM_003520 HIST1H2BN histone cluster 1, H2bn 89.53
NM_052936] ATG4A autophagy related 4A, cysteine peptidase85.61
NM_014884 SUGP2 SURP and G patch domain containing 270.67
NM_138501 TECR trans-2,3-enoyl-CoA reductase69.28
NM_004672 MAP3K6 mitogen-activated protein kinase kinase kinase 6 48.45
NM_005614 RHEB Homo sapiens Ras homolog enriched in brain 45.97
NM_013230 CD24 CD24 molecule 45.50
NM_001025300 RAB12 RAB12, member RAS oncogene family 44.06
NM_173698 FAM133A family with sequence similarity 133, member A-101.93
NM_014653 WSCD2 WSC domain containing 2 -30.48
NM_145290 GPR125 G protein-coupled receptor 125 -29.51
NM_020353 PLSCR4 phospholipid scramblase 4 -28.02
NM_001099921 MAGEB16 melanoma antigen family B, 16 -27.19
NM_033306 CASP4 caspase 4, apoptosis-related cysteine peptidase-23.01
NM_004126 GNG11 guanine nucleotide binding protein (G protein), gamma 11-22.73
NM_144722 SPEF2 sperm flagellar 2-20.86
NM_015660 GIMAP2 GTPase, IMAP family member 2 -19.99
NR_027755 LINC00922 long intergenic non-protein coding RNA 922, long non-coding RNA -19.17
NM_018437 HEMGN hemogen-18.55
NM_001005285 OR2AT4 olfactory receptor, family 2, subfamily AT, member 4-18.19
NM_000537 REN renin -17.26
NM_000519 HBD hemoglobin, delta -16.75
NM_213674 TPM2 tropomyosin 2 (beta) -16.59
NM_002421 MMP1 matrix metallopeptidase 1 -12.23
NM_000361 THBD thrombomodulin -11.98
NM_005807 PRG4 proteoglycan 4-11.81
NM_080429 AQP10 aquaporin 10 -11.33
NM_139022 TSPAN32 tetraspanin 32-10.78
NM_024711 GIMAP6 GTPase, IMAP family member 6-10.55
NM_002145 HOXB2 homeobox B2 -10.22
NM_019032 ADAMTSL4 ADAMTS-like 4-9.71
NM_002838 PTPRC Protein tyrosine phosphatase, receptor type C -7.81
NR_026812RUNX1-IT1RUNX1 intronic transcript 1 -5.91
NM_003153 STAT6 signal transducer and activator of transcription 6-4.07
Table 1(c)

Most up- and down-regulated genes in TSA+5-Aza treated MV4-11

Gene Bank Accession Gene symbol Gene description ( Homo sapiens) *Folds change
NM_001145191FAM200BFamily with sequence similarity 200, member B 521.92
NM_197958LARP6La ribonucleoprotein domain family, member 6 506.68
NM_017702DEF8differentially expressed in FDCP 8 homolog 268.16
NR_027028GUSBP1Homo sapiens glucuronidase, beta pseudogene 1 243.94
NM_032905RBM17RNA binding motif protein 17 160.05
NM_014773KIAA0141KIAA0141 (KIAA0141)157.47
NM_001204054NDUFC2NADH dehydrogenase (ubiquinone) 1, subcomplex unknown 2155.54
NM_016256NAGPAN-acetylglucosamine-1-phosphodiester alpha-N-acetylglucosaminidase 141.82
NM_032704TUBA1Ctubulin, alpha 1c 139.42
NM_013268LGALS13lectin, galactoside-binding, soluble 13 132.17
NM_004187KDM5Clysine (K)-specific demethylase 5C 116.85
NM_024097C1orf50chromosome 1 open reading frame 50 113.21
NM_006321ARIH2ariadne RBR E3 ubiquitin protein ligase 2 97.43
NM_014035SNX24sorting nexin 24 94.35
NM_000600IL6interleukin 6 (interferon, beta 2) 91.55
NM_138433KLHDC7Bkelch domain containing 7B 89.54
NM_033028BBS4Bardet-Biedl syndrome 4 87.94
NM_177424STX12syntaxin 12 87.27
NM_015046SETXsenataxin 87.24
NM_001031713MCUR1mitochondrial calcium uniporter regulator 1 85.70
NM_001010893SLC10A5solute carrier family 10, member 5 79.58
NM_031925TMEM120Atransmembrane protein 120A 78.16
NM_006945SPRR2Dsmall proline-rich protein 2D 71.36
NM_052936ATG4AHomo sapiens autophagy related 4A, cysteine peptidase 70.34
NM_014945ABLIM3actin binding LIM protein family, member 3 68.78
NM_015701ERLEC1endoplasmic reticulum lectin 1 61.29
NM_004672 MAP3K6 mitogen-activated protein kinase kinase kinase 6 59.79
NM_006415SPTLC1serine palmitoyltransferase, long chain base subunit 1 59.76
NM_001025300RAB12RAB12, member RAS oncogene family 59.16
NM_005988SPRR2Asmall proline-rich protein 2A 58.97
NM_001080541MGAHomo sapiens MGA, MAX dimerization protein 56.75
NM_144569SPOCD1Homo sapiens SPOC domain containing 1 54.22
NM_018357LARP6Homo sapiens La ribonucleoprotein domain family, member 6 54.17
NM_206818OSCARosteoclast associated, immunoglobulin-like receptor 53.30
NM_017956TRMT12tRNA methyltransferase 12 homolog (S. cerevisiae) 52.10
NM_005614RHEBRas homolog enriched in brain 50.16
NM_012337CCDC19coiled-coil domain containing 19 50.03
NM_014884SUGP2SURP and G patch domain containing 2 47.37
NM_015335MED13Lmediator complex subunit 13-like 47.11
NM_173698FAM133Afamily with sequence similarity 133, member A -153.62
NM_145290GPR125G protein-coupled receptor 125 -78.33
NM_017521FEVHomo sapiens FEV -77.72
NM_001541HSPB2Homo sapiens heat shock 27kDa protein 2-67.21
NM_032501ACSS1Homo sapiens acyl-CoA synthetase short-chain family member 1 -63.80
NM_021992TMSB15Athymosin beta 15a -55.18
NM_012449STEAP1six transmembrane epithelial antigen of the prostate 1 -44.93
NM_017414USP18ubiquitin specific peptidase 18 -44.70
NM_001803CD52CD52 molecule -44.63
NM_004126GNG11guanine nucleotide binding protein (G protein), gamma 11 -42.81
NM_000519HBDhemoglobin, delta -40.08
NM_033258GNG8guanine nucleotide binding protein (G protein), gamma 8 -38.65
NM_138444KCTD12potassium channel tetramerization domain containing 12 -35.88
NM_002866RAB3ARAB3A, member RAS oncogene family -35.15
NM_014697NOS1APnitric oxide synthase 1 (neuronal) adaptor protein -35.11
NM_018437HEMGNhemogen -34.39
NM_207459]TEX19testis expressed 19 -33.52
NM_004982KCNJ8potassium inwardly-rectifying channel, subfamily J, member 8 -33.13
NM_013251TAC3tachykinin 3 222335545766788WWSSF BBGTT-30.44
NM_032333FAM213Afamily with sequence similarity 213, member A -29.38
NM_213599ANO5anoctamin 5 -29.37
NM_130776XAGE3X antigen family, member 3 -28.64
NM_002585PBX1pre-B-cell leukemia homeobox 1-28.42
NM_001110199SRRM3Homo sapiens serine/arginine repetitive matrix 3 -28.20
NM_000537REN renin-27.47

*Folds-change of treatment group compared to control analyzed by Genespring software analysis, Moderated T-test, p<0.05)

Table 2(a)

Most up- and down-regulated genes in TSA treated Kasumi 1

Gene Bank Accession Gene symbol Gene description ( Homo sapiens) *Folds change
NM_139314ANGPTL4angiopoietin-like 4791.26
NM_182908DHRS2dehydrogenase/reductase (SDR family) member 2612.16
NM_001069TUBB2Atubulin, beta 2A class IIa 574.87
NM_001080434LMTK3lemur tyrosine kinase 3 356.19
NM_138345VWA5B2von Willebrand factor A domain containing 5B2 331.00
NM_030630HID1HID1 domain containing 331.00
NM_006928PMELpremelanosome protein 323.68
NM_145056DACT3dishevelled-binding antagonist of beta-catenin 3269.03
NM_144698ANKRD35ankyrin repeat domain 35, 258.42
NM_014971EFR3BEFR3 homolog B (S. cerevisiae) 248.79
NM_004933CDH15cadherin 15, type 1, M-cadherin (myotubule) 221.35
NM_006086TUBB3tubulin, beta 3 class III205.73
NM_000088COL1A1collagen, type I, alpha 1 122.33
NM_017577GRAMD1CGRAM domain containing 1C109.67
NM_080860RSPH1radial spoke head 1 homolog 109.55
NM_003835RGS9regulator of G-protein signaling 9103.85
NM_001098722GNG4guanine nucleotide binding protein (G protein), gamma 4102.41
NM_005325HIST1H1Ahistone cluster 1, H1a 99.67
NM_018667SMPD3sphingomyelin phosphodiesterase 3, neutral membrane (neutral sphingomyelinase II)98.71
NM_033103RHPN2rhophilin, Rho GTPase binding protein 2 91.75
NM_007224NXPH4neurexophilin 488.57
NM_014226MOKMOK protein kinase73.56
NM_001077621VPS37Dvacuolar protein sorting 37 homolog D69.03
NM_001145028PALM3paralemmin 366.97
NM_177403RAB7BRAB7B, member RAS oncogene family-264.07
NM_005574LMO2Homo sapiens LIM domain only 2 (rhombotin-like 1)-215.33
NM_001004196CD200CD200 molecule-162.39
NM_001146ANGPT1angiopoietin 1-159.45
NM_003474ADAM12ADAM metallopeptidase domain 12-137.13
NM_003942RPS6KA4Homo sapiens ribosomal protein S6 kinase, 90kDa, polypeptide 4-136.39
NM_080588PTPN7protein tyrosine phosphatase, non-receptor type 7-133.96
NM_130782RGS18regulator of G-protein signaling 18 -119.12
NM_033101LGALS12lectin, galactoside-binding, soluble, 12-94.20
NM_002005FESFES proto-oncogene, tyrosine kinase-93.71
NM_080387CLEC4DC-type lectin domain family 4, member D -93.00
NM_024888LPPR3lipid phosphate phosphatase-related protein type 3-80.70
NM_012252TFECtranscription factor EC-77.90
NM_001805CEBPECCAAT/enhancer binding protein (C/EBP), epsilon -69.46
NM_014682ST18suppression of tumorigenicity 18, zinc finger-67.63
NM_002467MYCv-myc avian myelocytomatosis viral oncogene homolog-65.46
NM_005263GFI1growth factor independent 1 transcription repressor-64.45
NM_153615RGL4ral guanine nucleotide dissociation stimulator-like 4 -63.06
NM_002287LAIR1leukocyte-associated immunoglobulin-like receptor 1-59.78
NM_002586PBX2pre-B-cell leukemia homeobox 2-58.11
NM_005211CSF1Rcolony stimulating factor 1 receptor-55.40
NM_002831PTPN6protein tyrosine phosphatase, non-receptor type 6-52.38
NM_000442PECAM1platelet/endothelial cell adhesion molecule 1 -52.24

*Folds-change of treatment group compared to control analyzed by Genespring software analysis, Moderated T-test, p<0.05)

Table 2(b)

Most up- and down-regulated genes in 5-Aza treated Kasumi 1

Gene Bank Accession Gene symbol Gene description ( Homo sapiens) *Folds change
NM_021120DLG3discs, large homolog 3 (Drosophila)14.12
NM_033114ZCRB1zinc finger CCHC-type and RNA binding motif 1 12.82
NM_001110514EBF4early B-cell factor 4 12.63
NM_013271PCSK1Nproprotein convertase subtilisin/kexin type 1 inhibitor 11.11
NM_003278CLEC3BC-type lectin domain family 3, member B 9.44
NM_003456ZNF205zinc finger protein 2059.23
NM_005252FOSFBJ murine osteosarcoma viral oncogene homolog8.83
NM_002840PTPRFprotein tyrosine phosphatase, receptor type F8.83
NM_019058DDIT4DNA-damage-inducible transcript 4 8.17
NM_002728PRG2proteoglycan 2, bone marrow7.82
NM_001122962SIRPB2signal-regulatory protein beta 27.78
NM_001039580MAP9microtubule-associated protein 9 7.46
NM_080863ASB16ankyrin repeat and SOCS box containing 16 7.21
NM_021158TRIB3tribbles pseudokinase 36.95
NM_153334SCARF2scavenger receptor class F member 26.80
NM_002390ADAM11ADAM metallopeptidase domain 11 5.63
NM_032797AIFM2apoptosis-inducing factor, mitochondrion-associated 24.98
NM_004626WNT11wingless-type MMTV integration site family, member 11 4.90
NM_032271TRAF7TNF receptor-associated factor 7, E3 ubiquitin protein ligase 3.67
NM_001015053HDAC5histone deacetylase 53.67
NM_001069TUBB2Atubulin, beta 2A class IIa 2.67
NM_139314ANGPTL4angiopoietin-like 42.67
NM_002831PTPN6protein tyrosine phosphatase, non-receptor type 62.27
NM_001292030TTC39Ctetratricopeptide repeat domain 39C-70.59
NM_002844PTPRKprotein tyrosine phosphatase, receptor type K-32.81
NM_198481VSTM1V-set and transmembrane domain containing 1-32.49
NM_000099CST3cystatin C-26.47
NM_001244008KIF1Akinesin family member 1A-22.49
NM_001190467PRR36proline rich 36-21.97
NM_024422DSC2desmocollin 2-20.96
NM_001282735SPATS2Lspermatogenesis associated, serine-rich 2-like-18.59
NM_015238WWC1WW and C2 domain containing 1-16.52
NM_021199SQRDLsulfide quinone reductase-like (yeast)-15.53
NM_001838CCR7chemokine (C-C motif) receptor 7 -13.97
NM_000474TWIST1twist family bHLH transcription factor 1 -13.27
NM_012395CDK14cyclin-dependent kinase 14-13.19
NM_000168GLI3GLI family zinc finger 3 -12.65
NM_024940DOCK5dedicator of cytokinesis 5 -11.91
NM_030906STK33serine/threonine kinase 33-11.90
NM_001900CST5cystatin D -11.86
NM_006897HOXC9homeobox C9 -11.74
NM_005855RAMP1receptor (G protein-coupled) activity modifying protein 1 -11.55
NM_033292CASP1caspase 1, apoptosis-related cysteine peptidase-11.50
AK027605CYP2S1cytochrome P450, family 2, subfamily S, polypeptide 1 -11.02
NM_003474ADAM12ADAM metallopeptidase domain 12-7.681
NM_172217IL16interleukin 16-4.46
NM_001025300RAB12RAB12, member RAS oncogene f -4.89

*Folds-change of treatment group compared to control analyzed by Genespring software analysis, Moderated T-test, p<0.05)

Table 2(c)

Most up- and down-regulated genes in TSA+5-Aza treated Kasumi 1

Gene Bank Accession Gene symbol Gene description ( Homo sapiens) *Folds change
NM_182908DHRS2dehydrogenase/reductase (SDR family) member 2 758.66
NM_001080434LMTK3lemur tyrosine kinase 3 541.34
NM_001069TUBB2Atubulin, beta 2A class IIa 435.79
NM_139314ANGPTL4angiopoietin-like 4 429.60
NM_138345VWA5B2von Willebrand factor A domain containing 5B2 398.46
NM_030630HID1HID1 domain containing341.01
NM_006928PMELpremelanosome protein 282.05
NM_014971EFR3BEFR3 homolog B (S. cerevisiae) 263.45
NM_144698ANKRD35ankyrin repeat domain 35 220.61
NM_145056DACT3dishevelled-binding antagonist of beta-catenin 219.77
NM_004933CDH15cadherin 15, type 1, M-cadherin 190.60
NM_006086TUBB3tubulin, beta 3 class III 173.87
NM_001098722GNG4guanine nucleotide binding protein (G protein), gamma 4 167.50
NM_080860RSPH1radial spoke head 1 homolog (Chlamydomonas)146.52
NM_003835RGS9regulator of G-protein signaling 9 126.58
NM_007224NXPH4neurexophilin 4 124.19
NM_020770CGNcingulin 118.29
NM_001145028PALM3paralemmin 3 114.39
NM_000088COL1A1collagen, type I, alpha 1 111.63
NM_003933BAIAP3BAI1-associated protein 3 107.26
NM_017577GRAMD1CGRAM domain containing 1C 95.72
NM_052899GPRIN1G protein regulated inducer of neurite outgrowth 1 95.72
NM_005325HIST1H1Ahistone cluster 1, H1a 95.08
NM_033141MAP3K9mitogen-activated protein kinase kinase kinase 9 92.48
NM_198573ENHOenergy homeostasis associated 92.06
NM_001039570KREMEN1kringle containing transmembrane protein 1 91.54
NM_018667SMPD3sphingomyelin phosphodiesterase 391.24
NM_012253TKTL1transketolase-like 1 87.98
NM_002599PDE2Aphosphodiesterase 2A, cGMP-stimulated 84.11
NM_033259CAMK2N2calcium/calmodulin-dependent protein kinase II inhibitor 2 80.49
NM_014226MOKMOK protein kinase 79.66
NM_001678ATP1B2ATPase, Na+/K+ transporting, beta 2 polypeptide 78.33
NM_006500MCAMmelanoma cell adhesion molecule 75.94
NM_001077621VPS37Dvacuolar protein sorting 37 homolog D 74.87
NM_052924RHPN1rhophilin, Rho GTPase binding protein 1 74.59
NM_020127TUFT1tuftelin 1 73.36
NM_001040709SYPL2synaptophysin-like 2 70.97
NM_032432ABLIM2actin binding LIM protein family, member 2 70.76
NM_001024401SBK1SH3 domain binding kinase 1 68.42
NM_022742CCDC136coiled-coil domain containing 136 68.41
NM_021979HSPA2heat shock 70kDa protein 2 67.51
NM_000142FGFR3fibroblast growth factor receptor 365.65
NM_033103RHPN2rhophilin, Rho GTPase binding protein 2 65.01
NM_198196CD96CD96 molecule (CD96)-228.86
NM_001972ELANEelastase, neutrophil expressed -172.59
NM_001244008KIF1Akinesin family member 1A -171.82
NM_133374ZNF618zinc finger protein 618 -169.32
NM_020125SLAMF8SLAM family member 8 -158.07
NM_003974DOK2docking protein 2-153.14
NM_080387CLEC4DC-type lectin domain family 4, member D -143.62
NM_130782RGS18regulator of G-protein signaling 18 -110.02
NM_033101LGALS12lectin, galactoside-binding, soluble, 12 -107.48
NM_178443FERMT3fermitin family member 3 -106.90
NM_012072CD93CD93 molecule -102.56
NM_001946DUSP6dual specificity phosphatase 6 -98.76
NM_012252TFECtranscription factor EC -92.29
NM_002467MYCv-myc avian myelocytomatosis viral oncogene homolog-91.05
NM_001004196CD200CD200 molecule -87.76
NM_005814GPA33glycoprotein A33 (transmembrane) -82.88
NM_153615RGL4ral guanine nucleotide dissociation stimulator-like 4 -81.77
NM_080588]PTPN7protein tyrosine phosphatase, non-receptor type 7 -79.77
NM_014795ZEB2zinc finger E-box binding homeobox 2 -79.47
NM_005211CSF1Rcolony stimulating factor 1 receptor -74.06
NM_001146ANGPT1angiopoietin 1 -70.80
NM_006418OLFM4olfactomedin 4 -70.64
NM_014682ST18Homo sapiens suppression of tumorigenicity 18 -68.89
NM_177403RAB7BRAB7B, member RAS oncogene family -67.90
NM_198481VSTM1V-set and transmembrane domain containing 1 -66.89
NM_005187CBFA2T3core-binding factor, runt domain, alpha subunit 2; translocated to, 3 -61.51
NM_003474ADAM12ADAM metallopeptidase domain 12 -59.66
NM_005574LMO2LIM domain only 2 -58.27
NM_080387CLEC4DC-type lectin domain family 4, member D -54.65
NM_001805CEBPECCAAT/enhancer binding protein (C/EBP), epsilon -48.73

*Folds-change of treatment group compared to control analyzed by Genespring software analysis, Moderated T-test, p<0.05)

  49 in total

Review 1.  A decade of exploring the cancer epigenome - biological and translational implications.

Authors:  Stephen B Baylin; Peter A Jones
Journal:  Nat Rev Cancer       Date:  2011-09-23       Impact factor: 60.716

Review 2.  Genetic and epigenetic heterogeneity in acute myeloid leukemia.

Authors:  Sheng Li; Christopher E Mason; Ari Melnick
Journal:  Curr Opin Genet Dev       Date:  2016-05-07       Impact factor: 5.578

3.  Diversification of transcriptional modulation: large-scale identification and characterization of putative alternative promoters of human genes.

Authors:  Kouichi Kimura; Ai Wakamatsu; Yutaka Suzuki; Toshio Ota; Tetsuo Nishikawa; Riu Yamashita; Jun-ichi Yamamoto; Mitsuo Sekine; Katsuki Tsuritani; Hiroyuki Wakaguri; Shizuko Ishii; Tomoyasu Sugiyama; Kaoru Saito; Yuko Isono; Ryotaro Irie; Norihiro Kushida; Takahiro Yoneyama; Rie Otsuka; Katsuhiro Kanda; Takahide Yokoi; Hiroshi Kondo; Masako Wagatsuma; Katsuji Murakawa; Shinichi Ishida; Tadashi Ishibashi; Asako Takahashi-Fujii; Tomoo Tanase; Keiichi Nagai; Hisashi Kikuchi; Kenta Nakai; Takao Isogai; Sumio Sugano
Journal:  Genome Res       Date:  2005-12-12       Impact factor: 9.043

Review 4.  Epigenetic Regulation of Cytochrome P450 Enzymes and Clinical Implication.

Authors:  Xiaojing Tang; Shuqing Chen
Journal:  Curr Drug Metab       Date:  2015       Impact factor: 3.731

5.  Dynamic transcriptomes of human myeloid leukemia cells.

Authors:  Hai Wang; Haiyan Hu; Qian Zhang; Yadong Yang; Yanming Li; Yang Hu; Xiuyan Ruan; Yaran Yang; Zhaojun Zhang; Chang Shu; Jiangwei Yan; Edward K Wakeland; Quanzhen Li; Songnian Hu; Xiangdong Fang
Journal:  Genomics       Date:  2013-06-24       Impact factor: 5.736

6.  Frequent SOCS3 and 3OST2 promoter methylation and their epigenetic regulation in endometrial carcinoma.

Authors:  Haiyan Chen; Cuijuan Zhang; Yan Sheng; Shuzhe Yao; Zhiyan Liu; Cheng Zhang; Tingguo Zhang
Journal:  Am J Cancer Res       Date:  2014-12-15       Impact factor: 6.166

7.  SHP-1 Acts as a Tumor Suppressor in Hepatocarcinogenesis and HCC Progression.

Authors:  Liang-Zhi Wen; Kai Ding; Ze-Rui Wang; Chen-Hong Ding; Shu-Juan Lei; Jin-Pei Liu; Chuan Yin; Ping-Fang Hu; Jin Ding; Wan-Sheng Chen; Xin Zhang; Wei-Fen Xie
Journal:  Cancer Res       Date:  2018-05-18       Impact factor: 12.701

Review 8.  JAK/STAT signaling in hematological malignancies.

Authors:  W Vainchenker; S N Constantinescu
Journal:  Oncogene       Date:  2012-08-06       Impact factor: 9.867

9.  SOCS3 Methylation Predicts a Poor Prognosis in HBV Infection-Related Hepatocellular Carcinoma.

Authors:  Xin Zhang; Qingshan You; Xiaolei Zhang; Xiangmei Chen
Journal:  Int J Mol Sci       Date:  2015-09-18       Impact factor: 5.923

10.  Methylation of the suppressor of cytokine signaling 3 gene (SOCS3) in myeloproliferative disorders.

Authors:  Nasios Fourouclas; Juan Li; Daniel C Gilby; Peter J Campbell; Philip A Beer; Elaine M Boyd; Anne C Goodeve; David Bareford; Claire N Harrison; John T Reilly; Anthony R Green; Anthony J Bench
Journal:  Haematologica       Date:  2008-09-24       Impact factor: 9.941

View more
  2 in total

1.  Jiyuan Oridonin A Overcomes Differentiation Blockade in Acute Myeloid Leukemia Cells With MLL Rearrangements via Multiple Signaling Pathways.

Authors:  Mei Qu; Yu Duan; Min Zhao; Zhanju Wang; Mengjie Zhao; Yao Zhao; Haihua Wang; Yu Ke; Ying Liu; Hong-Min Liu; Liuya Wei; Zhenbo Hu
Journal:  Front Oncol       Date:  2021-03-26       Impact factor: 6.244

2.  Thymoquinone Inhibits Growth of Acute Myeloid Leukemia Cells through Reversal SHP-1 and SOCS-3 Hypermethylation: In Vitro and In Silico Evaluation.

Authors:  Futoon Abedrabbu Al-Rawashde; Muhammad Farid Johan; Wan Rohani Wan Taib; Imilia Ismail; Syed Ahmad Tajudin Tuan Johari; Belal Almajali; Abdullah Saleh Al-Wajeeh; Mansoureh Nazari Vishkaei; Hamid Ali Nagi Al-Jamal
Journal:  Pharmaceuticals (Basel)       Date:  2021-12-09
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.