1 Department of Health Risk Analysis and Toxicology, Maastricht University, Maastricht, The Netherlands and 2 Department of Gastroenterology, Maasland Hospital Sittard, Sittard, The Netherlands
3 To whom correspondence should be addressed Email: j.vandelft{at}grat.unimaas.nl
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Abstract |
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Abbreviations: AFP, alpha-fetoprotein; AMACR, methyl-CoA racemase alpha; APC, adenomatous polyposis coli; ATF3, activating transcription factor 3; CCNA2, cyclin A2; CCNG1, cyclin G1; CDK, cyclin-dependent protein kinases; C-FOS, fos proto-oncogene; CHK1, checkpoint kinase-1; COX-2, cyclooxygenase-2; CRC, colorectal cancer; CYP2C9, cytochrome P450 2C9; CYP2C19, cytochrome P450 2C19; CYP2D6, cytochrome P450 2D6; CYP3A4, cytochrome P450 3A4; CYP27B1, cytochrome P450 27B1; MDM2, human mdm2-A; ODC1, ornithine decarboxylase 1; PKCB1, protein kinase C beta 1; PRDX1, peroxiredoxin 1; PTGS2, prostaglandin-endoperoxide synthase 2
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Introduction |
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The predominantly modifiable determinant of CRC is the diet. The most consistent finding is the association of vegetables with reduced risk of CRC (14). Numerous potentially anticarcinogenic agents are present in vegetables that have various potential mechanisms of action in the initiation and later stages of carcinogenesis. Compounds classified as blocking agents can prevent, or greatly reduce, initiation of carcinogenesis by altering the profile of both phase I and II drug metabolizing enzymes, by scavenging reactive oxygen and other free radical species and by altering rates of DNA repair. Suppressing agents affect later stages of carcinogenesis by reducing cell proliferation. This involves modulation of signal transduction pathways, leading to altered gene expression, cell cycle arrest or apoptosis and thereby preventing the accumulation of damaged cells (2,57).
A genetic model for CRC has been presented by Fearon and Vogelstein (8), which has been subsequently extended with additional genetic events and specific molecular pathways (9) presenting a network of molecular genetic pathways (810). These genetic pathways and the involved genes are obvious molecular targets for the protection against CRC by vegetables. Nowadays available microarray technology makes it feasible to assess the effect of a specific diet on the expression of multiple genes simultaneously (11).
The aim of this study was to identify genes that are modulated in vivo in colorectal mucosa by vegetables, and to investigate whether colon adenoma patients respond differently in comparison with healthy controls. Therefore, a human dietary intervention study was carried out in which the effect of an increased or decreased intake of vegetables on gene expression was investigated in biopsies from normal colorectal mucosa of female sporadic adenoma patients and healthy controls by applying microarray technology. A descriptive evaluation was made of the gene expression results with respect to their possible role in mechanisms underlying CRC risk.
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Materials and methods |
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Both patients and controls were randomly split into two groups of ten and four persons, respectively, receiving either a low (75 g/day) or high (300 g/day) vegetable diet for a period of 2 weeks. The length of this intervention period was chosen based on results of other studies, in which the effect of a vegetable intervention on gene expression changes was examined in various tissues including lymphocytes and colorectal mucosa. In these studies, the length of intervention was equal to or even shorter than 2 weeks and still a modulation of gene expression (mostly biotransformation genes) was reported (1216). Next, taking into account that the mean intake of vegetables of adult females in The Netherlands is 150 g/day (17), this implies that, on average, subjects in the low vegetable group decreased their vegetable intake by 50% and subjects in the high vegetable group doubled their vegetable intake. A frozen vegetable mix was provided, consisting of 30% wt/wt cauliflower, 30% wt/wt peas, 30% wt/wt carrots and 10% wt/wt onions (Findus, Sweden) together with instructions for preparation. During the intervention period, subjects followed their normal dietary habits with, however, adapting their vegetable consumption in that sense that they were allowed to consume only the provided vegetables.
Four rectal biopsies and 20 ml peripheral blood were sampled at the first endoscopic examination and at the day following the last day of the intervention period. Biopsies were taken from healthy mucosal tissue of the rectum 10 cm above the level of the anus, immediately frozen in liquid nitrogen and stored at 80°C until use. The rectum and colon are regarded as one anatomical and functional entity and therefore rectal biopsies represent colonic environment (18). Aliquots of blood plasma were stored at 20°C until analyses. In order to assess the compliance with the intervention, levels of - and ß-carotene, retinol and
-tocopherol in plasma were determined by the method of Hess et al. (19) by HPLC-UV. By means of questionnaires, the dietary and lifestyle habits on 2 consecutive days before and during the intervention period were recorded. Energy and nutrient intake were calculated using the computerized Dutch Nutrient Data bank (20).
This study was approved by the Medical Ethical Committee of the Maasland Hospital in Sittard and written informed consent was obtained from the participants prior to the start of the study.
Total RNA isolation and cDNA probe synthesis
Four biopsies (20 mg in total) from each subject were pooled and ground to a powder in a stainless steel mortar under liquid nitrogen and homogenized in 800 µl TRIZOL reagent (Gibco/BRL). Total RNA was extracted according to the manufacturer's instructions. The RNeasy® Mini Kit (Qiagen) was used to purify total RNA from salts and residual DNA. A quantity (varied from 25 to 50 mg) of each RNA sample was measured by a spectrophotometer. Integrity was determined by a Bioanalyzer (Agilent Technologies Netherlands B.V., The Netherlands). All samples contained intact total RNA with an rRNA ratio (28S/18S) >1.5.
Cyanine 3 (Cy3)- and Cyanine 5 (Cy5)-labeled cDNA probes were prepared using 10 µg total RNA from each subject before and after the intervention period, respectively, by the method of Hasseman et al. (21). Each subject acted as its own control, meaning that the fluorescent-labeled cDNAs of each subject before and after the intervention were mixed. A second microarray experiment was carried out for each subject whereby the dyes were switched (flip-dye experiment).
Microarray experiments
Gene expression analysis was on the PHASE-1 Microarray Human-600 (PHASE-1 Molecular Toxicology, Santa Fe), which contain 597 sequence verified human genes, representing biologically relevant and control genes. Each array batch passed the slide quality index in which several parameters such as signal to noise ratios, COVs, laser intensities and others were taken into account. PHASE-1 has routinely confirmed their microarrays by using RTPCR, histological analysis and other accurate measures of expression. The genes were selected based on relevance for responses of cells to xenobiotic compounds and knowledge of the involved processes. The presented pathways relate to inflammation, DNA damage and repair, oxidative stress, cell signaling, cell proliferation, detoxification, metabolism, transcription and apoptosis, which all relate to the genetic model of CRC (810). Target genes are single stranded, 500 nt in length and spotted in quadruplicate on glass microscope slides.
A labeled cDNA probe of each subject was hybridized to the PHASE-1 microarray according to the manufacturer's instructions. Slides were scanned on a GMS 418 Array Scanner (Affymetrix, High Wycombe, UK). Both Cy3 (532 nm) and Cy5 (635 nm) channels were scanned at a photomultiplier setting of 65%. Laser power was adjusted until there were no saturated spots. The images obtained (resolution 10 µ; 16 bit Tiff image) were processed with ImaGene 5.0 software (Biodiscovery, Los Angeles, CA) to measure mean signal intensities for spots and local background.
Microarray data analyses
Data were transferred to GeneSight 4.0 (Biodiscovery) for analysis. Flagged spots were excluded. For each spot, local background intensity was subtracted. The background corrected mean intensities were log transformed (base 2). Next, the expression difference for each spot was calculated by subtracting the log transformed mean intensity from the sample before the intervention from the log transformed mean intensity from the sample after the intervention. Expression differences were normalized using Lowess and the four replicates on each array of each gene were combined to a mean expression difference with exclusion of outliers (>2 SD).
To identify up- and down-regulated genes within a vegetable group 99.9% confidence intervals were calculated [method based on Kerr et al. (22)]. This very stringent interval was chosen to reduce the chance of false positive genes to 0.1%. Cut-off levels were set at +0.25 and 0.25, respectively, because most of the genes were located within these boundaries.
The list of up- and down-regulated genes was further analyzed by means of the online software application Expression Analysis Systematic Explorer (EASE; http://david.niaid.nih.gov/david/ease.htm) (23). EASE automates the process of biological theme determination and performs a statistical analysis of gene categories in the provided gene list to find those gene categories that are the most over-presented in the list of differentially expressed genes by a Fisher exact test.
Additional statistical analyses
Statistical analysis of the questionnaire and plasma data was carried out using SPSS version 6.1.1 for Macintosh. The ShapiroWilks test was used to test normality of the datasets. Potential differences between the groups were assessed using the non-parametric MannWhitney U test or unpaired t-test. The non-parametric Wilcoxon Matched-Pairs Signed Ranks test or the paired t-test was used to assess the differences within a vegetable group. All the tests were two-sided, and a P-value <0.05 was considered to indicate statistical significance.
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Results |
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Genes with different functions were modulated, only the 20 genes that are related to (colon)carcinogenesis are explained in more detail in Table III. Seven of these genes were similarly modulated in both patients and controls. Methyl-CoA racemase alpha (AMACR) and protein kinase C beta 1 (PKCB1) were up-regulated in the low vegetable group; cyclin A2 (CCNA2) and checkpoint kinase-1 (CHK1) were down-regulated. In the high vegetable group, cyclin G1 (CCNG1) was up-regulated, and fos proto-oncogene (C-FOS) and ornithine decarboxylase 1 (ODC1) were down-regulated. Other genes that were modulated in either patients or controls include alpha-fetoprotein (AFP), prostaglandin-endoperoxide synthase 2 (PTGS2) or cyclooxygenase-2 (COX-2), cytochrome P450 2C9 (CYP2C9), Ki67 antigen, 5,10-methylenetetrahydrofolate reductase (MTHFR), activating transcription factor 3 (ATF3), human mdm2-A (MDM2), cytochrome P450, family 27, subfamily B, polypeptide 1 (CYP27B1), peroxiredoxin 1 (PRDX1), proliferating cell nuclear antigen gene (PCNA), cytochrome P450 2C19 (CYP2C19), -2D6 (CYP2D6) and -3A4 (CYP3A4).
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Discussion |
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The results of the dietary questionnaires and plasma values support that the effects on gene expression found in this study truly are the result of changing the intake of vegetables (17,24).
The differences in expression level before and after the 2-week intervention period were relatively small, but distinct as based on confidence analyses. Only the genes that are known to be related to (colon)carcinogenesis are discussed here. First, genes that were significantly modulated in both patients and controls are reviewed. Next, the most interesting genes, which were significantly modulated in either patients or controls, are discussed. Table IV summarizes the effects on expression of these genes according to subject group and in relation to possible effects on carcinogenesis.
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In the high vegetable group, CCNG1 was up-regulated, and C-FOS and ODC1 were down-regulated for both patients and controls. CCNG1 is a transcriptional target of p53 and its up-regulation coincides with activation of p53. Activated p53 suppresses growth by activating genes that trigger growth arrest or apoptosis. It is speculated that p53 activation is achieved by CCNG1 by stoichiometrically limiting the binding between p53 and MDM2, a down-regulator of p53, or by altering the phosphorylation status of MDM2 via phosphatase A2 (30). Noteworthy, also MDM2 expression is regulated by p53 (3032). For patients, down-regulation of MDM2 occurred in the low vegetable group, up-regulation of MDM2 and CCNG1 was observed in the high vegetable group. C-FOS protein interacts with the protein of another proto-oncogene, C-JUN to form a heterodimer. This complex is able to recognize and bind a specific sequence of nucleotides referred to as the AP-1 binding site located in the promoter region of genes, which are expressed in transformed rapidly growing cells (33). C-FOS is over-expressed in the pre-neoplastic colonic lesions aberrant crypt foci (33). ODC1 is a transcriptional target of C-MYC and a modifier of adenomatous polyposis coli (APC)-dependent tumorigenesis. Most sporadic colon adenomas acquire mutations in the APC gene and show defects in APC-dependent signaling. Wild-type APC suppresses C-MYC, activates the C-MYC antagonist MAD1 and reduces the expression of ODC1 resulting in a decrease in polyamine synthesis and reduced tumorigenesis. ß-Carotene inhibits ODC1 expression (34). Intake and plasma levels of ß-carotene were significantly increased in the high vegetable group and could thus explain the ODC1 inhibition. For all these genes the modulatory effects of increased vegetable intake on their expression might result in a decreased cell growth and as a consequence in lower colon cancer risk.
Patients already have a genetic predisposition to develop adenomas as compared with controls and that could explain why we found 13 genes modulated differently in patients compared with controls. The most interesting ones are discussed here. Already mentioned is the effect of vegetables on MDM2 expression in patients. Furthermore, COX-2, up-regulated in patients on low vegetable intake, is an established target for preventive interventions, as non-steroidal anti-inflammatory drugs have been shown to suppress colon carcinogenesis through the inhibition of COX-2 (35). Inhibition of COX-2 expression by vegetable components has been reported previously (36,37). In a study of Plummer et al. (36), COX-2 induction by the colon tumor promotors tumor necrosis factor or fecapentaene-12 in human colon cells was diminished by the chemopreventive agent curcumin. Wenzel et al. (37) found that that dietary flavone was able to diminish COX-2 mRNA in the human carcinoma cell line HT-29 after a 48-h incubation. In the present study, the observed up-regulation of COX-2 could be the result of a decreased intake of possible COX-2 inhibitors and agrees with the observed cancer risk suppression by dietary vegetables.
In controls, but not in patients, several phase-1 biotransformation genes were modulated. In the low vegetable group CYP2C9 was up-regulated and in the high vegetable group CYP2C19, -2D6 and -3A4 were down-regulated. The CYP genes code for enzymes that function in a wide variety of metabolic pathways involving both endogenous and exogenous compounds. In endogenous processes, CYP enzymes are involved in the biosynthesis and catabolism of signaling molecules such as steroid hormones, retinoic acid and vitamin D (38). CYP27B1 codes for the enzyme that converts vitamin D to the active hormonal metabolite 1,25-dihydroxyvitamin D3, which may act as an anti-mitotic and pro-differentiating agent in colon cancer cells (39). The expression of CYP27B1 was down-regulated in the low and up-regulated in the high vegetable group. In addition to their role in endogenous processes, CYP enzymes catalyze the biotransformation of a wide variety of xenobiotic compounds, which require metabolic activation to form ultimate carcinogens or toxicants. By blocking the formation of ultimate carcinogens, initiation of carcinogenesis can be prevented (38). CYP2C9 (38,40) and CYP3A4 are responsible for the metabolism of a number of drugs, and the (colon)carcinogens polycyclic aromatic hydrocarbons and heterocyclic aromatic amines (41). Also, CYP2C19 and CYP2D6 metabolize a number of drugs, but have not been thoroughly studied in relation to cancer susceptibility (38). Once again, all these dietary effects on gene expression of CYP450 enzymes by altering vegetable intake agree with the presumed cancer-modulating properties of vegetables.
In conclusion, almost all the effects on the expression of genes by altering vegetable intake can be mechanistically linked to cellular processes that explain prevention of colon cancer risk by high vegetable intake or higher colon cancer risk by low vegetable intake (see Table IV). The only exception to this is CCNA2, which could be involved in currently unknown but relevant processes. Furthermore, it seems that for patients, genes are modulated that are involved in the late stages of CRC like MDM2 and COX-2, whereas for controls genes are involved in initiating events, i.e. the CYP450 genes. This human study is the first in which the vegetable intake was investigated to modulate the expression of genes involved in carcinogenesis in colorectal mucosa. An increased intake of vegetables resulted in down-regulation of genes promoting cell proliferation and bioactivation of procarcinogens, and in up-regulation of genes involved in cell growth arrest; in contrast, a decreased intake of vegetables results in down-regulation of genes inhibiting cell growth and up-regulation of genes promoting cellular differentiation and bioactivation of pro-carcinogens. Some of the modulated genes are already targets in colon-chemoprevention trials, like COX-2. Possibly, the others are new targets for chemoprevention. Further research is needed to investigate what would be the relative impact of preventive modulation of these particular genetic pathways in reducing CRC risk.
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References |
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