Oxidative Medicine and Cellular Longevity

Volume 2012 (2012), Article ID 390385, 17 pages

doi:10.1155/2012/390385

Research Article

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

Carlota Oleaga,¹ Carlos J. Ciudad,¹ Véronique Noé,¹ and Maria Izquierdo-Pulido²

¹Department of Biochemistry and Molecular Biology, School of Pharmacy, University of Barcelona, 08028 Barcelona, Spain

²Department of Nutrition and Food Science, School of Pharmacy, University of Barcelona, 08028 Barcelona, Spain

Received 10 February 2012; Revised 16 May 2012; Accepted 18 May 2012

Academic Editor: Luciano Pirola

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.

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 [12–15]. 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.

Table 1

Antibody
Molecular weight (KDa)
Dilution used
Supplier

STAT5B
95
1: 200
sc-835, Santa Cruz Biotechnology Inc.

ATF-2
72
1: 200
sc-6233, Santa Cruz Biotechnology Inc.

Cyclin D1
38
1: 200
sc-8396, Santa Cruz Biotechnology Inc.

-actin
42
1: 200
A2066, Sigma

Tubulin
60
1: 100
CP06, 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].

Table 2: List of overexpressed genes in HT29 cells upon incubation with instant caffeinated coffee.

Gene symbol
Gene title
value
FC absolute
Regulation

CALM3
Calmodulin 3 (phosphorylase kinase, delta)
0.016
1.3
Up

CDC42EP1
CDC42 effector protein (Rho GTPase binding) 1
0.027
1.3
Up

FOXN3
Forkhead box N3
0.022
1.3
Up

KIR2DL1
Killer cell immunoglobulin-like receptor, two domains, long cytoplasmic tail, 1
0.023
1.3
Up

ORAI2
ORAI calcium release-activated calcium modulator 2
0.011
1.3
Up

RAPGEF1
Rap guanine nucleotide exchange factor (GEF) 1
0.022
1.3
Up

STH
Saitohin
0.031
1.3
Up

SLC39A3
Solute carrier family 39 (zinc transporter), member 3
0.028
1.3
Up

ZNF397OS
Zinc finger protein 397 opposite strand
0.024
1.3
Up

ZP4
Zona pellucida glycoprotein 4
0.046
1.3
Up

FGFRL1
Fibroblast growth factor receptor-like 1
0.035
1.31
Up

ITGA9
Integrin, alpha 9
0.002
1.31
Up

IRAK1
Interleukin-1 receptor-associated kinase 1
0.038
1.31
Up

OBSL1
Obscurin-like 1
0.008
1.31
Up

RPS17L4
Ribosomal protein S17-like 4
0.026
1.31
Up

STAT5B
Signal transducer and activator of transcription 5B
0.007
1.31
Up

TRABD
TraB domain containing
0.043
1.31
Up

MYO9B
Myosin IXB
0.041
1.32
Up

NME7
Nonmetastatic cells 7, protein expressed in (nucleoside-diphosphate kinase)
0.037
1.32
Up

RPS6KA4
Ribosomal protein S6 kinase, 90 kDa, polypeptide 4
0.014
1.32
Up

SIRPA
Signal-regulatory protein alpha
0.019
1.32
Up

TBX20
T-box 20
0.035
1.32
Up

TCF20
Transcription factor 20 (AR1)
0.022
1.32
Up

ALDH3B1
Aldehyde dehydrogenase 3 family, member B1
0.005
1.33
Up

BGN
Biglycan
0.029
1.33
Up

GNB4
Guanine nucleotide binding-protein (G protein), b-polypeptide 4
0.044
1.33
Up

IFNA17
Interferon, alpha 17
0.026
1.33
Up

KY
Kyphoscoliosis peptidase
0.013
1.33
Up

SCARF1
Scavenger receptor class F, member 1
0.025
1.33
Up

SERPINB8
Serpin peptidase inhibitor, clade B (ovalbumin), member 8
0.01
1.33
Up

FST
Follistatin
0.025
1.34
Up

MOGAT1
Monoacylglycerol O-acyltransferase 1
0.009
1.34
Up

PPARGC1A
Peroxisome proliferator-activated receptor gamma, coactivator 1 alpha
0.015
1.34
Up

SUCLG2
Succinate-CoA ligase, GDP-forming, beta subunit
0.011
1.34
Up

SULT1B1
Sulfotransferase family, cytosolic, 1B, member 1
0.018
1.34
Up

TBX10
T-box 10
0.011
1.34
Up

ZNF503
Zinc finger protein 503
0.022
1.34
Up

HBA1
Hemoglobin, alpha 1
0.04
1.35
Up

MEPE
Matrix, extracellular phosphoglycoprotein with ASARM motif
0.001
1.35
Up

PPP1CB
Protein phosphatase 1, catalytic subunit, beta isoform
0.03
1.35
Up

ARV1
ARV1 homolog (S. cerevisiae)
0.011
1.36
Up

BCL3
B-cell CLL/lymphoma 3
0.034
1.36
Up

CTRC
Chymotrypsin C (caldecrin)
0.045
1.36
Up

EPOR
Erythropoietin receptor
0.008
1.37
Up

HMGA1
High-mobility group AT-hook 1
0.039
1.37
Up

IL19
Interleukin 19
0.018
1.38
Up

ABCC12
ATP-binding cassette, subfamily C (CFTR/MRP), member 12
6.00E-04
1.39
Up

RAI1
Retinoic acid induced 1
0.017
1.39
Up

KLF5
Kruppel-like factor 5 (intestinal)
0.028
1.4
Up

CBWD1
COBW domain containing 1
0.044
1.41
Up

ASAH3
N-acylsphingosine amidohydrolase (alkaline ceramidase) 3
0.039
1.43
Up

ABHD14B
Abhydrolase domain containing 14B
0.03
1.45
Up

TLN1
Talin 1
0.049
1.45
Up

ARHGAP23
Rho GTPase-activating protein 23
0.024
1.65
Up

HINT3
Histidine triad nucleotide binding protein 3
0.002
1.77
Up

ARHGDIA
Rho GDP dissociation inhibitor (GDI) alpha
0.034
1.83
Up

CALR
Calreticulin
0.007
1.93
Up

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).

Table 3: List of underexpressed genes in HT29 cells upon incubation with instant coffee.

Gene symbol
Gene title
value
FC absolute
Regulation

ACBD5
Acyl-coenzyme A binding domain containing 5
0.017
1.3
Down

CXADR
Coxsackie virus and adenovirus receptor
0.015
1.3
Down

FANCD2
Fanconi anemia, complementation group D2
0.047
1.3
Down

FRYL
FRY-like
0.039
1.3
Down

NUB1
Negative regulator of ubiquitin-like proteins 1
0.029
1.3
Down

PBRM1
Polybromo 1
0.004
1.3
Down

PRKACB
Protein kinase, cAMP-dependent, catalytic, beta
0.033
1.3
Down

RIF1
RAP1 interacting factor homolog (yeast)
0.012
1.3
Down

SLC39A6
Solute carrier family 39 (zinc transporter), member 6
0.022
1.3
Down

TMEM170
Transmembrane protein 170
0.032
1.3
Down

WDR26
WD repeat domain 26
0.028
1.3
Down

RNGTT
RNA guanylyltransferase and 5′-phosphatase
0.04
1.3
Down

CTDSPL2
CTD small phosphatase like 2
0.03
1.3
Down

ZC3H11A
Zinc finger CCCH-type containing 11A
0.014
1.3
Down

TMOD3
Tropomodulin 3 (ubiquitous)
0.0171
1.3
Down

CPD
Carboxypeptidase D
0.002
1.31
Down

CBL
Cas-Br-M ecotropic retroviral transforming sequence
0.008
1.31
Down

CDC42SE2
CDC42 small effector 2
0.022
1.31
Down

CLN5
Ceroid-lipofuscinosis, neuronal 5
0.001
1.31
Down

DDX3X
DEAD (Asp-Glu-Ala-Asp) box polypeptide 3, X-linked
0.027
1.31
Down

FGFR1OP2
FGFR1 oncogene partner 2
0.049
1.31
Down

LRRFIP1
Leucine-rich repeat (in FLII) interacting protein 1
0.026
1.31
Down

PDCD4
Programmed cell death 4
0.005
1.31
Down

REPS2
RALBP1-associated Eps domain containing 2
0.046
1.31
Down

SLC7A6
Solute carrier family 7, member 6
0.002
1.31
Down

TFRC
Transferrin receptor (p90, CD71)
0.038
1.31
Down

TMEM19
Transmembrane protein 19
0.024
1.31
Down

AGPS
Alkylglycerone phosphate synthase
0.001
1.31
Down

SLC4A7
Solute carrier family 4, member 7
0.028
1.31
Down

SPTAN1
Spectrin, alpha, nonerythrocytic 1 (alpha-fodrin)
0.02
1.31
Down

GPD2
Glycerol-3-phosphate dehydrogenase 2 (mitochondrial)
0.033
1.31
Down

BICD1
Bicaudal D homolog 1 (Drosophila)
0.008
1.31
Down

FBXW11
F-box and WD repeat domain containing 11
0.025
1.31
Down

BCLAF1
BCL2-associated transcription factor 1
0.025
1.32
Down

CDH1
Cadherin 1, type 1, E-cadherin (epithelial)
0.011
1.32
Down

CLK4
CDC-like kinase 4
0.049
1.32
Down

PTAR1
Protein prenyltransferase alpha subunit repeat containing 1
0.027
1.32
Down

SMEK2
SMEK homolog 2, suppressor of mek1 (Dictyostelium)
0.012
1.32
Down

CEPT1
Choline/ethanolamine phosphotransferase 1
0.038
1.32
Down

SAR1A
SAR1 gene homolog A (S. cerevisiae)
0.033
1.32
Down

PDGFC
Platelet-derived growth factor C
0.02
1.32
Down

NFAT5
Nuclear factor of activated T-cells 5, tonicity responsive
0.045
1.32
Down

FRS2
Fibroblast growth factor receptor substrate 2
0.03
1.32
Down

BMS1P5
BMS1 pseudogene 5
0.036
1.33
Down

GLS
Glutaminase
5.00E-04
1.33
Down

LMAN1
Lectin, mannose binding, 1
7.00E-04
1.33
Down

ARHGAP18
Rho GTPase-activating protein 18
8.00E-04
1.33
Down

ARHGAP5
Rho GTPase-activating protein 5
0.006
1.33
Down

CCNE2
Cyclin E2
0.036
1.33
Down

SPCS3
Signal peptidase complex subunit 3 homolog (S. cerevisiae)
0.008
1.33
Down

NCOA2
Nuclear receptor coactivator 2
0.005
1.33
Down

SRPRB
Signal recognition particle receptor, B subunit
0.018
1.33
Down

TLK1
Tousled-like kinase 1
0.04
1.33
Down

NCOA3
Nuclear receptor coactivator 3
0.048
1.33
Down

STRN3
Striatin, calmodulin-binding protein 3
2.00E-04
1.33
Down

AP1G1
Adaptor-related protein complex 1, gamma 1 subunit
0.004
1.34
Down

B3GALNT2
Beta-1,3-N-acetylgalactosaminyltransferase 2
0.034
1.34
Down

PPHLN1
Periphilin 1
2.00E-04
1.34
Down

SNX13
Sorting nexin 13
0.001
1.34
Down

TMED2
Transmembrane emp24 domain-trafficking protein 2
0.041
1.34
Down

BRWD1
Bromodomain and WD repeat domain containing 1
0.011
1.34
Down

HLA-B
Major histocompatibility complex, class I, B
0.028
1.34
Down

CHP
Calcium-binding protein P22
0.002
1.34
Down

MTMR9
Myotubularin-related protein 9
0.026
1.34
Down

DCUN1D4
DCN1, defective in cullin neddylation 1, domain containing 4
0.031
1.34
Down

ARL6IP2
ADP-ribosylation factor-like 6 interacting protein 2
0.02
1.35
Down

GLIS3
GLIS family zinc finger 3
0.01
1.35
Down

LARP4
La ribonucleoprotein domain family, member 4
0.019
1.35
Down

PTPLB
Protein tyrosine phosphatase-like member b
0.036
1.35
Down

TRAM1
Translocation-associated membrane protein 1
0.002
1.35
Down

TMEM64
Transmembrane protein 64
0.001
1.35
Down

CBFB
Core-binding factor, beta subunit
0.005
1.35
Down

SELT
Selenoprotein T
0.002
1.35
Down

PEX13
Peroxisome biogenesis factor 13
0.011
1.35
Down

TNKS2
TRF1-interacting ankyrin-related ADP-ribose polymerase 2
0.034
1.35
Down

TMPO
Thymopoietin
0.001
1.35
Down

LIN7C
Lin-7 homolog C (C. elegans)
0.007
1.35
Down

MTA2
Metastasis-associated 1 family, member 2
0.013
1.36
Down

TMEM168
Transmembrane protein 168
0.035
1.36
Down

CREBZF
CREB/ATF bZIP transcription factor
0.016
1.36
Down

OSTF1
Osteoclast-stimulating factor 1
0.002
1.36
Down

WDR57
WD repeat domain 57 (U5 snRNP specific)
0.001
1.36
Down

GLT25D1
Glycosyltransferase 25 domain containing 1
0.008
1.36
Down

NAPG
N-ethylmaleimide-sensitive factor attachment protein, gamma
0.015
1.36
Down

CCDC126
Coiled-coil domain containing 126
0.039
1.37
Down

LASS6
LAG1 homolog, ceramide synthase 6
0.005
1.37
Down

MYSM1
Myb-like, SWIRM and MPN domains 1
0.021
1.37
Down

CYP51A1
Cytochrome P450, family 51, subfamily A, polypeptide 1
0.007
1.37
Down

PDE4DIP
Phosphodiesterase 4D interacting protein (myomegalin)
0.024
1.37
Down

SAP30L
SAP30-like
0.012
1.37
Down

PTPRJ
Protein tyrosine phosphatase, receptor type, J
0.011
1.37
Down

PGGT1B
Protein geranylgeranyltransferase type I, beta subunit
9.00E-04
1.37
Down

ASPH
Aspartate beta-hydroxylase
0.011
1.37
Down

SEMA3C
Sema domain, (semaphorin) 3C
0.036
1.38
Down

WDR76
WD repeat domain 76
0.016
1.38
Down

ATP13A3
ATPase-type 13A3
0.002
1.38
Down

LMBR1
Limb region 1 homolog (mouse)
0.014
1.38
Down

GLUD1
Glutamate dehydrogenase 1
0.001
1.39
Down

GSTCD
Glutathione S-transferase, C-terminal domain containing
0.029
1.39
Down

SPTLC1
Serine palmitoyltransferase, subunit 1
0.02
1.39
Down

U2AF1
U2 small nuclear RNA auxiliary factor 1
9.00E-04
1.39
Down

UHMK1
U2AF homology motif (UHM) kinase 1
0.007
1.39
Down

ARGLU1
Arginine and glutamate-rich 1
6.00E-04
1.39
Down

ANKRD12
Ankyrin repeat domain 12
0.03
1.39
Down

PPP3R1
Protein phosphatase 3, regulatory subunit B, alpha isoform
0.023
1.39
Down

XRN1
5′-3′ exoribonuclease 1
0.019
1.4
Down

CLSPN
Claspin homolog (Xenopus laevis)
0.013
1.4
Down

CXADRP1
Coxsackie virus and adenovirus receptor pseudogene 1
0.034
1.4
Down

G3BP1
GTPase-activating protein- (SH3 domain) binding protein 1
0.002
1.4
Down

TMEM30A
Transmembrane protein 30A
0.01
1.4
Down

CLCN3
Chloride channel 3
0.035
1.41
Down

STK4
Serine/threonine kinase 4
0.039
1.41
Down

ZNF644
Zinc finger protein 644
0.02
1.41
Down

TCP11L1
T-complex 11 (mouse)-like 1
0.014
1.41
Down

SFRS6
Splicing factor, arginine/serine-rich 6
0.031
1.41
Down

NPL
N-acetylneuraminate pyruvate lyase
0.006
1.41
Down

G3BP2
GTPase-activating protein- (SH3 domain) binding protein 2
0.001
1.42
Down

HNRNPU
Heterogeneous nuclear ribonucleoprotein U
0.01
1.42
Down

TBL1XR1
Transducin (beta)-like 1 X-linked receptor 1
0.001
1.42
Down

PHTF2
Putative homeodomain transcription factor 2
0.002
1.42
Down

ADAM10
ADAM metallopeptidase domain 10
0.011
1.43
Down

ADAM9
ADAM metallopeptidase domain 9 (meltrin gamma)
0.01
1.43
Down

MALAT1
Metastasis-associated lung adenocarcinoma transcript 1
0.04
1.43
Down

SCARB2
Scavenger receptor class B, member 2
0.001
1.43
Down

CANX
Calnexin
0.043
1.43
Down

CASP2
Caspase 2, apoptosis-related cysteine peptidase
0.033
1.43
Down

TRPS1
Trichorhinophalangeal syndrome I
0.005
1.44
Down

ZFX
Zinc finger protein, X-linked
0.033
1.44
Down

SGPL1
Sphingosine-1-phosphate lyase 1
0.04
1.44
Down

PTPN11
Protein tyrosine phosphatase, nonreceptor type 11
0.045
1.44
Down

SFRS11
Splicing factor, arginine/serine-rich 11
0.045
1.45
Down

B3GNT5
Beta-1,3-N-acetylglucosaminyltransferase 5
0.021
1.45
Down

MAP3K1
Mitogen-activated protein kinase kinase kinase 1
0.019
1.45
Down

SNHG4
Small nucleolar RNA host gene (nonprotein coding) 4
0.004
1.46
Down

PARD6B
Par-6 partitioning defective 6 homolog beta (C. elegans)
0.04
1.46
Down

ROD1
ROD1 regulator of differentiation 1 (S. pombe)
0.001
1.46
Down

SPTBN1
Spectrin, beta, nonerythrocytic 1
0.02
1.48
Down

TXNDC1
Thioredoxin domain containing 1
0.013
1.48
Down

ATF2
Activating transcription factor 2
0.005
1.48
Down

RDX
Radixin
0.043
1.48
Down

SCAMP1
Secretory carrier membrane protein 1
0.009
1.48
Down

PTAR1
Protein prenyltransferase alpha subunit repeat containing 1
0.018
1.49
Down

RC3H2
Ring finger and CCCH-type zinc finger domains 2
0.0037
1.49
Down

ADAM17
ADAM metallopeptidase domain 17
0.007
1.49
Down

FAM76B
Family with sequence similarity 76, member B
0.014
1.5
Down

ITGB8
Integrin, beta 8
1.00E-04
1.5
Down

TRIM23
Tripartite motif-containing 23
0.005
1.5
Down

CASC5
Cancer susceptibility candidate 5
0.019
1.52
Down

SLC16A1
Solute carrier family 16, member 1
0.002
1.52
Down

FNBP1
Formin-binding protein 1
0.037
1.53
Down

PRKAR1A
Protein kinase, cAMP-dependent, regulatory, type I, alpha
9.00E-04
1.53
Down

B4GALT1
Beta 1,4-galactosyltransferase, polypeptide 1
0.035
1.55
Down

MDM4
Mdm4 p53-binding protein homolog (mouse)
0.011
1.58
Down

FGD4
FYVE, RhoGEF, and PH domain containing 4
0.001
1.59
Down

UBA6
Ubiquitin-like modifier activating enzyme 6
8.00E-04
1.62
Down

ZDHHC21
Zinc finger, DHHC-type containing 21
0.036
1.64
Down

REEP3
Receptor accessory protein 3
7.00E-04
1.65
Down

SSR3
Signal sequence receptor, gamma
0.014
1.65
Down

ZDHHC20
Zinc finger, DHHC-type containing 20
0.003
1.66
Down

EIF2S3
Eukaryotic translation initiation factor 2, subunit 3 gamma
0.001
1.7
Down

HNRNPH1
Heterogeneous nuclear ribonucleoprotein H1
0.011
1.79
Down

ATL3
Atlastin 3
0.001
2.02
Down

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).

Table 4: List of overexpressed genes in HT29 cells upon incubation with caffeic acid.

Gene symbol
Gene title
value
FC absolute
Regulation

SULT1B1
Sulfotransferase family, cytosolic, 1B, member 1
0.02
1.3
Up

BCL6B
B-cell CLL/lymphoma 6, member B (zinc finger protein)
3.00E-04
1.3
Up

KCNJ5
Potassium inwardly-rectifying channel, subfamily J, member 5
0.01
1.31
Up

EPOR
Erythropoietin receptor
0.02
1.32
Up

DNAJC21
DnaJ (Hsp40) homolog, subfamily C, member 21
0.049
1.33
Up

STAT5B
Signal transducer and activator of transcription 5B
0.012
1.33
Up

FST
Follistatin
0.021
1.37
Up

CD84
CD84 molecule
0.033
1.37
Up

THRA
Thyroid hormone receptor, alpha
0.017
1.37
Up

MAPK8IP3
Mitogen-activated protein kinase 8 interacting protein 3
0.028
1.4
Up

SIAE
Sialic acid acetylesterase
0.01
2.42
Up

HINT3
Histidine triad nucleotide-binding protein 3
0.033
2.6
Up

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).

Table 5: List of underexpressed genes in HT29 cells upon incubation with caffeic acid.

Gene symbol
Gene title
value
FC absolute
Regulation

MFSD7
Major facilitator superfamily domain containing 7
1.00E-04
1.3
Down

MSI2
Musashi homolog 2 (Drosophila)
0.027
1.3
Down

CDA
Cytidine deaminase
2.00E-04
1.31
Down

DEFB1
Defensin, beta 1
0.026
1.31
Down

PIP5K1A
Phosphatidylinositol-4-phosphate 5-kinase, type I, alpha
0.027
1.31
Down

ZDHHC20
Zinc finger, DHHC-type containing 20
0.005
1.31
Down

ZDHHC21
Zinc finger, DHHC-type containing 21
0.016
1.31
Down

SLC4A7
Solute carrier family 4, member 7
0.0249
1.32
Down

CEACAM1
Carcinoembryonic antigen-related cell adhesion molecule 1
0.0459
1.32
Down

PDZRN3
PDZ domain containing RING finger 3
0.002
1.32
Down

WDR62
WD repeat domain 62
0.005
1.32
Down

FAM76B
Family with sequence similarity 76, member B
0.036
1.32
Down

TCF21
Transcription factor 21
0.029
1.33
Down

TBL1XR1
Transducin (beta)-like 1 X-linked receptor 1
6.00E-04
1.33
Down

CLK4
CDC-like kinase 4
0.021
1.33
Down

CYP2A13
Cytochrome P450, family 2, subfamily A, polypeptide 13
0.009
1.34
Down

CXCR4
Chemokine (C-X-C motif) receptor 4
0.0488
1.34
Down

ATF2
Activating transcription factor 2
0.0158
1.35
Down

PDE10A
Phosphodiesterase 10A
0.03
1.35
Down

METT10D
Methyltransferase 10 domain containing
0.003
1.35
Down

PRMT2
Protein arginine methyltransferase 2
7.00E-04
1.36
Down

GLS
Glutaminase
5.70E-04
1.37
Down

SLC38A5
Solute carrier family 38, member 5
0.043
1.37
Down

TINAG
Tubulointerstitial nephritis antigen
0.043
1.38
Down

AQP1
Aquaporin 1 (Colton blood group)
0.0221
1.4
Down

JMJD6
Jumonji domain containing 6
0.004
1.4
Down

SAP30L
SAP30-like
0.021
1.4
Down

FGD4
FYVE, RhoGEF, and PH domain containing 4
0.026
1.52
Down

S100A2
S100 calcium-binding protein A2
0.005
1.53
Down

CTSZ
Cathepsin Z
0.045
1.53
Down

SLC4A4
Solute carrier family 4, member 4
9.00E-04
1.54
Down

AGR3
Anterior gradient homolog 3 (Xenopus laevis)
0.011
1.69
Down

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).

Table 6: Common differentially expressed genes in HT29 treated-cells.

Gene symbol
FC absolute ICC
value
Regulation
FC absolute CA
value
Regulation

FST
1.343
0.025
Up
1.375
0.022
Up

SULT1B1
1.349
0.018
Up
1.304
0.020
Up

EPOR
1.372
0.008
Up
1.321
0.021
Up

HINT3
2.410
0.040
Up
2.607
0.033
Up

STAT5B
1.312
0.007
Up
1.334
0.012
Up

GLS
1.335
0.001
Down
1.370
0.001
Down

PPP3R1
1.397
0.023
Down
1.423
0.026
Down

ATF2
1.481
0.005
Down
1.354
0.016
Down

SLC4A7
1.314
0.029
Down
1.322
0.025
Down

MARCH3
1.330
0.016
Down
1.319
0.005
Down

TBL1XR1
1.426
0.001
Down
1.332
0.001
Down

SAP30L
1.375
0.013
Down
1.405
0.021
Down

FGD4
1.593
0.001
Down
1.523
0.027
Down

ZDHHC20
1.665
0.004
Down
1.314
0.005
Down

ZDHHC21
1.642
0.037
Down
1.318
0.016
Down

FAM76B
1.506
0.014
Down
1.325
0.037
Down

CLK4
1.326
0.049
Down
1.339
0.021
Down

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.

Figure 1: Biological association network (BAN) of differentially expressed genes in common between CA and ICC. The list of common genes between both treatments was used to construct a BAN with the Pathway Analysis software within GeneSpring v.11.5.1. An expanded network was constructed by setting an advanced filter that included the categories of binding, expression, metabolism, promoter binding, protein modification, and regulation. Only proteins are represented. The BAN shows the node genes STAT5B and ATF-2 that were further studied.

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)).

(a)

(b)

(c)

(d)

Figure 2: Quantitation of mRNA and protein levels for STAT5B and ATF-2 in HT29 cells. The mRNA levels of STAT5B (a) and ATF-2 (b) were determined in control HT29 cells (empty bars) and cells treated with caffeic acid (CA, filled bars) and instant caffeinated coffee (ICC, grey bars) by RT real-time PCR as described in Methods. Results are expressed in fold changes compared to the control and are the mean ± SE of 3 different experiments. compared with the corresponding control. The protein levels of STAT5B (c) and ATF-2 (d) were determined in control HT29 cells (empty bars) and cells treated with caffeic acid (CA, filled bars) and instant caffeinated coffee (ICC, grey bars) by Western blot. Blots were reprobed with an antibody against β-actin or tubulin to normalize the results. Results represent the mean ± SE of 3 different experiments. and compared with the corresponding control.

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 [26–29] and ATF-2 [30–32].

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).

(a)

(b)

Figure 3: Expression of cyclin D1 upon incubation with ICC and CA in HT29 and MCF-7 cells. (a) Quantitation of STAT5b (empty bars), ATF-2 (filled bars), and cyclin D1 (grey bars) protein levels in MCF-7 cells. The protein levels were determined in control MCF-7 cells (CNT) and cells treated with caffeic acid (CA) and instant coffee (ICC) by Western blot. Blots were reprobed with an antibody against β-actin to normalize the results. Results represent the mean ± SE of 3 different experiments. and compared with the corresponding control. (b) Quantitation of STAT5b (empty bars), ATF-2 (filled bars), and cyclin D1 (grey bars) protein levels in HT29 cells. The protein levels were determined in control HT29 cells (CNT) and cells treated with caffeic acid (CA) and instant coffee (ICC) by Western blot. Blots were reprobed with an antibody against β-actin to normalize the results. Results represent the mean ± SE of 3 different experiments. and compared with the corresponding control.

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 [34–37].

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 [44–46]. 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 [50–52] 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 [54–56]. 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 [76–80]. 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, 81–83]. 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 [86–88]. 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.

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