Current Pharmaceutical Biotechnology, 2012, 13, 255-264
255
Genomics-Based Identification of Molecular Mechanisms behind the Cancer Preventive Action of Phytochemicals: Potential and Challenges
Theo M.C.M. de Kok*, Simone G.J. van Breda and Jacob J. Briedé
Department of Toxicogenomics, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6200 MD Maastricht, The Netherlands
Abstract: High intake of dietary phytochemicals, non-nutritive compounds found in vegetables and fruits, has been associated with a decreased risk of various types of cancer. With the introduction of new “omics” research approaches, technologies providing large scale and holistic data on biological responses to dietary or environmental factors, our understanding of the molecular mechanisms of the preventive action of individual phytochemicals has started to increase rapidly. This understanding contributes to the biological plausibility of the observed link between fruit and vegetable consumption and decreased cancer risk in epidemiological studies. In this mini-review, we present an overview of the characteristics of the different “omics” techniques, with emphasis on transcriptomics, epigenetics, and the analysis of single nucleotide polymorphisms, and evaluate their implications in studies on dietary phytochemicals. We focus particularly on
studies in human cell cultures in vitro and in human population studies and discuss the potential and different challenges
offered by each technique, as well as future perspectives on applications of these new tools in nutritional genomics research.
Keywords: Antioxidants, dietary intervention, genomics, human cancer prevention, multiomics phytochemicals, synergy, transcriptomics.
INTRODUCTION: CHEMOPREVENTIVE ACTION
OF DIETARY PHYTOCHEMICALS
It is widely recognized that dietary habits present a crucial factor in human cancer risk, and that changes in the dietary composition may have a strong impact on tumor initiation and further cancer development [1]. Extensive review of
the literature has demonstrated that mostly foods from plant
origin are linked with decreased cancer risk [1, 2]. The cancer preventive effects of particularly vegetables and fruits are
ascribed to the intake of fiber material and bioactive nonnutrients, also referred to as phytochemicals. These phytochemicals encompass a wide variety of chemical classes,
including minerals, amino acids, carotenoids, glucosinolates,
flavonoids, dithiolthiones and organosulphur compounds,
which may act through influences on multiple pathways involved in the carcinogenic process. As humans may consume
several thousands of different phytochemicals every day, it is
obvious that establishing causal relationships between general dietary patterns and cancer risk is a complex task. Additionally, several complex interactions amongst dietary constituents or between phytochemicals and genetic factors
(gene-diet interactions) may eventually explain the lack of
consistency in epidemiological data on cancer preventive
effects of dietary factors.
In order to use the full cancer preventive potential of phytochemicals, we need to understand these complex interac*Address correspondence to this author at the Department of Toxicogenomics, Faculty of Health, Medicine and Life Sciences, Maastricht University,
P.O. Box 616, 6200 MD Maastricht, The Netherlands; Tel: +31 43 388
1091; Fax: +31 43 388 4146; E-mail: [email protected]
1389-2010/12 $58.00+.00
tions, and have to explore new approaches and methodologies to do so. Where more traditional research designs were
successful in establishing relationships between dietary intake and only a limited number of relevant endpoints and
molecular mechanisms involved, the use of genomics techniques in functional food research may expand that horizon
and allow us to evaluate effects at a genome-wide level.
In this mini-review, we aim to evaluate the potential role
of genomics approaches in identifying relevant phytochemicals for cancer prevention. We also explore to what extent
the understanding of complex molecular mechanisms
brought forward by these approaches can be of use to establish optimal levels and combinations of these micronutrients
in the human diet. Apart from reviewing the literature on
genomics responses in human studies, with particular focus
on gene expression profiles established in either human cells
in vitro or in human in vivo research, we report on research
designs and data analysis strategies we are currently applying in our ongoing research.
NUTRITIONAL GENOMICS APPROACHES IN CANCER PREVENTION RESEARCH
In recent years, research in carcinogenesis has made remarkable steps forward, to a large extent based on the use of
new genomics-based molecular biological research methods.
Crucial genetic factors that predispose to specific types of
cancers have been identified as well as multiple genetic defects that may be induced by various environmental, dietary
or infectious agents. Our knowledge about these important
genetic hallmarks of tumorigenesis and the molecular processes involved may provide new molecular targets for cancer
prevention, as well as new strategies in cancer prevention
© 2012 Bentham Science Publishers
256 Current Pharmaceutical Biotechnology, 2012, Vol. 13, No. 1
research. Fig. (1) summarizes how the same genomics techniques applied to improve our understanding of the carcinogenic process may also be used to evaluate the cancer chemopreventive potential of phytochemicals. Such nutritional
genomics approaches are expected to result in the identification of genomics-based markers (e.g. gene expression or
metabolite profiles) that can not only be used for the prediction of potential beneficial health effects, but may also give
more insight into the actual mode of action. These biomarkers may include DNA methylation patterns, transcriptomic,
proteomic and metabolomics profiles, which all reflect cellular processes responding to the exposure to phytochemicals.
Although genetic polymorphisms are not influenced by the
diet, the analysis of different single nucleotide polymorphisms (SNPs) may be relevant to determine gene-diet interactions, and to interpret other genomics responses to phytochemical exposures [3, 4].
Genetics: SNP Analysis and Gene-Diet Interactions
Polymorphisms in genes involved in absorption, circulation, or metabolism of phytochemicals, can affect their
potential cancer preventive effects [5, 6]. Until recently, only
a few SNPs could be analyzed simultaneously using conventional PCR-based techniques and many studies have reported
the effects of nutrigenetics in relation to cancer risk [7, 8]. In
particular, the interaction between diet and polymorphisms
in genes encoding for phase I or II metabolizing enzymes is
widely studied [5, 9]. For example, London et al. [9] investigated the relation between urinary excretion of isothiocyanates and lung cancer risk, and found that individuals with
detectable isothiocyanates in urine, and bearing the glutathione S-transferase M1 (GSTM1) homozygous deletion
Regulation by the diet
Gene expression process
were at decreased risk. This effect was even stronger in individuals with both a deletion of GSTM1 and glutathione Stransferase T1 (GSTT1). In another study, polymorphisms of
N-acetyltransferase 2 (NAT2) and GSTM1 were examined in
volunteers consuming a vegetarian or a high meat diet [7].
DNA damage was measured in exfoliated colorectal mucosal
cells. It was found that the high meat diet significantly increased DNA damage in NAT2 rapid acetylators and among
individuals with a GSTM1+ genotype, while it showed no
increase in the other phenotype groups.
Since the identification of millions of SNPs by the International HapMap Consortium [10] and the introduction of
array-based genotyping techniques, it is possible to screen
the entire genome for genetic variations, referred to as genome-wide association studies (GWAS) [11]. However,
GWAS in studies with a relatively small number of subjects
will be limited by statistical power, and therefore the number
of SNPs that can be measured at the same time. To circumvent this, a pre-selection of relevant genes can be made, an
approach that has been successfully applied in a human dietary intervention study performed at our department [12].
This study showed that polymorphisms in 6 out of 34 selected genes significantly influenced the outcome of the intervention in 168 subjects. Preliminary data on the impact of
these SNPs on gene expression will be presented in section
entitled “Application of genomics tools in molecular epidemiology”.
Transcriptomics: Analysis of Gene Expression Responses
Early investigations in gene expression analysis already
revealed that micronutrients are very capable of changing the
Functional Genomic
techniques
Gene expression
regulation
Epigenetics:
DNA-methylation and
hisotone aceytylation
Transcription, RNA
processing and Stability
Transcriptomics:
DNA arrays - sequencing
RNA
Translation, modification
and stability
Proteins
Metabolites
Analysis
Genetics:
Genetic polymorphisms
(SNPs)
DNA
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de Kok et al.
Proteomics
G
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Metabolomics /
Metabonomics
Fig. (1). Nutritional genomics and the identification of genomics markers for cancer preventive effects; these biomarkers include genetic
profiles (single nucleotide polymorphisms), gene expression profiles, DNA-methylation patterns, protein profiles and metabolite profiles.
Modified from ref. [4].
Omics-Analysis of Cancer Prevention by Phytochemicals
expression levels of specific genes, and flavonoids are
probably the first and most extensively studied phytochemicals [13].
Methodologies
Several different techniques are available to study gene
expression responses, which can be subdivided into two
categories of application: i) transcriptomic studies aiming at
the identification of new genes, gene sets and complex gene
expression profiles that can be interpreted into modulation of
specific molecular pathways (whole genome DNA microarrays, serial analysis of gene expression (SAGE)) and ii) studies investigating differential gene expression of a preselected
set of interesting genes (low-density, dedicated microarrays).
Both DNA microarray techniques and SAGE are used to
produce a snapshot of the mRNA population in a sample.
Since arrays can contain tens of thousands of probes, a microarray experiment may identify complex transcriptomic
responses to phytochemicals. In contrast, SAGE is a sequence-based sampling technique that is not based on hybridization but provides insight in the transcriptome in the
form of small tags corresponding to fragments of those transcripts. For SAGE, mRNA sequences do not need to be
known a priori, implying that genes or gene variants which
are not known can be discovered.
DNA microarrays have been the technology of choice for
large-scale studies of gene expression levels, and the ability
of these arrays to simultaneously interrogate thousands of
transcripts makes this technique very valuable to establish
gene expression responses to phytochemicals. Nonetheless,
array technology has also several limitations, for example,
background levels of hybridization, effects of different hybridization properties of different probes, and arrays are limited to interrogating transcripts with relevant probes on the
array [14].
Sequencing-based approaches (RNA-seq) to measuring
gene expression levels have the potential to overcome these
limitations. It has for instance been demonstrated that the
information in a single lane of Illumina sequencing data is
comparable to that on a single array in enabling identification of differentially expressed genes, while allowing for
additional analyses such as detection of low-expressed
genes, alternative splice variants, and novel transcripts [14].
It is expected that RNA-seq will replace microarray-based
techniques and SAGE.
The gene expression changes induced by several phytochemicals, including quercetin, genistein, epigallocatechin 3gallate (EGCG), vitamin C and E or wine polyphenolics such
as resveratrol and organosulphur compounds have been investigated in microarray experiments as recently reviewed by
Knasmuller et al. [13]. However, all studies presented in this
review are performed in cell cultures or animal experiments,
but not in human dietary interventions. We will now discuss
the challenges in transcriptomics analysis in more detail including findings reported so far in the small number of publications on human in vivo studies.
Current Pharmaceutical Biotechnology, 2012, Vol. 13, No. 1
257
cusing on effects of single compounds in cultured cells. Although in vitro studies may generate important information
on gene expression changes and molecular pathways, the use
of different experimental settings, incubations, analytical
strategies and isomeric forms of phytochemicals, make the
interpretation a true challenge.
Experimental Conditions and Chemical Characteristics
of Phytochemicals
Phytochemicals can occur as different (stereo)isomers or
conjugated forms which may differ in their kinetic, toxicological and biological properties. For example, Baron et al.
[15] showed a difference in gene expression of several genes
induced by the 9-cis and all-trans isomers of carotenoids.
However, different isomers of vitamin E (synthetic all-rac tocopherol, or natural RRR--tocopherol) did not induce
different gene expression responses [16]. Brand et al. [17]
compared enantiomers of the aglycone form of the flavonone
hesperidin, hesperitin. In nature, the S-form is predominant,
while in vitro experiments are performed with the commercially available racemic mixture. Although significant differences in transport and metabolism, like conjugation, were
found, gene expression by the R- and S-form was comparable. In addition, non-conjugated forms of phytochemicals
have been extensively studied in vitro, while mainly the conjugated forms are found in food [18]. Quercetin-conjugates
display differential antioxidant properties in vitro [19], and
the differences between these could be revealed by genomewide transcriptomic analyses. The use of different solvents
also needs to be taken into consideration. Most phytochemicals are only soluble in organic solvents like dimethyl sulfoxide (DMSO), ethanol and tetrahydrofuran (THF). To
avoid cytotoxicity, maximally 0.5% solvent is used in cell
incubations, but comparable ethanol concentrations can
change expression of multiple genes [20], indicating that
solvents could disturb gene expression induced by the investigated phytochemicals. Furthermore, these solvents are potent radical scavengers and able to interfere with antioxidant
effects.
In Vitro Transcriptomics Studies
The advantage of using a single celltype as compared to
more complex in vitro systems, is that results are not disturbed or diluted by complex interference by deviant transcriptomic responses produced by different cell types [21].
Gene expression changes induced by phytochemicals may be
the consequence of direct radical scavenging activity, induction of antioxidant enzymes, modulation of phase I and II
metabolism, repression of inflammatory or induction of antiinflammatory mechanisms, and interference with other signaling pathways.
Challenges in Transcriptomics Analysis
The most direct approach to investigate beneficial health
effects is by interpretation of gene expression changes induced by a single phytochemical [22]. For example, van Erk
et al. [23] reported a broad range of effects caused by quercetin showing the influence on genes involved in cell proliferation, tumor suppression, cell adhesion and signal transduction.
A growing number of studies use transcriptomics techniques to investigate effects of phytochemicals, mostly fo-
Phytochemicals can act as direct radical scavengers, and
detection of the antioxidant activities of phytochemicals in
258 Current Pharmaceutical Biotechnology, 2012, Vol. 13, No. 1
cultured cells may require the stimulation of reactive oxygen
species (ROS) by oxidants, like H2O2 or menadione, to a
level that causes measurable damage. ROS triggers cell signaling molecules and a key sensor in the early response is the
antioxidant responsive element (ARE) binding transcription
factor nuclear factor (erythroid-derived 2)-like 2 (NFE2L2 or
NRF2) [24]. NRF2 activation induces ARE-mediated genes
resulting in an upregulation of antioxidants enzymes. Previously, we showed that different oxidants modified gene expression profiles showing different temporal effects and
pathway changes [25], suggesting that also antioxidant responses to phytochemicals should be evaluated using multiple oxidant systems. On the other hand, most cultured cell
lines are derived from tumor cells that already display increased levels of ROS [26]. Furthermore, oxygen levels in
cell cultures are higher than under normal physiological conditions, so it may not be necessary to apply oxidants.
Biological interpretation is further complicated by the
observation that some phytochemicals activate NRF2 responses via ROS formation [27]. Using specific inhibitory
antioxidants can discriminate between oxidant-induced genomics responses and other effects of phytochemicals. For
example, by the addition of catalase, EGCG and EGCGderived H2O2-induced gene expression can be distinguished
[28]. High levels of phytochemicals can result in pro-oxidant
effects, like oxidative DNA damage, but this can subsequently activate beneficial repair responses. Treatment with
pro-oxidant levels of vitamin C induced acute response
genes, but no induction of genes related to cell cycle arrest,
DNA repair or apoptosis was found [29].
Finally, it was suggested that the chemopreventive properties of interactions among various dietary ingredients may
result in the potentiation of the activities of single constituents, and therefore these interactions may better explain the
preventive effects of whole foods and diets in epidemiological studies. In an earlier review, an overview is presented of
different mixtures and combinations of polyphenols with
other classes of phytochemicals that show synergistic effects
[30].
In conclusion, for the correct interpretation of phytochemical-induced transcriptomic effects in cultured cells,
studies are needed that compare multiple phytochemicals on
well defined cell types using comparable incubations, different doses, time points, and phenotypical endpoints.
Human Studies Using Transcriptomics
Only a few human studies exist in which the effects of
dietary phytochemicals are established using transcriptomics.
Applying a dedicated array with 256 cytokine/human receptor genes, Majewicz et al. [31] showed the potential of trancriptomics analysis to establish effects of micronutrients. In
this study, the impact of vitamin C supplementation was determined in monocytes from smokers and non-smokers. In
total 22 genes showed a 2 fold change in non-smokers and
71 genes in apoE4 carriers/smokers. In smokers, 4 key genes
were differentially expressed: tumor necrosis factor-beta,
tumor necrosis factor-receptor, TRK1-transforming tyrosine
kinase protein, and monocyte chemotactic protein-1. In a
study from our department [32], two groups of adenoma patients and healthy controls received either a 50% decreased
de Kok et al.
(=75 g/day) or doubled (=300 g/day) vegetable intake for 2
weeks. Gene expression analysis in colon biopsies, using
dedicated arrays containing 600 relevant genes, showed that
mainly genes related to cell cycle control and genes for oxidoreductase activities were differentially expressed. Twenty
genes were modulated that were known to be related to (colon)carcinogenesis. Almost all effects of altered vegetable
intake were mechanistically linked to cellular processes that
explain either prevention of colorectal cancer risk by high
vegetable intake or increased colorectal cancer risk by low
vegetable intake.
In a third study, a combined mix of selected dietary factors (resveratrol, green tea extract, -tocopherol, vitamin C,
(omega-3) polyunsaturated fatty acids, and tomato extract)
were given as supplements to 36 healthy overweight men
with mildly elevated plasma C-reactive protein concentrations in a crossover study with treatment periods of 5 weeks
[33]. The transcriptomes of peripheral blood mononuclear
cells and adipose tissue were quantified using a custom designed genechip containing 23,941 probe sets [34]. Results
showed changes in inflammation-, oxidative- and metabolism-related processes.
In another study, 6 weeks selenium supplementation in
16 subjects resulted in subtle gene expression changes in
1256 genes (P<0.05) from lymphocytes, as detected by 22K
arrays. Pathway analysis indicated that most genes encoded
for proteins active in protein synthesis [35].
The results from human studies offer relevant information about molecular mechanisms modulated by phytochemicals, but also raise questions about the type of cells/
tissues that need to be studied.
Epigenetics and microRNAs
There is a growing body of evidence that dietary factors
can also modify gene expression by epigenetic and posttranscriptional mechanisms. Several different mechanisms
controlling gene expression at the transcription level have
been identified, including DNA methylation, histone modifications, and chromatin remodeling factors [36]. Additionally,
microRNAs (miRNAs) regulate gene expression at the posttranscription level, by targeting messenger RNAs for cleavage or translational repression, eventually resulting in silencing of the target mRNA and thus silencing specific gene expression [37]. Most widely studied among the gene expression control mechanisms are DNA methylation and histone
modifications, although interest in effects of dietary factors
on miRNAs is increasing.
Changes in DNA methylation have been observed in
many different cancer tissues, and global hypomethylation,
associated with chromosomal instability, is commonly observed in cancer cells [38]. On the other hand, regionspecific hypomethylation has been linked with oncogene
overexpression whereas site-specific hypermethylation has
often been associated with silencing of tumor suppressor
genes [39]. DNA methylation can be influenced by food
components through different mechanisms, of which the
presence of methyl donors such as folic acid, choline or betaine, is known to be crucial. Further, DNA methylation is
catalyzed by DNA methyltransferases (DNMTs) of which
Omics-Analysis of Cancer Prevention by Phytochemicals
Current Pharmaceutical Biotechnology, 2012, Vol. 13, No. 1
the activity can also be modulated by dietary compounds
[40, 41].
Histone modification is another epigenetic mechanism
that can be influenced by the diet [41, 42]. Generally, acetylation of histones is associated with an open chromatin structure and active chromatine, whereas methylated histones are
associated with gene silencing. The acetylation state is controlled by the balance between the activities of two antagonistic enzyme systems: the histone acetyltransferases (HATs)
that transfer acetyl groups to the lysine residues of the histones, and the histone deacetylases (HDACs) that in turn
hydrolyze these modifications [43].
Studies on epigenetic changes mainly focus on DNA
methylation, and were until recently restricted to either
global DNA methylation or the methylation status of specific
DNA sequences. Currently, a wide range of methods is
available to establish genomic DNA methylation, either
based on bisulfite treatment of the DNA, or on DNA immunoprecipitation (MeDIP). The latter technique provides
the basis for high-throughput whole genome detection
methods such as high-resolution DNA microarrays (MeDIPchip) or next-generation sequencing (MeDIP-seq) [43]. In
addition to MeDIP, chromatin immunoprecipitation provides
the basis for identifying the location of modified histones.
This technique is currently combined with microarray technology, like Chip-on-chip and Chip-seq. These highthroughput methods generate huge amounts of data and dataTable 1.
259
analysis is the major challenge in this field.
The fact that epigenetic regulation of gene expression is
involved in cancer progression and that epigenetic changes
are also reversible, make these processes a promising target
for drug development and cancer risk prevention strategies.
Epigenetic activities have been reported for several phytochemicals, of which an overview is given in Table 1. The
effects of the dietary flavonoids on promoter methylation
status and transcriptional activation of methylation-silenced
genes has recently been reviewed by Gilbert and Liu [41].
Also other classes of phytochemicals, such as organosulphur
compounds and isothiocyanates are known to influence H3
and/or H4 acetylation and to inhibit the activity of the
HDAC enzyme [54, 55, 57]. In vivo, a single dose of sulforaphane ingested by humans resulted in an induction of H3
and H4 hyperacetylation associated with HDAC inhibition in
peripheral blood mononuclear cells, suggesting that these
cells could be used as biomarkers for human HDACinhibition studies [58].
Recent evidence suggests that dietary compounds as diverse as EGCG, folate, genestein, retinoids, and curcumin
exert cancer-protective effects through modulation of
miRNA expression [63, 64]. miRNAs are short noncoding
RNAs that are important in post-translational gene regulation, including regulation of cell proliferation, apoptosis, and
differentiation processes. miRNAs are involved in cancer
initiation and progression and their expression patterns serve
Epigenetic Effects of Dietary Phytochemicals
Dietary Source and
Class
Epigenetic Mechanism
Effect
References
Green tea catechin
Demethylation of hypermethylated CpG islands of
tumor suppressor genes
Reactivation of silenced tumor suppressor genes e.g.
p16, RAR, O 6-methylguanine transferase, and
hMLH1 in different cell lines; particularly after prolonged treatment
[39, 44-46]
Genistein
Soy isoflavone
Demethylation of tumor
suppressor genes; histone
acetylation
Reactivation of silenced tumor suppressor genes e.g.
p16, RAR, O 6-methylguanine transferase, and
hMLH1 in different cell lines; synergistic effect of
HDAC and DNMT inhibition. Increased H3/H4 acetylation p16 and p21
[39, 47-49]
Caffeic acid /
Chlorogeneic acid
Catechol containing
coffee polyphenols
Inhibition of DNMT
Inhibition of DNA methylation through increased
formation of SAH
[50]
Selenium
Trace element
Modulation of DNA methylation status
Deficiency results in global hypomethylation
[51]
Folate
Dietary methyl donor
Modulation of DNA methylation status
Deficiency results in global hypomethylation; synergistic interaction with selenium
[52, 53]
Sulphoraphane
Isothiocyanate found in
e.g. cruciferous vegetables
Histone acetylation / HDAC
inhibition
Increased Histone H4 acetylation within the p21 promoter both in vitro (prostate, kidney and colon cell
lines) and in vivo (Apcmin mice and human subjects).
[54-58]
Phenethyl isothiocyanate
Isothiocyanate found in
e.g. cruciferous vegetables
Histone acetylation / HDAC
inhibition
Enhanced histone acetylation and selective modification of histone methylation for chromatin remodeling
[59, 60]
Dialyldisulfide
Organosulfur compound found in allium
Histone acetylation
Histone H3 / H4 acetylation within CDKN1A promoter
[61, 62]
Compound
EGCG
260 Current Pharmaceutical Biotechnology, 2012, Vol. 13, No. 1
de Kok et al.
as phenotypic signatures of different cancers. miRNAs may
be useful as biomarkers of cancer prevention or nutritional
status, as well as serve as potential molecular targets that are
influenced by dietary interventions. For instance, Tsang et al.
[63] showed the importance of miRNAs in the regulation of
the biological activity of EGCG and identified the role of
miR-16 in mediating the apoptotic effect of EGCG. Furthermore, curcumin was shown to induce apoptosis through a
miRNA pathway involving caspase-10 as a target of
miRNA-186* [65].
ics” techniques will become increasingly important in nutritional genomics studies [77, 78]. Development of integrated
data analyses tools is just starting and several approaches and
opinions have been published [77]. A promising tool is Bayesian networks analysis, which enables an integrative, multiplex correlation of different “omics” with phenotypic biomarkers [79].
Proteomics, Metabolomics and Integrative Multiomics
As mentioned above, the number of epidemiological
studies applying “omics” technologies is very limited, but
from these studies we learned that the results are valuable for
the understanding of phytochemical-induced effects. Below
we will describe the approach undertaken within an ongoing
large-scale human dietary intervention study, in which different “omics” technologies are applied to establish the biological pathways associated with phenotypic markers of effect and exposure within different genetic susceptible
groups. A detailed description of the study design has been
published [12]. In short, 168 healthy volunteers consumed a
blueberry/apple juice rich in quercetin, anthocyanins and
vitamin C for a period of 4 weeks, in order to evaluate the
preventive properties of fruit-borne antioxidants present in a
complex mixture. After the intervention, plasma concentrations of quercetin and vitamin C, and total plasma antioxidant capacity were significantly increased. Moreover, 20%
protection (P < 0.01) against ex vivo hydrogen peroxide provoked oxidative damage in lymphocytes as was detected by
the comet assay. Upon classification of subjects according to
34 genetic polymorphisms, 6 appeared to influence the outcome of the intervention.
Although all proteins are coded by mRNA, it is not realistic to expect that the presence and activity of enzymes can
be accurately predicted based on transcriptome analysis only
[66]. As the proteome consists of all proteins present in a
specific cell type it may actually provide a better indication
of the biological impact of dietary intake as compared to the
transcriptome. However, high throughput analysis of the
highly variable proteome is still a major challenge. Although
proteome analysis may hold great promise for application in
studies on cancer preventive effects of dietary phytochemicals, until now it has mainly been applied in in vitro and
animal studies, focusing on effects of specific compounds,
and a targeted analysis of proteins [13, 67-69]. Also a limited
number of human dietary intervention studies with either
cruciferous vegetables, vitamin C or -tocopherol have
shown relevant proteomics responses [31, 70-72]. These
studies demonstrate that indeed proteomics analysis, particularly when combined with transcriptome analysis, may reveal effects of dietary phytochemicals relevant in cancer
prevention.
Metabolomics approaches aim to identify changes in
relevant physiological processes, based on modifications in
the occurrence and concentrations of all end-products of
metabolic enzyme activity in response to exposures or
changes in environmental conditions. One of the biggest
advantages of this technique is that it can be applied to
biological samples like urine, serum or plasma, making it
very suitable for biomonitoring purposes. Although metabolomics analysis can bring comprehensive understanding of
biological processes a step forward, studies on the effects of
dietary phytochemicals are still very sparse. For instance,
Solanky et al. [73, 74] described soy-induced alterations in
protein, fat and carbohydrate metabolism based on plasma
metabolites related to the dietary intervention, whereas
Wong et al. [75] indicate metabolomic alterations in the urinary metabolite profile after isoflavone consumption. Other
studies focused more on the kinetics and metabolism of the
phytochemicals themselves. Fardet et al. [76] described the
analysis of different types of urinary metabolites of lignins in
a study that illustrates that metabolomics allows the identification of new metabolites of phytochemicals and can also be
used to distinguish individuals fed different phytochemicalcontaining foods.
Although each “omics” technique has its own merits and
limitations, combined analysis and interpretation of multiomics data are likely to offer the best opportunities for comprehensive understanding of the biological influences induced by phytochemicals. Data integration of different “om-
APPLICATION OF GENOMIC TOOLS IN MOLECULAR EPIDEMIOLOGY
In a follow-up of this project, whole genome microarray
analysis was performed to study gene expression modulation
in relation to markers of antioxidant action that were already
established in the group as a whole and in various subgroups
showing a protective effect against oxidative DNA damage.
We used a paired study design, in which each subject acted
as his/her own control. Microarray hybridization and primary
data analyses were carried out as described [80]. In addition
to the whole study population for which comet data were
available (n = 147), subgroups were defined according to the
magnitude of the effect in the comet assay, according to sex,
and according to polymorphism (GSTT1*0 or XRCC1*4)
(Table 2). For each subgroup, gene lists were generated by
means of pair wise t-tests (P<0.05). Venn diagrams were
generated in which the significantly changed genes were
incorporated for the subgroups under one heading, thereby
showing the number of genes which were specifically modulated in each subgroup separately (complement) (Table 2),
and modulated by all subgroups (intersection). As a number
of genes are similarly modulated within all subgroups under
one heading, these can not provide information on gene
regulation within a specific subgroup. For example, in men
(subgroup 6.1) and women (subgroup 6.2) a number of genes
will be similarly modulated, but these genes don’t provide
any information about sex-specific responses. In contrast, to
investigate the contribution of a specific subgroup, e.g. men
(subgroup 6.1) to the effect observed in another group, e.g.
to all subjects (group 1), similarly modulated genes are of
interest. This approach enables us to specifically relate gene
Omics-Analysis of Cancer Prevention by Phytochemicals
Table 2.
Current Pharmaceutical Biotechnology, 2012, Vol. 13, No. 1
261
Gene Expression Changes in Defined Subgroups as Analyzed by Whole Genome Gene Expression in Lymphocytes of Subjects Consuming One Litre of Blueberry Juice Per Day for 4 Weeks
Group$
N£
Effect in the Intervention on Oxidative DNA
Damage *
Significantly Modulated Genes #:
Subgroup Specific (Complement
Genes in Venn Diagram)
1) All subjects for which comet data were available
147
9485
2.1) All subjects mean different tail moment < -2
74
4304
2.2) All subjects mean different tail moment > -2
73
7776
3.1) All subjects mean different tail moment < -2
74
3528
3.2) All subjects mean different tail moment > -2 and < 2
37
No effect
1099
3.3) All subjects mean different tail moment > 2
36
5126
6.1) Men
46
3088
6.2) Women
101
4125
4.1) GSTT1 wildtypes
122
5765
4.2) GSTT1 homozygous
25
2179
5.1) XRCC1*4 wildtypes
57
1410
5.2) XRCC1*4 hetero- and homozygous
91
6274
Subgroup§
Effect on mean tail moment comet assay
One group
Two groups
Three groups
Sex
Two groups
Polymorphisms
GSTT1
XRCC1*4
$ Different groups were analyzed: based on the effect in the comet assay; based on sex; and, based on polymorphisms.
§ Subgroups defined per analyzed group
£ Number of subjects per subgroup.
* Arrows represent direction of effect, number of arrows indicate magnitude of effect.
# Include annotated and non-annotated genes. Significantly differentially expressed gene lists after the intervention were generated by means of pair wise t-tests
(P<0.05). Venn diagrams were created in which the significantly differentially expressed gene lists were incorporated for each group, thereby showing the
number of genes which were specifically modulated in each subgroup separately.
expression changes to a particular subgroup with a specific
property, in this example men (subgroup 6.1). In addition,
also the contribution of the gene expression response from a
particular subgroup with specific characteristics to the total
effect, in this example the contribution of the effect in men
(subgroup 6.1) to the effect observed in the whole group
(group 1), can be revealed. This approach increases the
power in finding relevant underlying molecular pathways.
Even though the magnitude of effect and the number of
significantly modulated genes for the different subgroups is
relatively low as compared to pharmaco- and toxicogenomic
studies, this is a commonly observed phenomenon [81] and
in line with other dietary intervention studies [35, 82, 83].
Although individual gene expression differences can be
of interest, interpretation of the intervention effect on biological processes can be studied using pathway analyses
tools. At the moment, the complement and intersection gene
sets are exported from the Venn diagrams and transferred
into these tools. We expect that the number and nature of
significantly modulated pathways will vary between different (sub)groups, as the number and type of genes also dif-
fered. In addition to common pathways, specific pathways
will provide information on the biological processes which
are particularly relevant for these (sub)groups.
Correlation analyses between gene expression changes
and phenotypic markers will provide information on whether
there is a linear relationship with measured parameters. This
approach has been successfully applied in the field of toxicogenomics in order to identify chemically induced gene
expression changes related to well-defined indices of toxicity
[84]. Applying this approach in our study, Spearman’s rank
correlations between gene expression and levels of oxidative
DNA damage for the different (sub)groups will identify significantly correlating genes that can be included in further
pathway analysis.
In conclusion, the application of genomics in molecular
epidemiology will offer more insight into the underlying
molecular mechanisms, allowing discovery of biomarkers to
assess efficacy of chemoprevention and investigation of the
relation between exposure and effects. In particular, using
phenotypic anchoring and investigating specific subgroups
with defined genetic background, will increase the power of
262 Current Pharmaceutical Biotechnology, 2012, Vol. 13, No. 1
functional interpretation of large data-sets, resulting in an
improved understanding of the mode of action of intervention-related effects.
CONCLUDING REMARKS
Phytochemicals have been identified as dietary factors
that may have an important impact on cancer risk development. This has been demonstrated in both epidemiological
and animal studies, whereas our understanding of the molecular mechanisms behind the cancer preventive action is
mainly based on results from in vitro studies. With the introduction of new “omics” techniques, our insight in the
mechanisms of action expands rapidly, and it is exactly this
insight that adds biological plausibility to the observed associations between high intake of foods rich in phytochemicals
and reduced cancer risk. These new developments enable the
identification of omics-based biomarkers that can be applied
in future molecular epidemiological studies and which are
likely to improve their sensitivity. Results from the earliest
studies in this field have demonstrated that both transcriptomic and proteomic changes can indeed be established after
human dietary interventions with phytochemicals. Gene expression changes have been established in both target tissues
and in lymphocytes as surrogate tissue, indicating the possibility of using specific gene expression profiles, preferably in
combination with other “omics” markers, in human population studies using biological materials such as blood and
urine, from already existing biobanks. This approach is already being applied in a limited number of projects focusing
on genomics responses to environmental and dietary exposures [85, 86].
Apart from the possibilities that “omics” techniques offer, also challenges and limitations have been identified.
These relate to the application of different study designs and
experimental conditions that are applied in in vitro studies,
which make the interpretation of the outcomes into potential
health effects in humans rather difficult. Also, each technique has it’s own technical limitations, which emphasizes
the fact that the integration of different genomics markers
along with phenotypical endpoints is the most promising
approach. This Systems Biology approach requires further
development of integrative data analysis tools, and although
progress is being made in this field, no applications have
been reported in relation to studies on dietary phytochemicals.
Genomics research on phytochemicals offers several attractive future perspectives. Apart from the application of
genomics markers in epidemiological studies, the evaluation
of the impact of genetic polymorphisms on gene expression
profiles and other genomics responses may identify susceptible subpopulations and groups that may particularly benefit
from dietary interventions with phytochemicals. This opens
possibilities to arrive at individual dietary advice that takes
genetic variability into account. The selection of genes to be
studied and the interaction between different polymorphisms
appears to be especially important in the study of variable
responses to dietary factors. Therefore, there are still some
scientific as well as ethical hurdles to overcome before sound
personalized nutritional recommendations can be provided.
Another future perspective is the potential use of genomics
de Kok et al.
markers in establishing antagonistic and synergistic effects
of combinations of phytochemicals based upon understanding of the combined and complementary modes of action.
Particularly in view of the fact that several phytochemicals
are known to possess both beneficial and detrimental effects
depending on the dose [87], establishing the optimal combinations and intake levels may lead more effective cancer risk
prevention strategies. Furthermore, understanding combined
modes of action of different classes of phytochemicals may
be valuable in selection and cultivation of varieties of crops
that eventually contribute to an optimally balanced diet
aimed at the prevention of cancer.
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