Microarray profiling of HepG2 cells ectopically expressing NDRG2

Gene 503 (2012) 48–55

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Microarray profiling of HepG2 cells ectopically expressing NDRG2 Xuewu Liu 1, Tianshui Niu 1, Xingping Liu, Wugang Hou, Jing Zhang ⁎, Libo Yao ⁎ State Key Laboratory of Cancer Biology, Department of Biochemistry and Molecular Biology, The Fourth Military Medical University, Xi'an 710032, PR China

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Article history: Accepted 17 April 2012 Available online 25 April 2012 Keywords: NDRG2 p38 G protein signaling pathway Microarray

a b s t r a c t Previous studies have demonstrated that N-Myc downstream-regulated gene 2 (NDRG2) is a tumor suppressor that is downregulated in many human cancers and when overexpressed, can inhibit tumor growth and metastasis. However, its molecular function, its modulatory targets, and signaling pathways associated with it remain unclear. Here, in an effort to identify the genes modulated by NDRG2 expression, a microarray study was conducted to detect the expression profile of HepG2 cells overexpressing NDRG2 or LacZ. Gene Ontology (GO) biological process analysis revealed that genes related to G protein signaling pathway were upregulated. Five of them were selected and verified by real-time PCR. Gene sets related to M phase of cell cycle were downregulated. This was in agreement with cell cycle analysis. Signaling pathway analysis demonstrated apparent augmented hematopoietic cell lineage pathway and cell adhesion, but reduced glycosylphosphatidylinositol (GPI)-anchor biosynthesis, protein degradation and SNARE interactions. Furthermore, through motif analysis and experimental validation, we found that the p38 phosphorylation can be increased by NDRG2. Our research provides the molecular basis for understanding the role of NDRG2 in tumor cells and raises interesting questions about its mechanisms and potential use in cancer therapy. © 2012 Elsevier B.V. All rights reserved.

1. Introduction NDRG2 is a member of the N-Myc downstream-regulated (NDR) family of genes consisting of four members, designated as NDRG1, NDRG2, NDRG3 and NDRG4 in humans (Yao et al., 2008). All of these members contain the NDR domain, whose molecular function is unknown. Phylogenetic analysis of NDRG2 homologs has shown that NDR domains are found in Dictyostelium discoideum, Arabidopsis thaliana and Drosophila melanogaster, but not in bacteria and fungi. The structures of human NDRG2 and mouse Ndrg2 have been found to display remarkable similarity to the structure of the α/β-hydrolase (ABH) superfamily despite limited sequence similarity. Thus far, the substrate of NDRG2 has not been identified. As no catalytic signature residues have been found, NDRG2 is thought to be a non-enzymatic member of the ABH superfamily (Hwang et al., 2011). NDRG2 has gained much attention for its potential role in tumor suppression in many kinds of human cancers. A recent study showed

Abbreviations: NDRG2, N-myc downstream-regulated gene 2; GO, Gene Ontology; PCR, Polymerase chain reaction; GPI, Glycosylphosphatidylinositol; ABH, α/β-hydrolase; NGF, Nerve growth factor; MOI, Multiplicity of infection; PSMF, Phenylmethylsulfonyl fluoride; SAPK/JNK, Stress-activated protein kinase/c-Jun NH2-terminal kinase; ERK1/2, Extracellular signal-regulated protein kinases 1 and 2; PBS, Phosphate buffered saline; GSEA, Gene set enrichment analysis; PNH, Paroxysmal nocturnal hemoglobinuria; AD, Alzheimer's disease. ⁎ Corresponding authors. Tel.: + 86 29 84774513; fax: + 86 29 84774513. E-mail addresses: [email protected] (J. Zhang), [email protected] (L. Yao). 1 Co-first authors. 0378-1119/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.gene.2012.04.044

that NDRG2 expression is suppressed in hepatocellular carcinomas owing to promoter methylation and ectopic expression of NDRG2 suppressed the invasion and migration of hepatocellular carcinoma SK-Hep-1 cells (Lee et al., 2008). In colon cancer, NDRG2 expression was found to correlate significantly with high risk adenoma and colorectal carcinoma. Expression of NDRG2 showed a positive correlation with tumor differentiation and negative correlation with tumor invasion depth and Dukes' stage of adenocarcinoma (Lorentzen et al., 2007). Overexpression of NDRG2 in SW620 colon cancer cells reduced the expression of CTNNB1, which plays a pivotal role in carcinogenesis (Kim et al., 2009b). Suppressed expression of NDRG2 has also been observed in various kinds of breast cancers (Lorentzen et al., 2011), gastric cancers (Choi et al., 2007) and low-grade glioblastomas (Tepel et al., 2008). In contrast to reduced expression of NDRG2 in tumors, increased expression of NDRG2 was found during cell differentiation, aging and onset of diabetes. For example, nerve growth factor (NGF) is able to induce the differentiation and neurite outgrowth of PC12 cells. When PC12 cells were exposed to NGF, neurites began to sprout after one day, and NDRG2 expression was induced in a time-dependent manner. Overexpression of NDRG2 promoted neurites elongation, indicating that NDRG2 functions as a positive regulator of cell differentiation (Takahashi et al., 2005). In addition, it was found that NDRG2 expression is upregulated in Alzheimer's disease (AD) brains (Mitchelmore et al., 2004). Overexpression of NDRG2 in hippocampal pyramidal neurons of transgenic mice leads to accumulation of NDRG2 protein in dendritic processes. Although the biological effect of NDRG2 as a tumor suppressor has been observed in several cancers, the mechanism underlying these effects has not

X. Liu et al. / Gene 503 (2012) 48–55

been well-understood. Identification of the genes regulated by NDRG2 should provide a good starting point for unraveling the molecular basis of NDRG2 function. In the present study, we conducted microarrays, data mining, and subsequent experimental validation to investigate the molecules and cellular processes affected by NDRG2. We found that: (1) gene sets related to the G protein cascade were significantly upregulated by NDRG2 overexpression; (2) NDRG2 overexpression arrested HepG2 cells in the G2/M phase; (3) NDRG2 was able to increase the phosphorylation of p38. Our findings enhance our understanding of the roles of NDRG2 in various cellular processes.

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2.5. Cell cycle analysis

2. Materials and methods

HepG2 cells infected by adenoviruses expressing NDRG2 (AdNDRG2) or the negative control Lac Z (Ad-Lac Z) were harvested at the indicated time points. The cells were then washed twice with PBS and were suspended in 0.5 mL PBS. Absolute ethanol (1 mL) was then added to the cells. The cells were stained with a hypotonic propidium iodide solution (100 μg/ml), and subjected to flow cytometric analysis of cell cycle distribution using a LSR1 flow cytometer (Becton Dickinson). The software CellQuest Pro (Becton Dickinson) was used to determine the percentage of HepG2 cells in the G0/G1, S and G2/M phases. Three replicates of each sample were performed for cell cycle analysis.

2.1. Cell culture

2.6. Microarrays and GSEA analysis

HepG2 cells and HHCC cells were cultured in Dulbecco's Modified Eagle's Medium (DMEM, Gibco) supplemented with 10% fetal bovine serum (FBS) at 37 °C in a humidified incubator with 5% CO2.

HepG2 cells were harvested at different periods of time after AdNDRG2 or Ad-LacZ infection and used for RNA extraction. Microarray analysis was performed using the Affymetrix Genechip human Gene 1.0 ST array (Shanghai Biochip Co. Ltd.). The cDNA preparation, labeling, hybridization, washing and scanning were conducted according to the Affymetrix Genechip Standard Protocol. Data was collected using GCOS software and normalized by Robust Multichip average (RMA). For Gene Set Enrichment Analysis (GSEA), gene sets were acquired from MSigDB collections (Subramanian et al., 2005). Gene sets with less than 10 genes were excluded. For a gene targeted by multiple probes, the reporter with the highest value was used. Data were analyzed using the GSEA2 software.

2.2. Gene infection Gene infection was performed as previously described (Zheng et al., 2011). Briefly, a multiplicity of infection (MOI) of 40 was determined experimentally for HepG2 cells. Cells were seeded on plates and incubated to reach about 80% confluence. After removing the growth medium, adenoviruses expressing NDRG2 or the control gene LacZ were added to HepG2 cells with serum free medium, incubated for 2 h, replaced with growth medium and incubated for different periods of time. 2.3. Real-time polymerase chain reaction (real-time PCR) Total RNA was extracted and reverse transcribed according to the procedure described previously (Zheng et al., 2011). The first cDNA obtained was used as a template for real-time PCR. Primers used in our study are listed in Supplementary Table A. Gene expression was detected with SYBR Green PCR Master Mix using the ABI PRISM 7500 Sequence Detection System (Applied Biosystems, UK). The reaction system consisted of 10 μL of SYBR Green PCR Master Mix, 500 nM of the forward and reverse primers and 3 μL template in a total volume of 20 μL. The thermal cycling conditions were as follows: 95 °C for 5 min, followed by 45 cycles of 95 °C for 5 s, 60 °C for 34 s. The relative mRNA level for each gene was calculated using ΔΔC T method (Livak and Schmittgen, 2001). β-actin was used as an internal control for normalization. 2.4. Western blot analysis Cells were harvested and lysed in lysis buffer containing 20 mM Tris, pH 7.4, 150 mM NaCl, 1% Triton X-100, 5 mM EDTA, 10 μg/ml leupeptin, 10 μg/ml aprotinin, and 1 mM PSMF. Protein concentration was determined using the BCA protein assay kit (Pierce). A total of 60 μg of cell lysate was loaded per lane for separation by electrophoresis and the protein was subsequently transferred to PVDF membranes. The membranes were blocked with 5% fat free milk in Tris buffered saline for 1 h at room temperature. The primary antibodies were added to membranes and incubated overnight at 4 °C. Primary antibodies used in the study included anti-NDRG2 (Abnova), anti-α-tubulin, anti-GAPDH (Boster), anti-p38, anti-phospho-p38, anti-JNK/SAPK, anti-phospho-JNK/SAPK, anti-ERK1/2, anti-phospho-ERK1/2 (Cell Signaling). After washing three times with PBS, the membranes were incubated with secondary antibody conjugated with IRDye™800 (1:10,000 dilution; Rockland Inc). The blots were then imaged by using the Odyssey infrared imaging system (LI-COR Inc.). Western blot analysis was repeated at least three times.

2.7. Statistic analysis Statistic analysis was performed using statistic toolbox of Matlab7.1. Data were summarized as mean± SD. One-way ANOVA was used for comparison between groups. P b 0.05 was considered to be statistically significant. 3. Results 3.1. Identification of genes regulated by NDRG2 overexpression As NDRG2 expression has been reported to be suppressed in liver tumors, we ectopically expressed NDRG2 in HepG2 cells, which is the most common cellular model for human liver tumor and has lower NDRG2 expression comparing with HHCC cells (Fig. 1A). HepG2 cells were infected with adenovirus expressing NDRG2 (Ad-NDRG2) or the control gene LacZ (Ad-LacZ) for different periods of time. Western blot analysis showed that NDRG2 overexpression was successfully achieved by this method (Fig. 1B, upper panel). Importantly, overexpression of LacZ had no effect on the expression of NDRG2 in HepG2 cells (Fig. 1B, lower panel). To identify the genes whose expression levels were changed by NDRG2 overexpression, we used Affymetrix chips (HuGene-1_0-st) to examine gene expression profiles of HepG2 cells overexpressing NDRG2 or LacZ. As shown in Fig. 1C, the NDRG2 expression observed in microarrays was at least 50-fold increase. The expression profiles of HepG2 cells expressing NDRG2 and LacZ were very similar, indicating that expression of only a small number of genes was altered by NDRG2 overexpression. We found that NDRG2 overexpression had the strongest effect on gene expression at 36 h with 23 upregulated and 235 downregulated probes showing at least 2-fold changes in expression. Fig. 1D shows the top 20 genes whose expression levels were decreased or increased by NDRG2 overexpression at 36 h. To validate the gene expression patterns observed in our experiment, we verified 9 genes whose expression levels had been reported to be regulated by NDRG2 overexpression in the previous studies (Kim et al., 2008; Kim et al., 2009a; Kim et al., 2009b; Lee et al., 2008; Liu

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Fig. 1. Identification of genes regulated by NDRG2 expression. (A) Western blot analysis of NDRG2 expression in HepG2 cells and HHCC cells. The data was from a representative experiment repeated three times with similar results. (B) NDRG2 expression pattern in HepG2 cells infected with Ad-NDRG2 (upper panel) or Ad-LacZ (lower panel). HepG2 cells were infected with Ad-NDRG2 or Ad-LacZ, then harvested at indicated time points and analyzed by Western blot. The data was from a representative experiment repeated three times with similar results. (C) Scatter plot comparing gene expression profiles between Ad-NDRG2 and Ad-LacZ cell lines. The two slope lines indicate 2-fold differences in either direction in gene expression. Yellow dot represents NDRG2 probe. (D) Heat map of top 20 genes upregulated or downregulated by NDRG2 overexpression. Genes were clustered using Pearson correlation as distance metrics.

et al., 2010; Park et al., 2007; Shon et al., 2009; Zheng et al., 2011). As shown in Table 1, among those genes, the expression patterns of 8 genes were found to be consistent with previous results, although the fold change values of them are less than one. However, we did not observe apparent increase in the expression of BMP4 as previously reported, which could be attributed to the different cell line used in our study. In order to extract meaningful information from our microarray data, we ranked probes based on their expression value in cells expressing NDRG2 relative to those expressing LacZ, and performed Table 1 Expression patterns of validated genes. Genes

Reported alteration caused by NDRG2

Fold change (log2)

References

CD24

Decreased

− 0.71

PDGFA VEGFA MITF CCND1

Decreased Decreased Decreased Decreased

− 0.18 − 0.24 − 0.64 − 0.25

BMP4

Increased

Zheng et al. (2011) Liu et al. (2010) Liu et al. (2010) Kim et al. (2008) Kim et al. (2009a) Shon et al. (2009) Park et al. (2007) Lee et al. (2008) Kim et al. (2009b)

SOCS1 Increased LAMB3 Decreased CTNNB1 Decreased

0.09 0.45 − 0.30 − 0.25

GSEA using gene sets published in the MSigDB database. Our analysis included Gene Ontology biological process analysis, signaling pathway analysis and motif analysis.

3.2. Gene Ontology biological process analysis To identify the biological processes altered by NDRG2 overexpression, we performed enrichment analysis on microarrays. Fig. 2A is a Venn diagram showing the gene sets significantly enriched among the upregulated or downregulated genes at different time points. No gene set was enriched at 6 h, and only one gene set was enriched among the downregulated genes at 18 h, demonstrating that NDRG2 overexpression altered the transcription of only a few genes at early stages. However, at 36 h, a total of 151 gene sets were enriched. The top 20 gene sets significantly enriched among upregulated and downregulated genes at 36 h are shown in Table 2. Among the upregulated genes, we found that gene set ‘synaptic transmission’ was enriched, suggesting that NDRG2 expression has a role in the process of communication from a neuron to a target across a synapse. This is in agreement with previous findings that NDRG2 locates within growth cone, functions in synaptic transduction and overexpression of NDRG2 induces the formation of synapse (Nichols et al., 2005; Takahashi et al., 2005). In addition, the gene sets ‘potassium ion transport’ and ‘detection of stimulus’ were significantly enriched among upregulated genes. Whether NDRG2 has a role in these biological processes needs further experimental validation.

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Fig. 2. Gene Ontology biological process analysis. (A) Venn diagrams of enriched gene sets in gene expression profiles of HepG2 cells overexpressing NDRG2 or LacZ at different time points. Number of enriched gene sets is denoted in parentheses. (B) Enrichment plots of the GPCR signaling pathway. Bottom, plot of ranked list of genes. Y axis, value of the ranking metric, X axis, rank for all genes. Genes with expressions that correlated the most with NDRG2 overexpression get the highest metrics score and are located at the left edge of the list. (C) Real-time PCR validation of selected genes in HepG2 cells overexpressing NDRG2 and LacZ. Those five genes are ARHGEF25, GNB3, PIR3R6, DGKH and ITPR3. The last panel is the expression of NDRG2. Results are presented as mean ± SD for 3 replicates. (D) Cell cycle analysis of HepG2 cells. Results are presented as the average of 3 replicates. (E) Growth curve of HepG2 cells infected with Ad-NDRG2 or Ad-LacZ.

Interestingly, the G protein signaling pathway was enriched among upregulated genes, implying that NDRG2 potentially enhances the G protein signaling pathway (Fig. 2B). Five genes of this signaling pathway were chosen and verified by real-time PCR. We found expression of all five of those genes to be increased by NDRG2 overexpression, although they all showed less than two fold change (Fig. 2C). These

results indicate that increased expression of NDRG2 potentially leads to activation of G protein signaling pathway. Among the downregulated genes, we found reduced expression of genes related to cofactor metabolic process, M phase and DNA repair. Although NDRG2 has been shown to be involved in inhibition of tumor metastasis, we did not observe gene sets related to cell

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Table 2 The top 20 GO biological process gene sets enriched among upregulated or downregulated genes at 36 h. Upregulated genes

Downregulated genes

POTASSIUM_ION_TRANSPORT SYNAPTIC_TRANSMISSION SENSORY_PERCEPTION_OF_CHEMICAL_STIMULUS BEHAVIOR DETECTION_OF_STIMULUS_INVOLVED_IN_SENSORY_PERCEPTION G_PROTEIN_COUPLED_RECEPTOR_PROTEIN_SIGNALING_PATHWAY SECOND_MESSENGER_MEDIATED_SIGNALING INNATE_IMMUNE_RESPONSE TRANSMISSION_OF_NERVE_IMPULSE DETECTION_OF_CHEMICAL_STIMULUS NEUROLOGICAL_SYSTEM_PROCESS CELL_CELL_SIGNALING CELLULAR_DEFENSE_RESPONSE REGULATION_OF_RESPONSE_TO_EXTERNAL_STIMULUS LOCOMOTORY_BEHAVIOR CALCIUM_MEDIATED_SIGNALING DETECTION_OF_STIMULUS CELL_RECOGNITION POLYSACCHARIDE_METABOLIC_PROCESS REGULATION_OF_DEFENSE_RESPONSE

PHOSPHOINOSITIDE_BIOSYNTHETIC_PROCESS PHOSPHOINOSITIDE_METABOLIC_PROCESS M_PHASE_OF_MITOTIC_CELL_CYCLE M_PHASE MITOSIS NUCLEOTIDE_EXCISION_REPAIR RNA_PROCESSING GLYCEROPHOSPHOLIPID_BIOSYNTHETIC_PROCESS PROTEIN_AMINO_ACID_LIPIDATION GOLGI_VESICLE_TRANSPORT COFACTOR_METABOLIC_PROCESS CELLULAR_RESPIRATION LIPOPROTEIN_BIOSYNTHETIC_PROCESS DNA_REPAIR CELL_CYCLE_PROCESS TRNA_METABOLIC_PROCESS AEROBIC_RESPIRATION RESPONSE_TO_DNA_DAMAGE_STIMULUS CELL_CYCLE_PHASE DNA_REPLICATION_INITIATION

A gene set with p b 0.05 and false discovery rate (FDR) less than 0.25 was considered to be significant. Gene sets were ranked by their normalized enrichment score (NES).

Table 3 Signaling pathways enriched among the upregulated or downregulated genes at 36 h. Upregulated genes

Downregulated genes

KEGG_HEMATOPOIETIC_CELL_LINEAGE KEGG_NEUROACTIVE_LIGAND_RECEPTOR_INTERACTION KEGG_OLFACTORY_TRANSDUCTION KEGG_ARRHYTHMOGENIC_RIGHT_VENTRICULAR_CARDIOMYOPATHY_ARVC KEGG_ASTHMA KEGG_CELL_ADHESION_MOLECULES_CAMS KEGG_HEDGEHOG_SIGNALING_PATHWAY KEGG_TYPE_I_DIABETES_MELLITUS KEGG_TASTE_TRANSDUCTION KEGG_GAP_JUNCTION KEGG_LONG_TERM_DEPRESSION

KEGG_GLYCOSYLPHOSPHATIDYLINOSITOL_GPI_ANCHOR_BIOSYNTHESIS KEGG_VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATION KEGG_RNA_POLYMERASE KEGG_RNA_DEGRADATION KEGG_UBIQUITIN_MEDIATED_PROTEOLYSIS KEGG_HOMOLOGOUS_RECOMBINATION KEGG_PROPANOATE_METABOLISM KEGG_TERPENOID_BACKBONE_BIOSYNTHESIS KEGG_PEROXISOME KEGG_AMINOACYL_TRNA_BIOSYNTHESIS KEGG_NUCLEOTIDE_EXCISION_REPAIR KEGG_CYTOSOLIC_DNA_SENSING_PATHWAY KEGG_PYRUVATE_METABOLISM KEGG_CELL_CYCLE KEGG_CITRATE_CYCLE_TCA_CYCLE KEGG_PORPHYRIN_AND_CHLOROPHYLL_METABOLISM KEGG_SELENOAMINO_ACID_METABOLISM KEGG_SNARE_INTERACTIONS_IN_VESICULAR_TRANSPORT KEGG_HISTIDINE_METABOLISM KEGG_PARKINSONS_DISEASE KEGG_PURINE_METABOLISM KEGG_BASAL_TRANSCRIPTION_FACTORS KEGG_MISMATCH_REPAIR KEGG_PROTEIN_EXPORT KEGG_BASE_EXCISION_REPAIR KEGG_DNA_REPLICATION KEGG_BUTANOATE_METABOLISM KEGG_RIG_I_LIKE_RECEPTOR_SIGNALING_PATHWAY KEGG_AMINO_SUGAR_AND_NUCLEOTIDE_SUGAR_METABOLISM KEGG_HUNTINGTONS_DISEASE KEGG_LYSINE_DEGRADATION KEGG_TRYPTOPHAN_METABOLISM KEGG_N_GLYCAN_BIOSYNTHESIS KEGG_PYRIMIDINE_METABOLISM KEGG_GLYCOLYSIS_GLUCONEOGENESIS KEGG_SYSTEMIC_LUPUS_ERYTHEMATOSUS KEGG_LYSOSOME KEGG_ONE_CARBON_POOL_BY_FOLATE KEGG_ARGININE_AND_PROLINE_METABOLISM KEGG_P53_SIGNALING_PATHWAY KEGG_FATTY_ACID_METABOLISM KEGG_PANCREATIC_CANCER KEGG_TOLL_LIKE_RECEPTOR_SIGNALING_PATHWAY KEGG_SMALL_CELL_LUNG_CANCER KEGG_ALZHEIMERS_DISEASE

A gene set with p b 0.05 and false discovery rate (FDR) less than 0.25 was considered to be significant. Gene sets were ranked by their normalized enrichment score (NES).

X. Liu et al. / Gene 503 (2012) 48–55 Table 4 Motif gene sets enriched among the upregulated genes at 6 h and 18 h.

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Table 5 Motif gene sets enriched among the downregulated genes at 6 h and 18 h.

6h

18 h

6 h and 18 h

6h

18 h

6 h and18 h

MEF2 NFAT HMGIY RREB1 SREBP1 RSRFC4 ATF4 MZF1 GATA1 AACWWCAANK PITX2 ER GGGNNTTTCC GCCNNNWTAAR AP1 AP2REP BACH1 OCT1 CAGNWMCNNNGAC STAT6 FXR RYTGCNNRGNAAC NFKB CATTGTYY TFIII TTF1 SF1 CTAWWWATA HOX13 AGCYRWTTC BACH2 ATF3 NRF2 PAX4 NKX25 LMO2COM TBP CEBPDELTA CREB ERR1 RORA1 POU3F2 ATF1 ISRE GATA6

TTF1 PXR NFKB STAT6 FXR ATCMNTCCGY NRF2 NFAT MEF2 YAATNRNNNYNATT ATF4 SF1 GGGNNTTTCC GATA1 TATA ER CREBP1 AP1 OCT1 AACWWCAANK GCCNNNWTAAR PITX2 GATA6 RSRFC4 TFIII CATTGTYY RORA1 TAL1BETAE47 SREBP1 LMO2COM HMGIY AP2GAMMA FOXD3 TAAWWATAG BACH1 PAX3 ETS1 CTAWWWATA MYOD BACH2

OCT1 AACWWCAANK AP1 ATF4 BACH1 BACH2 CATTGTYY CTAWWWATA ER FXR GATA1 GATA6 GCCNNNWTAAR GGGNNTTTCC HMGIY LMO2COM MEF2 NFAT NFKB NRF2 PITX2 RORA1 RSRFC4 SF1 SREBP1 STAT6 TFIII TTF1

KRCTCNNNNMANAGC

KRCTCNNNNMANAGC TTTNNANAGCYR GTTGNYNNRGNAAC

None

A gene set with p b 0.05 and false discovery rate (FDR) less than 0.25 was considered to be significant. Gene sets were ranked by their normalized enrichment score (NES).

migration to be significantly downregulated. The gene set ‘M phase’ was enriched among the downregulated genes, suggesting that overexpression of NDRG2 may lead HepG2 cells to M phase arrest. To verify our speculation, we performed cell cycle analysis. As expected, overexpression of NDRG2 resulted in significant increase in the percentage of M phase cells at 36 h compared to the control (Fig. 2D). Additionally, cells expressing NDRG2 exhibited growth retardation (Fig. 2E). Taken together, these data show that NDRG2 induces cell cycle arrest of HepG2 cells by downregulating the expression of genes involved in M phase. 3.3. Signaling pathway analysis The next step in our analysis was identification of the cellular pathways enriched among the regulated genes. As shown in Table 3, among the upregulated genes, we found that genes involved in the hematopoietic cell lineage pathway had the highest score, indicating that this gene set was most represented by upregulated genes. As this gene set comprises genes engaging the differentiation process of blood cells, increased expression of these genes means that

A gene set with p b 0.05 and false discovery rate (FDR) less than 0.25 was considered to be significant. Gene sets were ranked by their normalized enrichment score (NES).

NDRG2 is involved in promoting differentiation of blood cells. These results are consistent with previous finding that NDRG2 is expressed during the differentiation of dendritic cells and in response to maturation-inducing stimuli (Choi et al., 2003). Additionally, the pathway related to cell adhesion was also found to be enriched among the upregulated genes. According to the KEGG database, this pathway is important for brain morphology and is described as having a role in establishing and maintaining synapses. Therefore, NDRG2 expression may promote the formation of synapses, which is in agreement with previous findings (Nichols et al., 2005). Among the downregulated genes, the signaling pathway related to glycosylphosphatidylinositol (GPI)-anchor biosynthesis was enriched the most. GPI anchors are necessary for proper localization and function of cell membrane proteins. Defects in GPI anchor biosynthesis genes result in paroxysmal nocturnal hemoglobinuria (PNH) (Pu and Brodsky, 2011). Therefore, NDRG2 overexpression can potentially induce PNH. Signaling pathways linked to protein degradation and SNARE interactions in vascular transport were also significantly enriched among the downregulated genes. Since decreased protein degradation has been implicated in Alzheimer's disease, NDRG2 expression may facilitate the onset of AD. Finally, decreased expression of genes participating in SNARE interactions demonstrates that overexpression of NDRG2 may cause reduction of cell secretion. 3.4. Motif analysis The genes that were observed to be upregulated or downregulated upon NDRG2 overexpression could be part of the downstream effectors activated or suppressed by the signaling cascade regulated by NDRG2. The downstream effectors regulate the transcription of genes through post-transcriptional modification of transcription factors. Therefore, identification of transcription factors whose activities were altered by NDRG2 overexpression would therefore help us discover the downstream effectors of NDRG2-mediated signaling. We performed enrichment analysis on the microarray data obtained at 6 h and 18 h using motif gene sets from MSigDB. As shown in Table 4, 28 motifs were found to be significantly enriched among upregulated genes both at 6 h and 18 h. On the other hand, only one and three motifs were identified among downregulated genes at 6 h and 18 h respectively (Table 5). Identities of the transcription factors that bind to these motifs are unclear. Among the motifs enriched in upregulated genes, MEF2A, AP1, ER and NFATC1 have been reported to be phosphorylated by p38 (Lee and Bai, 2002; Lim and Kim, 2011; Matsumoto et al., 2004; Yang et al., 1999), implying that p38 activity might be altered by NDRG2 overexpression. To evaluate whether the p38 activity was enhanced by NDRG2 overexpression, we examined the phosphorylation state of p38 in cells infected with different doses of Ad-NDRG2. Fig. 3A shows that NDRG2 overexpression induced phosphorylation of p38, but had no effect on the total expression levels of p38. We also tested the activity of other MAP kinases, including ERK1/2 and SAPK/JNK (Fig. 3B). However, the phosphorylation levels of these two kinases were not altered by NDRG2 overexpression. These results demonstrate that NDRG2 overexpression can specifically activate p38 in HepG2 cells.

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Fig. 3. Western blot analysis of the activities of p38, ERK1/2 and SAPK/JNK. HepG2 cells were infected with different doses of Ad-NDRG2. Ad-LacZ was added to cells to make sure the MOI of total adenoviruses was 40. Cells were harvested after 18 h and analyzed by Western blot. The data was from a representative experiment repeated four times with similar results. (A) Analysis of p38 activity induced by NDRG2 overexpression. (B) Analysis of the phosphorylation of ERK1/2 and SAPK/JNK.

4. Discussion Several studies have provided evidence for a negative correlation between NDRG2 expression and tumor growth and metastasis (Choi et al., 2007; Kim et al., 2009b; Lee et al., 2008; Zheng et al., 2011). However, the mechanism behind these effects remains unknown. In order to understand the role of NDRG2 as a tumor suppressor, it is important to first understand its molecular function, its modulatory targets, and the pathways it is associated with. In the present work, we aimed to identify the genes modulated by NDRG2 by conducting a microarray analysis of HepG2 cells overexpressing NDRG2 using an adenovirus-based expression system. We found that NDRG2 overexpression upregulated 23 genes and downregulated 235 genes with at least 2-fold change in expression. Additionally, we found that gene sets such as ‘synaptic transmission’ were enriched in upregulated genes. We also found components of the G protein signaling cascade to be enriched among the upregulated genes, which was further confirmed by real-time PCR. Activation of the G protein signaling pathway has been reported to occur during many biological processes, including neurotransmission, chemotaxis, proliferation and smooth muscle contraction (Cotton and Claing, 2009), implying that NDRG2 might affect multiple cellular processes by modulating the G protein signaling pathway. In addition, we found that genes linked to the M phase of cell cycle were downregulated and overexpression of NDRG2 arrested HepG2 cells in the M phase. As drugs like paclitaxel used in tumor chemotherapy are predominantly M-phase-specific (Shah and Schwartz, 2001), overexpression of NDRG2 in HepG2 cells should significantly enhance the efficacy of these drugs. Given this possibility, combining NDRG2 overexpression with administration of an M-phase-specific drug may be an attractive strategy for tumor chemotherapy. However, careful studies should be done before the application of NDRG2 in tumor chemotherapy, as NDRG2 overexpression can potentially cause PNH and decrease protein degradation according to our analysis of the signaling pathways affected by NDRG2 overexpression. In an attempt to identify the signaling pathways affected by NDRG2, we performed motif analysis on our microarray data. We analyzed microarray data obtained at 6 h and 18 h after infection of HepG2 cells with Ad-NDRG2 or Ad-LacZ based on the assumption that the downstream effectors should be rapidly activated or suppressed by NDRG2 overexpression, leading to changes in the expression of their downstream regulated genes. This method would also allow us to avoid genes regulated indirectly via the NDRG2 cascade. The results of our motif analysis led us to identify p38 as such an effector. Furthermore, we found that NDRG2 overexpression specifically activated p38, but did not change the activity of other MAP kinases like ERK1/2 and JNK/SAPK. Our results are consistent with previous findings that phosphorylation of p38 can be induced by NDRG2 overexpression in malignant breast cancer cells (Park et al., 2007). In contrast to our findings in HepG2 cells, however, phosphorylation of JNK/SAPK was also found to be increased by NDRG2 expression

in breast cancers cells. This may be attributed to differences in the cell lines used in the two studies. Although we conducted our microarray study relatively soon after induction of NDRG2 overexpression, we cannot rule out the possibility that phosphorylation of p38 was indirectly induced by the NDRG2 cascade. However, in light of the evidence for interaction between the β subunit of G protein with NDL1 (Mudgil et al., 2009), an NDRG2 homolog, in A. thaliana, it is likely that NDRG2 is able to directly activate p38, since p38 is a downstream effector of the G protein signaling pathway. Further experiments need to be done to test this hypothesis. 5. Conclusion In this study, we reported that NDRG2 is able to augment G protein signaling pathway, arrest cells in the M phase, and increase the phosphorylation of p38. Our findings further expand our understanding of NDRG2 and its role in tumor cells, and have important implications for targeting NDRG2 for cancer therapy. Supplementary data to this article can be found online at doi:10. 1016/j.gene.2012.04.044. Acknowledgments This study was supported by grants from the Nature Science Foundation of China (Grant numbers: 30830054, 31070681, 81170748 and 31171112). References Choi, S.C., et al., 2003. Expression and regulation of NDRG2 (N-myc downstream regulated gene 2) during the differentiation of dendritic cells. FEBS Lett. 553 (3), 413–418. Choi, S.C., et al., 2007. Expression of NDRG2 is related to tumor progression and survival of gastric cancer patients through Fas-mediated cell death. Exp. Mol. Med. 39 (6), 705–714. Cotton, M., Claing, A., 2009. G protein-coupled receptors stimulation and the control of cell migration. Cell. Signal. 21 (7), 1045–1053. Hwang, J., et al., 2011. Crystal structure of the human N-Myc downstream-regulated gene 2 protein provides insight into its role as a tumor suppressor. J. Biol. Chem. 286 (14), 12450–12460. Kim, A., et al., 2008. NDRG2 gene expression in B16F10 melanoma cells restrains melanogenesis via inhibition of Mitf expression. Pigment Cell Melanoma Res. 21 (6), 653–664. Kim, Y.J., et al., 2009a. NDRG2 suppresses cell proliferation through down-regulation of AP-1 activity in human colon carcinoma cells. Int. J. Cancer 124 (1), 7–15. Kim, Y.J., et al., 2009b. NDRG2 expression decreases with tumor stages and regulates TCF/ beta-catenin signaling in human colon carcinoma. Carcinogenesis 30 (4), 598–605. Lee, H., Bai, W., 2002. Regulation of estrogen receptor nuclear export by ligand-induced and p38-mediated receptor phosphorylation. Mol. Cell. Biol. 22 (16), 5835–5845. Lee, D.C., et al., 2008. Functional and clinical evidence for NDRG2 as a candidate suppressor of liver cancer metastasis. Cancer Res. 68 (11), 4210–4220. Lim, H., Kim, H.P., 2011. Matrix metalloproteinase-13 expression in IL-1beta-treated chondrocytes by activation of the p38 MAPK/c-Fos/AP-1 and JAK/STAT pathways. Arch. Pharm. Res. 34 (1), 109–117. Liu, S., et al., 2010. NDRG2 induced by oxidized LDL in macrophages antagonizes growth factor productions via selectively inhibiting ERK activation. Biochim. Biophys. Acta 1801 (2), 106–113. Livak, K.J., Schmittgen, T.D., 2001. Analysis of relative gene expression data using real-time quantitative PCR and the 2(−delta delta C(T)) method. Methods 25 (4), 402–408.

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