Breast cancer is a major cause of death in women worldwide. Genetic and environmental factors play a significant role in breast cancer development, with family history being an important factor for determining the risk of breast cancer. The development of chemoresistance in breast cancer is a frequent cause of treatment failure (Pisani, 1992).
Resveratrol (RES) is a naturally occurring polyphenol, present in more than 72 plant species, including a wide variety of fruits and vegetables such as grapes, berries, peanuts, pines, and various herbs (Sobolev and Cole, 1999; Fremont, 2000; Sanders et al., 2000). There is evidence that wine consumption decreases the risk of cancer and that RES, present in red wine, may contribute to these cancer-preventive effects (Bianchini and Vainio, 2003). Jang et al. (1997) observed that this compound has antitumor properties at all three stages of skin carcinogenesis, including initiation, promotion, and progression. In addition, it prevents chemical carcinogen-induced epithelial cell transformation (Roy et al., 2009; Sengottuvelan et al., 2009) and inhibits neoangiogenesis (Tseng et al., 2004; Dann et al., 2009). Several studies have shown that RES inhibited the growth of different human cancer cell lines, including human oral squamous carcinoma, promyelocytic leukemia, breast, lung, prostate, rhabdomyosarcoma, and colon cancer cells (Elattar and Virji, 1999; Joe et al., 2002; Pozo-Guisado et al., 2002; Opipari et al., 2004; Chow et al., 2005; Stervbo et al., 2006; Alkhalaf, 2007; Lee et al., 2008; Benitez et al., 2009; Kim et al., 2009; Malhotra et al., 2011). This effect has been associated with the ability of RES to arrest cell cycle progression (Wolter et al., 2001; Bai et al., 2010), to promote cell differentiation (Wolter and Stein, 2002), and to induce programmed cell death (Park et al., 2001; Brito et al., 2008; Lin et al., 2008). Many studies have provided evidence for the anticarcinogenic activity of RES, but the precise mechanism involved in the modulation of oncogenic precursors of carcinogenesis remains to be elucidated.
In this study, we evaluated the changes in global gene expression profiles induced by the treatment of MCF-7 breast cancer cells with two concentrations of RES (150 and 250 μmol/l) to define the cellular pathways that are involved in the biological response of cancer cells to RES.
Materials and methods
Cell lines and reagents
The MCF-7 human breast cancer cells (ATCC) were maintained in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum in a 5% CO2 incubator at 37°C. RES was obtained from Sigma Chemical Company (St Louis, Missouri, USA). RES stock solution was prepared in absolute ethanol and diluted in culture medium.
MTT proliferation assay
Cells were plated at a density of 2×105 cells/dish in p60 cell culture dishes 24 h before the assay. Cells were cultured for 24, 48, and 72 h in the presence of different concentrations of RES (0–250 μmol/l in 0.3% ethanol). At the end of the treatment period, the cells were incubated in MTT (0.5 mg/ml) for 30 min. The medium was removed and the formazan dye crystals synthesized were solubilized with 500 µl of acid isopropanol, and absorbance was measured by a colorimetric assay at 540 nm wavelength (Bio-Rad Laboratories, Benicia, California, USA). The growth percentage was calculated using the initial number of control cells as 100% at 0 h.
Total RNA was extracted using TRIzol (Invitrogen, Carlsbad, California, USA) and purified using the RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s protocol. RNA was recovered in 30 μl of nuclease-free water and either used immediately or stored at −80°C until further analysis.
Microarray sample processing
The quality of the RNA samples was assessed using the RNA Nano Lab Chip kit (Agilent Technologies, Palo Alto, California, USA), which yielded RNA integrity numbers from 9.3 to 9.8. Total RNA was processed and hybridized in triplicate to the GeneChip Human Gene 1.0 ST (Affymetrix Inc., Santa Clara, California, USA), following the manufacturer’s recommendations as described previously (Yalcin, 2004). Briefly, 300 ng of the pooled RNA was converted into first-strand cDNA using Superscript II reverse transcriptase primed by a poly(T) oligomer. Second-strand cDNA synthesis was followed by an in-vitro transcription to generate cRNA.
The cRNA products were used as templates for a second cycle of cDNA synthesis, where deoxyuridine triphosphates were incorporated into the new strand. The cDNA was then fragmented using a uracil-DNA glycosilase and apurin apirymidin endonuclease. The fragments (50–70 mers) were then labeled by means of a biotin-labeled deoxynucleotide terminal addition reaction. The labeled cDNA product was heated to 95°C and hybridized to the Human Gene 1.0 ST microarray (Affymetrix Inc.) for 17+1 h at 45°C. Samples were washed with low (6×SSPE)-stringency and high (100 mmol/l MES, 0.1 mol/l NaCl)-stringency buffers and stained with streptavidin-phycoerythrin using the Affymetrix Fluidics Station 450 with the FS450_0007 protocol.
The GeneChip Scanner 3000 7G (Affymetrix Inc.) was used to collect fluorescent signals and the Expression Console software (Affymetrix Inc.) was used to obtain intensity signal and quality control data of the scanned arrays.
Analysis of array data
Signal intensities from each array were analyzed using Partek Genomic Suite version 6.4 (Partek, St Louis, Missouri, USA). Raw intensity probe values were normalized using robust multiarray analysis background correction. A two-way analysis of variance was carried out to identify differentially expressed genes. From the results of this analysis, the expression of genes with statistically significant values (P<0.05) and a fold change of more than 2 were used to select the set of relevant genes. The microarray data were deposited at the NCBI GEO database [GEO: GSE25412]. To identify those biological processes that show differentially expressed genes, we used the Advanced Pathway Painter v2.11 (GSA-Bansemer & Scheel GbR, Rostock, Germany), a bioinformatic tool used for the visualization of the expression data in the KEGG biological pathways context. The data set was analyzed using this tool and a gene expression fold change cutoff value of at least 2.0. These genes were submitted to the visualization tool of the software.
Real-time reverse-transcription polymerase chain reaction
cDNA synthesis and PCR amplification were carried out as described previously (Yalcin, 2004). Each sample was tested in triplicate with quantitative PCR, and mRNA ratios relative to the β2-microglobulin housekeeping gene were calculated for the standardization of gene expression levels. The primer sequences were designed using Primer Express Software (Applied Biosystems, Foster City, California, USA; Table 1). The SYBR Green reaction was carried out using a QuantiTect SYBR Green PCR Reagents kit (Qiagen, Valencia, California, USA) following the manufacturer’s recommendations. Before performing the real-time reverse-transcription PCR (RT-qPCR), a reaction optimization was performed for each gene-specific pair of primers to confirm the specificity of the amplification signal. Changes in fluorescence were recorded as the temperature was increased from 65 to 95°C at a rate of 0.2°C/s to obtain a DNA melting curve.
Data analysis using the 2−ΔΔCt method
For selected genes, real-time PCR was performed on the corresponding cDNA synthesized from each sample. The data were analyzed using the equation described by Livak (Livak and Schmittgen, 2001) as follows: Amount of target=2−ΔΔCt. We used the average ΔC t from RES untreated MCF-7 cells as a calibrator for each gene tested. Validation of the method was performed as reported previously (Yalcin, 2004). Data are presented as mean±SD. Statistical evaluation of significant differences was carried out using Student’s t-test. Differences of P less than 0.05 were considered statistically significant.
The microarray and RT-qPCR results were evaluated using Student’s paired t-test. Two-tailed P values of less than 0.05 were considered statistically significant.
Western blot analyses
MCF-7 breast cancer cells were treated for 48 h with ethanol or RES. Cells were lysed with RIPA lysis buffer. The cell suspension was sonicated and the supernatants were collected by centrifugation. Briefly, 30 μg protein was resolved on an SDS-8% polyacrylamide gel, proteins were transferred to a PVDF membrane, and probed overnight at 4°C with a specific primary antibody (NBS1 and RAD50 from Santa Cruz Biotechnology, Santa Cruz, California, USA; MRE11 from Cell Signaling, Danvers, Massachusetts, USA). The blots were developed using the chemiluminescent detection reagents (Immobilon western; Millipore, Billerica, Massachusetts, USA) and then analyzed through scanning densitometry using the Syngen Image Software (Syngene International Ltd, Iselin, New Jersey, USA). After stripping, the blots were reprobed with β-actin antibodies.
Resveratrol exerted dose-dependent and time-dependent antiproliferative effects on MCF-7 breast cancer cells
To determine the antiproliferative effects of RES in breast cancer cells, we evaluated its effects on the growth of the MCF-7 cell line by MTT assays. We first found that the vehicle did not affect the cell viability. We found that 0.3% (v/v) ethanol did not affect the growth of MCF-7 cells and therefore it was used throughout the experimental process and the initial number of cells was considered to be 100% in the MTT assay (Fig. 1).
After 48 h of treatment, RES induced statistically significant reductions in cell growth and viability with 200 and 250 μmol/l RES (P<0.005). At 150 μmol/l RES, cell growth was also significantly inhibited as compared with the control at 48 and 72 h (Fig. 1). We then compared 150 and 250 μmol/l RES, after 48 h of treatment, using the microarray technology because these treatments induced marked growth inhibition and a significant decrease in the viability of MCF-7 cells in a time-dependent and concentration-dependent manner compared with the ethanol-treated control (Fig. 1). These conditions are close to the IC50 reported for RES at 48 h in MCF-7 cells (IC50=151.8 μmol/l; Sareen et al., 2007).
Effect of resveratrol on the MCF-7 global gene expression profile
We have shown that the growth of MCF-7 cells is different under 150 and 250 μmol/l concentrations of RES. To identify genes responsive to these doses, we carried out a comprehensive analysis of genome-wide expression with microarrays. Series of three biological repeats were performed for 150 μmol/l RES, 250 μmol/l RES, and ethanol (control). After 48 h of treatment, total RNA extractions were performed as described in the Materials and methods section.
After analysis, we observed that the number of differentially expressed genes differed significantly under both conditions (Supplementary Fig. 1). We found that 1211 genes were differentially expressed in the 150 μmol/l RES-treated group; among these, 518 were upregulated and 693 were downregulated genes. In contrast, 2412 genes were differentially regulated in the 250 μmol/l RES-treated group, of which 651 genes were upregulated and 1761 were downregulated.
To identify those biological processes that show differentially expressed genes, we used the Advance pathway Painter v2.11 (GSA-Bansemer & Scheel GbR) on this data set, using a cutoff of at least 2.0 in gene expression. This allowed the identification of the most relevant biological mechanisms, pathways, and functions of the genes altered by RES treatments in MCF-7 cells. Using the Advance pathway Painter v2.11, we identified the Gene Ontology categories altered and we show a representative array of canonical pathways regulated by 150 μmol/l RES and 250 μmol/l RES (Fig. 2) in MCF-7 human breast cancer cells.
Grouping of the affected genes from these analyses showed that the most affected processes under both conditions of RES treatment were DNA replication, mismatch repair and the homologous recombination (HR) pathways, as well as the cell cycle pathway (Fig. 2). At 150 μmol/l RES treatment, we found underexpression of a group of master regulatory genes of the cell cycle and genes encoding DNA replication initiator proteins and the chromatin licensing as well as the minichromosome maintenance complex components (Supplementary Fig. 2). Similar effects for this pathway were observed with 250 μmol/l RES treatment (Supplementary Fig. 3).
The cell cycle was another severely affected pathway in 150 and 250 μmol/l RES-treated MCF-7 cells. Among the molecules that regulate the cell cycle are the cyclins, which are expressed and then degraded in a concerted manner to drive the stages of the cell cycle (Supplementary Fig. 4). In addition, at 250 μmol/l RES, we observed a decrease in the expression levels of DNA damage checkpoints ataxia telangiectasia mutated (ATM) and ataxia telangiectasia and Rad3-related protein (ATR) (Supplementary Fig. 5), suggesting that the effect of RES may be to enhance DNA damage.
At both concentrations, RES appears to downregulate the expression of genes such as BRCA2, MRE11, and RAD51 and genes that encode other key enzymes involved in the HR control pathway (Fig. 3). In this sense, at 250 μmol/l, this isoflavone decreased the expression of genes involved in genomic stability such as NBN (which encodes the NBS1 protein) and RAD50 (Fig. 3). Altogether, these results suggest that RES may be acting through the alteration of the cellular responses to DNA damage at different key levels.
Validation of differentially expressed genes
To validate the microarray results, the mRNA expression of selected genes involved in differentiation, proliferation, regulation of cell cycle, apoptosis, and HR (JUNB, CDKN1A, BIRC5, CCNB1, CDC25A, AUR-A, AUR-B, ESR1, LMNB1, LMNB2, MRE11, NBN, and RAD50) was confirmed using RT-qPCR. Triplicates were performed of each sample and for each gene. In all cases, the RT-qPCR data confirmed those obtained by 150 and 250 μmol/l RES array analyses (Fig. 4).
The components of the MRN complex are essential for DNA double-strand breaks (DSB) detection, DSB repair, and telomere length maintenance. As RT-qPCR showed downregulation of MRE11, NBN, and RAD50 expression in MCF-7 breast cancer cells treated with RES, we also performed western blot assays to determine whether there is a correlation between the mRNA level and the protein expression of these genes. We observed a single predominant protein band of the expected size corresponding to MRE11, NBS1, and RAD50 in whole-cell extracts obtained from untreated controls (Fig. 5). However, MRE11 and NBS1 protein levels decreased in MCF-7 cells treated with RES. We did not observe significant changes in the level of Rad50 protein expression (Fig. 5). Therefore, there is a correlation between downregulation of mRNA and protein expression of MRE11 and NBS1 in MCF-7 cells treated with RES, suggesting that the MRN complex could be disrupted by this naturally occurring polyphenol.
Microarrays can measure the expression of thousands of genes simultaneously, providing extensive information on gene networks and functions, as well as on drug efficacy and toxicity (Nees and Woodworth, 2001). Several reports have evaluated the effects of RES, a natural isoflavone, on gene expression in major cancer cell lines such as breast, prostate, colon, and leukemias using the microarray technique (Narayanan et al., 2002; Narayanan et al., 2003; Le Corre et al., 2004). Although many RES-responsive genes have been characterized, the complete pattern of RES-regulated genes is unknown in breast cancer models.
Our data from in-vitro studies suggest that RES exerts dose-dependent and time-dependent antiproliferative effects in MCF-7 cells, decreasing the number of viable cells (Fig. 1); this is in agreement with other studies (Kim et al., 2004). In the present work, several important cellular processes were affected by RES in the MCF-7 model. For example, several genes associated with DNA replication were strongly inhibited by this compound (Supplementary Figs 2 and 3). Among RES-induced downregulated genes involved in MCF-7 DNA replication, we found CDK2, ORC1L, ORC6L, and CDC6 under both treatment conditions.
It is known that MCM proteins are recruited to sites of DNA replication, forming the MCM2–MCM7 hexamer during the G1 phase of the cell cycle (Kearsey and Labib, 1998). This complex has helicase activity and facilitates DNA replication (Maiorano et al., 2006). The MCM proteins are frequently upregulated in a variety of dysplastic and cancer cells (Freeman et al., 1999; Alison et al., 2002), making them promising candidates as potential markers to target cancer cells specifically. There are no reports related to the effect of RES on the MCM gene family. In this study, we found that RES possesses an anti-MCM effect by inducing a significant decrease in MCM2–MCM7 and MCM10 gene expression in MCF-7 breast cancer cells under both treatment conditions.
However, we have found that RES also decreases the expression of HR-related genes. This result is in agreement with a previous study showing the effects of RES on DSBs repair in RES-treated lymphoblastoid cell lines (Gatz et al., 2008). In the study reported by Gatz and colleagues RES inhibited both HR and nonhomologous end joining independent of its known growth-regulatory and death-regulatory functions; they proposed that the activation of ATM and/or ATR is a central effect of RES. With respect to this, we observed a decrease in mRNA levels of many HR-related proteins, such as ATM, NBS1, and Rad51, suggesting a correlation with the previously reported (Gatz et al., 2008) decrease in the frequency of HR after RES treatment.
Genomic rearrangements are believed to result from the aberrant repair of DNA DSBs. These DSBs are repaired by two major pathways: HR and nonhomologous end joining (reviewed by Helleday et al., 2007). HR is more accurate because it relies on a template of homologous sequence, usually in the sister chromatid. If DNA repair pathways essential for tumor survival can be disrupted, then chemotherapy will be much more efficient. Thus, it can be argued that targeting both checkpoint and repair pathways in combination may selectively kill tumor cells over healthy ones.
Interestingly, we found a downregulated expression of Rad51, BRCA1, and BRCA2 genes when 150 μmol/l RES was applied to MCF-7 cells. BRCA1 plays an important role in the regulation of DNA repair and centrosome number. Both BRCA1 and BRCA2 are involved in the maintenance of genome stability, specifically through the HR pathway for double-strand DNA repair (Helleday et al., 2007). Our results suggest that RES reduces the expression of these targets, blocking repair mechanisms, which in turn leads to cell death.
Moreover, at 250 μmol/l RES, these changes were maintained and additional genes involved in HR were downregulated, such as those encoding proteins that form the MRN complex. This complex plays a crucial role in sensing DNA DSBs (Lavin, 2007). We found significant downregulation of MRE11 and NBS1 proteins, suggesting that RES disrupts the MRN complex.
The inherent resistance of tumors to DNA damage often limits the therapeutic efficacy of chemotherapy agents, such as cisplatin. An enhanced DNA repair and telomere maintenance response by the Mre11/Rad50/Nbs1 (MRN) complex is critical in driving this chemoresistance (Sorenson and Eastman, 1988; Abuzeid et al., 2009).
From a clinical viewpoint, increasing resistance requires an increased dosage of cisplatin (or any chemotherapy agent) and a subsequent risk for increased adverse effects and treatment-limiting toxicities. We believe that RES could be a novel chemosensitizing agent for cancer therapy in the context of chemoresistance. Thus, the downregulation of HR genes by RES might point to its importance as a promising target for anticancer therapy.
Our study shows that RES regulates the expression of genes implicated in biological pathways frequently altered during carcinogenesis. Our data show that RES acts by modifying the cellular growth and expression of cell cycle-related genes and also inhibits the expression of DNA repair genes in the MCF-7 breast cancer cell line. This inhibition of DNA repair genes suggests that this polyphenol might help to overcome drug resistance and provides a sound basis for conducting clinical trials with RES, in combination with other therapeutic agents. Combined treatment should enhance efficacy, reduce toxicity, and overcome chemoresistance, making RES an interesting candidate for its evaluation and potential application in tumor prevention and treatment.
This work was supported by grants from CONACyT to P.G. (45953-Q) and from INMEGEN as well as ICyT DF. During this work, I.L.G. was a recipient of CONACyT fellowships. The authors would like to thank Dr. Rosa María Bermúdez Cruz for critically reading the manuscript and M.C. Rodolfo Ocadiz-Delgado (CINVESTAV-IPN, Mexico) for technical support.
Conflicts of interest
There are no conflicts of interest.
Abuzeid WM, Jiang X, Shi G, Wang H, Paulson D, Araki K, et al. Molecular disruption of RAD50 sensitizes human tumor cells to cisplatin-based chemotherapy. J Clin Invest. 2009;119:1974–1985
Alison MR, Hunt T, Forbes SJ. Minichromosome maintenance (MCM) proteins may be pre-cancer markers. Gut. 2002;50:290–291
Alkhalaf M. Resveratrol
-induced growth inhibition in MDA-MB-231 breast cancer cells is associated with mitogen-activated protein kinase signaling and protein translation. Eur J Cancer Prev. 2007;16:334–341
Bai Y, Mao QQ, Qin J, Zheng XY, Wang YB, Yang K, et al. Resveratrol
induces apoptosis and cell cycle arrest of human T24 bladder cancer cells in vitro and inhibits tumor growth in vivo. Cancer Sci. 2010;101:488–493
Benitez DA, Hermoso MA, Pozo-Guisado E, Fernandez-Salguero PM, Castellon EA. Regulation of cell survival by resveratrol
involves inhibition of NF kappa B-regulated gene expression in prostate cancer cells. Prostate. 2009;69:1045–1054
Bianchini F, Vainio H. Wine and resveratrol
: mechanisms of cancer prevention? Eur J Cancer Prev. 2003;12:417–425
Brito PM, Simoes NF, Almeida LM, Dinis TC. Resveratrol
disrupts peroxynitrite-triggered mitochondrial apoptotic pathway: a role for Bcl-2. Apoptosis. 2008;13:1043–1053
Chow AW, Murillo G, Yu C, van Breemen RB, Boddie AW, Pezzuto JM, et al. Resveratrol
inhibits rhabdomyosarcoma cell proliferation. Eur J Cancer Prev. 2005;14:351–356
Dann JM, Sykes PH, Mason DR, Evans JJ. Regulation of vascular endothelial growth factor in endometrial tumour cells by resveratrol
and EGCG. Gynecol Oncol. 2009;113:374–378
Elattar TM, Virji AS. The effect of red wine and its components on growth and proliferation of human oral squamous carcinoma cells. Anticancer Res. 1999;19:5407–5414
Freeman A, Morris LS, Mills AD, Stoeber K, Laskey RA, Williams GH, Coleman N. Minichromosome maintenance proteins as biological markers of dysplasia and malignancy. Clin Cancer Res. 1999;5:2121–2132
Fremont L. Biological effects of resveratrol
. Life Sci. 2000;66:663–673
Gatz SA, Keimling M, Baumann C, Dork T, Debatin KM, Fulda S, Wiesmuller L. Resveratrol
modulates DNA double-strand break repair pathways in an ATM/ATR-p53- and Nbs1-dependent manner. Carcinogenesis. 2008;29:519–527
Helleday T, Lo J, van Gent DC, Engelward BP. DNA double-strand break repair: from mechanistic understanding to cancer treatment. DNA Repair (Amst). 2007;6:923–935
Jang M, Cai L, Udeani GO, Slowing KV, Thomas CF, Beecher CW, et al. Cancer chemopreventive activity of resveratrol
, a natural product derived from grapes. Science. 1997;275:218–220
Joe AK, Liu H, Suzui M, Vural ME, Xiao D, Weinstein IB. Resveratrol
induces growth inhibition, S-phase arrest, apoptosis, and changes in biomarker expression in several human cancer cell lines. Clin Cancer Res. 2002;8:893–903
Kearsey SE, Labib K. MCM proteins: evolution, properties, and role in DNA replication. Biochim Biophys Acta. 1998;1398:113–136
Kim MY, Trudel LJ, Wogan GN. Apoptosis induced by capsaicin and resveratrol
in colon carcinoma cells requires nitric oxide production and caspase activation. Anticancer Res. 2009;29:3733–3740
Kim YA, Choi BT, Lee YT, Park DI, Rhee SH, Park KY, Choi YH. Resveratrol
inhibits cell proliferation and induces apoptosis of human breast carcinoma MCF-7 cells. Oncol Rep. 2004;11:441–446
Lavin MF. ATM and the Mre11 complex combine to recognize and signal DNA double-strand breaks. Oncogene. 2007;26:7749–7758
Le Corre L, Fustier P, Chalabi N, Bignon YJ, Bernard-Gallon D. Effects of resveratrol
on the expression of a panel of genes interacting with the BRCA1 oncosuppressor in human breast cell lines. Clin Chim Acta. 2004;344:115–121
Lee SK, Zhang W, Sanderson BJ. Selective growth inhibition of human leukemia and human lymphoblastoid cells by resveratrol
via cell cycle arrest and apoptosis induction. J Agric Food Chem. 2008;56:7572–7577
Lin HY, Sun M, Tang HY, Simone TM, Wu YH, Grandis JR, et al. Resveratrol
causes COX-2- and p53-dependent apoptosis in head and neck squamous cell cancer cells. J Cell Biochem. 2008;104:2131–2142
Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001;25:402–408
Maiorano D, Lutzmann M, Mechali M. MCM proteins and DNA replication. Curr Opin Cell Biol. 2006;18:130–136
Malhotra A, Nair P, Dhawan DK. Curcumin and resveratrol
synergistically stimulate p21 and regulate COX-2 by maintaining adequate zinc levels during lung carcinogenesis. Eur J Cancer Prev. 2011;20:411–416
Narayanan BA, Narayanan NK, Stoner GD, Bullock BP. Interactive gene expression pattern in prostate cancer cells exposed to phenolic antioxidants. Life Sci. 2002;70:1821–1839
Narayanan BA, Narayanan NK, Re GG, Nixon DW. Differential expression of genes induced by resveratrol
in LNCaP cells: P53-mediated molecular targets. Int J Cancer. 2003;104:204–212
Nees M, Woodworth CD. Microarrays: spotlight on gene function and pharmacogenomics. Curr Cancer Drug Targets. 2001;1:155–175
Opipari AW Jr., Tan L, Boitano AE, Sorenson DR, Aurora A, Liu JR. Resveratrol
-induced autophagocytosis in ovarian cancer cells. Cancer Res. 2004;64:696–703
Park JW, Choi YJ, Suh SI, Baek WK, Suh MH, Jin IN, et al. Bcl-2 overexpression attenuates resveratrol
-induced apoptosis in U937 cells by inhibition of caspase-3 activity. Carcinogenesis. 2001;22:1633–1639
Pisani P. Breast cancer: geographic variation and risk factors. J Environ Pathol Toxicol Oncol. 1992;11:313–316
Pozo-Guisado E, Alvarez-Barrientos A, Mulero-Navarro S, Santiago-Josefat B, Fernandez-Salguero PM. The antiproliferative activity of resveratrol
results in apoptosis in MCF-7 but not in MDA-MB-231 human breast cancer cells: cell-specific alteration of the cell cycle. Biochem Pharmacol. 2002;64:1375–1386
Roy P, Kalra N, Prasad S, George J, Shukla Y. Chemopreventive potential of resveratrol
in mouse skin tumors through regulation of mitochondrial and PI3K/AKT signaling pathways. Pharm Res. 2009;26:211–217
Sanders TH, McMichael RW Jr., Hendrix KW. Occurrence of resveratrol
in edible peanuts. J Agric Food Chem. 2000;48:1243–1246
Sareen D, Darjatmoko SR, Albert DM, Polans AS. Mitochondria, calcium, and calpain are key mediators of resveratrol
-induced apoptosis in breast cancer. Mol Pharmacol. 2007;72:1466–1475
Sengottuvelan M, Deeptha K, Nalini N. Resveratrol
attenuates 1,2-dimethylhydrazine (DMH) induced glycoconjugate abnormalities during various stages of colon carcinogenesis. Phytother Res. 2009;23:1154–1158
Sobolev VS, Cole RJ. Trans-resveratrol
content in commercial peanuts and peanut products. J Agric Food Chem. 1999;47:1435–1439
Sorenson CM, Eastman A. Mechanism of cis-diamminedichloroplatinum (II)-induced cytotoxicity: role of G2 arrest and DNA double-strand breaks. Cancer Res. 1988;48:4484–4488
Stervbo U, Vang O, Bonnesen C. Time- and concentration-dependent effects of resveratrol
in HL-60 and HepG2 cells. Cell Prolif. 2006;39:479–493
Tseng SH, Lin SM, Chen JC, Su YH, Huang HY, Chen CK, et al. Resveratrol
suppresses the angiogenesis and tumor growth of gliomas in rats. Clin Cancer Res. 2004;10:2190–2202
Wolter F, Stein J. Resveratrol
enhances the differentiation induced by butyrate in caco-2 colon cancer cells. J Nutr. 2002;132:2082–2086
Wolter F, Akoglu B, Clausnitzer A, Stein J. Downregulation of the cyclin D1/Cdk4 complex occurs during resveratrol
-induced cell cycle arrest in colon cancer cell lines. J Nutr. 2001;131:2197–2203
Yalcin A. Quantification of thioredoxin mRNA expression in the rat hippocampus by real-time PCR following oxidative stress. Acta Biochim Pol. 2004;51:1059–1065