Introduction

 Cancer cells exhibit unique metabolic signatures that are required for their aberrant proliferation [1]. Thus, monitoring changes in small-molecular-weight compounds (metabonomics) may represent an approach for detecting subtle shifts in tumor cell behavior [2]. Consequently, metabonomics holds promise as an effective tool for diagnosing disease progression, for identifying potential molecular targets, and for developing preventive and therapeutic agents (drugs and bioactive food components) [3, 4]. The two most effective approaches for metabonomic measures include nuclear magnetic resonance (NMR) and mass spectrometry (MS). Urine [5, 6], saliva [7], and blood plasma [8] have all been used successfully to monitor metabonomic patterns prior to and following intervention. Currently, a wealth of information about metabonomics is accumulating, thanks to highly sensitive Fourier transform ion cyclotron resonance MS (FT-ICR MS) [9, 10] and reliable candidate technologies such as stable isotope monitoring [11]. Scientists have long recognized that the discovery of novel and noninvasive biomarkers is fundamental to designing effective clinical studies, forecasting disease risk, understanding how molecular pathways are interconnected within cells and organisms, and ultimately predicting health. For example, a change in serum lactate concentration, as determined by 1H-NMR spectroscopy predicts weight gain during chemotherapy and ultimately breast cancer recurrence risk [12]. Likewise, the elevated urinary prostaglandin E(2) metabolite (11-α-hydroxy-9, 15-dioxo-2,3,4,5-tetranorprostane-1, 20-dioic acid) has been reported to predict a poor prognosis in head and neck squamous cell carcinoma patients and thus the need for more aggressive intervention approaches [13]. 

Unfortunately, the relationship between a given set of biomarkers and a particular pathological condition is often complicated by adjustments and adaptations, making the predictive value of such measures difficult to establish. Metabonomic profiles of blood, urine, or tissues reflecting in situ status of metabolites may provide a means of identifying such biomarkers. The annotation of metabolites identified by NMR- and MS-based experiments remains a challenge due to the diversity of study conditions. Thus, it is important to develop a standardized format that allows the scientific community to understand results from studies with widely different conditions. To facilitate this process, a working group of the Metabolomics Standards Initiative was formed in 2004 [14]. This group has established guidelines for the exchange and/or report of metabonomics data. Currently available metabonomic databases, including NIST08, PubChem, and KEGG, also help identify metabolite spectral data and structural information.An extensive review of metabonomic databases is found in a published paper [15]. Well-annotated and user-friendly databases should be able to assist in resolving unknown dietary metabolites that play a role in cancer initiation and development. Considerable evidence points to diet as a variable that can influence cancer risk and/or tumor behavior [16]. This dietary effect may arise from its interactions with key regulatory molecules in various cancer processes, including carcinogen metabolism, hormonal balance, cell signaling, cell cycle control, apoptosis, and differentiation. The goal of this paper is to provide some insights into the metabonomic assessment of dietary effects on cancer.

  This is critical to evaluate whether a single or multiple dietary component(s) modulate the early transition phase from normal to cancer phenotypes, including changes in specific enzymatic activities and carbon flows. 2. Metabonomic Shifts Caused by Bioactive Food Components in Cancer Cells Metabolic profiling of cancer cells represents global phenotypic changes, including those in glucose metabolism, amino acid metabolism, and fatty acid metabolism. This section discusses diet-induced alterations in basic metabolism that are associated with changes in cancer cell behavior and the monitoring of those changes using global metabonomic profiles. 2.1. Glucose Metabolism. A distinct difference between normal and cancer cells lies in the way these cells utilize glucose for their survival. The energy that sustains cancer cells is preferentially derived from aerobic glycolysis, which produces significantly higher amounts of lactate from pyruvate, whereas normal cells use the aerobic tricarboxylic acid (TCA) cycle, which oxidizes pyruvate to CO2 and water. Furthermore, proliferating cancer cells also utilize glucose for the synthesis of nucleotides through the nonoxidative pentose phosphate pathway (PPP) and de novo fatty acid synthesis mediated by fatty acid synthase (FAS) [1]. These differences in metabolism between normal and cancer cells are particularly interesting because they are detectable by non-invasive profiling in blood or urine and thereby can serve as clinically useful biomarkers for predicting dietinduced shifts in the metabolic switch. Potential metabonomic targets for bioactive food components are discussed 2.1.1.

 Increased Glucose Uptake. Increased glucose uptake is recognized as a hallmark for cancer cell malignancy and serves as a basis for using 18F-deoxyglucose positron emission tomography for cancer detection. Recently, a KRAS mutation with aberrant cell proliferation was found to relate to the upregulation of the glucose transporter (GLUT1) gene, suggesting that genetic mutations acquired in tumor cells account for enhanced glucose uptake [17]. This change is critical for cell proliferation [18], and thus GLUT1 expression may represent a promising target for cancer prevention. A number of dietary components, including green tea polyphenolics, cinnamon polyphenol extracts, fish n-3 fatty acids, and vegetable flavonoids such as myricetin and quercetin, have been documented as modifiers of glucose uptake by altering GLUT1 expression [19–22]. Impressively, these effects occur in several cell lines, suggesting widespread utility of their benefits. The concentrations used, at least for some, appear physiologically relevant and therefore may occur after a simple dietary change. Although these findings provide promise for the diet-mediated prevention of cancer cell proliferation, unfortunately none of these dietary effects was examined with high-throughput metabonomic profiles. Considering the ability of metabonomics to detect changes in glucose metabolism in cancer cells [23], it is likely that these dietary effects on glucose uptake, including GLUT1 expression, can be detected using the same approach. 2.1.2. Aerobic Glycolysis.

 The conversion of glucose to lactate in the presence of oxygen is a critical aerobic pathway that allows cancer cells to proliferate rapidly. In vivo expression of the M2 isoform of the glycolytic enzyme pyruvate kinase (PK) is required for this process [24]. PK has four isozymes that are tissue specific: the L and R isoforms are expressed in liver and red blood cells, respectively the M1 in most adult tissues and M2 in lung and embryonic cells. In normal proliferating cells, PK exists in a tetrameric form that transfers one phosphate group from phosphoenolpyruvate (PEP) to adenosyl diphosphate, yielding one molecule of adenosine triphosphate (ATP). In cancer cells, however, this enzyme is exclusively expressed as an M2 type of pyruvate kinase (PKM2), which results in a conformational change from a tetrameric to a dimeric form that possesses a low affinity for PEP and thus limits enzymatic function. This structural change was shown to be mediated through phosphotyrosine peptides or src in cancer cells [25], suggesting that oncogenic tyrosine kinases (TKs) might be promising targets for cancer prevention. Support for this conclusion comes from observations that PKM2 is released from tumors into the blood and can be monitored non-invasively. Plasma tumor PKM2 is reported to increase significantly as tumor progresses in lung cancer, qualifying it as a valuable biomarker [26]. Recently, delphinidin, an anthocyanidin that is abundant in grapes, cranberries, and pomegranates, has been reported to inhibit TK activities, including receptor TKs [27]. Additionally, isothiocyanates in broccoli have been reported to inhibit TK [28].

 Overall, these findings suggest that some of the antiproliferative effects of bioactive food components may arise from their ability to convert tetrameric PKM2 to dimeric PKM2 and thereby bring about a shift in glucose flux from a nonoxidative to an oxidative pathway. Although some evidence exists that changes in glucose carbon flux from glycolysis to gluconeogenesis can be measured by the combination of LC/MS metabonomic profiling with stable isotope techniques using 13C-labeled glucose [29], these approaches have not been used for the study examining dietary effects. Thus, it is warranted to use metabonomic profiling to monitor the effects of diet or dietary components on PKM2-mediated shifts in glucose flux. Although limited numbers of metabonomic studies have examined the cancer preventive effects of dietary components, the efficacy of the dietary supplement silibinin provides some proof of principle. Silibinin, extracted from a milk thistle, has been reported to significantly influence the metabolism of prostate cancer cells [30]. Quantitative high-resolution proton NMR spectroscopy was used to monitor the metabonomic profile of blood and tissue extracts in non-human animals receiving or not receiving silibinin. The metabolomic profile suggested that feeding TRAMP/C57BL/6 mice with a 1% silibininsupplemented diet reduced lactate formation, increased glucose oxidation through the TCA cycle, reversed the increase in citrate use, and decreased cholesterol and phosphatidylcholine levels in prostatic tumors, which parallels earlier findings regarding the prostate cancer preventive potential of silibinin in this animal model. 

These results suggest that non-invasive metabolomic studies can help monitor the effectiveness of cancer preventives against malignancy. 2.1.3. Increased De Novo Biosynthesis of Nucleotides via the Pentose Phosphate Pathway. Since PKM2 in cancer cells does not convert PEP to pyruvate efficiently, the upstream glucose metabolites are redirected towards a biosynthetic pathway such as PPP. Any rapidly proliferating cells, including cancer cells, utilize PPP to generate ribose-5-phosphate and the reduced form of nicotinamide adenine dinucleotide phosphate (NADPH) from glucose, which is essential for de novo DNA formation. Evidence exists that vitamin E, which is abundant in wheat germ extract and various other fat sources, inhibits nonoxidative tumor cell PPP and thereby suppresses cancer cell proliferation [31]. In leukemia patients, vitamin E was found to decrease pentose cycle substrate flow into RNA ribose, which was measured using stable isotope-labeled [1,2-13C2] glucose as the single tracer and biological MS. These changes in glucose carbon flux correlated with the cell growth-controlling and apoptosisinducing effects of fermented wheat germ [31]. Another dietary component, genistein, which is found in soy, has also been shown to exhibit a similar effect on PPP without modulating fatty acid synthesis [32]. When MIA pancreatic cancer cells were treated with a physiological concentration of genistein (20 μM) for 3 days, the carbon flux from 13C-labeled glucose to nucleic acid ribose through the nonoxidative PPP decreased significantly [32].

 These changes in PPP coincided with the cancer protective effects of either vitamin E or genistein, implying that a shift in a metabolic signature may be a useful biomarker for monitoring the efficacy of dietary components. 2.2. Amino Acid and Fatty Acid Metabolism 2.2.1. Glutaminolysis. Glucose is the major energy source in normal cells. This nutrient undergoes the metabolic switch in tumor cells from energy production to de novo biosynthesis of macromolecules, including nucleic acids. This shift increases the demand for carbon sources in cancer cells to generate ATP. It has been reported that cancer cells accumulate glutamine faster than noncancerous cells [33] and utilize it as a substrate for the TCA cycle (glutaminolysis). Ultimately, the cancer cell catabolizes glutamine to ATP and lactate. This metabolic shift is thought to be mediated by the myc oncogene [34]. It is well established that the activity of this oncogene can be modulated by various dietary components, including betaine, folic acid, genistein, and fat [35–38]. For example, supplementing the diet with betaine (1%) fed to rats developing liver tumors caused by diethylinitrosamine significantly reduced liver c-myc expression [35]. 1H-NMR spectroscopy-based metabolic profiles of plasma and urine have revealed an interaction between betaine exposure and low-density lipoprotein receptor gene expression [39]. Metabonomic profiles that explore the influence of dietary fat metabolism regulators to detect variation in c-myc oncogene expression are warranted.Wnt-1-induced, but not basal, expression of c-Myc [37].

 It is logical that several dietary components may affect myc gene expression in vivo to regulate glutaminolysis, and this issue should be clarified using metabonomics. In tumor cells, the limited affinity of tumor-specific PKM2 for PEP forces some, but not all, pyruvates to be oxidized to citrate in the mitochondria. This citrate is then exported to the cytosol, where it is used as a substrate for fatty acid synthesis (Figure 2). This shift from oxidation to lipogenesis in citrate metabolism is evident by the increased activity of FAS, which converts glucose-originated malonyl-CoA to longchain fatty acids, mainly palmitate, in tumor cells. The synthesized fatty acids are incorporated into phospholipids, the accumulation of which may cause metabolic diseases, including cancer. For example, the de novo biosynthesis of fatty acids from glucose as determined by proton NMR spectroscopy (1H-MRS) is frequently observed with the lipid droplet formation in brain tumor glioma cells [40]. The possibility that these synthesized fatty acids may modulate the oncogenic PI3K/AKT pathway and thereby influence glucose uptake and metabolism cannot be ignored. A variety of dietary components, including tea catechin, docosahexaenoic acid (DHA) in fish oil, β-glucan in barley and mushrooms, resveratrol in red grapes, the vegetable flavonoid luteolin, and conjugated linoleic acid in milk, have been shown to suppress FAS expression and activity [41–46].

 Treatment of the human breast cancer cell SK Br-3, which constitutively expresses FAS, with 150 μM epigallocatechin3-gallate (EGCG) for 24 hours resulted in a marked reduction in this enzyme activity (59% ±13%), but not its expression, compared to controls [41]. In the same study, the suppressive effect of EGCG on FAS activity was confirmed in vivo using C57BL/6J male mice. Likewise, the oral feeding of C57BL/KsJ-db/db mice with DHA (1 g DHA/100 g diet) for 4 weeks significantly reduced hepatic FAS activity accompanied by lowered levels of triglyceride [42]. Finally, feeding C57BL mice a high-fat diet supplemented with 4% barley containing a high amount of β-glucan for 12 weeks significantly reduced the hepatic FAS activity [43]. It should be possible to detect diet-induced changes in FAS with metabolomic profiling, which allows the monitoring of changes in physiologic enzyme activities using LC/MS [47]. The responsiveness of FAS to dietary components, the differential expression of this enzyme in various stages of cancer development, and its critical role in de novo lipid synthesis made it an ideal target for the dietary prevention of cancer. It has been shown that altered FAS expression brings about the signature metabolic changes in human prostate cancer. Human prostatic epithelial cells are highly unique in accumulating zinc that blocks citrate degradation. In cancer cells, however, the prostate tissue contains low levels of citrate, because it does not accumulate zinc and because most of the citrate is used for fatty acid synthesis. 1H-MRS of prostate tissues confirmed the dramatic decrease in citrate levels in prostate gland during malignancy [30].