Advertisement
Article

Gene expression changes induced by green tea polyphenol (−)-epigallocatechin-3-gallate in human bronchial epithelial 21BES cells analyzed by DNA microarray

Ragini Vittal, Zachariah E. Selvanayagam, Yi Sun, Jungil Hong, Fang Liu, Khew-Voon Chin and Chung S. Yang
DOI:  Published September 2004

Abstract

Many studies suggest green tea is a cancer chemopreventive agent. This effect has been attributed to its major constituent (−)-epigallocatechin-3-gallate (EGCG). EGCG is also observed to have cytotoxic anticancer effects, especially when used in combination with certain chemotherapeutic agents. The biochemical actions of EGCG in chemoprevention and anticancer effects have been studied; however, the mechanisms of action are not clearly understood. We show here by expression genomics the effects of EGCG (25 μmol/L) in the Ha-ras gene transformed human bronchial epithelial 21BES cells. We found induction of temporal changes in gene expression and the coalescence of specific genetic pathways by EGCG. In this experimental system, hydrogen peroxide (H2O2) was produced. By treating cells with EGCG in the presence or absence of catalase, we further distinguished gene expression changes that are mediated by H2O2 from those that are H2O2 independent. Many genes and cellular pathways, including genes of the transforming growth factor-β signaling pathway, were H2O2 dependent because the effects were abolished by catalase. Gene expression changes that were not affected by catalase included those of the bone morphogenetic protein signaling pathway, peptidylprolyl isomerase (cyclophilin)–like 2, alkylated DNA repair enzyme alkB, polyhomeotic-like 2, and homeobox D1. We show further that EGCG and H2O2 differentially transactivated the bone morphogenetic protein and the transforming growth factor-β response element promoter reporters, respectively, thus confirming results from DNA microarray analysis. The elucidation of gene expression changes between H2O2-dependent and H2O2-independent responses helps us better understand the cancer chemopreventive and anticancer actions of EGCG.

Introduction

Some epidemiologic studies suggested that green tea, a widely consumed beverage, lowers the risk of certain types of cancers (1–3). Whereas tea contains several bioactive chemicals, it is particularly rich in catechins, of which (−)-epigallocatechin-3-gallate (EGCG) is most abundant and most active (1). Catechins and their metabolites are thought to contribute to the beneficial health effects ascribed to tea. In addition to its cancer preventive effects, EGCG has also been shown to have anticancer effects in various experimental systems including those of cervical, colon, stomach, and prostate cancers (1, 4–6). Recently, synergistic cytotoxic anticancer effects was also obtained when EGCG is applied in combination treatment with certain anticancer drugs (7–10). These chemosensitivity tests suggest that EGCG has a potential in adjuvant cancer therapy.

Many mechanisms have been proposed for the chemopreventive and anticancer activities of EGCG. These include the inhibition of telomerase, mitogen-activated protein kinase (MAPK), activator protein-1, nuclear factor-κB, binding of epidermal growth factor to its receptor, angiogenesis, and activation of apoptosis (11–18). These proposals suggest that EGCG may have pleiotropic effects in cells. Nevertheless, the targets for the chemopreventive and anticancer effects of EGCG have not been clearly elucidated.

EGCG have multiple biological effects by acting on different targets directly or indirectly. Further confounding the results is the generation of hydrogen peroxide (H2O2) when EGCG is added to cell culture system (19–23), thus raising questions about whether the reported biochemical effects of EGCG are attributable to EGCG directly or to H2O2. In our previous studies with human lung cancer cell lines and the Ha-ras gene transformed human bronchial epithelial 21BES cell line, EGCG was found to inhibit cell growth and to induce apoptosis (19, 20). The induction of apoptosis by EGCG in these cell lines was either partially or completely abolished in the presence of catalase, which decomposes H2O2.

Recent advances in gene expression profiling by DNA microarray have enabled genome-wide elucidation of the functional genomics of genes involved in various cellular pathways (24–30). We have shown recently that surveying genome-wide gene expression changes facilitates the identification of specific pathways essential for the tumor promoter 12-O-tetradecanoylphorbol-13-acetate–mediated differentiation in the human leukemia HL-60 cells (26). DNA microarray expression profiling of genes affected by EGCG has also been conducted with limited number of expressed sequence tag probes (5, 31, 32) and a few sampling of time points (either one or three time intervals) following EGCG treatment.

To further understand the anticancer and chemopreventive mechanisms of EGCG, we determined effect of EGCG on genome-wide expression profiles in 21BES cells. Our results show distinct temporal changes in gene expression induced by EGCG. Addition of catalase, which catalyzes the decomposition of H2O2, abolished a notable number of these gene changes such as transforming growth factor (TGF)-β2, SMAD3, and TSC22. Gene expression changes that are not inhibited by catalase include bone morphogenetic protein (BMP) type II receptor (BMPR2), peptidylprolyl isomerase (cyclophilin)–like 2, alkylated DNA repair enzyme alkB, and STAT5B. We show further that H2O2 transactivated TGF-β response element promoter activity and this transactivation was blocked by catalase, whereas EGCG transactivated BMP response element promoter and this effect was not influenced by catalase.

Materials and Methods

Cell Culture, Chemicals, and H2O2 Assay

The Ha-ras gene transformed human bronchial epithelial 21BES cell line was obtained from American Type Culture Collection (Rockville, MD) and maintained in LHC-9 medium (Biofluids, Rockville, MD). The purified green tea polyphenol EGCG was provided by Thomas J. Lipton Co. (Englewood Cliffs, NJ) and catalase was from Sigma Chemical Co. (St. Louis, MO).

Measurement of H2O2 production was conducted as described previously (21). In brief, EGCG (25 μmol/L) was added to LHC-9 medium either in the presence or in the absence of cells and with or without catalase (30 units/mL). At different time points, the amounts of H2O2 in medium were analyzed using an Amplex Red H2O2 assay kit (Molecular Probes, Eugene, OR).

DNA Microarray

DNA arrays were custom printed on 3 × 10 in. nylon membrane and contained ∼10,692 DNA elements composed of expressed sequence tags that either corresponded to human transcripts with known function in the Genbank database (7,117) or anonymous (3,575).

RNAs were isolated using TRIzol reagent (Invitrogen, Carlsbad, CA) according to the manufacturer's instruction. Integrity of isolated RNA was examined by gel electrophoresis.

Target Synthesis, Array Hybridization, Image Processing, and Statistical Analysis

cDNA targets were synthesized from the isolated total RNA with 33P-dCTP by oligodeoxythymidylic acid–primed polymerization using Superscript II reverse transcriptase (Life Technologies, Rockville, MD) as described previously (26). 33P-dCTP-labeled targets were hybridized to the membrane arrays, washed, and exposed on phosphorimage screen for ∼15 hours and scanned on a Typhoon PhosphorImager (Molecular Dynamics, Sunnyvale, CA). Scanned images of microarrays were analyzed using ImaGene (Biodiscovery, Danville, CA) and the output intensity data were further analyzed using custom statistical software.

Array data analysis was done as described previously (26). In brief, normalized expression data for each gene were analyzed by regression models to fit polynomial functions of the logarithm of time up to the third degree. A subset of genes with >2-fold changes for at least two consecutive time points and with significant coefficients of the highest degree (i.e., linear, quadratic, or cubic) at the significance level of 2% (to control possible type I error rate from multiple comparisons) was included in the polynomial regression analysis. Local regression models were also used to fit quadratic polynomials of the logarithm of time as before (26). For the selected genes, the patterns of gene expression were log transformed, centered by median, and subjected to cluster analyses by centered correlation and average linkage as the similarity/distance metric using the hierarchical cluster algorithm in Cluster and TreeView software suite (33). The entire microarray data set is available for searches at http://www.ncbi.nlm.nih.gov/geo under the data series accession no. GSE#.

Transactivation of TGF-β and BMP Response Element Promoter Reporter

21BES cells were transfected with either TGF-β (3TP-Lux; ref. 34) or BMP response element (MSX; ref. 35) promoter luciferase reporter plasmids and treated with either EGCG or H2O2 in the presence or absence of catalase 24 hours post-transfection. Luciferase assays were conducted in three independent transfections and normalized with Renilla luciferase activity.

Real-time Quantitative Reverse Transcription-PCR Validation of Gene Expression

Real-time quantitative reverse transcription-PCR was done to analyze the expression of BMPR2, CDH3, DUSP5, FKBP5, FOXP1, and ZNF184. Total RNA (∼35 ng) from untreated control and EGCG-treated cells as described above in the microarray studies were employed for the amplification. RNA from Raji cells (Applied Biosystems, Foster City, CA) was used as internal control for the expression of ZNF184 and the human placental RNA was used for all other genes. cDNA synthesis and real-time PCR amplification were conducted using Taqman assay. The minor groove binder probe was labeled by 5′-end FAM as reporter. Amplifications were conducted in triplicate using ABI Prism 7000 sequencing detector.

Results

Consistent with our previous report (20), we show here that exposing the Ha-ras gene transformed human bronchial epithelial 21BES cell line to EGCG (25 μmol/L) inhibited cell growth and caused cell death as determined morphologically by light microscopy (Fig. 1). Also consistent with previous observations (20, 21), we found a rapid but transient production of H2O2 when EGCG was added to the cell culture, with a peak concentration of ∼3 μmol/L (Fig. 2). Addition of catalase (30 units/mL) to the cell culture system markedly reduced the production of H2O2. Controls without EGCG had much lower levels of H2O2 (0.2–04 μmol/L) in the culture medium and catalase further decreased the H2O2 level (Fig. 2). The results suggest that H2O2 is generated by the auto-oxidation of EGCG in the culture medium and the addition of catalase effectively reduced H2O2 level. The presence of catalase delayed the EGCG-induced onset of cell death (Fig. 1, K, L, O, and P), suggesting that H2O2 is in part involved in the EGCG-induced apoptosis. This is consistent with our previous results as well as with others in that addition of exogenous catalase failed to completely prevent the EGCG-induced cytotoxicity and cell growth in the tumor cells (20, 36).

Figure 1.
Figure 1.

EGCG induced apoptosis in 21BES cells. Onset of cell death following EGCG (25 μmol/L) treatment either in the presence (M–P) or in the absence (I–L) of catalase (30 units/mL) was observed by light micrography compared with controls without (A–D) or with (E–H) catalase at the following time points: 1 hour (A, E, I, and M), 12 hours (B, F, J, and N), 36 hours (C, G, K, and O), and 48 hours (D, H, L, and P).

Figure 2.
Figure 2.

Formation of H2O2 in conditioned tissue culture medium from auto-oxidation of EGCG. Following EGCG addition to cell culture, conditioned medium was collected and assayed for H2O2 as described in Materials and Methods at 0, 0.25, 0.5, 1, 2, 3, 6, 12, 15, 24, 36, and 48 hours. ○, untreated control; •, catalase (30 units/mL); ▵ EGCG (25 μmol/L); ▴, catalase (30 units/mL) + EGCG (25 μmol/L).

We determined the time-dependent gene expression profiles of cells after exposure to EGCG. RNAs were isolated from 21BES cells treated with EGCG (25 μmol/L) in the presence or absence of catalase (30 units/mL) at 0, 0.25, 0.5, 1, 2, 3, 6, 12, 15, 24, 36, and 48 hours and compared with untreated controls. Samples were labeled by reverse transcription and hybridized to custom-printed cDNA arrays with 10,692 expressed sequence tags printed on nylon membranes (see Materials and Methods). Normalized data were analyzed by regression models and the expression levels for each gene were fitted to polynomial functions relative to the logarithm of time up to the third degree as described previously (26). Statistically significant alterations in the expression of many genes were observed. A subset of these alterations showing temporal expression patterns was selected for Cluster analysis and the results were displayed by TreeView (ref. 33; Fig. 3A). The distinct time-dependent changes in gene expression can be visually classified as early-response, intermediate-response, and late-response genes following EGCG treatment (Fig. 3B). We further analyzed the results by regression models to fit the polynomial functions, and quadratic patterns of gene induction by EGCG were observed for the early-response, intermediate-response, and late-response gene clusters (Fig. 3C). EGCG also abolished or down-regulated the expression of some temporally expressed genes (Fig. 3B). In addition, a cyclical pattern of gene expression that fits the cubical degree of the regression model was also observed (data not shown). The periodic changes in the expression of these genes may implicate their association with the cell cycle.

Figure 3.
Figure 3.

TreeView displays and polynomial regression analysis of temporal changes in gene expression by EGCG. DNA microarray expression data of EGCG (25 μmol/L)-treated 21BES cells in the presence or absence of catalase (30 units/mL) compared with untreated control with or without catalase were normalized and filtered as described in Materials and Methods. A, selected subset of genes was log transformed, centered by median, and subjected to cluster analyses by centered correlation and complete linkage using the hierarchical cluster algorithm and display using the TreeView software suite. B and C, temporal patterns of gene expression were obtained by polynomial regression analysis and the genes clusters were displayed with TreeView and histograms.

The temporal gene changes following EGCG treatment occurred as early as 15 minutes with the early-response genes, with increased expression returning to basal levels by 3 to 6 hours (Fig. 3C). A second cascade of gene induction followed between 3 and 10 hours and the late-response cluster between 12 and 36 hours post–EGCG treatment. In the early-response cluster, the down-regulated genes included sex determining region Y-box 12 (SOX12), peptidylprolyl isomerase (cyclophilin)–like 2 (PPIL2), zinc finger protein 33A (ZNF33A), inositol hexaphosphate kinase 1 (IHPK1), BMPR2, and alkylation repair alkB homologue (ALKBH) and the up-regulated genes included ubiquitin-activating enzyme E1C (UBE1C), FMS-related tyrosine kinase 1 (FLT1), and basic fibroblast growth factor 2 (FGF2; Fig. 3B). In the intermediate-response gene cluster, we found characteristic induction of transcription regulators [TGF-β-stimulated protein (TSC22), polyhomeotic-like 2 (PHC2), and homeobox D1 (HOXD1)] and genes that may have roles in apoptosis [thromboxane A2 receptor (TXA2R), tumor necrosis factor receptor gene superfamily member 6 (TNFRSF6), and MAPK activating death domain protein (MADD)] as well as cell growth inhibition and differentiation [eukaryotic translation initiation factor 4E (EIF4E), HOXD1, and TSC22; Fig. 3B]. Genes in the late-response cluster seemed to have roles in various cellular pathways including matrix metalloproteinase-9 (MMP9), caveolin 1 (CAV1), and cytochrome P450 CYP3A7 but notably an absence of transcription factors (Fig. 3B).

Because the addition of EGCG caused production of H2O2, which is a known inducer of gene expression (37–39), it is necessary to distinguish between the genes that are H2O2 dependent and the genes that are H2O2 independent. Therefore, we treated 21BES cells in the presence of catalase (30 units/mL) to abolish or minimize the effects of H2O2. Our results showed that some of the changes in gene expression were abolished by the addition of catalase (Fig. 4A), whereas other changes were unaffected (Fig. 4B), thus suggesting that the former group of genes is mediated by H2O2.

Figure 4.
Figure 4.

Effects of catalase on EGCG-induced changes in gene expression. 21BES cells were treated with EGCG (25 μmol/L) either in the presence or in the absence of catalase (30 units/mL), which resulted in distinct clusters of gene expression changes that were either abolished by catalase (A) or unaffected by catalase (B). The resulting clusters were further distinguished as either H2O2-dependent (A) or H2O2-independent (B) gene expression.

Notably, a significant number of the H2O2-affected genes (that were abolished by catalase) were early-response genes or biphasic genes that expressed in a cyclical fashion (Fig. 4A). In contrast, most genes, with expression not blocked by catalase, were of either the intermediate-response or the late-response clusters (Fig. 4B). These results suggest that the acute response in gene expression on addition of EGCG may be mostly mediated by H2O2.

Coordinated changes in the expression of genes with common pathways or functions were also observed (Fig. 4A). For example, there was the activation of components of the TGF-β signaling pathway (40) including TGF-β1 and TGF-β2, the TGF-β-stimulated protein TSC22, SMAD2, SMAD3, and SMAD6, and SMAD anchor for receptor activation (SARA) and some downstream targets including fibronectin, fibronectin receptor, laminin, laminin receptor, etc. (Fig. 4A). Interestingly, treating cells with catalase can abolish the activation of these genes (Fig. 4A), suggesting that these changes are mediated by H2O2. In contrast, decreased expression of a gene cluster of the BMP signaling pathway (41) including its BMPR2, SMAD7, some components of the MAPK pathway, FK506 binding protein 5, cullin 5, etc., were not blocked by catalase (Fig. 4B). These results suggest that the BMP signaling pathway and components of its downstream target genes are affected by EGCG independent of H2O2.

To confirm that genes of the BMP and TGF-β signaling pathways were targets of EGCG and H2O2, respectively, we examined their effects on the BMP and TGF-β response elements containing luciferase reporter plasmids (34, 35). We found that EGCG repressed transcription from the BMP response element promoter reporter (MSX) and this effect was not abolished by the presence of catalase (Fig. 5A). Furthermore, no activation of the BMP-responsive reporter was observed with H2O2 either in the absence or in the presence of catalase. We found transactivation of the TGF-β-responsive promoter reporter (3TP-Lux) by H2O2, which was modestly inhibited by catalase (Fig. 5B). No significant transactivation of TGF-β response element promoter reporter, however, was observed with EGCG (Fig. 5B). These results suggest that EGCG and H2O2 can specifically modulate transcription of genes of the BMP and TGF-β signaling pathways, respectively.

Figure 5.
Figure 5.

Transactivation of TGF-β and BMP response elements promoter reporters by EGCG and H2O2. Luciferase reporter constructs containing either TGF-β (A) or BMP (B) response elements were transfected into 21BES cells followed by treatment with either EGCG or H2O2. Cells were harvested for luciferase activity ∼24 hours posttreatment with EGCG or H2O2. 3TP-Lux, luciferase reporter plasmid containing multiple tandem repeats of the TGF-β response elements; MSX, reporter plasmid containing tandem repeats of the BMP response elements; BMPRI, expression plasmid containing a mutant activated BMPR1 used as control to monitor the activity of the MSX reporter plasmid. Columns, mean of triplicate experiments; bars, SE.

Using RNA samples derived from the microarray expression studies above, we further validated the expression of BMPR2, CDH3, DUSP5, FKBP5, FOXP1, and ZNF184 by real-time quantitative PCR. These genes were chosen from the cluster of the BMP signaling pathway. Our results suggested that the expression pattern of these genes agrees with those observed in the microarray experiments between untreated and EGCG-treated cells (Fig. 6).

Figure 6.
Figure 6.

Validation of gene expression by real-time quantitative reverse transcription-PCR. The expression of BMPR2, CDH3, DUSP5, FKBP5, FOXP1, and ZNF184 was determined by real-time quantitative reverse transcription-PCR as described in Materials and Methods. Analysis of each gene was conducted in triplicates and normalized against their expression in human placental cells (BMPR2, CDH3, DUSP5, FKBP5, and FOXP1) or Raji cells (ZNF184) using β-actin as internal control. The histograms showed the cycle threshold of each gene between untreated and EGCG-treated samples. Columns, mean of triplicate experiments; bars, SE. Asterisks, significantly altered in expression compared with untreated control (BMPR2, P = 0.0005; CDH3, P = 0.014; FOXP1, P = 0.012).

Discussion

Our results showed that, on addition of EGCG to 21BES cells, altered gene expression, cell growth inhibition, and apoptosis were observed (Fig. 1). More importantly, we were able to dissect the gene expression profiles into either H2O2-dependent or H2O2-independent expression patterns by treating 21BES cells with EGCG in the presence of catalase (Fig. 4). Most of the H2O2-mediated gene expression (Fig. 4A) occurred either as early-response or as intermediate-response genes, whereas a significant number of H2O2-independent genes occurred later in either the intermediate-response or the late-response clusters (Fig. 4B). The presence of catalase abolished the H2O2 induction of apoptosis genes (TXA2R, TNFRSF6, and MADD; Fig. 2B) and slowed down the rate of apoptosis. Cell death still occurred in 21BES cells with a delay of ∼12 to 24 hours, suggesting that EGCG also induced H2O2-independent apoptosis events.

Detailed kinetics analysis of gene expression changes showed that EGCG causes distinct temporal activation of gene expression that can be distinctly separated into early-response, intermediate-response, and late-response clusters of gene expression (Fig. 3). These temporal gene changes are coordinately modulated with transcription factors (TSC22, HOXD1, and PHC2), cell differentiation (EIF4E, PHC2, and HOXD1), and cell death regulators (TXA2R, TNFRSF6, and MADD) altered in the early-response and intermediate-response clusters followed by the activation of genes with a variety of cellular functions that are downstream targets of the early-response and intermediate-response genes. These patterns of gene changes suggest a hierarchical and coordinated regulation of gene expression by EGCG that are consistent with cell growth inhibition and the activation of apoptosis.

Among many of the gene expression changes observed, we found that those involving TGF-β and BMP signaling pathways were most interesting and selected for additional study. The EGCG-induced down-regulation of the BMP signaling pathway was not influenced by the presence of catalase (Fig. 3). This effect was confirmed by reporter assay, demonstrating that EGCG repressed BMP response element promoter activity, and the suppression was not affected by catalase (Fig. 5A). However, most of the genes of the TGF-β pathway can be abolished by catalase, suggesting that their induction is mediated by H2O2. We also confirmed by promoter reporter transactivation assay that H2O2 stimulated TGF-β response element promoter and the activation was inhibited by catalase (Fig. 5B). Unexpectedly, EGCG did not stimulate the TGF-β response element promoter reporter. We speculate that, because gene expression changes activated by EGCG are temporal sensitive, harvesting the cells for luciferase assays at 24 hours post-transfection and treatment with EGCG may not coincide with its temporal onset of induction of gene expression. Nevertheless, our results are consistent with the hypothesis that, in 21BES cells, the induction of the TGF-β signaling pathway is mediated by H2O2, whereas the suppression of the BMP signaling pathway is H2O2 independent.

BMPs belong to the TGF-β family and have been identified as factors that stimulate bone formation in vivo, but BMPs are multifunctional molecules regulating growth, differentiation, and apoptosis in various target cells (41). The observation that the mRNA levels of the BMPR2, SMAD7, and components of the MAPK pathway (MAP3K8 and MAPK-APK3; ref. 42; Fig. 4B) are decreased by EGCG suggests that the BMP signaling pathway is down-regulated by EGCG. It has been shown that BMPR2 stimulates the MAPK pathway by a BMPR2-induced up-regulation of mRNA for ERK1 and ERK2 (43). Thus, suppression of the BMP pathway by EGCG may result in a decrease of the MAPK pathway. In addition, EGCG can also inhibit the enzymatic activity of MAPK (14). Together, these effects may contribute to the growth inhibitory effects of EGCG. Activation of the BMP pathway, which also activates apoptosis as shown in previous studies (41), is consistent with the EGCG-induced cell apoptosis observed in our study (Fig. 1A).

H2O2 has been shown previously to induce gene expression (37–39). Its downstream signaling events include calcium mobilization and protein phosphorylation. A previous microarray expression profiling study showed that H2O2 induced a large number of gene changes (37) and some of these gene changes were also observed in our study. These include glutathione peroxidase 2, early growth response 1, CHK1 homologue, SMURF2 (an E3 ubiquitin ligase), Jun, cyclin A2, NADP+-dependent malic enzyme 1, etc., representing genes from diverse biochemical and functional pathways (Fig. 4A). However, there are also many differences in gene expression profile between ours and this previous study mainly due to the rather high concentration of exogenous H2O2 (500 μmol/L) used to treat the cells (37). The distinct dynamic patterns of early-response, intermediate-response, and late-response changes in gene expression in our study were not pursued by Chuang et al. (37). Clearly, detailed time course and dose-dependent analyses with multiple, closely spanned time points or dosages should be conducted in the future to gain further understanding of the gene expression pattern of H2O2.

The H2O2 formed on addition of EGCG to a cell culture system is probably due to the auto-oxidation of EGCG because of the presence of rather high oxygen partial pressure (160 mm Hg). The oxygen partial pressure is 100 to 150 mm Hg in lung alveoli, 85 to 90 mm Hg in arterial blood, and ∼40 mm Hg in mixed venous blood (44). Therefore, whether cellular EGCG causes the production of H2O2 in vivo is unknown and remains to be studied.

In the present study, the EGCG (25 μmol/L) used was following that applied in our previous studies (20). This concentration is higher than those detected in the plasma samples of humans and rodents following tea ingestion (1). Therefore, it remains to be determined whether the presently observed effects can be recapitulated in vivo after dietary or pharmacologic doses of green tea or EGCG. Nevertheless, a high concentration of EGCG can be delivered to the oral cavity; thereafter, high salivary concentrations of EGCG can be observed (45). In the oral cavity, the salivary oxygen partial pressure may approximate that in the cell culture.

In summary, gene expression profiling analysis in our study revealed temporal changes in gene expression profiles on addition of EGCG to 21BES cells. The distinction between H2O2-dependent and H2O2-independent pathways are important because the former, such as the effect on the TGF-β signaling pathway, may or may not occur in vivo. Gene changes not affected by catalase such as those of the BMP signaling pathway may be more important for EGCG-induced cell growth inhibition and death. Further studies will be required to determine whether BMP and its receptors as well as other gene expression changes significantly contribute to the cancer chemopreventive and anticancer effects of EGCG.

Footnotes

  • Grant support: USPHS grant CA 88961 (C.S. Yang).

  • The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

    • Accepted June 30, 2004.
    • Received March 15, 2004.
    • Revision received May 25, 2004.

References

  1. ↵
    Yang CS, Maliakal P, Meng X. Inhibition of carcinogenesis by tea. Annu Rev Pharmacol Toxicol 2002;42:25–54.
    OpenUrlCrossRefPubMed
  2. ↵
    Yang CS, Wang ZY. Tea and cancer. J Natl Cancer Inst 1993;85:1038–49.
    OpenUrlAbstract/FREE Full Text
  3. ↵
    Kohlmeier L, Weterings KG, Steck S, Kok FJ. Tea and cancer prevention: an evaluation of the epidemiologic literature. Nutr Cancer 1997;27:1–13.
    OpenUrlPubMed
  4. ↵
    Paschka AG, Butler R, Young CY. Induction of apoptosis in prostate cancer cell lines by the green tea component, (−)-epigallocatechin-3-gallate. Cancer Lett 1998;130:1–7.
    OpenUrlCrossRefPubMed
  5. ↵
    Ahn WS, Huh SW, Bae SM, et al. A major constituent of green tea, EGCG, inhibits the growth of a human cervical cancer cell line, CaSki cells, through apoptosis, G(1) arrest, and regulation of gene expression DNA. Cell Biol 2003;22:217–24.
    OpenUrl
  6. ↵
    Isemura M, Saeki K, Kimura T, Hayakawa S, Minami T, Sazuka M. Tea catechins and related polyphenols as anti-cancer agents. BioFactors 2000;13:81–5.
    OpenUrlPubMed
  7. ↵
    Liu JD, Chen SH, Lin CL, Tsai SH, Liang YC. Inhibition of melanoma growth and metastasis by combination with (−)-epigallocatechin-3-gallate and dacarbazine in mice. J Cell Biochem 2001;83:631–42.
    OpenUrlCrossRefPubMed
  8. ↵
    Masuda M, Suzui M, Weinstein IB. Effects of epigallocatechin-3-gallate on growth, epidermal growth factor receptor signaling pathways, gene expression, and chemosensitivity in human head and neck squamous cell carcinoma cell lines. Clin Cancer Res 2001;7:4220–9.
    OpenUrlAbstract/FREE Full Text
  9. ↵
    Masuda M, Suzui M, Lim JT, Weinstein IB. Epigallocatechin-3-gallate inhibits activation of HER-2/neu and downstream signaling pathways in human head and neck and breast carcinoma cells. Clin Cancer Res 2003;9:3486–91.
    OpenUrlAbstract/FREE Full Text
  10. ↵
    Stammler G, Volm M. Green tea catechins (EGCG and EGC) have modulating effects on the activity of doxorubicin in drug-resistant cell lines. Anticancer Drugs 1997;8:265–8.
    OpenUrlCrossRefPubMed
  11. ↵
    Naasani I, Seimiya H, Tsuruo T. Telomerase inhibition, telomere shortening, and senescence of cancer cells by tea catechins. Biochem Biophys Res Commun 1998;249:391–6.
    OpenUrlCrossRefPubMed
  12. ↵
    Naasani I, Oh-Hashi F, Oh-Hara T, et al. Blocking telomerase by dietary polyphenols is a major mechanism for limiting the growth of human cancer cells in vitro and in vivo. Cancer Res 2003;63:824–30.
    OpenUrlAbstract/FREE Full Text
  13. ↵
    Chung JY, Huang C, Meng X, Dong Z, Yang CS. Inhibition of activator protein 1 activity and cell growth by purified green tea and black tea polyphenols in H-ras-transformed cells: structure-activity relationship and mechanisms involved. Cancer Res 1999;59:4610–7.
    OpenUrlAbstract/FREE Full Text
  14. ↵
    Chung JY, Park JO, Phyu H, Dong Z, Yang CS. Mechanisms of inhibition of the Ras-MAP kinase signaling pathway in 30.7b Ras 12 cells by tea polyphenols (−)-epigallocatechin-3-gallate and theaflavin-3,3′-digallate. FASEB J 2001;15:2022–4.
    OpenUrlFREE Full Text
  15. ↵
    Lin JK, Liang YC, Lin-Shiau SY. Cancer chemoprevention by tea polyphenols through mitotic signal transduction blockade. Biochem Pharmacol 1999;58:911–5.
    OpenUrlCrossRefPubMed
  16. ↵
    Liang YC, Chen YC, Lin YL, Lin-Shiau SY, Ho CT, Lin JK. Suppression of extracellular signals and cell proliferation by the black tea polyphenol, theaflavin-3,3′-digallate. Carcinogenesis 1999;20:733–6.
    OpenUrlAbstract/FREE Full Text
  17. ↵
    Cao Y, Cao R. Angiogenesis inhibited by drinking tea. Nature 1999;398:381.
    OpenUrlCrossRefPubMed
  18. ↵
    Islam S, Islam N, Kermode T, et al. Involvement of caspase-3 in epigallocatechin-3-gallate-mediated apoptosis of human chondrosarcoma cells. Biochem Biophys Res Commun 2000;270:793–7.
    OpenUrlCrossRefPubMed
  19. ↵
    Yang GY, Liao J, Kim K, Yurkow EJ, Yang CS. Inhibition of growth and induction of apoptosis in human cancer cell lines by tea polyphenols. Carcinogenesis 1998;19:611–6.
    OpenUrlAbstract/FREE Full Text
  20. ↵
    Yang GY, Liao J, Li C, et al. Effect of black and green tea polyphenols on c-jun phosphorylation and H(2)O(2) production in transformed and non-transformed human bronchial cell lines: possible mechanisms of cell growth inhibition and apoptosis induction. Carcinogenesis 2000;21:2035–9.
    OpenUrlAbstract/FREE Full Text
  21. ↵
    Hong J, Lu H, Meng X, Ryu JH, Hara Y, Yang CS. Stability, cellular uptake, biotransformation, and efflux of tea polyphenol (−)-epigallocatechin-3-gallate in HT-29 human colon adenocarcinoma cells. Cancer Res 2002;62:7241–6.
    OpenUrlAbstract/FREE Full Text
  22. ↵
    Long LH, Clement MV, Halliwell B. Artifacts in cell culture: rapid generation of hydrogen peroxide on addition of (−)-epigallocatechin, (−)-epigallocatechin gallate, (+)-catechin, and quercetin to commonly used cell culture media. Biochem Biophys Res Commun 2000;273:50–3.
    OpenUrlCrossRefPubMed
  23. ↵
    Dashwood WM, Orner GA, Dashwood RH. Inhibition of β-catenin/Tcf activity by white tea, green tea, and epigallocatechin-3-gallate (EGCG): minor contribution of H(2)O(2) at physiologically relevant EGCG concentrations. Biochem Biophys Res Commun 2002;296:584–8.
    OpenUrlCrossRefPubMed
  24. ↵
    Chin KV, Kong AN. Application of DNA microarrays in pharmacogenomics and toxicogenomics. Pharm Res 2002;19:1773–8.
    OpenUrlCrossRefPubMed
  25. ↵
    Scherf U, Ross DT, Waltham M, et al. A gene expression database for the molecular pharmacology of cancer. Nat Genet 2000;24:236–44.
    OpenUrlCrossRefPubMed
  26. ↵
    Zheng X, Ravatn R, Lin Y, et al. Gene expression of TPA induced differentiation in HL-60 cells by DNA microarray analysis. Nucleic Acids Res 2002;30:4489–99.
    OpenUrlAbstract/FREE Full Text
  27. ↵
    Ogawa N, DeRisi J, Brown PO. New components of a system for phosphate accumulation and polyphosphate metabolism in Saccharomyces cerevisiae revealed by genomic expression analysis. Mol Biol Cell 2000;11:4309–21.
    OpenUrlAbstract/FREE Full Text
  28. ↵
    Sudarsanam P, Iyer VR, Brown PO, Winston F. Whole-genome expression analysis of snf/swi mutants of Saccharomyces cerevisiae. Proc Natl Acad Sci U S A 2000;97:3364–9.
    OpenUrlAbstract/FREE Full Text
  29. ↵
    Iyer VR, Eisen MB, Ross DT, et al. The transcriptional program in the response of human fibroblasts to serum. Science 1999;283:83–7.
    OpenUrlAbstract/FREE Full Text
  30. ↵
    Spellman PT, Sherlock G, Zhang MQ, et al. Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol Biol Cell 1998;9:3273–97.
    OpenUrlAbstract/FREE Full Text
  31. ↵
    Weinreb O, Mandel S, Youdim MB. cDNA gene expression profile homology of antioxidants and their antiapoptotic and proapoptotic activities in human neuroblastoma cells. FASEB J 2003;17:935–7.
    OpenUrlAbstract/FREE Full Text
  32. ↵
    Wang SI, Mukhtar H. Gene expression profile in human prostate LNCaP cancer cells by (−)epigallocatechin-3-gallate. Cancer Lett 2002;182:43–51.
    OpenUrlCrossRefPubMed
  33. ↵
    Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A 1998;95:14863–8.
    OpenUrlAbstract/FREE Full Text
  34. ↵
    Long J, Matsuura I, He D, Wang G, Shuai K, Liu F. Repression of Smad transcriptional activity by PIASy, an inhibitor of activated STAT. Proc Natl Acad Sci U S A 2003;100:9791–6.
    OpenUrlAbstract/FREE Full Text
  35. ↵
    Kusanagi K, Inoue H, Ishidou Y, Mishima HK, Kawabata M, Miyazono K. Characterization of a bone morphogenetic protein-responsive Smad-binding element. Mol Biol Cell 2000;11:555–65.
    OpenUrlAbstract/FREE Full Text
  36. ↵
    Yamamoto T, Lewis J, Wataha J, et al. Roles of catalase and hydrogen peroxide in green tea polyphenol-induced chemopreventive effects. J Pharmacol Exp Ther 2004;308:317–23.
    OpenUrlAbstract/FREE Full Text
  37. ↵
    Chuang YY, Chen Y, Gadisetti, et al. Gene expression after treatment with hydrogen peroxide, menadione, or t-butyl hydroperoxide in breast cancer cells. Cancer Res 2002;62:6246–54.
    OpenUrlAbstract/FREE Full Text
  38. ↵
    Griendling KK, Sorescu D, Lassegue B, Ushio-Fukai M. Modulation of protein kinase activity and gene expression by reactive oxygen species and their role in vascular physiology and pathophysiology. Arterioscler Thromb Vasc Biol 2000;20:2175–83.
    OpenUrlAbstract/FREE Full Text
  39. ↵
    Halliwell B, Clement MV, Ramalingam J, Long LH. Hydrogen peroxide. Ubiquitous in cell culture and in vivo? IUBMB Life 2000;50:251–7.
    OpenUrlCrossRefPubMed
  40. ↵
    Shi Y, Massague J. Mechanisms of TGF-β signaling from cell membrane to the nucleus. Cell 2003;113:685–700.
    OpenUrlCrossRefPubMed
  41. ↵
    Zhao GQ. Consequences of knocking out BMP signaling in the mouse. Genesis 2003;35:43–56.
    OpenUrlCrossRefPubMed
  42. ↵
    Chong H, Vikis HG, Guan KL. Mechanisms of regulating the Raf kinase family. Cell Signal 2003;15:463–9.
    OpenUrlCrossRefPubMed
  43. ↵
    Lou J, Tu Y, Li S, Manske PR. Involvement of ERK in BMP-2 induced osteoblastic differentiation of mesenchymal progenitor cell line C3H10T1/2. Biochem Biophys Res Commun 2000;268:757–62.
    OpenUrlCrossRefPubMed
  44. ↵
    Meerson F, Pozharov V, Minyailenko T. Superresistance against hypoxia after preliminary adaptation to repeated stress. J Appl Physiol 1994;76:1856–61.
    OpenUrlAbstract/FREE Full Text
  45. ↵
    Lee MJ, Lambert JD, Prabhu S, et al. Delivery of tea polyphenols to the oral cavity by green tea leaves and black tea extract. Cancer Epidemiol Biomarkers Prev 2004;13:132–7.
    OpenUrlAbstract/FREE Full Text
Back to top
Molecular Cancer Therapeutics: 3 (9)
September 2004
Volume 3, Issue 9

Sign up for alerts

View this article with LENS

Open full page PDF
Article Alerts
Email Article
Citation Tools
Gene expression changes induced by green tea polyphenol (−)-epigallocatechin-3-gallate in human bronchial epithelial 21BES cells analyzed by DNA microarray
Ragini Vittal, Zachariah E. Selvanayagam, Yi Sun, Jungil Hong, Fang Liu, Khew-Voon Chin and Chung S. Yang
Mol Cancer Ther September 1 2004 (3) (9) 1091-1099;
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo

Jump to section

Advertisement