How lipidomics provides new insight into drug discovery.

Review

How lipidomics provides new insight into drug discovery Antonin Lamaziere, Claude Wolf & Peter J Quinn† †

King’s College London, Department of Biochemistry, London, UK

1.

Introduction

2.

Three levels of metabolic regulation

3.

Antitumour action of lipid synthesis inhibitors

Expert Opin. Drug Discov. Downloaded from informahealthcare.com by University of Laval on 07/10/14 For personal use only.

4.

Potential of de novo lipogenesis inhibitors as anticancer drugs

5.

Hormone-driven lipogenesis and propensity for malignant transformation

6.

Drugs targeting lipid biosynthesis

7.

Targets of acetylCoA

8.

Toxicology of inhibitors of

carboxylase in plants lipogenesis 9. 10.

Potential medical application of DNL inhibitors Examining the lipidome to assess drug candidates

11.

Conclusions

12.

Expert opinion

Introduction: Automated lipidomic methods based on mass spectrometry (MS) are now proposed to screen a large variety of candidate drugs available that inhibit de novo lipid synthesis and replace tedious methods based on radiotracer incorporation. A major new interest in inhibitors of de novo lipogenesis is their proapoptotic effect observed in cancerous cells. Areas covered: In this review, the authors focus on the screening methods of antilipogenic inhibitors targeting the synthesis of malonylCoA (carbonic anhydrase, acetylCoA carboxylase), palmitylCoA (fatty acid synthase condensing and thioesterase subunits) and monounsaturated fatty acids (D9-desaturase). The consequences of inhibition depend on how the pathway deviates above the blockade: accelerated mitochondrial fatty acid oxidation following the decreased malonylCoA level, accumulation of ketone bodies and increased cholesterol synthesis following the increased acetylCoA level. Side effects such as anorexia and skin defects may critically decrease therapeutic indices in the long term. The authors emphasize the need for assessment of toxicity in short-term treatments inducing proapoptotic effects observed in aggressive hormone-dependent malignancies. Expert opinion: The activity of lipogenesis inhibitors can be recognised in lipid profiles established by a combination of MS-based measurements and multivariate analysis processing hundreds of lipid molecular species. Because the method can be automated, it is suitable for screening large chemical libraries, with particular focus on anticancer activities. Keywords: anticancer drug, inhibitors of lipogenesis, obesity, pharmacological screening, toxicology Expert Opin. Drug Discov. (2014) 9(7):819-836

1.

Introduction

The metabolic pathways of lipid biosynthesis and turnover in higher organisms have been delineated in studies dating back to the 1960s when laboratory methods of lipid analysis and characterisation became routine. Step changes in these methods introduced in more recent times, primarily mass spectrometry (MS)-based lipidomics, have witnessed a considerable refinement of our knowledge of the detailed structure and tissue content of lipids [1,2]. What is most impressive from a glance at a metabolic chart of reactions mapping lipid synthesis and metabolism is the highly complex passage these reactions follow in the generation of a huge assortment of molecular species representing the lipidome of an organism. Moreover, there are clear interdependencies in biosynthesis of polar and nonpolar lipids reflecting their respective structural and metabolic reserve roles. With the advent of current methods of interrogating the lipidome giving an unparalleled insight into the lipid composition of cells and organelles, a remarkable homeostasis of lipid metabolism has been revealed. This tight regulation is governed by the operation of biochemical sensors that tune the metabolism of lipids via hormones and translation factors to maintain a healthy metabolic status of the organism over time while nutrition is changed in amounts and quality [3]. 10.1517/17460441.2014.914026 © 2014 Informa UK, Ltd. ISSN 1746-0441, e-ISSN 1746-045X All rights reserved: reproduction in whole or in part not permitted

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Mass spectrometric lipidomic methods can characterise the effects and side effects of candidate drugs inhibiting lipogenesis. Automation of LC coupled with tandem MS provides high drug screen throughput that avoids use of radiotracers in clinical trials. Inhibition of de novo lipid synthesis has already been achieved by existing candidate drugs at the level of malonylCoA (inhibition of carbonic anhydrase and acetyl CoA carboxylase), fatty acid synthase (inhibition of the condensing or thioesterase subunits) and D9-desaturase (inhibition of stearoylCoA desaturase). The consequences of inhibition of key enzymes depend on how the biosynthetic pathway deviates above the blockade and include accelerated mitochondrial fatty acid oxidation, accumulation of ketone bodies and increased cholesterol synthesis. Inhibitors of de novo lipogenesis is observed in cancerous cells as a proapoptotic effect. Aggressive hormone-dependent malignancies developed from tissues with a functional lipogenesis such as breast cancers are particularly sensitive. Applying a procedure of ‘lipid profiling’ can circumvent the difficulties of quantification for such a large variety of lipid molecular species in animal tissues. Profiles handled by multivariate analysis procedures reveal the occurrence of intensive lipogenesis and the counter activity of inhibitors.

This box summarises key points contained in the article.

It is, therefore, not surprising that disturbance of lipid homeostasis can have a genetic origin or arise from abnormal nutritional and hormonal factors to which an individual may be subjected. The latter gives rise to recognisable metabolic disorders significant among which are diabetes, obesity, inflammatory diseases and possibly, malignancy [4]. The clinical management of these conditions requires not only adjustments in nutritional status mediated largely by prescribed lifestyle changes [5] but also supplementation of drugs that directly modulate lipid metabolic status. The most successful medical intervention in management of disorders of lipid metabolism is undoubtedly the widespread use of statins to inhibit HMGCo-A reductase, the key enzyme in sterol biosynthesis, to reduce blood cholesterol concentration [6]. This results in a considerable reduction in risk of coronary heart disease, stroke and peripheral arterial disease [7,8]. One of the reasons why these drugs are effective is that the source of cholesterol is partly de novo biosynthesis and partly from the diet; statins reduces the proportion of sterol generated via the biosynthetic route, which increases its uptake into peripheral cells from circulating atherogenic lipoproteins. Although cholesterol occupies a prominent position in risk to health, it is not unique amongst lipids representing increased propensity to disease. Storage of excess lipid in visceral fat depots, for example, is known to be associated with diabetes and comorbidities such as lipotoxicity related 820

to obesity [9]. The ability to regulate key enzymes, either at the level of transcription or catalytic activity, in the different pathways of lipid biosynthesis provides an opportunity to alleviate these debilitating conditions. The reverse strategy is adopted by exploiting a disturbance of lipid metabolism in development of selective herbicides or in genetic modification of oilseed crops to resist the action of herbicides-targeting lipid metabolism [10]. In animal malignancies, especially hormone-dependent cancers, it is likely that mutations affecting regulation of de novo lipogenesis (DNL) are also responsible for augmenting the supply of lipids required for cell proliferation [11,12]. Thus, anti-lipogenic agents are now examined for their anticancer activity. With the advent of current lipidomic methodologies, it is possible not only to screen efficacy of drug candidates targeting different aspects of lipid metabolism but also to monitor repercussions in the maze of interrelated pathways that regulate the lipidome. 2.

Three levels of metabolic regulation

The survival of organisms and their successful environmental adaptation rely on an ability to adjust energy flux through anabolic and catabolic pathways in conditions of changing nutrient status. In evolutionary terms, advantages accrue when the organism is hungry and in a low metabolic state it becomes aroused and alternatively when in a high metabolic or satiety state a sleep or cortical inactivity is induced. This requires the existence of feedback loops to coordinate metabolism with behaviour, that is, a metabolic-brain axis. Such short-term feedback loops have been proposed to operate to couple nutritional intake with activity of orexinergic neurons in the lateral hypothalamus [13]. The control of metabolism in multicellular organisms is also overseen by hormones that modulate key steps in multienzyme pathways. Hormonal control of nutritional behaviour is also exercised at the level of the brain. The most important regulator of lipid metabolism is leptin, which acts on receptors in the brain to reduce appetite (anorexigenic influence) and food intake [14]. Leptin is a polypeptide of 167 amino acids, synthesised and secreted from adipose tissues. Receptors for leptin are located in various sites of the brain. In the brainstem, leptin inhibits the activity of 5-hydroxytryptamine neurons thereby increasing the activity of anorexigenic proopiomelanocortin neurons of the arcuate nucleus of the hypothalamus. These neurons are also directly stimulated by leptin, whereas orexigenic neuropeptide Y neurons are inhibited by the hormone thereby suppressing appetite. Leptin also modulates orexigenic neurons via neurotensin neurons in the lateral hypothalamus and dopamine neurons of the ventral tegmental area included in the reward circuit of the brain. Another hormone secreted by adipose tissue is adiponectin, an adipocytokine, but in contrast to leptin, the serum levels are decreased not only in line with increasing obesity but also in type-2 diabetes and other diseases associated with obesity [15]. Adiponectin has been shown to stimulate b-oxidation

Expert Opin. Drug Discov. (2014) 9(7)

How lipidomics provides new insight into drug discovery

Dietary substrates Carbohydrates Glucose

DNL Pentoses-5-P Secondary substrates

Glucose-6-P

GPAT LPA Glycero-3-P AGPAT

Pyruvate NADPH2

PA

Pyruvate

Oleyl-CoA


Acetyl-CoA Acetyl-CoA Oxaloacetate

Citrate

-

PC HCO3CAV

Malate Pyruvate

CL (ATP) Citrate

HCO3-

ACC

Stearyl-CoA

Malonyl-CoA

Palmityl-CoA

CA II

FAS

DAG DGAT TAG

Oxaloacetate MDH1 Malate Pyruvate ME (NADP)

Final lipid storage

Figure 1. DNL pathway. DNL leads to incorporation of saturated and monounsaturated fatty acids into TAG stored in the adipose tissue or secreted as lipoproteins from the liver. While the primary substrate, acetylCoA, is produced from glycolysis in the mitochondria, other cytosolic steps generate malonylCoA. The formation of this ‘secondary’ substrate is impacted by numerous inhibitors such as cytosolic CA II, ACC isoenzymes. Such inhibition is manifest by reduced levels in malonylCoA, which accelerates acylCoA transfer into mitochondria via carnitine palmitoyltransferase for oxidation. Elevated acetylCoA levels can be converted to higher ketone bodies and cholesterol in the liver. MalonylCoA is the substrate for FAS producing palmitylCoA (16:0). The product of FAS is elongated and desaturated by stearoylCoA desaturase (SCD1) predominantly to oleylCoA (18:1n9). Other SCD1 by-products include palmitoyl- (16:1n7 and n9), vaccenyl- (18:1n7) and eicosatrienoyl-CoA (20:3n7 and n9), which are markers for DNL. In adipogenic tissues, the amounts of fatty acids produced are readily incorporated in TAG associated with cholesterol esters in lipid droplets. ACC: AcetylCoA carboxylase; AGPAT: Acylglycero-phosphate acyltransferase; CA V and CA II: Carbonic anhydrase V and II; CL(ATP): ATP-dependent citrate lyase; DAG: Diacylglycerol; DGAT: Diacylglycerol acyl transferase; DNL: De novo lipogenesis; FAS: Fatty acid synthase; GPAT: Glycerol-3Ph acyltransferase; LPA: Lysophosphatidate; MDH1: Cytosolic malate deshydrogenase; MDH1: Cytosolic NADP-dependent malate dehydrogenase; PC: Pyruvate carboxylase; TAG: Triacylglycerol.

of fatty acids in muscle and, depending on the level of association between monomeric units of the hormone, influences insulin sensitivity of plasma glucose. Characterising the mechanisms of energy sensing is currently a vibrant field of study. Approaches to the problem include identification of metabolite--enzyme interactions that alter metabolic fluxes at key points [16]. Allosteric modulators that have so far been described are the interaction of palmitate with glucokinase and glycogen phosphorylase, which serve to inhibit the activity of these enzymes resulting in sparing carbohydrate breakdown in muscle tissue under conditions where fatty acids are abundantly taken up from the circulation [17]. Another feedback modulator is the effect of malonylCoA on the activity of the isoenzyme, carnitine palmitoyltransferase-1 located in the arcuate nucleus of the brain, which is believed to link ceramide metabolism to food intake [18]. This link is possibly mediated by the leptin

equivalent, ghrelin, produced in the stomach and pancreas [19]. Figure 1 shows a diagram of DNL pathways. The figure is aimed to show the four enzyme steps (indicated in bold italic letters) targeted by the main classes of antilipogenic drugs developed up until now, that is, carbonic anhydrases (CA), which produces bicarbonate, the co-substrate with acetylCoA of acetylCoA carboxylase (ACC). In turn, ACC produces malonylCoA, which supplies the fatty acid synthase (FAS) in the cytosol. In humans, palmitic acid (16:0) is virtually the only product released from FAS. It is secondarily elongated to stearic acid (18:0) and desaturated by stearoylCoA desaturase (SCD1 or D9-desaturase) to oleic acid (18:1n9). Noticeably, a number of by-products are also formed by DNL such as palmitoleic acids (16:1n7 and 16:1n9), vaccenic acid (18:1n7) and eicosatrienoic acids (20:3n7 and 20:3n9; so-called Mead fatty acid). In human tissues with an intense rate of DNL (liver, adipose


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tissue), the deleterious surfactant activity of abundant free fatty acids on membrane structure is prevented by their incorporation into triacylglycerols (TAG). Because of methodological limitations, fatty acids were long considered as the final products of DNL on the basis of gas chromatography of fatty acid methyl esters (GC of FAME). Indeed, TAG can now be regarded as the final DNL products after adoption of LC coupled with tandem MS (LCMS2) as the conventional lipidomics method.


3. Antitumour action of lipid synthesis inhibitors

The recent potential of DNL inhibitors as anticancer agents has highlighted the need for high-throughput screening of the large natural and chemical libraries available in industries. It appears that automated lipidomics methods based on MS can be an efficient alternative to the multistep procedures for assaying the incorporation of radiotracers into lipids. Perturbation of lipid metabolism is symptomatic of a proliferative state. Lipid disregulation generates products required for membrane biogenesis, energy metabolism and operation of signalling pathways that define the diverse aspects of carcinogenesis. Moreover, it is now well established from epidemiological studies that there is a direct link between obesity and the incidence of particular cancers (endometrial, post-menopausal breast, oesophageal and renal cell cancers) but not others (melanoma, ovarian, rectal) [20]. This indicates that in some cases there is a connection between the physiological adjustments associated with excessive weight gain and co-morbidities that this entails and pathogenicity of the cancerous condition. The physiological conditions associated with obesity including insulin resistance with the consequence of high insulin and IGF circulating levels, lipotoxicity-inducing inflammatory responses, generation of adipokines and stimulation of lipid signalling pathways all appear to be potential drivers of cancer pathogenesis [21,22]. It is questionable whether this epidemiological correlation could be explained by the disregulation of lipid metabolism evident at the cellular scale rather than at the level of the whole animal [20]. This would imply that numerous antilipogenic drugs and inhibitors of cholesterol biosynthesis [23-27] should also be evaluated as agents preventing carcinogenic transformation. One of the hallmarks of many cancers is an upregulation of anaerobic glycolysis as well as fatty acid synthesis, a conspicuous reliance on de novo synthesis for domestic consumption in poorly vascularised tumours [28]. This is consistent with the fact that inhibitors of FAS attenuate cell proliferation, tumourigenicity and malignancy [29]. Incorporation of exogenous fatty acids into cancer cells does not generally result in their oxidative metabolism. The energy supply is thought to be more dependent on anaerobic glycolysis but less dependent on fatty acid oxidation requiring delivery of oxygen to the mitochondria. Fatty acids are instead redirected into 822

structural and putatively signalling phospholipids, sphingolipids and ether lipids [30]. RNAi blockade of the fatty acid synthesis pathway in colon cancer cells results in cytotoxicity that is reversible by addition of exogenous fatty acids. At the cellular level, the fatty acid rescue strategy characterises small-molecule inhibitors of fatty acid synthesis [31]. Disregulation of membrane choline phosphatide metabolism in prostate cancer, indeed, has also been exploited to distinguish normal from cancerous tissue [32]. Fatty acid and phospholipid biosynthesis may provide opportunities for influencing cell progression because structural lipids are integral to the intrinsic pathway of apoptosis. This is not the case in malignant (and, incidentally foetal) cells, which can be selectively targeted by drugs that inhibit DNL, whereas non-malignant tissues are only moderately perturbed. It should be emphasised that cell cultures commonly serving as models to screen candidate drugs are generally deficient in lipids; their fatty acid requirements are not completely met by the limited amounts of lipid present in the bovine calf serum supplemented to the culture medium. This may result in a bias because cell lines are selected to thrive under conditions of restricted lipid supply. This pathway is regulated by the BCL-2 family of proteins the members of which are categorised according to their structure and particular function in the pathway. Antiapoptotic members include BCL-2 and BCL-Lx that share 3 -- 4 conserved BCL-2 homology domains, whereas BAX and BAK act as proapoptotic agents and share three homology domains. Another group of proapoptotic proteins, BH3, serve as stress sensors that transmit the apoptotic signals to the multidomain components according to whether they are organised to form activators of proapoptotic or deactivators of antiapoptotic members of the BCL-2 family. Lipids play a crucial role in two processes regulating the intrinsic pathway. First, early entry of BCL-2 across the outer mitochondrial membrane ultimately leads to cardiolipin migration to the mitochondrial surface triggering mitophagy [33]. Second, the collapse of phosphatidylserine asymmetry across the plasma membrane and its appearance on the cell surface acts as an ‘eat me’ signal for macrophages [34]. Modulation of biosynthesis of cardiolipin and phosphatidylserine so that they become more susceptible to oxidation could be a strategy for accelerating apoptosis in malignant cells. Secreted protein, acidic and rich in cysteine (SPARC) is an antiadhesive, matricellular protein associated with cellular morphogenesis, migration and proliferation. It can serve as an example (and encouragement) to decipher the complexity of antiobesity and anticancer mechanisms of drugs at the cellular level [35]. Evidence suggests that SPARC inhibits adipogenesis partly by perturbation of basement membrane formation and partly by suppression of the central transcriptional cascade of adipogenesis via the Wnt/b-catenin pathway. These effects are allied to the effect of SPARC on activating signalling pathways controlling cell adhesion, proliferation, migration, invasion and apoptosis. Thus, SPARC is associated



with an aggressive tumour phenotype in melanomas and gliomas while it acts as a tumour suppressor in neuroblastomas, ovarian and colorectal cancers [36]. Therapeutic strategies involve formulation of taxanes as complexes with albumin, such as nab-paclitaxel [37], to aid active transport across endothelial cells via the gp60/caveolin-1 receptor pathway where they bind to SPARC on stroma and tumour cells. The binding results in stromal depletion, increased tumour vascularisation and regression [38].

Potential of de novo lipogenesis inhibitors as anticancer drugs


4.

With the notable exception of a few specific tissues (liver, lactating breast, adipose tissue, sebaceous glands), the functional rate of DNL is negligible in normal well-nourished adults [39] who can fulfill their lipid requirement entirely by a sufficient nutritional uptake and the appropriate distribution via lipoproteins. This is not the case in malignant and foetal cells, which can be selectively targeted by drugs that inhibit DNL, whereas non-malignant tissues are only moderately perturbed. As malignant cells are dividing more rapidly than healthy cells, there is an increased demand for biosynthesis of the building blocks for new cells. It may be anticipated, therefore, that inhibitors of DNL will restrict the supply of phospholipids required for membrane biogenesis. Furthermore, because of frequently defective vasculature, malignant tumours have a reduced capacity to take up circulating lipoproteins and free fatty acids. Indeed, many details in the mechanism implying lipids and leading to cancer cell apoptosis are encompassed by this simple model of unbalanced requirements in the presence of inhibitors of DNL to cell apoptosis. Malignant cell metabolism is indeed characterised by an accelerated rate of DNL [40] along with a preference for anaerobic glycolysis (Warburg effect) [41] and intense glutamine hydrolysis [42]. In an aggressive breast cancer, for example, it is has been reported that DNL resulting in high SCD1 expression associated with shorter survival [43] accounts for up to 90% of the tumour lipids. Aggressive breast cancer is also associated with levels of ATP citrate lyase and FAS (Figure 1) many fold higher than in normal cells and benign tumours [44]. FAS is subject to regulation via several factors. Refeeding carbohydrate after a period of fasting represents ‘only’ the physiological model of stimulation of the FAS by the transcriptional factor SREBP-1c induced by increased insulin secretion [45,46]. The action of glucocorticosteroids as well as sex steroids on their corresponding target tissues similarly can accelerate DNL as does carbohydrate in the liver. By contrast, polyunsaturated fatty acids serve to reduce the response to SREBP-1c. The binding of SREBP-1C on the promoter of clustered DNL genes is normally initiated by activating one in two different cascades; the phosphoinositide 3 kinase/protein kinase B (AKT) [47] and MAPK/extracellular signal regulated

kinase 1/2 [48]. In cancer cells targeted by growth factors and steroids (estrogens, androgens or progesterone) alternative pathways can also be evoked through their receptors (GFR/ SHR) to activate the mammalian target of rapamycin (mTOR) signalling pathway. FAS expression in cancer cells can also be directly activated by the tumour microenvironment (hypoxia and acidosis generated by anaerobic glycolysis) through the upregulation of the hypoxia-inducible factor 1a inducing AKT activation [49]. Besides, SREBP-1c-specific factors are at work in the cancer cell to induce accelerated lipogenesis. For example, Sp1 transcription factor activates DNL and proliferation in cancer cells [50]. Pro-oncogenic mutant of p53 are defective in tumour suppression as well as in repression of expression of the malic enzymes ME1 and ME2 in human and mouse cells [51]. Malic enzyme is important for NADPH production, transfer of mitochondrial acetylCoA to cytosol (Figure 1) and glutamine metabolism, all being upregulated in malignancies.

Hormone-driven lipogenesis and propensity for malignant transformation

5.

Drug targeting of DNL appears to be a potential therapeutic method in some types of cancer cells. Many hormonedependent cancers including breast, ovarian and prostate cancers exhibit accelerated rates of DNL in response to hormone stimulation as indicated above for activation of the mTOR signalling pathway. The same non-malignant tissues do have functional requirements for DNL, but the rate remains under hormonal control. Hormone-dependent tissues with high rates of DNL include lactating mammary glands [52], the cycling endometrium [53] and seminal vesicles [54]. Androgens also stimulate sebaceous glands [55], and surfactant production by type II alveolar cells is controlled by the balance of glucosteroids and androgens [56]. As already noted, the control of food intake exercised by the hypothalamus is a particular hormone-driven factor in the anorectic influence of inhibitors of DNL [57]. In the hypothalamus, the anorectic influence of high malonylCoA induced by FAS inhibitors as well as high ketone bodies and acidosis above the blockade by ACC inhibitors add up to the deterioration of the nutritional status of patients. Overall, strategies involving manipulation of lipid metabolism as a means of drug targeting malignancies must be cognizant of the possible side effects on the whole animal. 6.

Drugs targeting lipid biosynthesis

We present in Table 1 some recent examples of inhibitors with a proven or prospective activity as anticancer drugs, which although initially conceived as metabolism modulators, may prove to be useful anticancer drugs. These are inhibitors of FAS, reviewed in Ref. [58], CA [59,60], ACC [61,62] and


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SCD [63]. The properties of a selection of these drugs are listed in Table 1, and the structures are shown in Figure 2.The inhibitor of FAS derived from tea polyphenolic catechins (epigallocatechin-3-gallate) is a naturally abundant but weak inhibitor of DNL present in black and green teas. It shows activity against HER2+ breast cancer xenografts [64]. The more efficient hemi-synthetic catechin G28UMC is active in antiHER2-resistant cell lines [65]. It inhibits FAS and leads to apoptosis of breast carcinoma cells with simultaneous expression of FAS and HER2 in culture and in xenograft. Unlike C75, G28UMC does not increase carnitine palmitoyl transferase 1 (CPT-1) activity and mitochondrial oxidation of fatty acids. Accelerated oxidation due to the reduced inhibition of CPT-1 induces lipolysis and weight loss by reducing the intracellular level of malonylCoA. Nonspecific inhibitors of ACC lower malonylCoA then, in turn, lipogenesis, which may find an efficacious use for treatment of obesity/diabetes [66]. A recent study of the bacterial polyketide inhibitor, soraphen A, illustrates the multiplicity of isoenzyme activities [67]. Although ACC ACC2 generates malonylCoA acting on the mitochondrial membrane to inhibit CPT-1, ACC1 generates malonylCoA as a co-substrate for DNL and elongation of palmitoylCoA in the cytosol. This results in a perturbation of the fatty acid profile with less elongation derived from exogenous fatty acids but increased polyunsaturated by-products. Inhibition by soraphen A of Elov6 and Elov5 activities, explains why 16:1 and 18:3n6, respectively, are derived abundantly from 16:0 and 18:2n6. Such alterations in the fatty acid profile have unpredictable consequences. Another side effect is the stimulation of cholesterol biosynthesis from accumulated acetylCoA. This effect is to be considered for long-term treatment with inhibitors of ACC such as in diabetes. Another side effect is increased synthesis of ketone bodies by the liver (acidosis caused by acetoacetate and b-hydroxybutyrate). In the context of low insulin secretion and high glucogenesis increasing further an already elevated ketone body synthesis and acidosis by inhibition of ACC may represent a limitation for diabetes. However, there is experience in the long term of tolerance of sustained levels of ketone bodies established from the treatment of epilepsy in children and adults [68,69]. It is even questionable whether inhibitors of ACC and AC can be useful to complement the positive influence of the diet and drugs for refractory epilepsy. GSK993 is a small molecule acting as a potent SCD1 inhibitor both in vivo and in various cellular assays. It has been profiled to analyse the positive impact of a selective SCD1 inhibition on lipid and glucose parameters [70]. In Zucker fa/fa rats, the SCD1 inhibitor exerted a marked reduction in hepatic lipids as well as a significant improvement in glucose tolerance. In a diet-induced insulin-resistant rat model, GSK993 induced a significant reduction in hepatic very-low-density lipoprotein-triglyceride production. Following a hyperinsulinaemic--euglycaemic clamp in GSK993treated animals, an improvement in the insulin sensitivity is reflected by an increase in the glucose infusion rate. The effect 824

was compared with other desaturase inhibitors such as conjugated linoleic acid (95% inhibition of D9-desaturase) while the D5 desaturation index was selectively inhibited by CP24879 (87% inhibition) (Figure 1). Only GSK993 induced a dose-dependent reduction in synthesis of triglycerides in the liver [71] and an even stronger depression of cholesteryl ester synthesis (oleoyl cholesterol is the major molecular species of cholesterol esters in rodent liver). Plasma triglycerides were found reduced (-33%) in treated animals. As compared with ACC inhibitors, ketone bodies were also significantly increased by GSK993 (b-hydroxybutyrate is inversely correlated with fatty acid synthesis in treated animals). Importantly, attention should be focused on the impact of SCD1 inhibition in the skin [72]. Atrophy of sebaceous and meibomian glands and disruption of the epidermal lipid barrier leading to uncontrolled trans-epidermal water loss were demonstrated in SCD1-deficient mice [73]. 7.

Targets of acetylCoA carboxylase in plants

In seeking compounds to control lipid biosynthesis, it is pertinent to look at strategies used to develop selective herbicides that target ACC in plants to see if lessons can be learnt in animal lipogenesis. As distinct from animals, plants possess two different isoforms of ACC, which share about 60% sequence homology, one located in the cytoplasm and the other in the chloroplast. In the chloroplast, ACC is primarily concerned with de novo fatty acid synthesis whilst the cytoplasmic enzyme additionally provides malonylCoA for elongation of long-chain fatty acids and synthesis of secondary metabolites such as flavonoids and suberins. In contrast to the cytoplasmic enzyme in which the four functional domains of the enzyme, biotin carboxyl-carrier protein, biotin carboxylase, a-carboxyltransferase and b-carboxyltransferase, are encoded in a single polypeptide [74], the structure of the chloroplast enzyme is homomeric in monocotyledons but heteromeric in most other plants in which the subunits of the functional enzyme are encoded by individual genes [75]. This difference has been exploited to develop herbicides that selectively target the homomeric enzyme of the monocotyledon chloroplast including the aryloxyphenoxypropionates, the cyclohexanediones and the more recent phenylpyrazolin class consisting of pinoxaden herbicide. The binding sites of these herbicides to the ACC have been determined and the relative inhibitory effects examined [76]. Over time, mutations of the homomeric ACC have given rise to resistant varieties even in polyploidy species where cumulative mutations are needed to manifest resistance [77]. 8.

Toxicology of inhibitors of lipogenesis

Monitoring the effects of inhibitors of DNL using serum markers is problematic. A frequent pitfall is to confuse their potency in tissues, that is, the inhibition of intracellular activities, which impact differently the various tissues, with the



3

2

Antifugal a.b. from Cephalosporium caerulens

Synthetic (Xenical)

Pancreatic lipase/covalent inhibitor of FAS thioesterase FAS

Balance of PP1 dephosphorylation (insulin)/DNA PK

Switch of adipocyte precursor from a fibronectin- into laminin-enriched EC matrix

PPARa, LXRa

PPARa, LXRa

Target receptor(s)

FAS promoter (-65 E box)

" SREBP1c " LXR " ABCA1-G1 " inflammation cytokines # SREBP1c # LXR # ABC-A1-G1 # inflammation cytokines

Target sequence

[94,95]

In vivo in vitro transcriptomic and proteomic human and model studies Various cells/ SCID mice

C acetate incorporation in FA and cholesterol

14

Immunoprecipitation transcriptomics/ phosphorylation of USF1/2H2O incorporation in FA High-resolution structure of enzyme drug complex/oxidation of NADPH at 340 nm/14 C acetate incorporation into total lipids in MCF-7 XRD (2.3-A˚resolution)

Candida stellatoidea/rat adipocytes/

Purified human FAS/cytotoxicity against cultured breast cancer cells/weight loss in Balb/C mice

[79]

Adipose/liver in LDLr-/atherosclerosis model mouse

Transcriptomics/ proteomics/activity

[98,101]

[108]

[116,118]

[97,99,110,111]

[89-91,102]

Metabolic syndrome patients/ healthy controls

Transcriptomics, in vivo reporter assay/proteolytic processing

Preadipocyte differentiation (Wnt/b-catenin pathway) chromatin

[63,88]

Ref.

Human circulating macrophages/ lymphocytes

Model

Transcriptomics

Methodology

*See Figure 2. ACC: AcetylCoA carboxylase; CA: Carbonic anhydrase; CLA: Conjugated linoleic acid; CPT: Carnitine palmitoyl transferase; DHA: Docosahexaenoic acid; EC: Extra-cellular; EPA: Eicosapentaenoic acid; FA: Fatty acid; FACS: Fluorescence activated cell sorting; FAS: Fatty acid synthase; LDLr: LDL receptor; LXR: Liver X receptor; MCF: Human breast cancer cells; MUFA: Monounsaturated fatty acid; PP1: Phosphoprotein phosphatase 1; SAT: Saturated; SCD1: StearoylCoA desaturase; SPARC: Secreted protein, acidic and rich in cysteines; SREBP: Sterol response element binding protein; TLM: Thiolactomycin; USF1: Upstream stimulatory factor 1.

2,3 Epoxy 4 oxo 7,10 dodecadienamide

Orlistat

Cerulenin

(Phosphorylated and acylated) upstream stimulatory factor 1 (USF1) TLM

DNA protein kinase inhibitors

Type II dissociated bacterial FA synthases/b-ketoacyl synthase domain of mammalian FAS type I

Nucleus

SPARC

Secreted protein, acidic and rich in cysteine

From antibiotics (Nocardia sp.)

FAS

Extra-cellular matrix

ASO anti-SCD1

Antisense oligonucleotide anti-SCD1

1

Adipogenesis

Bionutrients (from plant and marine oil)

Omega-3 FA (EPA, DHA)

Essential omega-3 FAs (dietary)

(5R)Thiolactomycin analogs

SCD1

Bionutrients

Target enzyme

SAT/MUFAs

Synthetic/ natural

SAT/MUFAs (dietary/ endogenous synthesis)

Structure (Figure 2)

Abbreviation

Inhibitor name

Table 1. Drugs targeting lipogenesis.



825

826

(+) C75-CoA

CLA

3-Carboxy-4-alkyl-2methylenebutyrolactone

CLA trans-10, cis-12


Diclofop

Aryloxyphenoxypropionate

11

10

9

8

7

6

5

4

Structure (Figure 2)

Synthetic (MerrelI RMI 14 514)

Synthetic (Pfizer Inc.)

Synthetic

Synthetic (Pfizer Inc.)

Sulfamate (and other sulfamides)

Oil from Sterculia foetida seeds

Biohydrogenation of linoleic acid in the rumen

Synthetic

Synthetic/ natural

AcetylCoA carboxylase (ACC)

ACC 1 and 2

ACC

ACC1 (liver), ACC2 (muscle)

Human mitochondrial CA VA and VB, cytosol CA II (CAs)

SCD (D9-desaturase)

FAS

CPT-1/anorectic (malonyl-CoA> hypothalamus)

Target enzyme

Interaction with catalytic Zn2+ center

Target receptor(s)

Target sequence

Plant growth/ in vitro radiolabelled acetate incorporation NaH[14C]O3 incorporation in malonylCoA (purified ACC1/2)/ 14 C-acetate to 14 C-lipids (rat liver) Incorporation of 3 H2O in FA, of 14 HCO3 in malonylCoA

Spectrofluorometry of dansylamides derivatives/ X-ray diffract/molecular dynamics

C-labelled glucose incorporation (±insulin)/ FAS mRNA FACS/adipocyte morphology/ SAT:MU FA GC analysis

14

Methodology

Isolated hepatocytes/ microsome preparations

Rat liver (in vivo)

Incorporation of [14C]bicarbonate/ high-throughput screening (microsome)/ respiratory quotient (rat) Wild oat/ grassy weeds

Nitrosomethylureainduced mammary tumour growth/ differentiating adipocytes Recombinant hCA II and recombinant full-length hCA VA

mammary cells/in vivo Mitochondrial extracts expressing rat CPT-1A/rat Pig adipose tissue explant cultures

Model

[112,122]

[107]

[76,77]

[61,62,66,121]

[106,114]

[92,93,120]

[103]

[18,119]

Ref.


5-(Tetradecyl Oxy) -2-furoic Acid

TOFA

CP-640186

N-Substituted bipiperidylcarboxamide

Spirocyclic pyrazolo lactam

TPM

Topiramate

Sterculic acid

Abbreviation

Inhibitor name

Table 1. Drugs targeting lipogenesis (continued).


A. Lamaziere et al.


16

PTM

EGCG

(-) C75

(±)-C75

Platensimycin (platenomycin)

Epigallocatechin3-gallate

3-Carboxy-4-alkyl-2methylenebutyrolactone

(±) 3-Carboxy-4-alkyl-2methylenebutyrolactone

Synthetic

Synthetic

Natural polyphenol

Streptomyces platensis (Merk)

Synthetic (Merck)

Synthetic (GSK)

Synthetic (Abbott)

Antifungal polyketide from Sorangium cellulosum (Myxobacteria)

Synthetic/ natural

Slow binding ‘irreversible’ inhibition of FAS/antitumor/anore ctic (neuropeptide Y)

FAS/antitumor

Gram(+) elongationcondensing enzyme FabF/liver FAS FASN (ketoacyl reductase)

FAS 1 (condensation)

SCD1

SCD1

ACC1/ ACC2 inhibition #malonylCoA #FAS #elongases ELOV5-6

Target enzyme

Target receptor(s)

Target sequence

C-labelled acetate incorporation in TAG and PL

14

Apoptosis mediated by free radical/ nanoparticles to prostate cancer cells

Malonyl-CoA (HPLC) and 14 C-labelled FA/recombinant enzyme overexpression Production of 3H2O from the desaturation of 3H (9,10) stearoyl-CoA D9-Desaturase (3H2O from deuterated stearate desaturation) or conversion of radioactive FA Production of free coenzyme A (CoA-SH) from malonyl- and acetyl-CoA # Liver triglyceride" insulin sensitivity

Methodology

[117]

Prostate cancer/ malignant lymphocyte B

Ref.

[125,126]

[119]

[124]

db/+ mice fed a high-fructose diet

Cytosolic hepatic extracts obtained from rat/cancer cell line Rat liver purified FAS/SKBR3 breast cancer cells

[123]

[70]

Microsomes/ Zucker rats

Rat and human purified FAS

[113]

[96]

Human recombinant SCD1

HepG2/ LnCap cells

Model


15

3-Aryl-4-hydroxyquinolin2(1H)-one

14

GSK993

GSK993

13

1-(4-Phenoxypiperidin1-yl)-2-arylaminoethanone

Structure (Figure 2) 12

Abbreviation

Soraphen A

Inhibitor name

Table 1. Drugs targeting lipogenesis (continued).



827

A. Lamaziere et al.

FAS inhibitors

CA and ACC inhibitors

SCD inhibitors O

O R1

N S

R2 O

O

CH3 O

O

O

O

O

O


F

8: CP-640186 (R/S) (bipiperidylcarboxamide)

7: Sulfamate topiramate (TPM) O

N Cl

O

O

N N NHH O

N

NH2

O

1: Thiolactone analogs (TLM)

F

13: 1(4-phenoxypiperidinyl)2-arylamino-ethanone (Abbott)

O N

NH O

HO

2: Orlistat (N-formyl-Leu, palmityl, hexanoyl groups)

N

O

H N O

NH O

N O

HN

Cl

3: Cerulenin (2,3 epoxy 4 oxo 7,10 dodecadienamide)

Cl

O

Cl O

O

N

O

H2N

C O N N

O O

O

N

N

9: Diclofop (aryloxyphenoxypropionate)

14: GSK993

10: Spirocyclic pyrazololactam (Pfizer) HO

O C O

FAS inhibitors

O

O O

H3C

4: Butyrolactone (+)-C75

O N

OH C N H

Cl HO

11: TOFA (tetradecyloxyfuran-carboxylic ring)

C

O

C H

15: 3-Aryl-4-hydroxyquinone (merck)

C H

5: Conjugated Linoleic(trans-10, cis-12 CLA) H3C

O

O O HO

O

C OH

6: Sterculic acid (cyclopropenyl ring)

O CH3

H3C H3C

O HO

O

HC

O CH3

12: Soraphen A

Figure 2. Structure of FAS inhibitors and inhibitors of acetylCoA carboxylase. FAS: Fatty acid synthase.


O O C O C2H5

OH OH

O

O

O

H3C O

H3C

HO

828

O

OH O H3C

16: Platenomycin (macrolide)



consequences on serum lipids assessed by the routine tests, which reflects mostly the liver condition. The level of circulating triglycerides and cholesterol are not only influenced by the rate of synthesis in the liver but also largely dependent on their incorporation into apolipoproteins for secretion into the serum. Thereafter, the clearance of serum lipids relies on receptor-mediated lipoprotein uptake dependent on apolipoprotein interaction with specific receptors. All subsequent steps blur the relevant information, which is the correlation of lipid levels with beneficial and toxic effects. An exception among lipids is serum-free fatty acids taken up directly into peripheral cells by fatty acid transporters [78]. A clear example of dissociation between intracellular and serum activity is observed when SCD1 activity is reduced by antisense oligonucleotide-relieving insulin resistance and obesity but strongly promoting atherosclerosis in a mouse model of hyperlipidaemia and atherosclerosis (LDLr-/- Apob (100/100)). Accelerated atherosclerosis in this instance was correlated with an accumulation of saturated fatty acids above the SCD1 enzyme blockade, which has promoted inflammation through the toll-like receptor 4 [79].

Potential medical application of DNL inhibitors

9.

It may seem surprising that with such promising drugs with potential to control widespread conditions like diabetes, metabolic syndrome and as an adjuvant in different forms of cancer that introduction into clinical practice is so tardy. It is known that a series of synthetic and semisynthetic compounds have been trialed by pharmaceutical companies with interesting effects, but these are as yet a long way from commercialisation. One particular factor that must be addressed in clinical use of antilipogenics is the duration of therapy. Efficacious treatment of metabolic disorders such as obesity and metabolic syndrome needs to be evaluated against undesirable side effects that develop over time. This contrasts with anticancer therapies for aggressive hormone-dependent malignancies where antilipogenic drugs are administered for limited periods initially to check local progression of the primary tumour and metastases. These scenarios illustrate how evaluation of therapeutic indices has to be finely balanced. This is where new lipidomics methods can also be useful; the method is able to assay the lipidome in small tissue and tumourous samples from which the therapeutic index of candidates can be assessed. Moreover, most of the LCMS2 procedure (including lipid extraction) can be automated so that lipid profiling demands considerably less manpower than radiotracer incorporation procedures. 10. Examining the lipidome to assess drug candidates

Commonly, both in vitro and in vivo studies of DNL inhibitor activities are performed by incubating cells or administrating

rodents by oral gavage with 14C or 13C-labelled precursors such as 14C-glucose, 14C-acetate, NaH[14C]O3, 2H2O, 3H2O and 3H stearoylCoA (Table 1). The radioactivity recovered in lipid products is subsequently determined by scintillation counting. A stable isotope method used for quantitation of fatty acids has been detailed by Emken [80]. Using this methodology, analyses require a laborious protocol that may involve multiple time-consuming steps of lipid extraction/purification before final quantification of radioisotope incorporation by scintillation counting. Moreover, the use of 14C has become increasingly problematic with onerous radioisotope compliance regulations and good laboratory practices associated with using radioisotopes within protected environment. Stable isotope methodology using deuterated water (2H2O) is also available for labelling either fatty acids (endogenously synthesised) or the glycerol moiety in TAG. Thus, it is possible to discriminate between products of glycolytic and glyceroneogenic origin. The number of hydrogen atoms (n) incorporated from deuterated water into C--H bonds reflects the metabolic source under different conditions in rodents [81]. Adipose tissue acylglyceride glycerol in mice fed a restricted carbohydrate diet had significantly higher values of n than in mice fed a highcarbohydrate diet, suggesting that there is an increased contribution from glyceroneogenesis. Similarly, mice administered rosiglitazone had a significant relative increase in glyceroneogenesis. Another stable isotope methodology has also been described [82]. This method is safe and relatively easy to implement for DNL assessments in vivo in humans using heavy water (2H2O) as well as animals over prolonged periods. Nevertheless, it is still a time-consuming and a costly procedure; in humans, 1 -- 2 months of consumption of 70 ml of 2H2O per day is required to reach the isotopic dilution equilibrium. The advantages of this time-kinetic method must also be judged against model-independent biochemical methods such as lipidomics. Current advances in MS have made possible the highthroughput analysis of lipid metabolism, and particularly DNL. Two analytical strategies with different coupling exist in most specialised laboratories (GC-MS and LC-MS/MS) [83]. The separation of lipid classes by chromatography (HPLC, TLC, SPE) followed by determination of the fatty acid composition by GCMS as methyl esters (FAME) is a tedious but quantitative procedure. The result is the ‘total lipid class’ fatty acid composition (i.e., the fatty acid composition of a ‘total lipid class’ such as cholesterol esters, phosphatidylcholines and triglycerides). The method is not able to characterise specific molecular species of lipid except for cholesterol esters having a single acyl chain. Phospholipids and triglyceride structure with two and three acyls cannot be assigned, which prevents identification of any particular lipid species marking a specific condition. Tandem MS (MS2 and MS3) is capable of assaying discrete molecular species that can be selected as a metabolic marker after preliminary studies [84]. For an example, while palmitoyldioleyl TG (TG 52:02) is a marker for intense DNL in HepG2 culture, the palmitic acid molecular species is common


829


A. Lamaziere et al.

in most other cultured cells. The recent technological advances, leading to greater sensitivity, yield comprehensive structural information of complex lipidomes from impressively small tissue samples. Tandem mass spectrometry (LCMS2) is able to quantitate > 300 lipid species in the same chromatographic run from a single lipid extract. The acquisition rate of MS3 has also made progress but remains much slower than MS2 equipment. Soon it is expected that technological advances will allow an acquisition frequency fast enough to record a comprehensive scan of the whole lipidome during a single chromatography run. Because of the complexity of lipid metabolism, it is necessary to account for an extensive number of individual molecular species of lipid to obtain an accurate picture of changes in response to pharmaceutical agents. Therefore, despite some analytical obstacles such as the difficulty of isomeric resolution and the paucity of individual calibration standards to determine the response coefficient of each molecular species), MS appears to be a technique of choice to study the regulation of DNL. As an example, Cao et al. identified the DNL marker, palmitoleate (C16:1n-7) as the so-called ‘lipokine’ signal that mediated a protective effect leading to suppressed hepatic steatosis and improved muscle insulin resistance [85]. Using an LC-MS2 strategy, the change following incorporation of long-chain omega-3 docosahexaenoic (DHA; 22:6n-3) and eicosapentaenoic (EPA; 20:5n-3) fatty acids into hepatic lipids was investigated after feeding rats with fish oil. The results showed that long-chain omega-3 fatty acids inhibit DNL and change the hepatic fatty acid profile via reduced desaturase activity in the non-steatotic liver [86]. This approach paves the way for the study of pharmacological agents on lipogenesis in screening drug candidates [1]. An illustration of the analytical methods employed in candidate drug screening is shown in Figure 3. It points out how the difficulties of quantitation indicated above for processing large data batches generated by LCMS2 scanning of triglycerides could be circumvented by a multivariate analysis. Statistics are often seen as confusing and complex. However, multivariate data analysis (MVA) can be achieved to amass knowledge easily. Multivariate statistical procedures such as ‘Principle Component Analysis’ (PCA) provide an insight into correlations between the variations of lipid components of the lipidome (but not their amounts). The great advantage of MVA is that from dull dataset tables, simple 2D plots can give rise to cause and effect relationships and the corresponding statistics are straightforward. Indeed, MVA converts data into knowledge without narrowing down solely on allegedly unknown aspects and the representation of this knowledge can be displayed visually. Besides, in pharmaceutical production, a typical multivariate environment, this statistical approach has been used extensively in the past decade to improve and assure quality (ICH Q8 and Q10 guidelines on pharmaceutical development and pharmaceutical quality system). Our strategy is to transpose this well-recognised industrial methodology to drug selection/discovery applications. 830

The method gives a measure of the relative changes in a lipid profile. Because of the large number of individual species comprised in LCMS2 profiles, the method regroups co-variables (i.e., molecular species) into linear combinations. A few combinations assemble the species varying parallel (correlated) into a few ‘principle components’. This results in a reduction of the data dimension because two or three independent components from amongst hundreds of molecular species can be identified in most lipid classes from which a clear picture of the total variability of a lipid class can be achieved. In practice, a factorial plan reflecting > 50% of the total variability is sufficient to detect the influence of DNL inhibitors. PCA ‘load plot’ (Figure 3, panel A) gives the picture of separation between the variables (i.e., the molecular species) varying parallel (correlated) and species varying in the opposite direction. In a ‘load plot’, the correlated molecular species are projected in the same area, whereas the variables varying in the opposite direction point to the diametrically opposite quadrant. The PCA ‘score plot’ (Figure 3, panel B) illustrates the separation between observations (i.e., between samples) along the same ‘principle components’. The superimposition of the ‘load plot’ (i.e., the molecular species variations) over the ‘score plot’ (i.e., the samples) reveals, by a simple visual inspection, the variability of many lipid species in a range of samples. The inspection identifies the appropriate molecular species to differentiate the samples, which are the marker lipids. Furthermore, other statistical methods out of the scope of this review, such as discriminant analysis, confirm the choice of lipid markers. Finally, a model for the variation of the marker lipids as a function of the treatment and dose is obtained by various regression statistical procedures. In Figure 3, a principal component analysis of MS data recorded from serum lipid extracts (load plot, panel A and score plot, panel B) shows the correlation for serum TAGs in mice treated with different pharmacological agents impacting lipid metabolism in various directions. The control (label A) is compared with a peroxisome proliferator-activated receptor agonist (label B) or an inhibitor of a fatty acidbinding protein (label C). The three groups separate in the score plot corresponding to the factorial plan F1-F2. The plan formed with these two first components comprises 68% of the total variability for serum TAGs. The separation results from the different number of double bonds and different length of the acyl chains in TAGs. Incidentally, while the PPAR agonist and the control group TAGs are enriched in monounsaturated fatty acid species derived from DNL, the FABP inhibitor group (label C) TAGs are enriched in polyunsaturated fatty acids (6 -- 12 double bonds per TG molecule) but low in TAG with < 4 double bonds assigned to DNL products. The total lipid fatty acids, which were obtained independently by GC-MS were found to vary similarly with triglycerides. Noticeably, the separation of group scores based on LC-MS-MS analysis of triglycerides reaches higher significance with statistical tests.



Variables (axes F1 and F2: 68.6%)

Observations (axes F1 and F2: 68.6%) 5

TG 1-4 DB

1

TG52:02 TG50:01 TG54:02

0.75

C A

TG52:03


TG 6-12 DB TG60:12 TG56:07

TG50:02

0.25

TG58:10

0

TG56:08 TG60:11 TG56:09 TG58:09

TG52:04 TG54:03

-0.25

TG54:05 TG54:04

-0.5

TG52:05

TG50:03 TG48:02 TG50:04

F2 (19.44%)

F2 (19.44%)

0.5

A A

A

C

AA A A A A A A

0

C C

C

C C C C

B

TG58:08 TG54:06 TG56:06 TG54:07

B

B

B

B

B

BB

-0.75

TG52:06

TG 2-6 DB -1

-0.75 -0.5 -0.25 0 0.25 F1 (49.17%)

B

-5

-1 0.5

0.75

-10

1

-5

0

5

10

F1 (49.17%)

Figure 3. Principal component analysis of mass spectrometry profiles from serum triglycerides in treated mice (n = 27). The groups are treated with two different pharmacological agents and are compared with a control group. Score and loading plots (see text) (panel A and B) reflect the variability of TAG profiles scanned by LC-MS2. Labels identified as A, B, C indicate the treatment, control, peroxisome proliferator-activated receptor agonist and inhibitor of a fatty acid binding protein, respectively. The factorial plan (the two first principal components F1/F2) comprises 68.82% of the total variability of triglycerides in the three groups. LC-MS2: LC coupled with tandem MS; TAG: Triacylglycerol.

11.

Conclusions

A large variety of compounds are known to inhibit de novo lipid synthesis. Blockades can be achieved at the level of malonylCoA (inhibition of ACC and CAs), FAS (inhibition of the condensing and thioesterase subunit) and D9-desaturase (inhibition of the conversion to monounsaturated fatty acids). The consequences of inhibition depend on how the biosynthetic pathway deviates above the blockade. These include accelerated mitochondrial fatty acid oxidation, accumulation of ketone bodies and increased cholesterol synthesis. Flux through the respective pathways can be accurately monitored by interrogation of the lipidome using automated MS methods. The administration of candidate drugs in animal models can result in decreases in the adipose deposit, induction of an anorectic effect and improvement in insulin resistance associated with metabolic syndrome. Side effects such as anorexia and skin defects related to lowered sebaceous production may decrease the therapeutic index to a critical level in the long-term. A major new interest in inhibitors of DNL is their proapoptotic effects observed in cancerous cells that require abundant membrane lipid substrates for proliferation. Aggressive hormone-dependent malignancies developed from tissues

with a normal functional lipogenesis such as breast and prostate cancers are particularly sensitive to these inhibitors. It is anticipated that new drug formulations will be introduced to target lipid metabolism in cancer cell lines in the development of novel therapies for these diseases. 12.

Expert opinion

A number of efficient inhibitors of DNL have been characterised. The principle targets of inhibitors are CA, ACC, FAS and Stearoyl CoA Dehydrogenase I (CA, ACC, FAS and SCD1). Analysis of lipid structure by LCMS2 identifies changes in ‘molecular species’, that is, the change in the fatty acid composition in each of the lipid classes resulting from inhibition of DNL. Technical and methodological limitations, such as ambiguities associated with diglyceride fragment-ion structure and quantitation errors due to the lack of available calibration standards, have mandated a complementary approach in combination with LCMS2 for the practical purposes of drug screening. In the Method Section, we illustrate how a multivariate analysis can be employed to evaluate LCMS2 data. By this means, a statistical investigation of lipidomic profiles is able to avoid difficulties in quantifying individual molecular


831


A. Lamaziere et al.

species. Lipidomic profiles corresponding to the magnitude of rates of lipid synthesis are evaluated using the statistical procedure from which specific markers can be identified to monitor the influence of inhibitors. LCMS2 is widely available in most laboratories and can be automated. The screening of subtle variations in lipid profiles resulting from inhibition of DNL by candidate drugs is facilitated by a combination of automated LCMS2 combined with multivariate statistical analysis procedures. Screening of DNL inhibitors with radiotracer precursors incorporated into lipids has been a common approach until now. It is an expensive and time-consuming method (for the cost of radioactive or stable precursors in vivo, the lipid separation and assay…) as compared with automated LCMS2 lipidomics. Profiling of molecular species within a lipid class such as TAG, DG and CE in normal tissue and tumour should be used for a rapid evaluation of dose-effect and toxicology of antitumour candidate drugs. Toxicity has previously hampered the development of more DNL inhibitors. In their indication as antitumour drugs the therapeutic index of inhibitors should be reevaluated with short and intensive dose regimens. Structure--activity relationships have identified efficient compounds trialled in tissue cell cultures and animal studies including xenografts. Furthermore, rescue administration of exogenous fatty acids can be envisioned. This could be accompanied by lipidomic investigation to assay efficacy and followup of trials, while quantitative assay requires radiolabelled lipid precursors, which are impracticable in clinical situations. A critical factor in these evaluations is the monitoring of efficacy alongside undesirable side effects of these drugs. For example, complete teratogenesis is needed where these agents are expected to be toxic for foetal tissues as in the case of inhibitors of cholesterol synthesis [87]. Caution must be exercised in using cultured cells or laboratory animals in screening drug candidates because these models are frequently deficient in lipid supplies, and their baseline rate of de novo lipogenesis is not representative of common clinical conditions. Thus Bibliography Papers of special note have been highlighted as either of interest () or of considerable interest () to readers. 1.

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Declaration of interest The authors are supported by INSERM, Paris VI University and Kings College, London. C Wolf is the CEO-founder of APLIPID Sarl and owns shares in the company. A Lamaziere has also participated in studies conducted for APLIPID Sarl. The authors have no other relevant affiliations or financial involvement with any organisation or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

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Affiliation Antonin Lamaziere1, Claude Wolf2 & Peter J Quinn†3 † Author for correspondence 1 Sorbonne Universite´s -- UPMC Univ Paris 06, INSERM ERL, 1157, CNRS UMR 7203 LBM, CHU Saint-Antoine 27 rue de Chaligny, F-75012, Paris, France 2 Applied Lipid Investigations, APLIPID Sarl, Paris 75116, France 3 King’s College London, Department of Biochemistry, 150 Stamford Street, London SE1 9NH, UK Tel: +44 2078484408; E-mail: [email protected]

Notice of correction Please note that changes were made in first paragraph of section 4 and figure 2 was corrected after initial online publication of this article (12th May 2014).

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