Oxidative Medicine and Cellular Longevity

Oxidative Medicine and Cellular Longevity / 2012 / Article
Special Issue

Dietary Polyphenols and Their Effects on Cell Biochemistry and Pathophysiology

View this Special Issue

Research Article | Open Access

Volume 2012 |Article ID 390385 | 17 pages | https://doi.org/10.1155/2012/390385

Coffee Polyphenols Change the Expression of STAT5B and ATF-2 Modifying Cyclin D1 Levels in Cancer Cells

Academic Editor: Luciano Pirola
Received10 Feb 2012
Revised16 May 2012
Accepted18 May 2012
Published07 Aug 2012

Abstract

Background. Epidemiological studies suggest that coffee consumption reduces the risk of cancer, but the molecular mechanisms of its chemopreventive effects remain unknown. Objective. To identify differentially expressed genes upon incubation of HT29 colon cancer cells with instant caffeinated coffee (ICC) or caffeic acid (CA) using whole-genome microarrays. Results. ICC incubation of HT29 cells caused the overexpression of 57 genes and the underexpression of 161, while CA incubation induced the overexpression of 12 genes and the underexpression of 32. Using Venn-Diagrams, we built a list of five overexpressed genes and twelve underexpressed genes in common between the two experimental conditions. This list was used to generate a biological association network in which STAT5B and ATF-2 appeared as highly interconnected nodes. STAT5B overexpression was confirmed at the mRNA and protein levels. For ATF-2, the changes in mRNA levels were confirmed for both ICC and CA, whereas the decrease in protein levels was only observed in CA-treated cells. The levels of cyclin D1, a target gene for both STAT5B and ATF-2, were downregulated by CA in colon cancer cells and by ICC and CA in breast cancer cells. Conclusions. Coffee polyphenols are able to affect cyclin D1 expression in cancer cells through the modulation of STAT5B and ATF-2.

1. Introduction

Polyphenols are the most abundant antioxidants in the diet. Their main dietary sources are fruits and plant-derived beverages such as fruit juices, tea, coffee, and red wine. Current evidence strongly supports a contribution of polyphenols to the prevention of cardiovascular diseases, cancers, and osteoporosis suggesting a role of these antioxidants in the prevention of neurodegenerative diseases and diabetes mellitus [1].

It is well established that polyphenol ingestion results in an increase of the plasma-antioxidant capacity. However, there is still some uncertainties about their efficiency to enhance the protection of cellular components, such as lipids or DNA, against oxidative stress in humans [2]. Polyphenols and other antioxidants were thought to protect cell constituents against oxidative damage by scavenging free radicals. However, this concept now appears to be an oversimplified view of their mode of action [3]. More likely, cells respond to polyphenols mainly through direct interactions with receptors or enzymes involved in signal transduction, which may result in modification of the redox status of the cell and may trigger a series of redox-dependent reactions [4]. This could also apply to the anticarcinogenic effects of polyphenols, which properties may be explained by many different mechanisms.

Hydroxycinnamic acids are a major class of polyphenols found in almost every plant [2]. The major representative of hydroxycinnamic acids is caffeic acid, which occurs in food mainly as an ester with quinic acid named chlorogenic acid (5-caffeoylquinic acid). Coffee is a major source of chlorogenic acid in the human diet; the daily intake in coffee drinkers is 0.5–1 g whereas coffee abstainers will usually ingest <100 mg/day. Studies have shown that approximately the 33% of ingested chlorogenic acid and the 95% of caffeic acid are absorbed intestinally [5]. Thus, about two-thirds of ingested chlorogenic acid reach the colon where it is probably metabolized to caffeic acid [6].

Bioavailability data suggest that the biological effects of chlorogenic acid would become apparent after its metabolism to caffeic acid, and hence the need of studying the effects of this acid. Chlorogenic acid and caffeic acid are antioxidants in vitro [7], and they might inhibit the formation of mutagenic and carcinogenic N-nitroso compounds since they are inhibitors of the N-nitrosation reaction in vivo [8]. Furthermore, chlorogenic acid can inhibit DNA damage in vitro [9] as it inhibits lipid peroxidation-induced DNA adduct formation [10] and suppresses reactive oxygen species-mediated nuclear factor (NF-κB), activator protein-1 (AP-1), and mitogen-activated protein kinase activation by upregulating antioxidant enzymes [11]. These studies suggested that coffee polyphenols are potent chemopreventive agents.

Recent meta-analyses demonstrate inverse associations between coffee intake and the risk of colon, liver, breast, and endometrial cancer [1215]. Moreover, in prospective population-based cohort studies, the inverse association between coffee consumption and risk of cancer has been shown. The group of Naganuma [16] found that the consumption of at least one cup of coffee per day was associated with a 49% lower risk of upper gastrointestinal cancer in a Japanese population, while Wilson and collaborators [17] found that men who regularly drink coffee appeared to have a lower risk of developing a lethal form of prostate cancer. The lower risk was evident when consuming either regular or decaffeinated coffee. It has been proposed that the inverse association between coffee intake and colon cancer could be explained, at least in part, by the presence of chlorogenic acid in coffee [18]. Ganmaa et al. [19] observed a general protective effect of caffeine intake on breast cancer risk for both ER subtypes, but the effect was only found to be significant for ER-positive breast cancers. In this study, the association between caffeine and breast cancer was stronger among postmenopausal women with estrogen-receptor and progesterone-receptor-positive breast cancer than those with estrogen-receptor and progesterone-receptor negative breast cancer [19]. In another study, coffee drinking specifically reduced the risk of developing ER-negative breast cancer but not ER-positive breast cancer [20].

Although there is enough evidence from epidemiological data supporting that coffee seems to reduce the risk of certain cancers, the molecular mechanisms underlying the chemopreventive effects of coffee remain unknown. For this reason, the aim of our study was to determine the effect at the molecular level of coffee polyphenols at low concentrations equivalent to one cup of coffee, using as a model a human colon cancer cell line HT29 in a nutrigenomic approach. Furthermore, the effect of coffee polyphenols was also evaluated in breast cancer cells.

2. Materials and Methods

2.1. Materials and Chemicals

Cells were incubated with Instant Caffeinated Coffee (ICC) (regular lyophilized instant coffee) and Caffeic acid (CA, Sigma). Compounds were dissolved either in DMSO (CA), or sterile water (ICC), and stored at −20°C.

2.2. Cell Culture

Colon adenocarcinoma HT29 and breast cancer MCF-7 cell lines were routinely grown in Ham’s F12 medium supplemented with 7% fetal bovine serum (FBS, both from Gibco) at 37°C in a 5% CO2 humidified atmosphere in 10 cm dish, or in 33 mm plate.

Cells were incubated with ICC or CA at concentrations equivalent to one cup of coffee. The concentrations used in cell incubations, 7 μg/mL in H2O mQ for ICC and 1.68 μg/mL in DMSO for CA, respectively, took into account the amount of these compounds in one cup of coffee and their distribution in a regular human body with 75% water content. These concentrations did not cause any cytotoxic effect in the cell incubations as determined by the MTT assay [21].

2.3. Microarrays

Gene expression was analyzed by hybridization to The GeneChip Human Genome U133A plus 2.0 microarrays from Affymetrix, containing 47,000 transcripts and variants. HT29 cells were incubated with ICC and CA for 24 h. Total RNA was prepared from triplicate samples using Speedtools Total RNA Extraction Kit (Biotools) following the recommendations of the manufacturer. RNA quality was tested by 2100 Bioanalyzer Eukaryote Total RNA Nano Series II (Agilent Technologies). Labeling, hybridization, and detection were carried out following the manufacturer’s specifications at the IDIBAPS Genomic Service (Hospital Clínic, Barcelona).

2.4. Microarray Data Analyses

Quantification was carried out with GeneSpring GX v.11.5.1 software (Agilent Technologies), which allows multifilter comparisons using data from different experiments to perform the normalization, generation of lists, and the functional classification of the differentially expressed genes. The input data was subjected to preprocess baseline transformation using the Robust Multiarray Average summarization algorithm using the median of control samples. After grouping the triplicate of each experimental condition, list of differentially expressed genes could be generated by using volcano plot analysis. The expression of each gene is reported as the ratio of the value obtained after each condition relative to control condition after normalization and statistical analysis of the data. The corrected value cutoff applied was of <0.05; then the output of this statistical analysis was filtered by fold expression, selecting specifically those genes that had a differential expression of at least 1.3-fold. Gene classification was established by the Gene Ontology database.

2.5. Common Genes between ICC and CA Treatments

Common genes were selected from the lists of differentially expressed genes for each treatment using Venn-Diagrams. The newly generated list contained both over and underexpressed genes.

2.6. Generation of Biological Association Networks

BANs were constructed with the aid of the Pathway Analysis within the GeneSpring v.11.5.1 (Agilent) as described in Selga et al. [22] with the list of common genes differentially expressed in both treatments. A filtered screening was processed by the program between our data and bibliographic interaction databases up to a total of 100 related genes. Network associations were confirmed in the literature.

2.7. RT Real-Time PCR

Total RNA was extracted from HT29 cells using Ultraspec (Biotex) in accordance with the manufacturer's instructions.

Complementary DNA was synthesized as described in Selga et al. [23] and the cDNA product was used for amplification by real time PCR. STAT5B and ATF-2 mRNA levels were determined in an ABI Prism 7000 Sequence Detection System (Applied Biosystems) using 3 μL of the cDNA reaction and the assays-on-demand Hs00560035_m1 for STAT5B, Hs00153179_ml for ATF-2, and Hs00356991_m1 for APRT (all from Applied Biosystems). APRT mRNA was used as an endogenous control. The reaction was performed following the manufacturers recommendations. Fold changes in gene expression were calculated using the standard Ct method.

2.8. Western Blot

Whole extracts were obtained from control or treated cells according to Selga et al. [23]. Five μL of the extract was used to determine protein concentration by the Bradford assay (Bio-Rad). The extracts were frozen in liquid N2 and stored at −80°C. Total extracts (50 μg) were resolved on SDS-polyacrylamide gels and transferred to PVDF membranes (Immobilon P, Millipore) using a semidry electroblotter.

The SNAP i.d. protein detection system technology (Millipore) was used to probe the membranes. This system applies vacuum through the membrane to actively drive reagents to protein locations, unlike the traditional technique of diffusion over the membrane as a reagent transport. Table 1 compiles the antibodies used in the different determinations.


AntibodyMolecular weight (KDa)Dilution usedSupplier

STAT5B951: 200sc-835, Santa Cruz Biotechnology Inc.
ATF-2721: 200sc-6233, Santa Cruz Biotechnology Inc.
Cyclin D1381: 200sc-8396, Santa Cruz Biotechnology Inc.
-actin421: 200A2066, Sigma
Tubulin601: 100CP06, Calbiochem

Signals were detected by secondary horseradish peroxidase-conjugated antibody, either anti-rabbit (1 : 5000 or 1 : 10000 dilution; Dako) or anti-mouse (1 : 2500 dilution, Amersham NIF 824) and enhanced chemiluminescence using the ECL method, as recommended by the manufacturer (Amersham). Chemiluminescence was detected with ImageQuant LAS 4000 Mini technology (GE Healthcare).

2.9. Statistical Methods

For the RT-PCR and Western blot analyses, values are expressed as the mean ± SE of three different experiments. Data were evaluated by unpaired Student's t test, and analyses were performed using the PASW Statistics v. 18.0.0. software.

3. Results

3.1. Effect of ICC and CA Incubations in HT29 Gene Expression

The expression profile of over 47,000 transcripts and variants included in the microarray HG U133 plus 2.0 from Affymetrix was compared between HT29 control cells and cells incubated with either CA or ICC, at nontoxic concentrations for 24 h. GeneSpring GX software v.11.5.1 was used to analyze the results. A list of differentially expressed genes by 1.3-fold with a P value cutoff of <0.05 was generated as described in Methods. When HT29 cells were incubated with ICC, 57 genes were overexpressed whereas 161 genes were underexpressed. Among the overexpressed genes, 24% belonged to the Transcription factors category and 19% to Cell cycle or to Biosynthetic processes. Within the underexpressed genes, the category corresponding to cell cycle was the most affected (53% of the genes) followed by Transcription factors (19%) and Biosynthetic processes (12%). Upon incubation with CA, 12 genes were overexpressed whereas 32 genes were underexpressed. Among the overexpressed genes, 33% belonged to the Transcription factors category, 25% to Cell cycle, and 16,7% to Biosynthetic processes or immune response. Within the underexpressed genes, again the category corresponding to Cell cycle was the most affected (30% of the genes) followed by Biosynthetic processes (15%) and Transcription factors (12%). The lists of differentially expressed genes are presented as Tables 2, 3, 4, and 5. The data presented in this work have been deposited in the Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) and are accessible through GEO series accession number [GSM867162].


Gene symbolGene title valueFC absoluteRegulation

CALM3Calmodulin 3 (phosphorylase kinase, delta)0.0161.3Up
CDC42EP1CDC42 effector protein (Rho GTPase binding) 10.0271.3Up
FOXN3Forkhead box N30.0221.3Up
KIR2DL1Killer cell immunoglobulin-like receptor, two domains, long cytoplasmic tail, 10.0231.3Up
ORAI2ORAI calcium release-activated calcium modulator 20.0111.3Up
RAPGEF1Rap guanine nucleotide exchange factor (GEF) 10.0221.3Up
STHSaitohin0.0311.3Up
SLC39A3Solute carrier family 39 (zinc transporter), member 30.0281.3Up
ZNF397OSZinc finger protein 397 opposite strand0.0241.3Up
ZP4Zona pellucida glycoprotein 40.0461.3Up
FGFRL1Fibroblast growth factor receptor-like 10.0351.31Up
ITGA9Integrin, alpha 90.0021.31Up
IRAK1Interleukin-1 receptor-associated kinase 10.0381.31Up
OBSL1Obscurin-like 10.0081.31Up
RPS17L4Ribosomal protein S17-like 40.0261.31Up
STAT5BSignal transducer and activator of transcription 5B0.0071.31Up
TRABDTraB domain containing0.0431.31Up
MYO9BMyosin IXB0.0411.32Up
NME7Nonmetastatic cells 7, protein expressed in (nucleoside-diphosphate kinase)0.0371.32Up
RPS6KA4Ribosomal protein S6 kinase, 90 kDa, polypeptide 40.0141.32Up
SIRPASignal-regulatory protein alpha0.0191.32Up
TBX20T-box 200.0351.32Up
TCF20Transcription factor 20 (AR1)0.0221.32Up
ALDH3B1Aldehyde dehydrogenase 3 family, member B10.0051.33Up
BGNBiglycan0.0291.33Up
GNB4Guanine nucleotide binding-protein (G protein), b-polypeptide 40.0441.33Up
IFNA17Interferon, alpha 170.0261.33Up
KYKyphoscoliosis peptidase0.0131.33Up
SCARF1Scavenger receptor class F, member 10.0251.33Up
SERPINB8Serpin peptidase inhibitor, clade B (ovalbumin), member 80.011.33Up
FSTFollistatin0.0251.34Up
MOGAT1Monoacylglycerol O-acyltransferase 10.0091.34Up
PPARGC1APeroxisome proliferator-activated receptor gamma, coactivator 1 alpha0.0151.34Up
SUCLG2Succinate-CoA ligase, GDP-forming, beta subunit0.0111.34Up
SULT1B1Sulfotransferase family, cytosolic, 1B, member 10.0181.34Up
TBX10T-box 100.0111.34Up
ZNF503Zinc finger protein 5030.0221.34Up
HBA1Hemoglobin, alpha 10.041.35Up
MEPEMatrix, extracellular phosphoglycoprotein with ASARM motif0.0011.35Up
PPP1CBProtein phosphatase 1, catalytic subunit, beta isoform0.031.35Up
ARV1ARV1 homolog (S. cerevisiae)0.0111.36Up
BCL3B-cell CLL/lymphoma 30.0341.36Up
CTRCChymotrypsin C (caldecrin)0.0451.36Up
EPORErythropoietin receptor0.0081.37Up
HMGA1High-mobility group AT-hook 10.0391.37Up
IL19Interleukin 190.0181.38Up
ABCC12ATP-binding cassette, subfamily C (CFTR/MRP), member 126.00E-041.39Up
RAI1Retinoic acid induced 10.0171.39Up
KLF5Kruppel-like factor 5 (intestinal)0.0281.4Up
CBWD1COBW domain containing 10.0441.41Up
ASAH3N-acylsphingosine amidohydrolase (alkaline ceramidase) 30.0391.43Up
ABHD14BAbhydrolase domain containing 14B0.031.45Up
TLN1Talin 10.0491.45Up
ARHGAP23Rho GTPase-activating protein 230.0241.65Up
HINT3Histidine triad nucleotide binding protein 30.0021.77Up
ARHGDIARho GDP dissociation inhibitor (GDI) alpha0.0341.83Up
CALRCalreticulin0.0071.93Up

The table shows the list of overexpressed genes by 1.3-fold with a value obtained in cells treated with instant caffeinated coffee and includes the gene symbol for all genes, and their associated description. The ratio columns correspond to the absolute fold change in expression relative to the control group and the type of regulation (up: upregulation).

Gene symbolGene title valueFC absoluteRegulation

ACBD5Acyl-coenzyme A binding domain containing 50.0171.3Down
CXADRCoxsackie virus and adenovirus receptor0.0151.3Down
FANCD2Fanconi anemia, complementation group D20.0471.3Down
FRYLFRY-like0.0391.3Down
NUB1Negative regulator of ubiquitin-like proteins 10.0291.3Down
PBRM1Polybromo 10.0041.3Down
PRKACBProtein kinase, cAMP-dependent, catalytic, beta0.0331.3Down
RIF1RAP1 interacting factor homolog (yeast)0.0121.3Down
SLC39A6Solute carrier family 39 (zinc transporter), member 60.0221.3Down
TMEM170Transmembrane protein 1700.0321.3Down
WDR26WD repeat domain 260.0281.3Down
RNGTTRNA guanylyltransferase and 5-phosphatase0.041.3Down
CTDSPL2CTD small phosphatase like 20.031.3Down
ZC3H11AZinc finger CCCH-type containing 11A0.0141.3Down
TMOD3Tropomodulin 3 (ubiquitous)0.01711.3Down
CPDCarboxypeptidase D0.0021.31Down
CBLCas-Br-M ecotropic retroviral transforming sequence0.0081.31Down
CDC42SE2CDC42 small effector 20.0221.31Down
CLN5Ceroid-lipofuscinosis, neuronal 50.0011.31Down
DDX3XDEAD (Asp-Glu-Ala-Asp) box polypeptide 3, X-linked0.0271.31Down
FGFR1OP2FGFR1 oncogene partner 20.0491.31Down
LRRFIP1Leucine-rich repeat (in FLII) interacting protein 10.0261.31Down
PDCD4Programmed cell death 40.0051.31Down
REPS2RALBP1-associated Eps domain containing 20.0461.31Down
SLC7A6Solute carrier family 7, member 60.0021.31Down
TFRCTransferrin receptor (p90, CD71)0.0381.31Down
TMEM19Transmembrane protein 190.0241.31Down
AGPSAlkylglycerone phosphate synthase0.0011.31Down
SLC4A7Solute carrier family 4, member 70.0281.31Down
SPTAN1Spectrin, alpha, nonerythrocytic 1 (alpha-fodrin)0.021.31Down
GPD2Glycerol-3-phosphate dehydrogenase 2 (mitochondrial)0.0331.31Down
BICD1Bicaudal D homolog 1 (Drosophila)0.0081.31Down
FBXW11F-box and WD repeat domain containing 110.0251.31Down
BCLAF1BCL2-associated transcription factor 10.0251.32Down
CDH1Cadherin 1, type 1, E-cadherin (epithelial)0.0111.32Down
CLK4CDC-like kinase 40.0491.32Down
PTAR1Protein prenyltransferase alpha subunit repeat containing 10.0271.32Down
SMEK2SMEK homolog 2, suppressor of mek1 (Dictyostelium)0.0121.32Down
CEPT1Choline/ethanolamine phosphotransferase 10.0381.32Down
SAR1ASAR1 gene homolog A (S. cerevisiae)0.0331.32Down
PDGFCPlatelet-derived growth factor C0.021.32Down
NFAT5Nuclear factor of activated T-cells 5, tonicity responsive0.0451.32Down
FRS2Fibroblast growth factor receptor substrate 20.031.32Down
BMS1P5BMS1 pseudogene 50.0361.33Down
GLSGlutaminase5.00E-041.33Down
LMAN1Lectin, mannose binding, 17.00E-041.33Down
ARHGAP18Rho GTPase-activating protein 188.00E-041.33Down
ARHGAP5Rho GTPase-activating protein 50.0061.33Down
CCNE2Cyclin E20.0361.33Down
SPCS3Signal peptidase complex subunit 3 homolog (S. cerevisiae)0.0081.33Down
NCOA2Nuclear receptor coactivator 20.0051.33Down
SRPRBSignal recognition particle receptor, B subunit0.0181.33Down
TLK1Tousled-like kinase 10.041.33Down
NCOA3Nuclear receptor coactivator 30.0481.33Down
STRN3Striatin, calmodulin-binding protein 32.00E-041.33Down
AP1G1Adaptor-related protein complex 1, gamma 1 subunit0.0041.34Down
B3GALNT2Beta-1,3-N-acetylgalactosaminyltransferase 20.0341.34Down
PPHLN1Periphilin 12.00E-041.34Down
SNX13Sorting nexin 130.0011.34Down
TMED2Transmembrane emp24 domain-trafficking protein 20.0411.34Down
BRWD1Bromodomain and WD repeat domain containing 10.0111.34Down
HLA-BMajor histocompatibility complex, class I, B0.0281.34Down
CHPCalcium-binding protein P220.0021.34Down
MTMR9Myotubularin-related protein 90.0261.34Down
DCUN1D4DCN1, defective in cullin neddylation 1, domain containing 40.0311.34Down
ARL6IP2ADP-ribosylation factor-like 6 interacting protein 20.021.35Down
GLIS3GLIS family zinc finger 30.011.35Down
LARP4La ribonucleoprotein domain family, member 40.0191.35Down
PTPLBProtein tyrosine phosphatase-like member b0.0361.35Down
TRAM1Translocation-associated membrane protein 10.0021.35Down
TMEM64Transmembrane protein 640.0011.35Down
CBFBCore-binding factor, beta subunit0.0051.35Down
SELTSelenoprotein T0.0021.35Down
PEX13Peroxisome biogenesis factor 130.0111.35Down
TNKS2TRF1-interacting ankyrin-related ADP-ribose polymerase 20.0341.35Down
TMPOThymopoietin0.0011.35Down
LIN7CLin-7 homolog C (C. elegans)0.0071.35Down
MTA2Metastasis-associated 1 family, member 20.0131.36Down
TMEM168Transmembrane protein 1680.0351.36Down
CREBZFCREB/ATF bZIP transcription factor0.0161.36Down
OSTF1Osteoclast-stimulating factor 10.0021.36Down
WDR57WD repeat domain 57 (U5 snRNP specific)0.0011.36Down
GLT25D1Glycosyltransferase 25 domain containing 10.0081.36Down
NAPGN-ethylmaleimide-sensitive factor attachment protein, gamma0.0151.36Down
CCDC126Coiled-coil domain containing 1260.0391.37Down
LASS6LAG1 homolog, ceramide synthase 60.0051.37Down
MYSM1Myb-like, SWIRM and MPN domains 10.0211.37Down
CYP51A1Cytochrome P450, family 51, subfamily A, polypeptide 10.0071.37Down
PDE4DIPPhosphodiesterase 4D interacting protein (myomegalin)0.0241.37Down
SAP30LSAP30-like0.0121.37Down
PTPRJProtein tyrosine phosphatase, receptor type, J0.0111.37Down
PGGT1BProtein geranylgeranyltransferase type I, beta subunit9.00E-041.37Down
ASPHAspartate beta-hydroxylase0.0111.37Down
SEMA3CSema domain, (semaphorin) 3C0.0361.38Down
WDR76WD repeat domain 760.0161.38Down
ATP13A3ATPase-type 13A30.0021.38Down
LMBR1Limb region 1 homolog (mouse)0.0141.38Down
GLUD1Glutamate dehydrogenase 10.0011.39Down
GSTCDGlutathione S-transferase, C-terminal domain containing0.0291.39Down
SPTLC1Serine palmitoyltransferase, subunit 10.021.39Down
U2AF1U2 small nuclear RNA auxiliary factor 19.00E-041.39Down
UHMK1U2AF homology motif (UHM) kinase 10.0071.39Down
ARGLU1Arginine and glutamate-rich 16.00E-041.39Down
ANKRD12Ankyrin repeat domain 120.031.39Down
PPP3R1Protein phosphatase 3, regulatory subunit B, alpha isoform0.0231.39Down
XRN15-3 exoribonuclease 10.0191.4Down
CLSPNClaspin homolog (Xenopus laevis)0.0131.4Down
CXADRP1Coxsackie virus and adenovirus receptor pseudogene 10.0341.4Down
G3BP1GTPase-activating protein- (SH3 domain) binding protein 10.0021.4Down
TMEM30ATransmembrane protein 30A0.011.4Down
CLCN3Chloride channel 30.0351.41Down
STK4Serine/threonine kinase 40.0391.41Down
ZNF644Zinc finger protein 6440.021.41Down
TCP11L1T-complex 11 (mouse)-like 10.0141.41Down
SFRS6Splicing factor, arginine/serine-rich 60.0311.41Down
NPLN-acetylneuraminate pyruvate lyase0.0061.41Down
G3BP2GTPase-activating protein- (SH3 domain) binding protein 20.0011.42Down
HNRNPUHeterogeneous nuclear ribonucleoprotein U0.011.42Down
TBL1XR1Transducin (beta)-like 1 X-linked receptor 10.0011.42Down
PHTF2Putative homeodomain transcription factor 20.0021.42Down
ADAM10ADAM metallopeptidase domain 100.0111.43Down
ADAM9ADAM metallopeptidase domain 9 (meltrin gamma)0.011.43Down
MALAT1Metastasis-associated lung adenocarcinoma transcript 10.041.43Down
SCARB2Scavenger receptor class B, member 20.0011.43Down
CANXCalnexin0.0431.43Down
CASP2Caspase 2, apoptosis-related cysteine peptidase0.0331.43Down
TRPS1Trichorhinophalangeal syndrome I0.0051.44Down
ZFXZinc finger protein, X-linked0.0331.44Down
SGPL1Sphingosine-1-phosphate lyase 10.041.44Down
PTPN11Protein tyrosine phosphatase, nonreceptor type 110.0451.44Down
SFRS11Splicing factor, arginine/serine-rich 110.0451.45Down
B3GNT5Beta-1,3-N-acetylglucosaminyltransferase 50.0211.45Down
MAP3K1Mitogen-activated protein kinase kinase kinase 10.0191.45Down
SNHG4Small nucleolar RNA host gene (nonprotein coding) 40.0041.46Down
PARD6BPar-6 partitioning defective 6 homolog beta (C. elegans)0.041.46Down
ROD1ROD1 regulator of differentiation 1 (S. pombe)0.0011.46Down
SPTBN1Spectrin, beta, nonerythrocytic 10.021.48Down
TXNDC1Thioredoxin domain containing 10.0131.48Down
ATF2Activating transcription factor 20.0051.48Down
RDXRadixin0.0431.48Down
SCAMP1Secretory carrier membrane protein 10.0091.48Down
PTAR1Protein prenyltransferase alpha subunit repeat containing 10.0181.49Down
RC3H2Ring finger and CCCH-type zinc finger domains 20.00371.49Down
ADAM17ADAM metallopeptidase domain 170.0071.49Down
FAM76BFamily with sequence similarity 76, member B0.0141.5Down
ITGB8Integrin, beta 81.00E-041.5Down
TRIM23Tripartite motif-containing 230.0051.5Down
CASC5Cancer susceptibility candidate 50.0191.52Down
SLC16A1Solute carrier family 16, member 10.0021.52Down
FNBP1Formin-binding protein 10.0371.53Down
PRKAR1AProtein kinase, cAMP-dependent, regulatory, type I, alpha9.00E-041.53Down
B4GALT1Beta 1,4-galactosyltransferase, polypeptide 10.0351.55Down
MDM4Mdm4 p53-binding protein homolog (mouse)0.0111.58Down
FGD4FYVE, RhoGEF, and PH domain containing 40.0011.59Down
UBA6Ubiquitin-like modifier activating enzyme 68.00E-041.62Down
ZDHHC21Zinc finger, DHHC-type containing 210.0361.64Down
REEP3Receptor accessory protein 37.00E-041.65Down
SSR3Signal sequence receptor, gamma0.0141.65Down
ZDHHC20Zinc finger, DHHC-type containing 200.0031.66Down
EIF2S3Eukaryotic translation initiation factor 2, subunit 3 gamma0.0011.7Down
HNRNPH1Heterogeneous nuclear ribonucleoprotein H10.0111.79Down
ATL3Atlastin 30.0012.02Down

The table shows the list of underexpressed genes by 1.3-fold with a value obtained in cells treated with instant caffeinated coffee and includes the gene symbol for all genes, and their associated description. The ratio columns correspond to the absolute fold change in expression relative to the control group and the type of regulation (down: downregulation).

Gene symbolGene title valueFC absoluteRegulation

SULT1B1Sulfotransferase family, cytosolic, 1B, member 10.021.3Up
BCL6BB-cell CLL/lymphoma 6, member B (zinc finger protein)3.00E-041.3Up
KCNJ5Potassium inwardly-rectifying channel, subfamily J, member 50.011.31Up
EPORErythropoietin receptor0.021.32Up
DNAJC21DnaJ (Hsp40) homolog, subfamily C, member 210.0491.33Up
STAT5BSignal transducer and activator of transcription 5B0.0121.33Up
FSTFollistatin0.0211.37Up
CD84CD84 molecule0.0331.37Up
THRAThyroid hormone receptor, alpha0.0171.37Up
MAPK8IP3Mitogen-activated protein kinase 8 interacting protein 30.0281.4Up
SIAESialic acid acetylesterase0.012.42Up
HINT3Histidine triad nucleotide-binding protein 30.0332.6Up

The table shows the list of overexpressed genes by 1.3-fold with a value obtained in cells treated with caffeic acid and includes the gene symbol for all genes, their associated description. The ratio columns correspond to the absolute fold change in expression relative to the control group and the type of regulation (up: upregulation).

Gene symbolGene title valueFC absoluteRegulation

MFSD7Major facilitator superfamily domain containing 71.00E-041.3Down
MSI2Musashi homolog 2 (Drosophila)0.0271.3Down
CDACytidine deaminase2.00E-041.31Down
DEFB1Defensin, beta 10.0261.31Down
PIP5K1APhosphatidylinositol-4-phosphate 5-kinase, type I, alpha0.0271.31Down
ZDHHC20Zinc finger, DHHC-type containing 200.0051.31Down
ZDHHC21Zinc finger, DHHC-type containing 210.0161.31Down
SLC4A7Solute carrier family 4, member 70.02491.32Down
CEACAM1Carcinoembryonic antigen-related cell adhesion molecule 10.04591.32Down
PDZRN3PDZ domain containing RING finger 30.0021.32Down
WDR62WD repeat domain 620.0051.32Down
FAM76BFamily with sequence similarity 76, member B0.0361.32Down
TCF21Transcription factor 210.0291.33Down
TBL1XR1Transducin (beta)-like 1 X-linked receptor 16.00E-041.33Down
CLK4CDC-like kinase 40.0211.33Down
CYP2A13Cytochrome P450, family 2, subfamily A, polypeptide 130.0091.34Down
CXCR4Chemokine (C-X-C motif) receptor 40.04881.34Down
ATF2Activating transcription factor 20.01581.35Down
PDE10APhosphodiesterase 10A0.031.35Down
METT10DMethyltransferase 10 domain containing0.0031.35Down
PRMT2Protein arginine methyltransferase 27.00E-041.36Down
GLSGlutaminase5.70E-041.37Down
SLC38A5Solute carrier family 38, member 50.0431.37Down
TINAGTubulointerstitial nephritis antigen0.0431.38Down
AQP1Aquaporin 1 (Colton blood group)0.02211.4Down
JMJD6Jumonji domain containing 60.0041.4Down
SAP30LSAP30-like0.0211.4Down
FGD4FYVE, RhoGEF, and PH domain containing 40.0261.52Down
S100A2S100 calcium-binding protein A20.0051.53Down
CTSZCathepsin Z0.0451.53Down
SLC4A4Solute carrier family 4, member 49.00E-041.54Down
AGR3Anterior gradient homolog 3 (Xenopus laevis)0.0111.69Down

The table shows the list of underexpressed genes by 1.3-fold with a value obtained in cells treated with caffeic acid and includes the gene symbol for all genes, their associated description. The ratio columns correspond to the absolute fold change in expression relative to the control group and the type of regulation (down: downregulation).
3.2. Generation of Biological Association Networks

A Biological Association Network (BAN) was constructed using the Pathway Analysis within GeneSpring v.11.5.1 as described in Methods using as the starting list the common genes differentially expressed upon incubation with CA and ICC. This list included five overexpressed genes and twelve underexpressed genes (Table 6). In the generated network, signal transducer and activator of transcription 5B (STAT5B) and activating transcription factor 2 (ATF-2) appeared as highly interconnected nodes (Figure 1). These two main nodes were selected for further validations. STAT5B was overexpressed with respect to the control by 23.8% in cells treated with ICC and by 33.4% in cells treated with CA, whereas ATF-2 was found underexpressed in HT29 incubated with ICC (32.5% decrease compared to the control) and with CA (26% decrease).


Gene symbolFC absolute ICC valueRegulationFC absolute CA valueRegulation

FST1.3430.025Up1.3750.022Up
SULT1B11.3490.018Up1.3040.020Up
EPOR1.3720.008Up1.3210.021Up
HINT32.4100.040Up2.6070.033Up
STAT5B1.3120.007Up1.3340.012Up
GLS1.3350.001Down1.3700.001Down
PPP3R11.3970.023Down1.4230.026Down
ATF21.4810.005Down1.3540.016Down
SLC4A71.3140.029Down1.3220.025Down
MARCH31.3300.016Down1.3190.005Down
TBL1XR11.4260.001Down1.3320.001Down
SAP30L1.3750.013Down1.4050.021Down
FGD41.5930.001Down1.5230.027Down
ZDHHC201.6650.004Down1.3140.005Down
ZDHHC211.6420.037Down1.3180.016Down
FAM76B1.5060.014Down1.3250.037Down
CLK41.3260.049Down1.3390.021Down

Common differentially expressed genes in HT29 treated-cells with a value and a minimum fold of 1.3. Column ICC correspond to cells treated with instant caffeinated coffee and column CA corresponds to cells treated with caffeic acid. Overexpressed genes are indicated on the upper part of the table, whereas underexpressed genes are depicted in the lower part. The genes in bold, STAT5B and ATF-2, were chosen for further analysis.
3.3. Validation of STAT5B and ATF-2 Changes at the mRNA and Protein Levels

STAT5B overexpression in HT29 cells upon incubation with CA and ICC was confirmed at the mRNA (1.16- and 1.3-fold compared to the control, respectively) and protein levels (1.5- and 1.2-fold compared to the control, respectively) (Figures 2(a) and 2(c)). In the case of ATF-2, the changes in mRNA levels were confirmed for both CA and ICC (0.88- and 0.86-fold compared to the control, respectively), whereas the decrease in protein levels was only observed in CA-treated cells (0.62-fold compared to the control) (Figures 2(b) and 2(d)).

3.4. Expression of Cyclin D1 upon Incubation with ICC and CA

Cyclin D1 is overexpressed at the mRNA and protein level in over 50% of the breast cancers either in the presence or absence of gene amplification, and it is one of the most commonly overexpressed proteins in breast cancer [24, 25]. Cyclin D1 transcription is regulated by STAT5 [2629] and ATF-2 [3032].

We analyzed the levels of cyclin D1 by western blot in MCF-7 and HT29 cells upon incubation with ICC and CA. As shown in Figure 3(a), incubation of MCF-7 cells with either CA and ICC led to a drastic decrease in the levels of cyclin D1 protein, together with an increase in the levels of STAT5B, but not to a decrease in the levels of ATF-2. In HT29 cells, incubation with CA did not affect cyclin D1 levels, whereas the presence of ICC led to an increase in cyclin D1 levels 3 (b).

4. Discussion

In this work we analyzed the gene expression profile of human cancer cells treated with either ICC or CA. Caffeic acid was chosen since it is the main representative of hydroxycinnamic acids. Using microarrays we identified the differential expression of specific genes involved in several biological pathways. The changes in mRNA expression of two outlier genes, STAT5B and ATF-2, observed in the microarrays were confirmed by RT real-time PCR, and the changes in protein levels were also analyzed by Western blot. The selection of STAT5B and ATF-2 was made according to the results obtained in the construction of a biological association network. Finally, the modulation of cyclin D1, a target of STAT5B and ATF-2 transcription factors, upon incubation with coffee polyphenols was also established.

We show that ICC and the amount of CA of one cup of coffee are able to induce STAT5B mRNA and protein levels in HT29 cells. STAT5 was originally described as a prolactin-induced mammary gland factor [33]. The cloning of two closely related STAT5 cDNAs, from both mouse and human cDNA libraries, showed two distinct genes, STAT5A and STAT5B that encoded two STAT5 proteins [3437].

In addition to prolactin, STAT5 proteins are activated by a wide variety of cytokines and growth factors, including IL-2, IL-3, IL-5, IL-7, IL-9, IL-15, granulocyte-macrophage colony-stimulating factor, erythropoietin, growth hormone, thrombopoietin, epidermal growth factor, and platelet-derived growth factor. The key function of STAT5B is to mediate the effects of growth hormone [38, 39]. Modulation of STAT5 levels or transcriptional activity has already been described in cells treated with natural compounds such as nobiletin, a citrus flavonoid [40], thea flavins [41], and silibinin, a natural polyphenolic flavonoid which is a major bioactive component of silymarin isolated from Silybum marianum [42]. Furthermore, it has been reported that butein, the major biologically active polyphenolic component of the stems of Rhus verniciflua, downregulated the expression of STAT3-regulated gene products such as Bcl-xL, Bcl-2, cyclin D1, and Mcl-1 [43].

STAT5B participates in diverse biological processes, such as growth development, immunoregulation, apoptosis, reproduction, prolactin pathway, and lipid metabolism. STAT5B deficiency is a recently identified disease entity that involves both severe growth hormone-resistant growth failure and severe immunodeficiency [4446]. The induction of STAT5B expression upon incubation with CA and ICC could represent a nutritional tool to upregulate this transcription factor and suggests novel research strategies for natural therapies in Crohn’s disease and inflammatory bowel disease in which STAT5B appears to maintain the mucosal barrier integrity and tolerance [47, 48]. In colorectal cancer both STAT5a and STAT5b play important roles in progression and downregulation of both STAT5A and STAT5B results in a gradual decrease in cell viability, predominantly attributed to G1 cell cycle arrest, and apoptotic cell death [49]. In this context the increase in STAT5B caused by ICC and CA would have a negative effect on colorectal cancer patients, as it would trigger cell proliferation and survival.

In human breast cancer, STAT5A/B has been shown a dual role in the mammary gland as an initiator of tumor formation as well as a promoter of differentiation of established tumors. STAT3, STAT5A, and STAT5B are overexpressed or constitutively activated in breast cancer [5052] and active STAT5A/B in human breast cancer predicted favorable clinical outcome [53]. Prolactin receptor signal transduction through the Jak2-STAT5 pathway has been considered to be essential for proliferation and differentiation of normal mammary epithelial cells [5456]. It has been shown that the levels of NUC-pYSTAT5 decreased as breast cancer progressed from normal to in situ, to invasive, and then to nodal metastases [57]. Additionally Peck et al. [57] found that the absence of detectable NUC-pYStat5 in tumors of patients how where under antiestrogen therapy was associated with poor breast cancer-specific survival. We analyzed STAT5B modulation through the PRL pathway in response to coffee polyphenols in a breast cancer cell line. The MCF-7 cell line was chosen because expression of the prolactin receptor is more often found in estrogen receptor-positive breast tumors [58]. In our conditions, incubation with CA and ICC led to an increase in STAT5B protein levels in MCF-7 cells, and this result could be the basis for a possible inclusion of coffee polyphenols in the diet of breast cancer patients.

ATF-2 is a member of the ATF-cAMP response element-binding protein (CREB) family of transcription factors that can bind to the cAMP response element (CRE) found in many mammalian gene promoters [59, 60]. ATF-2 exhibits both oncogenic and tumor suppressor functions [61]. CREs are found in several genes involved in the control of the cell cycle, for example, the cyclin D1 gene, and ATF-2 binding to this sequence stimulates the transcription of cyclin D1 [30, 31]. ATF-2 mediated cyclin D1 promoter induction can be stimulated by a number of growth-promoting agents, such as estrogen [31], hepatocyte growth factor [62], and regenerating gene product [63]. ATF-2 has been correlated with proliferation, invasion, migration, and resistance to DNA-damaging agents in breast cancer cell lines.

The downregulation of ATF-2 expression after CA and ICC incubation in HT29 cells reported here is in accordance with the observed decrease in activity of ATF-2 in gastric cells when incubating with chlorogenic acid, the precursor of caffeic acid [64]. Surprisingly, the validation of the protein levels showed the upregulation of ATF-2 protein with ICC, but not with CA, both in HT29 and MCF-7 cells. This differential behavior could be due to other ICC components besides CA. In this direction Rubach et al. [64] reported a different response in ATF-2 activity after incubation of a gastric cell line with different coffee compounds. The presence of pyrogallol, catechol, βN-alkanoylhydroxytryptamides, and N-methylpyridinium increased ATF-2 activity, whereas chlorogenic acid and caffeine decrease it [64]. In our conditions incubation of HT29 cells with ICC caused a modest decrease in ATF-2 mRNA levels. However this effect was not translated at the protein level. We hypothesize that ICC contains other polyphenols in addition to caffeic acid that are able to increase ATF-2 protein levels through an increase of the translation of its mRNA, the increase of stability of the protein or an inhibition of its degradation. In this direction several plant polyphenols such as (-)-epigallocatechins-3-gallate (EGCG), genistein, luteolin, apigenin, chrysin, quercetin, curcumin, and tannic acid have been described to possess proteasome-inhibitory activity [65, 66].

The regulation of ATF-2 transcriptional activity, mostly at the level of its phosphorylation status, has been described upon treatment of cancer cells with several natural compounds. In MCF-7 cells, the anticancer agent 3,30-Diindolylmethane, derived from Brassica vegetables, activates both JNK and p38 pathways, resulting in c-Jun and ATF-2 phosphorylation, and the increase of binding of the c-Jun–ATF-2 homodimers and heterodimers to the proximal regulatory element of IFN-γ promoter [67]. Biochanin-A, an isoflavone, existing in red clover, cabbage and alfalfa, has an inhibitory and apoptogenic effect on certain cancer cells by blocking the phosphorylation of p38 MAPK and ATF-2 in a dose-dependent fashion [68]. The JNK stress-activated pathway is one of the major intracellular signal transduction cascades involved in intestinal inflammation [69, 70], and upregulation of ATF-2 has been shown in Crohn’s disease [71, 72]. Thus CA could represent potential therapeutical properties in different states of intestinal inflammation due to its combined effects on STAT5B and ATF-2 in HT29 cells.

Finally, the modulation of cyclin D1, a target of STAT5B and ATF-2 transcription factors, upon incubation with coffee polyphenols was established in colon and breast cancer cells. Cyclin D1 overexpression is common in colorectal cancer, but the findings regarding its prognostic value are conflicting. In a recent study, positive expression of cyclin D1 protein was detected in 95 of 169 colonic adenocarcinoma specimens, and increased cyclin D1 levels were associated with poorer prognosis [73]. Furthermore, there was a significant correlation between the positive expression of p-Stat5 and cyclin D1 in patients with colonic adenocarcinoma. However, in a second study, cyclin D1 overexpression was associated with improved outcome in a total of 386 patients who underwent surgical resection for colon cancer, classified as TNM stage II or III. Belt et al. [74] showed that low p21, high p53, low cyclin D1, and high AURKA were associated with disease recurrence in stage II and III colon cancer patients. In this context the effect of ICC on cyclin D1 levels could represent either a positive or a negative effect in colon cancer cells, depending on tumor progression. The increase in cyclin D1 levels could represent a marker of better outcome since it has been recently established that cyclin D1 expression is strongly associated with prolonged survival in male colorectal cancer and that lack of cyclin D1 is associated with a more aggressive phenotype in male patients [75]. However, several natural compounds such as anthocyanins, anthocyanidins, apigenin, luteolin, and fisetin have all been described to induce experimentally cell-cycle arrest and apoptosis through the decrease of cyclin D1 levels in HT29 cells [7680]. In accordance to these data, the increase observed in cyclin D1 levels in HT29 cells upon incubation with ICC could probably be the consequence of the presence of different compounds other than polyphenols in ICC.

In MCF-7 breast cancer cells, cyclin D1 was downregulated upon incubation with coffee polyphenols. The rationale for the choice of MCF-7 cell line was based on the observation that although cyclin D1 overexpression is present across multiple histologic subtypes of breast cancer, it has been shown that the large majority of cyclin D1–overexpressing breast cancers are ER positive [24, 25, 81]. Cyclin D1 overexpression has been reported between 40 and 90% of cases of invasive breast cancer, while gene amplification is seen in about 5–20% of tumors [24, 8183]. In cyclin D1-driven cancers, blocking cyclin D1 expression by targeting the cyclin D1 gene, RNA, or protein should increase the chances for therapeutic success. Cell culture studies have raised the possibility that certain compounds might act in this way [84, 85] and approaches to blocking cyclin D1 expression using antisense, siRNA, or related molecules specifically target the driving molecular lesion itself [8688]. It is believed that compounds that modulate cyclin D1 expression could have a role in the prevention and treatment of human neoplasias. For instance, flavopiridol, a synthetic flavonoid based on an extract from an Indian plant for the potential treatment of cancer, induces a rapid decline in cyclin D1 steady-state protein levels [89]. Taking all these results together, inhibition of cyclin D1 expression appears to be a good approach for cancer treatment. In this direction our observation that coffee and caffeic acid are able to drastically reduce the expression of cyclin D1 in breast cancer cells could suggest that some coffee components could be used as a coadjuvant therapeutic tool in the treatment of breast cancer.

Abbreviations

APRT:Adenine phosphoribosyltransferase
ATF-2:Activating transcription factor
BAN:Biological association network
CA:Caffeic acid
DMSO:Dimethyl sulfoxide
DEPC:Diethyl pyrocarbonate
ICC:Instant caffeinated coffee
RT-PCR:Reverse transcription-polymerase chain reaction
STAT5B:Signal transducer and activator of transcription 5B.

Acknowledgments

This work was supported by Grants CDTI 050618, SAF2008-0043, SAF2011-23582 (Ministerio de Educación y Ciencia de España), and ISCIII-RTICc RD06/0020 (Redes Temáticas de Investigación Cooperativa en Salud) RD06/0020/0046. Our research group holds the ‘‘quality distinction’’ from the ‘‘Generalitat de Catalunya’’ SGR2009-00118. C. Oleaga was a recipient of a fellowship from the FEC (Federación Española del Café). All the authors have no conflict of interests.

References

  1. A. Scalbert, C. Manach, C. Morand, C. Rémésy, and L. Jiménez, “Dietary polyphenols and the prevention of diseases,” Critical Reviews in Food Science and Nutrition, vol. 45, no. 4, pp. 287–306, 2005. View at: Publisher Site | Google Scholar
  2. A. Scalbert, I. T. Johnson, and M. Saltmarsh, “Polyphenols: antioxidants and beyond,” The American Journal of Clinical Nutrition, vol. 81, no. 1, pp. 215S–217S, 2005. View at: Google Scholar
  3. A. Azzi, K. J. Davies, and F. Kelly, “Free radical biology—terminology and critical thinking,” FEBS Letters, vol. 558, no. 1–3, pp. 3–6, 2004. View at: Publisher Site | Google Scholar
  4. B. Halliwell, J. Rafter, and A. Jenner, “Health promotion by flavonoids, tocopherols, tocotrienols, and other phenols: direct or indirect effects? Antioxidant or not?” The American Journal of Clinical Nutrition, vol. 81, no. 1, pp. 268S–276S, 2005. View at: Google Scholar
  5. M. R. Olthof, P. C. Hollman, and M. B. Katan, “Chlorogenic acid and caffeic acid are absorbed in humans,” Journal of Nutrition, vol. 131, no. 1, pp. 66–71, 2001. View at: Google Scholar
  6. M. R. Olthof, P. C. Hollman, M. N. Buijsman, J. M. van Amelsvoort, and M. B. Katan, “Chlorogenic acid, quercetin-3-rutinoside and black tea phenols are extensively metabolized in humans,” Journal of Nutrition, vol. 133, no. 6, pp. 1806–1814, 2003. View at: Google Scholar
  7. C. A. Rice-Evans, N. J. Miller, and G. Paganga, “Structure-antioxidant activity relationships of flavonoids and phenolic acids,” Free Radical Biology and Medicine, vol. 20, no. 7, pp. 933–956, 1996. View at: Publisher Site | Google Scholar
  8. Y. Kono, H. Shibata, Y. Kodama, and Y. Sawa, “The suppression of the N-nitrosating reaction by chlorogenic acid,” The Biochemical Journal, vol. 312, part 3, pp. 947–953, 1995. View at: Google Scholar
  9. H. Shibata, Y. Sakamoto, M. Oka, and Y. Kono, “Natural antioxidant, chlorogenic acid, protects against DNA breakage caused by monochloramine,” Bioscience, Biotechnology and Biochemistry, vol. 63, no. 7, pp. 1295–1297, 1999. View at: Google Scholar
  10. H. Kasai, S. Fukada, Z. Yamaizumi, S. Sugie, and H. Mori, “Action of chlorogenic acid in vegetables and fruits as an inhibitor of 8-hydroxydeoxyguanosine formation in vitro and in a rat carcinogenesis model,” Food and Chemical Toxicology, vol. 38, no. 5, pp. 467–471, 2000. View at: Publisher Site | Google Scholar
  11. R. Feng, Y. Lu, L. L. Bowman, Y. Qian, V. Castranova, and M. Ding, “Inhibition of activator protein-1, NF-κB, and MAPKs and induction of phase 2 detoxifying enzyme activity by chlorogenic acid,” The Journal of Biological Chemistry, vol. 280, no. 30, pp. 27888–27895, 2005. View at: Publisher Site | Google Scholar
  12. S. C. Larsson and A. Wolk, “Coffee consumption and risk of liver cancer: a meta-analysis,” Gastroenterology, vol. 132, no. 5, pp. 1740–1745, 2007. View at: Publisher Site | Google Scholar
  13. F. Bravi, C. Bosetti, A. Tavani et al., “Coffee drinking and hepatocellular carcinoma risk: a meta-analysis,” Hepatology, vol. 46, no. 2, pp. 430–435, 2007. View at: Publisher Site | Google Scholar
  14. Y. Je, W. Liu, and E. Giovannucci, “Coffee consumption and risk of colorectal cancer: a systematic review and meta-analysis of prospective cohort studies,” International Journal of Cancer, vol. 124, no. 7, pp. 1662–1668, 2009. View at: Publisher Site | Google Scholar
  15. N. Tang, B. Zhou, B. Wang, and R. Yu, “Coffee consumption and risk of breast cancer: a metaanalysis,” American Journal of Obstetrics and Gynecology, vol. 200, no. 3, pp. 290.e1–290.e9, 2009. View at: Publisher Site | Google Scholar
  16. T. Naganuma, S. Kuriyama, M. Kakizaki et al., “Coffee consumption and the risk of oral, pharyngeal, and esophageal cancers in Japan: the Miyagi Cohort Study,” American Journal of Epidemiology, vol. 168, no. 12, pp. 1425–1432, 2008. View at: Publisher Site | Google Scholar
  17. K. M. Wilson, J. L. Kasperzyk, J. R. Rider et al., “Coffee consumption and prostate cancer risk and progression in the health professionals follow-up study,” Journal of the National Cancer Institute, vol. 103, no. 11, pp. 876–884, 2011. View at: Publisher Site | Google Scholar
  18. A. Nkondjock, “Coffee consumption and the risk of cancer: an overview,” Cancer Letters, vol. 277, no. 2, pp. 121–125, 2009. View at: Publisher Site | Google Scholar
  19. D. Ganmaa, W. C. Willett, T. Y. Li et al., “Coffee, tea, caffeine and risk of breast cancer: a 22-year follow-up,” International Journal of Cancer, vol. 122, no. 9, pp. 2071–2076, 2008. View at: Publisher Site | Google Scholar
  20. J. Li, P. Seibold, J. Chang-Claude et al., “Coffee consumption modifies risk of estrogen-receptor negative breast cancer,” Breast Cancer Research, vol. 13, no. 3, article R49, 2011. View at: Publisher Site | Google Scholar
  21. T. Mosmann, “Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays,” Journal of Immunological Methods, vol. 65, no. 1-2, pp. 55–63, 1983. View at: Google Scholar
  22. E. Selga, C. Oleaga, S. Ramírez, M. C. de Almagro, V. Noé, and C. J. Ciudad, “Networking of differentially expressed genes in human cancer cells resistant to methotrexate,” Genome Medicine, vol. 1, no. 9, article 83, 2009. View at: Publisher Site | Google Scholar
  23. E. Selga, C. Morales, V. Noe, and M. A. Peinado, “Role of caveolin 1, E-cadherin, Enolase 2 and PKCalpha on resistance to methotrexate in human HT29 colon cancer cells,” BMC Medical Genomics, vol. 1, article 35, 2008. View at: Google Scholar
  24. C. E. Gillett, A. H. Lee, R. R. Millis, and D. M. Barnes, “Cyclin D1 and associated proteins in mammary ductal carcinoma in situ and atypical ductal hyperplasia,” The Journal of Pathology, vol. 184, pp. 396–400, 1998. View at: Google Scholar
  25. M. F. Buckley, K. J. Sweeney, J. A. Hamilton et al., “Expression and amplification of cyclin genes in human breast cancer,” Oncogene, vol. 8, no. 8, pp. 2127–2133, 1993. View at: Google Scholar
  26. E. J. Lim, Y. H. Joung, S. M. Jung et al., “Hemin inhibits cyclin D1 and IGF-1 expression via STAT5b under hypoxia in ERα-negative MDA-MB 231 breast cancer cells,” International Journal of Oncology, vol. 36, no. 5, pp. 1243–1251, 2010. View at: Publisher Site | Google Scholar
  27. Y. H. Joung, E. J. Lim, M. S. Kim et al., “Enhancement of hypoxia-induced apoptosis of human breast cancer cells via STAT5b by momilactone B,” International Journal of Oncology, vol. 33, no. 3, pp. 477–484, 2008. View at: Publisher Site | Google Scholar
  28. E. M. Fox, T. M. Bernaciak, J. Wen, A. M. Weaver, M. A. Shupnik, and C. M. Silva, “Signal transducer and activator of transcription 5b, c-Src, and epidermal growth factor receptor signaling play integral roles in estrogen-stimulated proliferation of estrogen receptor-positive breast cancer cells,” Molecular Endocrinology, vol. 22, no. 8, pp. 1781–1796, 2008. View at: Publisher Site | Google Scholar
  29. C. A. Lange, J. K. Richer, T. Shen, and K. B. Horwitz, “Convergence of progesterone and epidermal growth factor signaling in breast cancer: potentiation of mitogen-activated protein kinase pathways,” The Journal of Biological Chemistry, vol. 273, no. 47, pp. 31308–31316, 1998. View at: Publisher Site | Google Scholar
  30. F. Beier, R. J. Lee, A. C. Taylor, R. G. Pestell, and P. Luvalle, “Identification of the cyclin D1 gene as a target of activating transcription factor 2 in chondrocytes,” Proceedings of the National Academy of Sciences of the United States of America, vol. 96, no. 4, pp. 1433–1438, 1999. View at: Publisher Site | Google Scholar
  31. M. Sabbah, D. Courilleau, J. Mester, and G. Redeuilh, “Estrogen induction of the cyclin D1 promoter: involvement of a cAMP response-like element,” Proceedings of the National Academy of Sciences of the United States of America, vol. 96, no. 20, pp. 11217–11222, 1999. View at: Publisher Site | Google Scholar
  32. J. S. Lewis, T. J. Thomas, R. G. Pestell, C. Albanese, M. A. Gallo, and T. Thomas, “Differential effects of 16α-hydroxyestrone and 2-methoxyestradiol on cyclin D1 involving the transcription factor ATF-2 in MCF-7 breast cancer cells,” Journal of Molecular Endocrinology, vol. 34, no. 1, pp. 91–105, 2005. View at: Publisher Site | Google Scholar
  33. H. Wakao, F. Gouilleux, and B. Groner, “Mammary gland factor (MGF) is a novel member of the cytokine regulated transcription factor gene family and confers the prolactin response,” EMBO Journal, vol. 13, no. 9, pp. 2182–2191, 1994. View at: Google Scholar
  34. J. Hou, U. Schindler, W. J. Henzel, S. C. Wong, and S. L. McKnight, “Identification and purification of human stat proteins activated in response to interleukin-2,” Immunity, vol. 2, no. 4, pp. 321–329, 1995. View at: Google Scholar
  35. X. Liu, G. W. Robinson, F. Gouilleux, B. Groner, and L. Hennighausen, “Cloning and expression of Stat5 and an additional homologue (Stat5b) involved in prolactin signal transduction in mouse mammary tissue,” Proceedings of the National Academy of Sciences of the United States of America, vol. 92, no. 19, pp. 8831–8835, 1995. View at: Publisher Site | Google Scholar
  36. J. X. Lin, J. Mietz, W. S. Modi, S. John, and W. J. Leonard, “Cloning of human Stat5B: reconstitution of interleukin-2-induced Stat5A and Stat5B DNA binding activity in COS-7 cells,” The Journal of Biological Chemistry, vol. 271, no. 18, pp. 10738–10744, 1996. View at: Publisher Site | Google Scholar
  37. A. L. Mui, H. Wakao, A. M. O'Farrell, N. Harade, and A. Miyajima, “Interleukin-3, granulocyte-macrophage colony stimulating factor and interleukin-5 transduce signals through two STAT5 homologs,” EMBO Journal, vol. 14, no. 6, pp. 1166–1175, 1995. View at: Google Scholar
  38. G. B. Udy, R. P. Towers, R. G. Snell et al., “Requirement of STAT5b for sexual dimorphism of body growth rates and liver gene expression,” Proceedings of the National Academy of Sciences of the United States of America, vol. 94, no. 14, pp. 7239–7244, 1997. View at: Publisher Site | Google Scholar
  39. S. Teglund, C. McKay, E. Schuetz et al., “Stat5a and Stat5b proteins have essential and nonessential, or redundant, roles in cytokine responses,” Cell, vol. 93, no. 5, pp. 841–850, 1998. View at: Publisher Site | Google Scholar
  40. K. Kanda, K. Nishi, A. Kadota, S. Nishimoto, M. C. Liu, and T. Sugahara, “Nobiletin suppresses adipocyte differentiation of 3T3-L1 cells by an insulin and IBMX mixture induction,” Biochimica et Biophysica Acta, vol. 1820, no. 4, pp. 461–468, 2011. View at: Google Scholar
  41. S. Chattopadhyay, S. Bhattacharyya, B. Saha et al., “Tumor-shed PGE2 impairs IL2Rγc-signaling to inhibit CD4+ T cell survival: regulation by theaflavins,” PLoS ONE, vol. 4, no. 10, Article ID e7382, 2009. View at: Publisher Site | Google Scholar
  42. R. P. Singh, K. Raina, G. Deep, D. Chan, and R. Agarwal, “Silibinin suppresses growth of human prostate carcinoma PC-3 orthotopic xenograft via activation of extracellular signal-regulated kinase 1/2 and inhibition of signal transducers and activators of transcription signaling,” Clinical Cancer Research, vol. 15, no. 2, pp. 613–621, 2009. View at: Publisher Site | Google Scholar
  43. M. K. Pandey, B. Sung, K. S. Ahn, and B. B. Aggarwal, “Butein suppresses constitutive and inducible signal transducer and activator of transcription (stat) 3 activation and stat3-regulated gene products through the induction of a protein tyrosine phosphatase SHP-1,” Molecular Pharmacology, vol. 75, no. 3, pp. 525–533, 2009. View at: Publisher Site | Google Scholar
  44. K. Nadeau, V. Hwa, and R. G. Rosenfeld, “STAT5b deficiency: an unsuspected cause of growth failure, immunodeficiency, and severe pulmonary disease,” Journal of Pediatrics, vol. 158, no. 5, pp. 701–708, 2011. View at: Publisher Site | Google Scholar
  45. P. A. Scaglia, A. S. Martinez, E. Feigerlova et al., “A novel missense mutation in the SH2 domain of the STAT5B gene results in a transcriptionally inactive STAT5b associated with severe IGF-I deficiency, immune dysfunction, and lack of pulmonary disease,” The Journal of Clinical Endocrinology & Metabolism, vol. 97, pp. E830–E839, 2012. View at: Google Scholar
  46. P. Rotwein, “Mapping the growth hormone—Stat5b—IGF-I transcriptional circuit,” Trends in Endocrinology & Metabolism, vol. 23, pp. 186–193, 2012. View at: Google Scholar
  47. X. Han, B. Osuntokun, N. Benight, K. Loesch, S. J. Frank, and L. A. Denson, “Signal transducer and activator of transcription 5b promotes mucosal tolerance in pediatric Crohn's disease and murine colitis,” American Journal of Pathology, vol. 169, no. 6, pp. 1999–2013, 2006. View at: Publisher Site | Google Scholar
  48. X. Han, X. Ren, I. Jurickova et al., “Regulation of intestinal barrier function by signal transducer and activator of transcription 5b,” Gut, vol. 58, no. 1, pp. 49–58, 2009. View at: Publisher Site | Google Scholar
  49. W. Du, Y. C. Wang, J. Hong et al., “STAT5 isoforms regulate colorectal cancer cell apoptosis via reduction of mitochondrial membrane potential and generation of reactive oxygen species,” Journal of Cellular Physiology, vol. 227, pp. 2421–2429, 2012. View at: Google Scholar
  50. R. Garcia, T. L. Bowman, G. Niu et al., “Constitutive activation of Stat3 by the Src and JAK tyrosine kinases participates in growth regulation of human breast carcinoma cells,” Oncogene, vol. 20, no. 20, pp. 2499–2513, 2001. View at: Publisher Site | Google Scholar
  51. R. Garcia, C. L. Yu, A. Hudnall et al., “Constitutive activation of Stat3 in fibroblasts transformed by diverse oncoproteins and in breast carcinoma cells,” Cell Growth and Differentiation, vol. 8, no. 12, pp. 1267–1276, 1997. View at: Google Scholar
  52. H. Yamashita, H. Iwase, T. Toyama, and Y. Fujii, “Naturally occurring dominant-negative Stat5 suppresses transcriptional activity of estrogen receptors and induces apoptosis in T47D breast cancer cells,” Oncogene, vol. 22, no. 11, pp. 1638–1652, 2003. View at: Publisher Site | Google Scholar
  53. S. H. Tan and M. T. Nevalainen, “Signal transducer and activator of transcription 5A/B in prostate and breast cancers,” Endocrine-Related Cancer, vol. 15, no. 2, pp. 367–390, 2008. View at: Publisher Site | Google Scholar
  54. H. Yamashita and H. Iwase, “The role of Stat5 in estrogen receptor-positive breast cancer,” Breast Cancer, vol. 9, no. 4, pp. 312–318, 2002. View at: Google Scholar
  55. J. Frasor, U. Barkai, L. Zhong, A. T. Fazleabas, and G. Gibori, “PRL-induced ERα gene expression is mediated by Janus kinase 2 (Jak2) while signal transducer and activator of transcription 5b (Stat5b) phosphorylation involves Jak2 and a second tyrosine kinase,” Molecular Endocrinology, vol. 15, no. 11, pp. 1941–1952, 2001. View at: Publisher Site | Google Scholar
  56. J. Frasor and G. Gibori, “Prolactin regulation of estrogen receptor expression,” Trends in Endocrinology & Metabolism, vol. 14, no. 3, pp. 118–123, 2003. View at: Publisher Site | Google Scholar
  57. A. R. Peck, A. K. Witkiewicz, C. Liu et al., “Loss of nuclear localized and tyrosine phosphorylated Stat5 in breast cancer predicts poor clinical outcome and increased risk of antiestrogen therapy failure,” Journal of Clinical Oncology, vol. 29, no. 18, pp. 2448–2458, 2011. View at: Publisher Site | Google Scholar
  58. C. Perotti, R. Liu, C. T. Parusel et al., “Heat shock protein-90-alpha, a prolactin-STAT5 target gene identified in breast cancer cells, is involved in apoptosis regulation,” Breast Cancer Research, vol. 10, no. 6, article R94, 2008. View at: Publisher Site | Google Scholar
  59. T. W. Hai, F. Liu, W. J. Coukos, and M. R. Green, “Transcription factor ATF cDNA clones: an extensive family of leucine zipper proteins able to selectively form DNA-binding heterodimers,” Genes and Development, vol. 3, no. 12, pp. 2083–2090, 1989. View at: Google Scholar
  60. D. M. Benbrook and N. C. Jones, “Heterodimer formation between CREB and JUN proteins,” Oncogene, vol. 5, no. 3, pp. 295–302, 1990. View at: Google Scholar
  61. A. Bhoumik and Z. Ronai, “ATF2: a transcription factor that elicits oncogenic or tumor suppressor activities,” Cell Cycle, vol. 7, no. 15, pp. 2341–2345, 2008. View at: Google Scholar
  62. J. A. Recio and G. Merlino, “Hepatocyte growth factor/scatter factor activates proliferation in melanoma cells through p38 MAPK, ATF-2 and cyclin D1,” Oncogene, vol. 21, no. 7, pp. 1000–1008, 2002. View at: Publisher Site | Google Scholar
  63. S. Takasawa, T. Ikeda, T. Akiyama et al., “Cyclin D1 activation through ATF-2 in Reg-induced pancreatic β-cell regeneration,” FEBS Letters, vol. 580, no. 2, pp. 585–591, 2006. View at: Publisher Site | Google Scholar
  64. M. Rubach, R. Lang, E. Seebach, M. M. Somoza, T. Hofmann, and V. Somoza, “Multi-parametric approach to identify coffee components that regulate mechanisms of gastric acid secretion,” Molecular Nutrition & Food Research, vol. 56, pp. 325–335, 2012. View at: Google Scholar
  65. T. Mujtaba and Q. P. Dou, “Black tea polyphenols inhibit tumor proteasome activity,” In Vivo, vol. 26, pp. 197–202, 2012. View at: Google Scholar
  66. M. Shen, T. H. Chan, and Q. P. Dou, “Targeting tumor ubiquitin-proteasome pathway with polyphenols for chemosensitization,” Anti-Cancer Agents in Medicinal Chemistry. In press. View at: Google Scholar
  67. L. Xue, G. L. Firestone, and L. F. Bjeldanes, “DIM stimulates IFNγ gene expression in human breast cancer cells via the specific activation of JNK and p38 pathways,” Oncogene, vol. 24, no. 14, pp. 2343–2353, 2005. View at: Publisher Site | Google Scholar
  68. L. Kole, B. Giri, S. K. Manna, B. Pal, and S. Ghosh, “Biochanin-A, an isoflavon, showed anti-proliferative and anti-inflammatory activities through the inhibition of iNOS expression, p38-MAPK and ATF-2 phosphorylation and blocking NFκB nuclear translocation,” European Journal of Pharmacology, vol. 653, no. 1–3, pp. 8–15, 2011. View at: Publisher Site | Google Scholar
  69. Y. T. Ip and R. J. Davis, “Signal transduction by the c-Jun N-terminal kinase (JNK)—from inflammation to development,” Current Opinion in Cell Biology, vol. 10, no. 2, pp. 205–219, 1998. View at: Publisher Site | Google Scholar
  70. B. Romier, Y. J. Schneider, Y. Larondelle, and A. During, “Dietary polyphenols can modulate the intestinal inflammatory response,” Nutrition Reviews, vol. 67, no. 7, pp. 363–378, 2009. View at: Publisher Site | Google Scholar
  71. E. Hollenbach, M. Vieth, A. Roessner, M. Neumann, P. Malfertheiner, and M. Naumann, “Inhibition of RICK/nuclear factor-κB and p38 signaling attenuates the inflammatory response in a murine model of Crohn disease,” The Journal of Biological Chemistry, vol. 280, no. 15, pp. 14981–14988, 2005. View at: Publisher Site | Google Scholar
  72. S. Derer, G. H. Waetzig, D. Seegert, S. Nikolaus, S. Schreiber, and P. Rosenstiel, “A possible link between TIMP-1 induction and response to infliximab,” Gut, vol. 58, no. 6, pp. 888–889, 2009. View at: Publisher Site | Google Scholar
  73. Y. Mao, Z. Li, C. Lou, and Y. Zhang, “Expression of phosphorylated Stat5 predicts expression of cyclin D1 and correlates with poor prognosis of colonic adenocarcinoma,” International Journal of Colorectal Disease, vol. 26, no. 1, pp. 29–35, 2011. View at: Publisher Site | Google Scholar
  74. E. J. Belt, R. P. Brosens, P. M. Delis-van Diemen et al., “Cell cycle proteins predict recurrence in stage II and III colon cancer,” Annals of Surgical Oncology. In press. View at: Google Scholar
  75. S. Wangefjord, J. Manjer, A. Gaber, B. Nodin, J. Eberhard, and K. Jirstrom, “Cyclin D1 expression in colorectal cancer is a favorable prognostic factor in men but not in women in a prospective, population-based cohort study,” Biology of Sex Differences, vol. 2, article 10, 2011. View at: Google Scholar
  76. C. P. Hsu, Y. T. Shih, B. R. Lin, C. F. Chiu, and C. C. Lin, “Inhibitory effect and mechanisms of an anthocyanins- and anthocyanidins-rich extract from purple-shoot tea on colorectal carcinoma cell proliferation,” Journal of Agricultural and Food Chemistry, vol. 60, pp. 3686–3692, 2012. View at: Google Scholar
  77. M. Turktekin, E. Konac, H. I. Onen, E. Alp, A. Yilmaz, and S. Menevse, “Evaluation of the effects of the flavonoid apigenin on apoptotic pathway gene expression on the colon cancer cell line (HT29),” Journal of Medicinal Food, vol. 14, pp. 1107–1117, 2011. View at: Google Scholar
  78. D. Y. Lim, Y. Jeong, A. L. Tyner, and J. H. Park, “Induction of cell cycle arrest and apoptosis in HT-29 human colon cancer cells by the dietary compound luteolin,” American Journal of Physiology, vol. 292, no. 1, pp. G66–G75, 2007. View at: Publisher Site | Google Scholar
  79. G. Seelinger, I. Merfort, U. Wölfle, and C. M. Schempp, “Anti-carcinogenic effects of the flavonoid luteolin,” Molecules, vol. 13, no. 10, pp. 2628–2651, 2008. View at: Publisher Site | Google Scholar
  80. Y. Suh, F. Afaq, J. J. Johnson, and H. Mukhtar, “A plant flavonoid fisetin induces apoptosis in colon cancer cells by inhibition of COX2 and Wnt/EGFR/NF-κB-signaling pathways,” Carcinogenesis, vol. 30, no. 2, pp. 300–307, 2009. View at: Publisher Site | Google Scholar
  81. L. R. Zukerberg, W. I. Yang, M. Gadd et al., “Cyclin D1 (PRAD1) protein expression in breast cancer: approximately one-third of infiltrating mammary carcinomas show overexpression of the cyclin D1 oncogene,” Modern Pathology, vol. 8, no. 5, pp. 560–567, 1995. View at: Google Scholar
  82. D. Weinstat-Saslow, M. J. Merino, R. E. Manrow et al., “Overexpression of cyclin D mRNA distinguishes invasive and in situ breast carcinomas from non-malignant lesions,” Nature Medicine, vol. 1, no. 12, pp. 1257–1260, 1995. View at: Google Scholar
  83. J. F. Simpson, D. E. Quan, F. O'Malley, T. Odom-Maryon, and P. E. Clarke, “Amplification of CCND1 and expression of its protein product, cyclin D1, in ductal carcinoma in situ of the breast,” American Journal of Pathology, vol. 151, no. 1, pp. 161–168, 1997. View at: Google Scholar
  84. C. H. Hsiang and D. S. Straus, “Cyclopentenone causes cell cycle arrest and represses cyclin D1 promoter activity in MCF-7 breast cancer cells,” Oncogene, vol. 21, no. 14, pp. 2212–2226, 2002. View at: Publisher Site | Google Scholar
  85. S. Sawatsri, D. Samid, S. Malkapuram, and N. Sidell, “Inhibition of estrogen-dependent breast cell responses with phenylacetate,” International Journal of Cancer, vol. 93, no. 5, pp. 687–692, 2001. View at: Publisher Site | Google Scholar
  86. E. R. Sauter, M. Nesbit, S. Litwin, A. J. Klein-Szanto, S. Cheffetz, and M. Herlyn, “Antisense cyclin D1 induces apoptosis and tumor shrinkage in human squamous carcinomas,” Cancer Research, vol. 59, no. 19, pp. 4876–4881, 1999. View at: Google Scholar
  87. N. Arber, Y. Doki, E. K. Han et al., “Antisense to cyclin D1 inhibits the growth and tumorigenicity of human colon cancer cells,” Cancer Research, vol. 57, no. 8, pp. 1569–1574, 1997. View at: Google Scholar
  88. M. Kornmann, N. Arber, and M. Korc, “Inhibition of basal and mitogen-stimulated pancreatic cancer cell growth by cyclin D1 antisense is associated with loss of tumorigenicity and potentiation of cytotoxicity to cisplatinum,” The Journal of Clinical Investigation, vol. 101, no. 2, pp. 344–352, 1998. View at: Google Scholar
  89. B. Carlson, T. Lahusen, S. Singh et al., “Down-regulation of cyclin D1 by transcriptional repression in MCF-7 human breast carcinoma cells induced by flavopiridol,” Cancer Research, vol. 59, no. 18, pp. 4634–4641, 1999. View at: Google Scholar

Copyright © 2012 Carlota Oleaga et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

2056 Views | 1005 Downloads | 9 Citations
 PDF  Download Citation  Citation
 Download other formatsMore
 Order printed copiesOrder