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Warburg Effect and Mitochondrial Regulation -2.1.3

Writer and Curator: Larry H Bernstein, MD, FCAP 

2.1.3 Warburg Effect and Mitochondrial Regulation

Warburg Effect and Mitochondrial Regulation- 2.1.3

Word Cloud by Daniel Menzin

2.1.3.1 Regulation of Substrate Utilization by the Mitochondrial Pyruvate Carrier

NM Vacanti, AS Divakaruni, CR Green, SJ Parker, RR Henry, TP Ciaraldi, et a..
Molec Cell 6 Nov 2014; 56(3):425–435
http://dx.doi.org/10.1016/j.molcel.2014.09.024

Highlights

  • Oxidation of fatty acids and amino acids is increased upon MPC inhibition
    •Respiration, proliferation, and biosynthesis are maintained when MPC is inhibited
    •Glutaminolytic flux supports lipogenesis in the absence of MPC
    •MPC inhibition is distinct from hypoxia or complex I inhibition

Summary

Pyruvate lies at a central biochemical node connecting carbohydrate, amino acid, and fatty acid metabolism, and the regulation of pyruvate flux into mitochondria represents a critical step in intermediary metabolism impacting numerous diseases. To characterize changes in mitochondrial substrate utilization in the context of compromised mitochondrial pyruvate transport, we applied 13C metabolic flux analysis (MFA) to cells after transcriptional or pharmacological inhibition of the mitochondrial pyruvate carrier (MPC). Despite profound suppression of both glucose and pyruvate oxidation, cell growth, oxygen consumption, and tricarboxylic acid (TCA) metabolism were surprisingly maintained. Oxidative TCA flux was achieved through enhanced reliance on glutaminolysis through malic enzyme and pyruvate dehydrogenase (PDH) as well as fatty acid and branched-chain amino acid oxidation. Thus, in contrast to inhibition of complex I or PDH, suppression of pyruvate transport induces a form of metabolic flexibility associated with the use of lipids and amino acids as catabolic and anabolic fuels.

oxidation-of-fatty-acids-and-amino-acid

oxidation-of-fatty-acids-and-amino-acids

Graphical Abstract – Oxidation of fatty acids and amino acids is increased upon MPC inhibition

Figure 2. MPC Regulates Mitochondrial Substrate Utilization (A) Citrate mass isotopomer distribution (MID) resulting from culture with [U-13C6]glucose (UGlc). (B) Percentage of 13C-labeled metabolites from UGlc. (C) Percentage of fully labeled lactate, pyruvate, and alanine from UGlc. (D) Serine MID resulting from culture with UGlc. (E) Percentage of fully labeled metabolites derived from [U-13C5]glutamine (UGln). (F) Schematic of UGln labeling of carbon atoms in TCA cycle intermediates arising via glutaminoloysis and reductive carboxylation. Mitochondrion schematic inspired by Lewis et al. (2014). (G and H) Citrate (G) and alanine (H) MIDs resulting from culture with UGln. (I) Maximal oxygen consumption rates with or without 3 mM BPTES in medium supplemented with 1 mM pyruvate. (J) Percentage of newly synthesized palmitate as determined by ISA. (K) Contribution of UGln and UGlc to lipogenic AcCoA as determined by ISA. (L) Contribution of glutamine to lipogenic AcCoA via glutaminolysis (ISA using a [3-13C] glutamine [3Gln]) and reductive carboxylation (ISA using a [5-13C]glutamine [5Gln]) under normoxia and hypoxia. (M) Citrate MID resulting from culture with 3Gln. (N) Contribution of UGln and exogenous [3-13C] pyruvate (3Pyr) to lipogenic AcCoA. 2KD+Pyr refers to Mpc2KD cells cultured with 10 mM extracellular pyruvate. Error bars represent SD (A–E, G, H, and M), SEM(I), or 95% confidence intervals(J–L, and N).*p<0.05,**p<0.01,and ***p<0.001 by ANOVA with Dunnett’s post hoc test (A–E and G–I) or * indicates significance by non-overlapping 95% confidence intervals (J–L and N).

Figure 3. Mpc Knockdown Increases Fatty Acid Oxidation. (A) Schematic of changes in flux through metabolic pathways in Mpc2KD relative to control cells. (B) Citrate MID resulting from culture with [U-13C16] palmitate conjugated to BSA (UPalm). (C) Percentage of 13C enrichment resulting from culture with UPalm. (D) ATP-linked and maximal oxygen consumption rate, with or without 20m Metomoxir, with or without 3 mM BPTES. Culture medium supplemented with 0.5 mM carnitine. Error bars represent SD (B and C) or SEM (D). *p < 0.05, **p < 0.01, and ***p < 0.001 by two-tailed, equal variance, Student’s t test(B–D), or by ANOVA with Dunnett’s post hoc test (D).

Figure 4. Metabolic Reprogramming Resulting from Pharmacological Mpc Inhibition Is Distinct from Hypoxia or Complex I Inhibition

2.1.3.2 Oxidation of Alpha-Ketoglutarate Is Required for Reductive Carboxylation in Cancer Cells with Mitochondrial Defects

AR Mullen, Z Hu, X Shi, L Jiang, …, WM Linehan, NS Chandel, RJ DeBerardinis
Cell Reports 12 Jun 2014; 7(5):1679–1690
http://dx.doi.org/10.1016/j.celrep.2014.04.037

Highlights

  • Cells with mitochondrial defects use bidirectional metabolism of the TCA cycle
    •Glutamine supplies the succinate pool through oxidative and reductive metabolism
    •Oxidative TCA cycle metabolism is required for reductive citrate formation
    •Oxidative metabolism produces reducing equivalents for reductive carboxylation

Summary

Mammalian cells generate citrate by decarboxylating pyruvate in the mitochondria to supply the tricarboxylic acid (TCA) cycle. In contrast, hypoxia and other impairments of mitochondrial function induce an alternative pathway that produces citrate by reductively carboxylating α-ketoglutarate (AKG) via NADPH-dependent isocitrate dehydrogenase (IDH). It is unknown how cells generate reducing equivalents necessary to supply reductive carboxylation in the setting of mitochondrial impairment. Here, we identified shared metabolic features in cells using reductive carboxylation. Paradoxically, reductive carboxylation was accompanied by concomitant AKG oxidation in the TCA cycle. Inhibiting AKG oxidation decreased reducing equivalent availability and suppressed reductive carboxylation. Interrupting transfer of reducing equivalents from NADH to NADPH by nicotinamide nucleotide transhydrogenase increased NADH abundance and decreased NADPH abundance while suppressing reductive carboxylation. The data demonstrate that reductive carboxylation requires bidirectional AKG metabolism along oxidative and reductive pathways, with the oxidative pathway producing reducing equivalents used to operate IDH in reverse.

Proliferating cells support their growth by converting abundant extracellular nutrients like glucose and glutamine into precursors for macromolecular biosynthesis. A continuous supply of metabolic intermediates from the tricarboxylic acid (TCA) cycle is essential for cell growth, because many of these intermediates feed biosynthetic pathways to produce lipids, proteins and nucleic acids (Deberardinis et al., 2008). This underscores the dual roles of the TCA cycle for cell growth: it generates reducing equivalents for oxidative phosphorylation by the electron transport chain (ETC), while also serving as a hub for precursor production. During rapid growth, the TCA cycle is characterized by large influxes of carbon at positions other than acetyl-CoA, enabling the cycle to remain full even as intermediates are withdrawn for biosynthesis. Cultured cancer cells usually display persistence of TCA cycle activity despite robust aerobic glycolysis, and often require mitochondrial catabolism of glutamine to the TCA cycle intermediate AKG to maintain rapid rates of proliferation (Icard et al., 2012Hiller and Metallo, 2013).

Some cancer cells contain severe, fixed defects in oxidative metabolism caused by mutations in the TCA cycle or the ETC. These include mutations in fumarate hydratase (FH) in renal cell carcinoma and components of the succinate dehydrogenase (SDH) complex in pheochromocytoma, paraganglioma, and gastrointestinal stromal tumors (Tomlinson et al., 2002Astuti et al., 2001Baysal et al., 2000Killian et al., 2013Niemann and Muller, 2000). All of these mutations alter oxidative metabolism of glutamine in the TCA cycle. Recently, analysis of cells containing mutations in FH, ETC Complexes I or III, or exposed to the ETC inhibitors metformin and rotenone or the ATP synthase inhibitor oligomycin revealed that turnover of TCA cycle intermediates was maintained in all cases (Mullen et al., 2012). However, the cycle operated in an unusual fashion characterized by conversion of glutamine-derived AKG to isocitrate through a reductive carboxylation reaction catalyzed by NADP+/NADPH-dependent isoforms of isocitrate dehydrogenase (IDH). As a result, a large fraction of the citrate pool carried five glutamine-derived carbons. Citrate could be cleaved to produce acetyl-CoA to supply fatty acid biosynthesis, and oxaloacetate (OAA) to supply pools of other TCA cycle intermediates. Thus, reductive carboxylation enables biosynthesis by enabling cells with impaired mitochondrial metabolism to maintain pools of biosynthetic precursors that would normally be supplied by oxidative metabolism. Reductive carboxylation is also induced by hypoxia and by pseudo-hypoxic states caused by mutations in the von Hippel-Lindau (VHL) tumor suppressor gene (Metallo et al., 2012Wise et al., 2011).

Interest in reductive carboxylation stems in part from the possibility that inhibiting the pathway might induce selective growth suppression in tumor cells subjected to hypoxia or containing mutations that prevent them from engaging in maximal oxidative metabolism. Hence, several recent studies have sought to understand the mechanisms by which this pathway operates. In vitro studies of IDH1 indicate that a high ratio of NADPH/NADP+ and low citrate concentration activate the reductive carboxylation reaction (Leonardi et al., 2012). This is supported by data demonstrating that reductive carboxylation in VHL-deficient renal carcinoma cells is associated with a low concentration of citrate and a reduced ratio of citrate:AKG, suggesting that mass action can be a driving force to determine IDH directionality (Gameiro et al., 2013b). Moreover, interrupting the supply of mitochondrial NADPH by silencing the nicotinamide nucleotide transhydrogenase (NNT) suppresses reductive carboxylation (Gameiro et al., 2013a). This mitochondrial transmembrane protein catalyzes the transfer of a hydride ion from NADH to NADP+ to generate NAD+ and NADPH. Together, these observations suggest that reductive carboxylation is modulated in part through the mitochondrial redox state and the balance of substrate/products.

Here we used metabolomics and stable isotope tracing to better understand overall metabolic states associated with reductive carboxylation in cells with defective mitochondrial metabolism, and to identify sources of mitochondrial reducing equivalents necessary to induce the reaction. We identified high levels of succinate in some cells using reductive carboxylation, and determined that most of this succinate was formed through persistent oxidative metabolism of AKG. Silencing this oxidative flux by depleting the mitochondrial enzyme AKG dehydrogenase substantially altered the cellular redox state and suppressed reductive carboxylation. The data demonstrate that bidirectional/branched AKG metabolism occurs during reductive carboxylation in cells with mitochondrial defects, with oxidative metabolism producing reducing equivalents to supply reductive metabolism.

Shared metabolomic features among cell lines with cytb or FH mutations

To identify conserved metabolic features associated with reductive carboxylation in cells harboring defective mitochondrial metabolism, we analyzed metabolite abundance in isogenic pairs of cell lines in which one member displayed substantial reductive carboxylation and the other did not. We used a pair of previously described cybrids derived from 143B osteosarcoma cells, in which one cell line contained wild-type mitochondrial DNA (143Bwt) and the other contained a mutation in the cytb gene (143Bcytb), severely reducing complex III function (Rana et al., 2000Weinberg et al., 2010). The 143Bwt cells primarily use oxidative metabolism to supply the citrate pool while the 143Bcytb cells use reductive carboxylation (Mullen et al., 2012). The other pair, derived from FH-deficient UOK262 renal carcinoma cells, contained either an empty vector control (UOK262EV) or a stably re-expressed wild-type FH allele (UOK262FH). Metabolites were extracted from all four cell lines and analyzed by triple-quadrupole mass spectrometry. We first performed a quantitative analysis to determine the abundance of AKG and citrate in the four cell lines. Both 143Bcytb and UOK262EV cells had less citrate, more AKG, and lower citrate:AKG ratios than their oxidative partners (Fig. S1A-C), consistent with findings from VHL-deficient renal carcinoma cells (Gameiro et al., 2013b).

Next, to identify other perturbations, we profiled the relative abundance of more than 90 metabolites from glycolysis, the pentose phosphate pathway, one-carbon/nucleotide metabolism, the TCA cycle, amino acid degradation, and other pathways (Tables S1 and S2). Each metabolite was normalized to protein content, and relative abundance was determined between cell lines from each pair. Hierarchical clustering (Fig 1A) and principal component analysis (Fig 1B) revealed far greater metabolomic similarities between the members of each pair than between the two cell lines using reductive carboxylation. Only three metabolites displayed highly significant (p<0.005) differences in abundance between the two members of both pairs, and in all three cases the direction of the difference (i.e. higher or lower) was shared in the two cell lines using reductive carboxylation. Proline, a nonessential amino acid derived from glutamine in an NADPH-dependent biosynthetic pathway, was depleted in 143Bcytb and UOK262EV cells (Fig. 1C). 2-hydroxyglutarate (2HG), the reduced form of AKG, was elevated in 143Bcytb and UOK262EV cells (Fig. 1D), and further analysis revealed that while both the L- and D-enantiomers of this metabolite were increased, L-2HG was quantitatively the predominant enantiomer (Fig. S1D). It is likely that 2HG accumulation was related to the reduced redox ratio associated with cytb and FH mutations. Although the sources of 2HG are still under investigation, promiscuous activity of the TCA cycle enzyme malate dehydrogenase produces L-2HG in an NADH-dependent manner (Rzem et al., 2007). Both enantiomers are oxidized to AKG by dehydrogenases (L-2HG dehydrogenase and D-2HG dehydrogenase). It is therefore likely that elevated 2-HG is a consequence of a reduced NAD+/NADH ratio. Consistent with this model, inborn errors of the ETC result in 2-HG accumulation (Reinecke et al., 2011). Exposure to hypoxia (<1% O2) has also been demonstrated to reduce the cellular NAD+/NADH ratio (Santidrian et al., 2013) and to favor modest 2HG accumulation in cultured cells (Wise et al., 2011), although these levels were below those noted in gliomas expressing 2HG-producing mutant alleles of isocitrate dehydrogenase-1 or -2 (Dang et al., 2009).

Figure 1 Metabolomic features of cells using reductive carboxylation

 

Finally, the TCA cycle intermediate succinate was markedly elevated in both cell lines (Fig. 1E). We tested additional factors previously reported to stimulate reductive AKG metabolism, including a genetic defect in ETC Complex I, exposure to hypoxia, and chemical inhibitors of the ETC (Mullen et al., 2012Wise et al., 2011Metallo et al., 2012). These factors had a variable effect on succinate, with impairments of Complex III or IV strongly inducing succinate accumulation, while impairments of Complex I either had little effect or suppressed succinate (Fig. 1F).

Oxidative glutamine metabolism is the primary route of succinate formation

UOK262EV cells lack FH activity and accumulate large amounts of fumarate (Frezza et al., 2011); elevated succinate was therefore not surprising in these cells, because succinate precedes fumarate by one reaction in the TCA cycle. On the other hand, TCA cycle perturbation in 143Bcytb cells results from primary ETC dysfunction, and reductive carboxylation is postulated to be a consequence of accumulated AKG (Anastasiou and Cantley, 2012Fendt et al., 2013). Accumulation of AKG is not predicted to result in elevated succinate. We previously reported that 143Bcytb cells produce succinate through simultaneous oxidative and reductive glutamine metabolism (Mullen et al., 2012). To determine the relative contributions of these two pathways, we cultured 143Bwt and 143Bcytb with [U-13C]glutamine and monitored time-dependent 13C incorporation in succinate and other TCA cycle intermediates. Oxidative metabolism of glutamine generates succinate, fumarate and malate containing four glutamine-derived 13C nuclei on the first turn of the cycle (m+4), while reductive metabolism results in the incorporation of three 13C nuclei in these intermediates (Fig. S2). As expected, oxidative glutamine metabolism was the predominant source of succinate, fumarate and malate in 143Bwt cells (Fig. 2A-C). In 143Bcytb, fumarate and malate were produced primarily through reductive metabolism (Fig. 2E-F). Conversely, succinate was formed primarily through oxidative glutamine metabolism, with a minor contribution from the reductive carboxylation pathway (Fig. 2D). Notably, this oxidatively-derived succinate was detected prior to that formed through reductive carboxylation. This indicated that 143Bcytb cells retain the ability to oxidize AKG despite the observation that most of the citrate pool bears the labeling pattern of reductive carboxylation. Together, the labeling data in 143Bcytb cells revealed bidirectional metabolism of carbon from glutamine to produce various TCA cycle intermediates.

Figure 2  Oxidative glutamine metabolism is the primary route of succinate formation in cells using reductive carboxylation to generate citrate

Pyruvate carboxylation contributes to the TCA cycle in cells using reductive carboxylation

Because of the persistence of oxidative metabolism, we determined the extent to which other routes of metabolism besides reductive carboxylation contributed to the TCA cycle. We previously reported that silencing the glutamine-catabolizing enzyme glutaminase (GLS) depletes pools of fumarate, malate and OAA, eliciting a compensatory increase in pyruvate carboxylase (PC) to supply the TCA cycle (Cheng et al., 2011). In cells with defective oxidative phophorylation, production of OAA by PC may be preferable to glutamine oxidation because it diminishes the need to recycle reduced electron carriers generated by the TCA cycle. Citrate synthase (CS) can then condense PC-derived OAA with acetyl-CoA to form citrate. To examine the contribution of PC to the TCA cycle, cells were cultured with [3,4-13C]glucose. In this labeling scheme, glucose-derived pyruvate is labeled in carbon 1 (Fig. S3). This label is retained in OAA if pyruvate is carboxylated, but removed as CO2 during conversion of pyruvate to acetyl-CoA by pyruvate dehydrogenase (PDH).

Figure 3 Pyruvate carboxylase contributes to citrate formation in cells using reductive carboxylation

Oxidative metabolism of AKG is required for reductive carboxylation

Oxidative synthesis of succinate from AKG requires two reactions: the oxidative decarboxylation of AKG to succinyl-CoA by AKG dehydrogenase, and the conversion of succinyl-CoA to succinate by succinyl-CoA synthetase. In tumors with mutations in the succinate dehydrogenase (SDH) complex, large accumulations of succinate are associated with epigenetic modifications of DNA and histones to promote malignancy (Kaelin and McKnight, 2013Killian et al., 2013). We therefore tested whether succinate accumulation per se was required to induce reductive carboxylation in 143Bcytb cells. We used RNA interference directed against the gene encoding the alpha subunit (SUCLG1) of succinyl-CoA synthetase, the last step in the pathway of oxidative succinate formation from glutamine (Fig. 4A). Silencing this enzyme greatly reduced succinate levels (Fig. 4B), but had no effect on the labeling pattern of citrate from [U-13C]glutamine (Fig. 4C). Thus, succinate accumulation is not required for reductive carboxylation.

Figure 5 AKG dehydrogenase is required for reductive carboxylation

Figure 6 AKG dehydrogenase and NNT contribute to NAD+/NADH ratio

Finally, we tested whether these enzymes also controlled the NADP+/NADPH ratio in 143Bcytb cells. Silencing either OGDH or NNT increased the NADP+/NADPH ratio (Fig. 6F,G), whereas silencing IDH2reduced it (Fig. 6H). Together, these data are consistent with a model in which persistent metabolism of AKG by AKG dehydrogenase produces NADH that supports reductive carboxylation by serving as substrate for NNT-dependent NADPH formation, and that IDH2 is a major consumer of NADPH during reductive carboxylation (Fig. 6I).

Reductive carboxylation of AKG initiates a non-conventional form of metabolism that produces TCA cycle intermediates when oxidative metabolism is impaired by mutations, drugs or hypoxia. Because NADPH-dependent isoforms of IDH are reversible, supplying supra-physiological pools of substrates on either side of the reaction drives function of the enzyme as a reductive carboxylase or an oxidative decarboxylase. Thus, in some circumstances reductive carboxylation may operate in response to a mass effect imposed by drastic changes in the abundance of AKG and isocitrate/citrate. However, reductive carboxylation cannot occur without a source of reducing equivalents to produce NADPH. The current work demonstrates that AKG dehydrogenase, an NADH-generating enzyme complex, is required to maintain a low NAD+/NADH ratio for reductive carboxylation of AKG. Thus, reductive carboxylation not only coexists with oxidative metabolism of AKG, but depends on it. Furthermore, silencing NNT, a consumer of NADH, also perturbs the redox ratio and suppresses reductive formation of citrate. These observations suggest that the segment of the oxidative TCA cycle culminating in succinate is necessary to transmit reducing equivalents to NNT for the reductive pathway (Fig 6I).

Succinate accumulation was observed in cells with cytb or FH mutations. However, this accumulation was dispensable for reductive carboxylation, because silencing SUCLG1 expression had no bearing on the pathway as long as AKG dehydrogenase was active. Furthermore, succinate accumulation was not a universal finding of cells using reductive carboxylation. Rather, high succinate levels were observed in cells with distal defects in the ETC (complex III: antimycin, cytb mutation; complex IV: hypoxia) but not defects in complex I (rotenone, metformin, NDUFA1 mutation). These differences reflect the known suppression of SDH activity when downstream components of the ETC are impaired, and the various mechanisms by which succinate may be formed through either oxidative or reductive metabolism. Succinate has long been known as an evolutionarily conserved anaerobic end product of amino acid metabolism during prolonged hypoxia, including in diving mammals (Hochachka and Storey, 1975, Hochachka et al., 1975). The terminal step in this pathway is the conversion of fumarate to succinate using the NADH-dependent “fumarate reductase” system, essentially a reversal of succinate dehydrogenase/ETC complex II (Weinberg et al., 2000, Tomitsuka et al., 2010). However, this process requires reducing equivalents to be passed from NADH to complex I, then to Coenzyme Q, and eventually to complex II to drive the reduction of fumarate to succinate. Hence, producing succinate through reductive glutamine metabolism would require functional complex I. Interestingly, the fumarate reductase system has generally been considered as a mechanism to maintain a proton gradient under conditions of defective ETC activity. Our data suggest that the system is part of a more extensive reorganization of the TCA cycle that also enables reductive citrate formation.

In summary, we demonstrated that branched AKG metabolism is required to sustain levels of reductive carboxylation observed in cells with mitochondrial defects. The organization of this branched pathway suggests that it serves as a relay system to maintain the redox requirements for reductive carboxylation, with the oxidative arm producing reducing equivalents at the level of AKG dehydrogenase and NNT linking this activity to the production of NADPH to be used in the reductive carboxylation reaction. Hence, impairment of the oxidative arm prevents maximal engagement of reductive carboxylation. As both NNT and AKG dehydrogenase are mitochondrial enzymes, the work emphasizes the flexibility of metabolic systems in the mitochondria to fulfill requirements for redox balance and precursor production even when the canonical oxidative function of the mitochondria is impaired.

2.1.3.3 Rewiring Mitochondrial Pyruvate Metabolism. Switching Off the Light in Cancer Cells

Peter W. Szlosarek, Suk Jun Lee, Patrick J. Pollard
Molec Cell 6 Nov 2014; 56(3): 343–344
http://dx.doi.org/10.1016/j.molcel.2014.10.018

Figure 1. MPC Expression and Metabolic Targeting of Mitochondrial Pyruvate High MPC expression (green) is associated with more favorable tumor prognosis, increased pyruvate oxidation, and reduced lactate and ROS, whereas low expression or mutated MPC is linked to poor tumor prognosis and increased anaplerotic generation of OAA. Dual targeting of MPC and GDH with small molecule inhibitors may ameliorate tumorigenesis in certain cancer types.

The study by Yang et al., (2014) provides evidence for the metabolic flexibility to maintain TCA cycle function. Using isotopic labeling, the authors demonstrated that inhibition of MPCs by a specific compound (UK5099) induced glutamine-dependent acetyl-CoA formation via glutamate dehydrogenase (GDH). Consequently, and in contrast to single agent treatment, simultaneous administration of MPC and GDH inhibitors drastically abrogated the growth of cancer cells (Figure 1). These studies have also enabled a fresh perspective on metabolism in the clinic and emphasized a need for high-quality translational studies to assess the role of mitochondrial pyruvate transport in vivo. Thus, integrating the biomarker of low MPC expression with dual inhibition of

MPC and GDH as a synthetic lethal strategy (Yang et al., 2014) is testable and may offer a novel therapeutic window for patients (DeBerardinis and Thompson, 2012). Indeed, combinatorial targeting of cancer metabolism may prevent early drug resistance and lead to enhanced tumor control, as shown recently for antifolate agents combined with arginine deprivation with modulation of intracellular glutamine (Szlosarek, 2014). Moreover, it will be important to assess both intertumoral and intratumoral metabolic heterogeneity going forward, as tumor cells are highly adaptable with respect to the precursors used to fuel the TCA cycle in the presence of reduced pyruvate transport. The observation by Vacanti et al. (2014) that the flux of BCAAs increased following inhibition of MPC activity may also underlie the increase in BCAAs detected in the plasma of patients several years before a clinical diagnosis of pancreatic cancer (Mayers et al., 2014). Since measuring pyruvate transport via the MPC is technically challenging, the use of 18-FDG positron emission tomography and more recently magnetic spectroscopy with hyperpolarized 13C-labeled pyruvate will need to be incorporated into these future studies (Brindle et al., 2011).

References

Bricker, D.K., Taylor, E.B., Schell, J.C., Orsak, T., Boutron, A., Chen, Y.C., Cox, J.E., Cardon, C.M., Van Vranken, J.G., Dephoure, N., et al. (2012). Science 337, 96–100.

Brindle, K.M., Bohndiek, S.E., Gallagher, F.A., and Kettunen, M.I. (2011). Magn. Reson. Med. 66, 505–519.

DeBerardinis, R.J., and Thompson, C.B. (2012). Cell 148, 1132–1144.

Herzig, S., Raemy, E., Montessuit, S., Veuthey, J.L., Zamboni, N., Westermann, B., Kunji, E.R., and Martinou, J.C. (2012). Science 337, 93–96.

Mayers, J.R., Wu, C., Clish, C.B., Kraft, P., Torrence, M.E., Fiske, B.P., Yuan, C., Bao, Y., Townsend, M.K., Tworoger, S.S., et al. (2014). Nat. Med. 20, 1193–1198.

Metallo, C.M., and Vander Heiden, M.G. (2013). Mol. Cell 49, 388–398.

Schell, J.C., Olson, K.A., Jiang, L., Hawkins, A.J., Van Vranken, J.G., et al. (2014). Mol. Cell 56, this issue, 400–413.

Szlosarek, P.W. (2014). Proc. Natl. Acad. Sci. USA 111, 14015–14016.

Vacanti, N.M., Divakaruni, A.S., Green, C.R., Parker, S.J., Henry, R.R., et al. (2014). Mol. Cell 56, this issue, 425–435.

Yang, C., Ko, B., Hensley, C.T., Jiang, L., Wasti, A.T., et al. (2014). Mol. Cell 56, this issue, 414–424.

2.1.3.4 Betaine is a positive regulator of mitochondrial respiration

Lee I
Biochem Biophys Res Commun. 2015 Jan 9; 456(2):621-5.
http://dx.doi.org:/10.1016/j.bbrc.2014.12.005

Highlights

  • Betaine enhances cytochrome c oxidase activity and mitochondrial respiration.
    • Betaine increases mitochondrial membrane potential and cellular energy levels.
    • Betaine’s anti-tumorigenic effect might be due to a reversal of the Warburg effect.

Betaine protects cells from environmental stress and serves as a methyl donor in several biochemical pathways. It reduces cardiovascular disease risk and protects liver cells from alcoholic liver damage and nonalcoholic steatohepatitis. Its pretreatment can rescue cells exposed to toxins such as rotenone, chloroform, and LiCl. Furthermore, it has been suggested that betaine can suppress cancer cell growth in vivo and in vitro. Mitochondrial electron transport chain (ETC) complexes generate the mitochondrial membrane potential, which is essential to produce cellular energy, ATP. Reduced mitochondrial respiration and energy status have been found in many human pathological conditions including aging, cancer, and neurodegenerative disease. In this study we investigated whether betaine directly targets mitochondria. We show that betaine treatment leads to an upregulation of mitochondrial respiration and cytochrome c oxidase activity in H2.35 cells, the proposed rate limiting enzyme of ETC in vivo. Following treatment, the mitochondrial membrane potential was increased and cellular energy levels were elevated. We propose that the anti-proliferative effects of betaine on cancer cells might be due to enhanced mitochondrial function contributing to a reversal of the Warburg effect.

2.1.3.5 Mitochondrial dysfunction in human non-small-cell lung cancer cells to TRAIL-induced apoptosis by reactive oxygen species and Bcl-XL/p53-mediated amplification mechanisms

Y-L Shi, S Feng, W Chen, Z-C Hua, J-J Bian and W Yin
Cell Death and Disease (2014) 5, e1579
http://dx.doi.org:/10.1038/cddis.2014.547

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is a promising agent for anticancer therapy; however, non-small-cell lung carcinoma (NSCLC) cells are relatively TRAIL resistant. Identification of small molecules that can restore NSCLC susceptibility to TRAIL-induced apoptosis is meaningful. We found here that rotenone, as a mitochondrial respiration inhibitor, preferentially increased NSCLC cells sensitivity to TRAIL-mediated apoptosis at subtoxic concentrations, the mechanisms by which were accounted by the upregulation of death receptors and the downregulation of c-FLIP (cellular FLICE-like inhibitory protein). Further analysis revealed that death receptors expression by rotenone was regulated by p53, whereas c-FLIP downregulation was blocked by Bcl-XL overexpression. Rotenone triggered the mitochondria-derived reactive oxygen species (ROS) generation, which subsequently led to Bcl-XL downregulation and PUMA upregulation. As PUMA expression was regulated by p53, the PUMA, Bcl-XL and p53 in rotenone-treated cells form a positive feedback amplification loop to increase the apoptosis sensitivity. Mitochondria-derived ROS, however, promote the formation of this amplification loop. Collectively, we concluded that ROS generation, Bcl-XL and p53-mediated amplification mechanisms had an important role in the sensitization of NSCLC cells to TRAIL-mediated apoptosis by rotenone. The combined TRAIL and rotenone treatment may be appreciated as a useful approach for the therapy of NSCLC that warrants further investigation.

Abbreviations: c-FLIP, cellular FLICE-like inhibitory protein; DHE, dihydroethidium; DISC, death-inducing signaling complex; DPI, diphenylene iodonium; DR4/DR5, death receptor 4/5; EB, ethidium bromide; FADD, Fas-associated protein with death domain; MnSOD, manganese superoxide; NAC, N-acetylcysteine; NSCLC, non-small-cell lung carcinoma; PBMC, peripheral blood mononuclear cells; ROS, reactive oxygen species; TRAIL, tumor necrosis factor-related apoptosis-inducing ligand; UPR, unfolded protein response.

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) has emerged as a promising cancer therapeutic because it can selectively induce apoptosis in tumor cells in vitro, and most importantly, in vivo with little adverse effect on normal cells.1 However, a number of cancer cells are resistant to TRAIL, especially highly malignant tumors such as lung cancer.23 Lung cancer, especially the non-small-cell lung carcinoma (NSCLC) constitutes a heavy threat to human life. Presently, the morbidity and mortality of NSCLC has markedly increased in the past decade,4 which highlights the need for more effective treatment strategies.

TRAIL has been shown to interact with five receptors, including the death receptors 4 and 5 (DR4 and DR5), the decoy receptors DcR1 and DcR2, and osteoprotegerin.5 Ligation of TRAIL to DR4 or DR5 allows for the recruitment of Fas-associated protein with death domain (FADD), which leads to the formation of death-inducing signaling complex (DISC) and the subsequent activation of caspase-8/10.6 The effector caspase-3 is activated by caspase-8, which cleaves numerous regulatory and structural proteins resulting in cell apoptosis. Caspase-8 can also cleave the Bcl-2 inhibitory BH3-domain protein (Bid), which engages the intrinsic apoptotic pathway by binding to Bcl-2-associated X protein (Bax) and Bcl-2 homologous antagonist killer (BAK). The oligomerization between Bcl-2 and Bax promotes the release of cytochrome c from mitochondria to cytosol, and facilitates the formation of apoptosome and caspase-9 activation.7 Like caspase-8, caspase-9 can also activate caspase-3 and initiate cell apoptosis. Besides apoptosis-inducing molecules, several apoptosis-inhibitory proteins also exist and have function even when apoptosis program is initiated. For example, cellular FLICE-like inhibitory protein (c-FLIP) is able to suppress DISC formation and apoptosis induction by sequestering FADD.891011

Until now, the recognized causes of TRAIL resistance include differential expression of death receptors, constitutively active AKT and NF-κB,1213overexpression of c-FLIP and IAPs, mutations in Bax and BAK gene.2 Hence, resistance can be overcome by the use of sensitizing agents that modify the deregulated death receptor expression and/or apoptosis signaling pathways in cancer cells.5 Many sensitizing agents have been developed in a variety of tumor cell models.2 Although the clinical effectiveness of these agents needs further investigation, treatment of TRAIL-resistant tumor cells with sensitizing agents, especially the compounds with low molecular weight, as well as prolonged plasma half-life represents a promising trend for cancer therapy.

Mitochondria emerge as intriguing targets for cancer therapy. Metabolic changes affecting mitochondria function inside cancer cells endow these cells with distinctive properties and survival advantage worthy of drug targeting, mitochondria-targeting drugs offer substantial promise as clinical treatment with minimal side effects.141516 Rotenone is a potent inhibitor of NADH oxidoreductase in complex I, which demonstrates anti-neoplastic activity on a variety of cancer cells.1718192021 However, the neurotoxicity of rotenone limits its potential application in cancer therapy. To avoid it, rotenone was effectively used in combination with other chemotherapeutic drugs to kill cancerous cells.22

In our previous investigation, we found that rotenone was able to suppress membrane Na+,K+-ATPase activity and enhance ouabain-induced cancer cell death.23 Given these facts, we wonder whether rotenone may also be used as a sensitizing agent that can restore the susceptibility of NSCLC cells toward TRAIL-induced apoptosis, and increase the antitumor efficacy of TRAIL on NSCLC. To test this hypothesis, we initiated this study.

Rotenone sensitizes NSCLC cell lines to TRAIL-induced apoptosis

Four NSCLC cell lines including A549, H522, H157 and Calu-1 were used in this study. As shown in Figure 1a, the apoptosis induced by TRAIL alone at 50 or 100 ng/ml on A549, H522, H157 and Calu-1 cells was non-prevalent, indicating that these NSCLC cell lines are relatively TRAIL resistant. Interestingly, when these cells were treated with TRAIL combined with rotenone, significant increase in cell apoptosis was observed. To examine whether rotenone was also able to sensitize normal cells to TRAIL-mediated apoptosis, peripheral blood mononuclear cell (PBMC) isolated from human blood were used. As a result, rotenone failed to sensitize human PBMC to TRAIL-induced apoptosis, indicating that the sensitizing effect of rotenone is tumor cell specific. Of note, the apoptosis-enhancing effect of rotenone occurred independent of its cytotoxicity, because the minimal dosage required for rotenone to cause toxic effect on NSCLC cell lines was 10 μM, however, rotenone augmented TRAIL-mediated apoptosis when it was used as little as 10 nM.

Figure 1.

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To further confirm the effect of rotenone, cells were stained with Hoechst and observed under fluorescent microscope (Figure 1b). Consistently, the combined treatment of rotenone with TRAIL caused significant nuclear fragmentation in A549, H522, H157 and Calu-1 cells. Rotenone or TRAIL treatment alone, however, had no significant effect.

Caspases activation is a hallmark of cell apoptosis. In this study, the enzymatic activities of caspases including caspase-3, -8 and -9 were measured by flow cytometry by using FITC-conjugated caspases substrate (Figure 1c). As a result, rotenone used at 1 μM or TRAIL used at 100 ng/ml alone did not cause caspase-3, -8 and -9 activation. The combined treatment, however, significantly increased the enzymatic activities of them. Moreover, A549 or H522 cell apoptosis by TRAIL combined with rotenone was almost completely suppressed in the presence of z-VAD.fmk, a pan-caspase inhibitor (Figure 1d). All of these data indicate that both intrinsic and extrinsic pathways are involved in the sensitizing effect of rotenone on TRAIL-mediated apoptosis in NSCLC.

Upregulation of death receptors expression is required for rotenone-mediated sensitization to TRAIL-induced apoptosis

Sensitization to TRAIL-induced apoptosis has been explained in some studies by upregulation of death receptors,24 whereas other results show that sensitization can occur without increased TRAIL receptor expression.25 As such, we examined TRAIL receptors expression on NSCLC cells after treatment with rotenone. Rotenone increased DR4 and DR5 mRNA levels in A549 cells in a time or concentration-dependent manner (Figures 2a and b), also increased DR4 and DR5 protein expression levels (Supplementary Figure S1). Notably, rotenone failed to increase DR5 mRNA levels in H157 and Calu-1 cells (Supplementary Figure S2). To observe whether the increased DR4 and DR5 mRNA levels finally correlated with the functional molecules, we examined the surface expression levels of DR4 and DR5 by flow cytometry. The results, as shown in Figure 2c demonstrated that the cell surface expression levels of DR4 and DR5 were greatly upregulated by rotenone in either A549 cells or H522 cells.

Figure 2.

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To analyze whether the upregulation of DR4 and DR5 is a ‘side-effect’, or contrarily, necessary for rotenone-mediated sensitization to TRAIL-induced apoptosis, we blocked upregulation of the death receptors by small interfering RNAs (siRNAs) against DR4 and DR5 (Supplementary Figure S3). The results showed that blocking DR4 and DR5 expression alone significantly reduced the rate of cell apoptosis in A549 cells (Figure 2d). However, the highest inhibition of apoptosis was observed when upregulation of both receptors was blocked in parallel, thus showing an additive effect of blocking DR4 and DR5 at the same time. Similar results were also obtained in H522 cells

To analyze whether the upregulation of DR4 and DR5 is a ‘side-effect’, or contrarily, necessary for rotenone-mediated sensitization to TRAIL-induced apoptosis, we blocked upregulation of the death receptors by small interfering RNAs (siRNAs) against DR4 and DR5 (Supplementary Figure S3). The results showed that blocking DR4 and DR5 expression alone significantly reduced the rate of cell apoptosis in A549 cells (Figure 2d). However, the highest inhibition of apoptosis was observed when upregulation of both receptors was blocked in parallel, thus showing an additive effect of blocking DR4 and DR5 at the same time. Similar results were also obtained in H522 cells.

Rotenone-induced p53 activation regulates death receptors upregulation

TRAIL receptors DR4 and DR5 are regulated at multiple levels. At transcriptional level, studies suggest that several transcriptional factors including NF-κB, p53 and AP-1 are involved in DR4 or DR5 gene transcription.2 The NF-κB or AP-1 transcriptional activity was further modulated by ERK1/2, JNK and p38 MAP kinase activity. Unexpectedly, we found here that none of these MAP kinases inhibitors were able to suppress the apoptosis mediated by TRAIL plus rotenone (Figure 3a). To find out other possible mechanisms, we observed that rotenone was able to stimulate p53 phosphorylation as well as p53 protein expression in A549 and H522 cells (Figure 3b). As a p53-inducible gene, p21 mRNA expression was also upregulated by rotenone treatment in a time-dependent manner (Figure 3c). To characterize the effect of p53, A549 cells were transfected with p53 siRNA. The results, as shown in Figure 3d-1 demonstrated that rotenone-mediated surface expression levels of DR4 and DR5 in A549 cells were largely attenuated by siRNA-mediated p53 expression silencing. Control siRNA, however, failed to reveal such effect. Similar results were also obtained in H522 cells (Figure 3d-2). Silencing of p53 expression in A549 cells also partially suppressed the apoptosis induced by TRAIL plus rotenone (Figure 3e).

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Rotenone suppresses c-FLIP expression and increases the sensitivity of A549 cells to TRAIL-induced apoptosis

The c-FLIP protein has been commonly appreciated as an anti-apoptotic molecule in death receptor-mediated cell apoptosis. In this study, rotenone treatment led to dose-dependent downregulation of c-FLIP expression, including c-FLIPL and c-FLIPs in A549 cells (Figure 4a-1), H522 cells (Figure 4a-2), H441 and Calu-1 cells (Supplementary Figure S4). To test whether c-FLIP is essential for the apoptosis enhancement, A549 cells were transfected with c-FLIPL-overexpressing plasmids. As shown in Figure 4b-1, the apoptosis of A549 cells after the combined treatment was significantly reduced when c-FLIPL was overexpressed. Similar results were also obtained in H522 cells (Figure 4b-2).

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Bcl-XL is involved in the apoptosis enhancement by rotenone

Notably, c-FLIP downregulation by rotenone in NSCLC cells was irrelevant to p53 signaling (data not shown). To identify other mechanism involved, we found that anti-apoptotic molecule Bcl-XL was also found to be downregulated by rotenone in a dose-dependent manner (Figure 5a). Notably, both Bcl-XL and c-FLIPL mRNA levels remained unchanged in cells after rotenone treatment (Supplementary Figure S5). Bcl-2 is homolog to Bcl-XL. But surprisingly, Bcl-2 expression was almost undetectable in A549 cells. To examine whether Bcl-XL is involved, A549 cells were transfected with Bcl-XL-overexpressing plasmid. As compared with mock transfectant, cell apoptosis induced by TRAIL plus rotenone was markedly suppressed under the condition of Bcl-XL overexpression (Figure 5b). To characterize the mechanisms, surface expression levels of DR4 and DR5 were examined. As shown in Figure 5c, the increased surface expression of DR4 and DR5 in A549 cells, or in H522 cells were greatly reduced after Bcl-XLoverexpression (Figure 5c). In addition, Bcl-XL overexpression also significantly prevented the downregulation of c-FLIPL and c-FLIPs expression in A549 cells by rotenone treatment (Figure 5d).

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Rotenone suppresses the interaction between BCL-XL/p53 and increases PUMA transcription

Lines of evidence suggest that Bcl-XL has a strong binding affinity with p53, and can suppress p53-mediated tumor cell apoptosis.26 In this study, FLAG-tagged Bcl-XL and HA-tagged p53 were co-transfected into cells; immunoprecipitation experiment was performed by using FLAG antibody to immunoprecipitate HA-tagged p53. As a result, we found that at the same amount of p53 protein input, rotenone treatment caused a concentration-dependent suppression of the protein interaction between Bcl-XL and p53 (Figure 6a). Rotenone also significantly suppressed the interaction between endogenous Bcl-XL and p53 when polyclonal antibody against p53 was used to immunoprecipitate cellular Bcl-XL (Figure 6b). Recent study highlighted the importance of PUMA in BCL-XL/p53 interaction and cell apoptosis.27 We found here that rotenone significantly increased PUMA gene transcription (Figure 6c) and protein expression (Figure 6d) in NSCLC cells, but not in transformed 293T cell. Meanwhile, this effect was attenuated by silencing of p53 expression (Figure 6e).

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Mitochondria-derived ROS are responsible for the apoptosis-enhancing effect of rotenone

As an inhibitor of mitochondrial respiration, rotenone was found to induce reactive oxygen species (ROS) generation in a variety of transformed or non-transformed cells.2022 Consistently, by using 2′,7′-dichlorofluorescin diacetate (DCFH) for the measurement of intracellular H2O2 and dihydroethidium (DHE) for O2.−, we found that rotenone significantly triggered the .generation of H2O2(Figure 7a) and O2.− (Figure 7b) in A549 and H522 cells. To identify the origin of ROS production, we first incubated cells with diphenylene iodonium (DPI), a potent inhibitor of plasma membrane NADP/NADPH oxidase. The results showed that DPI failed to suppress rotenone-induced ROS generation (Figure 7c). Then, we generated A549 cells deficient in mitochondria DNA by culturing cells in medium supplemented with ethidium bromide (EB). These mtDNA-deficient cells were subject to rotenone treatment, and the result showed that rotenone-induced ROS production were largely attenuated in A549 ρ° cells, but not wild-type A549 cells, suggesting ROS are mainly produced from mitochondria (Figure 7d). Notably, the sensitizing effect of rotenone on TRAIL-induced apoptosis in A549 cells was largely dependent on ROS, because the antioxidant N-acetylcysteine (NAC) treatment greatly suppressed the cell apoptosis, as shown in annexin V/PI double staining experiment (Figure 7e), cell cycle analysis (Figure 7f) and caspase-3 cleavage activity assay (Figure 7g). Finally, in A549 cells stably transfected with manganese superoxide (MnSOD) and catalase, apoptosis induced by TRAIL and rotenone was partially reversed (Figure 7h). All of these data suggest that mitochondria-derived ROS, including H2O2 and O2.−, are responsible for the apoptosis-enhancing effect of rotenone.

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Rotenone promotes BCl-XL degradation and PUMA transcription in ROS-dependent manner

To understand why ROS are responsible for the apoptosis-enhancing effect of rotenone, we found that rotenone-induced suppression of BCL-XL expression can be largely reversed by NAC treatment (Figure 8a). To examine whether this effect of rotenone occurs at posttranslational level, we used cycloheximide (CHX) to halt protein synthesis, and found that the rapid degradation of Bcl-XL by rotenone was largely attenuated in A549 ρ0 cells (Figure 8b). Similarly, rotenone-induced PUMA upregulation was also significantly abrogated in A549 ρ0 cells (Figure 8c). Finally, A549 cells were inoculated into nude mice to produce xenografts tumor model. In this model, the therapeutic effect of TRAIL combined with rotenone was evaluated. Notably, in order to circumvent the potential neurotoxic adverse effect of rotenone, mice were challenged with rotenone at a low concentration of 0.5 mg/kg. The results, as shown in Figure 8d revealed that while TRAIL or rotenone alone remained unaffected on A549 tumor growth, the combined therapy significantly slowed down the tumor growth. Interestingly, the tumor-suppressive effect of TRAIL plus rotenone was significantly attenuated by NAC (P<0.01). After experiment, tumors were removed and the caspase-3 activity in tumor cells was analyzed by flow cytometry. Consistently, the caspase-3 cleavage activities were significantly activated in A549 cells from animals challenged with TRAIL plus rotenone, meanwhile, this effect was attenuated by NAC (Figure 8e). The similar effect of rotenone also occurred in NCI-H441 xenografts tumor model (Supplementary Figure S6).

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Restoration of cancer cells susceptibility to TRAIL-induced apoptosis is becoming a very useful strategy for cancer therapy. In this study, we provided evidence that rotenone increased the apoptosis sensitivity of NSCLC cells toward TRAIL by mechanisms involving ROS generation, p53 upregulation, Bcl-XL and c-FLIP downregulation, and death receptors upregulation. Among them, mitochondria-derived ROS had a predominant role. Although rotenone is toxic to neuron, increasing evidence also demonstrated that it was beneficial for improving inflammation, reducing reperfusion injury, decreasing virus infection or triggering cancer cell death. We identified here another important characteristic of rotenone as a tumor sensitizer in TRAIL-based cancer therapy, which widens the application potential of rotenone in disease therapy.

As Warburg proposed the cancer ‘respiration injury’ theory, increasing evidence suggest that cancer cells may have mitochondrial dysfunction, which causes cancer cells, compared with the normal cells, are under increased generation of ROS.33 The increased ROS in cancer cells have a variety of biological effects. We found here that rotenone preferentially increased the apoptosis sensitivity of cancer cells toward TRAIL, further confirming the concept that although tumor cells have a high level of intracellular ROS, they are more sensitive than normal cells to agents that can cause further accumulation of ROS.

Cancer cells stay in a stressful tumor microenvironment including hypoxia, low nutrient availability and immune infiltrates. These conditions, however, activate a range of stress response pathways to promote tumor survival and aggressiveness. In order to circumvent TRAIL-mediated apoptotic clearance, the expression levels of DR4 and DR5 in many types of cancer cells are nullified, but interestingly, they can be reactivated when cancer cells are challenged with small chemical molecules. Furthermore, those small molecules often take advantage of the stress signaling required for cancer cells survival to increase cancer cells sensitivity toward TRAIL. For example, the unfolded protein response (UPR) has an important role in cancer cells survival, SHetA2, as a small molecule, can induce UPR in NSCLC cell lines and augment TRAIL-induced apoptosis by upregulating DR5 expression in CHOP-dependent manner. Here, we found rotenone manipulated the oxidative stress signaling of NSCLC cells to increase their susceptibility to TRAIL. These facts suggest that cellular stress signaling not only offers opportunity for cancer cells to survive, but also renders cancer cells eligible for attack by small molecules. A possible explanation is that depending on the intensity of stress, cellular stress signaling can switch its role from prosurvival to death enhancement. As described in this study, although ROS generation in cancer cells is beneficial for survival, rotenone treatment further increased ROS production to a high level that surpasses the cell ability to eliminate them; as a result, ROS convert its role from survival to death.

2.1.3.6 PPARs and ERRs. molecular mediators of mitochondrial metabolism

Weiwei Fan, Ronald Evans
Current Opinion in Cell Biology Apr 2015; 33:49–54
http://dx.doi.org/10.1016/j.ceb.2014.11.002

Since the revitalization of ‘the Warburg effect’, there has been great interest in mitochondrial oxidative metabolism, not only from the cancer perspective but also from the general biomedical science field. As the center of oxidative metabolism, mitochondria and their metabolic activity are tightly controlled to meet cellular energy requirements under different physiological conditions. One such mechanism is through the inducible transcriptional co-regulators PGC1α and NCOR1, which respond to various internal or external stimuli to modulate mitochondrial function. However, the activity of such co-regulators depends on their interaction with transcriptional factors that directly bind to and control downstream target genes. The nuclear receptors PPARs and ERRs have been shown to be key transcriptional factors in regulating mitochondrial oxidative metabolism and executing the inducible effects of PGC1α and NCOR1. In this review, we summarize recent gain-of-function and loss-of-function studies of PPARs and ERRs in metabolic tissues and discuss their unique roles in regulating different aspects of mitochondrial oxidative metabolism.

Energy is vital to all living organisms. In humans and other mammals, the vast majority of energy is produced by oxidative metabolism in mitochondria [1]. As a cellular organelle, mitochondria are under tight control of the nucleus. Although the majority of mitochondrial proteins are encoded by nuclear DNA (nDNA) and their expression regulated by the nucleus, mitochondria retain their own genome, mitochondrial DNA (mtDNA), encoding 13 polypeptides of the electron transport chain (ETC) in mammals. However, all proteins required for mtDNA replication, transcription, and translation, as well as factors regulating such activities, are encoded by the nucleus [2].

The cellular demand for energy varies in different cells under different physiological conditions. Accordingly, the quantity and activity of mitochondria are differentially controlled by a transcriptional regulatory network in both the basal and induced states. A number of components of this network have been identified, including members of the nuclear receptor superfamily, the peroxisome proliferator-activated receptors (PPARs) and the estrogen-related receptors (ERRs) [34 and 5].

The Yin-Yang co-regulators

A well-known inducer of mitochondrial oxidative metabolism is the peroxisome proliferator-activated receptor γ coactivator 1α (PGC1α) [6], a nuclear cofactor which is abundantly expressed in high energy demand tissues such as heart, skeletal muscle, and brown adipose tissue (BAT) [7]. Induction by cold-exposure, fasting, and exercise allows PGC1α to regulate mitochondrial oxidative metabolism by activating genes involved in the tricarboxylic acid cycle (TCA cycle), beta-oxidation, oxidative phosphorylation (OXPHOS), as well as mitochondrial biogenesis [6 and 8] (Figure 1).

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Figure 1.  PPARs and ERRs are major executors of PGC1α-induced regulation of oxidative metabolism. Physiological stress such as exercise induces both the expression and activity of PGC1α, which stimulates energy production by activating downstream genes involved in fatty acid and glucose metabolism, TCA cycle, β-oxidation, OXPHOS, and mitochondrial biogenesis. The transcriptional activity of PGC1α relies on its interactions with transcriptional factors such as PPARs (for controlling fatty acid metabolism) and ERRs (for regulating mitochondrial OXPHOS).

The effect of PGC1α on mitochondrial regulation is antagonized by transcriptional corepressors such as the nuclear receptor corepressor 1 (NCOR1) [9 and 10]. In contrast to PGC1α, the expression of NCOR1 is suppressed in conditions where PGC1α is induced such as during fasting, high-fat-diet challenge, and exercise [9 and 11]. Moreover, the knockout of NCOR1 phenotypically mimics PGC1α overexpression in regulating mitochondrial oxidative metabolism [9]. Therefore, coactivators and corepressors collectively regulate mitochondrial metabolism in a Yin-Yang fashion.

However, both PGC1α and NCOR1 lack DNA binding activity and rather act via their interaction with transcription factors that direct the regulatory program. Therefore the transcriptional factors that partner with PGC1α and NCOR1 mediate the molecular signaling cascades and execute their inducible effects on mitochondrial regulation.

PPARs: master executors controlling fatty acid oxidation

Both PGC1α and NCOR1 are co-factors for the peroxisome proliferator-activated receptors (PPARα, γ, and δ) [71112 and 13]. It is now clear that all three PPARs play essential roles in lipid and fatty acid metabolism by directly binding to and modulating genes involved in fat metabolism [1314151617,18 and 19]. While PPARγ is known as a master regulator for adipocyte differentiation and does not seem to be involved with oxidative metabolism [14 and 20], both PPARα and PPARδ are essential regulators of fatty acid oxidation (FAO) [3131519 and 21] (Figure 1).

PPARα was first cloned as the molecular target of fibrates, a class of cholesterol-lowering compounds that increase hepatic FAO [22]. The importance of PPARα in regulating FAO is indicated in its expression pattern which is restricted to tissues with high capacity of FAO such as heart, liver, BAT, and oxidative muscle [23]. On the other hand, PPARδ is ubiquitously expressed with higher levels in the digestive tract, heart, and BAT [24]. In the past 15 years, extensive studies using gain-of-function and loss-of-function models have clearly demonstrated PPARα and PPARδ as the major drivers of FAO in a wide variety of tissues.

ERRS: master executors controlling mitochondrial OXPHOS

ERRs are essential regulators of mitochondrial energy metabolism [4]. ERRα is ubiquitously expressed but particularly abundant in tissues with high energy demands such as brain, heart, muscle, and BAT. ERRβ and ERRγ have similar expression patterns, both are selectively expressed in highly oxidative tissues including brain, heart, and oxidative muscle [45]. Instead of endogenous ligands, the transcriptional activity of ERRs is primarily regulated by co-factors such as PGC1α and NCOR1 [4 and 46] (Figure 1).

Of the three ERRs, ERRβ is the least studied and its role in regulating mitochondrial function is unclear [4 and 47]. In contrast, when PGC1α is induced, ERRα is the master regulator of the mitochondrial biogenic gene network. As ERRα binds to its own promoter, PGC1α can also induce an autoregulatory loop to enhance overall ERRα activity [48]. Without ERRα, the ability of PGC1α to induce the expression of mitochondrial genes is severely impaired. However, the basal-state levels of mitochondrial target genes are not affected by ERRα deletion, suggesting induced mitochondrial biogenesis is a transient process and that other transcriptional factors such as ERRγ may be important maintaining baseline mitochondrial OXPHOS [41•42 and 43]. Consistent with this idea, ERRγ (which is active even when PGC1α is not induced) shares many target genes with ERRα [49 and 50].

Conclusion and perspectives

Taken together, recent studies have clearly demonstrated the essential roles of PPARs and ERRs in regulating mitochondrial oxidative metabolism and executing the inducible effects of PGC1α (Figure 1). Both PPARα and PPARδ are key regulators for FA oxidation. While the function of PPARα seems more restricted in FA uptake, beta-oxidation, and ketogenesis, PPARδ plays a broader role in controlling oxidative metabolism and fuel preference, with its target genes involved in FA oxidation, mitochondrial OXPHOS, and glucose utilization. However, it is still not clear how much redundancy exists between PPARα and PPARδ, a question which may require the generation of a double knockout model. In addition, more effort is needed to fully understand how PPARα and PPARδ control their target genes in response to environmental changes.

Likewise, ERRα and ERRγ have been shown to be key regulators of mitochondrial OXPHOS. Knockout studies of ERRα suggest it to be the principal executor of PGC1α induced up-regulation of mitochondrial genes, though its role in exercise-dependent changes in skeletal muscle needs further investigation. Transgenic models have demonstrated ERRγ’s powerful induction of mitochondrial biogenesis and its ability to act in a PGC1α-independent manner. However, it remains to be elucidated whether ERRγ is sufficient for basal-state mitochondrial function in general, and whether ERRα can compensate for its function.

2.1.3.7 Metabolic control via the mitochondrial protein import machinery

Opalińska M, Meisinger C.
Curr Opin Cell Biol. 2015 Apr; 33:42-48
http://dx.doi.org:/10.1016/j.ceb.2014.11.001

Mitochondria have to import most of their proteins in order to fulfill a multitude of metabolic functions. Sophisticated import machineries mediate targeting and translocation of preproteins from the cytosol and subsequent sorting into their suborganellar destination. The mode of action of these machineries has been considered for long time as a static and constitutively active process. However, recent studies revealed that the mitochondrial protein import machinery is subject to intense regulatory mechanisms that include direct control of protein flux by metabolites and metabolic signaling cascades.
2.1.3.8 The Protein Import Machinery of Mitochondria—A Regulatory Hub

AB Harbauer, RP Zahedi, A Sickmann, N Pfanner, C Meisinger
Cell Metab 4 Mar 2014; 19(3):357–372

Mitochondria are essential cell. They are best known for their role as cellular powerhouses, which convert the energy derived from food into an electrochemical proton gradient across the inner membrane. The proton gradient drives the mitochondrial ATP synthase, thus providing large amounts of ATP for the cell. In addition, mitochondria fulfill central functions in the metabolism of amino acids and lipids and the biosynthesis of iron-sulfur clusters and heme. Mitochondria form a dynamic network that is continuously remodeled by fusion and fission. They are involved in the maintenance of cellular ion homeostasis, play a crucial role in apoptosis, and have been implicated in the pathogenesis of numerous diseases, in particular neurodegenerative disorders.

Mitochondria consist of two membranes, outer membrane and inner membrane, and two aqueous compartments, intermembrane space and matrix (Figure 1). Proteomic studies revealed that mitochondria contain more than 1,000 different proteins (Prokisch et al., 2004Reinders et al., 2006Pagliarini et al., 2008 and Schmidt et al., 2010). Based on the endosymbiotic origin from a prokaryotic ancestor, mitochondria contain a complete genetic system and protein synthesis apparatus in the matrix; however, only ∼1% of mitochondrial proteins are encoded by the mitochondrial genome (13 proteins in humans and 8 proteins in yeast). Nuclear genes code for ∼99% of mitochondrial proteins. The proteins are synthesized as precursors on cytosolic ribosomes and are translocated into mitochondria by a multicomponent import machinery. The protein import machinery is essential for the viability of eukaryotic cells. Numerous studies on the targeting signals and import components have been reported (reviewed in Dolezal et al., 2006,Neupert and Herrmann, 2007Endo and Yamano, 2010 and Schmidt et al., 2010), yet for many years little has been known on the regulation of the import machinery. This led to the general assumption that the protein import machinery is constitutively active and not subject to detailed regulation.

Figure 1. Protein Import Pathways of Mitochondria.  Most mitochondrial proteins are synthesized as precursors in the cytosol and are imported by the translocase of the outer mitochondrial membrane (TOM complex). (A) Presequence-carrying (cleavable) preproteins are transferred from TOM to the presequence translocase of the inner membrane (TIM23 complex), which is driven by the membrane potential (Δψ). The proteins either are inserted into the inner membrane (IM) or are translocated into the matrix with the help of the presequence translocase-associated motor (PAM). The presequences are typically cleaved off by the mitochondrial processing peptidase (MPP). (B) The noncleavable precursors of hydrophobic metabolite carriers are bound to molecular chaperones in the cytosol and transferred to the receptor Tom70. After translocation through the TOM channel, the precursors bind to small TIM chaperones in the intermembrane space and are membrane inserted by the Δψ-dependent carrier translocase of the inner membrane (TIM22 complex).
(C) Cysteine-rich proteins destined for the intermembrane space (IMS) are translocated through the TOM channel in a reduced conformation and imported by the mitochondrial IMS import and assembly (MIA) machinery. Mia40 functions as precursor receptor and oxidoreductase in the IMS, promoting the insertion of disulfide bonds into the imported proteins. The sulfhydryl oxidase Erv1 reoxidizes Mia40 for further rounds of oxidative protein import and folding. (D) The precursors of outer membrane β-barrel proteins are imported by the TOM complex and small TIM chaperones and are inserted into the outer membrane by the sorting and assembly machinery (SAM complex). (E) Outer membrane (OM) proteins with α-helical transmembrane segments are inserted into the membrane by import pathways that have only been partially characterized. Shown is an import pathway via the mitochondrial import (MIM) complex

Studies in recent years, however, indicated that different steps of mitochondrial protein import are regulated, suggesting a remarkable diversity of potential mechanisms. After an overview on the mitochondrial protein import machinery, we will discuss the regulatory processes at different stages of protein translocation into mitochondria. We propose that the mitochondrial protein import machinery plays a crucial role as regulatory hub under physiological and pathophysiological conditions. Whereas the basic mechanisms of mitochondrial protein import have been conserved from lower to higher eukaryotes (yeast to humans), regulatory processes may differ between different organisms and cell types. So far, many studies on the regulation of mitochondrial protein import have only been performed in a limited set of organisms. Here we discuss regulatory principles, yet it is important to emphasize that future studies will have to address which regulatory processes have been conserved in evolution and which processes are organism specific.

Protein Import Pathways into Mitochondria

The classical route of protein import into mitochondria is the presequence pathway (Neupert and Herrmann, 2007 and Chacinska et al., 2009). This pathway is used by more than half of all mitochondrial proteins (Vögtle et al., 2009). The proteins are synthesized as precursors with cleavable amino-terminal extensions, termed presequences. The presequences form positively charged amphipathic α helices and are recognized by receptors of the translocase of the outer mitochondrial membrane (TOM complex) (Figure 1A) (Mayer et al., 1995Brix et al., 1997van Wilpe et al., 1999Abe et al., 2000Meisinger et al., 2001 and Saitoh et al., 2007). Upon translocation through the TOM channel, the cleavable preproteins are transferred to the presequence translocase of the inner membrane (TIM23 complex). The membrane potential across the inner membrane (Δψ, negative on the matrix side) exerts an electrophoretic effect on the positively charged presequences (Martin et al., 1991). The presequence translocase-associated motor (PAM) with the ATP-dependent heat-shock protein 70 (mtHsp70) drives preprotein translocation into the matrix (Chacinska et al., 2005 and Mapa et al., 2010). Here the presequences are typically cleaved off by the mitochondrial processing peptidase (MPP). Some cleavable preproteins contain a hydrophobic segment behind the presequence, leading to arrest of translocation in the TIM23 complex and lateral release of the protein into the inner membrane (Glick et al., 1992Chacinska et al., 2005 and Meier et al., 2005). In an alternative sorting route, some cleavable preproteins destined for the inner membrane are fully or partially translocated into the matrix, followed by insertion into the inner membrane by the OXA export machinery, which has been conserved from bacteria to mitochondria (“conservative sorting”) (He and Fox, 1997Hell et al., 1998Meier et al., 2005 and Bohnert et al., 2010).  …

Regulatory Processes Acting at Cytosolic Precursors of Mitochondrial Proteins

Two properties of cytosolic precursor proteins are crucial for import into mitochondria. (1) The targeting signals of the precursors have to be accessible to organellar receptors. Modification of a targeting signal by posttranslational modification or masking of a signal by binding partners can promote or inhibit import into an organelle. (2) The protein import channels of mitochondria are so narrow that folded preproteins cannot be imported. Thus preproteins should be in a loosely folded state or have to be unfolded during the import process. Stable folding of preprotein domains in the cytosol impairs protein import.  …

Import Regulation by Binding of Metabolites or Partner Proteins to Preproteins

Binding of a metabolite to a precursor protein can represent a direct means of import regulation (Figure 2A, condition 1). A characteristic example is the import of 5-aminolevulinate synthase, a mitochondrial matrix protein that catalyzes the first step of heme biosynthesis (Hamza and Dailey, 2012). The precursor contains heme binding motifs in its amino-terminal region, including the presequence (Dailey et al., 2005). Binding of heme to the precursor inhibits its import into mitochondria, likely by impairing recognition of the precursor protein by TOM receptors (Lathrop and Timko, 1993González-Domínguez et al., 2001,Munakata et al., 2004 and Dailey et al., 2005). Thus the biosynthetic pathway is regulated by a feedback inhibition of mitochondrial import of a crucial enzyme, providing an efficient and precursor-specific means of import regulation dependent on the metabolic situation.

Figure 2. Regulation of Cytosolic Precursors of Mitochondrial Proteins

(A) The import of a subset of mitochondrial precursor proteins can be positively or negatively regulated by precursor-specific reactions in the cytosol. (1) Binding of ligands/metabolites can inhibit mitochondrial import. (2) Binding of precursors to partner proteins can stimulate or inhibit import into mitochondria. (3) Phosphorylation of precursors in the vicinity of targeting signals can modulate dual targeting to the endoplasmic reticulum (ER) and mitochondria. (4) Precursor folding can mask the targeting signal. (B) Cytosolic and mitochondrial fumarases are derived from the same presequence-carrying preprotein. The precursor is partially imported by the TOM and TIM23 complexes of the mitochondrial membranes and the presequence is removed by the mitochondrial processing peptidase (MPP). Folding of the preprotein promotes retrograde translocation of more than half of the molecules into the cytosol, whereas the other molecules are completely imported into mitochondria.

Regulation of Mitochondrial Protein Entry Gate by Cytosolic Kinases

Figure 3. Regulation of TOM Complex by Cytosolic Kinases

(A) All subunits of the translocase of the outer mitochondrial membrane (TOM complex) are phosphorylated by cytosolic kinases (phosphorylated amino acid residues are indicated by stars with P). Casein kinase 1 (CK1) stimulates the assembly of Tom22 into the TOM complex. Casein kinase 2 (CK2) stimulates the biogenesis of Tom22 as well as the mitochondrial import protein 1 (Mim1). Protein kinase A (PKA) inhibits the biogenesis of Tom22 and Tom40, and inhibits the activity of Tom70 (see B). Cyclin-dependent kinases (CDK) are possibly involved in regulation of TOM. (B) Metabolic shift-induced regulation of the receptor Tom70 by PKA. Carrier precursors bind to cytosolic chaperones (Hsp70 and/or Hsp90). Tom70 has two binding pockets, one for the precursor and one for the accompanying chaperone (shown on the left). When glucose is added to yeast cells (fermentable conditions), the levels of intracellular cAMP are increased and PKA is activated (shown on the right). PKA phosphorylates a serine of Tom70 in vicinity of the chaperone binding pocket, thus impairing chaperone binding to Tom70 and carrier import into mitochondria.

Casein Kinase 2 Stimulates TOM Biogenesis and Protein Import

Metabolic Switch from Respiratory to Fermentable Conditions Involves Protein Kinase A-Mediated Inhibition of TOM

Network of Stimulatory and Inhibitory Kinases Acts on TOM Receptors, Channel, and Assembly Factors

Protein Import Activity as Sensor of Mitochondrial Stress and Dysfunction

Figure 4. Mitochondrial Quality Control and Stress Response

(A) Import and quality control of cleavable preproteins. The TIM23 complex cooperates with several machineries: the TOM complex, a supercomplex consisting of the respiratory chain complexes III and IV, and the presequence translocase-associated motor (PAM) with the central chaperone mtHsp70. Several proteases/peptidases involved in processing, quality control, and/or degradation of imported proteins are shown, including mitochondrial processing peptidase (MPP), intermediate cleaving peptidase (XPNPEP3/Icp55), mitochondrial intermediate peptidase (MIP/Oct1), mitochondrial rhomboid protease (PARL/Pcp1), and LON/Pim1 protease. (B) The transcription factor ATFS-1 contains dual targeting information, a mitochondrial targeting signal at the amino terminus, and a nuclear localization signal (NLS). In normal cells, ATFS-1 is efficiently imported into mitochondria and degraded by the Lon protease in the matrix. When under stress conditions the protein import activity of mitochondria is reduced (due to lower Δψ, impaired mtHsp70 activity, or peptides exported by the peptide transporter HAF-1), some ATFS-1 molecules accumulate in the cytosol and can be imported into the nucleus, leading to induction of an unfolded protein response (UPRmt).

Regulation of PINK1/Parkin-Induced Mitophagy by the Activity of the Mitochondrial Protein Import Machinery

Figure 5.  Mitochondrial Dynamics and Disease

(A) In healthy cells, the kinase PINK1 is partially imported into mitochondria in a membrane potential (Δψ)-dependent manner and processed by the inner membrane rhomboid protease PARL, which cleaves within the transmembrane segment and generates a destabilizing N terminus, followed by retro-translocation of cleaved PINK1 into the cytosol and degradation by the ubiquitin-proteasome system (different views have been reported if PINK1 is first processed by MPP or not; Greene et al., 2012, Kato et al., 2013 and Yamano and Youle, 2013). Dissipation of Δψ in damaged mitochondria leads to an accumulation of unprocessed PINK1 at the TOM complex and the recruitment of the ubiquitin ligase Parkin to mitochondria. Mitofusin 2 is phosphorylated by PINK1 and likely functions as receptor for Parkin. Parkin mediates ubiquitination of mitochondrial outer membrane proteins (including mitofusins), leading to a degradation of damaged mitochondria by mitophagy. Mutations of PINK1 or Parkin have been observed in monogenic cases of Parkinson’s disease. (B) The inner membrane fusion protein OPA1/Mgm1 is present in long and short isoforms. A balanced formation of the isoforms is a prerequisite for the proper function of OPA1/Mgm1. The precursor of OPA1/Mgm1 is imported by the TOM and TIM23 complexes. A hydrophobic segment of the precursor arrests translocation in the inner membrane, and the amino-terminal targeting signal is cleaved by MPP, generating the long isoforms. In yeast mitochondria, the import motor PAM drives the Mgm1 precursor further toward the matrix such that a second hydrophobic segment is cleaved by the inner membrane rhomboid protease Pcp1, generating the short isoform (s-Mgm1). In mammals, the m-AAA protease is likely responsible for the balanced formation of long (L) and short (S) isoforms of OPA1. A further protease, OMA1, can convert long isoforms into short isoforms in particular under stress conditions, leading to an impairment of mitochondrial fusion and thus to fragmentation of mitochondria.

….

Mitochondrial research is of increasing importance for the molecular understanding of numerous diseases, in particular of neurodegenerative disorders. The well-established connection between the pathogenesis of Parkinson’s disease and mitochondrial protein import has been discussed above. Several observations point to a possible connection of mitochondrial protein import with the pathogenesis of Alzheimer’s disease, though a direct role of mitochondria has not been demonstrated so far. The amyloid-β peptide (Aβ), which is generated from the amyloid precursor protein (APP), was found to be imported into mitochondria by the TOM complex, to impair respiratory activity, and to enhance ROS generation and fragmentation of mitochondria (Hansson Petersen et al., 2008, Ittner and Götz, 2011 and Itoh et al., 2013). An accumulation of APP in the TOM and TIM23 import channels has also been reported (Devi et al., 2006). The molecular mechanisms of how mitochondrial activity and dynamics may be altered by Aβ (and possibly APP) and how mitochondrial alterations may impact on the pathogenesis of Alzheimer’s disease await further analysis.

It is tempting to speculate that regulatory changes in mitochondrial protein import may be involved in tumor development. Cancer cells can shift their metabolism from respiration toward glycolysis (Warburg effect) (Warburg, 1956, Frezza and Gottlieb, 2009, Diaz-Ruiz et al., 2011 and Nunnari and Suomalainen, 2012). A glucose-induced downregulation of import of metabolite carriers into mitochondria may represent one of the possible mechanisms during metabolic shift to glycolysis. Such a mechanism has been shown for the carrier receptor Tom70 in yeast mitochondria (Schmidt et al., 2011). A detailed analysis of regulation of mitochondrial preprotein translocases in healthy mammalian cells as well as in cancer cells will represent an important task for the future.

Conclusion

In summary, the concept of the “mitochondrial protein import machinery as regulatory hub” will promote a rapidly developing field of interdisciplinary research, ranging from studies on molecular mechanisms to the analysis of mitochondrial diseases. In addition to identifying distinct regulatory mechanisms, a major challenge will be to define the interactions between different machineries and regulatory processes, including signaling networks, preprotein translocases, bioenergetic complexes, and machineries regulating mitochondrial membrane dynamics and contact sites, in order to understand the integrative system controlling mitochondrial biogenesis and fitness.

2.1.3.9 Exosome Transfer from Stromal to Breast Cancer Cells Regulates Therapy Resistance Pathways

MC Boelens, Tony J. Wu, Barzin Y. Nabet, et al.
Cell 23 Oct 2014; 159(3): 499–513
http://www.sciencedirect.com/science/article/pii/S0092867414012392

Highlights

  • Exosome transfer from stromal to breast cancer cells instigates antiviral signaling
    • RNA in exosomes activates antiviral STAT1 pathway through RIG-I
    • STAT1 cooperates with NOTCH3 to expand therapy-resistant cells
    • Antiviral/NOTCH3 pathways predict NOTCH activity and resistance in primary tumors

Summary

Stromal communication with cancer cells can influence treatment response. We show that stromal and breast cancer (BrCa) cells utilize paracrine and juxtacrine signaling to drive chemotherapy and radiation resistance. Upon heterotypic interaction, exosomes are transferred from stromal to BrCa cells. RNA within exosomes, which are largely noncoding transcripts and transposable elements, stimulates the pattern recognition receptor RIG-I to activate STAT1-dependent antiviral signaling. In parallel, stromal cells also activate NOTCH3 on BrCa cells. The paracrine antiviral and juxtacrine NOTCH3 pathways converge as STAT1 facilitates transcriptional responses to NOTCH3 and expands therapy-resistant tumor-initiating cells. Primary human and/or mouse BrCa analysis support the role of antiviral/NOTCH3 pathways in NOTCH signaling and stroma-mediated resistance, which is abrogated by combination therapy with gamma secretase inhibitors. Thus, stromal cells orchestrate an intricate crosstalk with BrCa cells by utilizing exosomes to instigate antiviral signaling. This expands BrCa subpopulations adept at resisting therapy and reinitiating tumor growth.

stromal-communication-with-cancer-cells

stromal-communication-with-cancer-cells

Graphical Abstract

2.1.3.10 Emerging concepts in bioenergetics and cancer research

Obre E, Rossignol R
Int J Biochem Cell Biol. 2015 Feb; 59:167-81
http://dx.doi.org:/10.1016/j.biocel.2014.12.008

The field of energy metabolism dramatically progressed in the last decade, owing to a large number of cancer studies, as well as fundamental investigations on related transcriptional networks and cellular interactions with the microenvironment. The concept of metabolic flexibility was clarified in studies showing the ability of cancer cells to remodel the biochemical pathways of energy transduction and linked anabolism in response to glucose, glutamine or oxygen deprivation. A clearer understanding of the large-scale bioenergetic impact of C-MYC, MYCN, KRAS and P53 was obtained, along with its modification during the course of tumor development. The metabolic dialog between different types of cancer cells, but also with the stroma, also complexified the understanding of bioenergetics and raised the concepts of metabolic symbiosis and reverse Warburg effect. Signaling studies revealed the role of respiratory chain-derived reactive oxygen species for metabolic remodeling and metastasis development. The discovery of oxidative tumors in human and mice models related to chemoresistance also changed the prevalent view of dysfunctional mitochondria in cancer cells. Likewise, the influence of energy metabolism-derived oncometabolites emerged as a new means of tumor genetic regulation. The knowledge obtained on the multi-site regulation of energy metabolism in tumors was translated to cancer preclinical studies, supported by genetic proof of concept studies targeting LDHA, HK2, PGAM1, or ACLY. Here, we review those different facets of metabolic remodeling in cancer, from its diversity in physiology and pathology, to the search of the genetic determinants, the microenvironmental regulators and pharmacological modulators.

2.1.3.11 Protecting the mitochondrial powerhouse

M Scheibye-Knudsen, EF Fang, DL Croteau, DM Wilson III, VA Bohr
Trends in Cell Biol, Mar 2015; 25(3):158–170

Highlights

  • Mitochondrial maintenance is essential for cellular and organismal function.
    • Maintenance includes reactive oxygen species (ROS) regulation, DNA repair, fusion–fission, and mitophagy.
    • Loss of function of these pathways leads to disease.

Mitochondria are the oxygen-consuming power plants of cells. They provide a critical milieu for the synthesis of many essential molecules and allow for highly efficient energy production through oxidative phosphorylation. The use of oxygen is, however, a double-edged sword that on the one hand supplies ATP for cellular survival, and on the other leads to the formation of damaging reactive oxygen species (ROS). Different quality control pathways maintain mitochondria function including mitochondrial DNA (mtDNA) replication and repair, fusion–fission dynamics, free radical scavenging, and mitophagy. Further, failure of these pathways may lead to human disease. We review these pathways and propose a strategy towards a treatment for these often untreatable disorders.

Discussion

Radoslav Bozov –

Larry, pyruvate is a direct substrate for synthesizing pyrimidine rings, as well as C-13 NMR study proven source of methyl groups on SAM! Think about what cancer cells care for – dis-regulated growth through ‘escaped’ mutability of proteins, ‘twisting’ pathways of ordered metabolism space-time wise! mtDNA is a back up, evolutionary primitive, however, primary system for pulling strings onto cell cycle events. Oxygen (never observed single molecule) pulls up electron negative light from emerging super rich energy carbon systems. Therefore, ATP is more acting like a neutralizer – resonator of space-energy systems interoperability! You cannot look at a compartment / space independently , as dimension always add 1 towards 3+1.

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Warburg Effect Revisited – 2

Writer and Curator: Larry H. Bernstein, MD, FCAP

Finding Dysregulation in the Cancer Cell

2.1.         Warburg Effect Revisited

One of the great observations of the 20th century was the behavior of cancer cells to proliferate and rely on anaerobic glycolysis for the source of energy.  This was a restatement of the Pasteur effect, described 60 years earlier by the great French scientist in yeast experiments.  The experiments with yeast were again reperformed by Jose EDS Roselino, a Brazilian biochemist, who established an explanation for it 50 years after Warburg.  It is quite amazing the mitochondria were not yet discovered at the time that Warburg carried out the single-cell thickness measurements in his respiratory apparatus. He concluded from the observation that the cancer cells grew in a media that became acidic from producing lactic acid, that the cells were dysfunctional in the utilization of oxygen, as nonmalignant cells efficiently utilized oxygen. He also related the metabolic events to observations made by Meyerhof.  The mitochondria and the citric acid cycle at this time had not yet been discovered, and the latter was, worked out by Hans Krebs and Albert Szent-Gyorgi, both of whom worked with him on mitochondrial metabolism.  The normal cell utilizes glucose efficiently and lipids as well, generating energy through oxidative phosphorylation, with the production of ATP in a manner previously described in these posts.  Greater clarity was achieved with the discovery of Coenzyme A, and finally the electron transport chain (ETC).  This requires that the pyruvate be directed into the tricarboxylic acid cycle and to go through a series of reactions producing succinate and finally malate.

The following great achievements were made with regard to elucidating these processes:

1922 Archibald Vivian Hill United Kingdom “for his discovery relating to the production of heat in the muscle[26]
Otto Fritz Meyerhof Germany “for his discovery of the fixed relationship between the consumption of oxygen and the metabolism of lactic acid in the muscle”[26]
1931 Otto Heinrich Warburg Germany “for his discovery of the nature and mode of action of the respiratory enzyme[34]
1937 Albert Szent-Györgyi von Nagyrapolt Hungary “for his discoveries in connection with the biological combustion processes, with special reference to vitamin C and the catalysis of fumaric acid[40]
1953 Sir Hans Adolf Krebs United Kingdom “for his discovery of the citric acid cycle[53]
Fritz Albert Lipmann United States “for his discovery of co-enzyme A and its importance for intermediary metabolism”[53]
1955 Axel Hugo Theodor Theorell Sweden “for his discoveries concerning the nature and mode of action of oxidation enzymes”[55]
1978 Peter D. Mitchell United Kingdom “for his contribution to the understanding of biological energy transfer through the formulation of the chemiosmotic theory[77]
1997 Paul D. Boyer United States “for their elucidation of the enzymatic mechanism underlying the synthesis of adenosine triphosphate (ATP)”[96]
John E. Walker United Kingdom

 

 1967  Manfred Eigen   and the other half jointly to:

Ronald George Wreyford Norrish and Lord George Porter for their studies of extremely fast chemical reactions, effected by disturbing the equlibrium by means of very short pulses of energy.

1965   FRANÇOIS JACOB , ANDRÉ LWOFF And JACQUES MONOD for their discoveries concerning genetic control of enzyme and virus synthesis.

1964 KONRAD BLOCH And FEODOR LYNEN for their discoveries concerning the mechanism and regulation of the cholesterol and fatty acid metabolism.

If there is a more immediate need for energy (as in stressed muscular activity) with net oxygen insufficiency, the pyruvate is converted to lactic acid, with acidemia, and with much less ATP production, but the lactic academia and the energy deficit is subsequently compensated for.    The observation made by Jose EDS Rosalino was that yeast grown in a soil deficient in oxygen don’t put down roots.

^I. Topisirovic and N. Sonenberg

Cold Spring Harbor Symposia on Quantitative Biology, Volume LXXVI

http://dx.doi.org:/10.1101/sqb.2011.76.010785 ”A prominent feature of cancer cells is the use of aerobic glycolysis under conditions in which oxygen levels are sufficient to support energy production in the mitochondria (Jones and Thompson 2009; Cairns et al. 2010). This phenomenon, named the “Warburg effect,” after its discoverer Otto Warburg, is thought to fuel the biosynthetic requirements of the neoplastic growth (Warburg 1956; Koppenol et al. 2011) and has recently been acknowledged as one of the hallmarks of cancer (Hanahan and Weinberg 2011). mRNA translation is the most energy-demanding process in the cell (Buttgereit and Brand 1995).

Again, the use of aerobic glycolysis expression has been twisted.”

To understand my critical observation consider this: Aerobic glycolysis is the carbon flow that goes from Glucose to CO2 and water (includes Krens cycle and respiratory chain for the restoration of NAD, FAD etc.

Anerobic glyclysis is the carbon flow that goes from glucose to lactate. It uses conversion of pyruvate to lactate to regenerate NAD.

“Pasteur effect” is an expression coined by Warburg, which refers to the reduction in the carbon flow from glucose when oxygen is offered to yeasts. The major reason for that is in general terms, derived from the fact that carbon flow is regulated by several cell requirements but mainly by the ATP needs of the cell. Therefore, as ATP is generated 10 more efficiently in aerobiosis than under anaerobiosis, less carbon flow is required under aerobiosis than under anaerobiosis to maintain ATP levels. Warburg, after searching for the same regulatory mechanism in normal and cancer cells for comparison found that transformed cell continued their large flow of glucose carbons to lactate despite the presence of oxygen.

So, it is wrong to describe that aerobic glycolysis continues in the presence of oxygen. It is what it is expected to occur. The wrong thing is that anaerobic glycolysis continues under aerobiosis.
^Aurelian Udristioiu (comment)
In cells, the immediate energy sources involve glucose oxidation. In anaerobic metabolism, the donor of the phosphate group is adenosine triphosphate (ATP), and the reaction is catalyzed via the hexokinase or glucokinase: Glucose +ATP-Mg²+ = Glucose-6-phosphate (ΔGo = – 3.4 kcal/mol with hexokinase as the co-enzyme for the reaction.).

In the following step, the conversion of G-6-phosphate into F-1-6-bisphosphate is mediated by the enzyme phosphofructokinase with the co-factor ATP-Mg²+. This reaction has a large negative free energy difference and is irreversible under normal cellular conditions. In the second step of glycolysis, phosphoenolpyruvic acid in the presence of Mg²+ and K+ is transformed into pyruvic acid. In cancer cells or in the absence of oxygen, the transformation of pyruvic acid into lactic acid alters the process of glycolysis.

The energetic sum of anaerobic glycolysis is ΔGo = -34.64 kcal/mol. However a glucose molecule contains 686kcal/mol and, the energy difference (654.51 kcal) allows the potential for un-controlled reactions during carcinogenesis. The transfer of electrons from NADPH in each place of the conserved unit of energy transmits conformational exchanges in the mitochondrial ATPase. The reaction ADP³+ P²¯ + H²à ATP + H2O is reversible. The terminal oxygen from ADP binds the P2¯ by forming an intermediate pentacovalent complex, resulting in the formation of ATP and H2O. This reaction requires Mg²+ and an ATP-synthetase, which is known as the H+-ATPase or the Fo-F1-ATPase complex. Intracellular calcium induces mitochondrial swelling and aging. [12].

The known marker of monitoring of treatment in cancer diseases, lactate dehydrogenase (LDH) is an enzyme that is localized to the cytosol of human cells and catalyzes the reversible reduction of pyruvate to lactate via using hydrogenated nicotinamide deaminase (NADH) as co-enzyme.

The causes of high LDH and high Mg levels in the serum include neoplastic states that promote the high production of intracellular LDH and the increased use of Mg²+ during molecular synthesis in processes pf carcinogenesis (Pyruvate acid>> LDH/NADH >>Lactate acid + NAD), [13].

The material we shall discuss explores in more detail the dysmetabolism that occurs in cancer cells.

Is the Warburg Effect the Cause or the Effect of Cancer: A 21st Century View?
http://pharmaceuticalintelligence.com/2014/06/21/is-the-warburg-effect-the-cause-or-the-effect-of-cancer-a-21st-century-view-2/

Warburg Effect Revisited
http://pharmaceuticalintelligence.com/2013/11/28/warburg-effect-revisited/

AMPK Is a Negative Regulator of the Warburg Effect and Suppresses Tumor Growth In Vivo
http://pharmaceuticalintelligence.com/2013/03/12/ampk-is-a-negative-regulator-of-the-warburg-effect-and-suppresses-tumor-growth-in-vivo/

AKT Signaling Variable Effects
http://pharmaceuticalintelligence.com/2013/03/04/akt-signaling-variable-effects/

Otto Warburg, A Giant of Modern Cellular Biology
http://pharmaceuticalintelligence.com/2012/11/02/otto-warburg-a-giant-of-modern-cellular-biology/

The Metabolic View of Epigenetic Expression
http://pharmaceuticalintelligence.com/2015/03/28/the-metabolic-view-of-epigenetic-expression/

Metabolomics Summary and Perspective
http://pharmaceuticalintelligence.com/2014/10/16/metabolomics-summary-and-perspective/

2.1.1       Cancer Metabolism

2.1.1.1  Oncometabolites: linking altered  metabolism with cancer

Ming Yang, Tomoyoshi Soga, and Patrick J. Pollard
J Clin Invest Sep 2013; 123(9):3652–3658
http://dx.doi.org:/10.1172/JCI67228

The discovery of cancer-associated mutations in genes encoding key metabolic enzymes has provided a direct link between altered metabolism and cancer. Advances in mass spectrometry and nuclear magnetic resonance technologies have facilitated high-resolution metabolite profiling of cells and tumors and identified the accumulation of metabolites associated with specific gene defects. Here we review the potential roles of such “oncometabolites” in tumor evolution and as clinical biomarkers for the detection of cancers characterized by metabolic dysregulation.

The emerging interest in metabolites whose abnormal accumulation causes both metabolic and nonmetabolic dysregulation and potential transformation to malignancy (herein termed “oncometabolites”) has been fueled by the identification of cancerassociated mutations in genes encoding enzymes with significant roles in cellular metabolism (1–5). Loss-of-function mutations in genes encoding the Krebs cycle enzymes fumarate hydratase (FH) and succinate dehydrogenase (SDH) cause the accumulation of fumarate and succinate, respectively (6), whereas gain-offunction isocitrate dehydrogenase (IDH) mutations increase levels of D–2-hydroxyglutarate (D-2HG) (7, 8). These metabolites have been implicated in the dysregulation of cellular processes including the competitive inhibition of α-ketoglutarate–dependent (α-KG–dependent) dioxygenase enzymes (also known as 2-oxoglutarate–dependent dioxgenases) and posttranslational modification of proteins (1, 4, 9–11). To date, several lines of biochemical and genetic evidence support roles for fumarate, succinate, and D-2HG in cellular transformation and oncogenesis (3, 12).

The Journal of Clinical Investigation   http://www.jci.org   Volume 123   Number 9   September 2013

ventional gene sequencing methods may lead to false positives due to genetic polymorphism and sequencing artifacts (98). In comparison, screening for elevated 2HG levels is a sensitive and specific approach to detect IDH mutations in tumors. Whereas patient sera/plasma can be assessed in the case of AML (7, 8, 21, 99), exciting advances with proton magnetic resonance spectroscopy (MRS) have been made in the noninvasive detection of 2HG in patients with gliomas (100–103). Using MRS sequence optimization and spectral fitting techniques, Maher and colleagues examined 30 patients with glioma and showed that the detection of 2HG correlated 100% with the presence of IDH1 or IDH2 mutations (102). Andronesi et al. further demonstrated that two-dimensional correlation spectroscopy could effectively distinguish 2HG from chemically similar metabolites present in the brain (103). Negative IHC staining for SDHB correlates with the presence of SDH mutations, whether in SDHB, SDHC, or SDHD (104). This finding is most likely explained by the fact that mutations in any of the four subunits of SDH can destabilize the entire enzyme complex. PGLs/PCCs associated with an SDHA mutation show negative staining for SDHA as well as SDHB (105). Therefore, IHC staining for SDHB is a useful diagnostic tool to triage patients for genetic testing of any SDH mutation, and subsequent staining for the other subunits may further narrow the selection of genes to be tested. In contrast, detection of FH protein is often evident in HLRCC tumors due to retention of the nonfunctional mutant allele (106). However, staining of cysts and tumors for 2SC immunoreactivity reveals a striking correlation between FH inactivation and the presence of 2SC-modified protein (2SCP), which is absent in non-HLRCC tumors and normal tissue controls (106). IHC staining for 2SCP thus provides a robust diagnostic biomarker for FH deficiency (107).

Therapeutic targeting Because D-2HG is a product of neomorphic enzyme activities, curtailing the D-2HG supply by specifically inhibiting the mutant IDH enzymes provides an elegant approach to target IDH-mutant cancers. Indeed, recent reports of small-molecule inhibitors against mutant forms of IDH1 and IDH2 demonstrated the feasibility of this method. An inhibitor against IDH2 R140Q was shown to reduce both intracellular and extracellular levels of D-2HG, suppress cell growth, and increase differentiation of primary human AML cells (108). Similarly, small-molecule inhibition of IDH1 R132H suppressed colony formation and increased tumor cell differentiation in a xenograft model for IDH1 R132H glioma (58). The inhibitors exhibited a cytostatic rather than cytotoxic effect, and therefore their therapeutic efficacy over longer time periods may need further assessment (109). Letouzé et al. showed that the DNA methytransferase inhibitor decitabine could repress the migration capacities of SDHB-mutant cells (40). However, for SDH- and FH-associated cancers, a synthetic lethality approach is worth exploring because of the pleiotrophic effects associated with succinate and fumarate accumulation.

Outlook The application of next-generation sequencing technologies in the field of cancer genomics has substantially increased our understanding of cancer biology. Detection of germline and somatic mutations in specific tumor types not only expands the current repertoire of driver mutations and downstream effectors in tumorigenesis, but also sheds light on how oncometabolites may exert their oncogenic roles. For example, the identification of mutually exclusive mutations in IDH1 and TET2 in AML led to the characterization of TET2 as a major pathological target of D-2HG (34, 110). Additionally, the discovery of somatic CUL3, SIRT1, and NRF2 mutations in sporadic PRCC2 converges with FH mutation in HLRCC, in which NRF2 activation is a consequence of fumarate-mediated succination of KEAP1, indicating the functional prominence of the NRF2 pathway in PRCC2 (73). In light of this, the identification of somatic mutations in genes encoding the chromatin-modifying enzymes histone H3K36 methyltransferase (SETD2), histone H3K4 demethylase JARID1C (KDM5C), histone H3K27 demethylase UTX (KDM6A), and the SWI/SNF chromatin remodelling complex gene PBRM1 in clear cell renal cell carcinoma (111–113) highlights the importance of epigenetic modulation in human cancer and raises the potential for systematic testing in other types of tumors such as those associated with FH mutations. Technological advances such as those in gas and liquidchromatography mass spectrometry (114, 115) and nuclear magnetic resonance imaging (102) have greatly improved the ability to measure low-molecular-weight metabolites in tumor samples with high resolution (116). Combined with metabolic flux analyses employing isotope tracers and mathematical modeling, modern-era metabolomic approaches can provide direct pathophysiological insights into tumor metabolism and serve as an excellent tool for biomarker discovery. Using a data-driven approach, Jain and colleagues constructed the metabolic profiles of 60 cancer cell lines and discovered glycine consumption as a key metabolic event in rapidly proliferating cancer cells (117), thus demonstrating the power of metabolomic analyses and the relevance to future cancer research and therapeutics.

Acknowledgments The Cancer Biology and Metabolism Group is funded by Cancer Research UK and the European Research Council under the European Community’s Seventh Framework Programme (FP7/20072013)/ERC grant agreement no. 310837 to Dr. Pollard. Professor Soga receives funding from a Grant-in-Aid for scientific research on Innovative Areas, Japan (no. 22134007), and the Yamagata Prefectural Government and City of Tsuruoka.

Address correspondence to: Patrick J. Pollard, Cancer Biology and Metabolism Group, Nuffield Department of Medicine, Henry Wellcome Building for Molecular Physiology, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, United Kingdom. Phone: 44.0.1865287780; Fax: 44.0.1865287787; E-mail:  patrick.pollard@well.ox.ac.uk.

  1. Yang M, Soga T, Pollard PJ, Adam J. The emerging role of fumarate as an oncometabolite. Front Oncol. 2012;2:85. 2. Ward PS, Thompson CB. Metabolic reprogramming: a cancer hallmark even warburg did not anticipate. Cancer Cell. 2012;21(3):297–308. 3. Vander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science. 2009; 324(5930):1029–1033. 4. Thompson CB. Metabolic enzymes as oncogenes or tumor suppressors. N Engl J Med. 2009; 360(8):813–815. 5. Schulze A, Harris AL. How cancer metabolism is tuned for proliferation and vulnerable to disruption. Nature. 2012;491(7424):364–373.
  1. Pollard PJ, et al. Accumulation of Krebs cycle intermediates and over-expression of HIF1alpha in tumours which result from germline FH and SDH mutations. Hum Mol Genet. 2005; 14(15):2231–2239. 7. Ward PS, et al. The common feature of leukemiaassociated IDH1 and IDH2 mutations is a neomorphic enzyme activity converting alpha-ketoglutarate to 2-hydroxyglutarate. Cancer Cell. 2010; 17(3):225–234.

Because D-2HG is a product of neomorphic enzyme activities, curtailing the D-2HG supply by specifically inhibiting the mutant IDH enzymes provides an elegant approach to target IDH-mutant cancers. Indeed, recent reports of small-molecule inhibitors against mutant forms of IDH1 and IDH2 demonstrated the feasibility of this method. An inhibitor against IDH2 R140Q was shown to reduce both intracellular and extracellular levels of D-2HG, suppress cell growth, and increase differentiation of primary human AML cells (108). Similarly, small-molecule inhibition of IDH1 R132H suppressed colony formation and increased tumor cell differentiation in a xenograft model for IDH1 R132H glioma (58). The inhibitors exhibited a cytostatic rather than cytotoxic effect, and therefore their therapeutic efficacy over longer time periods may need further assessment (109). Letouzé et al. showed that the DNA methytransferase inhibitor decitabine could repress the migration capacities of SDHB-mutant cells (40). However, for SDH- and FH-associated cancers, a synthetic lethality approach is worth exploring because of the pleiotrophic effects associated with succinate and fumarate accumulation.

Technological advances such as those in gas and liquid chromatography mass spectrometry (114, 115) and nuclear magnetic resonance imaging (102) have greatly improved the ability to measure low-molecular-weight metabolites in tumor samples with high resolution (116). Combined with metabolic flux analyses employing isotope tracers and mathematical modeling, modern-era metabolomic approaches can provide direct pathophysiological insights into tumor metabolism and serve as an excellent tool for biomarker discovery. Using a data-driven approach, Jain and colleagues constructed the metabolic profiles of 60 cancer cell lines and discovered glycine consumption as a key metabolic event in rapidly proliferating cancer cells (117), thus demonstrating the power of metabolomic analyses and the relevance to future cancer research and therapeutics.

Figure 1 D-2HG produced by mutant IDH1/2 affects metabolism and epigenetics by modulating activities of α-KG–dependent oxygenases. Wild-type IDH1 and IDH2 catalyze the NADP+-dependent reversible conversion of isocitrate to α-KG, whereas cancer-associated gain-of-function mutations enable mutant IDH1/2 (mIDH1/2) to catalyze the oxidation of α-KG to D-2HG, using NADPH as a cofactor. Because D-2HG is structurally similar to α-KG, its accumulation can modulate the activities of α-KG–utilizing dioxygenases. Inhibition of 5mC hydroxylase TET2 and the KDMs results in increased CpG island methylation and increased histone methylation marks, respectively, thus blocking lineage-specific cell differentiation. Inhibition of collagen prolyl and lysyl hydroxylases (C-P4Hs and PLODs, respectively) leads to impaired collagen maturation and disrupted basement membrane formation. D-2HG can also stimulate the activities of HIF PHDs, leading to enhanced HIF degradation and a diminished HIF response, which are associated with increased soft agar growth of human astrocytes and growth factor independence of leukemic cells. Together these processes exert pleiotrophic effects on cell signaling and gene expression that probably contribute to the malignancy of IDH1/2-mutant cells.
Figure 2 Candidate oncogenic mechanisms of succinate and fumarate accumulation. SDH and FH are Krebs cycle enzymes and tumor suppressors. Loss-of-function mutations in SDH and FH result in abnormal accumulation of Krebs cycle metabolites succinate (Succ) and fumarate (Fum), respectively, both of which can inhibit the activities of α-KG–dependent oxygenases. Inhibition of HIF PHDs leads to activation of HIF-mediated pseudohypoxic response, whereas inhibition of KDMs and TET family of 5mC hydroxylases causes epigenetic alterations. Fumarate is electrophilic and can also irreversibly modify cysteine residues in proteins by succination. Succination of KEAP1 in FH deficiency results in the constitutive activation of the antioxidant defense pathway mediated by NRF2, conferring a reductive milieu that promotes cell proliferation. Succination of the Krebs cycle enzyme Aco2 impairs aconitase activity in Fh1-deficient MEFs. Fumarate accumulation may also affect cytosolic pathways by inhibiting the reactions involved in the biosynthesis of arginine and purine. AcCoA, acetyl CoA; Mal, malate; OAA, oxaloacetate; Succ-CA, succinyl CoA.

2.1.1.2. Emerging concepts: linking hypoxic signaling and cancer metabolism.

Lyssiotis CA, Vander-Heiden MG, Muñoz-Pinedo C, Emerling BM.
Cell Death Dis. 2012 May 3; 3:e303
http://dx.doi.org:/10.1038/cddis.2012.41

The Joint Keystone Symposia on Cancer and Metabolism and Advances in Hypoxic Signaling: From Bench to Bedside were held in Banff, Alberta, Canada from 12 to 17 February 2012. Drs. Reuben Shaw and David Sabatini organized the Cancer and Metabolism section, and Drs. Volker Haase, Cormac Taylor, Johanna Myllyharju and Paul Schumacker organized the Advances in Hypoxic Signaling section. Accumulating data illustrate that both hypoxia and rewired metabolism influence cancer biology. Indeed, these phenomena are tightly coupled, and a joint meeting was held to foster interdisciplinary interactions and enhance our understanding of these two processes in neoplastic disease. In this report, we highlight the major themes of the conference paying particular attention to areas of intersection between hypoxia and metabolism in cancer.

One opening keynote address was delivered by Craig Thompson (Memorial Sloan-Kettering, USA), in which he provided a comprehensive perspective on the current thinking around how altered metabolism supports cancer cell growth and survival, and discussed areas likely to be important for future discovery. In particular, Thompson highlighted the essential roles of glucose and glutamine in cell growth, how glucose- and glutamine-consuming processes are rewired in cancer and how this rewiring facilitates anabolic metabolism. These topics were at the core of many of the metabolism presentations that described in detail how some metabolic alterations contribute to the properties of transformed cells.

The other keynote address was delivered by Peter Ratcliffe (University of Oxford, UK), in which he provided a historical perspective on the progress of how signaling events sense oxygen. Mammals have evolved multiple acute and long-term adaptive responses to low oxygen levels (hypoxia). This response prevents a disparity in ATP utilization and production that would otherwise result in a bioenergetic collapse when oxygen level is low. Multiple effectors have been proposed to mediate the response to hypoxia including prolyl hydroxylases, AMPK, NADPH oxidases and the mitochondrial complex III. Currently, however, the precise mechanism by which oxygen is sensed in various physiological contexts remains unknown. Indeed, this was an active point of debate, with Peter Ratcliffe favoring the prolyl hydroxylase PHD2 as the primary cellular oxygen sensor.

Anabolic glucose metabolism and the Warburg effect

Nearly a century ago, Warburg noted that cancer tissues take up glucose in excess than most normal tissues and secrete much of the carbon as lactate. Recently, headway has been made toward determining how the enhanced glucose conversion to lactate occurs and contributes to cell proliferation and survival. Heather Christofk (University of California, Los Angeles, USA) and John Cleveland (the Scripps Research Institute, USA) described a role for the lactate/pyruvate transporter MCT-1 in carbon secretion, and suggested that blocking lactate or pyruvate transport may be a strategy to target glucose metabolism in cancer cells. Kun-Liang Guan (University of California, San Diego, USA) described a novel feedback loop to control glucose metabolism in highly glycolytic cells. Specifically, he discussed how glucose-derived acetyl-CoA can be used as a substrate to modify two enzymes involved in glucose metabolism, pyruvate kinase M2 (PKM2) and phosphoenolpyruvate carboxylase (PEPCK). In both cases, acetylation leads to protein degradation and decreased glycolysis and gluconeogenesis, respectively. Data presented from Matthew Vander Heiden’s laboratory (Koch Institute/MIT, USA) illustrated that loss of pyruvate kinase activity can accelerate tumor growth, suggesting that the regulation of glycolysis may be more complex than previously appreciated. Almut Schulze (London Research Institute, UK) discussed a novel regulatory role for phosphofructokinase in controlling glucose metabolism and Jeffrey Rathmell (Duke University, USA) discussed parallels between glucose metabolism in cancer cells and lymphocytes that suggest many of these phenotypes could be a feature of rapidly dividing cells.

Glutamine addiction

Cancer cells also consume glutamine to support proliferation and survival. Alfredo Csibi (Harvard Medical School, USA) described how mTORC1 promotes glutamine utilization by indirectly regulating the activity of glutamate dehydrogenase. This work united two major themes at the meeting, mTOR signaling and glutamine metabolism, highlighting the interconnectedness of signal transduction and metabolic regulation. Richard Cerione (Cornell University, USA) described a small molecule inhibitor of glutaminase that can be used to target glutamine-addicted cancer cells. Christian Metallo (University of California, San Diego, USA), Andrew Mullen (University of Texas Southwestern Medical School, USA) and Patrick Ward (Memorial Sloan-Kettering, USA) presented data demonstrating that the carbon skeleton of glutamine can be incorporated into newly synthesized lipids. This contribution of glutamine to lipid synthesis was most pronounced in hypoxia or when the mitochondrial electron transport chain was compromised.

Signal transduction and metabolism

The protein kinases AMPK and mTOR can function as sensors of metabolic impairment, whose activation by energy stress controls multiple cellular functions. Grahame Hardie (University of Dundee, UK) and Reuben Shaw (Salk Institute, USA) highlighted novel roles for AMPK, including inhibition of viral replication, and the control of histone acetylation via phosphorylation of class IIa HDACs, respectively. Brandon Faubert (McGill University, USA) reported on an AMPK-dependent effect on glucose metabolism in unstressed cells. Brendan Manning (Harvard Medical School, USA) found that chronic activation of mTOR in the mouse liver, due to genetic ablation of this complex, promotes the development of liver cancer. Kevin Williams (University of California, Los Angeles, USA) discussed how growth signaling can control both lipid and glucose metabolism by impinging on SREBP-1, a transcription factor downstream of mTOR. AMPK-independent control of mTOR was addressed by John Blenis (Harvard Medical School, USA), who discussed the possible role of mTOR stabilizing proteins as mediators of mTOR inactivation upon energetic stress. David Sabatini (Whitehead Institute/MIT, USA) discussed several aspects of amino-acid sensing by Rag GTPases and showed that constitutive activation of the Rag GTPases leads to metabolic defects in mice.

One of the outcomes of AMPK activation and mTOR inhibition is autophagy, which can provide amino acids and fatty acids to nutrient-deprived cells. Ana Maria Cuervo (Albert Einstein College of Medicine, USA) and Eileen White (Rutgers University, USA) illuminated the role of chaperone-mediated autophagy (CMA) and macroautophagy, respectively, in tumor survival. White described a role for macroautophagy in the regulation of mitochondrial fitness, maintenance of TCA cycle and tumorigenesis induced by oncogenic Ras. Cuervo described how CMA is consistently elevated in tumor cells, and how its inactivation leads to metabolic impairment via p53-mediated downregulation of glycolytic enzymes.

Oncogene-specific changes to metabolism

Lewis Cantley (Harvard Medical School, USA) described a metabolic role for oncogenic Kras in the rewiring of glucose metabolism in pancreatic cancer. Specifically, Myc-mediated transcription (downstream of MEK-ERK signaling) both enhances glucose uptake and diverts glucose carbon into the nonoxidative pentose phosphate pathway to facilitate nucleotide biosynthesis. Alejandro Sweet-Cordero (Stanford University, USA) described how oncogenic Kras increases glycolysis and represses mitochondrial respiration (via decreased pyruvate dehydrogenase phosphatase 1 (PDP1) expression) in colon cancer. While these studies indicate that hyperstimulation of the Erk pathway suppresses PDH flux through suppression of PDP1, Joan Brugge (Harvard Medical School, USA) described studies showing that reduction of Erk signaling in normal epithelial cells also causes suppression of PDH flux, in this case through loss of repression of PDK4. The seemingly contradictory nature of these results highlighted an important theme emphasized throughout the week-long conference—that cellular context has an important role in shaping how oncogenic mutations or pathway activation rewires metabolism.

Targeting cancer metabolism

There was extensive discussion around targeting metabolism for cancer therapy. Metformin and phenformin, which act in part by mitochondrial complex I inhibition, can activate AMPK and influence cancer cell metabolism. Kevin Struhl (Harvard Medical School, USA) described how metformin can selectively target cancer stem cells, whereas Jessica Howell (Harvard Medical School, USA) described how the therapeutic activity of metformin relies on both AMPK and mTOR signaling to mediate its effect. Similarly, David Shackelford (University of California, Los Angeles, USA) demonstrated efficacy for phenformin in LKB1-deficient mouse models.

Several presentations, including those by Taru Muranen (Harvard Medical School, USA), Karen Vousden and Eyal Gottlieb (both from the Beatson Institute for Cancer Research, UK), provided insight into genetic control mechanisms that cancer cells use to promote survival under conditions of increased biosynthesis. As an example, Vousden illustrated how p53 loss can make cancer cells more dependent on exogenous serine. Several additional presentations, including those by Gottlieb, Richard Possemato (Whitehead Institute/MIT, USA), Michael Pollak (McGill University, USA) and Kevin Marks (Agios Pharmaceuticals, USA), also included data highlighting the important role of serine biosynthesis and metabolism in cancer growth. Collectively, these data highlight a metabolic addiction that may be therapeutically exploitable. Similarly, Cristina Muñoz-Pinedo (Institut d’Investigació Biomèdica, Spain) described how mimicking glucose deprivation with 2-deoxyglucose can cause programmed cell death and may be an effective cancer treatment.

Regulation of hypoxic responses

Peter Carmeliet (University of Leuven, Belgium) highlighted the mechanisms of resistance against VEGF-targeted therapies. Roland Wenger (University of Zurich, Switzerland) discussed the oxygen-responsive transcriptional networks and, in particular, the difference between the transcription factors HIF-1α and HIF-2α. Importantly, he demonstrated a rapid role for HIF-1α, and a later and more persistent response for HIF-2α. These results were central to a recurrent theme calling for the distinction of HIF-1α and HIF-2α target genes and how these responses mediate divergent hypoxic adaptations.

Advances in hypoxic signaling

Brooke Emerling (Harvard Medical School, USA) introduced CUB domain-containing protein 1 (CDCP1) and showed persuasive data on CDCP1 being a HIF-2α target gene involved in cell migration and metastasis, and suggested CDCP1 regulation as an attractive therapeutic target. Johannes Schodel (University of Oxford, UK) described an elegant HIF-ChIP-Seq methodology to define direct transcriptional targets of HIF in renal cancer.

Randall Johnson (University of Cambridge, UK) emphasized that loss of HIF-1α results in decreased lung metastasis. Lorenz Poellinger (Karolinska Institutet, Sweden) focused on how hypoxia can alter the epigenetic landscape of cells, and furthermore, how the disruption of the histone demethylase JMJD1A and/or the H3K9 methyltransferase G9a has opposing effects on tumor growth and HIF target gene expression.

Paul Schumacker (Northwestern University, USA) further emphasized the importance of mitochondrial ROS signaling under hypoxic conditions showing that ROS could be detected in the inter-membrane space of the mitochondria before activating signaling cascades in the cytosol. He also presented evidence for mitochondria as a site of oxygen sensing in diverse cell types. Similarly, Margaret Ashcroft (University College London, UK) argued for a critical role of mitochondria in hypoxic signaling. She presented on a family of mitochondrial proteins (CHCHD4) that influence hypoxic signaling and tumorigenesis and suggested that CHCHD4 is important for HIF and tumor progression.

2.1.1.3  Glutaminolysis: supplying carbon or nitrogen or both for cancer cells?

Dang CV
Cell Cycle. 2010 Oct 1; 9(19):3884-6

A cancer cell comprising largely of carbon, hydrogen, oxygen, phosphorus, nitrogen and sulfur requires not only glucose, which is avidly transported and converted to lactate by aerobic glycolysis or the Warburg effect, but also glutamine as a major substrate. Glutamine and essential amino acids, such as methionine, provide energy through the TCA cycle as well as nitrogen, sulfur and carbon skeletons for growing and proliferating cancer cells. The interplay between utilization of glutamine and glucose is likely to depend on the genetic make-up of a cancer cell. While the MYC oncogene induces both aerobic glycolysis and glutaminolysis, activated β-catenin induces glutamine synthesis in hepatocellular carcinoma. Cancer cells that have elevated glutamine synthetase can use glutamate and ammonia to synthesize glutamine and are hence not addicted to glutamine. As such, cancer cells have many degrees of freedom for re-programming cell metabolism, which with better understanding will result in novel therapeutic approaches.

Figure 1. Glutamine, glucose and glutamate are imported into the cytoplasm of a cell. Glucose is depicted to be converted primarily (large powder blue arrow) to lactate via aerobic glycolysis or the Warburg effect or channeled into the mitochondrion as pyruvate and converted to acetyl-CoA for oxidation. Glutamine is shown imported and used for different processes including glutaminolysis, which involves the conversion of glutamine to glutamate and ammonia by glutaminase (GLS). Glutamate is further oxidized via the TCA cycle to produce ATP and contribute anabolic carbon skeletons. Some cells can import glutamate and use ammonia to generate glutamine through glutamine synthetase (GLUL); glutamine could then be used for different purposes including glutathione synthesis (not shown).

The liver is organized into lobules, which have zones of cells around the perivenous region enriched with glutamine synthetase, which detoxifies ammonia by converting it to glutamine through the amination of glutamate (Fig. 1). As such, liver cancers vary in the degree of glutamine synthetase expression depending on the extent of anaplasia or de-differentiation. Highly undifferentiated liver cancers tend to be more glycolytic than those that retain some of the differentiated characteristics of liver cells. Furthermore, glutamine synthetase (considered as a direct target of activated β-catenin, which also induces ornithine aminotransferase and glutamate transporters) expression in liver cancers has been directly linked to β-catenin activation or mutations.  Hence, the work by Meng et al. illustrates, first and foremost, the metabolic heterogeneity amongst cancer cell lines, such that the ability to utilize ammonia instead of glutamine by Hep3B cells depends on the expression of glutamine synthetase. The Hep3B cells are capable of producing glutamine from glutamate and ammonia, as suggested by the observation that a glutamine-independent derivative of Hep3B has high expression of glutamine synthetase. In this regard, Hep3B could utilize glutamate directly for the production of α-ketoglutarate or to generate glutamine for protein synthesis or other metabolic processes, such as to import essential amino acids.  In contrast to Hep3B, other cell lines in the Meng et al. study were not demonstrated to be glutamine independent and thus become ammonia auxotrophs. Hence, the mode of glutamine or glucose utilization is dependent on the metabolic profile of cancer cells.
The roles of glutamine in different cancer cell lines are likely to be different depending on their genetic and epigenetic composition. In fact, well-documented isotopic labeling studies have demonstrated a role for glutamine to provide anapleurotic carbons in certain cancer and mammalian cell types. But these roles of glutaminolysis, whether providing nitrogen or anabolic carbons, should not be generalized as mutually exclusive features of all cancer cells. From these considerations, it is surmised that the expression of glutamine synthetase in different cancers will determine the extent by which these cancers are addicted to exogenous glutamine.

2.1.1.4  The Warburg effect and mitochondrial stability in cancer cells

Gogvadze V, Zhivotovsky B, Orrenius S.
Mol Aspects Med. 2010 Feb; 31(1):60-74
http://dx.doi.org:/10.1016/j.mam.2009.12.004

The last decade has witnessed a renaissance of Otto Warburg’s fundamental hypothesis, which he put forward more than 80 years ago, that mitochondrial malfunction and subsequent stimulation of cellular glucose utilization lead to the development of cancer. Since most tumor cells demonstrate a remarkable resistance to drugs that kill non-malignant cells, the question has arisen whether such resistance might be a consequence of the abnormalities in tumor mitochondria predicted by Warburg. The present review discusses potential mechanisms underlying the upregulation of glycolysis and silencing of mitochondrial activity in cancer cells, and how pharmaceutical intervention in cellular energy metabolism might make tumor cells more susceptible to anti-cancer treatment.

mitochondrial stabilization gr1

mitochondrial stabilization gr1

http://ars.els-cdn.com/content/image/1-s2.0-S0098299709000934-gr1.sml

Fig. 1. (1) Oligomerization of Bax is mediated by the truncated form of the BH3-only, pro-apoptotic protein Bid (tBid); (2) Bcl-2, Bcl-XL, Mcl-1, and Bcl-w, interact with the pro-apoptotic proteins, Bax and Bak, to prevent their oligomerization; (3) The anti-apoptotic protein Bcl-XL prevents tBid-induced closure of VDAC and apoptosis by maintaining VDAC in open configuration allowing ADT/ATP exchange and normal mitochondrial functioning; (4) MPT pore is a multimeric complex, composed of VDAC located in the OMM, ANT, an integral protein of the IMM, and a matrix protein, CyPD; (5) Interaction with VDAC allows hexokinase to use exclusively intramitochondrial ATP to phosphorylate glucose, thereby maintaining high rate of glycolysis.

mitochodrial stabilization gr2

mitochodrial stabilization gr2

http://ars.els-cdn.com/content/image/1-s2.0-S0098299709000934-gr2.sml

Fig. 2. Different sites of therapeutic intervention in cancer cell metabolism. (1) The non-metabolizable analog of glucose, 2-deoxyglucose, decreases ATP level in the cell; (2) 3-bromopyruvate suppresses the activity of hexokinase, and respiration in isolated mitochondria; (3) Phloretin a glucose transporter inhibitor, decreases ATP level in the cell and markedly enhances the anti-cancer effect of daunorubicin; (4) Dichloroacetate (DCA) shifts metabolism from glycolysistoglucoseoxidation;(5)Apoptolidin,aninhibitorofmitochondrialATPsynthase,inducescelldeathindifferentmalignantcelllineswhenapplied together with the LDH inhibitor oxamate (6).

Warburg Symposium

https://youtu.be/LpE6w6J3jU0

2.1.1.5 Oxidative phosphorylation in cancer cells

Giancarlo Solaini Gianluca SgarbiAlessandra Baracca

BB Acta – Bioenergetics 2011 Jun; 1807(6): 534–542
http://dx.doi.org/10.1016/j.bbabio.2010.09.003

Research Highlights

►Mitochondrial hallmarks of tumor cells.►Complex I of the respiratory chain is reduced in many cancer cells.►Oligomers of F1F0ATPase are reduced in cancer cells.►Mitochondrial membranes are critical to the life or death of cancer cells.

Evidence suggests that mitochondrial metabolism may play a key role in controlling cancer cells life and proliferation. Recent evidence also indicates how the altered contribution of these organelles to metabolism and the resistance of cancer mitochondria against apoptosis-associated permeabilization are closely related. The hallmarks of cancer growth, increased glycolysis and lactate production in tumours, have raised attention due to recent observations suggesting a wide spectrum of oxidative phosphorylation deficit and decreased availability of ATP associated with malignancies and tumour cell expansion. More specifically, alteration in signal transduction pathways directly affects mitochondrial proteins playing critical roles in controlling the membrane potential as UCP2 and components of both MPTP and oxphos complexes, or in controlling cells life and death as the Bcl-2 proteins family. Moreover, since mitochondrial bioenergetics and dynamics, are also involved in processes of cells life and death, proper regulation of these mitochondrial functions is crucial for tumours to grow. Therefore a better understanding of the key pathophysiological differences between mitochondria in cancer cells and in their non-cancer surrounding tissue is crucial to the finding of tools interfering with these peculiar tumour mitochondrial functions and will disclose novel approaches for the prevention and treatment of malignant diseases. Here, we review the peculiarity of tumour mitochondrial bioenergetics and the mode it is linked to the cell metabolism, providing a short overview of the evidence accumulated so far, but highlighting the more recent advances. This article is part of a Special Issue entitled: Bioenergetics of Cancer.

Mitochondria are essential organelles and key integrators of metabolism, but they also play vital roles in cell death and cell signaling pathways critically influencing cell fate decisions [1][2] and [3]. Mammalian mitochondria contain their own DNA (mtDNA), which encodes 13 polypeptides of oxidative phosphorylation complexes, 12S and 16S rRNAs, and 22 tRNAs required for mitochondrial function [4]. In order to synthesize ATP through oxidative phosphorylation (oxphos), mitochondria consume most of the cellular oxygen and produce the majority of reactive oxygen species (ROS) as by-products [5]. ROS have been implicated in the etiology of carcinogenesis via oxidative damage to cell macromolecules and through modulation of mitogenic signaling pathways [6][7] and [8]. In addition, a number of mitochondrial dysfunctions of genetic origin are implicated in a range of age-related diseases, including tumours [9]. How mitochondrial functions are associated with cancer is a crucial and complex issue in biomedicine that is still unravelled [10] and [11], but it warrants an extraordinary importance since mitochondria play a major role not only as energy suppliers and ROS “regulators”, but also because of their control on cellular life and death. This is of particular relevance since tumour cells can acquire resistance to apoptosis by a number of mechanisms, including mitochondrial dysfunction, the expression of anti-apoptotic proteins or by the down-regulation or mutation of pro-apoptotic proteins [12].

Cancer cells must adapt their metabolism to produce all molecules and energy required to promote tumor growth and to possibly modify their environment to survive. These metabolic peculiarities of cancer cells are recognized to be the outcome of mutations in oncogenes and tumor suppressor genes which regulate cellular metabolism. Mutations in genes including P53, RAS, c-MYC, phosphoinosine 3-phosphate kinase (PI3K), and mTOR can directly or through signaling pathways affect metabolic pathways in cancer cells as discussed in several recent reviews [13][14][15][16] and [17]. Cancer cells harboring the genetic mutations are also able to thrive in adverse environments such as hypoxia inducing adaptive metabolic alterations which include glycolysis up-regulation and angiogenesis factor release [18] and [19]. In response to hypoxia, hypoxia-induced factor 1 (HIF-1) [20], a transcription factor, is up-regulated, which enhances expression of glycolytic enzymes and concurrently it down regulates mitochondrial respiration through up-regulation of pyruvate dehydrogenase kinase 1 (PDK1) (see recent reviews [21] and [22]). However, several tumours have been reported to display high HIF-1 activity even in normoxic condition, now referred to as pseudohypoxia [23][24] and [25]. In addition, not only solid tumours present a changed metabolism with respect to matched normal tissues, hematological cell malignancies also are characterized by peculiar metabolisms, in which changes of mitochondrial functions are significant [26],[27] and [28], therefore indicating a pivotal role of mitochondria in tumours independently from oxygen availability.

Collectively, actual data show a great heterogeneity of metabolism changes in cancer cells, therefore comprehensive cellular and molecular basis for the association of mitochondrial bioenergetics with tumours is still undefined, despite the numerous studies carried out. This review briefly revisits the data which are accumulating to account for this association and highlights the more recent advances, particularly focusing on the metabolic and structural changes of mitochondria.

Mitochondria-related metabolic changes of cancer cells

Accumulating evidence indicate that many cancer cells have an higher glucose consumption under normoxic conditions with respect to normal differentiated cells, the so-called “aerobic glycolysis” (Warburg effect), a phenomenon that is currently exploited to detect and diagnose staging of solid and even hematological malignancies [27]. Since the initial publication by Otto Warburg over half a century ago [29], an enormous amount of studies on many different tumours have been carried out to explain the molecular basis of the Warburg effect. Although the regulatory mechanisms underlying aerobic and glycolytic pathways of energy production are complex, making the prediction of specific cellular responses rather difficult, the actual data seem to support the view that in order to favour the production of biomass, proliferating cells are commonly prone to satisfy the energy requirement utilizing substrates other than the complete oxidation of glucose (to CO2 and H2O). More precisely, only part (40 to 75%, according to [30]) of the cells need of ATP is obtained through the scarcely efficient catabolism of glucose to pyruvate/lactate in the cytoplasm and the rest of the ATP need is synthesized in the mitochondria through both the tricarboxylic acid (TCA) cycle (one ATP produced each acetyl moiety oxidized) and the associated oxidative phosphorylation that regenerates nicotinamide- and flavin-dinucleotides in their oxidized state(NAD+ and FAD). This might be due to the substrate availability as it was shown in HeLa cells, where replacing glucose with galactose/glutamine in the culture medium induced increased expression of oxphos proteins, suggesting an enhanced energy production from glutamine [31]. As a conclusion the authors proposed that energy substrate can modulate mitochondrial oxidative capacity in cancer cells. A direct evidence of this phenomenon was provided a few years later in glioblastoma cells, in which it was demonstrated that the TCA cycle flux is significantly sustained by anaplerotic alfa-ketoglutarate produced from glutamine and by acetyl moieties derived from the pyruvate dehydrogenase reaction where pyruvate may have an origin other than glucose [32]. The above changes are the result of genetic alteration and environmental conditions that induce many cancer cells to change their metabolism in order to synthesize molecules necessary to survive, grow and proliferate, including ribose and NADPH to synthesize nucleotides, and glycerol-3 phosphate to produce phospholipids. The synthesis of the latter molecules requires major amount of acetyl moieties that are derived from beta-oxidation of fatty acids and/or from cytosolic citrate (citrate lyase reaction) and/or from the pyruvate dehydrogenase reaction. Given the important requirement for NADPH in macromolecular synthesis and redox control, NADPH production in cancer cells besides being produced through the phosphate pentose shunt, may be significantly sustained by cytosolic isocitrate dehydrogenases and by the malic enzyme (see Ref. [33] for a recent review). Therefore, many cancer cells tend to have reduced oxphos in the mitochondria due to either or both reduced flux within the tricarboxylic acid cycle and/or respiration (Fig. 1). The latter being also caused by reduced oxygen availability, a typical condition of solid tumors, that will be discussed below.

Schematic illustration of mitochondrial metabolism and metabolic reprogramming in tumours gr1

Schematic illustration of mitochondrial metabolism and metabolic reprogramming in tumours gr1

http://ars.els-cdn.com/content/image/1-s2.0-S0005272810007024-gr1.jpg

Fig. 1. Schematic illustration of mitochondrial metabolism and metabolic reprogramming in tumours. In normal cells (A), glucose is phosphorylated by HK-I, then the major part is degraded via glycolysis to pyruvate, which prevalently enters the mitochondria, it is decarboxylated and oxidized by PDH to acetyl-coenzyme A, which enters the TCA cycle where the two carbons are completely oxidized to CO2 whereas hydrogen atoms reduce NAD+ and FAD, which feed the respiratory chain (turquoise). Minor part of glycolytic G-6P is diverted to produce ribose 5-phosphate (R-5P) and NADPH, that will be used to synthesize nucleotides, whereas triose phosphates in minimal part will be used to synthesize lipids and phospholipids with the contribution of NADPH and acetyl-coenzyme A. Amino acids, including glutamine (Gln) will follow the physiological turnover of the proteins, in minimal part will be used to synthesize the nucleotides bases, and the excess after deamination will be used to produce energy. In the mitochondria inner membranes are located the respiratory chain complexes and the ATP synthase (turquoise), which phosphorylates ADP releasing ATP, that in turn is carried to the cytosol by ANT (green) in exchange for ADP. About 1–2% O2 uptaken by the mitochondria is reduced to superoxide anion radical and ROS. In cancer cells (B), where anabolism is enhanced, glucose is mostly phosphorylated by HK-II (red), which is up-regulated and has an easy access to ATP being more strictly bound to the mitochondria. Its product, G-6P, is only in part oxidized to pyruvate. This, in turn, is mostly reduced to lactate being both LDH and PDH kinase up-regulated. A significant part of G-6P is used to synthesize nucleotides that also require amino acids and glutamine. Citrate in part is diverted from the TCA cycle to the cytosol, where it is a substrate of citrate lyase, which supplies acetyl-coenzyme A for lipid and phospholipid synthesis that also requires NADPH. As indicated, ROS levels in many cancer cells increase.

Of particular relevance in the study of the metabolic changes occurring in cancer cells, is the role of hexokinase II. This enzyme is greatly up-regulated in many tumours being its gene promoter sensitive to typical tumour markers such as HIF-1 and P53 [30]. It plays a pivotal role in both the bioenergetic metabolism and the biosynthesis of required molecules for cancer cells proliferation. Hexokinase II phosphorylates glucose using ATP synthesized by the mitochondrial oxphos and it releases the product ADP in close proximity of the adenine nucleotide translocator (ANT) to favour ATP re-synthesis within the matrix (Fig. 1). Obviously, the expression level, the location, the substrate affinity, and the kinetics of the enzyme are crucial to the balancing of the glucose fate, to either allowing intermediates of the glucose oxidation pathway towards required metabolites for tumour growth or coupling cytoplasmic glycolysis with further oxidation of pyruvate through the TCA cycle, that is strictly linked to oxphos. This might be possible if the mitochondrial-bound hexokinase activity is reduced and/or if it limits ADP availability to the mitochondrial matrix, to inhibit the TCA cycle and oxphos. However, the mechanism is still elusive, although it has been shown that elevated oncogene kinase signaling favours the binding of the enzyme to the voltage-dependent anion channel (VDAC) by AKT-dependent phosphorylation [34] (Fig. 2). VDAC is a protein complex of the outer mitochondrial membrane which is in close proximity of ANT that exchanges ADP for ATP through the inner mitochondrial membrane [35]. However, the enzyme may also be detached from the mitochondrial membrane, to be redistributed to the cytosol, through the catalytic action of sirtuin-3 that deacylates cyclophilin D, a protein of the inner mitochondrial membrane required for binding hexokinase II to VDAC (Fig. 2[36]. Removing hexokinase from the mitochondrial membrane has also another important consequence in cancer cells: whatever mechanism its removal activates, apoptosis is induced [37] and [38]. These observations indicate hexokinase II as an important tool used by cancer cells to survive and proliferate under even adverse conditions, including hypoxia, but it may result an interesting target to hit in order to induce cells cytotoxicity. Indeed, a stable RNA interference of hexokinase II gene showed enhanced apoptosis indices and inhibited growth of human colon cancer cells; in accordance in vivo experiments indicated a decreased tumour growth [39].

Schematic illustration of the main mitochondrial changes frequently occurring in cancer cells gr2

Schematic illustration of the main mitochondrial changes frequently occurring in cancer cells gr2

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Fig. 2. Schematic illustration of the main mitochondrial changes frequently occurring in cancer cells. The reprogramming of mitochondrial metabolism in many cancer cells comprises reduced pyruvate oxidation by PDH followed by the TCA cycle, increased anaplerotic feeding of the same cycle, mostly from Gln, whose entry in the mitochondrial matrix is facilitated by UCP2 up-regulation. This increases also the free fatty acids uptake by mitochondria, therefore β-oxidation is pushed to produce acetyl-coenzyme A, whose oxidation contributes to ATP production. In cancer cells many signals can converge on the mitochondrion to regulate the mitochondrial membrane permeability, which may respond by elevating the MPTP (PTP) threshold, with consequent enhancement of apoptosis resistance. ROS belong to this class of molecules since it can enhance Bcl2 and may induce DNA mutations. Dotted lines indicate regulation; solid lines indicate reaction(s).

Respiratory chain complexes and ATP synthase

Beyond transcriptional control of metabolic enzyme expression by oncogenes and tumour suppressors, it is becoming evident that environmental conditions affect the mitochondrial energy metabolism, and many studies in the last decade indicate that mitochondrial dysfunction is one of the more recurrent features of cancer cells, as reported at microscopic, molecular, biochemical, and genetic level [7], [40] and [41]. Although cancer cells under several conditions, including hypoxia, oncogene activation, and mDNA mutation, may substantially differ in their ability to use oxygen, only few reports have been able to identify a strict association between metabolic changes and mitochondrial complexes composition and activity. In renal oncocytomas [42] and in lung epidermoid carcinoma [43], the NADH dehydrogenase activity and protein content of Complex I were found to be strongly depressed; subsequently, in a thyroid oncocytoma cell line [44] a similar decrease of Complex I activity was ascribed to a specific mutation in the ND1 gene of mitochondrial DNA. However, among the respiratory chain complexes, significant decrease of the only Complex I content and activity was found in K-ras transformed cells in our laboratory [45], and could not be ascribed to mtDNA mutations, but rather, based on microarray analysis of oxphos genes, we proposed that a combination of genetic (low transcription of some genes) and biochemical events (assembly factors deficiency, disorganization of structured supercomplexes, and ROS-induced structural damage) might cause the Complex I defects.

In some hereditary tumours (renal cell carcinomas) a correlation has been identified between mitochondrial dysfunctions and content of oxphos complexes [46]. For instance, the low content of ATP synthase, often observed in clear cell type renal cell carcinomas and in chromophilic tumours, seems to indicate that the mitochondria are in an inefficient structural and functional state [46]. However, it cannot be excluded that, in some cases, the structural alteration of ATP synthase may offer a functional advantage to cells exhibiting a deficient respiratory chain for instance to preserve the transmembrane electrical potential (Δψm) [47]. It is likely that low levels of ATP synthases may play a significant role in cancer cell metabolism since it has been reported that in tumours from many different tissues, carcinogenesis specifically affects the expression of F1-ATPase β subunit, suggesting alterations in the mechanisms that control mitochondrial differentiation (see for a detailed review [48]). What it seems intriguing is the overexpression of the inhibitor protein, IF1, reported in hepatocellular carcinomas [49] and [50] and in Yoshida sarcoma [51]. Normally, this protein binds to the F1 domain of the ATP synthase inhibiting its activity [52], and it is believed to limit the ATP hydrolysis occurring in the mitochondria of hypoxic cells, avoiding ATP depletion and maintaining Δψm to a level capable to avoid the induction of cell death [5]. But why is its expression in cancer cells enhanced in front of a reduced F1-ATPase β subunit?

The first possibility is that IF1 has a function similar to that in normal cells, simply avoiding excessive ATP hydrolysis therefore limiting Δψm enhancement, but in cancer cells this is unlikely due to both the reduced level of ATP synthase [46] and the high affinity of IF1 for the enzyme. A second possibility might be that cancer cells need strongly reduced oxphos to adapt their metabolism and acquire a selective growth advantage under adverse environmental conditions such as hypoxia, as it has been experimentally shown [53]. Finally, IF1 might contribute to the saving of the inner mitochondrial membrane structure since it has been reported its capability to stabilize oligomers of ATP synthase, which in turn can determine cristae shapes [54]. In this regard, recent experimental evidence has shed some light on a critical role of mitochondrial morphology in the control of important mitochondrial functions including apoptosis [55] and oxidative phosphorylation [56]. In particular, dysregulated mitochondrial fusion and fission events can now be regarded as playing a role in cancer onset and progression [57]. Accordingly, mitochondria-shaping proteins seem to be an appealing target to modulate the mitochondrial phase of apoptosis in cancer cells. In fact, several cancer tissues: breast, head-and-neck, liver, ovarian, pancreatic, prostate, renal, skin, and testis, showed a pattern suggestive of enlarged mitochondria resulting from atypical fusion [58].

Mitochondrial membrane potential in cancer cells

Critical mitochondrial functions, including ATP synthesis, ion homeostasis, metabolites transport, ROS production, and cell death are highly dependent on the electrochemical transmembrane potential, a physico-chemical parameter consisting of two components, the major of which being the transmembrane electrical potential (Δψm) (see for a recent review [59]). In normal cells, under normoxic conditions, Δψm is build up by the respiratory chain and is mainly used to drive ATP synthesis, whereas in anoxia or severe hypoxia it is generated by the hydrolytic activity of the ATP synthase complex and by the electrogenic transport of ATP in exchange for ADP from the cytosol to the matrix, operated by the adenine nucleotide translocator [17]. Dissipation of the mitochondrial membrane potential (proton leak) causes uncoupling of the respiratory chain electron transport from ADP phosphorylation by the ATP synthase complex. Proton leak functions as a regulator of mitochondrial ROS production and its modulation by uncoupling proteins may be involved in pathophysiology, including tumours. In addition, Δψm plays a role in the control of the mitochondrial permeability transition pore (MPTP), that might be critical in determining reduced sensitivity to stress stimuli that were described in neoplastic transformation [60], implying that dysregulation of pore opening might be a strategy used by tumour cells to escape death. Indeed, it has recently been reported that ERK is constitutively activated in the mitochondria of several cancer cell types, where it inhibits glycogen synthase kinase-3-dependent phosphorylation of CyP-D and renders these cells more refractory to pore opening and to the ensuing cell death [61].

It is worth mentioning a second protein of the inner mitochondrial membrane, the uncoupling protein, UCP2 (Fig. 2), which contributes to regulate Δψm. Indeed, recent observations evidenced its overexpression in various chemoresistent cancer cell lines and in primary human colon cancer. This overexpression was associated with an increased apoptotic threshold [62]. Moreover, UCP2 has been reported to be involved in metabolic reprogramming of cells, and appeared necessary for efficient oxidation of glutamine [63]. On the whole, these results led to hypothesize an important role of the uncoupling protein in the molecular mechanism at the basis of the Warburg effect, that suppose a reduced Δψm-dependent entry of pyruvate into the mitochondria accompanied by enhanced fatty acid oxidation and high oxygen consumption (see for a review [64]). However, in breast cancer Sastre-Serra et al. [65] suggested that estrogens by down-regulating UCPs, increase mitochondrial Δψm, that in turn enhances ROS production, therefore increasing tumorigenicity. While the two above points of view concur to support increased tumorigenicity, the mechanisms at the basis of the phenomenon appear on the opposite of the other. Therefore, although promising for the multiplicity of metabolic effects in which UCPs play a role (see for a recent review [66]), at present it seems that much more work is needed to clarify how UCPs are related to cancer.

A novel intriguing hypothesis has recently been put forward regarding effectors of mitochondrial function in tumours. Wegrzyn J et al. [67] demonstrated the location of the transcription factor STAT3 within the mitochondria and its capability to modulate respiration by regulating the activity of Complexes I and II, and Gough et al. [68] reported that human ras oncoproteins depend on mitochondrial STAT3 for full transforming potential, and that cancer cells expressing STAT3 have increased both Δψm and lactate dehydrogenase level, typical hallmarks of malignant transformation (Fig. 2). A similar increase of Δψm was recently demonstrated in K-ras transformed fibroblasts [45]. In this study, the increased Δψm was somehow unexpected since the cells had shown a substantial decrease of NADH-linked substrate respiration rate due to a compatible reduced Complex I activity with respect to normal fibroblasts. The authors associated the reduced activity of the enzyme to its peculiar low level in the extract of the cells that was confirmed by oxphos nuclear gene expression analysis. This significant and peculiar reduction of Complex I activity relative to other respiratory chain complexes, is recurrent in a number of cancer cells of different origin [42][44][45] and [69]. Significantly, all those studies evidenced an overproduction of ROS in cancer cells, which was consistent with the mechanisms proposed by Lenaz et al. [70] who suggested that whatever factor (i.e. genetic or environmental) initiate the pathway, if Complex I is altered, it does not associate with Complex III in supercomplexes, consequently it does not channel correctly electrons from NADH through coenzyme Q to Complex III redox centres, determining ROS overproduction. This, in turn, enhances respiratory chain complexes alteration resulting in further ROS production, thus establishing a vicious cycle of oxidative stress and energy depletion, which can contribute to further damaging cells pathways and structures with consequent tumour progression and metastasis [69].

Hypoxia and oxidative phosphorylation in cancer cells

Tumour cells experience an extensive heterogeneity of oxygen levels, from normoxia (around 2–4% oxygen tension), through hypoxia, to anoxia (< 0.1% oxygen tension). The growth of tumours beyond a critical mass > 1–2 mm3 is dependent on adequate blood supply to receive nutrients and oxygen by diffusion [88]. Cells adjacent to capillaries were found to exhibit a mean oxygen concentration of 2%, therefore, beyond this distance, hypoxia occurs: indeed, cells located at 200 μm displayed a mean oxygen concentration of 0.2%, which is a condition of severe hypoxia [89]. Oxygen shortage results in hypoxia-dependent inhibition of mitochondrial activity, mostly mediated by the hypoxia-inducible factor 1 (HIF-1)[90] and [91]. More precisely, hypoxia affects structure, dynamics, and function of the mitochondria, and in particular it has a significant inhibitory effect on the oxidative phosphorylation machinery, which is the main energy supplier of cells (see Ref. [22] for a recent review). The activation of HIF-1 occurs in the cytoplasmic region of the cell, but the contribution of mitochondria is critical being both cells oxygen sensors and suppliers of effectors of HIF-1α prolyl hydroxylase like α-ketoglutarate and probably ROS, that inhibit HIF-1α removal [92]. As reported above, mitochondria can also promote HIF-1α stabilization if the TCA flux is severely inhibited with release of intermediate molecules like succinate and fumarate into the cytosol. On the other hand, HIF-1 can modulate mitochondrial functions through different mechanisms, that besides metabolic reprogramming [7][22][93] and [94], include alteration of mitochondrial structure and dynamics[58], induction of microRNA-210 that decreases the cytochrome c oxidase (COX) activity by inhibiting the gene expression of the assembly protein COX10 [95], that also increases ROS generation. Moreover, these stress conditions could induce the anti-apoptotic protein Bcl-2, which has also been reported to regulate COX activity and mitochondrial respiration [96] conferring resistance to cells death in tumours (Fig. 2). This effect might be further enhanced upon severe hypoxia conditions, since COX is also inhibited by NO, the product of activated nitric oxide synthases [97].

The reduced respiration rate occurring in hypoxia favours the release of ROS also by Complex III, which contribute to HIF stabilization and induction of Bcl-2 [98]. In addition, hypoxia reduces oxphos by inhibiting the ATP synthase complex through its natural protein inhibitor IF1 (discussed in a previous section), which contributes to the enhancement of the “aerobic glycolysis”, all signatures of cancer transformation.

The observations reported to date indicate that cancer cells exhibit large varieties of metabolic changes which are associated with alterations in the mitochondrial structure, dynamics and function, and with tumour growth and survival. On one hand, mitochondria can regulate tumour growth through modulation of the TCA cycle and oxidative phosphorylation. The altered TCA cycle provides intermediates for both macromolecular biosynthesis and regulation of transcription factors such as HIF, and it allows cytosolic reductive power enhancement. Oxphos provides significant amounts of ATP which varies among tumour types. On the other hand, mitochondria are crucial in controlling redox homeostasis in the cell, inducing them to be either resistant or sensitive to apoptosis. All these reasons locate mitochondria at central stage to understanding the molecular basis of tumour growth and to seeking for novel therapeutical approaches.

Due to the complexity and variability of mitochondrial roles in cancer, careful evaluation of mitochondrial function in each cancer type is crucial. Deeper and more integrated knowledge of mitochondrial mechanisms and cancer-specific mitochondrial modulating means are expected for reducing tumorigenicity and/or improving anticancer drugs efficacy at the mitochondrial level. Although the great variability of biochemical changes found in tumour mitochondria, some highlighted peculiarities such as reduced TCA cycle flux, reduced oxphos rate, and reduced Complex I activity with respect to tissue specific normal counterparts are more frequent. In addition, deeper examination of supramolecular organization of the complexes in the inner mitochondrial membrane has to be considered in relation to oxphos dysfunction.

2.1.1.6  Oxidation–reduction states of NADH in vivo: From animals to clinical use

Mayevsky A, Chance B.
Mitochondrion. 2007 Sep; 7(5):330-9
http://dx.doi.org:/10.1016/j.mito.2007.05.001

Mitochondrial dysfunction is part of many pathological states in patients, such as sepsis or stroke. Presently, the monitoring of mitochondrial function in patients is extremely rare, even though NADH redox state is routinely measured in experimental animals. In this article, we describe the scientific backgrounds and practical use of mitochondrial NADH fluorescence measurement that was applied to patients in the past few years. In addition to NADH, we optically measured the microcirculatory blood flow and volume, as well as HbO(2) oxygenation, from the same tissue area. The four detected parameters provide real time data on tissue viability, which is critical for patients monitoring.

(very important article)

2.1.1.7  Mitochondria in cancer. Not just innocent bystanders

Frezza C, and Gottlieb E
Sem Cancer Biol 2009; 19: 4-11
http://dx.doi.org:/10.1016/j.semcancer.2008.11.008

The first half of the 20th century produced substantial breakthroughs in bioenergetics and mitochondria research. During that time, Otto Warburg observed abnormally high glycolysis and lactate production in oxygenated cancer cells, leading him to suggest that defects in mitochondrial functions are at the heart of malignant cell transformation. Warburg’s hypothesis profoundly influenced the present perception of cancer metabolism, positioning what is termed aerobic glycolysis in the mainstream of clinical oncology. While some of his ideas stood the test of time, they also frequently generated misconceptions regarding the biochemical mechanisms of cell transformation. This review examines experimental evidence which supports or refutes the Warburg effect and discusses the possible advantages conferred on cancer cells by ‘metabolic transformation’.

Fig.1. Mitochondria as a crossroad for catabolic and anabolic pathways in normal and cancer cells. Glucose and glutamine are important carbon sources which are metabolized in cells for the generation of energy and anabolic precursors. The pathways discussed in the text are illustrated and colour coded: red, glycolysis; white, TCA cycle; pink, non-essential amino acids synthesis; orange, pentose phosphate pathway and nucleotide synthesis; green, fatty acid and lipid synthesis; blue, pyruvate oxidation in the mitochondria; brown, glutaminolysis; black, malic enzyme reaction. Solid arrows indicate a single step reaction;dashed-dotted arrows indicate transport across membranes and dotted arrows indicate multi-step reactions. Abbreviations: HK, hexokinase; AcCoA, acetyl co-enzyme A; OAA, oxaloacetate; αKG, α-ketoglutarate.

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Fig. 2. Mitochondria as a target for multiple metabolic transformation events. Principal metabolic perturbations of cancer cells are induced by genetic reprogramming and environmental changes. The activation of Akt and MYC oncogenes and the loss of p53 tumor suppressor gene are among the most frequent events in cancer. Furthermore, all solid tumors are exposed to oxidative stress and hypoxia hence to HIF activation.These frequent changes in cancer cells trigger a dramatic metabolic shift from oxidative phosphorylation to glycolysis. In addition, direct genetic lesions of mtDNA or of nuclear encoded mitochondrial enzyme (SDH or FH) can directly abrogate oxidative phosphorylation in cancer. 3- D structures of the respiratory complexes in the scheme were retrieved from Protein DataBank (PDB:www.rcsb.org) except for complex I which was retrieved from [87]. PDB codes are as follow: SDH (II), 1 LOV; complex III (III), 1BGY; COX (IV), 1OCC; ATP synthase (V), 1QO1.

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Fig. 3. The physiological roles of SDH in the TCA cycle and the ETC and its potential roles in cancer. (A) Ribbon diagram of SDH structure (PBD code: 1LOV). The catalytic subunits: the flavoprotein (SDHA) and the iron-sulphur protein (SDHB) are depicted in red and yellow, respectively, and the membrane anchors and ubiquinone binding proteins SDHC and SDHD are depicted in cyan and green, respectively. (B) Other than being a TCA enzyme, SDH is an additional entry point to the ETC (most electrons are donated from NADH to complex I—not shown in this diagram). The electron flow in and out of complex II and III is depicted by the yellow arrows. During succinate oxidation to fumarate by SDHA, a two-electron reduction of FAD to FADH2 occurs. Electrons are transferred through their on–Sulphur centres on SDHB to ubiquinone (Q) bound to SDHC and SDHD in the inner mitochondrial membrane (IMM), reducing it to ubiquinol (QH2). Ubiquinol transfers its electrons through complex III, in a mechanism named the Q cycle, to cytochrome c (PDB: 1CXA). Electrons then flow from cytochrome c to COX where the final four-electron reduction of molecular oxygen to water occurs (not shown in this diagram). Complex III is the best characterized site of ROS production in the ETC, where a single electron reduction of oxygen to superoxide can occur (red arrow). It was proposed that obstructing electron flow within complex II might support a single electron reduction of oxygen at the FAD site (red arrow). Superoxide is dismutated to hydrogen peroxide which can then leave the mitochondria and inhibit PHD in the cytosol, leading to HIF[1] stabilization. Succinate or fumarate, which accumulate in SDH- or FH-deficient tumors, can also leave the mitochondria and inhibit PHD activity in the cytosol. The red dotted line represents the outer mitochondrial membrane (OMM).

2.1.1.8  Mitochondria in cancer cells: what is so special about them?

Gogvadze V, Orrenius S, Zhivotovsky B.
Trends Cell Biol. 2008 Apr; 18(4):165-73
http://dx.doi.org:/10.1016/j.tcb.2008.01.006

The past decade has revealed a new role for the mitochondria in cell metabolism–regulation of cell death pathways. Considering that most tumor cells are resistant to apoptosis, one might question whether such resistance is related to the particular properties of mitochondria in cancer cells that are distinct from those of mitochondria in non-malignant cells. This scenario was originally suggested by Otto Warburg, who put forward the hypothesis that a decrease in mitochondrial energy metabolism might lead to development of cancer. This review is devoted to the analysis of mitochondrial function in cancer cells, including the mechanisms underlying the upregulation of glycolysis, and how intervention with cellular bioenergetic pathways might make tumor cells more susceptible to anticancer treatment and induction of apoptosis.

Glucose utilization pathway

Glucose utilization pathway

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Figure 1. Glucose utilization pathway. When glucose enters the cell, it is phosphorylated by hexokinase to glucose-6-phosphate, which is further metabolized by glycolysis to pyruvate. Under aerobic conditions, most of the pyruvate in non-malignant cells enters the mitochondria, with only a small amount being metabolized to lactic acid. In mitochondria, pyruvate dehydrogenase (PDH) converts pyruvate into acetyl-CoA, which feeds into the Krebs cycle. Oxidation of Krebs cycle substrates by the mitochondrial respiratory chain builds up the mitochondrial membrane potential (Dc) – the driving force for ATP synthesis. By contrast, in tumor cells, the oxidative (mitochondrial) pathway of glucose utilization is suppressed, and most of the pyruvate is converted into lactate. Thus, the fate of pyruvate is determined by the relative activities of two key enzymes – lactate dehydrogenase and pyruvate dehydrogenase.

Mechanisms of mitochondrial silencing in tumors

Mechanisms of mitochondrial silencing in tumors

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Figure 2. Mechanisms of mitochondrial silencing in tumors. The activity of PDH is regulated by pyruvate dehydrogenase kinase 1 (PDK1), the enzyme that phosphorylates and inactivates pyruvate dehydrogenase. HIF-1 inactivates PDH through PDK1 induction, resulting in suppression of the Krebs cycle and mitochondrial respiration. In addition, HIF-1 stimulates expression of the lactate dehydrogenase A gene, facilitating conversion of pyruvate into lactate by lactate dehydrogenase (LDH). Mutation of p53 can suppress the mitochondrial respiratory activity through downregulation of the Synthesis of Cytochrome c Oxidase 2 (SCO2) gene, the product of which is required for the assembly of cytochrome c oxidase (COX) of the mitochondrial respiratory chain. Thus, mutation of p53 can suppress mitochondrial respiration and shift cellular energy metabolism towards glycolysis.

Production of ROS by mitochondria

In any cell, the majority of ROS are by-products of mitochondrial respiration. Approximately 2% of the molecular oxygen consumed during respiration is converted into the superoxide anion radical, the precursor of most ROS. Normally, a four-electron reduction of O2, resulting in the production of two molecules of water, is catalyzed by complex IV (COX) of the mitochondrial respiratory chain. However, the electron transport chain contains several redox centers (e.g. in complex I and III) that can leak electrons to molecular oxygen, serving as the primary source of superoxide production in most tissues. The one-electron reduction of oxygen is thermodynamically favorable for most mitochondrial oxidoreductases. Superoxide-producing sites and enzymes were recently analyzed in detail in a comprehensive review [87]. ROS, if not detoxified, oxidize cellular proteins, lipids, and nucleic acids and, by doing so, cause cell dysfunction or death. A cascade of water and lipid soluble antioxidants and antioxidant enzymes suppresses the harmful ROS activity. An imbalance that favors the production of ROS over antioxidant defenses, defined as oxidative stress, is implicated in a wide variety of pathologies, including malignant diseases. It should be mentioned that mitochondria are not only a major source of ROS but also a sensitive target for the damaging effects of oxygen radicals. ROS produced by mitochondria can oxidize proteins and induce lipid peroxidation, compromising the barrier properties of biological membranes. One of the targets of ROS is mitochondrial DNA (mtDNA), which encodes several proteins essential for the function of the mitochondrial respiratory chain and, hence, for ATP synthesis by oxidative phosphorylation. mtDNA, therefore, represents a crucial cellular target for oxidative damage, which might lead to lethal cell injury through the loss of electron transport and ATP generation. mtDNA is especially susceptible to attack by ROS, owing to its close proximity to the electron transport chain, the major locus for free-radical production, and the lack of protective histones. For example, mitochondrially generated ROS can trigger the formation of 8-hydroxydeoxyguanosine as a result of oxidative DNA damage; the level of oxidatively modified bases in mtDNA is 10- to 20-fold higher than that in nuclear DNA. Oxidative damage induced by ROS is probably a major source of mitochondrial genomic instability leading to respiratory dysfunction.

Figure 3. Stabilization of mitochondria against OMM permeabilization in tumor cells. OMM permeabilization is a key event in apoptotic cell death. (a) During apoptosis, tBid-mediated oligomerization of Bax causes OMM permeabilization and release of cytochrome c (red circles). (b) Bcl-2 protein binds Bax and prevents its oligomerization. A shift in the balance between pro- apoptotic and antiapoptotic proteins in cancer cells, in favor of the latter, reduces the availability of Bax and prevents OMM permeabilization. (c) Upregulation of hexokinase in tumors and its binding to VDAC in the OMM not only facilitates glucose phosphorylation using mitochondrially generated ATP but keeps VDAC in the open state, preventing its interaction with tBid (de).

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Figure 4. Shifting metabolism from glycolysis to glucose oxidation. Utilization of pyruvate is controlled by the relative activities of two enzymes, PDH and LDH. In cancer cells, PDH activity is suppressed by PDH kinase-mediated phosphorylation, and, therefore, instead of entering the Krebs cycle, pyruvate is converted into lactate. Several attempts have been made to redirect pyruvate towards oxidation in the mitochondria. Thus, inhibition of PDK1 by dichloroacetate might stimulate the activity of PDH and, hence, direct pyruvate to the mitochondria. A similar effect can be achieved by inhibition of LDH by oxamate. Overall, suppression of PDK1 and LDH activities will stimulate mitochondrial ATP production and might be lethal to tumor cells, even if these inhibitors are used at non-toxic doses. In addition, stimulation of mitochondrial function, for example though overexpression of mitochondrial frataxin, a protein associated with Friedreich ataxia, was shown to stimulate oxidative metabolism and inhibited growth in several cancer cell lines [86].
2.1.1.9  Glucose avidity of carcinomas

Ortega AD1, Sánchez-Aragó M, Giner-Sánchez D, Sánchez-Cenizo L, et al.
Cancer Letters 276 (2009) 125–135
http://dx.doi.org:/10.1016/j.canlet.2008.08.007

The cancer cell phenotype has been summarized in six hallmarks [D. Hanahan, R.A. Weinberg, The hallmarks of cancer, Cell 100 (1) (2000) 57-70]. Following the conceptual trait established in that review towards the comprehension of cancer, herein we summarize the basis of an underlying principle that is fulfilled by cancer cells and tumors: its avidity for glucose. Our purpose is to push forward that the metabolic reprogramming that operates in the cancer cell represents a seventh hallmark of the phenotype that offers a vast array of possibilities for the future treatment of the disease. We summarize the metabolic pathways that extract matter and energy from glucose, paying special attention to the concerted regulation of these pathways by the ATP mass-action ratio. The molecular and functional evidences that support the high glucose uptake and the “abnormal” aerobic glycolysis of the carcinomas are detailed discussing also the role that some oncogenes and tumor suppressors have in these pathways. We overview past and present evidences that sustain that mitochondria of the cancer cell are impaired, supporting the original Warburg’s formulation that ascribed the high glucose uptake of cancer cells to a defective mitochondria. A simple proteomic approach designed to assess the metabolic phenotype of cancer, i.e., its bioenergetic signature, molecularly and functionally supports Warburg’s hypothesis. Furthermore, we discuss the clinical utility that the bioenergetic signature might provide. Glycolysis is presented as the “selfish” pathway used for cellular proliferation, providing both the metabolic precursors and the energy required for biosynthetic purposes, in the context of a plethora of substrates. The glucose avidity of carcinomas is thus presented as the result of both the installment of glycolysis for cellular proliferation and of the impairment of mitochondrial activity in the cancer cell. At the end, the repression of mitochondrial activity affords the cancer cell with a cell-death resistant phenotype making them prone to malignant growth.

Fig. 1. Pathways of glucose metabolism. The model shows some of the relevant aspects of the metabolism of glucose. After entering the cell by specific transporters, glucose can be (i) catabolized by the pentose phosphate pathway (PPP) to obtain reducing power in the form of NADPH, (ii) used for the synthesis of carbohydrates or (iii) utilized by glycolysis to generate pyruvate and other metabolic intermediates that could be used in different anabolic processes (blue rectangles). In the cytoplasm, the generated pyruvate can be reduced to lactate and further exported from the cell or oxidized in the mitochondria by pyruvate dehydrogenase to generate acetyl-CoA, which is condensed with oxaloacetate in the tricarboxylic acid cycle (TCA cycle). The operation of the TCA cycle completes the oxidation of mitochondrial pyruvate. Different pathways that drain intermediates of the TCA cycle (oxaloacetate, succinyl-CoA, a-ketoglutarate and citrate) for biosynthetic purposes (blue rectangles) are represented. The transfer of electrons obtained in biological oxidations (NADH/FADH2) to molecular oxygen by respiratory complexes of the inner mitochondrial membrane (in green) is depicted by yellow lines. The utilization of the proton gradient generated by respiration for the synthesis of ATP by the H+-ATP synthase (in orange) in oxidative phosphorylation (OXPHOS) is also indicated. The incorporation of glutamine carbon skeletons into the TCA cycle is shown. The utilization of NADPH in anabolic pathways is also indicated.

Fig. 3. Fluxes of matter and energy in differentiated, proliferating and cancer cells. In differentiated cells, the flux of glycolysis is low because the requirement for precursors for anabolic purposes is low and there is a high energy yield by the oxidation of pyruvate in mitochondrial oxidative phosphorylation (OXPHOS). In this situation, mitochondrial activity produces large amounts of ROS that are normally quenched by the cellular antioxidant defense. In proliferating and cancer cells, there is a high demand of glucose to provide metabolic precursors for the biosynthesis of the macromolecules of daughter cells and because most of the energy required for anabolic purposes derives from non-efficient non-respiratory modes (glycolysis, pentose phosphate pathway) of energy generation. Limiting mitochondrial activity in these situations ensures less ROS production and their further downstream consequences. In addition, cancer cells have less overall mitochondrial complement or activity than normal cells by repressing the biogenesis of mitochondria.

Fig. 2. Genetic alterations underlying the glycolytic phenotype of cancer cells. The diagram represents the impact of gain-of-function mutations in oncogenes (ovals) and loss-of-function mutations in tumor suppressors (rectangles) in glycolysis and in the mitochondrial utilization of pyruvate in cancer cells. Hypoxia (low O2) induces the stabilization of HIF-1, which promotes transcriptional activation of the glucose transporter, glycolytic genes and PDK1. The expression of PDK1 results in the inactivation of pyruvate dehydrogenase and thus in a decreased oxidation of pyruvate in the TCA cycle concurrent to its enhanced cytoplasmic reduction to lactate by lactate dehydrogenase (LDHA). In addition, HIF1a reciprocally regulates the expression of two isoforms of the cytochrome c oxidase complex. The oncogen myc also supports an enhanced glycolytic pathway by transcriptional activation of glycolytic genes. High levels of c-myc could also promote the production of reactive oxygen species (ROS) that could damage nuclear (nDNA) and mitochondrial (mtDNA). The loss-of-function of the tumor suppressor p53 promotes an enhanced glycolytic phenotype by the repression of TIGAR expression. Likewise, loss-of-function of p53 diminished the expression of SCO2, a gene required for the appropriate assembly of cytochrome c oxidase, and thus limits the activity of mitochondria in the cancer cell.
Discussion:

Jose E S Roselino

  1. Warburg Effect revisited
    It is very interesting the series of commentaries following Warburg Effect revisited. However, it comes as no surprise that almost all of them have small or greater emphasis in the molecular biology (changes in gene expression) events of the metabolic regulation involved.
    I would like to comment on some aspects: 1- Warburg did the initial experiments following Pasteur line of reasoning that aimed at carbon flow through the cell (yeast in his case) instead of describing anything inside the cell. It is worth to recall that for the sake of his study, Pasteur considered anything inside the cell under the domain of divine forces. He, at least in defence of his work, entirely made outside the cell, considered that inside the cells was beyond human capability of understanding – He has followed vitalism as his line of reasoning in defence of his work – Interestingly, the same scientist that has ruled out spontaneous generation when Pasteurization was started. Therefore, Pasteur measured everything outside the cell (mainly sugar, ethanol – the equivalent of our lactic acid end product of anaerobic metabolism) and found that as soon as yeasts were placed in the presence of oxygen, sugar was consumed at low speed in comparison with the speed measured in anaerobiosis and ethanol was also produced at reduced speed. This is an indication of a fast biological regulatory mechanism that obviously, do not require changes in gene expression. As previously said, Warburg work translated for republishing in the Journal Biological Chemistry mentioned “grana” for mitochondria calling attention on an “inside-the-cell” component. It seems that, there is not a unique, single site of metabolism, where the Pasteur Effect – Warburg Effect seems to be elicited by the shift from anaerobiosis to aerobiosis or vice versa.
    In order to find a core for the mechanism the best approach seems to take into account one of the most important contributions of one of the greatest north-American biochemists, Briton Chance. He has made it with his polarographic method of following continuously the oxygen consumption of the cell´s mitochondria.
    Mitochondria burn organic carbon molecules under a very stringent control mechanism of oxidative-phosphorylation ATP production. Measured in the form of changes in the speed of oxygen consumption over time as Respiratory Control Ratio (RCR). When no ATP is required by the cell, oxygen consumption goes at low speed (basal or state II or IV). When ADP is offered to the mitochondria as an indication that ATP synthesis is necessary, oxygen consumption is activated in state III respiration. Low respiration means low burning activity of organic (carbon) molecules what in this case, means indirectly low glucose consumption. While high respiration is the converse – greater glucose consumption.
    Aerobic metabolism of glucose to carbonic acid and water provides a change in free energy enough for 38 molecules of ATP (the real production is +/- 32 ATP in aerobic condition) while glucose to lactic acid metabolism in anaerobiosis leads to 2 ATP production after discounting the other 2 required at initial stages of glucose metabolism.
    The low ATP yield in anaerobiosis explains the fast glucose metabolism in anaerobiosis while the control by RCR in mitochondria explains the reduction in glucose metabolism under aerobiosis as long as the ATP requirements of the cell remains the same – This is what it is assumed to happen in quiescent cells. Not necessarily in fast growing cells as cancer cells are. However, this will not be discussed here. In my first experiments in the early seventies, with M. Rouxii a dimorphic mold-yeast biological system the environmental change (aerobic – anaerobic) led to morphogenetic change presented as morphogenetic expression of the Pasteur Effect. In this case, the enzyme that replaces mitochondria in ATP production (Pyruvate Kinase) converting phosphoenolpyruvate into pyruvate together with ADP into ATP, shows changes that can be interpreted as change in gene expression together with new self-assembly of enzyme subunits. (Dimer AA – yeast in anaerobic growth or sporangiospores- converted into dimer AB in aerobic mold). In Leloir opinions at that time, PK I (AA) was only highly glycosylated, while PK II (AB) was less glycosylated without changes in gene expression.

    In case you read comments posted, you will see that the reference to aerobic glycolysis, continues to be made together with, new deranged forms of reasoning as is indicated by referring to: Mitochondrial role in ion homeostasis…
    Homeostasis is a regulation of something, ions, molecules, pH etc. that is kept outside the cell, therefore any role for mitochondria on it is only made indirectly, by its ATP production.
    However, mitochondria has a role together with other cell components in the regulation of for instance, intracellular Ca levels (Something that is not a homeostatic regulation). This is a very important point for the following reason: Homeostasis is maintained as a composite result of several differentiated cellular, tissue and organ functions. Differentiated function is something clearly missing in cancer cells. The best form to refer to the mitochondrial function regarding ions is to indicate a mitochondrial role in ion fluxes.
    In short, to indicate how an environmental event or better saying condition could favour genetic changes instead of being caused by genetic changes is to follow the same line of reasoning that is followed in understanding the role of cardioplegia. To stop heart beating is adequate for heart surgery it is also adequate for heart cells by sparing the ATP use during surgery and therefore, offering better recovery condition to the heart afterwards.
    In the case, here considered, even assuming that the genome is not made more unstable during hypoxic condition it is quite possible to understand that sharing ATP with both differentiated cell function and replication may led quality control of DNA in short supply of much needed ATP and this led to maintenance of mutations as well as less organized genome.

    • Thank you. I enjoy reading your comments. They are very instructive. I don’t really think that I comprehend the use of the term “epigenetics” and longer. In fact, it was never clear to me when I first heard it used some years ago.

      The term may have been closely wedded to the classic hypothesis of a unidirectional DNA–> RNA–> protein model that really has lost explanatory validity for the regulated cell in its environment. The chromatin has an influence, and protein-protein interactions are everywhere. As you point out, these are adjusting to a fast changing substrate milieu, and the genome is not involved. But in addition, the proteins may well have a role in suppression or activation of signaling pathways, and thereby, may well have an effect on gene expression. I don’t have any idea about how it would work, but mutations would appear to follow the metabolic condition of the cell over time. It would appear to be – genomic modification.

  2. In aerobic glucose metabolism, the oxidation of citric acid requires ADP and Mg²+, which will increase the speed of the reaction: Iso-citric acid + NADP (NAD) — isocitrate dehydrogenase (IDH) = alpha-ketoglutaric acid. In the Krebs cycle (the citric cycle), IDH1 and IDH2 are NADP+-dependent enzymes that normally catalyze the inter-conversion of D-isocitrate and alpha-ketoglutarate (α-KG). The IDH1 and IDH2 genes are mutated in > 75% of different malignant diseases. Two distinct alterations are caused by tumor-derived mutations in IDH1 or IDH2: the loss of normal catalytic activity in the production of α-ketoglutarate (α-KG) and the gain of catalytic activity to produce 2-hydroxyglutarate (2-HG), [22].
    This product is a competitive inhibitor of multiple α-KG-dependent dioxygenases, including demethylases, prolyl-4-hydroxylase and the TET enzymes family (Ten-Eleven Translocation-2), resulting in genome-wide alternations in histones and DNA methylation. [23]
    IDH1 and IDH2 mutations have been observed in myeloid malignancies, including de novo and secondary AML (15%–30%), and in pre-leukemic clone malignancies, including myelodysplastic syndrome and myeloproliferative neoplasm (85% of the chronic phase and 20% of transformed cases in acute leukemia), [24].
    Normally, cells in the body communicate via intra-cytoplasmic channels and maintain the energetic potential across cell membranes, which is 1-2.5 µmol of ATP in the form of ATP-ADP/ATP-ADP-IMP. These normal energetic values occur during normal cell division. If the intra-cellular and extra-cellular levels of Mg2+ are high, the extra-cellular charges of the cells will not be uniformly distributed.
    This change in distribution induces a high net positive charge for the cell and induces a loss of contact inhibition via the electromagnetic induction of oscillation [28, 29, 30]. Thereafter, malignant cells become invasive and metastasize.
    ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
    -22. Hartmann C, Meyer J, Balss J. Capper D, et al. Type and frequency of IDH1 and IDH2 mutations are related to astrocytic and oligodendroglial differentiation and age: a study of 1,010 diffuse gliomas. Acta Neuropathol 2009; 118: 464-474.

    23. Raymakers R.A, Langemeijer S.M., Kuiper R.P, Berends M, et al. Acquired mutations in TET2 are common in myelodysplastic syndromes. Nat. Genet 2009; 41; 838–849.

    24 Wagner K, Damm F, Gohring G., Gorlich K et al. Impact of IDH1 R132 mutations and an IDH1 single nucleotide polymorphism in cytogenetically normal acute myeloid leukemia: SNP rs11554137 is an adverse prognostic factor. J. Clin. Oncol.2010; 28: 2356–2364.
    Plant Molecular Biology 1989; 1: 271–303.

    29. Chien MM, Zahradka CE, Newel MC, Fred JW. Fas induced in B cells apoptosis require an increase in free cytosolic magnesium as in early event. J Biol Chem.1999; 274: 7059-7066.

    30. Milionis H J, Bourantas C L, Siamopoulos C K, Elisaf MS. Acid bases and electrolytes abnormalities in Acute Leukemia. Am J Hematol 1999; (62): 201-207.

    31. Thomas N Seyfried; Laura M Shelton.Cancer as a Metabolic Disease. Nutr Metab 2010; 7: 7

    – Aurelian Udristioiu, M.D,
    – Lab Director, EuSpLM,
    – City Targu Jiu, Romania
    AACC, National Academy of Biochemical Chemistry (NACB) Member, Washington D.C, USA.

 

 

 

 

 

 

 

 

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Tweeting by @pharma_BI and by @AVIVA1950 for #AM2015 and @MassBio LIVE from MassBio Annual Meeting 2015, Cambridge, MA, Sonesta Hotel, March 26 – March 27, 2015

Reporter: Aviva Lev-Ari, PhD, RN

Article ID #172: Tweeting by @pharma_BI and by @AVIVA1950 for #AM2015 and @MassBio LIVE from MassBio Annual Meeting 2015, Cambridge, MA, Sonesta Hotel, March 26 – March 27, 2015. Published on 3/28/2015

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The Metabolic View of Epigenetic Expression

Writer and Curator: Larry H Bernstein, MD, FCAP

Introduction

This is the fifth contribution to a series of articles on cancer, genomics, and metabolism.   I begin this after reading an article by Stephen Williams “War on Cancer May Need to Refocus Says Cancer Expert on NPR”, and after listening to NPR “On the Media”. This is an unplanned experience, perhaps partly related to an Op-Ed in the New York Times two days before by Angelina Jolie Pittman.  Taking her article prior to pre-emptive breast surgery for the BRCA1 mutation two years ago and her salpingo-oophorectomy at age 39 years with her family history, and her adoption of several children even prior to her marriage to Brad Pitt, reveals an unusual self-knowledge as well as perspective on the disease risk balanced with her maternal instincts.  I sense (but don’t know) that she had a good knowledge not stated about the estrogen sensitivity of breast cancer for some years, and balanced that knowledge in her life decisions.

Tracing the history of cancer and the Lyndon Johnson initiated “War on Cancer” the initiative is presented as misguided.  Moreover, the imbalance is posed aas focused overly on genomics, and there is an imbalnced in the attention to the types of cancer, bladder cancer (urothelial) receiving too little attention. However, the events that drive this are complex, and not surprising.  The funding is driven partly by media attention (a film star or President’s wife) and not to be overlooked, watch where the money flows.  People who have the ability to donate and also have a family experience will give, regardless of the statistics because it is 100 percent in their eyes.

Insofar as the scientific endeavor goes, young scientists are committed to a successful research career, and they also need funding, so they have to balance the risk of success and failure in the choice of problems they choose to work on.  But until the 20th century, the biological sciences were largely descriptive. The emergence of a “Molecular Biology” is a unique 20th century development. The work of Pathology – pioneered by Rokitansky, Virchow, and to an extent also the anatomist/surgeon John Harvey – was observational science.  The description of Hodgkin’s lymphoma was observational, and it was a breakthrough in medicine.

With the emergence of genomics from biochemistry and genetics in molecular biology (biology at the subcellular level), a part of medicine that was well founded became an afterthought.  After all, after many years of the history of medicine and pathology, it is well known that cancers are not only a dysmetabolism of cellular replication and cellular regulation, but cancers have a natural history related to organ system, tissue specificity, sex, and age of occurrence. This should be well known to the experienced practitioner, but not necessarily to the basic researcher with no little clinical exposure.  Consequently, it was quite remarkable to me to find that the truly amazing biochemist who gave a “Harvey Lecture” at Harvard on the pyridine nucleotide transhydrogenases, and who shared in the discovery of Coenzyme A, had made the observation that organs that are primarily involved with synthetic activity -adrenal, pituitary, and thyroid, testis, ovary, breast (most notably) – have a more benign course than those of stomach, colon, pancreas, melanoma, hematopoietic, and sarcomas. The liver is highly synthetic, but doesn’t fit so nicely because of the role in detoxification and the large role in glucose and fat catabolism.  Further, this was at a time that we knew nothing about the cell death pathway and cellular repair, and how is it in concert with cell proliferation.

The first important reasoning about cancer metabolism was opened by Otto Warburg in the late 1920s.  I have  little reason to doubt his influence on Nathan Kaplan, who used the terms DPN(+/H) and TPN(+/H), disregarding the terms NAD(+/H) and NADP(+/H), although I was told it was because of the synthesis of the pyridine nucleotide adducts for study (APDPN, etc.).

In a recent article, I had an interesting response from Jose ES Rosalino:

In mRNA Translation and Energy Metabolism in Cancer

Topisirovic and N. Sonenberg – Cold Spring Harbor Symposia on Quantitative Biology, Volume LXXVI – http://dx.doi.org:/10.1101/sqb.2011.76.010785

“A prominent feature of cancer cells is the use of aerobic glycolysis under conditions in which oxygen levels are sufficient to support energy production in the mitochondria (Jones and Thompson 2009; Cairns et al. 2010). This phenomenon, named the “Warburg effect,” after its discoverer Otto Warburg, is thought to fuel the biosynthetic requirements of the neoplastic growth (Warburg 1956; Koppenol et al. 2011) and has recently been acknowledged as one of the hallmarks of cancer (Hanahan and Weinberg 2011). mRNA translation is the most energy-demanding process in the cell (Buttgereit and Brand 1995). Again, the use of aerobic glycolysis expression has being twisted.”

To understand my critical observation consider this: Aerobic glycolysis is the carbon flow that goes from Glucose to CO2 and water (includes Krebs cycle and respiratory chain for the restoration of NAD, FAD etc.

Anerobic glyclysis is the carbon flow that goes from glucose to lactate. It uses conversion of pyruvate to lactate to regenerate NAD.

“Pasteur effect” is an expression coined by Warburg it refers to the reduction in the carbon flow from glucose when oxygen is offered to yeasts. The major reason for that is in general terms, derived from the fact that carbon flow is regulated by several cell requirements but majorly by the ATP needs of the cell. Therefore, as ATP is generated 10 more efficiently in aerobiosis than under anaerobiosis, less carbon flow is required under aerobiosis than under anaerobiosis to maintain ATP levels. Warburg, after searching for the same regulatory mechanism in normal and cancer cells for comparison found that transformed cell continued their large flow of glucose carbons to lactate despite of the presence of oxygen.

So, it is wrong to describe that aerobic glycolysis continues in the presence of oxygen. It is what it is expected to occur. The wrong thing is that anaerobic glycolysis continues under aerobiosis.

In our discussion of transcription and cell regulatory processes, we have already encountered a substantial amount of “enzymology” that drives what is referred to as “epigenetics”.  Enzymatic reactions are involved almost everywhere we look at the processes involved in RNA nontranscriptional affairs.

Enzyme catalysis

Pyruvate carboxylase is critical for non–small-cell lung cancer proliferation
K Sellers,…, TW-M Fan
J Clin Invest. Jan 2015; xx
http://dx.doi.org:/10.1172/JCI72873

Anabolic biosynthesis requires precursors supplied by the Krebs cycle, which in turn requires anaplerosis to replenish precursor intermediates. The major anaplerotic sources are pyruvate and glutamine, which require the activity of pyruvate carboxylase (PC) and glutaminase 1 (GLS1), respectively. Due to their rapid proliferation, cancer cells have increased anabolic and energy demands; however, different cancer cell types exhibit differential requirements for PC- and GLS-mediated pathways for anaplerosis and cell proliferation. Here, we infused patients with early-stage non–small-cell lung cancer (NSCLC) with uniformly 13C-labeled glucose before tissue resection and determined that the cancerous tissues in these patients had enhanced PC activity. Freshly resected paired lung tissue slices cultured in 13C6-glucose or 13C5, 15N2-glutamine tracers confirmed selective activation of PC over GLS in NSCLC. Compared with noncancerous tissues, PC expression was greatly enhanced in cancerous tissues, whereas GLS1 expression showed no trend. Moreover, immunohistochemical analysis of paired lung tissues showed PC overexpression in cancer cells rather than in stromal cells of tumor tissues. PC knockdown induced multinucleation, decreased cell proliferation and colony formation in human NSCLC cells, and reduced tumor growth in a mouse xenograft model. Growth inhibition was accompanied by perturbed Krebs cycle activity, inhibition of lipid and nucleotide biosynthesis, and altered glutathione homeostasis. These findings indicate that PC-mediated anaplerosis in early stage NSCLC is required for tumor survival and proliferation.

Accelerated glycolysis under aerobic conditions (the “Warburg effect”) has been a hallmark of cancer for many decades (1). It is now recognized that cancer cells must undergo many other metabolic reprograming changes (2) to meet the increased anabolic and energetic demands of proliferation (3, 4). It is also becoming clear that different cancer types may utilize a variety of metabolic adaptations that are context dependent, commensurate with the notion that altered metabolism is a hallmark of cancer (12). Enhanced glucose uptake and aerobic glycolysis generates both energy (i.e., ATP) and molecular precursors for the biosynthesis of complex carbohydrates, sugar nucleotides, lipids, proteins, and nucleic acids. However, increased glycolysis alone is insufficient to meet the total metabolic demands of proliferating cancer cells. The Krebs cycle is also a source of energy via the oxidation of pyruvate, fatty acids, and amino acids such as glutamine. Moreover, several Krebs cycle intermediates are essential for anabolic and glutathione metabolism, including citrate, oxaloacetate, and α-ketoglutarate (Figure 1A).

Figure 1. PC is activated in human NSCLC tumors. (A) PC and GLS1 catalyze the major anaplerotic inputs (blue) into the Krebs cycle to support the anabolic demand for biosynthesis (green). Also shown is the fate of 13C from 13C6-glucose through glycolysis and into the Krebs cycle via PC (red).
(B) Representative Western blots of PC and GLS1 protein expression levels in human NC lung (N) and NSCLC (C) tissues. (C) Pairwise PC and GLS1 expression (n = 86) was normalized to α-tubulin and plotted as the log10 ratio of CA/NC tissues. For PC, nearly all log ratios were positive (82 of 86), with a clustering in the 0.5–1 range (i.e., typically 3- to 10-fold higher expression in the tumor tissue; Wilcoxon test, P < 0.0001). In contrast, GLS1 expression was nearly evenly distributed between positive and negative log10 ratios and showed no statistically significant difference between the CA and NC tissues (Wilcoxon test, P = 0.213). Horizontal bar represents the median. (D) In vivo PC activity was enhanced in CA tissue compared with that in paired NC lung tissues (n = 34) resected from the same human patients given 13C6-glucose 2.5–3 hours before tumor resection. PC activity was inferred from the enrichment of 13C3-citrate (Cit+3), 13C5-Cit (Cit+5), 13C3-malate (Mal+3), and 13C3-aspartate (Asp+3) as determined by GC-MS. *P < 0.05 and **P < 0.01 by paired Student t test. Error bars represent the SEM.

Continued functioning of the Krebs cycle requires the replenishment of intermediates that are diverted for anabolic uses or glutathione synthesis. This replenishment process, or anaplerosis, is accomplished via 2 major pathways: glutaminolysis (deamidation of glutamine via glutaminase [GLS] plus transamination of glutamate to α-ketoglutarate) and carboxylation of pyruvate to oxaloacetate via ATP-dependent pyruvate carboxylase (PC) (EC 6.4.1.1) (refs. 3, 20, 21, and Figure 1A). The relative importance of these pathways is likely to depend on the nature of the cancer and its specific metabolic adaptations, including those to the microenvironment (20, 22). For example, glutaminolysis was shown to be activated in the glioma cell line SF188, while PC activity was absent, despite the high PC activity present in normal astrocytes. However, SF188 cells use PC to compensate for GLS1 suppression or glutamine restriction (20), and PC, rather than GLS1, was shown to be the major anaplerotic input to the Krebs cycle in primary glioma xenografts in mice. It is also unclear as to the relative importance of PC and GLS1 in other cancer cell types or, most relevantly, in human tumor tissues in situ. Our preliminary evidence from 5 non–small-cell lung cancer (NSCLC) patients indicated that PC expression and activity are upregulated in cancerous (CA) compared with paired noncancerous (NC) lung tissues (21), although it was unclear whether PC activation applies to a larger NSCLC cohort or whether PC expression was associated with the cancer and/or stromal cells

Here, we have greatly extended our previous findings (21) in a larger cohort (n = 86) by assessing glutaminase 1 (GLS1) status and analyzing in detail the biochemical and phenotypic consequences of PC suppression in NSCLC. We found PC activity and protein expression levels to be, on average, respectively, 100% and 5- to 10-fold higher in cancerous (CA) lung tissues than in paired NC lung tissues resected from NSCLC patients, whereas GLS1 expression showed no significant trend. We have also applied stable isotope–resolved metabolomic (SIRM) analysis to paired freshly resected CA and NC lung tissue slices in culture (analogous to the Warburg slices; ref. 25) using either [U-13C] glucose or [U-13C,15N] glutamine as tracers. This novel method provided information about tumor metabolic pathways and dynamics without the complication of whole-body metabolism in vivo.

PC expression and activity, but not glutaminase expression, are significantly enhanced in early stages of malignant NSCLC tumors. PC protein expression was significantly higher in primary NSCLC tumors than in paired adjacent NC lung tissues (n = 86, P < 0.0001, Wilcoxon test) (Figure 1, B and C). The median PC expression was 7-fold higher in the tumor, and the most probable (modal) overexpression in the tumor was approximately 3-fold higher (see Supple-mental Table 1; supplemental material available online with this article; http://dx.doi.org:/10.1172/JCI72873DS1). We found that PC expression was also higher in the tumor tissue compared with that detected in the NC tissue in 82 of 86 patients. In contrast, GLS1 expression was not significantly different between the tumor and NC tissues (P = 0.213, Wilcoxon test) (Figure 1C and Supplemental Table 1). The 13C3-Asp produced from 13C6-glucose (Figure 1A) infused into NSCLC patients was determined by gas chromatography–mass spectrometry (GC-MS) to estimate in vivo PC activity. A bolus injection of 10 g 13C6-glucose in 50 ml saline led to an average of 44% 13C enrichment in the plasma glucose immediately after infusion (Supplemental Table 2). Because the labeled glucose was absorbed by various tissues over the approximately 2.5 hours between infusion and tumor resection, plasma glucose enrichment dropped to 17% (Supplemental Table 2). The labeled glucose in both CA and NC lung tissues was metabolized to labeled lactate, but this occurred to a much greater extent in the CA tissues (Supplemental Figure 1A), which indicates accelerated glycolysis in these tissues.

Fresh tissue (Warburg) slices confirm enhanced PC and Krebs cycle activity in NSCLC. To further assess PC activity relative to GLS1 activity in human lung tissues, thin (<1 mm thick) slices of paired CA and NC lung tissues freshly resected from 13 human NSCLC patients were cultured in 13C6-glucose or 13C5,15N2-glutamine for 24 hours. These tissues maintain biochemical activity and histological integrity for at least 24 hours under culture conditions (Figure 2A, Supplemental Figure 2, A and B, and ref. 26). When the tissues were incubated with 13C6-glucose, CA slices showed a significantly greater percentage of enrichment in glycolytic 13C3-lactate (3 in Figure 2B) than did the NC slices, indicative of the Warburg effect. In addition, the CA tissues had significantly higher fractions of 13C4-, 13C5-, and 13C6-citrate (4, 5, and 6 of citrate, respectively, in Figure 2B) than did the NC tissues. These isotopologs require the combined action of PDH, PC, and multiple turns of the Krebs cycle (Figure 2C). Consistent with the labeled citrate data, the increase in the percentage of enrichment of 13C3-, 13C4-, and 13C5-glutamate (3, 4, and 5 of glutamate, respectively, in Figure 2B) in the CA tissues indicates enhanced Krebs cycle and PC activity.

Figure 2. Ex vivo CA lung tissue slices have enhanced oxidation of glucose through glycolysis and the Krebs cycle with and without PC input compared with that of paired NC lung slices. Thin slices of CA and NC lung tissues freshly resected from 13 human NSCLC patients were incubated with 13C6-glucose for 24 hours as described in the Methods. The percentage of enrichment of lactate, citrate, glutamate, and aspartate was determined by GC-MS. (A) 1H{13C} HSQC NMR showed an increase in labeled lactate, glutamate, and aspartate. In addition, CA tissues had elevated 13C abundance in the ribose moiety of the adenine-containing nucleotides (1′-AXP), indicating that the tissues were viable and had enhanced capacity for nucleotide synthesis. (B) CA tissue slices (n = 13) showed increased glucose metabolism through glycolysis based on the increased percentage of enrichment of 13C3-lactate (“3”), and through the Krebs cycle based on the increased percentage of enrichment of 13C4–6-citrate (“4–6”) and 13C3–5-glutamate (“3–5”) (see 13C fate tracing in C). *P < 0.05 and **P < 0.01 by paired Student’s t test. Error bars represent the SEM. (C) An atom-resolved map illustrates how PC, PDH, and 2 turns of the Krebs cycle activity produced the 13C isotopologs of citrate and glutamate in B, whose enrichment were significantly enhanced in CA tissue slices.

Figure 4. PC suppression via shRNA inhibits proliferation and tumorigenicity of human NSCLC cell lines in vitro and in vivo. Proliferation and colony-formation assays were initiated 1 week after transduction and selection with puromycin. A549 xenograft in NSG mice was performed 8 days after transduction. *P < 0.01, **P < 0.001, ***P < 0.0001, and ****P < 0.00001 by Student t test, assuming unequal variances. Error bars represent the SEM. (A) NSCLC cells lines were transduced with shPC55 or shEV. Proliferation assays (n = 6) revealed substantial growth inhibition induced by PC knockdown in all 5 cell lines after a relatively long latency period. (B) Colony-formation assays indicated that PC knockdown reduced the capacity of A549 and PC9 cells to form colonies in soft agar (n = 3). (C) Tumor xenografts from shPC55-transduced A549 cells showed a 2-fold slower growth rate than did control shEV tumors (P < 0.001 by the unpaired Welch version of the t test). Tumor size was calculated as πab/4, where a and b are the x,y diameters. Each point represents an average of 6 mice. The solid lines are the nonlinear regression fits to the equation: size = a + bt2, as described in the Methods. (D) The extent of PC knockdown in the mouse xenografts (n = 6) was lesser than that in cell cultures, leading to less attenuation of PC expression (30%–60% of control) and growth inhibition. In addition, PC expression in the excised tumors correlated with the individual growth rates, as determined by Pearson’s correlation coefficient.

Fatty acyl synthesis from 13C5-glutamine (“Even” in Figure 6B) via glutaminolysis and the Krebs cycle was greatly attenuated in PC-suppressed cells. Taken together, these results suggest that PC knockdown severely inhibits lipid production by blocking the biosynthesis of fatty acyl components but not the glucose-derived glycerol backbone. This is consistent with decreased Krebs cycle activity (Figure 5), which in turn curtails citrate export from the mitochondria to supply the fatty acid precursor acetyl CoA in the cytoplasm.

Figure 5. PC knockdown perturbs glucose and glutamine flux through the Krebs cycle. 13C Isotopolog concentrations were determined by GC-MS (n = 3). Values represent the averages of triplicates, with standard errors. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 by Student’s t test, assuming unequal variances. The experiments were repeated 3 times. (A) A549 cells were transduced with shPC55 for 10 days before incubation with 13C6-glucose for 24 hours. As expected, the 13C isotopologs of Krebs cycle metabolites produced via PC and Krebs cycle activity were depleted in PC-deficient cells (tracked by blue dots in the atom-resolved map and blue circles in the bar graphs; see also Figure 2C). In addition, 13C6-glucose metabolism via PDH was also perturbed (indicated by red dots and circles). (B) Treatment of PC-knockdown cells with 13C5,15N2-glutamine revealed that anaplerotic input via GLS did not compensate for the loss of PC activity, since GLS activity was attenuated, as inferred from the activity markers (indicated by red dots and circles). Decarboxylation of glutamine-derived malate by malic enzyme (ME) and reentry of glutamine-derived pyruvate into the Krebs cycle via PC or PDH (shown in blue and green, respectively) were also attenuated. Purple diamonds denote 15N; black diamonds denote 14N.

Figure 6. PC suppression hinders Krebs cycle–fueled biosynthesis. (A) 13C atom–resolved pyrimidine biosynthesis from 13C6-glucose and 13C5-glutamine is depicted with a 13C5-ribose moiety (red dots) produced via the pentose phosphate pathway (PPP) and 13C1-3  uracil ring (blue dots) derived from  13C2-4-aspartate produced via the Krebs cycle or the combined action of ME and PC (blue dots). A549 cells transduced with shPC55 or shEV were incubated with 13C6-glucose or 13C5-glutamine for 24 hours. Fractional enrichment of UTP and CTP isotopologs from FT-ICR-MS analysis of polar cell extracts showed reduced enrichment of 13C6-glucose–derived 13C5-ribose (the “5” isotopolog) and 13C6-glucose– or 13C5-glutamine–derived 13C1-3-pyrimidine rings (the “6–8” or “1–3” isotopologs, highlighted by dashed green rectangles; for the “6–8” isotopologs, 5 13Cs arose from ribose and 1–3 13Cs from the ring) (10, 45). These data suggest that PC knockdown inhibits de novo pyrimidine biosynthesis from both glucose and glutamine. (B) Glucose and glutamine carbons enter fatty acids via citrate. FT-ICR-MS analysis of labeled lipids from the nonpolar cell extracts showed that PC knockdown severely inhibited the incorporation of glucose and glutamine carbons into the fatty acyl chains (even) and fatty acyl chains plus glycerol backbone (odd >3) of phosphatidylcholine lipids. However, synthesis of the 13C3-glycerol backbone (the “3” isotopolog) or its precursor 13C3-α-glycerol-3-phosphate (αG3P, m+3) from 13C6-glucose was enhanced rather than inhibited by PC knockdown. These data suggest that PC suppression specifically hinders fatty acid synthesis in A549 cells. Values represent the averages of triplicates (n = 3), with standard errors. *P < 0.05, **P < 0.01,  and ***P < 0.001 by Student’s t test, assuming unequal variances.

De novo glutathione synthesis was analyzed by 1H{13C} HSQC NMR. Glutathione synthesis from both glucose and glutamine was suppressed by PC knockdown (Supplemental Figure 9, A and B). Reduced de novo synthesis led to a large decrease in the total level of reduced glutathione (GSH; Supplemental Figure 12, A and B). At the same time, PC-knockdown cells accumulated slightly more oxidized GSH (GSSG; Supplemental Figure 12, A and B), leading to a significantly reduced GSH/GSSG ratio both in cell culture and in vivo (Supplemental Figure 12C). To determine whether this perturbation of glutathione homeostasis compromises the ability of PC-suppressed cells to handle oxidative stress, we measured ROS production by DCFDA fluorescence. PC-knockdown cells had over 70% more basal ROS than did control cells (0 mM H2O2; Supplemental Figure 12D). When cells were exposed to increasing concentrations of H2O2, the knockdown cells were less able to quench ROS, as they produced up to 300% more ROS than did control cells (Supplemental Figure 12D). However, N-acetylcysteine (NAC) at 10 mM did not rescue the growth of PC-knockdown cells, suggesting that such a growth effect is not simply related to an inability to regenerate GSH from GSSG. Altogether, these results show that PC suppression compromises anaplerotic input into the Krebs cycle, which in turn reduces the activity of the Krebs cycle, while limiting the ability of A549 cells to synthesize nucleotides, lipids, and glutathione. These downstream effects of PC knockdown were also evident when comparing the metabolism of shPC55-transduced A549 cells against that of A549 cells transduced with a scrambled vector (shScr) (Supplemental Figure 13), which suggests that they are on-target effects of PC knockdown.

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In vivo HIF-mediated reductive carboxylation is regulated by citrate levels and sensitizes VHL-deficient cells to glutamine deprivation.
Gameiro PA, Yang J, Metelo AM,…, Stephanopoulos G, Iliopoulos O.
Cell Metab. 2013 Mar 5; 17(3):372-85.
http://dx.doi.org:/10.1016/j.cmet.2013.02.002

Hypoxic and VHL-deficient cells use glutamine to generate citrate and lipids through reductive carboxylation (RC) of α-ketoglutarate. To gain insights into the role of HIF and the molecular mechanisms underlying RC, we took advantage of a panel of disease-associated VHL mutants and showed that HIF expression is necessary and sufficient for the induction of RC in human renal cell carcinoma (RCC) cells. HIF expression drastically reduced intracellular citrate levels. Feeding VHL-deficient RCC cells with acetate or citrate or knocking down PDK-1 and ACLY restored citrate levels and suppressed RC. These data suggest that HIF-induced low intracellular citrate levels promote the reductive flux by mass action to maintain lipogenesis. Using [(1-13)C]glutamine, we demonstrated in vivo RC activity in VHL-deficient tumors growing as xenografts in mice. Lastly, HIF rendered VHL-deficient cells sensitive to glutamine deprivation in vitro, and systemic administration of glutaminase inhibitors suppressed the growth of RCC cells as mice xenografts.

Cancer cells undergo fundamental changes in their metabolism to support rapid growth, adapt to limited nutrient resources, and compete for these supplies with surrounding normal cells. One of the metabolic hallmarks of cancer is the activation of glycolysis and lactate production even in the presence of adequate oxygen. This is termed the Warburg effect, and efforts in cancer biology have revealed some of the molecular mechanisms responsible for this phenotype (Cairns et al., 2011). More recently, 13C isotopic studies have elucidated the complementary switch of glutamine metabolism that supports efficient carbon utilization for anabolism and growth (DeBerardinis and Cheng, 2010). Acetyl-CoA is a central biosynthetic precursor for lipid synthesis, being generated from glucose-derived citrate in well-oxygenated cells (Hatzivassiliou et al., 2005). Warburg-like cells, and those exposed to hypoxia, divert glucose to lactate, raising the question of how the tricarboxylic acid (TCA) cycle is supplied with acetyl-CoA to support lipogenesis. We and others demonstrated, using 13C isotopic tracers, that cells under hypoxic conditions or defective mitochondria primarily utilize glutamine to generate citrate and lipids through reductive carboxylation (RC) of α-ketoglutarate by isocitrate dehydrogenase 1 (IDH1) or 2 (IDH2) (Filipp et al., 2012; Metallo et al., 2012; Mullen et al., 2012; Wise et al., 2011).

The transcription factors hypoxia inducible factors 1α and 2α (HIF-1α, HIF-2α) have been established as master regulators of the hypoxic program and tumor phenotype (Gordan and Simon, 2007; Semenza, 2010). In addition to tumor-associated hypoxia, HIF can be directly activated by cancer-associated mutations. The von Hippel-Lindau (VHL) tumor suppressor is inactivated in the majority of sporadic clear-cell renal carcinomas (RCC), with VHL-deficient RCC cells exhibiting constitutive HIF-1α and/or HIF-2α activity irrespective of oxygen availability (Kim and Kaelin, 2003). Previously, we showed that VHL-deficient cells also relied on RC for lipid synthesis even under normoxia. Moreover, metabolic profiling of two isogenic clones that differ in pVHL expression (WT8 and PRC3) suggested that reintroduction of wild-type VHL can restore glucose utilization for lipogenesis (Metallo et al., 2012). The VHL tumor suppressor protein (pVHL) has been reported to have several functions other than the well-studied targeting of HIF. Specifically, it has been reported that pVHL regulates the large subunit of RNA polymerase (Pol) II (Mikhaylova et al., 2008), p53 (Roe et al., 2006), and the Wnt signaling regulator Jade-1. VHL has also been implicated in regulation of NF-κB signaling, tubulin polymerization, cilia biogenesis, and proper assembly of extracellular fibronectin (Chitalia et al., 2008; Kim and Kaelin, 2003; Ohh et al., 1998; Thoma et al., 2007; Yang et al., 2007). Hypoxia inactivates the α-ketoglutarate-dependent HIF prolyl hydroxylases, leading to stabilization of HIF. In addition to this well-established function, oxygen tension regulates a larger family of α-ketoglutarate-dependent cellular oxygenases, leading to posttranslational modification of several substrates, among which are chromatin modifiers (Melvin and Rocha, 2012). It is therefore conceivable that the effect of hypoxia on RC that was reported previously may be mediated by signaling mechanisms independent of the disruption of the pVHL-HIF interaction. Here we

  • demonstrate that HIF is necessary and sufficient for RC,
  • provide insights into the molecular mechanisms that link HIF to RC,
  • detected RC activity in vivo in human VHL-deficient RCC cells growing as tumors in nude mice,
  • provide evidence that the reductive phenotype of VHL-deficient cells renders them sensitive to glutamine restriction in vitro, and
  • show that inhibition of glutaminase suppresses growth of VHL-deficient cells in nude mice.

These observations lay the ground for metabolism-based therapeutic strategies for targeting HIF-driven tumors (such as RCC) and possibly the hypoxic compartment of solid tumors in general.

HIF Inactivation Is Necessary for Downregulation of Reductive Carboxylation by pVHL

(A) Expression of HIF-1 α, HIF-2α, and their target protein GLUT1 in UMRC2-derived cell lines, as indicated.

(B) Carbon atom transition map: the fate of [1-13C1] and [5-13C1]glutamine used to trace reductive carboxylation in this work (carbon atoms are represented by circles). The [1-13C1] (green circle) and [5-13C1] (red circle) glutamine-derived isotopic labels are retained during the reductive TCA cycle (bold red pathway). Metabolites containing the acetyl-CoA carbon skeleton are highlighted by dashed circles.

(C) Relative contribution of reductive carboxylation.

(D and E) Relative contribution of glucose oxidation to the carbons of indicated metabolites (D) and citrate (E). Student’s t test compared VHL-reconstituted to vector-only or to VHL mutants (Y98N/Y112N). Error bars represent SEM. Pyr, pyruvate; Lac, lactate; AcCoA, acetyl-CoA, Cit, citrate; IsoCit, isocitrate; Akg, α-ketoglutarate; Suc, succinate; Fum, fumarate; Mal, malate; OAA, oxaloacetate; Asp, aspartate; Glu, glutamate; PDH, pyruvate dehydrogenase; ME, malic enzyme; IDH, isocitrate dehydrogenase enzymes; ACO, aconitase enzymes; ACLY, ATP-citrate lyase; GLS, glutaminase.

To test the effect of HIF activation on the overall glutamine incorporation in the TCA cycle, we labeled an isogenic pair of VHL-deficient and VHL-reconstituted UMRC2 cells with [U-13C5]glutamine, which generates M4 fumarate, M4 malate, M4 aspartate, and M4 citrate isotopomers through glutamine oxidation. As seen in Figure S1B, VHL-deficient/VHL-positive UMRC2 cells exhibit similar enrichment of M4 fumarate, M4 malate, and M4 asparate (but not citrate) showing that VHL-deficient cells upregulate reductive carboxylation without compromising oxidative metabolism from glutamine. Next, we tested whether HIF inactivation by pVHL is necessary to regulate the reductive utilization of glutamine for lipogenesis. To this end, we traced the relative incorporation of [U-13C6]glucose or [5-13C1]glutamine into palmitate. Labeled carbon derived from [5-13C1]glutamine can be incorporated into fatty acids exclusively through RC, and the labeled carbon cannot be transferred to palmitate through the oxidative TCA cycle (Figure 1B, red carbons). Tracer incorporation from [5-13C1]glutamine occurs in the one carbon (C1) of acetyl-CoA, which results in labeling of palmitate at M1, M2, M3, M4, M5, M6, M7, and M8 mass isotopomers. In contrast, lipogenic acetyl-CoA molecules originating from [U-13C6]glucose are fully labeled, and the labeled palmitate is represented by M2, M4, M6, M8, M10, M12, M14, and M16 mass isotopomers. VHL-deficient control cells and cells expressing pVHL type 2B mutants exhibited high palmitate labeling from the [5-13C1]glutamine; conversely, reintroduction of wild-type or type 2C pVHL mutant (L188V) resulted in high labeling from [U-13C6]glucose (Figures 2A and 2B, box inserts highlight the heavier mass isotopomers).

hif-inactivation-is-necessary-for-downregulation-of-reductive-carboxylation-by-pvhl

hif-inactivation-is-necessary-for-downregulation-of-reductive-carboxylation-by-pvhl

Figure 2.  HIF Inactivation Is Necessary for Downregulation of Reductive Lipogenesis by pVHL

Next, to determine the specific contribution from glucose oxidation or glutamine reduction to lipogenic acetyl-CoA, we performed isotopomer spectral analysis (ISA) of palmitate labeling patterns. ISA indicates that wild-type pVHL or pVHL L188V mutant-reconstituted UMRC2 cells relied mainly on glucose oxidation to produce lipogenic acetyl-CoA, while UMRC2 cells reconstituted with a pVHL mutant defective in HIF inactivation (Y112N or Y98N) primarily employed RC. Upon disruption of the pVHL-HIF interaction, glutamine becomes the preferred substrate for lipogenesis, supplying 70%–80% of the lipogenic acetyl-CoA (Figure 2C). This is not a cell-line-specific phenomenon, but it applies to VHL-deficient human RCC cells in general; the same changes are observed in 786-O cells reconstituted with wild-type pVHL or mutant pVHL or infected with vector only as control (Figure S2). Type 2A pVHL mutants (Y112H, which retain partial HIF binding) confer an intermediate reductive phenotype between wild-type VHL (which inactivates HIF) and type 2B pVHL mutants (which are totally defective in HIF regulation) as seen in Figures 1 and ​and 2.2. Taken together, these data demonstrate that the ability of pVHL to regulate reductive carboxylation and lipogenesis from glutamine tracks genetically with its ability to bind and degrade HIF, at least in RCC cells.

HIF Is Sufficient to Induce RC from Glutamine in RCC Cells

To test the hypothesis that HIF-2α is sufficient to promote RC from glutamine, we expressed a pVHL-insensitive HIF-2α mutant (HIF-2α P405A/P531A, marked as HIF-2α P-A) in VHL-reconstituted 786-O cells (Figure 3). HIF-2α P-A is constitutively expressed in this polyclonal cell population, despite the reintroduction of wild-type VHL, reflecting a pseudohypoxia condition (Figure 3A). We confirmed that this mutant is transcriptionally active by assaying for the expression of its targets genes GLUT1, LDHA, HK1, EGLN, HIG2, and VEGF (Figures 3B and S3A). As shown in Figure 3C, reintroduction of wild-type VHLinto 786-O cells suppressed RC, whereas the expression of the constitutively active HIF-2α mutant was sufficient to stimulate this reaction, restoring the M1 enrichment of TCA cycle metabolites observed in VHL-deficient 786-O cells. Expression of HIF-2α P-A also led to a concomitant decrease in glucose oxidation, corroborating the metabolic alterations observed in glutamine metabolism (Figures 3D and 3E). Additional evidence of the HIF2α-regulation on the reductive phenotype was obtained with [U-13C5]glutamine, which generates M5 citrate, M3 fumarate, M3 malate, and M3 aspartate through RC (Figure 3F).

Our current work showed that HIF-2α is sufficient to induce the reductive program in RCC cells that express only the HIF-2α paralog, while mouse NEK cells appeared to use HIF-1α preferentially to promote RC. Together with the evidence that HIF-1α and HIF-2α may have opposite roles in tumor growth, it is possible that the cellular context dictates which paralog activates RC. It is also possible that HIF-2α adopts the RC regulatory function of HIF-1α upon deletion of the latter in RCC cells. Further studies are warranted in understanding the relative role of HIF-α paralogs in regulating RC in different cell types.

Finally, the selective sensitivity to glutaminase inhibitors exhibited by VHL-deficient cells, together with the observed RC activity in vivo, strongly suggests that reductive glutamine metabolism may fuel tumor growth. Investigating whether the reductive flux correlates with tumor hypoxia and/or contributes to the actual cell survival under low oxygen conditions is warranted. Together, our findings underscore the biological significance of reductive carboxylation in VHL-deficient RCC cells. Targeting this metabolic signature of HIF may open viable therapeutic opportunities for the treatment of hypoxic and VHL-deficient tumors.

Elevated levels of 14-3-3 proteins, serotonin, gamma enolase and pyruvate kinase identified in clinical samples from patients diagnosed with colorectal cancer
Dowling P, Hughes DJ, Larkin AM, Meiller J, …, Clynes M
Clin Chim Acta. 2015 Feb 20;441:133-41.
http://dx.doi.org:/10.1016/j.cca.2014.12.005.

Highlights

  • Identification of a number of significant proteins and metabolites in CRC patients
  • 14-3-3 proteins, serotonin, gamma enolase and pyruvate kinase all significant
  • Intense staining for 14-3-3 epsilon in tissue specimens from CRC patients
  • Tissue 14-3-3 epsilon levels concordant with abundance in the circulation
  • Biomolecules provide insight into the biology associated with tumor development

Background: Colorectal cancer (CRC), a heterogeneous disease that is common in both men and women, continues to be one of the predominant cancers worldwide. Lifestyle, diet, environmental factors and gene defects all contribute towards CRC development risk. Therefore, the identification of novel biomarkers to aid in the management of CRC is crucial. The aim of the present study was to identify candidate biomarkers for CRC, and to develop a better understanding of their role in tumorogenesis. Methods: In this study, both plasma and tissue samples from patients diagnosed with CRC, together with non-malignant and normal controls were examined using mass spectrometry based proteomics and metabolomics approaches.
Results: It was established that the level of several biomolecules, including serotonin, gamma enolase, pyruvate kinase and members of the 14-3-3 family of proteins, showed statistically significant changes when comparing malignant versus non-malignant patient samples, with a distinct pattern emerging mirroring cancer cell energy production. Conclusion: The diagnosis and management of CRC could be enhanced by the discovery and validation of new candidate biomarkers, as found in this study, aimed at facilitating early detection and/or patient stratification together with providing information on the complex behavior of cancer cells.

Table 2 – List of proteins found to show statistically significant differences between control (n=10) and CRC (n=16; 8 stage III/8 stage IV) patient plasma samples fractionated using Proteominer beads. Information provided in the table includes accession number, discovery platform used, protein description, the number of unique peptides for quantitation, a mascot score for protein identification (confidence number), ANOVA p-values(≥0.05), fold change in protein abundance (≥2-fold) and highest/lowest mean change.

Table 3 – List of metabolites found to show statistically significant differences between control (n=8) and CRC (n=16; 8 stage III/8 stage IV) patient plasma samples. Included in the table is the Human Metabolome Database (HMDB) entry, platform used to analyse the biochemicals, biochemical name, ANOVA p-values (≥0.05), fold-change and highest/lowest mean change.

Fig.1. Box and whisker plots for: (A) M2-PK, (B) gamma enolase, (C) 14-3-3 (pan) and (D) serotonin. ELISA analysisofM2-PK, gamma enolase, serotonin and 14-3-3 (pan) in plasma samples from control (n = 20), polyps (n = 10), adenoma (n = 10), stage I/II CRC (n= 20) and stage III/IV (n= 20)patients. The figures show statistically significant p-value for various comparisons between the different sample groups. This ELISA measurement for 14-3-3 detects all known isoforms of mammalian 14-3-3 proteins (β/α, γ, ε, η, ζ/δ, θ/τ and σ).

Role of lipid peroxidation derived 4-hydroxynonenal (4-HNE) in cancer- Focusing on mitochondria
Huiqin Zhonga, Huiyong Yin
Redox Biol Apr 2015; 4: 193–199

Oxidative stress-induced lipid peroxidation has been associated with human physiology and diseases including cancer. Overwhelming data suggest that reactive lipid mediators generated from this process, such as 4-hydroxynonenal (4-HNE), are biomarkers for oxidative stress and important players for mediating a number of signaling pathways. The biological effects of 4-HNE are primarily due to covalent modification of important biomolecules including proteins, DNA, and phospholipids containing amino group. In this review, we summarize recent progress on the role of 4-HNE in pathogenesis of cancer and focus on the involvement of mitochondria: generation of 4-HNE from oxidation of mitochondria-specific phospholipid cardiolipin; covalent modification of mitochondrial proteins, lipids, and DNA; potential therapeutic strategies for targeting mitochondrial ROS generation, lipid peroxidation, and 4-HNE.

Reactive oxygen species (ROS), such as superoxide anion, hydrogen peroxide, hydroxyl radicals, singlet oxygen, and lipid peroxyl radicals, are ubiquitous and considered as byproducts of aerobic life [1]. Most of these chemically reactive molecules are short-lived and react with surrounding molecules at the site of formation while some of the more stable molecules diffuse and cause damages far away from their sites of generation. Overproduction of these ROS, termed oxidative stress, may provoke oxidation of polyunsaturated fatty acids (PUFAs) in cellular membranes through free radical chain reactions and form lipid hydroperoxides as primary products [2]; some of these primary oxidation products may decompose and lead to the formation of reactive lipid electrophiles. Among these lipid peroxidation (LPO) products, 4-hydroxy-2-nonenals (4-HNE) represents one of the most bioactive and well-studied lipid alkenals [3]. 4-HNE can modulate a number of signaling processes mainly through forming covalent adducts with nucleophilic functional groups in proteins, nucleic acids, and membrane lipids. These properties have been extensively summarized in some excellent reviews [4], [5], [6], [7], [8], [9] and [10].

Conclusions

Lipid peroxidation-derived 4-HNE is a prototypical reactive lipid electrophile that readily forms covalent adducts with nucleophilic functional groups in macromolecule such as proteins, DNA, and lipids (Fig. 3). A body of work have shown that generation of 4-HNE macromolecule adducts plays important pathological roles in cancer through interactions with mitochondria. First of all, mitochondria are one of the most important cellular sites of 4-HNE production, presumably from oxidation of abundant PUFA-containing lipids, such as L4CL. Emerging evidence suggest that this process play a critical role in apoptosis. Secondly, in response to the toxicity of 4-HNE, mitochondria have developed a number of defense mechanisms to convert 4-HNE to less reactive chemical species and minimize its toxic effects. Thirdly, 4-HNE macromolecule adducts in mitochondria are involved in the cancer initiation and progression by modulating mitochondrial function and metabolic reprogramming. 4-HNE protein adducts have been widely studied but the mtDNA modification by lipid electrophiles has yet to emerge. The biological consequence of PE modification remains to be defined, especially in the context of cancer. Last but not the least, manipulation of mitochondrial ROS generation, lipid peroxidation, and production of lipid electrophiles may be a viable approach for cancer prevention and treatment.

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Shoeb, N.H. Ansari, S.K. Srivastava, K.V. Ramana. 4-hydroxynonenal in the pathogenesis and progression of human diseases. Current Medicinal Chemistry, 21 (2) (2014):230–237 http://dx.doi.org/10.2174/09298673113209990181 23848536

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Barrera, S. Pizzimenti,…, A. Lepore, et al. Role of 4-hydroxynonenal-protein adducts in human diseases. Antioxidants & Redox Signaling (2014) http://dx.doi.org/10.1089/ars.2014.6166 25365742

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Guéraud, M. Atalay, N. Bresgen, …, I. Jouanin, W. Siems, K. Uchida. Chemistry and biochemistry of lipid peroxidation products. Free Radical Research, 44 (10) (2010): 1098–1124 http://dx.doi.org/10.3109/10715762.2010.498477.20836659

Z.H. Chen, E. Niki. 4-hydroxynonenal (4-HNE) has been widely accepted as an inducer of oxidative stress. Is this the whole truth about it or can 4-HNE also exert protective effects? IUBMB Life, 58 (5–6) (2006): 372–373. http://dx.doi.org/10.1080/15216540600686896 16754333

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Fig. 2.   Catabolism of 4-HNE in mitochondria. ROS induced lipid peroxidation in IMM and OMM (outer membrane of mitochondria) leads to 4-HNE formation. In matrix, 4-HNE conjugation with GSH produces glutathionyl-HNE (GS-HNE); this process occurs spontaneously or can be catalyzed by GSTs. 4-HNE is reduced to 1,4-dihydroxy-2-nonene (DHN) catalyzed ADH or AKRs. ALDH2 catalyzes the oxidation of 4-HNE to form 4-hydroxy-2-nonenoic acid (HNA).

Role of 4-hydroxynonenal in cancer focusing on mitochondria

Role of 4-hydroxynonenal in cancer focusing on mitochondria

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Role of 4-hydroxynonenal in cancer focusing on mitochondria

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Fig. 3. A schematic view of 4-HNE macromolecule adducts in cancer cell. 4-HNE macromolecule adducts are involved in cancer initiation, progression, metabolic reprogramming, and cell death. 4-HNE (depicted as a zigzag line) is produced through ROS-induced lipid peroxidation of mitochondrial and plasma membranes. Biological consequences of 4-HNE adduction:

  1. reducing membrane integrity;
  2. affecting protein function in cytosol;
  3. causing nuclear and mitochondrial DNA damage;
  4. inhibiting ETC activity;
  5. activating UCPs activity;
  6. reducing TCA activity;
  7. inhibiting ALDH2 activity.

DNA methylation paradigm shift: 15-lipoxygenase-1 upregulation in prostatic intraepithelial neoplasia and prostate cancer by atypical promoter hypermethylation.
Kelavkar UP1, Harya NS, … , Chandran U, Dhir R, O’Keefe DS.
Prostaglandins Other Lipid Mediat. 2007 Jan; 82(1-4):185-97

Fifteen (15)-lipoxygenase type 1 (15-LO-1, ALOX15), a highly regulated, tissue- and cell-type-specific lipid-peroxidating enzyme has several functions ranging from physiological membrane remodeling, pathogenesis of atherosclerosis, inflammation and carcinogenesis. Several of our findings support a possible role for 15-LO-1 in prostate cancer (PCa) tumorigenesis. In the present study, we identified a CpG island in the 15-LO-1 promoter and demonstrate that the methylation status of a specific CpG within this island region is associated with transcriptional activation or repression of the 15-LO-1 gene. High levels of 15-LO-1 expression was exclusively correlated with one of the CpG dinucleotides within the 15-LO-1 promoter in all examined PCa cell-lines expressing 15-LO-1 mRNA. We examined the methylation status of this specific CpG in microdissected high grade prostatic intraepithelial neoplasia (HGPIN), PCa, metastatic human prostate tissues, normal prostate cell lines and human donor (normal) prostates. Methylation of this CpG correlated with HGPIN, PCa and metastatic human prostate tissues, while this CpG was unmethylated in all of the normal prostate cell lines and human donor (normal) prostates that either did not display or had minimal basal 15-LO-1 expression. Immunohistochemistry for 15-LO-1 was performed in prostates from PCa patients with Gleason scores 6, 7 [(4+3) and (3+4)], >7 with metastasis, (8-10) and 5 normal (donor) individual males. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to detect 15-LO-1 in PrEC, RWPE-1, BPH-1, DU-145, LAPC-4, LNCaP, MDAPCa2b and PC-3 cell lines. The specific methylated CpG dinucleotide within the CpG island of the 15-LO-1 promoter was identified by bisulfite sequencing from these cell lines. The methylation status was determined by COBRA analyses of one specific CpG dinucleotide within the 15-LO-1 promoter in these cell lines and in prostates from patients and normal individuals. Fifteen-LO-1, GSTPi and beta-actin mRNA expression in BPH-1, LNCaP and MDAPCa2b cell lines with or without 5-aza-2′-deoxycytidine (5-aza-dC) and trichostatin-A (TSA) treatment were investigated by qRT-PCR. Complete or partial methylation of 15-LO-1 promoter was observed in all PCa patients but the normal donor prostates showed significantly less or no methylation. Exposure of LNCAP and MDAPCa2b cell lines to 5-aza-dC and TSA resulted in the downregulation of 15-LO-1 gene expression. Our results demonstrate that 15-LO-1 promoter methylation is frequently present in PCa patients and identify a new role for epigenetic phenomenon in PCa wherein hypermethylation of the 15-LO-1 promoter leads to the upregulation of 15-LO-1 expression and enzyme activity contributes to PCa initiation and progression.

Transcriptional regulation of 15-lipoxygenase expression by promoter methylation.
Liu C1, Xu D, Sjöberg J, Forsell P, Björkholm M, Claesson H
Exp Cell Res. 2004 Jul 1; 297(1):61-7.

15-Lipoxygenase type 1 (15-LO), a lipid-peroxidating enzyme implicated in physiological membrane remodeling and the pathogenesis of atherosclerosis, inflammation, and carcinogenesis, is highly regulated and expressed in a tissue- and cell-type-specific fashion. It is known that interleukins (IL) 4 and 13 play important roles in transactivating the 15-LO gene. However, the fact that they only exert such effects on a few types of cells suggests additional mechanism(s) for the profile control of 15-LO expression. In the present study, we demonstrate that hyper- and hypomethylation of CpG islands in the 15-LO promoter region is intimately associated with the transcriptional repression and activation of the 15-LO gene, respectively. The 15-LO promoter was exclusively methylated in all examined cells incapable of expressing 15-LO (certain solid tumor and human lymphoma cell lines and human T lymphocytes) while unmethylated in 15-LO-competent cells (the human airway epithelial cell line A549 and human monocytes) where 15-LO expression is IL4-inducible. Inhibition of DNA methylation in L428 lymphoma cells restores IL4 inducibility to 15-LO expression. Consistent with this, the unmethylated 15-LO promoter reporter construct exhibited threefold higher activity in A549 cells compared to its methylated counterpart. Taken together, demethylation of the 15-LO promoter is a prerequisite for the gene transactivation, which contributes to tissue- and cell-type-specific regulation of 15-LO expression.

mechanism of the lipoxygenase reaction

Radical mechanism of the lipoxygenase reaction pattabhiraman

Radical mechanism of the lipoxygenase reaction pattabhiraman

http://edoc.hu-berlin.de/dissertationen/pattabhiraman-shankaranarayanan-2003-11-03/HTML/pattabhiraman_html_705b7fbd.png

Position determinants of lipoxygenase reaction pattabhiraman

Position determinants of lipoxygenase reaction pattabhiraman

http://edoc.hu-berlin.de/dissertationen/pattabhiraman-shankaranarayanan-2003-11-03/HTML/pattabhiraman_html_m3642741b.jpg

Position determinants of lipoxygenase reaction

This suggests that the space inside the active site cavity plays an important role in the positional specificity (Borngräber et al., 1999). The reverse process on 12-LOX works equally well (Suzuki et al., 1994; Watanabe and Haeggstrom, 1993). However, conversion to 5-LOX by mutagenesis has not been successful. The positional determinant residues on 15-LOX were mutated to those of 5-LOX but the enzyme was inactive (Sloane et al., 1990). 15-LOX possess the ability to oxygenate 15-HpETE to form 5, 15-diHpETE. Methylation of carboxy end of the substrate increased the activity significantly. This phenomenon was hypothesised to be due to an inverse orientation of the substrate at the active site. In this case the caroboxy end may slide into the cavity as suggested by experiments with modified [page 6↓]substrates and site directed mutagenesis (Schwarz et al., 1998; Walther et al., 2001). Thus, the determinant of positional specificity is not only the volume but also the orientation of the substrate in the active site.

The N-terminal domain of the enzyme does not play a major role in the dioxygenation reaction of 12/15 lipoxygenase. N-terminal domain truncations did not impair the lipoxygenase activity. The ability of the enzyme to bind to membranes, however, is impaired in the mutants (point and truncations) of the N-ternimal domain without significant alterations to the catalytic activity (Walther et al., 2002). Mutation to Trp 181, which is localised in the catalytic domain, also impaired membrane binding function. This suggests that the C-terminal domain is responsible for the catalytic activity and a concerted action of N-terminal and C-terminal domain was necessary for effective membrane binding.

Metabolomic studies

New paradigms for metabolic modeling of human cells

Mardinoglu A, Nielsen J
Curr Opin Biotechnol. 2015 Jan 2; 34C:91-97.
http://dx.doi.org:/10.1016/j.copbio.2014

integration of genetic and biochemical knowledge

integration of genetic and biochemical knowledge

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Highlights

  • We presented the timeline of generation and evaluation of global reconstructions of human metabolism.
  • We reviewed the generation of the context specific GEMs through the use of human generic GEMs.
  • We discussed the generation of multi-tissue GEMs in the context of whole-body metabolism.
  • We finally discussed the integration of GEMs with other biological networks.

Abnormalities in cellular functions are associated with the progression of human diseases, often resulting in metabolic reprogramming. GEnome-scale metabolic Models (GEMs) have enabled studying global metabolic reprogramming in connection with disease development in a systematic manner. Here we review recent work on reconstruction of GEMs for human cell/tissue types and cancer, and the use of GEMs for identification of metabolic changes occurring in response to disease development. We further discuss how GEMs can be used for the development of efficient therapeutic strategies. Finally, challenges in integration of cell/tissue models for simulation of whole body functions as well as integration of GEMs with other biological networks for generating complete cell/tissue models are presented.

http://ars.els-cdn.com/content/image/1-s2.0-S0958166914002286-gr2.sml

Inter- and intra-tumor profiling of multi-regional colon cancer and metastasis
Kogita A, Yoshioka Y, …, Nakai T, Okuno K, Nishio K
Biochem Biophys Res Commun. 2015 Feb 27; 458(1):52-6.
http://dx.doi.org:/10.1016/j.bbrc.2015.01.064

Highlights

  • Mutation profiling of tumors of multi-regional colon cancers using targeted sequencing.
  • Formalin-fixed paraffin embedded samples were available for next-generation sequencing.
  • Different clones existed in primary tumors and metastatic tumors.
  • Muti-clonalities between intra- and inter-tumors.

Intra- and inter-tumor heterogeneity may hinder personalized molecular-target treatment that depends on the somatic mutation profiles. We performed mutation profiling of formalin-fixed paraffin embedded tumors of multi-regional colon cancer and characterized the consequences of intra- and inter-tumor heterogeneity and metastasis using targeted re-sequencing. We performed targeted re-sequencing on multiple spatially separated samples obtained from multi-regional primary colon carcinoma and associated metastatic sites in two patients using next-generation sequencing. In Patient 1 with four primary tumors (P1-1, P1-2, P1-3, and P1-4) and one liver metastasis (H1), mutually exclusive pattern of mutations was observed in four primary tumors. Mutations in primary tumors were identified in three regions; KARS (G13D) and APC (R876*) in P1-2, TP53 (A161S) in P1-3, and KRAS (G12D), PIK3CA (Q546R), and ERBB4 (T272A) in P1-4. Similar combinatorial mutations were observed between P1-4 and H1. The ERBB4 (T272A) mutation observed in P1-4, however, disappeared in H1. In Patient 2 with two primary tumors (P2-1 and P2-2) and one liver metastasis (H2), mutually exclusive pattern of mutations were observed in two primary tumors. We identified mutations; KRAS (G12V), SMAD4 (N129K, R445*, and G508D), TP53 (R175H), and FGFR3 (R805W) in P2-1, and NRAS (Q61K) and FBXW7 (R425C) in P2-2. Similar combinatorial mutations were observed between P2-1 and H2. The SMAD4 (N129K and G508D) mutations observed in P2-1, however, were nor detected in H2. These results suggested that different clones existed in primary tumors and metastatic tumor in Patient 1 and 2 likely originated from P1-4 and P2-1, respectively. In conclusion, we detected the muti-clonalities between intra- and inter-tumors based on mutational profiling in multi-regional colon cancer using next-generation sequencing. Primary region from which metastasis originated could be speculated by mutation profile. Characterization of inter- and inter-tumor heterogeneity can lead to underestimation of the tumor genomics landscape and treatment strategy of personal medicine.

Fig.1. Treatment timelines for the two patients. A) Patient 1 (a 55-year-old man) had multifocal sigmoid colon cancers, and all of which were surgically resected in their entirety (P1-1, P1-2, P1-3, and P1-4). The patient received adjuvant chemotherapy (8 courses of XELOX). Eight months later, a single liver metastasis (H1) was detected, and the patients received neoadjuvant treatment of XELOX plus bevacizumab. Thereafter, he received a partial hepatectomy. B) Patient 2 (an 84-year-old woman) had cecal and sigmoid colon cancers (P2-1 and P2-2, respectively) with a single liver metastasis (H2). She received a subtotal colectomy and subsegmental hepatectomy.

Fig. 2. Schematic representation of intra-tumor heterogeneity in two patients. A) In patient 1, primary tumor (P1-4) contains two or more subclones. The clone without the ERBB4 (T272A) mutation created the liver metastasis. B) In patient 2, primary tumor (P2-1) contains two or more subclones. The clone without the SMAD4 (N129K and G508D) mutation created the liver metastasis.

Loss of Raf-1 Kinase Inhibitor Protein Expression Is Associated With Tumor Progression and Metastasis in Colorectal Cancer

Parham MinooInti ZlobecKristi BakerLuigi TornilloLuigi TerraccianoJeremy R. Jass, and Alessandro Lugli
American Journal of Clinical Pathology, 127, 820-827
http://dx.doi.org:/10.1309/5D7MM22DAVGDT1R8(2007)

Raf-1 kinase inhibitor protein (RKIP) is known as a critical down-regulator of the mitogen-activated protein kinase signaling pathway and a potential molecular determinant of malignant metastasis. The aim of this study was to determine the prognostic significance of RKIP expression in colorectal cancer (CRC). Immunohistochemical staining for RKIP was performed on a tissue microarray comprising 1,197 mismatch repair (MMR)-proficient and 141 MMR-deficient CRCs. The association of RKIP with clinicopathologic features was analyzed. Loss of cytoplasmic RKIP was associated with distant metastasis (P = .038), higher N stage (P = .032), vascular invasion (P = .01), and worse survival (P = .001) in the MMR-proficient group. In MMR-deficient CRCs, loss of cytoplasmic RKIP was associated with distant metastasis (P = .043) and independently predicted worse survival (P = .004). Methylation analysis of 28 cases showed that loss of RKIP expression is unlikely to be due to promoter methylation.

Raf-1 kinase inhibitor protein (RKIP) is a ubiquitously expressed and highly conserved protein that belongs to the phosphatidylethanolamine-binding protein family.1,2 RKIP is present in the cytoplasm and at the cell membrane3 and appears to have multiple biologic functions that implicate spermatogenesis, neural development, cardiac function, and membrane biogenesis.4-6 RKIP has also been shown to have a role in the regulation of multiple signaling pathways. Originally, RKIP was identified as a phospholipid-binding protein and, subsequently, as an interacting partner of Raf-1 kinase that blocks mitogen-activated protein kinase (MAPK) initiated by Raf-1.7 Initial studies showed that RKIP achieves this role by competitive interference with the binding of MEK to Raf-1.8 Recently, RKIP was shown to inhibit activation of Raf-1 by blocking phosphorylation of Raf-1 by p21-activated kinase and Src family kinases.9 It has also been suggested that RKIP could be involved in regulation of apoptosis by modulating the NF-κB pathway10 and in regulation of the spindle checkpoint via Aurora B.11 RKIP has also been implicated in tumor biology. In breast and prostate cancers, ectopic expression of RKIP sensitized cells to chemotherapeutic-induced apoptosis, and reduced expression of RKIP led to resistance to chemotherapy.12 A link between RKIP and cancer was first established in prostate cancer, with RKIP showing reduced expression in prostate cancer cells and the lowest expression levels in metastatic cells, suggesting that RKIP expression is inversely associated with the invasiveness of prostate cancer.13 Restoration of RKIP expression in metastatic prostate cancer cells inhibited invasiveness of the cells in vitro and in vivo in spontaneous lung metastasis but not the growth of the primary tumor in a murine model.13

Clinicopathologic Parameters The clinicopathologic data for 1,420 patients included T stage (T1, T2, T3, and T4), N stage (N0, N1, and N2), tumor grade (G1, G2, and G3), vascular invasion (presence or absence), and survival. The distribution of these features has been described previously.18-20 For 478 patients, information on local recurrence and distant metastasis was also available.

Methylation of RKIP Methylation of RKIP promoter was examined by methylation-specific polymerase chain reaction (PCR) using an AmpliTaq Gold kit (Roche, Branchburg, NJ) as described previously.25 The primers for amplification of the unmethylated sequence were 5′-TTTAGTGATATTTTTTGAGATATGA-3′ and 3′-CACTCCCTAACCTCTAATTAACCAA-5′ and for the methylated reaction were 5′-TTTAGCGATATTTTTTGAGATACGA-3′ and 3′-GCTCCCTAACCTCTAATTAACCG- 5′. The conditions for amplification were 10 minutes at 95°C followed by 39 cycles of denaturing at 95°C for 30 seconds, annealing at 52°C for 30 seconds, and 30 seconds of extension at 72°C. The PCR products were subjected to electrophoresis on 8% acrylamide gels and visualized by SYBR gold nucleic acid gel stain (Molecular Probes, Eugene, OR). CpGenome Universal Methylated DNA (Chemicon, Temecula, CA) was used as a positive control sample for methylation. Randomization of MMR-Proficient CRCs The 1,197 MMR-proficient CRCs were randomly assigned into 2 groups consisting of 599 (group 1) and 598 (group 2) cases and matched for sex, tumor location, T stage, N stage, tumor grade, vascular invasion, and survival ❚Table 1❚. Immunohistochemical cutoff scores for RKIP expression were determined for group 1, and the association of RKIP expression and T stage, N stage, tumor grade, vascular invasion, local recurrence, distant metastasis, and 10-year survival were studied in group 2.

❚Table 1❚ Characteristics of the Randomized Mismatch Repair–Proficient Subgroups of Colorectal Cancer Cases*

Variable p
Group Gp 1 (n=599) Gp 2 (n=598) 0.235
Sex M F M F
288 (48.3) 308

(51.7)

287

(48.2)

308

(51.8)

0.82
Tumor location Right-sided 417 (70.6) 417 (71.2) Left-sided 174 (29.4) 169 (28.8)
T1 T2 T3 T4
T stage 25 (4.3) 35 (6.0) 92(15.8) 97(16.7) 375(64.2)
365(62.8)
92(15.8)
84(14.5)
0.514
N stage N0 N1 N2
289(50.7) 154(27.0) 154(26.9) 127(22.3) 120(21.0) 0.847
Tumor grade G1 G2 G3
14 (2.4) 13 (2.2) 503(86.7) 507(86.7) 63 (10.9) 65 (11.1) 0.969
Vascular invasion Presence 412 (70.9) 422 (72.1) Absence 169 (29.1) 163 (27.9) 0.643
Median survival, mo 68.0 (57.0-91.0) 76.0 (62.0-88.0) 0.59

(95% confidence interval) * Data are given as number (percentage) unless otherwise indicated.
Data were not available for all cases; percentages are based on the number of cases available for the variable, not the total number of cases in the group. Cases were assigned into groups matched for all variables listed. †
The χ2 test was used for sex, tumor location, T stage, N stage, tumor grade, and vascular invasion and log-rank test for survival analysis. P > .05 indicates that there is no difference between groups 1 and 2.
Breast and prostate cancer: more similar than different

Gail P. Risbridger1, Ian D. Davis2, Stephen N. Birrell3 & Wayne D. Tilley3
Nature Reviews Cancer 10, 205-212 (March 2010)
http://dx.doi.org:/10.1038/nrc2795

Breast cancer and prostate cancer are the two most common invasive cancers in women and men, respectively. Although these cancers arise in organs that are different in terms of anatomy and physiological function both organs require gonadal steroids for their development, and tumours that arise from them are typically hormone-dependent and have remarkable underlying biological similarities. Many of the recent advances in understanding the pathophysiology of breast and prostate cancers have paved the way for new treatment strategies. In this Opinion article we discuss some key issues common to breast and prostate cancer and how new insights into these cancers could improve patient outcomes.

Emerging field of metabolomics. Big promise for cancer biomarker identification and drug discovery
Patel S, Ahmed S.
J Pharm Biomed Anal. 2015 Mar 25; 107C:63-74.
http://DX.doi.ORG:/10.1016/j.jpba.2014.12.020

Highlights

  • Mass spectrometry, nuclear magnetic resonance and chemometrics have enabled cancer biomarker discovery.
  • Metabolomics can non-invasively identify biomarkers for diagnosis, prognosis and treatment of cancer.
  • All major types of cancers and their biomarkers discovered by metabolomics have been discussed.
  • This review sheds light on the pitfalls and potentials of metabolomics with respect to oncology.

Most cancers are lethal and metabolic alterations are considered a hallmark of this deadly disease. Genomics and proteomics have contributed vastly to understand cancer biology. Still there are missing links as downstream to them molecular divergence occurs. Metabolomics, the omic science that furnishes a dynamic portrait of metabolic profile is expected to bridge these gaps and boost cancer research. Metabolites being the end products are more stable than mRNAs or proteins. Previous studies have shown the efficacy of metabolomics in identifying biomarkers associated with diagnosis, prognosis and treatment of cancer. Metabolites are highly informative about the functional status of the biological system, owing to their proximity to organismal phenotypes. Scores of publications have reported about high-throughput data generation by cutting-edge analytic platforms (mass spectrometry and nuclear magnetic resonance). Further sophisticated statistical softwares (chemometrics) have enabled meaningful information extraction from the metabolomic data. Metabolomics studies have demonstrated the perturbation in glycolysis, tricarboxylic acid cycle, choline and fatty acid metabolism as traits of cancer cells. This review discusses the latest progress in this field, the future trends and the deficiencies to be surmounted for optimally implementation in oncology. The authors scoured through the most recent, high-impact papers archived in Pubmed, ScienceDirect, Wiley and Springer databases to compile this review to pique the interest of researchers towards cancer metabolomics.

Table.  Novel Cancer Markers Identified by Metabolomics

Quantitative analysis of acetyl-CoA production in hypoxic cancer cells reveals substantial contribution from acetate
Jurre J Kamphorst, Michelle K Chung, Jing Fan and Joshua D Rabinowitz
Cancer & Metabolism 2014, 2:23
http://dx.doi.org:/10.1186/2049-3002-2-23

Background: Cell growth requires fatty acids for membrane synthesis. Fatty acids are assembled from 2-carbon units in the form of acetyl-CoA (AcCoA). In nutrient and oxygen replete conditions, acetyl-CoA is predominantly derived from glucose. In hypoxia, however, flux from glucose to acetyl-CoA decreases, and the fractional contribution of glutamine to acetyl-CoA increases. The significance of other acetyl-CoA sources, however, has not been rigorously evaluated. Here we investigate quantitatively, using 13C-tracers and mass spectrometry, the sources of acetyl-CoA in hypoxia. Results: In normoxic conditions, cultured cells produced more than 90% of acetyl-CoA from glucose and glutamine-derived carbon. In hypoxic cells, this contribution dropped, ranging across cell lines from 50% to 80%. Thus, under hypoxia, one or more additional substrates significantly contribute to acetyl-CoA production. 13C-tracer experiments revealed that neither amino acids nor fatty acids are the primary source of this acetyl-CoA. Instead, the main additional source is acetate. A large contribution from acetate occurs despite it being present in the medium at a low concentration (50–500 μM). Conclusions: Acetate is an important source of acetyl-CoA in hypoxia. Inhibition of acetate metabolism may impair tumor growth.

Cancer cells have genetic mutations that drive proliferation. Such proliferation creates a continuous demand for structural components to produce daughter cells [13]. This includes demand for fatty acids for lipid membranes. Cancer cells can obtain fatty acids both through uptake from extracellular sources and through de novo synthesis, with the latter as a major route by which non-essential fatty acids are acquired in many cancer types [4,5].

The first fatty acid to be produced by de novo fatty acid synthesis is palmitate. The enzyme fatty acid synthase (FAS) makes palmitate by catalyzing the ligation and reduction of 8-acetyl (2-carbon) units donated by cytosolic acetyl-CoA. This 16-carbon fatty acid palmitate is then incorporated into structural lipids or subjected to additional elongation (again using acetyl-CoA) and desaturation reactions to produce the diversity of fatty acids required by the cell.

Acetyl-CoA sits at the interface between central carbon and fatty acid metabolism. In well-oxygenated conditions with abundant nutrients, its 2-carbon acetyl unit is largely produced from glucose. First, pyruvate dehydrogenase produces acetyl-CoA from glucose-derived pyruvate in the mitochondrion, followed by ligation of the acetyl group to oxaloacetate to produce citrate. Citrate is then transported into the cytosol and cytosolic acetyl-CoA produced by ATP citrate lyase.

In hypoxia, flux from glucose to acetyl-CoA is impaired. Low oxygen leads to the stabilization of the HIF1 complex, blocking pyruvate dehydrogenase (PDH) activity via activation of HIF1-responsive pyruvate dehydrogenase kinase 1 (PDK1) [6,7]. As a result, the glucose-derived carbon is shunted towards lactate rather than being used for generating acetyl-CoA, affecting carbon availability for fatty acid synthesis.

To understand how proliferating cells rearrange metabolism to maintain fatty acid synthesis under hypoxia, multiple studies focused on the role of glutamine as an alternative carbon donor[810]. The observation that citrate M+5 labeling from U-13C-glutamine increased in hypoxia led to the hypothesis that reductive carboxylation of glutamine-derived α-ketoglutarate enables hypoxic cells to maintain citrate and acetyl-CoA production. As was noted later, though, dropping citrate levels in hypoxic cells make the α-ketoglutarate to citrate conversion more reversible and an alternative explanation of the extensive citrate and fatty acid labeling from glutamine in hypoxia is isotope exchange without a net reductive flux [11]. Instead, we and others found that hypoxic cells can at least in part bypass the need for acetyl-CoA for fatty acid synthesis by scavenging serum fatty acids [12,13].

In addition to increased serum fatty acid scavenging, we observed a large fraction of fatty acid carbon (20%–50% depending on the cell line) in hypoxic cells not coming from either glucose or glutamine. Here, we used 13C-tracers and mass spectrometry to quantify the contribution from various carbon sources to acetyl-CoA and hence identify this unknown source. We found only a minor contribution of non-glutamine amino acids and of fatty acids to acetyl-CoA in hypoxia. Instead, acetate is the major previously unaccounted for carbon donor. Thus, acetate assimilation is a route by which hypoxic cells can maintain lipogenesis and thus proliferation.

Figure 1. Percentage 13C-labeling of cytosolic acetyl-CoA can be quantified from palmitate labeling. (A) Increasing 13C2-acetyl-CoA labeling shifts palmitate labeling pattern to the right. 13C2-acetyl-CoA labeling can be quantified by determining a best fit between observed palmitate labeling and computed binomial distributions (shown on right-hand side) from varying fractions of acetyl-CoA (AcCoA) labeling. (B) Steady-state palmitate labeling from U-13C-glucose and U-13C-glutamine in MDA-MB-468 cells. (C) Percentage acetyl-CoA production from glucose and glutamine. For (B) and (C), data are means ± SD of n = 3.

Fraction palmitate M + x = (16/x)(p)x (1−p)(16−x)

We applied this approach to MDA-MB-468 cells grown in medium containing U-13C-glucose and U-13C-glutamine. The resulting steady-state palmitate labeling patterns showed multiple heavily 13C-labeled forms as well as a remaining unlabeled M0 peak (Figure 1B). The M0-labeled form results from scavenging of unlabeled serum fatty acids and can be disregarded for the purpose of determining AcCoA labeling. From the remaining labeling distribution, we calculated 87% AcCoA labeling from glucose and 6% from glutamine, with 93% collectively accounted for by these two major carbon sources (Additional file 1: Figure S1). Similar results were also obtained for HeLa and A549 cells (Figure 1C)

Figure 2. Acetyl-CoA labeling from 13C-glucose and 13C-glutamine decreases in hypoxia. (A) Steady-state palmitate labeling from U-13C-glucose and U-13C-glutamine in normoxic and hypoxic (1% O2) conditions. (B) Percentage acetyl-CoA production from glucose and glutamine in hypoxia. (C) One or more additional carbon donors contribute substantially to acetyl-CoA production in hypoxia. Abbreviations: Gluc, glucose; Gln, glutamine. Data are means ± SD of n = 3.

Figure 3.  Amino acids (other than glutamine) and fatty acids are not major sources of cytosolic acetyl-CoA in hypoxia. (A) Palmitate labeling in hypoxic (1% O2) MDA-MB-468 cells, grown for 48 h in medium where branched chain amino acids plus lysine and threonine were substituted with their respective U-13C-labeled forms. (B) Same conditions, except that glucose and glutamine only or glucose and all amino acids, were substituted with the U-13C-labeled forms. (C) Palmitate labeling in hypoxic (1% O2) MDA-MB-468 cells, grown in medium supplemented with 20 μM U-13C-palmitate for 48 h. Data are means ± SD of n = 3.

Acetate is the main additional AcCoA carbon source in hypoxia

We next investigated if hypoxic cells could activate acetate to AcCoA. Although we used dialyzed serum in our experiments and acetate is not a component of DMEM, we contemplated the possibility that trace levels could still be present or that acetate is produced as a catabolic intermediate from other sources (for example from protein de-acetylation). We cultured MDA-MB-468 cells in 1% O2 in DMEM containing U-13C-glucose and U-13C-glutamine and added increasing amounts of U-13C-acetate (Figure 4A). AcCoA labeling rose considerably with increasing U-13C-acetate concentrations, from approximately 50% to 86% with 500 μM U-13C-acetate. No significant increase in labeling of AcCoA was observed in normoxic cells following incubation with U-13C-acetate. Thus, acetate selectively contributes to AcCoA in hypoxia.

Figure 4.  The main additional AcCoA source in hypoxia is acetate. (A) Percentage 13C2-acetyl-CoA labeling quantified from palmitate labeling in hypoxic (1% O2) and normoxic MDA-MB-468 cells grown in medium with U-13C-glucose and U-13C-glutamine and additionally supplemented with indicated concentrations of U-13C-acetate. (B) Acetate concentrations in fresh 10% DFBS, DMEM, and DMEM with 10% DFBS. (C) Percentage 13C2-acetyl-CoA labeling for hypoxic (1% O2) HeLa and A549 cells. For (A) and (C), data are means ± SD of n ≥ 2. For (B), data are means ± SEM of n = 3.

Tumors require a constant supply of fatty acids to sustain cellular replication. It is thought that most cancers derive a considerable fraction of the non-essential fatty acids through de novo synthesis. This requires AcCoA with its 2-carbon acetyl group acting as the carbon donor. In nutrient replete and well-oxygenated conditions, AcCoA is predominantly made from glucose. However, tumor cells often experience hypoxia, causing limited entry of glucose-carbon into the TCA cycle. This in turn affects AcCoA production, and it has been proposed that hypoxic cells can compensate by increasing AcCoA production from glutamine-derived carbon in a pathway involving reductive carboxylation of α-ketoglutarate [810].

Irrespective of the precise net contribution of acetate in hypoxia, a remarkable aspect is that a significant contribution occurs based only on contaminating acetate (~300 μM) in the culturing medium. This is considerably less than glucose (25 mM) or glutamine (4 mM). Acetate concentrations in the plasma of human subjects have been reported in the range of 50 to 650 μM [2225], and therefore, significant acetate conversion to AcCoA may occur in human tumors. This is supported by clinical observations that 11C-acetate PET can be used to image tumors, in particular those where conventional FDG-PET typically fails [26]. Our results indicate that 11C-acetate PET could be particularly important in notoriously hypoxic tumors, such as pancreatic cancer. Preliminary results provide evidence in this direction [27].

Finally, as our measurements of fatty acid labeling reflect specifically cytosolic AcCoA, it is likely that the cytosolic acetyl-CoA synthetase ACSS2 plays an important role in the observed acetate assimilation. Accordingly, inhibition of ACSS2 merits investigation as a potential therapeutic approach.

In hypoxic cultured cancer cells, one-quarter to one-half of cytosolic acetyl-CoA is not derived from glucose, glutamine, or other amino acids. A major additional acetyl-CoA source is acetate. Low concentrations of acetate (e.g., 50–650 μM) are found in the human plasma and also occur as contaminants in typical tissue culture media. These amounts are avidly incorporated into cellular acetyl-CoA selectively in hypoxia. Thus, 11C-acetate PET imaging may be useful for probing hypoxic tumors or tumor regions. Moreover, inhibiting acetate assimilation by targeting acetyl-CoA synthetases (e.g., ACSS2) may impair tumor growth.

Differential metabolomic analysis of the potential antiproliferative mechanism of olive leaf extract on the JIMT-1 breast cancer cell line
Barrajón-Catalán E, Taamalli A, Quirantes-Piné R, …, Micol V, Zarrouk M
J Pharm Biomed Anal. 2015 Feb; 105:156-62.
http://dx.doi.org:/10.1016/j.jpba.2014.11.048

A new differential metabolomic approach has been developed to identify the phenolic cellular metabolites derived from breast cancer cells treated with a supercritical fluid extracted (SFE) olive leaf extract. The SFE extract was previously shown to have significant antiproliferative activity relative to several other olive leaf extracts examined in the same model. Upon SFE extract incubation of JIMT-1 human breast cancer cells, major metabolites were identified by using HPLC coupled to electrospray ionization quadrupole-time-of-flight mass spectrometry (ESI-Q-TOF-MS). After treatment, diosmetin was the most abundant intracellular metabolite, and it was accompanied by minor quantities of apigenin and luteolin. To identify the putative antiproliferative mechanism, the major metabolites and the complete extract were assayed for cell cycle, MAPK and PI3K proliferation pathways modulation. Incubation with only luteolin showed a significant effect in cell survival. Luteolin induced apoptosis, whereas the whole olive leaf extract incubation led to a significant cell cycle arrest at the G1 phase. The antiproliferative activity of both pure luteolin and olive leaf extract was mediated by the inactivation of the MAPK-proliferation pathway at the extracellular signal-related kinase (ERK1/2). However, the flavone concentration of the olive leaf extract did not fully explain the strong antiproliferative activity of the extract. Therefore, the effects of other compounds in the extract, probably at the membrane level, must be considered. The potential synergistic effects of the extract also deserve further attention. Our differential metabolomics approach identified the putative intracellular metabolites from a botanical extract that have antiproliferative effects, and this metabolomics approach can be expanded to other herbal extracts or pharmacological complex mixtures.

Pancreatic cancer early detection. Expanding higher-risk group with clinical and metabolomics parameters
Shiro Urayama
World J Gastroenterol. 2015 Feb 14; 21(6): 1707–1717.
http://dx.doi.org:/10.3748/wjg.v21.i6.1707

Pancreatic ductal adenocarcinoma (PDAC) is the fourth and fifth leading cause of cancer death for each gender in developed countries. With lack of effective treatment and screening scheme available for the general population, the mortality rate is expected to increase over the next several decades in contrast to the other major malignancies such as lung, breast, prostate and colorectal cancers. Endoscopic ultrasound, with its highest level of detection capacity of smaller pancreatic lesions, is the commonly employed and preferred clinical imaging-based PDAC detection method. Various molecular biomarkers have been investigated for characterization of the disease, but none are shown to be useful or validated for clinical utilization for early detection. As seen from studies of a small subset of familial or genetically high-risk PDAC groups, the higher yield and utility of imaging-based screening methods are demonstrated for these groups. Multiple recent studies on the unique cancer metabolism including PDAC, demonstrate the potential for utility of the metabolites as the discriminant markers for this disease. In order to generate an early PDAC detection screening strategy available for a wider population, we propose to expand the population of higher risk PDAC group with combination clinical and metabolomics parameters.

Core tip: This is a summary of current pancreatic cancer cohort early detection studies and a potential approach being considered for future application. This is an area that requires heightened efforts as lack of effective treatment and screening scheme for wider population is leading this particular disease to be the second lethal cancer by 2030.

Currently, pancreatic ductal adenocarcinoma (PDAC) is the fourth major cause of cancer mortality in the United States[1]. It is predicted that 46420 new cases and 39590 deaths would result from pancreatic cancer in the United States in 2014[2]. Worldwide, there were 277668 new cases and 266029 deaths from this cancer in 2008[3]. In comparison to other major malignancies such as breast, colon, lung and prostate cancers with their respective 89%, 64%, 16%, 99% 5-year survival rate, PDAC at 6% is conspicuously low[2]. For PDAC, the only curative option is surgical resection, which is applicable in only 10%-15% of patients due to the common discovery of late stage at diagnosis[4]. In fact, PDAC is notorious for late stage discovery as evidenced by the low percentage of localized disease at diagnosis, compared to other malignancies: breast (61%), colon (40%), lung (16%), ovarian (19%), prostate (91%), and pancreatic cancer (7%) [5]. With the existing effective screening methods, the decreasing trends of cancer death rate are seen in major malignancies such as breast, prostate and colorectal cancer. In contrast, it is estimated that PDAC is expected to be surfacing as the second leading cause of cancer death by 2030[6].

With the distinct contribution of late-stage discovery and general lack of effective medical therapy, a critical approach in reversing the poor outcome of pancreatic cancer is to develop an early detection scheme for the tumor. In support of this, we see the trend that despite the poor prognosis of the disease, for those who have undergone curative resection with negative margins, the 5-year survival rate is 22% in contrast to 2% for the advanced-stage with distant metastasis[7,8]. An earlier diagnosis with tumor less than 2 cm (T1) is associated with a better 5-year survival of 58% compared to 17% for stage IIB PDAC[9]. Ariyama et al. [10] reported complete survival of 79 patients with less than 1 cm tumors after surgical resection. Furthermore, as a recent report indicates, the estimated time from the transformation to pre-metastatic growths of pancreatic cancer is approximately 15 years[11]; there is a wide potential window of opportunity to apply developing technologies in early detection of this cancer.

Current screening programs have demonstrated that the EUS evaluation can detect premalignant lesions and early cancers in certain small subset of high-risk groups. However, as the overwhelming majority of PDAC cases involve patients who develop the disease sporadically without a recognized genetic abnormality, the application of this modality for PDAC detection screening is very limited for the general adult population.

Select population based approach

Identification of a higher-PDAC-risk group: As the prevalence of PDAC in the general United States population over the age 55 is approximately 68 per 100000, a candidate discriminant test with a specificity of 98% and a sensitivity of 100% would generate 1999 false-positive test results and 68 true-positives[74]. Thus, relying on a single determinant for distinguishing the PDAC early-stage cases from the general population would necessitate a highly accurate test with a specificity of greater than 99%. More practical approach, then, would be to begin with a subset of population with a higher prevalence, and in conjunction with novel surrogate markers to curtail the at-risk subset, we could begin to identify the group with significantly increased PDAC risk for whom the endoscopic/imaging-based screening strategy could be applied.

An initial approach in selection of the screening population is to utilize selective clinical parameters that could be used to curtail the subset of the general population at increased PDAC risk. For instance, based on the epidemiological evidence, such clinical parameters include hyperglycemia or diabetes, which are noted in 50%-80% of pancreatic cancer patients [7579]. Though not encompassing all PDAC patients, this subset includes a much larger proportion of PDAC patients for whom we may select further for screening. Similarly, patients with a history of chronic pancreatitis or obesity are reported to have increased PDAC risk during their lifetime[8085].

With the recent advancement in the technology and resumed interest in the cancer-associated metabolic abnormality [89,90], application of metabolomics in the cancer field has attracted more attention [91]. Cancer-related metabolic reprogramming, Warburg effect, has been known since nearly a century ago in association with various solid tumors including PDAC [92], as cancer cells undergo energetically inefficient glycolysis even in the presence of oxygen in the environment (aerobic glycolysis)[93]. A number of common cancer mutations including Akt1, HIF (hypoxia-inducible factor), and p53 have been shown to support the Warburg effect through glycolysis and down-regulation of metabolite flux through the Krebs cycle [94101]. In PDAC, increased phosphorylation or activation of Akt1 has also been reported (illuminating on the importance of enzyme functionality)[102] as well as involvement of HIF1 in the tumor growth via effects on glycolytic process [103,104] and membrane-bound glycoprotein (MUC17) regulation [105] – reflective of activation of metabolic pathways. Further evidences of loss-of-function genetic mutations in key mitochondrial metabolic enzymes such as succinate dehydrogenase and fumarate hydratase, isocitrate dehydrogenase, phosphoglycerate dehydrogenase support carcinogenesis and the Warburg effect [106110]. Other important alternative pathways in cancer metabolism such as glutaminolysis and pyruvate kinase isoform suppression have been shown to accumulate respective upstream intermediates and reduction of associated end products such as NADPH, ribose-5-phosphate and nucleic acids [111-116]. As such, various groups have reported metabolomics biomarker applications for different cancers [117,118].

As a major organ involved in metabolic regulation in a healthy individual, pancreatic disorder such as malignancy is anticipated to influence the normal metabolism, presenting further rationale and interest in elucidating the implication of malignant transformation and PDAC development. Proteomic analysis of the pancreatic cancer cells demonstrated alteration in proteins involved in metabolic pathways including increased expression of glycolytic and reduced Krebs cycle enzymes, and accumulation of key proteins involved in glutamine metabolism, in support of Warburg effect. These in turn play significant role in nucleotide and amino acid biosynthesis required for sustaining the proliferating cancer cells[119]. Applications of sensitive mass spectrometric techniques in metabolomics study of PDAC detection biomarkers have led to identification of a set of small molecules or metabolites (or biochemical intermediates) that are potent discriminants of developing PDAC and the controls (See Figure ​1  as an example of metabolomics based analysis, allowing segregation of PDAC from benign cases). Recent reports from our group as well as others have demonstrated that specific candidate metabolites consisting of amino acids, bile acids, and a number of lipids and fatty acids – suspected to be reflective of tumor proliferation as well as many systemic response yet to be determined – were identified as potential discriminant for blood-based PDAC biomarkers[120-123]. As a further supporting data, elucidation of lipids and fatty acids as discriminant factors from PDAC and benign lesions from the cancer tissue and adjacent normal tissue has been reported recently[124].

metabolomics based analysis for PDC WJG-21-1707-g001

metabolomics based analysis for PDC WJG-21-1707-g001

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4323446/bin/WJG-21-1707-g001.gif

Figure 1 Example of metabolomics based analysis, allowing segregation of pancreatic ductal adenocarcinoma from benign cases. Heat map illustration of discriminant capability of a metabolite set derived from gas chromatography and liquid chromatography/mass spectrometry …

By virtue of simultaneously depicting the multiple metabolite levels, metabolomics approach reveals various biochemical pathways that are uniquely involved in malignant conditions and has led to findings such as abnormalities of glycine and its mitochondrial biosynthetic pathway, as a potential therapeutic target in certain cancers[125]. Moreover, in combination with other systems biology approaches such as transcriptomics and proteomics, further refinement in characterization of cancer development and therapeutic targets as well as identification of potential biomarkers could be realized for PDAC. Since many enzymes in a metabolic network determine metabolites’ level and nonlinear quantitative relationship from the genes to the proteome and metabolome levels exist, a metabolome cannot be easily decomposed to a specific single marker, which will designate the cancer state[126]. Thus, in order to delineate a pathological state such as PDAC, multiple metabolomic features might be required for accurate depiction of a developing cancer. Future studies are anticipated to incorporate cancer systems’ biological knowledge, including metabolomics, for optimal designation of PDAC biomarkers, which would be utilized in conjunction with a clinical-parameter-derived population subset for establishing the PDAC screening population. Subsequently, further validation studies for the PDAC biomarkers need to be performed.

Current imaging-based detection and diagnostic methods for PDAC is effectively providing answers to clinical questions raised for patients with signs or symptoms of suspected pancreatic lesions. However, the endoscopic/imaging-based screening schemes are currently limited in applications to early PDAC detection in asymptomatic patients, aside from a small group of known genetically high-risk groups. There is a high demand for developing a method of selecting distinct subsets among the general population for implementing the endoscopic/imaging screening test effectively. Application of combinations of clinical risk parameters/factors with the developing molecular biomarkers from translational science such as metabolomics analysis brings hopes of providing us with early PDAC detection markers, and developing effective early detection screening scheme for the patients in the near future.

Serum metabolomic profiles evaluated after surgery may identify patients with estrogen receptor negative early breast cancer at increased risk of disease recurrence
Tenori L, Oakman C, Morris PG, …, Luchinat C, Di Leo A.
Mol Oncol. 2015 Jan; 9(1):128-39.
http://dx.doi.org:/10.1016/j.molonc.2014.07.012

Purpose: Metabolomics is a global study of metabolites in biological samples. In this study we explored whether serum metabolomic spectra could distinguish between early and metastatic breast cancer patients and predict disease relapse. Methods: Serum samples were analysed from women with metastatic (n = 95) and predominantly oestrogen receptor (ER) negative early stage (n = 80) breast cancer using high resolution nuclear magnetic resonance spectroscopy. Multivariate statistics and a Random Forest classifier were used to create a prognostic model for disease relapse in early patients.
Results: In the early breast cancer training set (n = 40), metabolomics correctly distinguished between early and metastatic disease in 83.7% of cases. A prognostic risk model predicted relapse with 90% sensitivity (95% CI 74.9-94.8%), 67% specificity (95% CI 63.0-73.4%) and 73% predictive accuracy (95% CI 70.6-74.8%). These results were reproduced in an independent early breast cancer set (n = 40), with 82% sensitivity, 72% specificity and 75% predictive accuracy. Disease relapse was associated with significantly lower levels of histidine (p = 0.0003) and higher levels of glucose (p = 0.01), and lipids (p = 0.0003), compared with patients with no relapse.
Conclusions: The performance of a serum metabolomic prognostic model for disease relapse in individuals with ER-negative early stage breast cancer is promising. A confirmation study is ongoing to better define the potential of metabolomics as a host and tumour-derived prognostic tool.

Figure 1 e Clusterization of serum metabolomic profiles. Discrimination between metastatic (green, n [ 95) and early (red, n [ 40) breast cancer patients using the random forest classifier. (a) CPMG; (b) NOESY1D; (c) Diffusion.

Figure 2 e Training set. Comparison between metabolomic classification and actual relapse. The receiver operator curves (ROC) and the area under the curve (AUC) scores are presented for CPMG, NOESY1D and Diffusion.

Figure 3 e Validation set. Comparison between CPMG random forest risk score metabolomic classification and actual relapse The receiver operator curve (ROC) and the area under the curve (AUC) score are presented for the CPMG analysis.

Figure 4 e Discriminant metabolites. Discriminant metabolites (p < 0.05) between profiles from early (green, n [ 80) and metastatic (red, n [ 95) breast cancer patients. Box and whisker plots: horizontal line within the box [ mean; bottom and top lines of the box [ 25th and 75th percentiles, respectively; bottom and top whiskers [ 5th and 95th percentiles, respectively. Median values (arbitrary units) are provided in the associated table, along with raw p values and p values adjusted for multiple testing. pts: patients.

Transparency in metabolic network reconstruction enables scalable biological discovery
Benjamin D Heavner, Nathan D Price
Current Opinion in Biotechnology, Aug 2015; 34: 105–109
Highlights

  • Assembling a network reconstruction can reveal knowledge gaps.
  • Building a functional metabolic model enables testable prediction.
  • Recent work has found that most models contain the same reactions.
  • Reconstruction and functional model building should be explicitly separated.

Reconstructing metabolic pathways has long been a focus of active research. Now, draft models can be generated from genomic annotation and used to simulate metabolic fluxes of mass and energy at the whole-cell scale. This approach has led to an explosion in the number of functional metabolic network models. However, more models have not led to expanded coverage of metabolic reactions known to occur in the biosphere. Thus, there exists opportunity to reconsider the process of reconstruction and model derivation to better support the less-scalable investigative processes of biocuration and experimentation. Realizing this opportunity to improve our knowledge of metabolism requires developing new tools that make reconstructions more useful by highlighting metabolic network knowledge limitations to guide future research.

metabolic network reconstruction

metabolic network reconstruction

http://ars.els-cdn.com/content/image/1-s2.0-S0958166914002250-fx1.jpg

Mapping metabolic pathways has been a focus of significant scientific efforts dating from the emergence of biochemistry as a distinct scientific field in the late 19th century [1]. This endeavor remains an important effort for at least two compelling reasons. First, cataloguing and characterizing the full range of metabolic processes across species (which because of genomics are being discovered at an incredible pace) is a fundamentally important step towards a complete understanding of our ecological environment. Second, mapping metabolic pathways in organisms — many of which can be found with specialized properties shaped by their environment — facilitates metabolic engineering to advance nascent industrial biotechnology efforts ranging from augmenting/replacing petroleum-derived chemical precursors or fuels to biopharmaceutical production [2]. However, despite laudable efforts to enable high-throughput ‘genomic enzymology’ [3•], the traditional biochemical approaches of enzyme expression, purification, and characterization remain time-intensive, capital-intensive, and labor-intensive, and have not expanded in scale like our ability to identify and characterize life genomically. Characterizing new metabolic function is further hampered by the challenge of cultivating environmental isolates in laboratory conditions [4]. Fortunately, recent efforts to leverage genome functional annotation and established knowledge of biochemistry have enabled the computational assembly of ‘draft metabolic reconstructions’ [5], which are parts lists of metabolic network components. In this context, a reconstruction is not just the information embodied in the stoichiometric matrix describing metabolic network structure, but also the associated metadata and annotation that entails an organism-specific knowledge base. Such a reconstruction can serve as the basis for making functional models amenable to mathematical simulation. Thus, a reconstruction is a bottom-up assembly of biochemical information, and a model can serve as a framework for integrating top-down information (for example, model constraints can be generated from statistically inferred gene regulatory networks [6]). Such computational approaches are significantly faster and less expensive than biochemical characterization [7]. They are also providing new resources facilitate cultivation of novel environmental isolates [8], and the scope of draft metabolic network coverage across the biome has increased much faster than wet lab characterization. If the distinction between reconstruction and model formulation can be strengthened and supported through software implementation, there is great opportunity for using both tasks to further advance rapid discovery of biological function.

The iterative process of manual curation of a draft metabolic network reconstruction to assemble a higher confidence compendium of organism-specific metabolism (a process termed ‘biocuration’ [9 and 10]) remains time-intensive and labor-intensive. Biocuration of metabolic reconstructions currently advances on a decadal time scale [11 and 12]. Thus, much research effort has focused instead on developing techniques for rapid development of models that are amenable to simulation [13 and 14]. Thousands of models have been derived from automatically assembled draft reconstructions [15], but most of these models consist of highly conserved portions of metabolism since they are propagated primarily via orthology. Though the number of models is large, they do not reflect the true diversity of cellular metabolic capabilities across different organisms [16•]. Applying the rapid and scalable process of draft network reconstruction to support and accelerate the less-scalable processes of biocuration and in vitro or in vivo experimentation remains an unrealized opportunity. The path forward should focus on increased emphasis on transparently documenting the reconstruction process and developing tools to highlight, rather than obscure, knowledge limitations that ultimately cause limitations to model predictive accuracy.

More explicit annotation of metabolic network reconstruction and model derivation steps can help direct research efforts

Testing implicit hypotheses arising from reconstruction assembly provides one opportunity for guiding experimental efforts. However, the very act of identifying ambiguous information in the literature should also be exploited to contribute to experimental efforts, independent of the choices a researcher makes in assembling a reconstruction. Preliminary steps to facilitate large-scale computational identification of biological uncertainty have been made, such as the development of the Evidence Ontology [18]. However, realizing the potential for using reconstruction assembly to highlight experimental opportunities will require a broader shift to emphasize the limits of our knowledge, rather than only the predictive power of a model that can be derived from a reconstruction. Computational reconstruction of metabolic networks provides two distinct opportunities for guiding experimental efforts even before a mathematically computable model is derived from the assembled knowledge: highlighting areas of uncertainty in the current knowledge of an organism, and introducing hypotheses of metabolic function as choices are made throughout biocuration efforts.

The subsequent process of deriving a mathematically computable model from a reconstruction provides additional opportunities for scalable hypothesis generation that could be exploited to inform experimental efforts. While stoichiometrically constrained models derived from reconstructions are ‘parameter-light’ when compared to dynamic enzyme kinetic models, they are not really ‘parameter free’ [19]. As modelers derive a model from an assembled reconstruction, they must make choices. And, like the ambiguities and choices that are made and should be highlighted in assembling a reconstruction, highlighting the choices made in deriving a model provides further opportunity for scalable hypothesis generation. Examples of choices that often arise in deriving a functional model include adding intracellular transport reactions, filling network gaps, or trimming network dead ends to improve network connectivity [20]. Researchers seeking to conduct Flux Balance Analysis (FBA) [21] or similar approaches must formulate an objective function, can include testable parameters such as ATP maintenance requirements, and can compare model predictions to designated reference phenotype observations. Each of these model-building and tuning activities presents opportunities to rapidly develop and prioritize new hypotheses of metabolic function.

The effort to computationally reconstruct biochemical knowledge to compile organism-specific reconstructions, and to derive computable models from these reconstructions, is a relatively young field of research with abundant opportunity for facilitating biological discovery of metabolic function. Judgment is required in assembling a reconstruction, and there should be careful consideration of the fact that judgment calls represent an implicit hypothesis. Making these hypotheses more explicit would help guide subsequent investigation. Bernhard Palsson and colleagues call for ‘an open discussion to define the minimal quality criteria for a genome scale reconstruction’ [16•] — an effort we fully support. We believe that such a beneficial ‘minimal quality criteria’ should be guided by the goals of reproducibility and transparency, including those aspects that can help to guide discovery of novel gene functions.

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CRISPR/Cas9: Contributions on Endoribonuclease Structure and Function, Role in Immunity and Applications in Genome Engineering

Writer and Curator:Larry H Bernstein, MD, FCAP 

2.2.25

2.2.25   CRISPR/Cas9: Contributions on Endoribonuclease Structure and Function, Role in Immunity and Applications in Genome Engineering, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

This is the fourth contribution to a series on transcriptional control and cellular remodeling. The previous dealt with RNAs – mRNA, miRNA, RNAi, siRNA, shRNA, small RNAs, lncRNAs, DICER, SLICER, RISC, recombination, and related processes.  It is clear that the classical model was limited, is history, and could not predict a large universe encompassing DNA, RNA, transcription, translation, signaling, proteins, protein conformation, mRNA-miRNA interactions, protein-protein interactions, inter- and intracellular interactions, and cellular remodeling.

Cutting it close: CRISPR-associated endoribonuclease structure and function
Hochstrasser ML and Doudna JA
Trends in Biochemical Sciences, Jan 2015; 40(1):58-66
http://dx.doi.org/10.1016/j.tibs.2014.10.007

RNAi pathways in eukaryotes, as in archaea, possess an adaptive immune system consisting of repetitive genetic elements known as clustered regularly clustered interspersed short palindromic repeats (CRISPERS) and CRISPR-associated (cas) proteins. CRISPR-cas systems require small RNAs for sequence-specific detection and degradation of complex nucleic acids. Cas 5 and cas 6 enzymes have evolved to specifically recognize and process CRISPR-derived transcripts to function as small RNAs used as guides by interference complexes.

Figure 1. Overview of CRISPR RNA (crRNA) processing and comparison between CRISPR–Cas interference systems. There are three main pathways of CRISPR adaptive immunity (Types I–III) and several subtypes, each typified by a different set of Cas proteins. The first stage of the CRISPR–Cas system is acquisition, in which a foreign DNA sequence is incorporated into the host CRISPR locus. Next, the entire repeat-spacer array is transcribed into a long precursor crRNA (pre-crRNA). A single cleavage within each repeat sequence generates shorter, mature crRNAs. Some crRNAs undergo an additional trimming step. The enzymes responsible for catalysis and exact mode of crRNA processing differ in each system. The crRNA is loaded into an interference complex where it serves as a guide for targeting invasive DNA, or in Type III-B systems, RNA.

Figure 2. Fundamental structural features of CRISPR endoRNases. (A) Topology diagram of a typical Cas6 C-terminal RRM fold with key structural features labeled. (B) Two views of Thermus thermophilus Cas6e (PDB: 2Y8W) colored as in (A). For clarity, the N-terminal RRM fold has been omitted in the left panel. (C) Comparison of structures of Cas6 and Cas5c enzymes associated with different CRISPR subtypes (in parentheses), highlighting shared structural elements, colored as in (A) and (B), with the Cas5 ‘thumb’ in black (PDB: 4ILL, 2XLK, 3UFC, 4F3M). Note that no active site residues are shown for Pyrococcus furiosus Cas6-3nc because this protein is non-catalytic.

Figure 3. Structure and sequence-specific RNA binding by Cas6 enzymes. (A) First two images: Thermus thermophilus Cas6A in the apo form and bound to its product CRISPR RNA (crRNA) (PDB: apo – 4C97, product-bound – 4C8Z). Second two images: electrostatic surface potential rendering of the same enzyme in two views with the first eight nucleotides of the Pyrococcus furiosus crRNA 30 handle (PDB: 3PKM) modeled onto the structure based on alignment of the two proteins, as in Niewoehner et al. [30]. For simplicity, only one subunit of the non-crystallographic dimer is shown. (B) Pseudomonas aeruginosa Cas6f bound to its cognate RNA (PDB: 2XLK). Close-up views highlight the active site and sequence-specific interactions by the groove-binding element. (C) Sulfolobus solfataricus Cas6-1A bound to its pre-crRNA substrate (PDB: 4ILL). The active site and sequence-specific contacts made by the glycine-rich loop are shown in detail. For simplicity, only one subunit of the SsoCas6-1A dimer is shown.

CRISPRs (clustered regularly interspaced short palindromic repeats) are DNA loci containing short repetitions of base sequences. Each repetition is followed by short segments of “spacer DNA” from previous exposures to a virus.[2]

CRISPRs are found in approximately 40% of sequenced bacteria genomes and 90% of sequenced archaea.[3][4]

CRISPRs are often associated with cas genes that code for proteins related to CRISPRs. The CRISPR/Cas system is a prokaryotic immune system that confers resistance to foreign genetic elements such as plasmids and phages[5][6] and provides a form of acquired immunity. CRISPR spacers recognize and cut these exogenous genetic elements in a manner analogous to RNAi in eukaryotic organisms.[2]

Since 2013, the CRISPR/Cas system has been used for gene editing (adding, disrupting or changing the sequence of specific genes) and gene regulation in species throughout the tree of life.[7] By delivering the Cas9 protein and appropriate guide RNAs into a cell, the organism’s genome can be cut at any desired location.

It may be possible to use CRISPR to build RNA-guided gene drives capable of altering the genomes of entire populations.

Gene-editing predecessors

In the early 2000s, researchers developed zinc finger nucleases, synthetic proteins whose DNA-binding domains enable them to cut DNA at specific spots. Later, synthetic nucleases called TALENs provided an easier way to target specific DNA and were predicted to surpass zinc fingers. They both depend on making custom proteins for each DNA target, a more cumbersome procedure than guide RNAs. CRISPRs are more efficient and can target more genes than these earlier techniques.

Repeats and spacers

CRISPR loci range in size from 24 to 48 base pairs. They usually show some dyad symmetry, implying the formation of a secondary structure such as a hairpin, but are not truly palindromic. Repeats are separated by spacers of similar length. Some CRISPR spacer sequences exactly match sequences from plasmids and phages, although some spacers match the prokaryote’s genome (self-targeting spacers). New spacers can be added rapidly in response to phage infection.

http://en.wikipedia.org/wiki/CRISPR

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http://www.frontiersin.org/files/Articles/58953/fgene-04-00193-r2/image_m/fgene-04-00193-g001.jpg

http://2013.igem.org/wiki/images/thumb/c/c0/CRISPR_Cooperativity_2.png/720px-CRISPR_Cooperativity_2.png

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A CRISPR CASe for high-throughput silencing

A CRISPR CASe for high-throughput silencing

dual gRNA vector

dual gRNA vector

Genome editing with RNA-guided Cas9 nuclease in Zebrafish embryos

Genome editing with RNA-guided Cas9 nuclease in Zebrafish embryos

The role of CRISPR–Cas systems in adaptive immunity and beyond

Barrangue R
Current Opinion in Immunology 2015; 32:36–41
http://dx.doi.org/10.1016/j.coi.2014.12.008

CRISPR–Cas immune systems. CRISPR-encoded immunization and interference. In the adaptation stage, exogenous DNA is sampled and a novel spacer is integrated into the CRISPR locus; in the expression stage, the CRISPR array is transcribed and processed into small interfering CRISPR RNAs (crRNAs) that guide Cas endonucleases towards target complementary DNA in the interference stage.

Cas-mediated DNA targeting and cleavage. The Cas9 endonuclease forms a ribonucleoprotein complex in combination with the dual guide RNA (crRNA and tracrRNA), and the target dsDNA. First, the Cas9:guide RNA complex binds to proto-spacer adjacent motif (PAM) and drives the formation of an R-loop in the target DNA for genesis of a double stranded break using the RuvC and HNH nickase domains. The former primarily involves the recognition (REC) Cas9 lobe (top), and the latter is primarily driven by the nuclease (NUC) lobe (bottom). Cas-mediated targeting can aim at phage DNA for antiviral resistance (cleaved viral DNA cannot replicate), plasmid DNA to preclude the uptake and dissemination of plasmids (cleaved plasmid DNA cannot replicate), and chromosomal DNA for genome editing (insertion of mutations using endogenous DNA repair systems at the site of cleavage) or transcriptional control (dCas9 binding blocks RNA polymerase).

CRISPR-Cas9 Knockin Mice for Genome Editing and Cancer Modeling
Cell Oct 9, 2014; 159:440–455
http://dx.doi.org/10.1016/j.cell.2014.09.014

Figure2. Ex Vivo Genome Editing of Primary Immune Cells Derived from Constitutive Cas9-Expressing Mice (A) Schematic of ex vivo genome editing experimental flow. (B)Flow cytometry histogram of bone marrow cells from constitutive Cas9-expressing (green) and wild-type (blue) mice, showing Cas9-P2A-EGFP expressiononlyinCas9mice.Dataareplottedasa percentage of the total number of cells. (C) sgRNA design for targeting the mouse Myd88 locus. (D) sgRNA design for targeting the mouse A20 locus. (E) Myd88 indel analysis of constitutive Cas9expressing DCs transduced with either a Myd88targeting sgRNA (sgMyd88-1 and sgMyd88-2) or controls (CTR, average of four control sgRNAs), showing indel formation only in Myd88-targeted cells. Data are plotted as the percent of Illumina sequencing reads containing indels at the target site. Mutations are categorized as frameshift (fs, yellow bar) or non-frameshift (nfs, orange bar). (F) A20 indel analysis of constitutive Cas9-expressing DCs transduced with either an A20-targeting sgRNA (sgA20-1) or controls (CTR, average of four control sgRNAs), showing indel formation only in A20-targeted cells. Data are plotted as the percent of Illumina sequencing reads containing indels at the target site. Mutations are categorized as frameshift (fs, yellow bar) or non-frameshift (nfs, orange bar). (G) Myd88 mRNA quantification of constitutive Cas9-expressing DCs transduced with either Myd88-targeting sgRNA (sgMyd88-1 or sgMyd882) or controls (CTR, average of six control sgRNAs), showing reduced expression only in Myd88-targeted cells. Data are plotted as Myd88 mRNA levels from Nanostring nCounter analysis. (H) Immunoblot of constitutive Cas9-expressing DCs transduced with either Myd88-targeting sgRNA (sgMyd88-1 or sgMyd88-2) or controls (four control sgRNAs), showing depletion of MyD88 protein only in Myd88-targeted cells. b-actin was used as a loading control. (*) Overexposed, repeated-measurement. (I) Nanostring nCounter analysis of constitutive Cas9-expressing DCs transduced with either Myd88-targeting sgRNA (sgMyd88-1 or sgMyd882) or shRNA (shMyd88), A20-targeting sgRNA (sgA20-1 or sgA20-2), or shRNA (shA20), showing analtered LPS response.(Inset)Theclustershowing the highest difference between Myd88- and A20 targeting sgRNAs, including key inflammatory genes(IL1a,IL1b,Cxcl1,Tnf,etc.).(Red)High;(blue) low; (white) unchanged; based on fold change relative to measurements with six control sgRNAs. See also Figure S2.

Figure 5. In Vivo Tumor Formation in AAV9-KPL-Injected Mice (A) Lung mCT images of Cre-dependent Cas9 mice injected with either AAV9-KPL or AAV9-sgLacZ 2 months posttransduction, showing tumor formation (indicated by the arrowhead) only in AAV9-KPL injected mice. (B)LungmCT3DrenderingofCre-dependent Cas9 mice injected with AAV9-KPL 2 months posttransduction, showing tumor formation (indicated by a yellow oval). (C) Major tumor burden quantification of Cre-dependent Cas9 mice injected with either AAV9-KPL or AAV9-sgLacZ, showing significant tumor burden in AAV9KPL-injected mice. Data are plotted as mean ± SEM. **p < 0.005. (D) Representative lung H&E images of Cre-dependent Cas9 mice injected with either AAV9-KPL or AAV9-sgLacZ 9 weeks posttransduction, showing heterogeneous tumor formation in AAV9-KPL-injected mice. Arrowheads highlight a representative subset of tumors within the lungs of AAV9-KPL injected mice.

Development and Applications of CRISPR-Cas9 for Genome Engineering
Zhu PD, Lander ES, Zhang F
Cell Jun 5, 2014; 157:1262-1278
http://dx.doi.org/10.1016/j.cell.2014.05.010

Figure 1. Applications of Genome Engineering Genetic and epigenetic control of cells with genome engineering technologies is enabling a broad range of applications from basic biology to biotechnology and medicine. (Clockwise from top) Causal genetic mutations or epigenetic variants associated with altered biological function or disease phenotypes can nowberapidlyandefficientlyrecapitulated inanimalorcellularmodels (Animal models, Genetic variation). Manipulating biological circuits couldalso facilitate the generation of useful synthetic materials, such as algae-derived, silicabased diatoms for oral drug delivery (Materials). Additionally, precise genetic engineering of important agricultural crops could confer resistance to environmental deprivation or pathogenic infection, improving food security while avoiding the introduction of foreign DNA (Food). Sustainable and cost-effective biofuels are attractive sources for renewable energy, which could be achieved by creating efficient metabolic pathways for ethanol production in algae or corn (Fuel). Direct in vivo correction of genetic or epigenetic defects in somatic tissue would be permanent genetic solutions that address the root cause of genetically encoded disorders (Gene surgery). Finally, engineering cells to optimize high yield generation of drug precursors in bacterial factories could significantly reduce the cost and accessibility of useful therapeutics (Drug development).

Figure 2. Genome Editing Technologies Exploit Endogenous DNA Repair Machinery (A) DNA double-strand breaks (DSBs) are typically repaired by nonhomologous end-joining (NHEJ) or homology-directed repair (HDR). In the errorprone NHEJ pathway, Ku heterodimers bind to DSB ends and serve as a molecular scaffold for associated repair proteins. Indels are introduced when the complementary strands undergo end resection and misaligned repair due to microhomology, eventually leading to frameshift mutations and gene knockout. Alternatively, Rad51 proteins may bind DSB ends during the initial phase of HDR, recruiting accessory factors that direct genomic recombination with homology arms on an exogenous repair template. Bypassing the matching sister chromatid facilitates the introduction of precise gene modifications. (B) Zinc finger (ZF) proteins and transcription activator-like effectors (TALEs) are naturally occurring DNA-binding domains that can be modularly assembled to target specific sequences. ZF and TALE domains each recognize 3 and 1 bp of DNA, respectively. Such DNA-binding proteins can be fused to the FokI endonuclease to generate programmable site-specific nucleases. (C) The Cas9 nuclease from the microbial CRISPR adaptive immune system is localized to specific DNA sequences via the guide sequence on its guide RNA (red), directly base-pairing with the DNA target. Binding of a protospacer-adjacent motif (PAM, blue) downstream of the target locus helps to direct Cas9-mediated DSBs.

Figure 3. Key Studies Characterizing and Engineering CRISPR Systems Cas9 has also been referred to as Cas5, Csx12, and Csn1 in literature prior to 2012. For clarity, we exclusively adopt the Cas9 nomenclature throughout this Review. CRISPR, clustered regularly interspaced short palindromic repeats; Cas, CRISPR-associated; crRNA, CRISPR RNA; DSB, double-strand break; tracrRNA, trans-activating CRISPR RNA.

Figure 4. Natural Mechanisms of Microbial CRISPR Systems in Adaptive Immunity Following invasion of the cell by foreign genetic elements from bacteriophages or plasmids (step 1: phage infection), certain CRISPR-associated (Cas) enzymes acquire spacers from the exogenous protospacer sequences and install them into the CRISPR locus within the prokaryotic genome (step 2: spacer acquisition). These spacers are segregated between direct repeats that allow the CRISPR system to mediate self and nonself recognition. The CRISPR array is a noncoding RNA transcript that is enzymatically maturated through distinct pathways that are unique to each type of CRISPR system (step 3: crRNA biogenesis and processing). In types I and III CRISPR, the pre-crRNA transcript is cleaved within the repeats by CRISPR-associated ribonucleases, releasing multiple small crRNAs. Type III crRNA intermediates are further processed at the 30 end by yet-to-be-identified RNases to produce the fully mature transcript. In type II CRISPR, an associated trans-activating CRISPR RNA (tracrRNA) hybridizes with the direct repeats, forming an RNA duplex that is cleaved and processed by endogenous RNase III and other unknown nucleases. Maturated crRNAs from type I and III CRISPR systems are then loaded onto effector protein complexes for target recognition and degradation. In type II systems, crRNA-tracrRNA hybrids complex with Cas9 to mediate interference. Both type I and III CRISPR systems use multiprotein interference modules to facilitate target recognition. In type I CRISPR, the Cascade complex is loaded with a crRNA molecule, constituting a catalytically inert surveillance complex that recognizes target DNA. The Cas3 nuclease is then recruited to the Cascade-bound R loop, mediating target degradation. In type III CRISPR, crRNAs associate either with Csm or Cmr complexes that bind and cleave DNA and RNA substrates, respectively. In contrast, the type II system requires only the Cas9 nuclease to degrade DNA matching its dual guide RNA consisting of a crRNA-tracrRNA hybrid.

Figure 5. Structural and Metagenomic Diversity of Cas9 Orthologs (A) Crystal structure of Streptococcus pyogenes Cas9 in complex with guide RNA and target DNA. (B) Canonical CRISPR locus organization from type II CRISPR systems, which can be classified into IIA-IIC based on their cas gene clusters. Whereas type IIC CRISPR loci contain the minimal set of cas9, cas1, and cas2, IIA and IIB retain their signature csn2 and cas4 genes, respectively. (C) Histogram displaying length distribution of known Cas9 orthologs as described in UniProt, HAMAP protein family profile MF_01480. (D) Phylogenetic tree displaying the microbial origin of Cas9 nucleases from the type II CRISPR immune system. Taxonomic information was derived from greengenes 16S rRNA gene sequence alignment, and the tree was visualized using the Interactive Tree of Life tool (iTol). (E) Four Cas9 orthologs from families IIA, IIB, and IIC were aligned by ClustalW (BLOSUM). Domain alignment is based on the Streptococcus pyogenes Cas9, whereas residues highlighted in red indicate highly conserved catalytic residues within the RuvC I and HNH nuclease domains.

Figure 6. Applications ofCas9 as aGenome Engineering Platform (A) The Cas9 nuclease cleaves DNA via its RuvC and HNHnucleasedomains,eachofwhichnicks a DNA strand to generate blunt-end DSBs. Either catalytic domain can be inactivated to generate nickase mutants that cause single-strand DNA breaks. (B) Two Cas9 nickase complexes with appropriatelyspacedtargetsitescanmimictargetedDSBs viacooperative nicks, doubling thelengthof target recognition without sacrificing cleavage efficiency. (C) Expression plasmids encoding the Cas9 gene and a short sgRNA cassette driven by the U6 RNA polymerase III promoter can be directly transfected into cell lines of interest. (D) Purified Cas9 protein and in vitro transcribed sgRNA can be microinjected into fertilized zygotes for rapid generation of transgenic animal models. (E) For somatic genetic modification, high-titer viral vectors encoding CRISPR reagents can be transduced into tissues or cells of interest. (F) Genome-scale functional screening can be facilitated by mass synthesis and delivery of guide RNA libraries. (G) Catalytically dead Cas9 (dCas9) can be converted into a general DNA-binding domain and fused to functional effectors such as transcriptional activators or epigenetic enzymes. The modularity of targeting and flexible choice of functional domains enable rapid expansion of the Cas9 toolbox. (H) Cas9 coupled to fluorescent reporters facilitates live imaging of DNA loci for illuminating the dynamics of genome architecture. (I) Reconstituting split fragments of Cas9 via chemical or optical induction of heterodimer domains, such as the cib1/cry2 system from Arabidopsis, confers temporal control of dynamic cellular processes.

Characterization and Optimization of the CRISPR/Cas System for Applications in Genome Engineering
http://nrs.harvard.edu/urn-3:HUL.InstRepos:12407619

Two important advances in the last several decades have propelled our understanding of molecular processes far beyond descriptions of biology at macroscopic levels and fundamentally altered the way that we comprehend organisms, tissues, and cells. First, growing hand in hand with the exponential expansion of computing power, the development of genome sequencing technology, enabling high resolution mapping of DNA sequences, has allowed us to define, down to the nucleotide level, differences between multiple species, members of a species, and within an individual, between classes of cells, as well as diseased and malignant cells. At this point, our ability to make sense of this wealth of genomic information is only limited by our ability to make ever-more precise cellular and genomic alterations to which we may ascribe a phenotypic change. To achieve this, we have concurrently created tools that have allowed us to query the functions of genes and genetic variations from scales large to small by means of first random and then targeted mutagenesis, followed by increasingly refined means of manipulating either the genome directly or the activity of the genes themselves at the level of RNA or protein.

The ability to precisely manipulate the genome in a targeted manner is fundamental to driving both basic science research and development of medical therapeutics. Until recently, this has been primarily achieved through coupling of a nuclease domain with customizable protein modules that recognize DNA in a sequence-specific manner such as zinc finger or transcription activator-like effector domains. Though these approaches have allowed unprecedented precision in manipulating the genome, in practice they have been limited by the reproducibility, predictability, and specificity of targeted cleavage, all of which are partially attributable to the nature of protein-mediated DNA sequence recognition. It has been recently shown that the microbial CRISPR-Cas system can be adapted for eukaryotic genome editing. Cas9, an RNA guided DNA endonuclease, is directed by a 20-nt guide sequence via Watson-Crick base-pairing to its genomic target. Cas9 subsequently induces a double-stranded DNA break that results in targeted gene disruption through non-homologous end-joining repair or gene replacement via homologous recombination. Finally, the RNA guide and protein nuclease dual component system allows simultaneous delivery of multiple guide RNAs (sgRNA) to achieve multiplex genome editing with ease and efficiency.

The potential effects of off-target genomic modification represent a significant caveat to genome editing approaches in both research and therapeutic applications. Prior work from our lab and others has shown that Cas9 can tolerate some degree of mismatch with the guide RNA to target DNA base pairing. To increase substrate specificity, we devised a technique that uses a Cas9 nickase mutant with appropriately paired guide RNAs to efficiently inducing double-stranded breaks via simultaneous nicks on both strands of target DNA. As single-stranded nicks are repaired with high fidelity, targeted genome modification only occurs when the two opposite-strand nicks are closely spaced. This double nickase approach allows for marked reduction of off-target genome modification while maintaining robust on-target cleavage efficiency, making a significant step towards addressing one of the primary concerns regarding the use of genome editing technologies.

The ability to multiplex genome engineering by simply co-delivering multiple sgRNAs is a versatile property unique to the CRISPR-Cas system. While co-transfection of multiple guides is readily feasible in tissue culture, many in vivo and therapeutic applications would benefit from a compact, single vector system that would allow robust and reproducible multiplex editing. To achieve this, we first generated and functionally validated alternate sgRNA architectures to characterize the structure-function relationship of the Cas9 protein with the sgRNA in DNA recognition and cleavage. We then applied this knowledge towards the development and optimization of a tandem synthetic guide RNA (tsgRNA) scaffold that allows for a single promoter to drive expression of a single RNA transcript encoding two sgRNAs, which are subsequently processed into individual active sgRNAs.

A programmable genome editing tool fundamentally consists of two key elements: a DNA recognition domain conferring target specificity and a nuclease domain, ideally without any sequence specificity on its own. A key breakthrough came with the observation that the restriction enzyme FokI has molecularly distinct binding and cleavage domains, and that swapping of recognition domains could alter FokI targeting specificity. Prior to this realization, zinc fingers were discovered as a class of protein motifs in X. laevi, and found to be frequently occurring in mammalian cells as transcription factors where bind DNA in a modular, sequence specific manner. Each individual module of a Cys2-His2 zinc finger domain, the most commonly used ZF-type domain in genome engineering applications, contains approximately 30 amino acids that fold to interact with 3-bp of DNA.

With the creation of custom zinc-finger arrays capable of targeting any DNA sequence, either through stringing together of pre-defined modules with known, predicted 3bp-binding affinity or selection-based protocols with randomized ZF array libraries to account and optimize for inter-modular interactions, the pairing of the DNA-targeting ZF and FokI nuclease components created a new class of zinc finger nucleases (ZFNs) that quickly proved to be an adaptable and efficient method for targeting specific genomic loci in a variety of model organisms. While zinc finger technology can in theory target any specific genomic sequence, the difficulty of accurately predicting protein conformational folding and DNA-protein interactions prior to array assembly can make ZFN construction a somewhat tedious and costly process involving a substantial validation phase prior to practical use.

More recently, an analogous, simpler alternative was developed following the deciphering of the DNA recognition patterns of another class of proteins: the transcription activator-like effector proteins (TALEs). First observed in the rice pathogen Xanthomonas, these proteins consisted of naturally occurring modular arrays of 33-35 amino acid domains, each interacting with a single base pair. Although the single base discrimination of TALE modules compared to 3bp recognition in ZF domains provides greater ease and flexibility in designing TALE arrays to genomic targets, the inherently repetitive nature of TALE repeats posed a technical challenge that required the development of new assembly methodologies. Even so, given the modular separation of DNA recognition activity from nuclease or other effector domains, TALE-derived proteins have been able to quickly co-opt existing technology generated by the studies involving ZF proteins to similarly demonstrate effective genome editing capabilities in a wide variety of model organisms and systems.

One of the major limitations of the aforementioned genome-engineering technologies is their intrinsic dependence on protein-DNA interactions to drive specificity. As such, even after following rational design or thorough in vitro selection processes, it is necessary to perform extensive in vitro validation as protein activity and affinity may vary depending on the specific context in unpredictable ways. Practically, these factors necessitate the construction of multiple sets of TALENs or ZFNs for each locus targeted and, as a consequence, make high-throughput screening applications less tractable.

Although not directly manipulating the genome, the use of small-interfering RNAs (siRNA) to modulate gene expression represents a powerful alternative technology that is not bound by many of the short-comings of these existing genome editing technologies and revolutionized our ability to functionally interrogate the genome. The foundational observation was first made in C. elegans, that the introduction of double-stranded RNA into a cell results in potent post- transcriptional silencing of gene or genes carrying sequences complementary to the exogenous sequence. There are a number of key features that made the RNAi approach particularly tractable and drove its widespread and rapid adoption in basic science research.

  1. RNAi is an extremely efficient method of gene silencing. It is not uncommon to achieve greater than 85% gene knockdown, which, while not complete, is often more than sufficient for inducing a phenotype by which to assess gene function.
  2. siRNA targeting is mediated by predictable Watson-Crick base-pairing. This has allowed the elucidation of design parameters to both maximize on-target silencing and minimize off-target effects. Additionally, the relative ease of designing and creating siRNA constructs allows for rapid prototyping and validation of new targets.
  3. the mechanism of siRNA action takes advantage of a highly-conserved endogenous pathway for processing small RNAs, which minimizes the amount of material that needs to be delivered for adequate effect.

This has had a number of key impacts including but not limited to the possibility of multiplexed delivery to silence more than a single gene at a time or to target a single gene with multiple siRNAs to maximize knock-down, as well as the generation of large siRNA libraries allowing the development of high-throughput screening methodologies for rapid phenotyping in different contexts. The efficacy, predictability, and generalizability of RNAi technologies provided it with enough compelling qualities to become a truly disruptive technology in the field of genome engineering.

Re-purposing the bacterial CRISPR/Cas system for genome editing

The RNA-guided CRISPR (clustered regularly interspaced short palindromic repeats) endonuclease system was first observed in E. coli in 1987 by its striking eponymous genomic structure evolved as an adaptive immune system, bacteria and archaea use a set of CRISPR- associated (Cas) genes to incorporate exogenous material into the CRISPR locus, and subsequently transcribe them as RNA templates for targeted destruction of the mobile elements at either DNA or RNA level.

Three types of CRISPR systems have been identified to date, differing in their targets as well as mechanisms of action. Type I and III CRISPR systems employ an ensemble of Cas gene to carryout RNA processing, recognition of target, and cleavage33,34. By contrast, the type II CRISPRCas system makes use of a single endonuclease, Cas9, to locate and cleave target DNA. Cas9 is guided by a pair non-coding RNAs, a guide-bearing and variable crRNA and a required auxiliary transactivating crRNA (tracrRNA). The crRNA contains a 20-nt guide sequence, also known as a spacer, that determines target specificity by via Watson-Crick base-pairing with target DNA, followed by the invariant “direct repeat” portion that base-pairs with the “antirepeat” portion of the tracrRNA to form an RNA duplex. In the native bacterial system, multiple crRNAs are co-transcribed as a pre-crRNA array before being processed down to individual units for directing Cas9 against various targets. In the CRISPR-Cas system derived from Streptococcus pyogenes, the target DNA sequence always precedes a 5’-NGG protospacer adjacent motif (PAM), which can differ depending on the CRISPR system.

The S. pyogenes CRISPR-Cas system was the first to be reconstituted in mammalian cells through the heterologous expression of human codon-optimized Cas9 and the two RNA components. By altering the the 20-nt guide sequence within the sgRNA, Cas9 can be redirected toward any target bearing an appropriate PAM. Furthermore, elements from the crRNA and tracrRNA can be artificially linked to create a chimeric, single guide RNA (sgRNA), further simplifying the system for eukaryotic gene targeting.

At an overall structural level, Cas9 contains two nuclease domains, HNH and RuvC, each of which cleaves one strand of the target DNA. A mutation in either one of its catalytic domains converts Cas9 nuclease into a nickase, which has shown to induce single-stranded breaks for high-fidelity HDR applications, potentially ameliorating unwanted indel mutations from off target DSBs. Finally, a catalytically inactive or dead Cas9 (dCas9) with mutations in both DNA-cleaving catalytic residues can serve as an RNA-guided DNA-binding scaffold for localizing target effector domains that gene expression at the transcriptional level.

Engineering synthetic TALE and CRISPR-Cas9 transcription factors for regulating gene expression
Methods 2014; 69:188-197
http://dx.doi.org/10.1016/j.ymeth.2014.06.014

Fig.1. TheTAL effectorDNA-binding domain.(A) Through a DNA–protein interaction, each TALE repeatbinds one bp of DNA.TheTALE repeat is shown in blue, and the repeat variable di residue (RVD) at the 12th and 13th position are shown in green and red, respectively. (B) TALEs can be linked in tandem to recognize virtually any DNA sequence. The desired string of TALEs is then fused to an effector domain to induce a specific action at a predetermined DNA sequence. Crystal structure adapted from [60].

Fig. 2. The CRISPR/Cas9 DNA-binding domain. The Cas9 protein forms a complex with the gRNA, which recognizes a specific 20 bp DNA target sequence, known as the protospacer. A short sequence directly downstream from the protospacer, the protospacer adjacent motif (PAM),is requiredfor Cas9-mediated cleavage. ThePAM sequence is highly variable between different organisms (Table 2). With only two amino acid substitutions (D10A and H840A), Cas9 endonuclease activity can been eliminated while maintaining its RNA-guided DNA-binding activity. This deactivated Cas9 (dCas9) functions as a modular DNA-binding domain, similar to TALEs. RNA-guided transcriptional activators and repressors have been created by fusing dCas9 with different effector domains.

Fig.3. Golden gate assembly ofTALEs.Golden Gate assembly makesuse of type IIS restriction enzymes, including BsaI, BsmBI,and Esp3I, that cleave outside their recognition sequence to create unique overhangs. Therefore it is possible to digest and ligate multiple inserts into a destination plasmid with a single restriction enzyme in a single reaction. In step 1, single RVDs are excised from module plasmids and ligated into the desired array plasmid (sample overhangs are shown). This platform allows for construction ofup to 10RVDsinto each array plasmid. Importantly,the array plasmids confer spectinomycin resistance (SpecR) rather than tetracycline resistance (TetR). This ensures that only successfully assembled array plasmids are propagated. In step 2, the array plasmids and the last repeat (LR) plasmid are assembled in a second Golden Gate reaction to obtain the final desired TALE construct. Similar to step 1, in step 2 the final backbone vector confers ampicillin resistance (AmpR), rather than spectinomycin or tetracycline resistance, to ensure that only successfully assembled vectors are propagated. Replacement of the b-galactosidase expression cassette (LacZ) in the final step allows for blue-white screening of successful ligations. Figure adapted from [37].

Fig. 4. Custom gRNA cloning. The most common gRNA cloning methods make use of the BbsI type IIS restriction enzyme that cleaves outside its recognition sequence to create unique overhangs. Single stranded oligonucleotides containing each protospacer are annealed to create overhangs that are compatible with the BbsI sites in the destination vector. Upon ligation, the protospacer is inserted directly following the human U6 promoter and in front of the remainder of the chimeric gRNA sequence. The underlined G indicates the transcriptional start site.

The CRISPR/Cas9 gRNA Targeting System

The recent discovery of the CRISPR/Cas9 sysem has provided researchers an invaluable tool to target and modify any genomic sequence with high levels of efficacy and specificity. The system, consisting of a nuclease (Cas9) and a DNA-directed guide RNA (gRNA), allows for sequence-specific cleavage of target sequence containing a protospacer adaptor motif “NGG”. By changing the gRNA target sequence, virtually any gene sequence upstream of a PAM motif can be targeted by the CRISPR/Cas9 system, enabling the possibility of systematic targeting of sequences on a genomic scale. The most successful gene targeting using the CRISPR/Cas9 system is through expression of multiple gRNAs to guide the enzyme complex to several locations within the target gene to be cut or nicked.

The scalability of the Multiplex gRNA Cloning Kit allows for simultaneous cloning of two or more gRNAs at once into a single vector. This enables researchers to perform more advanced CRISPR/Cas9 techniques such as tandem double-nicking (4 gRNAs total) to remove defined genomic segments using Cas9 Nickase with significantly decreased chances for off-target effects.

The cloning of four gRNAs will require the researcher to perform three separate PCR reactions with separate primer pairs and blocks. Once the correct size amplicons are generated and gel-purified, they can be mixed at equimolar ratios (1:1:1) based on their concentrations and used as inserts in the subsequent fusion reaction with a suitable linearized destination vector.

https://www.systembio.com/downloads/Multiplex-gRNA-Cas9-system_ver5.pdf

https://www.systembio.com/images/How-quad-plex-cloning-works.jpg

https://www.addgene.org/static/data/easy-thumbnails/filer_public/cms/filer_public/7a/b2/7ab294b8-7f7a-4c30-8650-dbb520e2beb4/grna-and-cas9_1.jpg__600x277_q85_subsampling-2_upscale.png

Generation and utility of genetically humanized mouse models
Scheer N, Snaith M, Wolf CR, and Seibler J
Drug Discov Today 2013; 18(23/24):1200-1210
http://dx.doi.org/10.1016/j.drudis.2013.07.007

Applications of genetically humanized mouse models
Type of humanized mouse model Applications
Proteins involved in drug metabolismand disposition Drug–drug interaction studies
Identification and safety assessmentof human metabolites

Assessment of drug bioavailability

and clearance
PKPD modelling

Proteins of the immune and hematopoietic system Studying infectious diseases
Vaccine development and testingStudying autoimmune disorders, ..

involving the immune system

Discovery and testing of antibodies

for therapeutic use

Supported engraftment of human

cells in mice

Proteins involved in pathogeninfection Studying human infectiousdiseases
Aneuploidies or chromosomalre-arrangements Studying human hereditarydiseases
Drug targets Efficacy testing
Human regulatory elements Studying human gene expressionand regulation
Human proto-oncogenes ortumor suppressor genes Cancerogenicity testing

Components of the major pathway for drug metabolism and disposition.

Ligand-dependent activation of the xenobiotic receptors PXR, CAR, PPARa and AHR leads to a translocation to the nucleus and, together with their respective heterodimerization partners retinoic X receptor (RXR) and aryl hydrocarbon receptor nuclear translocator (ARNT), to binding of corresponding response elements and an induction of target genes.

Identifying Drug-Target Selectivity of Small-Molecule CRM1/XPO1 Inhibitors by CRISPR-Cas9 Genome Editing
JE Neggers, et al.
Chemistry & Biology , Jan 22, 2015; 22:107–116
http://dx.doi.org/10.1016/j.chembiol.2014.11.015

Figure 1. Generation of a Mutant XPO1C528S Cell Line Using CRISPR/Cas9 Genome Editing and Homologous Recombination (A) A schematic presentation of the two SINE compounds KPT-185 and KPT-330. (B) Schematic overview of the CRISPR/Cas9induced homologous recombination of human XPO1. Exons are represented by open thick arrows. The blue arrow indicates the sgRNA target site, and small arrowheads beneath the exons indicate forward and reverse PCR A or sequencing primersB.Thesiteofrecombinationis enlarged, and the location of the double strand break (scissors and arrow) is shown. Both the WT XPO1 and donor mutant template sequences are shown at the bottom (magenta, PAM motif; bold, cysteine 528 codon; red, template mutations; underlined, sgRNA sequence). (C) Sequencing chromatogram of genomic DNA of the XPO1 region around the targeted cysteine codon (in bold) from XPO1C528S cells (clone 6).See also Figure S1 and Table S1. (D) Partial protein sequence of XPO1 in WT and mutant XPO1C528S cells (clone 6). Residue 528 of XPO1 is shown in bold. (E) Sequencing chromatogram of the mRNA from XPO1C528S cells (clone 6) in the XPO1 region around the targeted cysteine codon. (F) Visualization of XPO1 protein expression in WT and mutant XPO1C528S cells (clone 6) by immunoblot with b-tubulin as loading control. (G) Relative comparison of XPO1 mRNA expression levels quantified with a probe specific to exon 2 of XPO1 (unpaired student’s t test p value, <0.0001). GAPDH and b-actin were used as internal controls. (H) Relative comparison of mean XPO1 protein expression in WT and XPO1C528S cells (clone 6) as measured by immunofluorescence staining and quantified by confocal fluorescence microscopy (unpaired student’s t test p value, <0.0001). Error bars indicate the 95% confidence interval.

Repurposing CRISPR as an RNA-Guided platform for sequence-specific control of gene expression
LS Qi. MH Larson, LA Gilbert, JA Duoda, et al.
Cell Feb 28, 2013; 152:1173–1183
http://dx.doi.org/10.1016/j.cell.2013.02.022

Figure 1. Design of the CRISPR Interference System (A)Theminimalinterferencesystemconsistsofasingleproteinandadesigned sgRNA chimera. The sgRNA chimera consists of three domains (boxed region): a 20 nt complementary region for specific DNA binding, a 42 nt hairpin for Cas9 binding (Cas9 handle), and a 40 nt transcription terminator derived from S. pyogenes. The wild-type Cas9 protein contains the nuclease activity. The dCas9 protein is defective in nuclease activity. (B) The wild-type Cas9 protein binds to the sgRNA and forms a protein-RNA complex. The complex binds to specific DNA targets by Watson-Crick base pairing between the sgRNA and the DNA target. In the case of wild-type Cas9, the DNA will be cleaved due to the nuclease activity of the Cas9 protein. We hypothesize that the dCas9 is still able to form a complex with the sgRNA and bind to specific DNA target. When the targeting occurs on the protein-coding region, it could block RNA polymerase and transcript elongation. See also Figure S1

Figure 2. CRISPRi Effectively Silences Transcription Elongation and Initiation (A) The CRISPRi system consists of an inducible Cas9 protein and a designed sgRNA chimera. The dCas9 contains mutations of the RuvC1 and HNH nuclease domains. The sgRNA chimera contains three functional domains, as described in Figure 1. (B) Sequence of designed sgRNA (NT1) and the DNA target. NT1 targets the nontemplate DNA strand of the mRFP-coding region. Only the region surrounding the base-pairing motif (20 nt) is shown. Base-pairing nucleotides are shown in orange, and the dCas9-binding hairpin is in blue. The PAM sequence is shown in red. (C) CRISPRi blocks transcription elongation in a strand-specific manner. A synthetic fluorescence-based reporter system containing an mRFP-coding gene is inserted into the E.coli MG1655 genome (then sfA locus). Six sgRNAs that bind to either the template DNA strand or the nontemplate DNA strand are coexpressed with the dCas9 protein, with their effects on the target mRFP measured by in vivo fluorescence assay. Only sgRNAs that bind to the nontemplate DNA strand showed silencing (10- to 300-fold). The control shows fluorescence of the cells with dCas9 protein but without the sgRNA. (D) CRISPRi blocks transcription initiation. Five sgRNAs are designed to bind to different regions around an E.coli promoter (J23119). The transcription start site is labeled as +1. The dotted oval shows the initial RNAP complex that covers a 75 bp region from 55 to +20. Only sgRNAs targeting regions inside of the initial RNAP complex show repression (P1–P4). Unlike transcription elongation block, silencing is independent of the targeted DNA strand. (E) CRISPRi regulation is reversible. Both dCas9 and sgRNA (NT1) are under the control of an aTc-inducible promoter. Cell culture was maintained during exponential phase. At timeT=0, 1mM of a Tc was supplemented to cells with OD=0.001. Repression of target mRFP starts within 10min.The fluorescence signal decays in a way that is consistent with cell growth, suggesting that the decay is due to cell division. In 240 min, the fluorescence reaches the fully repressed level. At T= 370 min, a T cis washed away from the growth media, and cells are diluted back to OD = 0.001. Fluorescence starts to increase after 50 min and takes about 300 min to rise to the same level as the positive control. Positive control: always without the inducer; negative control: always with 1 mM aTc inducer. Fluorescence results in (C)–(E) represent average and SEM of at least three biological replicates. See also Figures S2 and S3.

Figure 3. CRISPRi Functions by Blocking Transcription Elongation (A) FLAG-tagged RNAP molecules were immunoprecipitated, and the associated nascent mRNA transcripts were sequenced. (Top) Sequencing results of the nascent
mRFP transcript in cells without sgRNA. (Bottom) Results in cells with sgRNA. In the presence of sgRNA, a strong transcriptional pause is observed 19 bp upstream of the target site, after which the number of sequencing reads drops precipitously. (B) A proposed CRISPRi mechanism based on physical collision between RNAP and dCas9-sgRNA. The distance from the center of RNAP to its front edge is ~19 bp, which matches well with our measured distance between the transcription pause site and 30 of sgRNA base-pairing region. The paused RNAP aborts transcription elongation upon encountering the dCas9-sgRNA roadblock.

Figure 4. Targeting Specificity of the CRISPRi System (A) Genome-scale mRNA sequencing (RNA-seq) confirms that CRISPRi targeting has no off-target effects. The sgRNA NT1 that bindsto the mRFP coding region is used. The dCas9, mRFP, and sfGFP genes are highlighted. (B)Multiple sgRNAs can independently silence two fluorescent protein reporters in the same cell. Each sgRNA specifically represses its cognate gene,but not the other gene. When both sgRNAs are present, both genes are silenced. Error bars represent SEM from at least three biological replicates. (C) Microscopic images for using two sgRNAs to control two fluorescent proteins. (Top) Bright-field images of the E. coli cells; (middle) RFP channel; (bottom) GFP channel. Coexpression of one sgRNA and dCas9 only silences the cognate fluorescent protein, but not the other. The knockdown effect is strong, as almost no fluorescence is observed from cells with certain fluorescent protein silenced. Scale bar, 10 mm. Control shows cells without any fluorescent protein reporters.

In vitro and in vivo growth suppression of human papillomavirus 16-positive cervical cancer cells by CRISPR-Cas9
S Zhen, L Hua, et al.
BBRC 2014; 450:1422-1426
http://dx.doi.org/10.1016/j.bbrc.2014.07.014

Fig. 4. Suppression of in vivo growth of SiHa cells in BALB/c nude mice by CRISPR/ Cas9. (A) In vivo tumor growth curves of CRISPR/Cas9 systems-treated SiHa cells. The mean tumor volumes ± SD (bars) are shown at the times that tumor measurements were made (n = 6). (B) Tumor weight 10 weeks after inoculation. All tumors were excised and weighted.

One-Step Generation of Mice Carrying Mutations in Multiple Genes by CRISPR-Cas-mediated genome engineering
Wang H, Yang H, et al.
Cell  2013; 153:910-918
http://dx.doi.org/10.1016/j.cell.2013.04.025

Figure 2. Single- and Double-Gene Targeting In Vivo by Injection into Fertilized Eggs (A) Genotyping of Tet1 single-targeted mice. (B) Upper: genotyping of Tet2 single-targeted mice. RFLP analysis; lower: Southern blot analysis. (C) The sequence of both alleles of targeted gene in Tet1 biallelic mutant mouse 2 and Tet2 biallelic mutant mouse 4. (D) Genotyping of Tet1/Tet2 double-mutant mice. Analysis of mice 1 to 12 is shown. Upper: RFLP analysis; lower: southern blot analysis. The Tet1 locus is displayed on the left and the Tet2 locus on the right. (E) The sequence of four mutant alleles from double-mutant mouse 9 and 10. PAM sequences are labeled in red. (F) Three-week-old double-mutant mice. All RFLP and Southern digestions and probes are the same as those used in Figure 1. See also Figures S2 and S3.

The impact of CRISPR–Cas9 on target identification and validation
JD Moore
Drug Discov Develop 2015
http://dx.doi.org/10.1016/j.drudis.2014.12.016

Gene editing with Cas9. (a) Knock-out generation via Cas9 and a single synthetic guide (sg)RNA. sgRNAs form Watson–Crick base pairs with target sequences recruiting the wild-type Cas9 nuclease. Cas9 generates double stranded breaks that are typically repaired by the imprecise NHEJ mechanism resulting in small insertions or deletions, most of which generate frameshift mutations. Transient expression of sgRNA plus Cas9 leads to editing of 2–25% of alleles. Derivative clones are analysed to find examples where Gene editing with Cas9. (a) Knock-out generation via Cas9 and a single synthetic guide (sg)RNA. sgRNAs form Watson–Crick base pairs with target sequences recruiting the wild-type Cas9 nuclease. Cas9 generates double stranded breaks that are typically repaired by the imprecise NHEJ mechanism resulting in small insertions or deletions, most of which generate frameshift mutations. Transient expression of sgRNA plus Cas9 leads to editing of 2–25% of alleles. Derivative clones are analysed to find examples where both alleles have been repaired with frame shift mutations. (b) Knock-out generation via Cas9 and a pair of sgRNAs. When wild-type Cas9 is expressed with a pair of sgRNAs targeting sites in the same region of a gene, simultaneous dual double-stranded breaks will be introduced in a fraction of cells. Repair via NHEJ will tend to delete the intervening sequence. (c) Knock-in generation using sgRNAs, donor DNA and either wild-type Cas9 or the Cas9-D10A nickase mutant. Wild-type Cas9 generates double stranded breaks that can be repaired by NHEJ generating indels or by homology-directed repair (HDR) leading to knock-in of mutations present on homology templates. The Cas9-D10A nickase mutant only generates single stranded breaks, which are not a substrate for the NHEJ pathway. However, these can be processed by HDR leading to the introduction of knock-in mutations. (d) Using the Cas9D10A nickase mutant to enhance the specificity of gene editing. The sgRNA shown in red also recruits Cas9 to partially mismatched off-target sites where wild-type Cas9 can efficiently introduce double stranded breaks leading to editing of an off-target exon.  More…

Repurposing CRISPR-Cas9 for in situ functional assays
Malina A, Mills JR, …, Pelletier J.
Genes & Development 2015; 27:2602–2614
http://www.genesdev.org/cgi/doi/10.1101/gad.227132.113

Figure 1. Genome editing of a TLR locus in 293Tcells using an engineered all-in-one type II CRISPR system. (A) Schematic diagram of LeGO-based lentivirus (pLC) constructs driving expression of Cas9 and sgRNAs. (B) Predicted secondary structure (http://rna.tbi. univie.ac.at/cgi-bin/RNAfold.cgi) of sgRNA showing alignment of trigger sequence with target and PAM. The first nucleotide of the trigger sequence is forcibly a G, since the sgRNA is expressed from the murine U6 promoter. (C) Schematic of TLR with the position and nucleotide sequence of the TLR trigger, PAM, and stop codon shown. (D) A genomically integrated TLR is efficiently targeted by pLC-TLR. Quantitation of 293T TLR cells transfected with the indicated Cas9/sgRNA expression constructs and, where indicated, in combination with D20 eGFP. (E) Immunoblot showing expression and subcellular localization of Cas9 from the experiment presented in D. (C) Cytoplasmic fraction; (M) membrane fraction; (N) nuclear fraction. Blots were probed with the antibodies indicated below each panel. (F) Lentiviral-mediated NHEJ and HDR in 293T TLR cells. Cells were infected with lentivirus expressing Cas9 and the corresponding sgRNA and analyzed by flow cytometry 6 d later. The D20 eGFP donor plasmid was introduced by transfection 1 d prior to transduction with the Cas9/sgRNA lentiviral construct.

Figure 2. Cas9-mediated editing of Trp53 in Arf[1]/[1] MEFs leads to Nutlin-3a resistance. (A) Schematic diagram of the pQ-based retroviral constructs driving expression of Cas9, GFP, and sgRNAs (pQCiG). (B) Flow cytometric analysis of Arf[1]/[1] and p53[1]/[1] MEFs transduced with QCiG-Rosa, QCiG-p53, or MLP-p53.1224 retroviruses, cultured 3 d later in the presence of vehicle or 10 mM Nutlin-3a for 24 h, and then allowed to recover for 4 d. (C) Colony formation assay of infected Arf[1]/[1] and p53[1]/[1] MEFs with QCiG-Rosa, QCiGp53, or MLP-p53.1224. Five-thousand cells were seeded, exposed to 10 mM Nutlin-3a for 24 h, and allowed to recover for 12 d in the absence of drug, at which point they were stained with crystal violet. (D) SURVEYOR assay of DNA isolated from QCiG-p53- and QCiG-Rosa-infected Arf[1]/[1] MEFs exposed to 10 mM Nutlin-3a for 24 h and allowed to recover for 4 d. The arrowhead denotes the expected SURVEYOR cleavage products. (E) Immunoblot documenting Cas9 and p53 expression in QCiG- and MLP-infected MEFs. The asterisk denotes the position of a prominent p53 truncated product

Figure 3. Cas9-mediated editing of Trp53 in Arf[1]/[1]Em-myc lymphomas is positively selected for following DXR treatment in vivo. (A) Schematic diagram of in vivo fitness assay. (B) Kaplan-Meier analysis of tumor-free survival of mice injected with Rosa26 or Trp53 Cas9 targeted Arf[1]/[1]Em-myc and p53[1]/[1]Em-myc lymphomas following treatment with DXR. (C) Detection of GFP in tumors arising from QCiG-p53-infected Arf[1]/[1]Em-myc lymphomas following exposure to DXR and analyzed 3 d later. White arrows denote GFP fluorescence in lymph nodes originating from the presence of QCiG-p53 in the resulting tumors. (D) FACS analysis of the indicated Cas9 targeted Em-myc lymphomas analyzed before injection into mice (input), from tumors arising in vivo (pre-DXR), and from tumors for which the host had received DXR treatment (post-DXR). (E) SURVEYOR assay of DNA from QCiG-p53- and QCiG-Rosa-infected Arf-/-Em-myc lymphomas isolated from mice prior to DXR treatment. (F) Immunoblot showing long-term Cas9, p53, and GFP expression in QCiG-Rosa and QCiG-p53 Arf-/-Em-Myc lymphomas in vivo. Samples are from three separate tumors isolated prior to (pre-DXR) or following (post-DXR) DXR treatment. In the case of post-DXR samples for QCiG-Rosa Arf-/-Em-myc lymphomas, tumors were harvested after relapse (~10 d after post-DXR treatment). The asterisk highlights a truncated p53 protein arising in the Cas9 edited samples.

Figure 4. Analysis of indels at the Trp53 locus and at predicted off-target sites in Arf-/-MEFs and Arf-/-Em-myc tumors edited with Rosa26 and Trp53 sgRNAs. (A) Total count and location of insertions and deletions in exon 7 of Trp53 in Arf-/-Em-myc cells prior to injection, post-implantation, and post-DXR treatment, respectively. The vertical dashed line represents the predicted Cas9 cleavage site. (B) Frequency of mutant reads obtained following sequencing of Trp53 exon 7 from the indicated cells and tumors. T-1, T-2, and T-3 represent three independent tumors. (C, top panel) Sequence alignment of the trigger site in the Trp53 and Trp53 pseudogene. Differences are highlighted in green. (Bottom panel) Pie charts illustrating the proportion of mutated sequence reads at Trp53 (left) and the Trp53 pseudogene (right) relative to wild-type sequences (wt; blue). DNA was isolated from samples of Arf-/-Em-myc lymphoma cells infected with QCiG-Rosa-infected (top), QCiG-p53-infected (middle), or QCiG-p53-infected cells that were exposed to 10 mM Nutlin-3a for 3 d followed by a 10-d recovery period (bottom). (D) Prediction of genomic sequences showing sequences complementary to the first 13 perfectly matched nucleotides 59 to the PAM of the Trp53 trigger sequence with all possible combinations of PAM. The trigger sequence is shown in blue, PAM is in red, and flanking nucleotides are in black. The genomic location is shown at the right. (E) Percent mutant reads at the indicated genomic locus in Rosa26- and Trp53-modified Arf-/- MEFs. The total read count for each amplified region ranged from ;11,000 to 15,000 (sample #8), ;18,000 to 23,000 (sample #7), and ;20,000 to 53,000 (all others). Read counts for locus #2 are absent, since the barcode that had been used in the preparation of that sample could not be deciphered from the output of reads.

TALE nucleases- tailored genome engineering made easy
Mussolino C, Cathomen T
Current Opinion in Biotechnology 2012; 23:644–650
http://dx.doi.10.1016/j.copbio.2012.01.013

Generation of customized TALENs by ‘Golden Gate’ cloning. Dependent on the user-defined target sequence, the respective repeat units with desired specificities can be assembled using a two-step ‘Golden Gate’ cloning protocol. A TALEN monomer is generated by incorporating the TALE designer array in a TALEN backbone, which contains an N-terminal NLS, the ‘0 repeat’ binding to the 50-T nucleotide, the 17.5 ‘half-repeat’, and the terminal FokI cleavage domain (N).

TALEN or Cas9 – Rapid, efficient and specific choices for genome modifications
Wei C, Liu J, et al.
J Genetics and Genomics 40 (2013) 281e289
http://dx.doi.org/10.1016/j.jgg.2013.03.013

Fig. 1. Schematic principles of TALEN- and CRISPR/Cas9-mediated genomic modifications. A: a single TALEN consists of an N-terminal domain including a nuclear localization signal (NLS, blue); a central domain typically composed of tandem TALE repeats (green) for the recognition of a specific DNA sequence; and a C-terminal domain of the functional endonuclease Fok I (black). Each TALE repeat comprises of a 34-amino-acid unit that differs at the position of 12th and 13th amino acids: NG (recognizing T), NI (recognizing A), HD (recognizing C), or NN (recognizing G) (color boxes). B: double-strand breaks (DSBs) that are resulted from the cut by dimeric Fok I can be repaired either by non-homologous end joining (NHEJ) to yield indels or by homologous recombination (HR) with available homologous donor templates. The red star indicates where indels occur. C: the CRISPR/Cas9 system consists of a group of CRISPR-associated (Cas) genes (arrows with the direction to the right) and a CRISPR locus that contains an array of repeats (dark diamonds) e spacer (color boxes) sequences. All repeats are the same in sequence and all spacers are different and complementary to their target DNA sequences. The tracrRNA (trans-activating crRNA, arrow on the most left) can help to produce the crRNA (CRISPR RNA). D: the Cas9 protein (blue) binds to crRNA (orange) and tracrRNA (purple) to form a ribonucleoprotein complex. The crRNA sequence guides this complex to a complementary sequence in the target DNA (black). Then the HNH and RuvC domains of Cas9 nick the complementary and non-complementary strands, respectively, making a DSB. PAM: protospacer adjacent motif NGG (yellow box). gRNA: guiding RNA. NCC is a complementary motif of the PAM motif (NGG).

Table 1 Comparison of TALEN- and CRISPR/Cas9-mediated genomic modifications e principles and applications

TALEN CRIPR/Cas9
Target-binding principle Protein-DNA specific recognition Watson Crick complementary rule
Working mode TALE specifically recognizes the target DNA and dimeric Fok I makes the DSB, which is repaired by NHEJ or HR Guide RNA specifically recognizes the target DNA and Cas9 makes the DSB, which is repaired by NHEJ or HR
Essential components TALE-Fok I fusion protein Guide RNA and Cas9
Off-target effects Minor effects Not determined
Efficiency High but variable High but variable
Target site availability No restriction PAM (NGG) motif restriction
Work in pair/dimmer Yes No
Inheritability in animals Yes Not determined
3D structure Yes Yes
Time to construct 5-7 d 1-3 d
Origin discovery Plant pathogen E. coli

Genome-Scale CRISPR-Mediated Control of Gene Repression and Activation
Gilbert LA, et al.
Cell, Oct 23, 2014; 159: 647–661
http://dx.doi.org/10.1016/j.cell.2014.09.029

Figure 1. A Tiling sgRNA Screen Defines Rules for CRISPRi Activity at Endogenous Genes in Human Cells (A) Massively parallel determination of growth or toxin-resistance phenotypes caused by sgRNAs in mammalian cells expressing dCas9 or dCas9 fusion constructs. (B) UCSC genome browser tracks showing the genomic organization, GC content, and repetitive elements around the TSS of a representative gene, VPS54, across a 10 kb window targeted by the tiling sgRNA library. sgRNA ricin-resistance phenotypes (as Z scores, see Figure S1 and Experimental Procedures) in dCas9 and dCas9-KRAB expressing K562 cells are depicted in black on the top and bottom, respectively. See also Figure S2A for more examples. (C) Sliding-window analysis of all 49 genes targeted in a tiling sgRNA library. Green line: median sgRNA activity in a defined window for all genes. Orange region: observed average window of maximum CRISPRi activity. Data displayed as a phenotype signed Z score, excluding all guides longer than 22 bp. (D) CRISPRi activity for all 49 genes in defined windows relative to the TSS of each gene. (E) Ricin-resistance phenotypes, comparing CRISPRi sgRNAs selected by our rules to RNAi, for genes previously established to cause ricin-resistance phenotypes when knocked down by RNAi. Mean ± SD phenotype-signed Z score of 100 sets of 10 randomly subsampled sgRNAs or shRNAs. See also Figure S2F

Figure 2. CRISPRi Activity is Highly Sensitive to Mismatches Between the sgRNA and DNA sequence On- and off-target activity of dCas9, dCas9-KRAB and Cas9 for sgRNAs with a varying number and position of mismatches. Off-target activity of sgRNAs with mismatches is displayed as percent of the on-target activity for the corresponding sgRNA without mismatches. Asterisk indicates sgRNAs with three, four, or five mismatches randomly distributed across region 3 of the sgRNA sequence. Data are displayed for each mismatch position as the mean of all sgRNAs with that mismatch; see Figure S3 for individual sgRNA activities. sgRNAs were included in the analysis only if the fully matched guide was highly active (phenotype-signed Z score R 4); n = 5 for dCas9, n = 11 for dCas9-KRAB, and n = 10 for Cas9.

Figure 3. A Tiling sgRNA Screen Defines Rules for CRISPRa Activity at Endogenous Genes in Human Cells (A) A schematic of the dCas9-SunTag + scFV-VP64 + sgRNA system for CRISPRa. (B)ActivityofsgRNAsinK562cellsstablyexpressingeachcomponentofCRISPRa,asafunctionofthedistanceofthesgRNAsitetotheTSSofthetargetedgene (Phenotype-signed Z scores; therefore, negative values represent opposite results than from knockdown). Top, sgRNAs targeting VPS54; Bottom, slidingwindow analysis of all 49 genes targeted by our tiling library in green. Green line, median activity; orange, window of maximal activity. Guides longer than 22 bp were excluded. See also Figure S4. (C)CRISPRaphenotypesandCRISPRi(dCas9-KRAB)phenotypesareanticorrelated forselect genes.Foreachgene,aMann-Whitneypvalueiscalculatedusing CRISPRi/a sgRNA activity relative to a negative control distribution for 24 subsampled sgRNAs. Mean ± SD p value of 100 randomly subsampled sets is displayed. (D) CRISPRi knockdown and CRISPRa activation of the same gene can have opposing effects on ricin resistance in both primary screens and single sgRNA validation experiments (mean ± SD of 3 replicates). (E) Modulation of expression levels for 3 genes by CRISPRi and CRISPRa as quantified by qPCR plotted against the ricin-resistance phenotype (mean ± SD of 3 replicates) measured for each sgRNA.

Figure 4. Genome-Scale CRISPRi and CRISPRa Screens Reveal Genes Controlling Cell Growth (A) sgRNA phenotypes from a genome-scale CRISPRi screen for growth in human K562 cells (black). Three classes of negative control sgRNAs are color-coded: nontargeting sgRNAs (gray), sgRNAs targeting Y-chromosomal genes (green) and sgRNAs targeting olfactory genes (orange). (B) Coexpression of sgRNAs and dCas9-KRAB or dCas9-SunTag + scFV-VP64 is not toxic in K562 cell lines over 16 days. (C) Gene set enrichment analysis (GSEA) for hits from the CRISPRi screen. A histogram of gene distribution is shown under the GSEA curve. (D) CRISPRi versus CRISPRa gene phenotypes for genome-scale growth screens (black). For the 50 genes in the CRISPRa screen with the most negative growth phenotype, each gene was annotated and labeled based on evidence of activity as a tumor suppressor (orange), developmental transcription factor (green), or in regulation of the centrosome (purple). Two additional CRISPRi hit genes that are discussed in the text are labeled in red. See Table S4 for annotations and references. (E) GSEA for hits from the CRISPRa growth screen. A histogram of gene distribution is shown under the GSEA curve.

Figure 5. CRISPRi Gene Silencing Is Inducible, Reversible, and Nontoxic (A) Expression construct encoding an inducible KRAB-dCas9 fusion protein. (B) Western blot analysis of inducible KRAB-dCas9 in the absence, presence, and after washout of doxycycline. (C) Relative RAB1A expression levels (as quantified by qPCR) in inducible CRISPRi K562 cells transduced with RAB1A-targeting sgRNAs in the absence, presence, and after washout of doxycycline. Mean ± standard error of technical replicates (n = 2) normalized to control cells (assayed in the presence of doxycycline) from the day 2 time point. (D) Competitive growth assays performed with inducible CRISPRi K562 cells transduced with the indicated sgRNAs in the presence and absence of doxycycline. Data are represented as the mean ± SD of replicates (n = 3). See also Figure S5G. (E) A CRISPRi sublibrary screen for effects on cell growth was performed with inducible CRISPRi K562 cells in the presence and absence of doxycycline. (F) Cumulative growth curves from the sublibrary screen represented in (E) show no bulk changes to growth caused by induction of KRAB-dCas9. Mean ± SD of replicate infections each screened in duplicate.

Figure 6. Genome-Scale CRISPRi and CRISPRa Screens Reveal Known and New Pathways and Complexes Governing the Response to a Cholera-Diphtheria Fusion Toxin (A) Model for CTx-DTA binding, retrograde trafficking, retrotranslocation, and cellular toxicity. (B) Overview of top hit genes detected by the CTx-DTA screen. Dark red and blue circles: Top 50 sensitizing and protective hits, respectively. Light red and blue circles: further hits that fall into the same protein complexes or pathways as top 50 hits. Circle area is proportional to phenotype strength. White stars denote genes identified in a previous haploid mutagenesis screen (Guimaraes et al., 2011). See also Figure S6 for hit gene names. (C) CRISPRi and CRISPRa hits in sphingolipid metabolism. Display as in (B), except that the left and right sides of each circle represent the phenotypes in the CRISPRi and CRISPRa screens, respectively.

Figure 7. CRISPRi Strongly Represses Gene Expression of Both Protein-Coding and Noncoding Genes, Resulting in Reproducible Phenotypes (A–C) Cells expressing a negative control sgRNA or an sgRNA targeting SEL1L or B4GALNT1 were incubated with cholera toxin and fractionated to quantify cholera toxin present in the cytosolic and membrane fractions by western blot. B4GALNT1 repression blocks toxin uptake, whereas SEL1L repression prevents toxin retrotranslocation from the membrane fraction to the cytosol. (D) Validation of CTx-DTA screen phenotypes with single sgRNA retest experiments. Data are represented as the mean ± SD of replicates (n = 3). (E) CRISPRi knockdown of 13 hit genes (28 sgRNAs; sgRNAs correspond to 7D) identified in the CTx-DTA screen was quantified by qPCR. The gray shaded region denotes sgRNAs showing at least 90% knockdown for each gene. Data are normalized to a negative control sgRNA (NC). (F) CRISPRi knockdown of 6 lncRNA genes was quantified by qPCR. Two to three sgRNAs computationally predicted to target each gene were cloned and transduced into K562 cells expressing dCas9-KRAB. Data are normalized to a negative control sgRNA (NC). (G) K562 cells expressing dCas9-KRAB were transduced with either a nontargeting sgRNA or an sgRNA targeting the XIST locus (sgXIST-1). The cells were then stained with DAPI and an RNA FISH probe for the XIST transcript. Two hundred nonapoptotic interphase cells in each condition were scored for XIST RNA coating. XIST is undetectable in cells transduced with sgXIST-1. Scale bar, 5 mm

Other related articles published on this topic in this Open Access Online Scientific Journal include the following:

Advances in Gene Editing Technology: New Gene Therapy Options in Personalized Medicine

Curators: Stephen J Williams, PhD and Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2015/03/16/advances-in-gene-editing-technology-new-gene-therapy-options-in-personalized-medicine/

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2.0 Genomics and Epigenetics: Genetic Errors and Methodologies – Cancer and Other Diseases

Writer and Curator: Larry H Bernstein, MD, FCAP

This is the second article in a series concerning genomic expression, The first of which was concerned with the expanded technologies in use for study of genomic expression.  This portion will also cover more of genetic errors as well as methodologies, but not all examples are in the realm of cancer.

I shall start with a New York Times editorial on July 24, 2015 by Angelina Jolie Pitt on her experience with BRCA1 gene and her family history.  It is very instructive on how she worked through her experience.

http://www.nytimes.com/2015/03/24/opinion/angelina-jolie-pitt-diary-of-a-surgery.html?

Two years ago she was found to have a positive test for BRCA1, carrying an 87 percent risk for breast cancer and a 50 percent risk for ovarian cancer.  At that time she had a preventive mastectomy.  The decision was not easy, but it also brought into consideration that her mother and grandmother both died of breast cancer.  She did not have an oophorectomy at that time because on considering the advice of medical experts, she would have been left with no estrogen support. She wanted to delay her early vegetative senescence.  She has reached the age of 39 years and on the advice of medical expert opinion, she proceeded with salpingo-oophorectomy, at age 39 years, a decade before  her  mother had developed cancer.  But her delay was to allow her to recover and adjust emotionally to her ongoing situation, with a remaining risk for ovarian cancer.

She tested negative for CA-1251-5 at this time prior to surgery. But the CA-125 test could well be negative with early onset ovarian cancer. It may be considered a better test for following treatment than for early diagnosis. Her choice was to sacrifice early menopause to the ability to live through her childrens’ childhood development.  This was a well thought out decision.  In addition, there were abnormal inflammatory markers that were not specific for cancer rsik, but were worth taking into account.  The procedure itself was simpler than the mastectomy.

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http://static01.nyt.com/images/2015/03/23/opinion/23op-ed/23op-ed-master315.jpg

2.1  CA-125 and Ovarian Cancer

2.1.1  lmmunoradiometric Assay of CA 125 in Effusions: Comparison with Carcinoembryonic Antigen

Marguerite M. Pinto, MD,‘ Larry H. Bernstein, MD,* Dennis A. Brogan, MPH, MT

and Elaine Criscuolo, CT(ASCP) CMIACS

The levels of CA 125 antigen were measured in 167 effusions from 150 patients using radioimmunoassay, and the results compared with the levels of carcinoembryonic antigen (CEA) in the fluids. The results indicate that an elevated fluid CA 125 level (>14,000 U/ml-68,000 U/ml) and a negative fluid CEA level (4 ng/ml) is suggestive of serous and endometrioid carcinoma of ovary, and adenocarcinoma of the endometrium and fallopian tube. Alternatively, an elevated fluid CEA level (14 ng/ml-600 ng/ml) and a negative CA 125 level (20-5000 U/ml) is seen in metastatic carcinomas of breast, lung, gastrointestinal tract, and mucinous ystadenocarcinoma. Lymphomas, melanomas, and benign effusions are negative for both antigens. The combined use of CEA and CA 125 antigen in fluids is useful in the differential diagnosis of adenocarcinoma of unknown primary. Cancer 59:218-222, 1987.

2.1.2 CA-125 in fine-needle aspirates of solid tumors: comparison with cytologic diagnosis and carcinoembryonic antigen (CEA) assay.

Marguerite M. Pinto, S Kotta

Diagnostic Cytopathology 03/1996; 14(2):121-5.
http://dx.doi.org:/10.1002/(SICI)1097-0339(199603)14:2<121::AID-DC4>3.0.CO;2-M

One hundred and twenty-two fine needle aspirates (FNA) from female patients were studied to determine whether CA-125 assay contributed to cytologic diagnosis and CEA assay. Cytologic examination was done on Papanicolaou-stained smears and cell blocks, CEA by EIA (Abbott Laboratory, > 5 ng/ml cutoff) and CA-125 by RIA (Abbott Laboratory, North Chicago, IL, > 66 mu/ml cutoff). Final diagnosis were correlated with histologic diagnosis when available, clinical, radiologic studies, and follow-up. Results: 29 benign, 93 malignant. Sensitivities and specificities: cytology, 91%, 100%; CEA: 59%, 86%; CA-125, 50%, 55%. CEA plus cytology sensitivity, 97%. CA-125 content was highest in endometrial/ovarian carcinoma (39,899 mu/ml) and < 5,000 mu/ml in other tumors and benign FNA in contrast to CEA which showed highest levels in carcinomas of colon, pancreas, and lung (> 280 ng/ml). While elevated CEA enhances the sensitivity of cytologic diagnosis of carcinomas of the colon, pancreas, and lung, low CEA and high CA-125 content supports an ovarian/endometrial primary.

2.1.3  Diagnostic efficiency of carcinoembryonic antigen and CA125 in the cytological evaluation of effusions.

Pinto MM, Bernstein LH, Rudolph RA, Brogan DA, Rosman M.
Arch Pathol Lab Med. 1992 Jun; 116(6):626-31.

In our previous study, the combination of the concentrations of carcinoembryonic antigen (CEA) and CA125 and the findings from cytological examination in 189 benign and malignant pleural and peritoneal effusions was useful in the diagnosis/classification of malignant effusions. Sensitivity of CEA (level, greater than 5 ng/mL) was 68%; specificity was 99% for the diagnosis of malignant effusions secondary to carcinoma of the lung, breast, gastrointestinal tract, and mucinous carcinoma of the ovary. Sensitivity of CA125 (level, greater than 5000 U/mL) was 85%; specificity was 96% for the diagnosis of malignant effusions in carcinoma of the ovary, fallopian tube, and endometrium. We now expanded the study to include 840 pleural and peritoneal effusions (benign, n = 520; malignant, n = 320) and analyzed the data by the statistical method of Rudolph and colleagues. Based on new cutoff values, ie, CEA level at 6.3 ng/mL and CA125 level at 3652 U/mL, the sensitivities for detection of malignant effusions secondary to carcinomas of the lung, breast, and gastrointestinal tract and mucinous carcinoma of the ovary varied between 75% and 100%; specificity was 98%. Sensitivity of CA125 for detection of malignant effusions from müllerian epithelial carcinoma was 71%; specificity was 99%. The elevated CEA fluid level alone helped to diagnose malignant effusions of the gastrointestinal tract in 54%, breast in 19%, and lung in 16%. The high CA125 fluid level was predictive of müllerian epithelial carcinoma. Adjunctive use of CEA and CA125 levels in fluid enhances the sensitivity of cytological diagnosis and may be predictive of the primary site in patients who present with carcinoma of an unknown primary source.

2.2 Carcinoembryonic antigen in diagnostics

2.2.1 Carcinoembryonic antigen content in fine needle aspirates of the lung. A diagnostic adjunct to cytology.

Pinto MM1, Ha DJ.
Acta Cytol. 1992 May-Jun; 36(3):277-82

Carcinoembryonic Antigen (CEA) was measured in 59 consecutive fine needle aspirates (FNAs) of the lung from 58 patients to determine if the CEA content would enhance the sensitivity of the cytologic diagnosis. Twenty-eight males and 30 females with tumors 1-40 cm in diameter were studied. Final diagnoses were correlated with the clinical history, radiologic studies, tissue (when available) and follow-up. Image-guided FNAs were performed by radiologists using a 22-gauge Chiba needle and 20-mL syringe with one to four passes per specimen. Cytologic examination included rapid assessment in the radiology suite and a final diagnosis in 24 hours. CEA was measured by enzyme immunoassay using monoclonal antibody. Nine benign aspirates and 50 malignant aspirates were diagnosed. The sensitivity of cytology was 86% and specificity, 100%. Using 5 ng/mL as the cutoff, the sensitivity of CEA for malignant aspirates was 50% and specificity, 90%. The combined sensitivity of CEA and cytology was 95%. The mean CEA in malignant aspirates was 131 ng/mL and in benign aspirates, 2.41. The highest mean CEA was seen in adenocarcinoma, 402.6 ng/mL. Lower CEA content was seen in epidermoid carcinoma (58.6 ng/mL), large cell carcinoma (8.09), oat cell carcinoma, metastatic carcinoma of the kidney and breast, thymoma and lymphoma (each less than 1 ng/mL). Elevated CEA alone was diagnostic in two aspirates of bronchioloalveolar carcinoma; carcinoma with an unknown primary source, three; and large cell carcinoma, one. The adjunctive use of CEA in FNAs of the lung enhances the sensitivity of the cytologic diagnosis.

2.2.2  Relationship between serum CA125 half life and survival in ovarian cancer

Table
Gupta and Lis Journal of Ovarian Research 2009 2:13
http://dx.doi.org:/10.1186/1757-2215-2-13

First Author, Year, Study Place Data Collection Study
Design
Sample
Size
RR/HR, (95% CI),
P-Value
Riedinger JM, 2006, France 1988 to
1996
R 553 2.04 (1.58-2.63), < 0.0001
Gadducci A, 2004, Italy 1996 to2002 R 71 3.11 (1.22-7.98), 0.0181
Munstedt K, 1997, Germany 1987 to1994 R 85 0.6184
Gadducci A, 1995, Italy 1986 to1992 R 225 2.13 (1.23-3.68), 0.0073
Rosman M, 1994, Connecticut 1985 to
1989
R 51 3.6 (1.8-7.4), < 0.001
Yedema C A, 1993, Netherlands 1984 to
1990
R 60 9.17 (1.49-56.3), 0.01
Hawkins RE, 1989, London NA P 29 3.7 (0.7-20.1), 0.001;27.8 (4.0-193), 0.001

1CA125 half-life was independent prognostic indicator for survival
2FIGO stage, tumor grade, residual disease, CA125
http://www.ovarianresearch.com/content/2/1/13/table/T6

3.3.0      DNA double strand breaks

2.3.1.  Collaboration and competition – DNA double-strand break repair pathways

Kass EM, Jasin M
FEBS Letters 2010; 584:3703-3708
http://dx.doi.org:/jfebslet.2010.07.057

DNA double-strand breaks occur in replication and exogenous sources pose risk to genome stability. There are two pathways to repair.  They are non-homologous end joining and homologous recombination. Both pathways cooperate and compete at double-strand break sites.

2.3.2 DNA Double-Strand Break Repair Inhibitors as Cancer Therapeutics

Srivastava M, Rashavan SC
Chem & Biol 2015 Jan; pp17-29
http://dx.doi.org:/10.1016/jchembiol.2014.11.013

Homologous recombination and non-homologous end joining are the two major repair pathways expressed in eukaryotes.  For double-strand breaks, and the DSB repair gene is vulnerable to chemotherapy and radiation therapy, accounting for treatment resistance. Therefore, targeting DSB repair is attractive. Blocking the residual repair using inhibitors can potentiate treatment.

2.3.3  Animation published in DNA Repair: Helleday T, Lo J, van Gent DC, Engelward BP. DNA double-strand break repair: From mechanistic understanding to cancer treatment. DNA Repair. (14 Mar 2007)
2.3.3.1 http://web.mit.edu/engelward-lab/animations/DSBR.html

2.3.3.2 https://www.youtube.com/watch?v=eg8rpYFsqCA

2.3.4 Homology-dependent double strand break repair. Oxford Academic (Oxford University Press)

https://www.youtube.com/watch?v=86JCMM5kb2A

2.4.0 Managing DNA data sets

2.4.1 Bionimbus –  a cloud for managing, analyzing and sharing large genomics datasets

The Bionimbus Protected Data Cloud (PDC) is a collaboration between the Open Science Data Cloud (OSDC) and the IGSB (IGSB,) the Center for Research Informatics (CRI), the Institute for Translational Medicine (ITM), and the University of Chicago Comprehensive Cancer Center (UCCCC). The PDC allows users authorized by NIH to compute over human genomic data from dbGaP in a secure compliant fashion. Currently, selected datasets from the The Cancer Genome Atlas (TCGA) are available in the PDC.

https://bionimbus-pdc.opensciencedatacloud.org/

2.4.1.2 Accounting for uncertainty in DNA sequencing data

O’Rawe JA, Ferson S, Lyon GJ
Trends in Genetics 2015 Feb; 31(2):61-66
http://dx.doi.org:/10.101/jtig.2014.12.002

This article reviews uncertainty in quantification in DNA sequency applications and sources of error propagation, and it proposes methods to account for errors and uncertainties.

2.5.0 Linking Traits to Mechanisms and UPR response/proteostasis

2.5.1 Stress-Independent Activation of XBP1s and/or ATF6 Reveals –Three Linking traits based on their shared molecular mechanisms

Shoulders MD, Ryno LM, Genereux JC,…Wiseman BL
Cell Reports 2013 Apr; 3, pp 1279-1292
http://dx.doi.org:/10.1016/j.celrep.2013.03.024

The unfolded protein response (UPR) maintains ER proteostasis through the transcription factors XP1s and ATF6. This study measured orthogonal small molecule-mediated activation of transcription factors nXP1s and/or ATF6 using transcriptomics and quantitative proteomics. The finding is that three ER proteostasis environmants differentially influence

  1. Folding
  2. Traffiking, and
  3. Degradation of destabilized ER client proteins

Without affecting endogenous proteome. The proteostasis network is remodeled with the potential for selective restoration of the aberrant ER proteostasis.

2.5.2 Biological and chemical approaches to diseases of proteostasis deficiency.

Powers ET, Morimoto RI, Dillin A, Kelly JW, Balch WE
Annu Rev Biochem. 2009; 78:959-91.
http://dx.doi.org:/10.1146/annurev.biochem.052308.114844

Many diseases appear to be caused by the misregulation of protein maintenance. Such diseases of protein homeostasis, or “proteostasis,” include loss-of-function diseases (cystic fibrosis) and gain-of-toxic-function diseases (Alzheimer’s, Parkinson’s, and Huntington’s disease). Proteostasis is maintained by the proteostasis network, which comprises pathways that control protein synthesis, folding, trafficking, aggregation, disaggregation, and degradation. The decreased ability of the proteostasis network to cope with inherited misfolding-prone proteins, aging, and/or metabolic/environmental stress appears to trigger or exacerbate proteostasis diseases. Herein, we review recent evidence supporting the principle that proteostasis is influenced both by an adjustable proteostasis network capacity and protein folding energetics, which together determine the balance between folding efficiency, misfolding, protein degradation, and aggregation. We review how small molecules can enhance proteostasis by binding to and stabilizing specific proteins (pharmacologic chaperones) or by increasing the proteostasis network capacity (proteostasis regulators). We propose that such therapeutic strategies, including combination therapies, represent a new approach for treating a range of diverse human maladies.

2.5.3 Extracellular Chaperones and Proteostasis

Amy R. Wyatt, Justin J. Yerbury, Heath Ecroyd, and Mark R. Wilson
Annual Review of Biochemistry 2013 Jun; 82: 295-322
http://dx.doi.org:/10.1146/annurev-biochem-072711-163904

There exists a family of currently untreatable, serious human diseases that arise from the inappropriate misfolding and aggregation of extracellular proteins. At present our understanding of mechanisms that operate to maintain proteostasis in extracellular body fluids is limited, but it has significantly advanced with the discovery of a small but growing family of constitutively secreted extracellular chaperones. The available evidence strongly suggests that these chaperones act as both sensors and disposal mediators of misfolded proteins in extracellular fluids, thereby normally protecting us from disease pathologies. It is critically important to further increase our understanding of the mechanisms that operate to effect extracellular proteostasis, as this is essential knowledge upon which to base the development of effective therapies for some of the world’s most debilitating, costly, and intractable diseases.

http://www.proteostasis.com/our-technology/proteostasis-network.html

proteostasis model

http://www.proteostasis.com/images/stories/technology/illustration1.gif

2.6.0 Transcription

2.6.1 Looping Back to Leap Forward. Transcription Enters a New Era

Levine M, Cattoglio C, Tijan R
Cell 2014 Mar; 157: 13-22.
http://dx.doi.org:/10.1016/j.cell.2014.02.009

Organism complexity is not in gene number, but lies in gene regulation. The human genbome contains hundreds of thousands of enhancers, and genes are embedded in a milieu of enhancers . Proliferation of cis-regulatory DNAs is accompanied by complexity and functional diversity of transcription machinery recognizing distal enhancers and promotors, and high-order spatial organization. This article reviews the dynamic communication of remote enhancers with target promoters.

2.6.2 Activating gene expression in mammalian cells with promoter-targeted duplex RNAs.

Janowski BA, Younger ST, Hardy DB, Ram R, Huffman KE, Corey DR.
Nat Chem Biol. 2007 Mar; 3(3):166-73
http://dx.doi.org:/10.1038/nchembio860

The ability to selectively activate or inhibit gene expression is fundamental to understanding complex cellular systems and developing therapeutics. Recent studies have demonstrated that duplex RNAs complementary to promoters within chromosomal DNA are potent gene silencing agents in mammalian cells. Here we report that chromosome-targeted RNAs also activate gene expression. We have identified multiple duplex RNAs complementary to the progesterone receptor (PR) promoter that increase expression of PR protein and RNA after transfection into cultured T47D or MCF7 human breast cancer cells. Upregulation of PR protein reduced expression of the downstream gene encoding cyclooygenase 2 but did not change concentrations of estrogen receptor, which demonstrates that activating RNAs can predictably manipulate physiologically relevant cellular pathways. Activation decreased over time and was sequence specific. Chromatin immunoprecipitation assays indicated that activation is accompanied by reduced acetylation at histones H3K9 and H3K14 and by increased di- and trimethylation at histone H3K4. These data show that, like proteins, hormones and small molecules, small duplex RNAs interact at promoters and can activate or repress gene expression.
2.6.3 Tight control of gene expression in mammalian cells by tetracycline-responsive promoters.

M Gossen and H Bujard
Proc Natl Acad Sci U S A. 1992 Jun 15; 89(12): 5547–5551.

Control elements of the tetracycline-resistance operon encoded in Tn10 of Escherichia coli have been utilized to establish a highly efficient regulatory system in mammalian cells. By fusing the tet repressor with the activating domain of virion protein 16 of herpes simplex virus, a tetracycline-controlled transactivator (tTA) was generated that is constitutively expressed in HeLa cells. This transactivator stimulates transcription from a minimal promoter sequence derived from the human cytomegalovirus promoter IE combined with tet operator sequences. Upon integration of a luciferase gene controlled by a tTA-dependent promoter into a tTA-producing HeLa cell line, high levels of luciferase expression were monitored. These activities are sensitive to tetracycline. Depending on the concentration of the antibiotic in the culture medium (0-1 microgram/ml), the luciferase activity can be regulated over up to five orders of magnitude. Thus, the system not only allows differential control of the activity of an individual gene in mammalian cells but also is suitable for creation of “on/off” situations for such genes in a reversible way.

Diagrams of two regulatable gene expression systems.

Diagrams of two regulatable gene expression systems.

http://www.intechopen.com/source/html/16788/media/image5.jpeg

schematic-representation-of-transgenic-mouse-breeding-scheme-h2b-gfp-mice-should-not-express-gfp-in-the-absence-of-a-tetracycline-regulatable-transactivator

schematic-representation-of-transgenic-mouse-breeding-scheme-h2b-gfp-mice-should-not-express-gfp-in-the-absence-of-a-tetracycline-regulatable-transactivator

http://openi.nlm.nih.gov/imgs/512/321/2408727/2408727_pone.0002357.g001.png

2.7.0 Epigenetics and Cancer

2.7.1 Epigenetics and cancer metabolism

Johnson C, Warmoes MO, Shen X, Locasale JW
Cancer Letters 2015;  356:309-314.
http://dx.doi.org:/10.1016/j.canlet.2013.09.043

Cancer is characterized by adaptive metabolic changes for proliferation and survival of the neoplastic cell, which is accompanied by dysfunctional metabolic enzyme changes in a specific nutrient supplied environment. The oncogenic change uses epigenetic level enzymes that catalyze posttranslational modifications of the DNA/histone expression with metabolites including cofactors and substrates for reactions. This interaction of epigenetics and metabolism provides new insights for anti-cancer therapy.

2.7.2 Cancer Epigenetics. From Mechanism to Therapy

Dawson MA, Konzarides T
Cell 2012 Jul; 150:12-27
http://dx.doi.org:/10.1016/j.cell.2012.06.013

Carcinogenesis requires all of the following:

  • DNA methylation
  • Histone modification
  • Nucleosome remodeling
  • RNA mediated targeting

This article reviews basic principles of epigenetic pathways that are dysregulated in carcinogenesis.

2.7.4 A subway review of cancer pathways

Hahn WC, Weinberg RA
Nature Reviews: Cancer
http://www.nature.com/nrc/poster/subpathways/index.html

Cancer arises from the stepwise accumulation of genetic changes that confer upon an incipient neoplastic cell the properties of unlimited, self-sufficient growth and resistance to normal homeostatic regulatory mechanisms. Advances in human genetics and molecular and cellular biology have identified a collection of cell phenotypes � the main destinations in the subway map below � that are required for malignant transformation1. Specific molecular pathways (subway lines) are responsible for programming these behaviours. Although the connections between cancer-cell wiring and function remain incompletely explored and specified � hence the many lines under construction � the broad outlines of the molecular circuitry of the cancer cell can now be sketched. Further advances in understanding these pathways and their interconnections will accelerate the development of molecularly targeted therapies that promise to change the practice of oncology.

cancer subway map

cancer subway map

http://www.nature.com/nrc/poster/subpathways/images/map.gif

Subway map designed by Claudia Bentley.

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New methods for Study of Cellular Replication, Growth, and Regulation

Writer and Curator: Larry H Bernstein, MD, FCAP

Introduction:

This article is the first in a series on genomics, epigenomics and cancer.  It is necessary here to introduce the large advancement in the technological advances that have followed the Human Genome Project and its thrust into the domain of genome expression.  While the genome is the code that is passed on from generation to generation in a family chain, and while there now is an ability to trace genes that have existed and are traceable by evolutionary history to early eukaryotic species, that portion of the cell line is defining and only modified in time.  It is only a beginning in the unraveling of the question – What is life?

This article has the following structure:

1.1.1       Gene Amplification

1.1.2       Protein-binding Receptors

1.1.3 Advanced Proteomic Technologies for Cancer Biomarker Discoveries

1.1.3.1 State of the art technologies

1.1.3.1.1 2D difference gel electrophoresis (2DIGE)

1.1.3.1.2 MALDI imaging technology (see also 1.1.5)

1.1.3.1.3 Electron Transfer Dissociation

1.1.3.1.4 Reverse-phase Protein Array (RPA)

1.1.3.2 Principles of Protein Microarrays

1.1.3.3 Disposable reagentless electrochemical immunosensor array based on a polymer/sol/gel membrane for simultaneous measurement of several tumor markers

1.1.4 p16INK4a Expression Correlates with Degree of Cervical Neoplasia: A Comparison with Ki-67 Expression and Detection of High-Risk HPV Types

1.1.5 Quantitative real-time detection of magnetic nanoparticles by their nonlinear magnetization

1.1.6 Proteomics and biomarkers

1.1.6.1 Identification by proteomic analysis of calreticulin as a marker for bladder cancer and evaluation of the diagnostic accuracy of its detection in urine

1.1.6.2 Multiplexed proteomic analysis of oxidation and concentrations of CSF proteins in Alzheimer’s disease

1.1.6.3 The Brain Injury Biomarker VLP-1 Is Increased in the Cerebrospinal Fluid of Alzheimer Disease Patients

1.1.6.4 Determination of non-α1-antichymotrypsin-complexed PSA as an indirect measurement of free PSA: analytical performance and diagnostic accuracy

1.1.6.5 Ultrasensitive densitometry detection of cytokines with nanoparticle-modified aptamers

1.1.6.6 Protein profiling of microdissected pancreas carcinoma and identification of HSP27 as a potential serum marker

1.1.7 Mass Spectrometry Methods

1.1.7.1 LC-MS/MS quantification of Zn-α2 glycoprotein: A potential serum biomarker for prostate cancer

1.1.7.2 A novel, high-throughput workflow for discovery and identification of serum carrier protein-bound peptide biomarker candidates in ovarian cancer samples

1.1.7.3 Mass Spectrometry-based hepcidin measurements in serum and urine: analytical aspects and clinical implications

1.1.7.4 Current state and future directions of neurochemical biomarkers for Alzheimer’s disease

1.1.7.5 Use of SELDI-TOF mass spectrometry for identification of new biomarkers: potential and limitations

1.1.1 Gene Amplification

An increase in the number of copies of a gene. There may also be an increase in the RNA and protein made from that gene. Gene amplification is common in cancer cells, and some amplified genes may cause cancer cells to grow or become resistant to anticancer drugs. Genes may also be amplified in the laboratory for research purposes.

http://www.cancer.gov/dictionary?cdrid=650175

Actinin-4 gene Amplification in Ovarian Cancer: A Candidate Oncogene Associated with Poor Patient Prognosis and Tumor Chemoresistance

Yamamoto S, Tsuda H, Kazufumi H, Onozato K, …, Matsubar O

Medscape 6/18/2009

http://medscape.com/viewarticle/704105

Actinin-4, an isoform of non-muscular α-actinin, enhances cell motility by bundling the actin cytoskeleton. We previously reported a prognostic implication of high histochemical expression of actinin-4 protein in ovarian cancers.  Chromosomal gain or amplification of the 19q 12-q13 region has been reported in ovarian cancer. We hypothesized that the actinin-4 (ACTN4) gene might be a target of the 19q 12-q13 amplicon and play an essential role in ovarian cancer progression. In total, we investigated 136 advanced-stage ovarian cancers the copy number of the ACTN4 gene on chromosome 19q3, and used fluorescence in situ hybridization to determine the correlation of the ACTN4 copy number with actinin-4 protein immunoreactivity and major clinicopathological factors. We detected a higher copy number ( > 4) of  of the ACTN4 gene in 29 (21%) cases and it was associated with the intensity of the actinin-4 immunoreactivity (p < 0.0001), a high histological tumor grade (p < 0.030), a clear-cell adenocarcinoma histology (p = 0.012), resistancxe to first- line chemotherapies (p = 0.028), and poor patient outcome (p=0.0011). Uni-
variate analyses using the Cox regression model showed that a higher ACTN4 gene copy numberwas predicted patient outcome more accurately than high actinin-4 immunoreactivity (relative risk: 2.48 vs 1.55). Multivariate analysis indicated that a higher copy number of the ACTN4 gene may be a targetof the 19q amplicon, acting as a candidate oncogene, and serve as a predictor of poor outcome and tumor chemoresistance in patients with advanced-stage ovarian cancers (from Modern Pathology).

1.1.2       Protein-binding Receptors

Customizing the Targeting of IGF-1 Receptor

Renato Baserga
Medscape 5/6/2009. From Future Oncology
http://medscape.com/viewarticle/589011

The type 1 IGF receptor (IGF—IR) is activated by two ligands, IGF-1 and IGF-2, and by insulin at supraphysiological concentrations. It plays a significant role in the growth of normal and abnormal cells, and antibodies against the IGF-IR are now in clinical trials. Targeting of the IGF-IR in cancer cells (by antibodies or other means) can be improved by the appropriate selection of responsive tumors.

The prominence of IGF-IR has increased considerably in the past few years, progressing from a redundant insulin receptor to one that is important in cell and body growth, cell survival and malignant transformation. The IGF-IR can send either a mitogenic or a differentiation signal depending on substrate availability. In many cell types (fibroblasts, epithelial cells, etc.) the IGF-IR sends an unambiguous mitogenic, antiapoptotic signal. In other cell types, such as myeloid cells, neuronal cells and others, activation of IGF-IR induces differentiation. When cells do not express or express very low levels of IRS-1, a substrate of both the IGF_IR and the insulin receptor (InR), IGF-1 induces differentiation. This is the case with 32D myeloid precursor cells that do’t express IRS-1 and are induced to differentiate by IGF-1. Ectopic expression of IRS-1 in 32D cells abrogates differentiation; the cells become transformed and even form tumors in mice. IRS-1 activates the P13K pathway, which is the main mitogenic pathway originating from the IGF-IR. However, the shc-Ras-ERKs pathway also plays a role in the mitogenic signal of the IGF-IR, with the two converging at GSK3-β. The demonstration that knockout mouse embryo cells for the IGF-IR receptor were refractory to transformation by viruses, oncogenes and overexpressed growth factor receptors clearly demonstrated the major role played by the IGF-IR in cellular transformation.

Methods for Targeting the IGF-1 Receptor

·        The original methods for targeting the IGF-1 receptor in experimental animals were antisense strategies and dominant-negative mutants of the receptor. They are obsolete.
·        Several antibodies to the IGF-IR are effective in inhibiting tumor growth in vitro and in mice. They are now in Phase I clinical trials.
·        Other investigators have identified specific inhibitors of the IGF-1 receptor tyrosine kinase activity. (cyclolignans)
·        To induce apoptosis, it is probably necessary to downregulate the receptor. Without downregulation, there is inhibition of growth, but no apoptosis.
·        Targeting the ligands gives good results in mice, but fails in humans. Adult mice express only IGF-1, but humans keep synthesizing both IGF-1 and IGF-2 in adult life.

Summary of IRS-1

·        Insulin receptor substrate (IRS-1) is a multitask protein that interacts with many other proteins.·        IRS-1 is mitogenic, inhibits differentiation, protects from apoptosis and regulates cell (and body size).·        IRS-1 is essential to mitogenic IGF-IR signaling.

·        IRS-1 is activated by the EGF receptor, cMet and the Ewing’s sarcoma oncogene.

·        IRS-1 plays a significant role in transformation by T antigen and v-src.

·        Doenregulation of IRS-1 causes growth arrest and differentiation.

·        Nuclear IRS-1 acts as a transcriptional cofactor for both RNA pol 1 and 2-directed genes.

·        IRS-1 effects on cells can be dissociated from the effects of IGF-IR, IRS-2 and insulin receptor.

·        IRS-1 is a biomarker of sensitivity of cancer cells to IGF-IR targeting.

·        Hypothesis: IRS-1 is an antitumor suppressor, similar to anti-p53 protein.

 

The ability of IRS-1 to cause cell transformation, and the tendency to lose the transformed phenotype in cells in which IRS-1 is low or has been downregulated, suggests that the importance of the IGF-IR in cancer may be dependent on IRS-1 as much as on the receptor itself. When IRS-1 is activated directly, for instance by v-src, the IGF-IR is no longer a requiremeny for malignant transformation.  Metastases are very susceptible to IGF-IR therapy.

IGF-IR Targeting Summary

  • In the absence of IRS-1, the IGF1R sends a differentiation signal, which becomes mitogenic with IRS1 expression, and targeting IGF1R in cells that do not express IRS-1 may be counterproductive.
  • In colon cancer liver metastases the cancer cells of awash in IGF-1.
  • In Ewing’s sarcoma, a tumor sensitive to IGF1r targeting in clinical trials, there is an autocrine mechanism that may make the cancer cells IGF-1 dependent, but an oncogene/IRS-1 interaction may also make these cells incapable of switching to other growth factors.
  • IGF-1R sends a potent anti-apoptotic signal, independent of its mitogenicity. This property could be exploited to increase chemo- or radio- toxicity.
  • IGF-1R expression is required for anchorage independence.

1.1.3 Advanced Proteomic Technologies for Cancer Biomarker Discoveries

1.1.3.1 State of the art technologies

Wong SCC, Chan CML, Ma BBY,…,Chan ATC.

Medscape 6/10/2009. From Expert Review of Proteomics.
http://medscape.com/viewarticle/703566

Proteomic technologies have experienced major improvements in recent years. Such advances have facilitated the discovery of potential tumor markers with improved sensitivities and specificities for the diagnosis, prognosis and treatment monitoring of cancer patients. The topic of discussion is four state of the art technologies: 2D difference gel electrophoresis, MALDI imaging mass spectrometry, electron transfer dissociation mass spectrometry and reverse-phase protein array.  These have contributed to large advances in proteomic technologies from 1997-2008.

1.1.3.1.1 2D difference gel electrophoresis (2DIGE)

The 2D DIGE method is an improved 2GE technique. Two different protein samples (e.g., control and disease) and, optionally, one reference sample (e.g., control and disease together) are labeled with one of three different fluorophore: cyanine (cy)2, 3 or 5. These fluorophores have the same charge, similar molecular weight and distinct fluorescent properties, allowing their discrimination during scanning using appropriate optical filters.Two types of cyanine dyes are available: CyDyeTM  DIGE Fluor minimal dyse and CyDye DIGE Fluor saturation dye (GE Healthcare, Uppsala, Sweden).The minimal dye labelks a small percentage of lysine residues with minimal change in the electrophoretic mobility pattern of the protein, whereas the saturation dye labels all available cysteine residues and is, therefore, more sensitive, but causes EP mobility shift of labelled proteins.  Different types of protein sample may be used.Labeled sample pairs are mixed and  run in a single gel.The same pooled reference sample is used for all gels within an experiment.The gel is scanned at three wavelengths for Cy2 (488 nm), Cy3 (532 nm) and Cy5 (633 nm), and a gel image for each of the samples is obtained.Variation between the gels is minimized. Correct matching of protein spots is improved.Normalization and quantitation of the spots is most accurate.The linear dynamic range is four orders of magnitude and it is fully compatible for quantitation with MS. The technique is mainly used for the discovery of novel biomarkers.

1.1.3.1.2 MALDI imaging technology (see also 1.1.5)

MALDI Imaging Mass Spectrometry gives a deeper understanding of biochemical processes in the tumor cells and tissues. Immunohistochemistry is limitated, but the MALDI technique is high-throughput.MALDI IMS was developed to allow researchers to analyze proteomic expression profiles directly from patient tissue sections.The tissue is first mounted, then MALDI matrix is applied onto the tissue sample and MALDI MS is applied to obtain mass spectra from predefined locations across the tissue section.All acquired spectra are then compiled into a composite 2D map for the tissue sample.The expression profiles of numerous proteins can be obtained without the need for antibodies. It is also possible to correlate the mapping with tissue histology.

Post-translational modifications have a role in structure and function of proteins: protein folding, protein localization, regulation of activity and mediation of protein-protein interaction. Two common forms of PTM have been implicated in cancer neoplasia: phosphorylation and glycosylation.  Phosphoproteomic studies led to identification of novel tyrosine kinase substrates in breast cancer, and to discovery of novel therapeutic targets for brain cancer, and to increased understanding of signaling pathways in lung cancer.  The identification of novel therapeutic targets for ovarian cancer resulted from identification of abnormally glycosylated proteins – mucins.

1.1.3.1.3 Electron Transfer Dissociation

Electron Transfer Dissociation is a recently developed technique for the analysis of peptides by MS, utilizing radiofrequency quadrupole ion traps such as 2D linear IT, spherical IT and OrbitrapTM (Thermo Fisher,MA).Peptides are fragmented by transfer of electrons from anions to induce cleavage of CαN bonds along the peptide backbone, producing c- and z-type ions. In contrast to CID, ETD preserves the localization of labile PTM and provides peptide-sequence information, but it fails to fragment peptide bonds adjacent to proline.CID and ETD should be used to complement each other. An advantage of the TED is that in the analysis of phosphopeptides a near complete series of c- and z-ions is observed without the loss of phosphoric acid. The method has provided for proteomic researchers a tool for comprehensive analysis of peptides and their PTMs.

1.1.3.1.4 Reverse-phase Protein Array (RPA)

Then there is the Reverse-phase Protein array, which has the advantage that it identifies changes associated with the development of cancer. The identification of such proteins can be used as biomarkers for diagnosis, prognosis, treatment decisions and therapeutic monitoring. Still, patient samples pose a challenge:

  • Proteomic patterns differ among cell types;
  • Protein expression changes dynamically over time;
  • Proteins have a broad dynamic range of expression levels spanning several orders of magnitude;
  • Proteins can be present in multiple forms, such as polymorphysms and splice variants;
  • Traditional proteomic methods, such as, @DE, require larger amounts of protein than those obtained from biopsy samples;
  • Many existing proteomic technologies cannot ber used to study protein-protein interactions.

The method of RPA is simple and requires the spotting of patient samples in an array format onto a nitrocellulose support.Each array is incubated with a particular antibody, and signal intensity is proportional to the amount of analyte. Signal detection is by fluorescence, chemiluminescence or colorimetric methods.  The results are qwuantified by scanning and analyzed by softwares such as P-SCAN and ProteinScan.

Main advantages of RPA are:

  • Various types of biological samples;
  • Investigation of PTMs;
  • Protein-protein interactions;
  • Labeling of samples with fluorescent dyes or mass tags;
  • Quantitation within the linear range of detection;
  • Direct measurement of target proteins by spotting reference standards.

Key Issues

  • 2DE couple with MS has been a mainstay for discovery of novel biomarkewrs;
  • 2D DIGE has improved quantification accuracy;
  • MALDI imaging MS allows detedtion and comparison with histopathology;
  • ETD-MS has opened up the possibility of identifying the structure and localization of PTM and the peptide/protein.
  • RPA is a powerful tool for high-throughput validation across hundreds of samples.

1.1.3.2  Principles of Protein Microarrays


Preface, Foreward and Chapter 1: In Protein Microarrays, Ed. Mark Schena
Mark Schena, Joseph L. Hackett and Emanuel F. Petricoin
Jones and Bartlett Publ. 2002, ON, CA

What is true inside the cell cannot always be recapitulated outside the cell.  The year is 1986 and the second year of graduate school of UCSF. With cloned receptor in hand (just isolated by Roger Miesfeld), I set out to test whether glucocorticoid receptor function could be recapitulated in yeast cells. This might allow us to test evolutionary nconservation in eukaryotes.  Remarkably, the rat receptor sprsang to life on the first attempt, producing a diagnostic blue colot change in yeast cells expressing a β-galactosidase fusion and a broad smile on the face of a young scientist. Receptor experiments in yeast necessarily required grinding up yeast cells, fractionating the proteins by denaturing polyacrylamide gel electrophoresis, transferring the proteins onto nitrocellulose, probing the immobilized proteins with a monoclonal antibody, and examining the filter to confirm the presence of the expressed rat protein.

Protein-ntibody interactions on protein chips are determined by complex associations between epitopes on the target protein and the antigen-binding site on the detection molecule. Individual protein-ligand pairs can possess widely different affinities.  Proteomic microarrays require capture and detection molecules with high affinities and low dissociation rates . For these and other reasons protein chips are more challenging than DNA chips. Antibodies, aptamers, recombinant proteins, peptides, phage, evem small molecular weight chemicals/drugs can be used as a bait molecule and/or detection reagent. The molecule may be an antibody or the cellular lysate itself, which are immobilized onto the substratum and act as a bait molecule.  Each spot contains one type of immobilized antibody or bait protein. The first problem is the vast range of concentrations to be detected (up to a factor of 1010 .  Adequate sensitivity must be achieved (at least femtomolar range), and the amplification chemistry must be tolerant to the large dynamic range of the analytes.

Microarrays are analytical devices that possess four distinct characteristics:

  1. Microscopic target elements or spot;
  2. Planar substrates;
  3. Rows and columns of elements; and
  4. Specific binding between microarray target elements on the substrate and probe molecules in solution.

The scope of microarray research includes:

  1. Gene expression
  2. Signal transduction
  3. Genome mismatch scanning
  4. Inflammation
  5. Cancer
  6. Cell cycle
  7. DNA replication
  8. Oxidative stress
  9. Hormone action
  10. Apoptosis
  11. Neurodegenerative disease
  12. Infectious disease
  13. Cytoskeleton, and
  14. Protein trafficking.

The proliferation of microarrays beyond the realm of DNA and gene expression was inevitable, and the idea of making and using microarrays of proteins, lipids, carbohydrates, and small molecules was an obvious extension of the original DNA microarray format. This exciting technology area provides the foundation for the book, Protein Microarrays.  Proteins, not mRNAs are the true functional components of cells. They mediate gene regulation, enzyme catalysis, cellular metabolism, DNA replication, and cell division and confer cell shape and mobility and the capacity to communicate within and between cells. a hypothetical 400 amino acid protein would have a molecular weight of 54 kDa.
Many cellular proteins fall in the molecular weight range of 10-125 kDa, and nearly every human protein weighs < 500 kDa.

The 20 amino acids are chemically diverse and correspondingly confer to the proteins their structural and functional diversity and impart their catalytic specificity and binding properties. The amino acids are bound in the protein by the amino acid side chains of the polypeptide. The nh-CO peptide unit has a partial double-bond character due to the amide bond, and its conformations are restricted by that structure. In addition, proteins have secondary, tertiary and quaternary structure. Hydrophobic amino acids are in the interior, and hydrophilic amino acid residues are on the exterior. The hydrophilic exterior allows for water solubility.

The following are microarray assay formats used in expression profiling:

  1. Protein expression
  2. Serum-based diagnostics
  3. Protein-protein binding
  4. Drug-target binding
  5. Receptor-epitope binding.

1.1.3.3  Disposable reagentless electrochemical immunosensor array based on a polymer/sol/gel membrane for simultaneous measurement of several tumor markers

Wu J, Yan F, Zhang X, Yan Y, Tang J, Ju H.
Clin Chem 2008; 54(9):1481-1489.
http://dx.doi.org:/10.1373/clinchem.2007.102350

Background: A reagentless sensor array for simultaneous multianalyte testing (SMAT) may enable accurate diagnosis and be applicable for point-of-care testing. We developed a disposable reagentless immunosensor array for simple immunoassay of panels of tumor markers. Methods: We carried out SMAT with a direct capture format, in which colloidal gold nanoparticles with bound horseradish peroxidase (HRP)-labeled antibodies were immobilized on screen-printed carbon electrodes with biopolymer/sol-gel to trap their corresponding antigens from sample solution. Upon formation of immunocomplex, the direct electrochemical signal of the HRP decreased owing to increasing spatial blocking, and the analytes could be simultaneously determined by monitoring the signal changes.
Results: The proposed reagentless immunosensor array allowed simultaneous detection of carcinoma antigen 153, carcinoma antigen 125, carbohydrate antigen 199, and carcinoembryonic antigen in clinical serum samples in the ranges of 0.4–140 kU/L, 0.5–330 kU/L, 0.8–190 kU/L, and 0.1–44 μg/L, respectively, with detection limits of 0.2 kU/L, 0.5 kU/L, 0.3 kU/L, and 0.1 μg/L corresponding to the signals 3 SD above the mean of a zero standard. The interassay imprecision of the arrays was <9.5%, and they were stable for 35 days. The positivity detection rate of panels of tumor markers was >95.5% for 95 cases of cancer-positive sera. Conclusions: The immunosensor array provides a SMAT with short analytical time, small sampling volume, no need for substrate, and, no between-electrode cross-talk. This method not only proved the capability of the array in point-of-care testing, but also allowed simultaneous testing of several tumor markers.

Cancer is one of the leading causes of mortality, and early clinical diagnosis is crucial for successful treatment of the disease. Many immunosensors and immunoassay methods have been developed for the determination of a single tumor marker, whose concentration in human serum is associated with the stages of tumors (1)(2)(3)(4). Because many cancers express 1 marker [e.g., breast cancer is associated with carcinoma antigens 153 and 125 (CA 153 and CA 125)1 and carcinoembryonic antigen (CEA)], and concentrations of several tumor markers often increase in the serum of a patient, accurate simultaneous multianalyte test (SMAT) of combinations of tumor markers may improve the diagnosis of certain types of tumor (5)(6)(7)(8).

SMAT may offer a shorter analytical time, higher sample throughput, lower sampling volume, and lower cost per assay compared with traditional single-analyte tests (9)(10). Thus, multilabel assays and spatially resolved assay systems have been developed as the main modes to perform SMAT (11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25). Application of the multilabel assays has been limited by difficulty in accurate quantification due to different optimal assay conditions and the signal overlap of different labels (11)(12)(13). Although a set of substrate zone-resolved techniques have been proposed to overcome these drawbacks (14)(15), the restriction in the number of available labels still greatly limits their application.

Spatially resolved assays with a single label seem well suited for performing SMAT, and optical SMAT, relying on fluorescence emission and optical reflectance, has been developed into mature technology. Optical SMAT, however, often needs an expensive array detector, such as a charge-coupled device camera (16)(17). Electrochemical array, which is distinguished by its convenient miniaturization for high-throughput systems, low assay cost, and absence of sophisticated and expensive array detectors, shows promising application in cancer screening (18)(19). Electrochemical cross-talk caused by diffusion of the detectable enzymatic products is the main problem in the fabrication of electrochemical array. To solve this problem, many approaches have been followed. One approach, for example, is to ensure that the distance between adjacent electrodes is larger than the diffusion distance of enzymatic product (20)(21)(22)(23), but such an approach conflicts with the goal of miniaturization. Another simple method to completely avoid the electrochemical cross-talk can be achieved by immobilizing the electron-transfer mediator on an individual immunosensor to shuttle electrons (24)(25), but this approach requires the addition of hydrogen peroxide, leading to limited practical application.

A reagentless electrochemical immunosensor is an attractive strategy (26). In our previous work, we prepared several reagentless immunosensors by using sol-gel matrix to immobilize immunoreagents and detected the direct electron transfer of labeled enzyme, horseradish peroxidase (HRP) (27)(28)(29)(30)(31). To achieve SMAT, this work further fabricated a reagentless immunosensor array by individually embedding 4 kinds of HRP-labeled antibody-modified gold nanoparticles in a newly designed biopolymer/sol-gel matrix formed on screen-printed carbon electrodes (SPCEs), where the HRP-Ab-Au nanoparticles were limited in the holes of the biopolymer/sol-gel film. Chitosan, a biopolymer with excellent film-forming ability, biocompatibility, nontoxicity, and high mechanical strength, acted as the adhesion frame in the synthesis of the sol-gel and made the electrical communication between redox sites of the enzyme and sensing surface easier due to the cooperative effort of chitosan and sol-gel matrix. The presence of gold nanoparticles accelerated the electron transfer between immobilized HRP and the electrode and increased the hole size for improving the permeability of the sol-gel matrix so that the antigens in solution could easily penetrate into the sol-gel film for immunoreaction. Upon formation of immunocomplexes, the electrochemical responses decreased due to increasing spatial blocking, leading to the reagentless immunosensing to corresponding antigens without cross-talk. The proposed electrochemical immunosensor array had high analyte throughput, showed acceptable comparability to conventional methods for measuring several tumor markers, could be fabricated with mass production techniques, and thus provided the potential for application in point-of-care testing (POCT).

Schematic diagrams of immunosensors array and multianalyte electrochemical immunoassay system.

Schematic diagrams of immunosensors array and multianalyte electrochemical immunoassay system.

Figure 1.

Schematic diagrams of immunosensors array and multianalyte electrochemical immunoassay system.

(a), Nylon sheet, (b), silver ink, (c), graphite auxiliary electrode, (d), Ag/AgCl reference electrode, (e), graphite working electrode, (f), insulating dielectric.

The DPV curves of both the bare and biopolymer/sol-gel modified SPCEs in 0.2 mol/L PBS, pH 6.9, did not show any detectable signal in the applied potential window (Fig. 3 ). After we embedded 0.17 μL of 50 mg/L HRP-anti-CA 153 in the biopolymer/sol-gel, the modified SPCEs displayed a sensitive peak around −540 mV (vs Ag/AgCl) (curve d, Fig. 3 ), which was close to the reduction peak potential of HRP/biopolymer/sol-gel prepared with 0.17 μL of 2.0 mg/L HRP (curve c, Fig. 3 ), indicating the direct electron transfer between electrode and the labeled HRP with regard to Fe(III)-Fe(II) conversion. The small difference of peak potentials between HRP-anti-CA 153 and HRP resulted from the change of microenvironment around HRP molecules because of the presence of antibody. In the presence of gold nanoparticles in the biopolymer/sol-gel, the reduction peak of the equal amount of HRP-antibody conjugate increased 2.1-fold (curve e, Fig. 3 ). The cyclic voltammetric experiments at different gold electrodes showed the same appearance, and upon incorporation of gold nanoparticles into the biopolymer/sol-gel at SPCEs, the reduction peak current at the same scan rate increased 1.98-fold (see Supplemental Fig. 1 in the Data Supplement that accompanies the online version of this article at  http://www.clinchem.org/content/vol54/issue9). Thus the Au nanoparticles could accelerate the direct electrochemistry of HRP to further amplify the detectable signal. This peak was also 2.7 times higher than that of HRP-anti-CA 153-Au nanoparticles/sol-gel modified SPCE (curve f, Fig. 3 ), indicating the positive effects of chitosan with good biocompatibility and hydrophilicity (35), which enhanced water uptake and swelling of the film and led to better permeability of the film for the transfer of counter ions to neutralize the charge change during the redox process and a favorable microenvironment for electron hopping or electron self-exchange between immobilized HRP molecules (36). Thus electron transfer kinetics and direct electrochemical signal increased. After the modified SPCE was incubated with CA 153, the direct electrochemical signal decreased markedly due to the increased barrier that resulted from the formation of immunocomplex (curve g, Fig. 3 ), leading to a reagentless immunosensing method for antigen detection.

DPVs of bare SPCE

DPVs of bare SPCE

DPVs of bare SPCE (a), biopolymer/sol-gel (b), HRP/biopolymer/sol-gel (c), HRP-anti-CA 153/biopolymer/sol-gel (d), HRP-anti-CA 153-Au nanoparticles/biopolymer/sol-gel (e), HRP-anti-CA 153-Au nanoparticles/sol-gel modified SPCE in pH 6.9 PBS (f), and panel e in pH 6.9 PBS after incubation in 20 μL of 50 kU/L CA 153 at room temperature for 40 min (g).

The formation of immunocomplex depended on the incubation temperature and time. For the sake of convenient manipulation, the incubation step was performed with 20 μL antigen solution or the mixture of antigens for SMAT at room temperature, after which the DPV response of the labeled HRP decreased with increasing incubation time and reached a relatively stable value at 30–40 min (Fig. 4A ), indicating saturated formation of immunocomplex in the membrane. Thus, 40 min was chosen as the optimal incubation time for SMAT.

Dependences of DPV responses of immunosensors on incubation time

Dependences of DPV responses of immunosensors on incubation time

Dependences of DPV responses of immunosensors on incubation time (A) and pH of detection solution (B) for CA 153, CA 125, CA 199, and CEA.

Table 1.

Positivity detection rates of clinical sera.

Sample n Associated tumor markers Positive cases, n Positivity detection rate, %
Colorectal or gastric cancer 53 CA 199, CEA 531 100
Epithelial ovarian cancer 22 CA 125, CA 199, CEA 211 95.5
Breast cancer 8 CA 153, CA 125, CEA 81 100
Lung cancer 12 CA 199, CEA 121 100
Normal serum 20 CA 153, CA 125, CA 199, CEA 22 10

In comparison with previous reports (24)(25), this array avoids the addition of mediator to shuttle electrons, and thus can exclude the electrochemical cross-talk at the electrode dimensions used here. Furthermore, the measurement of the direct electrochemical signal of HRP labeled to immunoreagents also avoids the need for other reagents in the detection process. Although the measurements show acceptable results, adding sulfite in the detection solution is not the best solution for the removal of oxygen. Thus, a system has been developed for POCT to exclude oxygen from the detection solution (see Supplemental Fig. 3 in the online Data Supplement).

1.1.3.4  p16INK4a Expression Correlates with Degree of Cervical Neoplasia: A Comparison with Ki-67 Expression and Detection of High-Risk HPV Types

S Nicholas Agoff, Patricia Lin, Janice Morihara, Constance Mao, Nancy B Kiviat and Laura A Koutsky
Mod Pathol 2003;16(7):665–673

Although recent studies have suggested that p16INK4a may be a useful surrogate biomarker of cervical neoplasia, Ki-67 and human papillomavirus testing have also been shown to be useful in detecting neoplasia. To help delineate the utility of p16INK4a, biopsy samples (n = 569: negative, 133; reactive, 75; atypical, 39; low grade, 76; moderate, 80; and severe intraepithelial neoplasia, 113; also, squamous cell carcinoma, 46; adenocarcinoma, 7) were analyzed by immunohistochemistry for expression of p16INK4a and Ki-67 (n = 432), as well as by in situhybridization for human papillomavirus Type 16 (n = 219). Testing for high-risk human papillomavirus types by polymerase chain reaction and HybridCapture2 was performed on concurrent cervical swab specimens. Recuts of the original blocks were reexamined (n = 198). Endometrial biopsies (n = 10) were also analyzed for p16INK4a expression. Degree of p16INK4a and Ki-67 expression correlated with degree of cervical neoplasia (P < .001) and with presence of high-risk human papillomavirus types (P < .001). There was no relationship between p16INK4a overexpression and inflammation or hormonal status. Ki-67 expression correlated with inflammation (P = 0.003) and was expressed in more reactive and atypical lesions than p16INK4a (P = 0.008). Probes for human papillomavirus 16 stained 54% of cervical neoplastic lesions; the degree of staining correlated significantly with degree of neoplasia (P < .001) and p16INK4astaining (P < .001). Interobserver reproducibility was substantial for p16INK4a and Ki-67 interpretation (weighted kappa: 0.74 and 0.70, respectively). Expression of p16INK4a was observed in all endometrial biopsies. Compared with Ki-67 expression and detection of high-risk human papillomavirus, p16INK4a was less likely to be positive in samples from women with negative, reactive, and atypical biopsies. Although expression of p16INK4ain endometrial epithelium may be problematic in terms of screening, the potential of p16INK4a as a screening test warrants investigation.

The screening of women by Pap smear has led to a remarkable decline in the mortality from cervical cancer; however, secondary to subjective criteria, interpretation of Pap smears is subject to marked inter- and intraobserver variability as well as having a relatively low sensitivity for cervical neoplasia on a single sample (as low as 66% sensitivity for biopsy-proven high-grade squamous intraepithelial lesions [HSIL]) (1, 2). Recently, histology, which is thought of as the gold standard for the diagnosis of cervical neoplasia, has also been found to suffer from marked intra- and interobserver variability, and testing for high-risk human papillomavirus (HPV) by Hybrid Capture 2, which has been shown to be very sensitive in the detection of cervical neoplasia and useful in the triaging of ASCUS smears, has a low specificity for cervical neoplasia (1,3). Thus, new biomarkers that are more sensitive and specific in the detection of cervical neoplasia and more reproducible than cervical cytology are needed.

Human papillomaviruses (HPV) are known to be a major causative agent in cervical neoplasia and invasive cervical carcinoma. Many different HPV types associated with cervical neoplasia have been discovered, and they have been subdivided into high- and low-risk categories based on their association with invasive cervical carcinoma (4). This association is based, in part, on the relative affinity that the HPV-type specific oncoproteins E6 and E7 bind to cellular regulatory proteins, specifically, the p53 tumor suppressor protein and the retinoblastoma protein (Rb) (5). Inactivation of these factors, either by degradation (p53) or functional inactivation (Rb), leads to disruption of the cell cycle and increased proliferation, thought to ultimately give rise to carcinoma.

p16INK4a is a cyclin-dependent kinase inhibitor that regulates the activity of cyclin-dependent kinases 4 and 6 and is often inactivated in many cancers by genetic deletion or hypermethylation (6). In non-HPV–associated tumors, this inactivation leads to increased cyclin-dependent kinase activity and inactivation of Rb. However, in HPV-associated tumors, inactivation of Rb by E7 leads to markedly increased levels of p16INK4a. Recent studies have documented overexpression of p16INK4a not only in cervical intraepithelial neoplasia (CIN) but in cervical cancer as well (6, 7, 8, 9, 10).

For p16INK4a, the results were reported in semiquantitative fashion (negative, or 1+ to 3+) based on none, 5–25%, 25–75%, and >75% of cells immunostained in a lesion. Strong nuclear as well as cytoplasmic staining was considered a positive reaction. Wispy weak cytoplasmic staining present in rare cells (<5%) was considered plusminus, and for analysis was grouped into the negative category. For Ki-67, the results were also reported in a semiquantitative fashion as cells in the lower 1/3 of the epithelium staining (i.e., usually basilar cell staining), cells in the middle 1/3–2/3 staining, or cells in the upper 1/3 staining (14). Strong nuclear staining was considered a positive reaction. Stains were analyzed by two authors (SNA and JM) for reproducibility; each was blinded to the other’s result.

The degree of p16INK4a expression correlated well with the degree of cervical neoplasia, and this correlation improved slightly when compared with the recut slide diagnosis (P < .001; Fig. 1; Tables 1 and 2). There was very little expression in negative and reactive lesions, with only 11% to 12% showing greater than or equal to1+ staining (24 of 208 -original diagnosis, 12 of 112 recut diagnosis). 57% of the CIN I cases had greater than or equal to1+ expression, compared with 75% of CIN II lesions and 91% of CIN III lesions. On the recut diagnosis, 97% of CIN III lesions stained greater than or equal to1+. There were 10 (9%) CIN III original diagnosis that did not stain for p16INK4a, but on review, the majority of these were secondary to the lesion being cut through and not present on the immunohistochemistry (IHC) slide. For the recut diagnosis, there was only 1 (3%) case that did not stain with p16INK4a, and on review, two of three pathologists agreed that this represented CIN III, whereas the third felt it represented atypical squamous metaplasia. p16INK4a expression of 1+ or greater was present in 89%(47/53) of the invasive carcinomas. Review of negative cases confirmed the carcinoma diagnosis.

p16INK4a and Ki-67 expression in normal, low-grade squamous dysplasia, and high grade squamous dysplasia

p16INK4a and Ki-67 expression in normal, low-grade squamous dysplasia, and high grade squamous dysplasia

p16INK4a and Ki-67 expression in normal cervical squamous mucosa (A, H&E stain; B, p16INK4a; C, Ki-67), low-grade squamous dysplasia (CIN I; D, H&E stain; E, p16INK4a; F, Ki-67), and high grade squamous dysplasia (CIN III; G, H&E stain; H, p16INK4a, I, Ki-67).

1.1.3.5  Quantitative real-time detection of magnetic nanoparticles by their nonlinear magnetization

A novel method of highly sensitive quantitative detection of magnetic nanoparticles (MP) in biological tissues and blood system has been realized and tested in real time in vivoexperiments. The detection method is based on nonlinear magnetic properties of MP and the related device can record a very small relative variation of nonlinear magnetic susceptibility up to 108 at room temperature, providing sensitivity of several nanograms of MP in 0.1mlvolume. Real-time quantitative in vivomeasurements of dynamics of MP concentration in blood flow have been performed. A catheter that carried the blood flow of a rat passed through the measuring device. After an MP injection, the quantity of MP in the circulating blood was continuously recorded. The method has also been used to evaluate the MP distribution between rat’s organs. Its sensitivity was compared with detection of the radioactive MP based on isotope of Fe59. The comparison of magnetic and radioactive signals in the rat’s blood and organ samples demonstrated similar sensitivity for both methods. However, the proposed magnetic method is much more convenient as it is safe, less expensive, and provides real-time measurementsin vivo. Moreover, the sensitivity of the method can be further improved by optimization of the device geometry.

1.1.6  Proteomics and biomarkers

1.1.6.1 Identification by proteomic analysis of calreticulin as a marker for bladder cancer and evaluation of the diagnostic accuracy of its detection in urine

Kageyama S, Isono Y, Iwaka H,…, Yoshiki T.
Clin Chem 2004; 50(5):857-866.
http://dx.doi.org:/10.1373/clinchem.2003.027425
How are we going to discover new cancer biomarkers? A proteomic approach for bladder cancer.
Editorial. Eftherios P. Diamandis
Clin Chem 2003; 50(5):794-795.
http://dx.doi.org:/10.1373.2004.032177

BACKGROUND: New methods for detection of bladder cancer are needed because cystoscopy is both invasive and expensive and urine cytology has low sensitivity. We screened proteins as tumor markers for bladder cancer by proteomic analysis of cancerous and healthy tissues and investigated the diagnostic accuracy of one such marker in urine. METHODS: Three specimens of bladder cancer and healthy urothelium, respectively, were used for proteome differential display using narrow-pH-range two-dimensional electrophoresis. To evaluate the presence of calreticulin (CRT) as detected by Western blotting, we obtained 22 cancerous and 10 noncancerous surgical specimens from transurethral resection or radical cystectomy. To evaluate urinary CRT, we collected 70 and 181 urine samples from patients with and without bladder cancer, respectively. Anti-CRT COOH-terminus antibody was used to detect CRT in tissue and urine. RESULTS: Proteomic analysis revealed increased CRT (55 kDa; pI 4.3) in cancer tissue. Quantitative Western blot analysis showed that CRT was increased in cancer tissue (P = 0.0003). Urinary CRT had a sensitivity of 73% (95% confidence interval, 62-83%) at a specificity of 86% (80-91%) for bladder cancer in the samples tested. CONCLUSIONS: Proteomic analysis is useful in searching for candidate proteins as biomarkers and led to the identification of urinary CRT. The diagnostic accuracy of urinary CRT for bladder cancer appears comparable to that of Food and Drug Administration-cleared urinary markers, but further studies are needed to determine its diagnostic role.

A handful of cancer biomarkers are currently used routinely for population screening, disease diagnosis, prognosis, monitoring of therapy, and prediction of therapeutic response. Unfortunately, most of these biomarkers suffer from low sensitivity, specificity, and predictive value, particularly when applied to rare diseases in population screening programs. Thus, for the classic cancer biomarkers much is left to be desired in terms of clinical applicability. We need new cancer biomarkers that will further enhance our ability to diagnose, prognose, and predict therapeutic response in many cancer types. Because biomarkers can be analyzed relatively noninvasively and economically, it is worth investing in discovering more biomarkers in the future. The completion of the Human Genome Project has raised expectations that the knowledge of all genes and proteins will lead to identification of many candidate biomarkers for cancer and other diseases. These predictions still need to be realized. The prevailing view among specialists is that the most powerful single cancer biomarkers may have already been discovered. Likely, in the future we will discover biomarkers that are less sensitive or specific but could be used in panels, in combination with powerful bioinformatic tools, to devise diagnostic algorithms with improved sensitivity and specificity. These efforts are currently in progress1.

  1. Stephan C, Vogel B, Cammann H, Lein M, Klevecka V, Sinha P, et al. [An artificial neural network as a tool in risk evaluation of prostate cancer. Indication for biopsy with the PSA range of 2–20 microg/l]. Urologe A 2003; 42:1221–9.

In this issue of Clinical Chemistry, Kageyama et al. propose proteomic analysis of urine as a new way to identify bladder cancer biomarkers. Previously, Celis et al. 2 used two-dimensional gel electrophoresis and developed a comprehensive database for bladder cancer profiles of both transitional and squamous cell carcinomas. Through their studies, Kageyama et al. were able to identify a potential tumor marker, calreticulin, which is found in the urine of patients with bladder carcinoma. The authors used a differential display method of bladder cancer vs healthy urothelial tissue and mass spectrometry to identify proteins that are increased in cancer tissue. In addition to calreticulin, an endoplasmic reticulum chaperone, they found nine other candidate proteins that could constitute new biomarkers for bladder carcinoma. The authors confirmed their data with quantitative Western blot analysis, immunoprecipitation, and immunohistochemistry. Their reported sensitivity and specificity were 73% and 86%, respectively, similar to the values reported for other biochemical bladder markers. However, the diagnostic accuracy of their test was vulnerable to urinary tract infections3.

3 Positive correlations were found among the appearance of adenylate kinase activity in the urine and the existence of bacteriuria, the Fairley test, and other criteria of urinary infection. Since the adenylate kinase isozymes of human tissues are organ specific and can be distinguished from one another, the appearance of adenylate kinase isozymes in urine was used in this study to identify the existence of infection in bladder or kidney. The findings suggest the usefulness of measuring the appearance of urinary adenylate kinase isozymes for the purpose of detection and differential diagnoses of urinary infections, particularly since adenylate kinase is absent or found in low concentrations in urine and serum under normal conditions.

Currently, potential bladder tumor markers can be used in various clinical scenarios, including4:

  • Serial testing for earlier detection of recurrence;
    • Complementary testing to urine cytology to improve the detection rate;
    • Providing a less expensive and more objective alternative

to the urine cytology test; and
• Directing the cytoscopic evaluation of patient followup.

The gold standard for the detection of urothelial neoplasia is cytologic examination of urothelial cells from voided urine, urinary bladder washings, and urinary tract brushing specimens in combination with cystoscopic examination5,6.

  1. Celis A, Rasmussen HH, Celis P, Basse B, Lauridsen JB, Ratz G, et al. Short-term culturing of low-grade superficial bladder transitional cell carcinomas leads to changes in the expression levels of several proteins involved in key cellular activities. Electrophoresis 1999;20:355–61.
  2. Bernstein LH, Horenstein JM, and Russell PJ. Urinary adenylate kinase and urinary infections. J Clin Microbiol. 1983 Sep; 18(3): 578–584
  3. Fritsche HA. Bladder cancer and urine tumor marker tests. In: Diamandis EP, Fritsche HA, Lilja H, Chan DW, Schwartz MK. Tumor markers: physiology,pathobiology, technology and clinical applications. Washington: AACC Press, 2002; 281–6.
  4. Bailey MJ. Urinary markers in bladder cancer. BJU Int 2003; 91:772–3
  5. Eissa S, Kassim S, El-Ahmady O. Detection of bladder tumours: role of cytology, morphology-based assays, biochemical and molecular markers. Curr Opin Obstet Gynecol 2003;15:395–403

Current guidelines suggest that low-risk patients should be surveyed once a year with cystoscopy and high-risk patients at 3-month intervals. Currently, cystoscopy is always combined with VUC. Because, as mentioned earlier, new urinary bladder tests such as BTA or NMP22 could detect lower-grade disease recurrence with higher sensitivity than VUC, it could be worthwhile to consider including one or more of these tests in the routine follow-up of patients with bladder carcinoma. However, large prospective studies will be necessary to test the clinical utility of these assays against cytology.

1.1.6.2  Multiplexed proteomic analysis of oxidation and concentrations of CSF proteins in Alzheimer’s disease

Korolainen MA, Nyman TA, Nyyssonen P, Hartikainen ES, Pirttila Y.
Clin Chem 2007; 53(4):657-665.
http://dx.doi.org:/10.1373/clinchem.2006.078014

Carbonylation is an irreversible oxidative modification of proteins that has been linked to various conditions of oxidative stress, aging, physiological disorders, and disease. Increased oxidative stress is thus also considered to play a role in the pathogenesis of age-related neurodegenerative disorders such as Alzheimer disease (AD). In addition, it has recently become evident that the response mechanisms to increased oxidative stress may depend on sex. Several oxidized carbonylated proteins have been identified in plasma and brain of AD patients by use of 2-dimensional oxyblotting.

Signals for beta-trace, lambda chain, and transthyretins were decreased in probable AD patients compared with controls. The only identified protein exhibiting an increased degree of carbonylation in AD patients was lambda chain. The concentrations of proteins did not generally differ between men and women; however, vitamin D-binding protein, apolipoprotein A-I, and alpha-1-antitrypsin exhibited higher extents of carbonylation in men.

None of the brain-specific proteins exhibited carbonylation changes in probable AD patients compared with age-matched neurological controls showing no cognitive decline. The carbonylation status of proteins differed between women and men. Two-dimensional multiplexed oxyblotting is applicable to study both the concentrations and carbonylation of cerebrospinal fluid proteins.

1.1.6.3  The Brain Injury Biomarker VLP-1 Is Increased in the Cerebrospinal Fluid of Alzheimer Disease Patients

Jin-Moo Lee, Kaj Blennow, Niels Andreasen, Omar Laterza, Vijay Modur, Jitka Olander, Feng Gao, Matt Ohlendorf, and Jack H. Ladenson
Clinical Chemistry  2008; 54:10 1617–1623
http://dx.doi.org:/10.1373/clinchem.2008.104497

BACKGROUND: Definitive diagnosis of Alzheimer disease (AD) can be made only by histopathological examination of brain tissue, prompting the search for premortem disease biomarkers. We sought to determine if the novel brain injury biomarker, visinin-like protein 1 (VLP-1), is altered in the CSF of AD patients compared with controls, and to compare its values to the other well-studied CSF biomarkers 42-amino acid amyloid- peptide (A1–42), total Tau (tTau), and hyperphosphorylated Tau (pTau). METHODS: Using ELISA, we measured concentrations of A1–42, tTau, pTau, and VLP-1 in CSF samples from 33 AD patients and 24 controls. We compared the diagnostic performance of these biomarkers using ROC curves. RESULTS: CSF VLP-1 concentrations were significantly higher in AD patients [median (interquartile range) 365 (166) ng/L] compared with controls [244 (142.5) ng/L]. Although the diagnostic performance of VLP-1 alone was comparable to that of A, tTau, or pTau alone, the combination of the 4 biomarkers demonstrated better performance than each individually. VLP-1 concentrations were higher in AD subjects with APOE 4/4 genotype [599 (240) ng/L] compared with 3/4 [376 (127) ng/L] and 3/3 [280 (115.5) ng/L] genotypes. Furthermore, VLP-1 values demonstrated a high degree of correlation with pTau (r 0.809) and tTau (r 0.635) but not A1–42 (r 0.233). VLP-1 was the only biomarker that correlated with MMSE score (r 0.384, P 0.030). CONCLUSIONS: These results suggest that neuronal injury markers such as VLP-1 may have utility as biomarkers for AD.

The diagnosis of Alzheimer disease (AD),6 the most common form of dementia in Western countries, is largely based on historical and clinical criteria. Although many studies report a reasonably high degree of diagnostic accuracy (80%–90%), these studies often include patients with advanced disease evaluated at specialized centers (1 ). At present, postmortem examination of brain tissue is the only tool for definitive diagnosis. Therefore, the development of a biomarker for AD would aid greatly in the diagnosis of this disease. In addition, such a marker could potentially be used to measure efficacy in future therapeutic trials. Most studies of AD biomarkers have focused on known pathological substrates for the disease. Amyloid plaques and neurofibrillary tangles are pathological hallmarks of AD (2 ) and primarily comprise abnormally aggregated endogenous proteins. Amyloid plaques (extracellular proteinaceous aggregates) are principally composed of the amyloid- peptide (A), a 38 – to 42–amino acid peptide fragment of the amyloid precursor protein (APP). The major species, the 42– amino acid peptide (A1–42) (3, 4 ), is significantly decreased in the cerebrospinal fluid (CSF) of patients with AD (5– 8 ). Neurofibrillary tangles are intraneuronal protein aggregates found mainly in neurites and primarily composed of hyperphosphorylated Tau (pTau), a microtubule-associated protein.

Fig. 1. CSF VLP-1 values in AD patients and controls. Scatter plot of CSF VLP-1 values in control vs AD patients. The line within the box represents the median value, the box encompasses 25th to 75th percentiles, and the error bars encompass the 10th to 90th percentiles. A significant difference was found in control vs AD patients (P 0.001, Student t-test).

To see if VLP-1 provides utility to the diagnosis of AD beyond the contribution of A, tTau, or pTau alone, we performed a ROC analysisfor each individual biomarker alone compared to the combination of all biomarkers. The AUCs for VLP-1, A, tTau, pTau, and an optimum linear combination of all biomarkers are shown in Fig. 2. AUCs were similar between all biomarkers individually; however, the linear combination of all biomarkers resulted in an approximately 5% improvement (Fig. 2).

To examine possible relationships between CSF VLP-1 values and patient characteristics, we performed correlation analyses between VLP-1 and age, disease duration, MMSE, and the number of APOE 4 alleles. VLP-1 correlated with MMSE and the number of APOE 4 alleles (Fig. 3A). None of the other biomarkers correlated with MMSE in this patient population (A1–42, r 0.350, P 0.497; tTau, r 0.295, P 0.100; pTau, r 0.202, P 0.264). To further examine the relationship between APOE genotype and CSF VLP-1 concentrations, we calculated mean CSF VLP-1 values by different genotypes. APOE 4/4 individuals had the highest concentrations, followed by 3/4 and 3/3 individuals (Fig. 3B).

To examine if VLP-1 concentrations in the CSF were related to values of the other biomarkers studied, we performed correlations between VLP-1 and tTau, pTau, or A1–42 using data from both AD patients and controls (Fig. 4). VLP-1 and pTau showed the greatest correlation (r 0.809) (Fig. 4C), whereas A1–42 did not correlate with VLP-1 (Fig. 4A, r 0.233). Individual correlations for AD patients analyzed separately from controls were also performed, and revealed results similar to that of the total patient population: VLP-1 vs A1–42 was not statistically significant (r 0.29671 and 0.1698 in AD and controls, respectively), whereas VLP-1 vs tTau (r 0.6221 and 0.7247 in AD and controls) and pTau (r 0.8747 and 0.6227 in AD and controls) were significantly correlated in the AD and control populations analyzed separately.

Dementia severity appears to correlate with the number of neurofibrillary tangles, but not to the degree of plaque deposition (13 ). The close correlation between VLP-1 and pTau concentrations in the CSF of AD patients is consistent with these findings, as is the lack of correlation with A. There are several limitations to this study. First, the number of patients in both control and disease groups is limited. Further studies will be needed to confirm our findings in larger, more well-characterized populations. Second, because the diagnosis of AD was made by clinical criteria, there will undoubtedly be a small but significant group of patients that were misdiagnosed (10%–20%) (1 ). This may account for some of the overlap in values for CSF biomarkers. ApoE genotyping in the control group might help with this diagnostic uncertainty. A much more rigorous study would require autopsy confirmation of diagnosis. Third, our study is limited to a comparison of VLP-1 concentrationsin AD patients vs controls, a situation thatis unlikely to occur clinically. A more relevant comparison should be made across patients carrying the differential diagnosis of dementia. Finally, our CSF samples represent a single snapshot in AD pathogenesis; further studies will be required to understand the time course or biomarker evolution with disease pathogenesis.

1.1.6.4 Determination of non-α1-antichymotrypsin-complexed PSA as an indirect measurement of free PSA: analytical performance and diagnostic accuracy.

Wesselin S, Dtephan C, Semjonow A,…, Jung K.
Clin Chem 2003;49(6):887-894.
http://dx.doi.org:/10.1373/49.6.887

Background: A new assay measures prostate-specific antigen (PSA) not complexed to α1-antichymotrypsin (nACT-PSA) after removing PSA complexed to ACT by use of anti-ACT antibodies. We evaluated nACT-PSA and its ratio to total PSA (tPSA) as alternatives to free PSA (fPSA) and its ratio to tPSA in differentiating prostate cancer (PCa) and benign prostatic hyperplasia (BPH) in patients with tPSA of 2–20 μg/L. Methods: PSA in serum of 183 untreated patients with PCa and 132 patients with BPH was measured retrospectively on the chemiluminescence immunoassay analyzer LIAISON® (Byk-Sangtec Diagnostica) with the LIAISON tPSA and LIAISON fPSA assays. The nACT-PSA fraction was determined with a prototype assay measuring the residual PSA after precipitation of ACT-PSA with an ACT-precipitating reagent.
Results: nACT-PSA was higher than fPSA in samples with fPSA concentrations <1 μg/L but lower in samples with >1 μg/L fPSA. The median ratios of fPSA/tPSA and of nACT-PSA/tPSA were significantly different between patients with BPH and PCa (19.4% vs 12.2% and 17.4% vs 13.0%, respectively). Within the tPSA ranges tested (2–20, 2–10, and 4–10 μg/L), areas under the ROC curves for the fPSA/tPSA ratios were significantly larger than those for nACT-PSA/tPSA. In the tPSA ranges <10 μg/L, the areas under the ROC curves for fPSA/tPSA were significantly larger than those for tPSA, whereas the areas for nACT-PSA/tPSA were not. At decision limits for 95% sensitivity and specificity, both ratios significantly increased specificity and sensitivity, respectively, compared with tPSA, but the fPSA/tPSA ratio showed higher values. Conclusions: nACT-PSA and its ratio to tPSA provide lower diagnostic sensitivity and specificity than fPSA/tPSA. The fPSA/tPSA ratio represents the state-of-the-art method for differentiating between PCa and BPH.

1.1.6.5 Ultrasensitive densitometry detection of cytokines with nanoparticle-modified aptamers

Li yuan-Yuan, Zhang C, Li Bo-Sheng, …, Xu Shun-Quing
Clin Chem 2007; 53(6):1061-1066
http://dx.doi.org:/10.1373/clinchem.2006.082271

Background: Aptamers mimic properties of antibodies and sometimes turn out to be even better than antibodies as reagents for assays. We describe the establishment of an ultrasensitive densitometry method for cytokine detection by nanoparticle (NP)-modified aptamers. Methods: The assay simultaneously uses a gold NP–modified aptamer and a biotin-modified aptamer to bind to the target protein, forming a sandwich complex. The absorbance signal generated by the aptamer-protein complex is amplified and detected with a microplate reader. Results: The assay for platelet-derived growth factor B-chain homodimer (PDGF-BB) was linear from 1 fmol/L to 100 pmol/L (R2 = 0.9869). The analytical detection limit was 83 amol/L. The intraassay and interassay imprecision (CVs) was ≤7.5%. Serum concentrations of PDGF-BB determined with the gold NP–modified aptamer assay and with ELISA were not significantly different. Conclusions: The gold NP–modified aptamer assay provides a fast, convenient method for cytokine detection and improves the detection range and the detection limit compared with ELISA.

1.1.6.6  Protein profiling of microdissected pancreas carcinoma and identification of HSP27 as a potential serum marker.

Melle C, Ernst G, Escher N, Hartmann D,…, von Eggeling F.
Clin Chem 2007; 53(4):629-635.
http://dx.doi.org:/10.1373/clinchem.2006.079194

Background: Patients with pancreatic adenocarcinomas have a poor prognosis because of late clinical manifestation and the tumor’s aggressive nature. We used proteomic techniques to search for markers of pancreatic carcinoma. Methods: We performed protein profiling of microdissected cryostat sections of 9 pancreatic adenocarcinomas and 10 healthy pancreatic tissue samples using ProteinChip technology (surface-enhanced laser desorption/ionization). We identified proteins by use of 2-dimensional gel electrophoresis, peptide fingerprint mapping, and immunodepletion and used immunohistochemistry for in situ localization of the proteins found. We used ELISA to quantify these proteins in preoperative serum samples from 35 patients with pancreatic cancer and 37 healthy individuals. Results: From among the differentially expressed signals that were detected by ProteinChip technology, we identified 2 proteins, DJ-1 and heat shock protein 27 (HSP27). We then detected HSP27 in sera of patients by use of ELISA, indicating a sensitivity of 100% and a specificity of 84% for the recognition of pancreatic cancer. Conclusions: The detection of DJ-1 and HSP27 in pure defined tissue and the retrieval of HSP27 in serum by antibody-based methods identifies a potential marker for pancreatic cancer.

1.1.7  Mass Spectrometry Methods

1.1.7.1 LC-MS/MS quantification of Zn-α2 glycoprotein: A potential serum biomarker for prostate cancer

Bondar OP, Barnidge DR, KKlee EW, Davis BJ, Klee GG
Clin Chem 2007; 53(4):673-678 http://dx.doi.org:/10.1373/clinchem.2006.079681

LC-MS/MS – tandem mass spectrometry

Background: Zn-α2 glycoprotein (ZAG) is a relatively abundant glycoprotein that has potential as a biomarker for prostate cancer. We present a high-flow liquid chromatography–tandem mass spectrometry (LC-MS/MS) method for measuring serum ZAG concentrations by proteolytic cleavage of the protein and quantification of a unique peptide. Methods: We selected the ZAG tryptic peptide 147EIPAWVPEDPAAQITK162 as the intact protein for quantification and used a stable isotope-labeled synthetic peptide with this sequence as an internal standard. Standards using recombinant ZAG in bovine serum albumin, 50 g/L, and a pilot series of patient sera were denatured, reduced, alkylated, and digested with trypsin. The concentration of ZAG was calculated from a dose–response curve of the ratio of the relative abundance of the ZAG tryptic peptide to internal standard. Results: The limit of detection for ZAG in serum was 0.08 mg/L, and the limit of quantification was 0.32 mg/L with a linear dynamic range of 0.32 to 10.2 mg/L. Replicate digests from pooled sera run during a period of 3 consecutive days showed intraassay imprecision (CV) of 5.0% to 6.3% and interassay imprecision of 4.4% to 5.9%. Mean (SD) ZAG was higher in 25 men with prostate cancer [7.59 (2.45) mg/L] than in 20 men with nonmalignant prostate disease [6.21 (1.65) mg/L, P = 0.037] and 6 healthy men [3.65 (0.71) mg/L, P = 0.0007]. Conclusions: The LC-MS/MS assay can be used to evaluate the clinical utility of ZAG as a cancer biomarker.

1.1.7.2 A novel, high-throughput workflow for discovery and identification of serum carrier protein-bound peptide biomarker candidates in ovarian cancer samples.

Lopez MF, Mikulskis A, Kuzdzal S, Golenko E,…, Fishman D.
Clin Chem 2007; 53(6):1067-1074.
http://dx.doi.org:/10.1373/clinchem.2006.080721

MALDI-TOF MS

Background: Most cases of ovarian cancer are detected at later stages when the 5-year survival is ∼15%, but 5-year survival approaches 90% when the cancer is detected early (stage I). To use mass spectrometry (MS) of serum proteins for early detection, a seamless workflow is needed that provides an opportunity for rapid profiling along with direct identification of the underpinning ions. Methods: We used carrier protein–bound affinity enrichment of serum samples directly coupled with MALDI orthagonal TOF MS profiling to rapidly search for potential ion signatures that contained discriminatory power. These ions were subsequently directly subjected to tandem MS for sequence identification. Results: We discovered several biomarker panels that enabled differentiation of stage I ovarian cancer from unaffected (age-matched) patients with no evidence of ovarian cancer, with positive results in >93% of samples from patients with disease-negative results and in 97% of disease-free controls. The carrier protein–based approach identified additional protein fragments, many from low-abundance proteins or proteins not previously seen in serum. Conclusions: This workflow system using a highly reproducible, high-resolution MALDI-TOF platform enables rapid enrichment and profiling of large numbers of clinical samples for discovery of ion signatures and integration of direct sequencing and identification of the ions without need for additional offline, time-consuming purification strategies.

1.1.7.3  Mass Spectrometry-based hepcidin measurements in serum and urine: analytical aspects and clinical implications.

Kemna EHJM, Tjalsma H, Podust VN, Swinkels DW.
Clin Chem 2007; 53(4):620-628.
http://DX.DOI.ORG:/10.1373/clinchem.2006.079186

SELDI-TOF MS

Background: Discovery of the central role of hepcidin in body iron regulation has shed new light on the pathophysiology of iron disorders. Information is lacking on newer analytical approaches to measure hepcidin in serum and urine. Recent reports on the measurement of urine and serum hepcidin by surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) necessitate analytical and clinical evaluation of MS-based methodologies. Methods: We used SELDI-TOF MS, immunocapture, and tandem MS to identify and characterize hepcidin in serum and urine. In addition to diagnostic application, we investigated analytical reproducibility and biological and preanalytical variation for both serum and urine on Normal Phase 20 and Immobilized Metal Affinity Capture 30 ProteinChip arrays. We obtained samples from healthy controls and patients with documented iron-deficiency anemia, inflammation-induced anemia, thalassemia major, and hereditary hemochromatosis. Results: Proteomic techniques showed that hepcidin-20, -22, and -25 isoforms are present in urine. Hepcidin-25 in serum had the same amino acid sequence as hepcidin-25 in urine, whereas hepcidin-22 was not detected in serum. The interarray CV was 15% to 27%, and interspot CV was 11% to 13%. Preliminary studies showed that hepcidin-25 differentiated disorders of iron metabolism. Urine hepcidin is more affected by multiple freeze-thaw cycles and storage conditions, but less influenced by diurnal variation, than is serum hepcidin. Conclusion: SELDI-TOF MS can be used to measure hepcidin in both serum and urine, but serum requires a standardized sampling protocol.

1.1.7.4  Current state and future directions of neurochemical biomarkers for Alzheimer’s disease.

In this comprehensive review, we summarize the current state-of-the-art of neurochemical biomarkers for Alzheimer’s disease. Predominantly, these biomarkers comprise cerebrospinal fluid biomarkers directly related to the pathophysiology of this disorder (such as amyloid beta protein, tau protein). We particularly pay attention to the innovations in this area that have been made in technological aspects during the past 5 years (e.g., multiplex analysis of biomarkers, proteomics), to the discovery of novel, potential biomarkers (e.g., amyloid beta oligomers, isoprostanes), and to the extension of this research towards identification of biomarkers in plasma.

1.1.7.5  Use of SELDI-TOF mass spectrometry for identification of new biomarkers: potential and limitations.

Surface-enhanced laser desorption time of flight mass spectrometry (SELDI-TOF-MS) is an important proteomic technology that is immediately available for the high throughput analysis of complex protein samples. Over the last few years, several studies have demonstrated that comparative protein profiling using SELDI-TOF-MS breaks new ground in diagnostic protein analysis particularly with regard to the identification of novel biomarkers. Importantly, researchers have acquired a better understanding also of the limitations of this technology and various pitfalls in biomarker discovery. Bearing these in mind, great emphasis must be placed on the development of rigorous standards and quality control procedures for the pre-analytical as well as the analytical phase and subsequent bioinformatics applied to analysis of the data. To avoid the risk of false-significant results studies must be designed carefully and control groups accurately selected. In addition, appropriate tools, already established for analysis of highly complex microarray data, need to be applied to protein profiling data. To validate the significance of any candidate biomarker derived from pilot studies in appropriately designed prospective multi-center studies is mandatory; reproducibility of the clinical results must be shown over time and in different diagnostic settings. SELDI-TOF-MS-based studies that are in compliance with these requirements are now required; only a few have been published so far. In the meantime, further evaluation and optimization of both technique and marker validation strategies are called for before MS-based proteomic algorithms can be translated into routine laboratory testing.

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Researchers unlock the mysteries of how cells rush to a wound and heal it

Reporter: Aviva Lev-Ari, PhD, RN

 

 

A multidisciplinary research team has discovered how cells know to rush to a wound and heal it — opening the door to new treatments for diabetes, heart disease and cancer. The findings shed light on the mechanisms of cell migration, particularly in the wound-healing process. The results represent a major advancement for regenerative medicine, in which biomedical engineers and other researchers manipulate cells’ form and function to create new tissues, and even organs, to repair, restore or replace those damaged by injury or disease.

 

The answer, it turns out, involves delicate interactions between biomechanical stress, or force, which living cells exert on one another, and biochemical signaling. The University of Arizona researchers discovered that when mechanical force disappears — for example at a wound site where cells have been destroyed, leaving empty, cell-free space — a protein molecule, known as DII4, coordinates nearby cells to migrate to a wound site and collectively cover it with new tissue. What’s more, they found, this process causes identical cells to specialize into leader and follower cells. Researchers had previously assumed leader cells formed randomly. “The results significantly increase our understanding of how tissue regeneration is regulated and advance our ability to guide these processes,” said Pak Kin Wong, UA associate professor of mechanical and aerospace engineering and lead investigator of the research.

 

Wong’s team observed that when cells collectively migrate toward a wound, leader cells expressing a form of messenger RNA, or mRNA, genetic code specific to the DII4 protein emerge at the front of the pack, or migrating tip. The leader cells, in turn, send signals to follower cells, which do not express the genetic messenger. This elaborate autoregulatory system remains activated until new tissue has covered a wound.

 

The same migration processes for wound healing and tissue development also apply to cancer spreading, the researchers noted. The combination of mechanical force and genetic signaling stimulates cancer cells to collectively migrate and invade healthy tissue.

 

Biologists have known of the existence of leader cells and the DII4 protein for some years and have suspected they might be important in collective cell migration. But precisely how leader cells formed, what controlled their behavior, and their genetic makeup were all mysteries — until now. “Knowing the genetic makeup of leader cells and understanding their formation and behavior gives us the ability to alter cell migration,” Wong said.

 

With this new knowledge, researchers can re-create, at the cellular and molecular levels, the chain of events that brings about the formation of human tissue. Bioengineers now have the information they need to direct normal cells to heal damaged tissue, or prevent cancer cells from invading healthy tissue.

Source: www.eurekalert.org

See on Scoop.itCardiovascular and vascular imaging

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Voluntary and Involuntary S- Insufficiency

Writer and Curator: Larry H Bernstein, MD, FCAP 

Transthyretin and the Stressful Condition

Introduction

This article is written among a series of articles concerned with stress, obesity, diet and exercise, as well as altitude and deep water diving for extended periods, and their effects.  There is a reason that I focus on transthyretin (TTR), although much can be said about micronutients and vitamins, and fat soluble vitamins in particular, and iron intake during pregnancy.    While the importance of vitamins and iron are well accepted, the metabolic basis for their activities is not fully understood.  In the case of a single amino acid, methionine, it is hugely important because of the role it plays in sulfur metabolism, the sulfhydryl group being essential for coenzyme A, cytochrome c, and for disulfide bonds.  The distribution of sulfur, like the distribution of iodine, is not uniform across geographic regions.  In addition, the content of sulfur found in plant sources is not comparable to that in animal protein.  There have been previous articles at this site on TTR, amyloid and sepsis.

Transthyretin and Lean Body Mass in Stable and Stressed State

http://pharmaceuticalintelligence.com/2013/12/01/transthyretin-and-lean-body-mass-in-stable-and-stressed-state/

A Second Look at the Transthyretin Nutrition Inflammatory Conundrum

http://pharmaceuticalintelligence.com/2012/12/03/a-second-look-at-the-transthyretin-nutrition-inflammatory-conundrum/

Stabilizers that prevent transthyretin-mediated cardiomyocyte amyloidotic toxicity

http://pharmaceuticalintelligence.com/2013/12/02/stabilizers-that-prevent-transthyretin-mediated-cardiomyocyte-amyloidotic-toxicity/

Thyroid Function and Disorders

http://pharmaceuticalintelligence.com/2015/02/05/thyroid-function-and-disorders/

Proteomics, Metabolomics, Signaling Pathways, and Cell Regulation: a Compilation of Articles in the Journal http://pharmaceuticalintelligence.com

http://pharmaceuticalintelligence.com/2014/09/01/compilation-of-references-in-leaders-in-pharmaceutical-intelligence-about-proteomics-metabolomics-signaling-pathways-and-cell-regulation-2/

Malnutrition in India, high newborn death rate and stunting of children age under five years

http://pharmaceuticalintelligence.com/2014/07/15/malnutrition-in-india-high-newborn-death-rate-and-stunting-of-children-age-under-five-years/

Vegan Diet is Sulfur Deficient and Heart Unhealthy

http://pharmaceuticalintelligence.com/2013/11/17/vegan-diet-is-sulfur-deficient-and-heart-unhealthy/

How Methionine Imbalance with Sulfur-Insufficiency Leads to Hyperhomocysteinemia

http://pharmaceuticalintelligence.com/2013/04/04/sulfur-deficiency-leads_to_hyperhomocysteinemia/

Amyloidosis with Cardiomyopathy

http://pharmaceuticalintelligence.com/2013/03/31/amyloidosis-with-cardiomyopathy/

Advances in Separations Technology for the “OMICs” and Clarification of Therapeutic Targets

http://pharmaceuticalintelligence.com/2012/10/22/advances-in-separations-technology-for-the-omics-and-clarification-of-therapeutic-targets/

Sepsis, Multi-organ Dysfunction Syndrome, and Septic Shock: A Conundrum of Signaling Pathways Cascading Out of Control

http://pharmaceuticalintelligence.com/2012/10/13/sepsis-multi-organ-dysfunction-syndrome-and-septic-shock-a-conundrum-of-signaling-pathways-cascading-out-of-control/

Automated Inferential Diagnosis of SIRS, sepsis, septic shock

http://pharmaceuticalintelligence.com/2012/08/01/automated-inferential-diagnosis-of-sirs-sepsis-septic-shock/

Transthyretin and the Systemic Inflammatory Response 

Transthyretin has been widely used as a biomarker for identifying protein-energy malnutrition (PEM) and for monitoring the improvement of nutritional status after implementing a nutritional intervention by enteral feeding or by parenteral infusion. This has occurred because transthyretin (TTR) has a rapid removal from the circulation in 48 hours and it is readily measured by immunometric assay. Nevertheless, concerns have been raised about the use of TTR in the ICU setting, which prompts a review of the actual benefit of using this test in a number of settings. TTR is easily followed in the underweight and the high risk populations in an ambulatory setting, which has a significant background risk of chronic diseases.  It is sensitive to the systemic inflammatory response syndrom (SIRS), and needs to be understood in the context of acute illness to be used effectively. There are a number of physiologic changes associated with SIRS and the injury/repair process that will affect TTR and will be put in context in this review. The most important point is that in the context of an ICU setting, the contribution of TTR is significant in a complex milieu.  copyright @ Bentham Publishers Ltd. 2009.

Transthyretin as a marker to predict outcome in critically ill patients.
Arun Devakonda, Liziamma George, Suhail Raoof, Adebayo Esan, Anthony Saleh, Larry H. Bernstein.
Clin Biochem Oct 2008; 41(14-15): 1126-1130

A determination of TTR level is an objective method od measuring protein catabolic loss of severly ill patients and numerous studies show that TTR levels correlate with patient outcomes of non-critically ill patients. We evaluated whether TTR level correlates with the prevalence of PEM in the ICUand evaluated serum TTR level as an indicator of the effectiveness of nutrition support and the prognosis in critically ill patients.

TTR showed excellent concordance with patients classified with PEM or at high malnutrition risk, and followed for 7 days, it is a measure of the metabolic burden. TTR levels did not respond early to nutrition support because of the delayed return to anabolic status. It is particularly helpful in removing interpretation bias, and it is an excellent measure of the systemic inflammatory response concurrent with a preexisting state of chronic inanition.

 The Stressful Condition as a Nutritionally Dependent Adaptive Dichotomy

Yves Ingenbleek and Larry Bernstein
Nutrition 1999;15(4):305-320 PII S0899-9007(99)00009-X

The injured body manifests a cascade of cytokine-induced metabolic events aimed at developing defense mechanisms and tissue repair. Rising concentrations of counterregulatory hormones work in concert with cytokines to generate overall insulin and insulin-like growth factor 1 (IGF-1), postreceptor resistance and energy requirements grounded on lipid dependency. Dalient features are self-sustained hypercortisolemia persisting as long as cytokines are oversecreted and down-regulation of the hypothalamo-pituitary-thyroid axis stabilized at low basal levels. Inhibition of thyroxine 5’deiodinating activity (5’DA) accounts for the depressed T3 values associated with the sparing of both N and energy-consuming processes. Both the liver and damaged territories adapt to stressful signals along up-regulated pathways disconnected from the central and peripheral control systems. Cytokines stimulate 5’DA and suppress the synthesis of TTR, causing the drop of retinol-binding protein (RBP) and the leakage of increased amounts of T4 and retinol in free form. TTR and RBP thus work as prohormonal reservoirs of precursor molecules which need to be converted into bioactive derivatives (T3 and retinoic acids) to reach transcriptional efficiency. The converting steps (5’DA and cellular retinol-binding protein-1) are activated to T4 and retinol, themselves operating as limiting factors to positive feedback loops. …The suicidal behavior of TBG, CBG, and IGFBP-3 allows the occurrence of peak endocrine and mitogenic influences at the site of inflammation. The production rate of TTR by the liver is the main determinant of both the hepatic release and blood transport of holoRBP, which explains why poor nutritional status concomitantly impairs thyroid- and retinoid-dependent acute phase responses, hindering the stressed body to appropriately face the survival crisis.  …
abbreviations: TBG, thyroxine-binding globulain; CBG, cortisol-binding globulin; IGFBP-3, insulin growth factor binding protein-3; TTR, transthyretin; RBP, retionol-binding protein.

Why Should Plasma Transthyretin Become a Routine Screening Tool in Elderly Persons? 

Yves Ingenbleek.
J Nutrition, Health & Aging 2009.

The homotetrameric TTR molecule (55 kDa as MM) was first identified in cerebrospinal fluid (CSF).  The initial name of prealbumin (PA)  was assigned based on the electrophoretic migration anodal to albumin. PA was soon recognized as a specific binding protein for thyroid hormone. and also of plasma retinol through the mediation of the small retinol-binding protein (RBP, 21 kDa as MM), which has a circulating half-life half that of TTR (24 h vs 48 h).

There exist at least 3 goos reasons why TTR should become a routine medical screening test in elderly persons.  The first id grounded on the assessment of protein nutritional status that is frequently compromized and may become a life threatening condition.  TTR was proposed as a marker of protein-energy malnutrition (PEM) in 1972. As a result of protein and energy deprivation, TTR hepatic synthesis is suppressed whereas all plasma indispensable amino acids (IAAs) manifest declining trends with the sole exception of methionine (Met) whose concentration usually remains unmodified. By comparison with ALB and transferrin (TF) plasma values, TTR did reveal a much higher degree of reactivity to changes in protein status that has been attributed to its shorter biological half-life and to its unusual tryptophan richness. The predictive ability of outcome offered by TTR is independent of that provided by ALB and TF. Uncomplicated PEM primarily affects the size of body nitrogen (N) pools, allowing reduced protein syntheses to levels compatible with survival.  These adaptiver changes are faithfully identified by the serial measurement of TTR whose reliability has never been disputed in protein-depleted states. On the contrary, the nutritional relevance of TTR has been controverted in acute and chronic inflammatory conditions due to the cytokine-induced transcriptional blockade of liver synthesis which is an obligatory step occurring independently from the prevailing nutritional status. Although PEM and stress ful disorders refer to distinct pathogenic mechanisms, their combined inhibitory effects on TTR liber production fueled a long-lasting strife regarding a poor specificity.  Recent body compositional studies have contributed to disentagling these intermingled morbidities, showing that evolutionary patterns displayed by plasma TTR are closely correlated with the fluctuations of lean body mass (LBM).

The second reason follows from advances describing the unexpected relationship established between TTR and homocysteine (Hcy), a S-containing AA not found in customary diets but resulting from the endogenous transmethylation of dietary methionine.  Hcy may be recycled to Met along a remethylation pathway (RM) or irreversibly degraded throughout the transsulfuration (TS) cascade to relase sulfaturia as end-product. Hcy is thus situated at the crossrad of RM and TS pathways which are in equilibrium keeping plasma Met values unaltered.  Three dietary water soluble B viatamins are implicated in the regulation of the Hcy-Met cycle. Folates (vit B9) are the most powerful agent, working as a supplier of the methyl group required for the RM process whereas cobalamines (vit B12) and pyridoxine (vit B6) operate as cofactors of Met-synthase and cystathionine-β-synthase.  Met synthase promotes the RM pathway whereas the rate-limiting CβS governs the TS degradative cascade. Dietary deficiency in any of the 3 vitamins may upregulate Hcy plasma values, an acquied biochemiucal anomaly increasingly encountered in aged populations.

The third reason refers to recent and fascinating data recorded in neurobiology and emphasizing the specific properties of TTR in the prevention of brain deterioration. TTR participates directly in the maintenance of memory and normal cognitive processes during the aging process by acting on the retinoid signaling pathway.  Moreover, TTR may bind amyloid β peptide in vitro, preventing its transformation into toxic amyloid fibrils and amyloid plaques.  TTR works as a limiting factor for the plasma transport of retinoid, which in turn operates as a limiting determinant of both physiologically active retinoic acid (RA) derivatives, implying that any fluctuation in protein status might well entail corresponding  alterations in cellular bioavailability of retinoid compounds.  Under normal aging circumstances, the concentration of retinoid compounds declines in cerebral tissues together with the downregulation of RA receptor expression. In animal models, depletion of RAs causes the deposition of amyloid-β peptides, favoring the formation of amyloid plaques.

Prealbumin and Nutritional Evaluation

Larry Bernstein, Walter Pleban
Nutrition Apr 1996; 12(4):255-259.
http://nutritionjrnl.com/article/S0899-9007(96)90852-7

We compressed 16-test-pattern classes of albumin (ALB), cholesterol (CHOL), and total protein (TPR) in 545 chemistry profiles to 4 classes by conveerting decision values to a number code to separate malnourished (1 or 2) from nonmalnourished (NM)(0) patients using as cutoff values for NM (0), mild (1), and moderate (2): ALB 35, 27 g/L; TPR 63, 53 g/L; CHOL 3.9, 2.8 mmol/L; and BUN 9.3, 3.6 mmol/L. The BUN was found to have  to have too low an S-value to make a contribution to the compressed classification. The cutoff values for classifying the data were assigned prior to statistical analysis, after examining information in the structured data. The data was obtained by a natural experiment in which the test profiles routinely done by the laboratory were randomly extracted. The analysis identifies the values used that best classify the data and are not dependent on distributional assumptions. The data were converted to 0, 1, or 2 as outcomes, to create a ternary truth table (eaxch row in nnn, the n value is 0 to 2). This allows for 3(81) possible patterns, without the inclusion of prealbumin (TTR). The emerging system has much fewer patterns in the information-rich truth table formed (a purposeful, far from random event). We added TTR, coded, and examined the data from 129 patients. The classes are a compressed truth table of n-coded patterns with outcomes of 0, 1, or 2 with protein-energy malnutrition (PEM) increasing from an all-0 to all-2 pattern.  Pattern class (F=154), PAB (F=35), ALB (F=56), and CHOL (F=18) were different across PEM class and predicted PEM class (R-sq. = 0.7864, F=119, p < E-5). Kruskall-Wallis analysis of class by ranks was significant for pattern class E-18), TTR (6.1E-15) ALB (E-16), CHOL (9E-10), and TPR (5E-13). The medians and standard error (SEM) for TTR, ALB, and CHOL of four TTR classes (NM, mild, mod, severe) are: TTR = 209, 8.7; 159, 9.3; 137, 10.4; 72, 11.1 mg/L. ALB – 36, 0.7; 30.5, 0.8; 25.0, 0.8; 24.5, 0.8 g/L. CHOL = 4.43, 0.17; 4.04, 0.20; 3.11, 0.21; 2.54, 0.22 mmol/L. TTR and CHOL values show the effect of nutrition support on TTR and CHOL in PEM. Moderately malnourished patients receiving nutrition support have TTR values in the normal range at 137 mg/L and at 159 mg/L when the ALB is at 25 g/L or at 30.5 g/L.

An Informational Approach to Likelihood of Malnutrition 

Larry Bernstein, Thomas Shaw-Stiffel, Lisa Zarney, Walter Pleban.
Nutrition Nov 1996;12(11):772-776.  PII: S0899-9007(96)00222-5.
http://dx.doi.org:/nutritionjrnl.com/article/S0899-9007(96)00222-5

Unidentified protein-energy malnutrition (PEM) is associated with comorbidities and increased hospital length of stay. We developed a model for identifying severe metabolic stress and likelihood of malnutrition using test patterns of albumin (ALB), cholesterol (CHOL), and total protein (TP) in 545 chemistry profiles…They were compressed to four pattern classes. ALB (F=170), CHOL (F = 21), and TP (F = 5.6) predicted PEM class (R-SQ = 0.806, F= 214; p < E^-6), but pattern class was the best predictor (R-SQ = 0.900, F= 1200, p< E^-10). Ktuskal-Wallis analysis of class by ranks was significant for pattern class (E^18), ALB (E^-18), CHOL (E^-14), TP (@E^-16). The means and SEM for tests in the three PEM classes (mild, mod, severe) were; ALB – 35.7, 0.8; 30.9, 0.5; 24.2, 0.5 g/L. CHOL – 3.93, 0.26; 3.98, 0.16; 3.03, 0.18 µmol/L, and TP – 68.8, 1.7; 60.0, 1.0; 50.6, 1.1 g/L. We classified patients at risk of malnutrition using truth table comprehension.

Downsizing of Lean Body Mass is a Key Determinant of Alzheimer’s Disease

Yves Ingenbleek, Larry Bernstein
J Alzheimer’s Dis 2015; 44: 745-754.
http://dx.doi.org:/10.3233/JAD-141950

Lean body mass (LBM) encompasses all metabolically active organs distributed into visceral and structural tissue compartments and collecting the bulk of N and K stores of the human body. Transthyretin (TTR)  is a plasma protein mainly secreted by the liver within a trimolecular TTR-RBP-retinol complex revealing from birth to old age strikingly similar evolutionary patterns with LBM in health and disease. TTR is also synthesized by the choroid plexus along distinct regulatory pathways. Chronic dietary methionine (Met) deprivation or cytokine-induced inflammatory disorders generates LBM downsizing following differentiated physiopathological processes. Met-restricted regimens downregulate the transsulfuration cascade causing upstream elevation of homocysteine (Hcy) safeguarding Met homeostasis and downstream drop of hydrogen sulfide (H2S) impairing anti-oxidative capacities. Elderly persons constitute a vulnerable population group exposed to increasing Hcy burden and declining H2S protection, notably in plant-eating communities or in the course of inflammatory illnesses. Appropriate correction of defective protein status and eradication of inflammatory processes may restore an appropriate LBM size allowing the hepatic production of the retinol circulating complex to resume, in contrast with the refractory choroidal TTR secretory process. As a result of improved health status, augmented concentrations of plasma-derived TTR and retinol may reach the cerebrospinal fluid and dismantle senile amyloid plaques, contributing to the prevention or the delay of the onset of neurodegenerative events in elderly subjects at risk of Alzheimer’s disease.

Amyloidogenic and non-amyloidogenic transthyretin variants interact differently with human cardiomyocytes: insights into early events of non-fibrillar tissue damage

Pallavi Manral and Natalia Reixach
Biosci.Rep.(2015)/35/art:e00172 http://dx.doi.org:/10.1042/BSR20140155

TTR (transthyretin) amyloidosis are diseases characterized by the aggregation and extracellular deposition of the normally soluble plasma protein TTR. Ex vivo and tissue culture studies suggest that tissue damage precedes TTR fibril deposition, indicating that early events in the amyloidogenic cascade have an impact on disease development. We used a human cardiomyocyte tissue culture model system to define these events. We previously described that the amyloidogenic V122I TTR variant is cytotoxic to human cardiac cells, whereas the naturally occurring, stable and non-amyloidogenic T119M TTR variant is not. We show that most of the V122I TTR interacting with the cells is extracellular and this interaction is mediated by a membraneprotein(s). In contrast, most of the non-amyloidogenic T119M TTR associated with the cells is intracellular where it undergoes lysosomal degradation. The TTR internalization process is highly dependent on membrane cholesterol content. Using a fluorescent labelled V122I TTR variant that has the same aggregation and cytotoxic potential as the native V122I TTR, we determined that its association with human cardiomyocytes is saturable with a KD near 650nM. Only amyloidogenic V122I TTR compete with fluorescent V122I force ll-binding sites. Finally, incubation of the human cardiomyocytes with V122I TTR but not with T119M TTR, generates superoxide species and activates caspase3/7. In summary, our results show that the interaction of the amyloidogenic V122I TTR is distinct from that of a non-amyloidogenic TTR variant and is characterized by its retention at the cell membrane, where it initiates the cytotoxic cascade.

Emerging roles for retinoids in regeneration and differentiation in normal and disease states

Lorraine J. Gudas
Biochimica et Biophysica Acta 1821 (2012) 213–221
http://dx.doi.org:/10.1016/j.bbalip.2011.08.002

The vitamin (retinol) metabolite, all-transretinoic acid (RA), is a signaling molecule that plays key roles in the development of the body plan and induces the differentiation of many types of cells. In this review the physiological and pathophysiological roles of retinoids (retinol and related metabolites) in mature animals are discussed. Both in the developing embryo and in the adult, RA signaling via combinatorial Hoxgene expression is important for cell positional memory. The genes that require RA for the maturation/differentiation of T cells are only beginning to be cataloged, but it is clear that retinoids play a major role in expression of key genes in the immune system. An exciting, recent publication in regeneration research shows that ALDH1a2(RALDH2), which is the rate-limiting enzyme in the production of RA from retinaldehyde, is highly induced shortly after amputation in the regenerating heart, adult fin, and larval fin in zebrafish. Thus, local generation of RA presumably plays a key role in fin formation during both embryogenesis and in fin regeneration. HIV transgenic mice and human patients with HIV-associated kidney disease exhibit a profound reduction in the level of RARβ protein in the glomeruli, and HIV transgenic mice show reduced retinol dehydrogenase levels, concomitant with a greater than 3-fold reduction in endogenous RA levels in the glomeruli. Levels of endogenous retinoids (those synthesized from retinol within cells) are altered in many different diseases in the lung, kidney, and central nervous system, contributing to pathophysiology.

The Membrane Receptor for Plasma Retinol-Binding Protein, A New Type of Cell-Surface Receptor

Hui Sun and Riki Kawaguchi
Intl Review Cell and Molec Biol, 2011; 288:Chap 1. Pp 1:34
http://dx.doi.org:/10.1016/B978-0-12-386041-5.00001-7

Vitamin A is essential for diverse aspects of life ranging from embryogenesis to the proper functioning of most adul torgans. Its derivatives (retinoids) have potent biological activities such as regulating cell growth and differentiation. Plasma retinol-binding protein (RBP) is the specific vitamin A carrier protein in the blood that binds to vitamin A with high affinity and delivers it to target organs. A large amount of evidence has accumulated over the past decades supporting the existence of a cell-surface receptor for RBP that mediates cellular vitamin A uptake. Using an unbiased strategy, this specific cell-surface RBP receptor has been identified as STRA6, a multi-transmembrane domain protein with previously unknown function. STRA6 is not homologous to any protein of known function and represents a new type of cell-surface receptor. Consistent with the diverse functions of vitamin A, STRA6 is widely expressed in embryonic development and in adult organ systems. Mutations in human STRA6 are associated with severe pathological phenotypes in many organs
such as the eye, brain, heart, and lung. STRA6 binds to RBP with high affinity and mediates vitamin A uptake into cells. This review summarizes the history of the RBP receptor research, its expression in the context of known functions of vitamin A in distinct human organs, structure/function analysis of this new type of membrane receptor, pertinent questions regarding its very existence, and its potential implication in treating human diseases.

Choroid plexus dysfunction impairs beta-amyloid clearance in a triple transgenic mouse model of Alzheimer’s disease

Ibrahim González-Marrero, Lydia Giménez-Llort, Conrad E. Johanson, et al.
Front Cell Neurosc  Feb2015; 9(17): 1-10
http://dx.doi.org:/10.3389/fncel.2015.00017

Compromised secretory function of choroid plexus (CP) and defective cerebrospinal fluid (CSF) production, along with accumulation of beta-amyloid (Aβ) peptides at the blood-CSF barrier (BCSFB), contribute to complications of Alzheimer’s disease (AD). The AD triple transgenic mouse model (3xTg-AD) at 16 month-old mimics critical hallmarks of the human disease: β-amyloid (Aβ) plaques and neurofibrillary tangles (NFT) with a temporal-and regional-specific profile. Currently, little is known about transport and metabolic responses by CP to the disrupted homeostasis of CNS Aβ in AD. This study analyzed the effects of highly-expressed AD-linked human transgenes (APP, PS1 and tau) on lateral ventricle CP function. Confocal imaging and immunohistochemistry revealed an increase only of Aβ42 isoform in epithelial cytosol and in stroma surrounding choroidal capillaries; this buildup may reflect insufficient clearance transport from CSF to blood. Still, there was increased expression, presumably compensatory, of the choroidal Aβ transporters: the low density lipoprotein receptor-related protein1 (LRP1) and the receptor for advanced glycation end product (RAGE). A thickening of the epithelial basal membrane and greater collagen-IV deposition occurred around capillaries in CP, probably curtailing solute exchanges. Moreover, there was attenuated expression of epithelial aquaporin-1 and transthyretin(TTR) protein compared to Non-Tg mice. Collectively these findings indicate CP dysfunction hypothetically linked to increasing Aβ burden resulting in less efficient ion transport, concurrently with reduced production of CSF (less sink action on brain Aβ) and diminished secretion of TTR (less neuroprotection against cortical Aβ toxicity). The putative effects of a disabled CP-CSF system on CNS functions are discussed in the context of AD.

Endoplasmic reticulum: The unfolded protein response is tangled In neurodegeneration

Jeroen J.M. Hoozemans, Wiep Scheper
Intl J Biochem & Cell Biology 44 (2012) 1295–1298
http://dx.doi.org/10.1016/j.biocel.2012.04.023

Organelle facts•The ER is involved in the folding and maturation ofmembrane-bound and secreted proteins.•The ER exerts protein quality control to ensure correct folding and to detect and remove misfolded proteins.•Disturbance of ER homeostasis leads to protein misfolding and induces the UPR.•Activation of the UPR is aimed to restore proteostasis via an intricate transcriptional and (post)translational signaling network.•In neurodegenerative diseases classified as tauopathies the activation of the UPR coincides with the pathogenic accumulation of the microtubule associated protein tau.•The involvement of the UPR in tauopathies makes it a potential therapeutic target.

The endoplasmic reticulum (ER) is involved in the folding and maturation of membrane-bound and secreted proteins. Disturbed homeostasis in the ER can lead to accumulation of misfolded proteins, which trigger a stress response called the unfolded protein response (UPR). In neurodegenerative diseases that are classified as tauopathies, activation of the UPR coincides with the pathogenic accumulation of the microtubule associated protein tau. Several lines of evidence indicate that UPR activation contributes to increased levels of phosphorylated tau, a prerequisite for the formation of tau aggregates. Increased understanding of the crosstalk between signaling pathways involved in protein quality control in the ERand tau phosphorylation will support the development of new therapeutic targets that promote neuronal survival.

Chemical and/or biological therapeutic strategies to ameliorate protein misfolding diseases

Derrick Sek Tong Ong and Jeffery W Kelly
Current Opin Cell Biol 2011; 23:231–238
http://dx.doi.org:/10.1016/j.ceb.2010.11.002

Inheriting a mutant misfolding-prone protein that cannot be efficiently folded in a given cell type(s) results in a spectrum of human loss-of-function misfolding diseases. The inability of the biological protein maturation pathways to adapt to a specific misfolding-prone protein also contributes to pathology. Chemical and biological therapeutic strategies are presented that restore protein homeostasis, or proteostasis, either by enhancing the biological capacity of the proteostasis network or through small molecule stabilization of a specific misfolding-prone protein. Herein, we review the recent literature on therapeutic strategies to ameliorate protein misfolding diseases that function through either of these mechanisms, or a combination thereof, and provide our perspective on the promise of alleviating protein misfolding diseases by taking advantage of proteostasis adaptation.

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Diet and Cholesterol

Writer and Curator: Larry H. Bernstein, MD, FCAP 

 

Introduction

We are all familiar with the conundrum of diet and cholesterol.  As previously described, cholesterol is made by the liver. It is the backbone for the synthesis of sex hormones, corticosteroids, bile, and vitamin D. It is also under regulatory control, and that is not fully worked out, but it has health consequences. The liver is a synthetic organ that is involved with glycolysis, gluconeogenesis, cholesterol synthesis, and unlike the heart and skeletal muscles – which are energy transducers – the liver is anabolic, largely dependent on NADPH.  The mitochondria, which are associated with aerobic metabolism, respiration, are also rich in the liver.  The other part of this story is the utilization of lipids synthesized by the liver in the vascular endothelium.  The vascular endothelium takes up and utilizes/transforms cholesterol, which is involved in the degenerative development of pathogenic plaque.  Plaque is associated with vascular rigidity, rupture and hemorrhage, essential in myocardial inmfarction. What about steroid hormones?  There is some evidence that sex hormone differences may be a factor in coronary vascular disease and cardiac dysfunction.  The evidence that exercise is beneficial is well established, but acute coronary events can occur during exercise.  WE need food, and food is at the center of the discussion – diet and cholesterol.  The utilization of food varies regionally, and is dependent on habitat.  But it is also strongly influence by culture.  We explore this further in what follows.

A high fat, high cholesterol diet leads to changes in metabolite patterns in pigs – A metabolomic study

Jianghao Sun, Maria Monagas, Saebyeol Jang, Aleksey Molokin, et al.
Food Chemistry 173 (2015) 171–178
http://dx.doi.org/10.1016/j.foodchem.2014.09.161

Non-targeted metabolite profiling can identify biological markers of dietary exposure that lead to a better understanding of interactions between diet and health. In this study, pigs were used as an animal model to discover changes in metabolic profiles between regular basal and high fat/high cholesterol diets. Extracts of plasma, fecal and urine samples from pigs fed high fat or basal regular diets for 11 weeks were analysed using ultra-high performance liquid chromatography with high-resolution mass spectrometry (UHPLC–HRMS) and chemometric analysis. Cloud plots from XCMS online were used for class separation of the most discriminatory metabolites. The major metabolites contributing to the discrimination were identified as bile acids (BAs), lipid metabolites, fatty acids, amino acids and phosphatidic acid (PAs), phosphatidylglycerol (PGs), glycerophospholipids (PI), phosphatidylcholines (PCs) and tripeptides. These results suggest the developed approach can be used to identify biomarkers associated with specific feeding diets and possible metabolic disorders related to diet.

Nutritional metabolomics is a rapidly developing sub-branch of metabolomics, used to profile small-molecules to support integration of diet and nutrition in complex bio-systems research. Recently, the concept of ‘‘food metabolome’’ was introduced and defined as all metabolites derived from food products. Chemical components in foods are absorbed either directly or after digestion, undergo extensive metabolic modification in the gastrointestinal tract and liver and then appear in the urine and feces as final metabolic products. It is well known that diet has a close relationship with the long-term health and well-being of individuals. Hence, investigation of the ‘‘food metabolome’’ in biological samples, after feeding specific diets, has the potential to give objective information about the short- and long-term dietary intake of individuals, and to identify potential biomarkers of certain dietary patterns. Previous studies have identified potential biomarkers after consumption of specific fruits, vegetables, cocoa, and juices. More metabolites were revealed by using metabolomic approaches compared with the detection of pre-defined chemicals found in those foods.

Eating a high-fat and high cholesterol diet is strongly associated with conditions of obesity, diabetes and metabolic syndrome, that are increasingly recognized as worldwide health concerns. For example, a high fat diet is a major risk factor for childhood obesity, cardiovascular diseases and hyperlipidemia. Little is known on the extent to which changes in nutrient content of the human diet elicit changes in metabolic profiles. There are several reports of metabolomic profiling studies on plasma, serum, urine and liver from high fat-diet induced obese mice, rats and humans. Several potential biomarkers of obesity and related diseases, including lysophosphatidylcholines (lysoPCs), fatty acids and branched-amino acids (BCAAs) have been reported.

To model the metabolite response to diet in humans, pigs were fed a high fat diet for 11 weeks and the metabolite profiles in plasma, urine and feces were analyzed. Non-targeted ultra high performance liquid chromatography tandem with high resolution mass spectrometry (UHPLC–MS) was utilized for metabolomics profiling. Bile acids (BAs), lipid metabolites, fatty acids, amino acids and phosphatidic acid (PAs), phosphatidylglycerol (PGs), glycerophospholipids (PI), phosphatidylcholines (PCs), tripeptides and isoflavone conjugates were found to be the final dietary metabolites that differentiated pigs fed a high-fat and high cholesterol diet versus a basal diet. The results of this study illustrate the capacity of this metabolomic profiling approach to identify new metabolites and to recognize different metabolic patterns associated with diet.

Body weight, cholesterol and triglycerides were measured for all the pigs studied. There was no significant body weight gain between pigs fed diet A and diet B after 11 weeks of treatment. The serum cholesterol and triglyceride levels were significantly higher in pigs fed with diet B compared with the control group at the end of experiment.

Plasma, urine and fecal samples were analyzed in both positive and negative ionization mode. To obtain reliable and high-quality metabolomic data, a pooled sample was used as a quality control (QC) sample to monitor the run. The QC sample (a composite of equal volume from 10 real samples) was processed as real samples and placed in the sample queue to monitor the stability of the system. All the samples were submitted in random for analysis. The quantitative variation of the ion features across the QC samples was less than 15%. The ion features from each possible metabolite were annotated by XCMS online to confirm the possible fragment ions, isotopic ions and possible adduct ions. The reproducibility of the chromatography was determined by the retention time variation profiles that were generated by XCMS. The retention time deviation was less than 0.3 min for plasma samples, less than 0.3 min for fecal samples, and less than 0.2 min for urine samples, respectively. On the basis of these results of data quality assessment, the differences between the test samples from different pigs proved more likely to reflect varied metabolite profiles rather than analytical variation. The multivariate analysis results from the QC sample showed the deviation of the analytical system was acceptable.
Good separation can be observed between pigs on the two diets, which is also reflected in the goodness of prediction (Q2), of 0.64 using data from the positive ionization mode. For negative ionization mode data, better separation appears with a Q2of 0.73.

Cloud plot is a new multidimensional data visualization method for global metabolomic data (Patti et al., 2013). Data characteristics, such as the p-value, fold change, retention time, mass-to-charge ratio and signal intensity of features, can be presented simultaneously using the cloud plot. In this study, the cloud plot was used to illustrate the ion features causing the group separation. In Fig. 2 and 82 features with p < 0.05 and fold change >2, including visualisation of the p-value, the directional fold change, the retention time and the mass to charge ratio of features, are shown. Also, the total ion chromato-grams for each sample were shown. The upper panel in (2A) shows the chromatograms of plasma samples from pigs fed the high fat diet, while the lower panel shows the chromatograms of samples from pigs fed the regular diet. Features whose intensity is increased are shown in green, whereas features whose intensity is decreased are shown in pink (2A). The size of each bubble corresponds to the log fold change of the feature: the larger the bubble, the larger the fold changes. The statistical significance of the fold change, as calculated by a Welch t-test with unequal variances, is represented by the intensity of the feature’s color where features with low p-values are brighter compared to features with high p-values. The Y coordinate for each feature corresponds to the mass-to-charge ratio of the compound, as determined by mass spectrometry. Each feature is also color coded, such as features that are shown with a black outline have database hits in METLIN, whereas features shown without a black outline do not have any database hits.

From the cloud plot (Fig. 2A), 82 discriminating ion features from positive data and 48 discriminating ions features from negative data were considered as of great importance for class separation. After filtering out the fragment ions, isotope annotations, and adduct ions, thirty-one metabolites were tentatively assigned using a Metlin library search (Table S4).

Among the assigned metabolites detected, five of the highest abundant metabolites were identified as bile acid and bile acid conjugates (Fig. 2B). This series of compounds shared the following characteristics; the unconjugated bile acids showed [M-H] ion as base peak in the negative mode.

The characteristic consistent with bile acid hyodeoxycholic acid (HDCA) was confirmed with a reference standard. For the conjugated bile acids (usually with glycine and taurine), the [M-H] and [M+H]+ are always observed as the base peaks. For example, the ion feature m/z 448.3065 at 21.18 min was identified as chenodeoxycholic acid glycine conjugate. The neutral loss of 62 amu (H2O + CO2) was considered as a characteristic fragmentation pathway for bile acid glycine conjugates. This above mentioned characteristic can easily identify a series of bile acids compounds. The five metabolite ions detected in plasma were significantly different between pigs fed the high fat diet (Fig. 2B, red bars) and regular diet (Fig. 2B, blue bars) for 11 weeks, and were identified as chenodeoxycholic acid glycine conjugate, tauroursodeoxycholic acid, hyodeoxycholic acid, deoxycholic acid glycine conjugate and glycocholic acid; chenodeoxycholic acid glycine and hyodeoxycholic acid.

Figures 1-4 , not shown.
Fig 1. The PCA score plot of plasma (A) (+)ESI data with all the ion features; (B) (+)ESI data with selected ion features; (C) (-)ESI data with all ion features; (D) (-)ESI data with selected ion features. Samples were taken from pigs fed diet A (BS, blue) and diet B (HF, red). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig 2. Cloud plot showing 82 discriminatory ion features (negative ion data) in plasma, and (B) box-plot of data set of the five most abundant bile acids identified in plasma (negative ion data) samples.

Fig. 3. PCA score plot of fecal samples from pigs fed diet A (BS, blue) and diet B (HF, red) (A) week 0, (B) week 2, (C) week 4 (D) week 6, (E) week 11 for distal samples (F) week 11 for proximal colon samples. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 4. PCA and PLS-DA score plot of urine samples from (+)ESI-data (A and C) and (-)ESI-data (B and D) taken at the end of the study (week 11) from pigs fed diet A (BS, blue) and diet B (HF, red). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Plasma, fecal and urine metabolites from pigs fed either a high fat or regular diet were investigated using a UHPLC–HRMS based metabolomic approach. Their metabolic profiles were compared by multivariate statistical analysis.
Diet is logically believed to have a close relationship with metabolic profiles. Feeding a high fat and high cholesterol diet to pigs for 11 weeks resulted in
an increase in bile acids and their derivatives in plasma, fecal and urine samples, though at this stage, there was no significant weight gain observed.

In a previous study, a significantly higher level of muricholic acid, but not cholic acid, was found in pigs fed a high fat diet. The gut microbiota of these pigs were altered by diet and considered to regulate bile acid metabolism by reducing the levels of tauro-beta-muricholic acid. In our study, the unconjugated bile acids, hyodeoxycholic acid and deoxycholic acid were found to be significantly higher in the fecal samples of pigs fed a high-fat diet.

Chenodeoxycholic acid glycine was 8.6 times higher in pigs fed a high fat and high cholesterol diet compared to those fed a regular diet. These results confirm that feeding a high fat and high cholesterol diet leads to a changing metabolomic pattern over time, represented by excretion of certain bile acids in the feces. We also found that several metabolites associated with lipid metabolism were increased in the feces of pigs fed the high-fat diet. Feeding the high fat diet to pigs for 11 weeks did not induce any overt expression of disease, except for significantly higher levels of circulating cholesterol and triglycerides in the blood. It is likely, however, that longer periods of feeding would increase expression of metabolic syndrome disorders and features of cardiovascular disease in pigs, as have been previously demonstrated. Products of lipid metabolism that changed early in the dietary treatment could be useful as biomarkers. This may be important because the composition of the fats in the diet, used in this study, was complex and from multiple sources including lard, soybean oil and coconut oil.

In summary, a number of metabolite differences were detected in the plasma, urine and feces of pigs fed a high fat and high cholesterol diet versus a regular diet that significantly increased over time. PCA showed a clear separation of metabolites in all biological samples tested from pigs fed the different diets. This methodology could be used to associate metabolic profiles with early markers of disease expression or the responsiveness of metabolic profiles to alterations in the diet. The ability to identify metabolites from bio-fluids, feces, and tissues that change with alterations in the diet has the potential to identify new biomarkers and to better understand mechanisms related to diet and health.

Amino acid, mineral, and polyphenolic profiles of black vinegar, and its lipid lowering and antioxidant effects in vivo

Chung-Hsi Chou, Cheng-Wei Liu, Deng-Jye Yang, Yi-Hsieng S Wuf, Yi-Chen Chen
Food Chemistry 168 (2015) 63–69
http://dx.doi.org/10.1016/j.foodchem.2014.07.035

Black vinegar (BV) contains abundant essential and hydrophobic amino acids, and polyphenolic contents, especially catechin and chlorogenic acid via chemical analyses. K and Mg are the major minerals in BV, and Ca, Fe, Mn, and Se are also measured. After a 9-week experiment, high-fat/cholesterol-diet (HFCD) fed hamsters had higher (p < 0.05) weight gains, relative visceral-fat sizes, serum/liver lipids, and serum cardiac indices than low-fat/cholesterol diet (LFCD) fed ones, but BV supplementation decreased (p < 0.05) them which may resulted from the higher (p < 0.05) fecal TAG and TC contents. Serum ALT value, and hepatic thiobarbituric acid reactive substances (TBARS), and hepatic TNF-α and IL-1β contents in HFCD-fed hamsters were reduced (p < 0.05) by supplementing BV due to increased (p < 0.05) hepatic glutathione (GSH) and trolox equivalent antioxidant capacity (TEAC) levels, and catalase (CAT) and glutathione peroxidase (GPx) activities. Taken together, the component profiles of BV contributed the lipid lowering and antioxidant effects on HFCD fed hamsters.

World Health Organization (WHO) reported that more than 1.4 billion adults were overweight (WHO, 2013). As we know, imbalanced fat or excess energy intake is one of the most important environmental factors resulted in not only increased serum/liver lipids but also oxidative stress, further leading cardiovascular disorders and inflammatory responses. Food scientists strive to improve serum lipid profile and increase serum antioxidant capacity via  medical foods or functional supplementation.

Vinegar is not only used as an acidic seasoning but also is shown to have some beneficial effects, such as digestive, appetite stimulation, antioxidant, exhaustion recovering effects, lipid lowering effects, and regulations of blood pressure. Polyphenols exist in several food categories, such as vegetable, fruits, tea, wine, juice, and vinegar that have effects against lipid peroxidation, hypertension, hyperlipidemia, inflammation, DNA damage, and. Black vinegar (BV) (Kurosu) is produced from unpolished rice with rice germ and bran through a stationary surface fermentation and contains higher amounts of amino acids and organic acids than other vinegars. Black vinegar is also characterised as a health food rather than only an acidic seasoning because it was reported to own a DPPH radical scavenging ability and decrease the adipocyte size in rat models. Moreover, the extract of BV shows the highest radical scavenging activity in a DPPH radical system than rice, grain, apple, and wine vinegars. The extract suppresses increased lipid peroxidation in mouse skin treated with 12-o-tetradecanoylphorbol-13-acetate.

This study focused on the nutritional compositions in BV, and the in-vivo lipid lowering and antioxidant effects. First, the amino acid, mineral, and polyphenolic profile of BV were identified. Hypolipidemic hamsters induced by a high-fat/cholesterol diet (HFCD) were orally administered with different doses of BV. Serum lipid profile and liver damage indices liver and fecal lipid contents, as well as hepatic antioxidant capacities [thiobarbituric acid reactive substances (TBARS), glutathione (GSH), trolox equivalent antioxidant capacity (TEAC), and activities of superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx)] and hepatic cytokine levels were assayed to demonstrated physiological functions of BV.

Higher serum AST, ALT, and free fatty acids, as well as hepatic cholesterol, triacylglycerol, MDA, hydroperoxide, and cytokine (IL-1β and TNF-α) levels were easily observed in a high-fat-consumption rodent. Several reports indicated some amino acids antioxidant activities in vitro and in vivo. Acidic amino acids, such as Asp and Glu and hydrophobic amino acids, such as Ile, Leu, and Val display high antioxidant properties. Recently, an in vivo study indicated that a pepsin hydrolyzation significantly enhanced Asp, Glu, Leu, and Val contents in chicken livers; meanwhile, chicken-liver hydrolysates showed an antioxidant capacity in brain and liver of D-galactose treated mice. In addition, it was also reported that Mg and Se play important roles in SOD and GPx activities, respectively. Uzun and Kalender (2013) used chlorpyrifos, an organophosphorus insecticide, to induce hepatotoxic and hematologic changes in rats, but they observed that catechin can attenuate the chlorpyrifos-induced hepatotoxicity by increasing GPx and glutathione-S-transferase activities and decreasing MDA contents. Meanwhile, chlorogenic acid elevated SOD, CAT, and GPx activities with concomitantly decreased lipid peroxidation of liver and kidney in streptozotocin-nicotinamide induced type-2 diabetic rats. Hence, it is reasonable to assume that increased antioxidant capacities and decreased damage in livers of HFCD fed hamsters supplemented with BV should be highly related to the components, i.e. amino acid profile, mineral profile, and polyphenol contents, as well as the lowered liver lipid accumulations.

In analyses of amino acids, minerals and polyphenols, BV contained abundant essential amino acids and hydrophobic amino acids. Mg, K, Ca, Fe, Mn, and Se were measured in BV where K and Mg were major. Gallic acid, catechin, chlorogenic acid, p-hydroxybezoic acid, p-cumeric acid, ferulic acid, and sinapic acid were also identified in BV where catechin and chlorogenic acid were the majorities. Meanwhile, the lipid-lowering and antioxidant effects of BV were also investigated via a hamster model. BV supplementation apparently decreased weight gain (g and %), relative size of visceral fat, serum/liver TC levels, serum cardiac index, and hepatic TBARS values and damage indices (serum ALT and hepatic TNF-α and IL-1β) but increased fecal lipid contents and hepatic antioxidant capacities (GSH level, TEAC level, CAT activity, and GPx activity) in HFCD fed hamsters. To sum up, those benefits could be attributed to a synergetic effect of compounds in BV.

Analysis of pecan nut (Carya illinoinensis) unsaponifiable fraction – Effect of ripening stage on phytosterols and phytostanols composition

Intidhar Bouali, Hajer Trabelsi, Wahid Herchi, Lucy Martine, et al.
Food Chemistry 164 (2014) 309–316
http://dx.doi.org/10.1016/j.foodchem.2014.05.029

Changes in 4-desmethylsterol, 4-monomethylsterol, 4,4-dimethylsterol and phytostanol composition were quantitatively and qualitatively investigated during the ripening of three varieties of Tunisian grown pecan nuts. These components have many health benefits, especially in lowering LDL-cholesterol and preventing heart disease. The phytosterol composition of whole pecan kernel was quantified by Gas Chromatography–Flame Ionization Detection (GC–FID) and identified by Gas Chromatography–Mass Spectrometry (GC–MS). Fifteen phytosterols and one phytostanol were quantified. The greatest amount of phytosterols (2852.5 mg/100 g of oil) was detected in Mahan variety at 20 weeks after the flowering date (WAFD). Moore had the highest level of phytostanols (7.3 mg/100 g of oil) at 20 WAFD. Phytosterol and phytostanol contents showed a steep decrease during pecan nut development. Results from the quantitative characterization of pecan nut oils revealed that β-sitosterol, D5-avenasterol, and campesterol were the most abundant phytosterol compounds at all ripening stages.

Association between HMW adiponectin, HMW-total adiponectin ratio and early-onset coronary artery disease in Chinese population

Ying Wang, Aihua Zheng, Yunsheng Yan, Fei Song, et al.
Atherosclerosis 235 (2014) 392-397
http://dx.doi.org/10.1016/j.atherosclerosis.2014.05.910

Objective: Adiponectin is an adipose-secreting protein that shows atheroprotective property and has inverse relation with coronary artery disease (CAD). High-molecular weight (HMW) adiponectin is reported as the active form of adiponectin. In the present study, we aimed to investigate the association between total adiponectin, HMW adiponectin, HMW-total adiponectin ratio and the severity of coronary atherosclerosis, and to compare their evaluative power for the risk of CAD. Methods: Serum levels of total and HMW adiponectin were measured in 382 early-onset CAD (EOCAD) patients and 305 matched controls undergoing coronary angiography by enzyme-linked immunosorbent assay (ELISA). Gensini score was used to evaluate the severity of coronary atherosclerosis. Results: CAD onset age was positively correlated with HMW adiponectin (r = 0.383, P < 0.001) and HMW-total adiponectin ratio (r = 0.429, P < 0.001) in EOCAD patients. Total and HMW adiponectin and HMW-total adiponectin ratio were all inversely correlated with Gensini score (r=0.417, r=0.637, r=0.578, respectively; all P < 0.001). Multivariate binary logistic regression analysis demonstrated that HMW adiponectin and HMW-total adiponectin ratio were both inversely correlated with the risk of CAD (P < 0.05). ROC analysis indicated that areas under the ROC curves of HMW adiponectin and HMW-total adiponectin ratio were larger than that of total adiponectin (P < 0.05). Conclusions: Adiponectin is cardioprotective against coronary atherosclerosis onset in EOCAD patients. HMW adiponectin and HMW-total adiponectin ratio show stronger negative associations with the severity of coronary atherosclerosis than total adiponectin does. HMW adiponectin and HMW-total adiponectin ratio are effective biomarkers for the risk of CAD in Chinese population.

Gender and age were well matched between patients and controls. EOCAD patients were tended to have a history of diabetes or hypertension, more current smoking, and more use of lipid lowering drugs. Levels of total cholesterol, LDL-c, FPG, HbA1c and triglycerides were significantly higher in the patients than in controls, while HDL-cholesterol, total adiponectin, HMW adiponectin, and HMW-total adiponectin ratio were significantly lower in the patients. EOCAD patients developed different degrees of coronary atherosclerosis, and had significantly higher levels of high-sensitivity CRP and larger circumferences of waist and hip than controls.

Spearman correlation coefficients between selected cardiovascular risk factors, Gensini score and adiponectin were significant. Total and HMW adiponectin and HMW-total adiponectin ratio were all inversely correlated with Gensini score, BMI and pack years of cigarette smoking. Total and HMW adiponectin were negatively associated with triglycerides and circumference of waist and hip. LDL-cholesterol and high-sensitivity CRP were inversely correlated with HMW adiponectin and HMW-total adiponectin ratio, while HDL-cholesterol and age were positively correlated with them. FPG was only inversely associated with HMW-total adiponectin ratio.

All participants were divided into four groups according to their Gensini score, group A (control, n = 305), group B (<20, n = 154), group C (20-40, n = 121) and group D (>40, n = 105). With the increasing of Gensini score, a stepwise downward trend was observed in levels of total and HMW adiponectin and HMW-total adiponectin ratio (P < 0.001). Specifically, total adiponectin of four groups were 1.58 (0.61-4.36) mg/ml, 1.21 (0.70-2.83) mg/ml, 1.00 (0.73-1.88) mg/ml, and 0.76 (0.37-1.19) mg/ml, respectively. Except group A with B and group B with C, the differences of pairwise comparisons among all the other groups were statistically significant (all P < 0.05). HMW adiponectin of four groups were 0.91 (0.39-3.26) mg/ml, 0.55 (0.32-1.49) mg/ml, 0.46 (0.21-0.876) mg/ml, and 0.23 (0.14-0.39) mg/ml, respectively. The differences of pairwise comparisons among all the other groups were statistically significant (all P < 0.05) except group B with C. HMW-total adiponectin ratio of four groups were 0.58 (0.31-0.81), 0.47 (0.26-0.69), 0.41 (0.24-0.57), and 0.36 (0.21-0.42), respectively. The differences of pairwise comparisons among all the other groups were statistically significant (all P < 0.05) except group B with C. In the model of multivariate binary logistic regression analysis, after adjustment for conventional cardiovascular risk factors, HMW adiponectin (OR = 0.234, P < 0.011) and HMW-total adiponectin ratio (OR = 0.138, P < 0.005) remained inversely correlated with the risk of CAD, while no significant association was observed between total adiponectin and CAD

Areas under the ROC curves were compared pairwise to identify the diagnostic power for CAD among total adiponectin, HMW adiponectin, and HMW-total adiponectin ratio. HMW adiponectin and HMW-total adiponectin ratio showed greater capability for identifying CAD than total adiponectin did (0.797 vs. 0.674, 0.806 vs. 0.674; respectively, all P < 0.05); however, no significant difference was observed between HMW and HMW-total ratio (P > 0.05).

Associations between total adiponectin, HMW adiponectin, HMW-total adiponectin ratio and the severity of coronary atherosclerosis

Associations between total adiponectin, HMW adiponectin, HMW-total adiponectin ratio and the severity of coronary atherosclerosis in EOCAD patients (evaluated by Gensini score). *P < 0.05; **P < 0.001; ***P < 0.005 by Mann-Whitney U test.

Compares diagnostic power

Compares diagnostic power

Fig. Compares diagnostic power among total adiponectin, HMW adiponectin and HMW-total adiponectin ratio for CAD by ROC curves. Diagnostic power for CAD was based on discriminating patients with or without coronary atherosclerosis. The area under the curve for HMW-total adiponectin ratio (dotted black line) was larger than that for total adiponectin (fine black line) (0.806 [95%CI 0.708-0.903] vs. 0.674 [95%CI 0.552-0.797], P < 0.05) and HMW adiponectin (bold black line) (0.806 [95%CI 0.708-0.903] vs. 0.797 [95%CI 0.706-0.888], no statistically difference). Sensitivity, specificity and optimal cut off value for them were total adiponectin (57.38%, 75.86%, 1.11 mg/ml), HMW (55.74%, 93.1%, 0.49 mg/ml) and H/T (78.69%, 75.86%, 0.52), respectively.

There are two strengths in our study. One is the precise Gensini scoring system to carefully evaluate stenosis of coronary artery or branches > 0% diameter as coronary lesion, another is the specific study subjects of EOCAD in a Chinese Han population that is particularly genetically determined and not influenced by racial/ethnic disparities. The limitations of our study lie in the interference of medications such as the effect of lipid lowering drugs on the levels of adiponectin, and cardiovascular risk factors. Smoking is a conventional cardiovascular risk factor, whose interaction with HMW adiponectin level is rarely investigated, but it has been revealed to be associated with HMW adiponectin level in men according to the study from Kawamoto R et al. We did not adjust the result for the pack/year variable in the multivariate logistic regression analysis for the limitation of small sample size of male subjects in our study. The relatively small study sample also restrained our conclusion generalizable to all populations. Future researches in larger study samples and different populations are in need to validate our findings, and to explore the association of smoking with adiponectin in male subgroup analysis, and to investigate the potential mechanisms by which adiponectin affects the progression of coronary atherosclerosis.

In summary, the present study has demonstrated that adiponectin is protective against coronary atherosclerosis onset in EOCAD patients. HMW adiponectin and HMW-total adiponectin ratio show stronger negative associations with the severity of coronary atherosclerosis than total adiponectin does. HMW adiponectin and HMW-total adiponectin ratio are more effective biomarkers for the risk of CAD than total adiponectin.

Berberis aristata combined with Silybum marianum on lipid profile in patients not tolerating statins at high doses

Giuseppe Derosa, Davide Romano, Angela D’Angelo, Pamela Maffioli
Atherosclerosis 239 (2015) 87-92
http://dx.doi.org/10.1016/j.atherosclerosis.2014.12.043

Aim: To evaluate the effects of Berberis aristata combined with Silybum marianum in dyslipidemic patients intolerant to statins at high doses.
Methods: 137 euglycemic, dyslipidemic subjects, with previous adverse events to statins at high doses, were enrolled. Statins were stopped for 1 month (run-in), then they were re-introduced at the half of the previously taken dose. At randomization, patients tolerating the half dose of statin, were assigned to
add placebo or B. aristata/S. marianum 588/105 mg, 1 tablet during the lunch and 1 tablet during the dinner, for six months. We evaluated lipid profile and safety parameters variation at randomization, and after 3, and 6 months.
Results: B. aristata/S. marianum reduced fasting plasma glucose (-9 mg/dl), insulin (-0.7 mU/ml), and HOMA-index (-0.35) levels compared to baseline and also to placebo. Lipid profile did not significantly change after 6 months since the reduction of statin dosage and the introduction of B. aristata/S. marianum, while it worsened in the placebo group both compared to placebo and with active treatment (+23.4 mg/dl for total cholesterol, +19.6 mg/dl for LDL-cholesterol, +23.1 mg/dl for triglycerides with placebo compared to B. aristata/S. marianum). We did not record any variations of safety parameters
in either group. Conclusions: B. aristata/S. marianum can be considered as addition to statins in patients not tolerating high dose of these drugs.

Statins, also known as 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase inhibitors, are effective medications for reducing the risk of death and future cardiovascular disease. In the latest years, however, statin intolerance (including adverse effects related to quality of life, leading to decisions to decrease or stop the use of an otherwise-beneficial drug) has come to the forefront of clinical concern, whereas the safety of statins has come to be regarded as largely favorable. Statin intolerance is defined as any adverse symptoms, signs, or laboratory abnormalities attributed by the patient or physician to the statin and in most cases perceived by the patient to interfere unacceptably with activities of daily living, leading to a decision to stop or reduce statin therapy. The physician might also decide to stop or reduce statin therapy on the basis of clinical/laboratory assessment [abnormal liver function tests, creatine phosphokinase values (CPK)] suggesting undue risk. Adverse events are more common at higher doses of statins, and often contribute to patients low adherence to treatment. For this reason, researchers are testing alternative strategies for lipid treatment when statin intolerance is recognized. One strategy to reduce the risk of statin-induced adverse events includes using a low-dose of statin combined with nonstatin drugs in order to achieve the goals of therapy. Nonstatin drugs include nutraceuticals; in the latest years relatively large number of dietary supplements and nutraceuticals have been studied for their supposed or demonstrated ability to reduce cholesterolemia in humans, in particular Berberis Aristata, has been studied in randomized clinical trials and proved to be effective in improving lipid profile. In particular, B. aristata acts up-regulating LDL-receptor (LDL-R) expression independent of sterol regulatory element binding proteins, but dependent on extracellular signal-regulated kinases (ERK) and c-Jun N-terminal kinase (JNK) activation leading to total cholesterol (TC) and LDL-C reduction of about 30 and 25%, respectively. Hwever, B. aristata is a problem in terms of oral bioavailability, affected by a P-glycoprotein (P-gp) mediated gut extrusion process. P-gp seems to reduce by about 90% the amount of B. aristata able to cross the enterocytes, but the use of a potential P-gp inhibitor could ameliorate its oral poor bioavailability improving its effectiveness. Among the potential Pgp inhibitors, silymarin from S. marianum, an herbal drug used as liver protectant, could be considered a good candidate due to its high safety profile.

Analyzing the results of our study, it can appear, at a first glance, that B. aristata/S. marianum has a neutral effect of lipid profile that did not change during the study after the addition of the nutraceutical combination. This lack of effect, however, is only apparent, because, when we analyzed what happens in placebo group, we observed a worsening of lipid profile after statin dose reduction. In other words, the addition of B. aristata/S. marianum neutralized the worsening of lipid profile observed with placebo after statins dose reduction. These results are in line with what was reported by Kong et al., who evaluated the effects of a combination of berberine and simvastatin in sixty-three outpatients diagnosed with hypercholesterolemia. As compared with monotherapies, the combination showed an improved lipid lowering effect with 31.8% reduction of serum LDL-C, and similar efficacies were observed in the reduction of TC as well as Tg in patients. Considering the results of this study, B. aristata/S. marianum can be considered as addition to statins in patients not tolerating high dose of these drugs.

CETP inhibitors downregulate hepatic LDL receptor and PCSK9 expression in vitro and in vivo through a SREBP2 dependent mechanism

Bin Dong, Amar Bahadur Singh, Chin Fung, Kelvin Kan, Jingwen Liu
Atherosclerosis 235 (2014) 449-462
http://dx.doi.org/10.1016/j.atherosclerosis.2014.05.931

Background: CETP inhibitors block the transfer of cholesteryl ester from HDL-C to VLDL-C and LDL-C, thereby raising HDL-C and lowering LDL-C. In this study, we explored the effect of CETP inhibitors on hepatic LDL receptor (LDLR) and PCSK9 expression and further elucidated the underlying regulatory mechanism. Results: We first examined the effect of anacetrapib (ANA) and dalcetrapib (DAL) on LDLR and PCSK9 expression in hepatic cells in vitro. ANA exhibited a dose-dependent inhibition on both LDLR and PCSK9 expression in CETP-positive HepG2 cells and human primary hepatocytes as well as CETP-negative mouse primary hepatocytes (MPH). Moreover, the induction of LDLR protein expression by rosuvastatin in MPH was blunted by cotreatment with ANA. In both HepG2 and MPH ANA treatment reduced the amount of mature form of SREBP2 (SREBP2-M). In vivo, oral administration of ANA to dyslipidemic C57BL/6J mice at a daily dose of 50 mg/kg for 1 week elevated serum total cholesterol by approximately 24.5% (p < 0.05%) and VLDL-C by 70% (p < 0.05%) with concomitant reductions of serum PCSK9 and liver LDLR/SREBP2-M protein. Finally, we examined the in vitro effect of two other strong CETP inhibitors evacetrapib and torcetrapib on LDLR/PCSK9 expression and observed a similar inhibitory effect as ANA in a concentration range of 1-10 µM. Conclusion: Our study revealed an unexpected off-target effect of CETP inhibitors that reduce the mature form of SREBP2, leading to attenuated transcription of hepatic LDLR and PCSK9. This negative regulation of SREBP pathway by ANA manifested in mice where CETP activity was absent and affected serum cholesterol metabolism.

Effect of Eclipta prostrata on lipid metabolism in hyperlipidemic animals

Yun Zhao, Lu Peng, Wei Lu, Yiqing Wang, Xuefeng Huang, et al.
Experimental Gerontology 62 (2015) 37–44
http://dx.doi.org/10.1016/j.exger.2014.12.017

Eclipta prostrata (Linn.) Linn. is a traditional Chinese medicine and has previously been reported to have hypolipidemic effects. However, its mechanism of action is not well understood. This study was conducted to identify the active fraction of Eclipta, its toxicity, its effect on hyperlipidemia, and its mechanism of action. The ethanol extract (EP) of Eclipta and fractions EPF1–EPF4, obtained by eluting with different concentrations of ethanol from a HPD-450 macroporous resin column chromatography of the EP, were screened in hyperlipidemic mice for lipid lowering activity, and EPF3 was the most active fraction. The LD50 of EPF3 was undetectable because no mice died with administration of EPF3 at 10.4 g/kg. Then, 48 male hamsters were used and randomly assigned to normal chow diet, high-fat diet, high-fat diet with Xuezhikang (positive control) or EPF3 (75, 150 and 250 mg/kg) groups. We evaluated the effects of EPF3 on body weight gain, liver weight gain, serum lipid concentration, antioxidant enzyme activity, and the expression of genes involved in lipid metabolism in hyperlipidemic hamsters. The results showed that EPF3 significantly decreased body-weight gain and liver-weight gain and reduced the serum lipid levels in hyperlipidemic hamsters. EPF3 also increased the activities of antioxidant enzymes; upregulated the mRNA expression of peroxisome proliferator-activated receptor α (PPARα), low density lipoprotein receptor (LDLR), lecithin-cholesterol transferase (LCAT) and scavenger receptor class B type Ι receptor (SR-BI); and down-regulated the mRNA expression of 3-hydroxy-3-methyl-glutaryl-CoA reductase (HMGR) in the liver. These results indicate that EPF3 ameliorates hyperlipidemia, in part, by reducing oxidative stress and modulating the transcription of genes involved in lipid metabolism.

Although Eclipta has long been used as a food additive, no studies or reports have clearly shown any liver or kidney toxicity from its use. Therefore, E. prostrata is safe and beneficial for preventing hyperlipidemia in experimental animals and can be used as an alternative medicine for the regulation of dyslipidemia.

Effect of high fiber products on blood lipids and lipoproteins in hamsters

HE Martinez-Floresa, Y Kil Chang, F Martinez-Bustosc, V Sgarbieri
Nutrition Research 24 (2004) 85–93
http://dx.doi.org:/10.1016/S0271-5317(03)00206-9

Serum and liver lipidemic responses in hamsters fed diets containing 2% cholesterol and different dietary fiber sources were studied. The following diets were made from: a) the control diet made from extruded cassava starch (CSH) contained 9.3% cellulose, b) cassava starch extruded with 9.7% resistant starch (CS-RS), c) cassava starch extruded with 9.9% oat fiber (CS-OF), d) the reference diet contained 9.5% cellulose, and no cholesterol was added. Total cholesterol, LDLVLDL-cholesterol and triglycerides were significantly lower (P < 0.05) in serum of hamsters fed on the CS-RS (17.87%, 62.92% and 9.17%, respectively) and CS-OF (15.12%, 67.41% and 18.35%, respectively) diets, as compared to hamster fed with the CSH diet. Similar results were found in the livers of hamsters fed on the CS-RS and CS-OF diets, as compared to hamsters fed with the CSH diet. The diets containing these fibers could be used as active ingredients in human diets to improve the human health.

A new piece in the puzzling effect of n-3 fatty acids on atherosclerosis?

Wilfried Le Goff
Atherosclerosis 235 (2014) 358-362
http://dx.doi.org/10.1016/j.atherosclerosis.2014.03.038

Omega-3 fatty acids (ω-3) FA are reported to be protective against cardiovascular disease (CVD), notably through their beneficial action on atherosclerosis development. In this context dietary intake of long chain marine eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) is recommended and randomised trials largely support that EPA and DHA intake is associated with a reduction of CVD. However, mechanisms governing the atheroprotective action of ω-3 FA are still unclear and numerous studies using mouse models conducted so far do not allow to reach a precise view of the cellular and molecular effects of ω-3 FA on atherosclerosis. In the current issue of Atherosclerosis, Chang et al. provide important new information on the anti-atherogenic properties of ω-3 FA by analyzing the incremental replacement of saturated FA by pure fish oil as a source of EPA and DHA in Ldlr -/- mice fed a high fat/high cholesterol diet.

Cardiovascular disease (CVD) is the leading causes of death in the world and is frequently associated with atherosclerosis, a pathology characterized by the accumulation of lipids, mainly cholesterol in the arterial wall. Among major risk factors for CVD, circulating levels of lipids and more especially those originating from diets are closely linked to development of atherosclerosis. In this context, not only cholesterol, but also dietary fatty acids (FA) may appear particularly deleterious in regards to atherosclerosis and associated CVD. However, although saturated fats are proatherogenic, omega-3 fatty acids (ω-3 FA), and more especially long-chain marine eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), exert atheroprotective properties through several potential underlying mechanisms. Therefore, the intake of EPA and DHA is recommended around the world and randomised trials with ω-3 FA confirmed that EPA and DHA intake reduced risk for CVD events. However benefits of ω-3 FA intake were challenged by recent clinical trials that failed to replicate protective effects of EPA + DHA on CVD, raising the controversy on the healthy side of marine ω-3 FA.

Animal models are commonly employed in order to decipher mechanisms by which ω-3 FA exert their beneficial actions regarding lipid metabolism and atherosclerosis. Since the last past 20 years, mouse models, and more especially genetically modified mouse models, became the reference model to evaluate the effects of dietary fatty acids, especially ω-3 FA, on atherosclerosis development [7-20]. However, the use of different mouse models of atherosclerosis (Apoe-/-, Ldlr-/-, double Apoe-/- x Ldlr-/- , Ldlr-/- x hApoB mice), as well as diet composition (chow, high cholesterol, high fat, high cholesterol/high fat), source of ω-3 FA supplementation (fish oil, perilla seed oil, flaxseed, pure ALA, EPA or DHA), duration of the diet (from 4 to 32 weeks), size of atherosclerotic lesions in control animals (from 51 to 700.103 mm2) in

those studies led to heterogeneous results and therefore to a partial understanding of the effects of ω-3 FA on atherosclerosis.

Contrary to what observed in Apoe-/- mice, dietary supplementation of Ldlr-/- mice with ω-3 FA led to a reproducible reduction of aortic atherosclerosis, although to various degrees, confirming that Ldlr-/- mice constitute the most appropriate model for studying the atheroprotective effects of ω-3 FA. When evaluated, the decrease of atherosclerosis upon ω-3 FA-rich diet was accompanied by a reduction in the macrophage content as well as inflammation in aortic lesions highlighting the major impact of ω-3 FA on monocyte recruitment and subsequent macrophage accumulation in the arterial wall. However, although supplementation with ω-3 FA allows an efficacious lowering of plasma lipid levels in humans, studies in mouse models suggest that the antiatherogenic action of ω-3 FA is independent of any effects on plasma cholesterol or triglyceride levels. However, that must be asserted with caution as lipid metabolism is quite different in mouse in comparison to humans, highlighting the need to study in the future the effects of ω-3 FA on atherosclerosis in a mouse model exhibiting a more “humanized” lipid metabolism as achieved in hApoB/CETP mice.

In a previous issue of Atherosclerosis, Chang et al. reevaluate the impact of fish oil ω-3 FA on atherosclerosis development by operating an incremental replacement of saturated fats (SAT) by ω-3 FA (pure fish oil, EPA- and DHA-rich) in Ldlr-/- mice fed a high-fat (21%, w/w)/high-cholesterol (0.2%, w/w) diet for a 12-week period. This experimental approach is quite pertinent as dietary fat intake in developed countries, as in United States, derived mostly from saturated FA and is poor in ω-3 FA. Then, using this strategy the authors were able to evaluate the potential beneficial effects of a supplementation with fish oil ω-3 FA in a dietary context for which ω-3 FA intake is relevant.

Here, Chang et al. demonstrated that the progressive increase of dietary intake of fish oil ω-3 FA (EPA and DHA) abrogated the deleterious effects of a SAT diet, thereby suggesting that a dietary ω-3 FA intake on a SAT background is potentially efficient to decrease CVD in humans. Indeed, replacement of SAT by fish oil ω-3 FA markedly reduced plasma cholesterol and triglycerides levels and abolished diet-induced atherosclerosis mediated by SAT in Ldlr-/-mice. To note that in the present study, Ldlr-/- mice only developed small atherosclerosic lesions (~100.103 mm2) after 12 weeks of diet with SAT.

As previously reported, decreased atherosclerotic lesions were accompanied by a reduced content of aortic macrophages and inflammation. Based on their previous works, the authors proposed that the reduction of atherosclerosis upon ω-3 FA resulted from an impairment of cholesterol uptake by arterial macrophages consecutive to the decrease of Lipoprotein Lipase (LPL) expression in those cells. Indeed, beyond its lipolysis action on triglycerides, LPL was reported to promote lipid accumulation, in particular in macrophages, by binding to lipoproteins and cell surface proteoglycans and then acting as a bridging molecule that facilitates cellular lipid uptake. Coherent with this mechanism, macrophage LPL expression was reported to promote foam cell formation and atherosclerosis. In the present study, replacement of SAT by ω-3 FA both decreased expression and altered distribution of arterial LPL. Such a mechanism for ω-3 FA (EPA and DHA) was proposed by this group in earlier studies to favor reduction of arterial LDL-cholesterol. It is noteworthy that lipid rafts alter distribution of LPL at the cell surface and subsequently the LPL dependent accumulation of lipids in macrophages and foam cell formation. As incorporation of ω-3 FA, such as DHA, into cell membrane phospholipids disrupts lipid rafts organization, it cannot be exclude that reduction of lipid accumulation in arterial macrophages upon addition of ω-3 FA results in part from an impairment of the localization and of the anchoring function of LPL at the cell surface of macrophages. Indeed Chang et al. observed that progressive replacement of SAT by ω-3 FA affected aortic FA composition leading to a pronounced increase of arterial EPA and DHA, then suggesting that content of ω-3 FA in macrophage membrane may be equally altered. However, the implication of LPL in the atheroprotective effects of ω-3 FA need to be validated using an appropriate mouse model for which LPL expression may be controlled.

Among the various mechanisms by which ω-3 FA exert anti-inflammatory properties, EPA and DHA repressed inflammation by shutting down NF-kB activation in macrophages. Since expression of TLR-4 and NF-kB target genes, IL-6 and TNFα, in aorta from mice fed diets containing ω-3 FA were decreased when compared to SAT, those results strongly support the contention that ω-3 FA repress inflammation by inhibiting the TLR4/NF-kB signaling cascade likely through the macrophage ω-3 FA receptor GPR120.

Although further studies are needed to explore the complete spectrum of actions of ω-3 FA on atherosclerosis development and CVD, this study provides important information that supports that ω-3 FA intake is a pertinent strategy to reduce risk of CVD.

Effects of dietary hull-less barley β-glucan on the cholesterol metabolism of hypercholesterolemic hamsters

Li-Tao Tong, Kui Zhong, Liya Liu, Xianrong Zhou, Ju Qiu, Sumei Zhou
Food Chemistry 169 (2015) 344–349
http://dx.doi.org/10.1016/j.foodchem.2014.07.157

The aim of the present study is to investigate the hypocholesterolemic effects of dietary hull-less barley β-glucan (HBG) on cholesterol metabolism in hamsters which were fed a hypercholesterolemic diet. The hamsters were divided into 3 groups and fed experimental diets, containing 5‰ HBG or 5‰ oat β-glucan (OG), for 30 days. The HBG, as well as OG, lowered the concentration of plasma LDL-cholesterol significantly. The excretion of total lipids and cholesterol in feces were increased in HBG and OG groups compared with the control group. The activity of 3-hydroxy-3-methyl glutaryl-coenzyme A (HMG-CoA) reductase in liver was reduced significantly in the HBG group compared with the control and OG groups. The activity of cholesterol 7-α hydroxylase (CYP7A1) in the liver, in the HBG and OG groups, was significantly increased compared with the control group. The concentrations of acetate, propionate and total short chain fatty acids (SCFAs) were not significantly different between the HBG and control groups. These results indicate that dietary HBG reduces the concentration of plasma LDL cholesterol by promoting the excretion of fecal lipids, and regulating the activities of HMG-CoA reductase and CYP7A1 in hypercholesterolemic hamsters.

Effects of dietary wheat bran arabinoxylans on cholesterolmetabolism of hypercholesterolemic hamsters

Li-Tao Tong, Kui Zhong, Liya Liu, Ju Qiu, Lina Guo, et al.
Carbohydrate Polymers 112 (2014) 1–5
http://dx.doi.org/10.1016/j.carbpol.2014.05.061

The aim of the present study is to investigate the effects of dietary wheat bran arabinoxylans (AXs) on cholesterol metabolism in hypercholesterolemic hamsters. The hamsters were divided into 3 groups and fed the experimental diets containing AXs or oat β-glucan at a dose of 5 g/kg for 30 days. As the results,the AXs lowered plasma total cholesterol and LDL-cholesterol concentrations, and increased excretions of total lipids, cholesterol and bile acids, as well as oat β-glucan. The AXs reduced the activity of 3-hydroxy-3-methyl glutaryl-coenzyme A (HMG-CoA) reductase, and increased the activity of cholesterol 7-α hydroxylase (CYP7A1) in liver. Moreover, the AXs increased propionate and the total short-chain fatty acids (SCFAs) concentrations. These results indicated that dietary AXs reduced the plasma total cholesterol and LDL-cholesterol concentrations by promoting the excretion of fecal lipids, regulating the activities of HMG-CoA reductase and CYP7A1, and increasing colonic SCFAs in hamsters.

High-fructose feeding promotes accelerated degradation of hepatic LDL receptor and hypercholesterolemia in hamsters via elevated circulating PCSK9 levels

Bin Dong, Amar Bahadur Singh, Salman Azhar, Nabil G. Seidah, Jingwen Liu
Atherosclerosis 239 (2015) 364-374
http://dx.doi.org/10.1016/j.atherosclerosis.2015.01.013

Background: High fructose diet (HFD) induces dyslipidemia and insulin resistance in experimental animals and humans with incomplete mechanistic understanding. By utilizing mice and hamsters as in vivo models, we investigated whether high fructose consumption affects serum PCSK9 and liver LDL receptor (LDLR) protein levels. Results: Feeding mice with an HFD increased serum cholesterol and reduced serum PCSK9 levels as compared with the mice fed a normal chow diet (NCD). In contrast to the inverse relationship in mice, serum PCSK9 and cholesterol levels were co-elevated in HFD-fed hamsters. Liver tissue analysis revealed that PCSK9 mRNA and protein levels were both reduced in mice and hamsters by HFD feeding, however, liver LDLR protein levels were markedly reduced by HFD in hamsters but not in mice. We further showed that circulating PCSK9 clearance rates were significantly lower in hamsters fed an HFD as compared with the hamsters fed NCD, providing additional evidence for the reduced hepatic LDLR function by HFD consumption. The majority of PCSK9 in hamster serum was detected as a 53 kDa N-terminus cleaved protein. By conducting in vitro studies, we demonstrate that this 53 kDa truncated hamster PCSK9 is functionally active in promoting hepatic LDLR degradation. Conclusion: Our studies for the first time demonstrate that high fructose consumption increases serum PCSK9 concentrations and reduces liver LDLR protein levels in hyper-lipidemic hamsters. The positive correlation between circulating cholesterol and PCSK9 and the reduction of liver LDLR protein in HFD-fed hamsters suggest that hamster is a better animal model than mouse to study the modulation of PCSK9/LDLR pathway by atherogenic diets.

High-oleic canola oil consumption enriches LDL particle cholesteryl oleate content and reduces LDL proteoglycan binding in humans

Peter J.H. Jones, Dylan S. MacKay, Vijitha K. Senanayake, Shuaihua Pu, et al.
Atherosclerosis 238 (2015) 231-238
http://dx.doi.org/10.1016/j.atherosclerosis.2014.12.010

Oleic acid consumption is considered cardio-protective according to studies conducted examining effects of the Mediterranean diet. However, animal models have shown that oleic acid consumption increases LDL particle cholesteryl oleate content which is associated with increased LDL-proteoglycan binding and atherosclerosis. The objective was to examine effects of varying oleic, linoleic and docosahexaenoic acid consumption on human LDL-proteoglycan binding in a non-random subset of the Canola Oil Multi-center Intervention Trial (COMIT) participants. COMIT employed a randomized, double-blind, five-period, crossover trial design. Three of the treatment oil diets: 1) a blend of corn/safflower oil (25:75); 2) high oleic canola oil; and 3) DHA-enriched high oleic canola oil were selected for analysis of LDL-proteoglycan binding in 50 participants exhibiting good compliance. LDL particles were isolated from frozen plasma by gel filtration chromatography and LDL cholesteryl esters quantified by mass-spectrometry. LDL-proteoglycan binding was assessed using surface plasmon resonance. LDL particle cholesterol ester fatty acid composition was sensitive to the treatment fatty acid compositions, with the main fatty acids in the treatments increasing in the LDL cholesterol esters. The corn/safflower oil and high-oleic canola oil diets lowered LDL-proteoglycan binding relative to their baseline values (p < 0.0005 and p < 0.0012, respectively). At endpoint, high-oleic canola oil feeding resulted in lower LDL-proteoglycan binding than corn/safflower oil (p < 0.0243) and DHA-enriched high oleic canola oil (p < 0.0249), although high-oleic canola oil had the lowest binding at baseline (p < 0.0344). Our findings suggest that high-oleic canola oil consumption in humans increases cholesteryl oleate percentage in LDL, but in a manner not associated with a rise in LDL-proteoglycan binding.

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