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Posts Tagged ‘fumarate’


Warburg Effect and Mitochondrial Regulation -2.1.3

Writer and Curator: Larry H Bernstein, MD, FCAP 

2.1.3 Warburg Effect and Mitochondrial Regulation

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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Refined Warburg hypothesis -2.1.2

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

Refined Warburg Hypothesis -2.1.2

The Warburg discoveries from 1922 on, and the influence on metabolic studies for the next 50 years was immense, and then the revelations of the genetic code took precedence.  Throughout this period, however, the brilliant work of Briton Chance, a giant of biochemistry at the University of Pennsylvania, opened new avenues of exploration that led to a recent resurgence in this vital need for answers in cancer research. The next two series of presentations will open up this resurgence of fundamental metabolic research in cancer and even neurodegenerative diseases.

2.1.2.1 Cancer Cell Metabolism. Warburg and Beyond

Hsu PP, Sabatini DM
Cell, Sep 5, 2008; 134:703-707
http://dx.doi.org:/10.016/j.cell.2008.08.021

Described decades ago, the Warburg effect of aerobic glycolysis is a key metabolic hallmark of cancer, yet its significance remains unclear. In this Essay, we re-examine the Warburg effect and establish a framework for understanding its contribution to the altered metabolism of cancer cells.

It is hard to begin a discussion of cancer cell metabolism without first mentioning Otto Warburg. A pioneer in the study of respiration, Warburg made a striking discovery in the 1920s. He found that, even in the presence of ample oxygen, cancer cells prefer to metabolize glucose by glycolysis, a seeming paradox as glycolysis, when compared to oxidative phosphorylation, is a less efficient pathway for producing ATP (Warburg, 1956). The Warburg effect has since been demonstrated in different types of tumors and the concomitant increase in glucose uptake has been exploited clinically for the detection of tumors by fluorodeoxyglucose positron emission tomography (FDG-PET). Although aerobic glycolysis has now been generally accepted as a metabolic hallmark of cancer, its causal relationship with cancer progression is still unclear. In this Essay, we discuss the possible drivers, advantages, and potential liabilities of the altered metabolism of cancer cells (Figure 1). Although our emphasis on the Warburg effect reflects the focus of the field, we would also like to encourage a broader approach to the study of cancer metabolism that takes into account the contributions of all interconnected small molecule pathways of the cell.

Figure 1. The Altered Metabolism of Cancer Cells

Drivers (A and B). The metabolic derangements in cancer cells may arise either from the selection of cells that have adapted to the tumor microenvironment or from aberrant signaling due to oncogene activation. The tumor microenvironment is spatially and temporally heterogeneous, containing regions of low oxygen and low pH (purple). Moreover, many canonical cancer-associated signaling pathways induce metabolic reprogramming. Target genes activated by hypoxia inducible factor (HIF) decrease the dependence of the cell on oxygen, whereas Ras, Myc, and Akt can also upregulate glucose consumption and glycolysis. Loss of p53 may also recapitulate the features of the Warburg effect, that is, the uncoupling of glycolysis from oxygen levels. Advantages (C–E). The altered metabolism of cancer cells is likely to imbue them with several proliferative and survival advantages, such as enabling cancer cells to execute the biosynthesis of macromolecules (C), to avoid apoptosis (D), and to engage in local metabolite-based paracrine and autocrine signaling (E). Potential Liabilities (F and G). This altered metabolism, however, may also confer several vulnerabilities on cancer cells. For example, an upregulated metabolism may result in the build up of toxic metabolites, including lactate and noncanonical nucleotides, which must be disposed of (F). Moreover, cancer cells may also exhibit a high energetic demand, for which they must either increase flux through normal ATP-generating processes, or else rely on an increased diversity of fuel sources (G).

The Tumor Microenvironment Selects for Altered Metabolism

One compelling idea to explain the Warburg effect is that the altered metabolism of cancer cells confers a selective advantage for survival and proliferation in the unique tumor microenvironment. As the early tumor expands, it outgrows the diffusion limits of its local blood supply, leading to hypoxia and stabilization of the hypoxia-inducible transcription factor, HIF. HIF initiates a transcriptional program that provides multiple solutions to hypoxic stress (reviewed in Kaelin and Ratcliffe, 2008). Because a decreased dependence on aerobic respiration becomes advantageous, cell metabolism is shifted toward glycolysis by the increased expression of glycolytic enzymes, glucose transporters, and inhibitors of mitochondrial metabolism. In addition, HIF stimulates angiogenesis (the formation of new blood vessels) by upregulating several factors, including most prominently vascular endothelial growth factor (VEGF).

The oxygen levels within a tumor vary both spatially and temporally, and the resulting rounds of fluctuating oxygen levels potentially select for tumors that constitutively upregulate glycolysis. Interestingly, with the possible exception of tumors that have lost the von Hippel-Lindau protein (VHL), which normally mediates degradation of HIF, HIF is still coupled to oxygen levels, as evident from the heterogeneity of HIF expression within the tumor microenvironment (Wiesener et al., 2001; Zhong et al., 1999). Therefore, the Warburg effect—that is, an uncoupling of glycolysis from oxygen levels—cannot be explained solely by upregulation of HIF.

Recent work has demonstrated that the key components of the Warburg effect—increased glucose consumption, decreased oxidative phosphorylation, and accompanying lactate production—are also distinguishing features of oncogene activation. The signaling molecule Ras, a powerful oncogene when mutated, promotes glycolysis (reviewed in Dang and Semenza, 1999; Samanathan et al., 2005). Akt kinase, a well-characterized downstream effector of insulin signaling, reprises its role in glucose uptake and utilization in the cancer setting (reviewed in Manning and Cantley, 2007), whereas the Myc transcription factor upregulates the expression of various metabolic genes (reviewed in Gordan et al., 2007). The most parsimonious route to tumorigenesis may be activation of key oncogenic nodes that execute a proliferative program, of which metabolism may be one important arm. Moreover, regulation of metabolism is not exclusive to oncogenes. Loss of the tumor suppressor protein p53 prevents expression of the gene encoding SCO2 (the synthesis of cytochrome c oxidase protein), which interferes with the function of the mitochondrial respiratory chain (Matoba et al., 2006). A second p53 effector, TIGAR (TP53-induced glycolysis and apoptosis regulator), inhibits glycolysis by decreasing levels of fructose-2,6-bisphosphate, a potent stimulator of glycolysis and inhibitor of gluconeogenesis (Bensaad et al., 2006). Other work also suggests that p53-mediated regulation of glucose metabolism may be dependent on the transcription factor NF-κB (Kawauchi et al., 2008).
It has been shown that inhibition of lactate dehydrogenase A (LDH-A) prevents the Warburg effect and forces cancer cells to revert to oxidative phosphorylation in order to reoxidize NADH and produce ATP (Fantin et al., 2006; Shim et al., 1997). While the cells are respiratory competent, they exhibit attenuated tumor growth, suggesting that aerobic glycolysis might be essential for cancer progression. In a primary fibroblast cell culture model of stepwise malignant transformation through overexpression of telomerase, large and small T antigen, and the H-Ras oncogene, increasing tumorigenicity correlates with sensitivity to glycolytic inhibition. This finding suggests that the Warburg effect might be inherent to the molecular events of transformation (Ramanathan et al., 2005). However, the introduction of similar defined factors into human mesenchymal stem cells (MSCs) revealed that transformation can be associated with increased dependence on oxidative phosphorylation (Funes et al., 2007). Interestingly, when introduced in vivo these transformed MSCs do upregulate glycolytic genes, an effect that is reversed when the cells are explanted and cultured under normoxic conditions. These contrasting models suggest that the Warburg effect may be context dependent, in some cases driven by genetic changes and in others by the demands of the microenvironment. Regardless of whether the tumor microenvironment or oncogene activation plays a more important role in driving the development of a distinct cancer metabolism, it is likely that the resulting alterations confer adaptive, proliferative, and survival advantages on the cancer cell.

Altered Metabolism Provides Substrates for Biosynthetic Pathways

Although studies in cancer metabolism have largely been energy-centric, rapidly dividing cells have diverse requirements. Proliferating cells require not only ATP but also nucleotides, fatty acids, membrane lipids, and proteins, and a reprogrammed metabolism may serve to support synthesis of macromolecules. Recent studies have shown that several steps in lipid synthesis are required for and may even actively promote tumorigenesis. Inhibition of ATP citrate lyase, the distal enzyme that converts mitochondrial-derived citrate into cytosolic acetyl coenzyme A, the precursor for many lipid species, prevents cancer cell proliferation and tumor growth (Hatzivassiliou et al., 2005). Fatty acid synthase, expressed at low levels in normal tissues, is upregulated in cancer and may also be required for tumorigenesis (reviewed in Menendez and Lupu, 2007). Furthermore, cancer cells may also enhance their biosynthetic capabilities by expressing a tumor-specific form of pyruvate kinase (PK), M2-PK. Pyruvate kinase catalyzes the third irreversible reaction of glycolysis, the conversion of phosphoenolpyruvate (PEP) to pyruvate. Surprisingly, the M2-PK of cancer cells is thought to be less active in the conversion of PEP to pyruvate and thus less efficient at ATP production (reviewed in Mazurek et al., 2005). A major advantage to the cancer cell, however, is that the glycolytic intermediates upstream of PEP might be shunted into synthetic processes.

Biosynthesis, in addition to causing an inherent increase in ATP demand in order to execute synthetic reactions, should also cause a decrease in ATP supply as various glycolytic and Krebs cycle intermediates are diverted. Lipid synthesis, for example, requires the cooperation of glycolysis, the Krebs cycle, and the pentose phosphate shunt. As pyruvate must enter the mitochondria in this case, it avoids conversion to lactate and therefore cannot contribute to glycolysis-derived ATP. Moreover, whereas increased biosynthesis may explain the glucose hunger of cancer cells, it cannot explain the increase in lactic acid production originally described by Warburg, suggesting that lactate must also result from the metabolism of non-glucose substrates. Recently, it has been demonstrated that glutamine may be metabolized by the citric acid cycle in cancer cells and converted into lactate, producing NADPH for lipid biosynthesis and oxaloacetate for replenishment of Krebs cycle intermediates (DeBerardinis et al., 2007).

Metabolic Pathways Regulate Apoptosis

In addition to involvement in proliferation, altered metabolism may promote another cancer-essential function: the avoidance of apoptosis. Loss of the p53 target TIGAR sensitizes cancer cells to apoptosis, most likely by causing an increase in reactive oxygen species (Bensaad et al., 2006). On the other hand, overexpression of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) prevents caspase-independent cell death, presumably by stimulating glycolysis, increasing cellular ATP levels, and promoting autophagy (Colell et al., 2007). Whether or not GAPDH plays a physiological role in the regulation of cell death remains to be determined. Intriguingly, Bonnet et al. (2007) have reported that treating cancer cells with dichloroacetate (DCA), a small molecule inhibitor of pyruvate dehydrogenase kinase, has striking effects on their survival and on xenograft tumor growth.

DCA, a currently approved treatment for congenital lactic acidosis, activates oxidative phosphorylation and promotes apoptosis by two mechanisms. First, increased flux through the electron transport chain causes depolarization of the mitochondrial membrane potential (which the authors found to be hyperpolarized specifically in cancer cells) and release of the apoptotic effector cytochrome c. Second, an increase in reactive oxygen species generated by oxidative phosphorylation upregulates the voltage-gated K+ channel, leading to potassium ion efflux and caspase activation. Their work suggests that cancer cells may shift their metabolism to glycolysis in order to prevent cell death and that forcing cancer cells to respire aerobically can counteract this adaptation.

Cancer Cells May Signal Locally in the Tumor Microenvironment

Cancer cells may rewire metabolic pathways to exploit the tumor microenvironment and to support cancer-specific signaling. Without access to the central circulation, it is possible that metabolites can be concentrated locally and reach suprasystemic levels, allowing cancer cells to engage in metabolite-mediated autocrine and paracrine signaling that does not occur in normal tissues. So called androgen-independent prostate cancers may only be independent from exogenous, adrenal-synthesized androgens. Androgen-independent prostate cancer cells still express the androgen receptor and may be capable of autonomously synthesizing their own androgens (Stanbrough et al., 2006).

Metabolism as an Upstream Modulator of Signaling Pathways

Not only is metabolism downstream of oncogenic pathways, but an altered upstream metabolism may affect the activity of signaling pathways that normally sense the state of the cell. Individuals with inherited mutations in succinate dehydrogenase and fumarate hydratase develop highly angiogenic tumors, not unlike those exhibiting loss of the VHL tumor suppressor protein that acts upstream of HIF (reviewed in Kaelin and Ratcliffe, 2008). The mechanism of tumorigenesis in these cancer syndromes is still contentious. However, it has been proposed that loss of succinate dehydrogenase and fumarate hydratase causes an accumulation of succinate or fumarate, respectively, leading to inhibition of the prolyl hydroxylases that mark HIF for VHL-mediated degradation (Isaacs et al., 2005; Pollard et al., 2005; Selak et al., 2005). In this rare case, succinate dehydrogenase and fumarate hydratase are acting as bona fide tumor suppressors.

There are many complex questions to be answered: Is it possible that cancer cells exhibit “metabolite addiction”? Are there unique cancer-specific metabolic pathways, or combinations of pathways, utilized by the cancer cell but not by normal cells? Are different stages of metabolic adaptations required for the cancer cell to progress from the primary tumor stage to invasion to metastasis? How malleable is cancer metabolism?

2.1.2.2 Cancer metabolism. The Warburg effect today

Ferreira LMR
Exp Molec Pathol 2010; 89:372-383.
http://dx.doi.org/10.1016/j.yexmp.2010.08.006

One of the first studies on the energy metabolism of a tumor was carried out, in 1922, in the laboratory of Otto Warburg. He established that cancer cells exhibited a specific metabolic pattern, characterized by a shift from respiration to fermentation, which has been later named the Warburg effect. Considerable work has been done since then, deepening our understanding of the process, with consequences for diagnosis and therapy. This review presents facts and perspectives on the Warburg effect for the 21st century.

Research highlights

► Warburg first established a tumor metabolic pattern in the 1920s. ► Tumors’ increased glucose uptake has been studied since then. ► Cancer bioenergetics’ study provides insights in all its hallmarks. ► New cancer diagnostic and therapeutic techniques focus on cancer metabolism.

Introduction
Contestation to Warburg’s ideas
Glucose’s uptake and intracellular fates
Lactate production and induced acidosis
Hypoxia
Impairment of mitochondrial function
Tumour microenvironment
Proliferating versus cancer cells
More on cancer bioenergetics – integration of metabolism
Perspectives

2.1.2.3 New aspects of the Warburg effect in cancer cell biology

Bensinger SJ, Cristofk HR
Sem Cell Dev Biol 2012; 23:352-361
http://dx.doi.org:/10.1016/j.semcdb.2012.02.003

Altered cellular metabolism is a defining feature of cancer [1]. The best studied metabolic phenotype of cancer is aerobic glycolysis–also known as the Warburg effect–characterized by increased metabolism of glucose to lactate in the presence of sufficient oxygen. Interest in the Warburg effect has escalated in recent years due to the proven utility of FDG-PET for imaging tumors in cancer patients and growing evidence that mutations in oncogenes and tumor suppressor genes directly impact metabolism. The goals of this review are to provide an organized snapshot of the current understanding of regulatory mechanisms important for Warburg effect and its role in tumor biology. Since several reviews have covered aspects of this topic in recent years, we focus on newest contributions to the field and reference other reviews where appropriate.

Highlights

► This review discusses regulatory mechanisms that contribute to the Warburg effect in cancer. ► We list cancers for which FDG-PET has established applications as well as those cancers for which FDG-PET has not been established. ► PKM2 is highlighted as an important integrator of diverse cellular stimuli to modulate metabolic flux and cancer cell proliferation. ► We discuss how cancer metabolism can directly influence gene expression programs. ► Contribution of aerobic glycolysis to the cancer microenvironment and chemotherapeutic resistance/susceptibility is also discussed.

Regulation of the Warburg effect

PKM2 integrates diverse signals to modulate metabolic flux and cell proliferation

PKM2 integrates diverse signals to modulate metabolic flux and cell proliferation

Fig. 1. PKM2 integrates diverse signals to modulate metabolic flux and cell proliferation

Metabolism can directly influence gene expression programs

Metabolism can directly influence gene expression programs

Fig. 2. Metabolism can directly influence gene expression programs. A schematic representation of how metabolism can intrinsically influence epigenetics resulting in durable and heritable gene expression programs in progeny.

2.1.2.4 Choosing between glycolysis and oxidative phosphorylation. A tumor’s dilemma

Jose C, Ballance N, Rossignal R
Biochim Biophys Acta 201; 1807(6): 552-561.
http://dx.doi.org/10.1016/j.bbabio.2010.10.012

A considerable amount of knowledge has been produced during the last five years on the bioenergetics of cancer cells, leading to a better understanding of the regulation of energy metabolism during oncogenesis, or in adverse conditions of energy substrate intermittent deprivation. The general enhancement of the glycolytic machinery in various cancer cell lines is well described and recent analyses give a better view of the changes in mitochondrial oxidative phosphorylation during oncogenesis. While some studies demonstrate a reduction of oxidative phosphorylation (OXPHOS) capacity in different types of cancer cells, other investigations revealed contradictory modifications with the upregulation of OXPHOS components and a larger dependency of cancer cells on oxidative energy substrates for anabolism and energy production. This apparent conflictual picture is explained by differences in tumor size, hypoxia, and the sequence of oncogenes activated. The role of p53, C-MYC, Oct and RAS on the control of mitochondrial respiration and glutamine utilization has been explained recently on artificial models of tumorigenesis. Likewise, the generation of induced pluripotent stem cells from oncogene activation also showed the role of C-MYC and Oct in the regulation of mitochondrial biogenesis and ROS generation. In this review article we put emphasis on the description of various bioenergetic types of tumors, from exclusively glycolytic to mainly OXPHOS, and the modulation of both the metabolic apparatus and the modalities of energy substrate utilization according to tumor stage, serial oncogene activation and associated or not fluctuating microenvironmental substrate conditions. We conclude on the importance of a dynamic view of tumor bioenergetics.

Research Highlights

►The bioenergetics of cancer cells differs from normals. ►Warburg hypothesis is not verified in tumors using mitochondria to synthesize ATP. ►Different oncogenes can either switch on or switch off OXPHOS. ►Bioenergetic profiling is a prerequisite to metabolic therapy. ►Aerobic glycolysis and OXPHOS cooperate during cancer progression.

  1. Cancer cell variable bioenergetics

Cancer cells exhibit profound genetic, bioenergetic and histological differences as compared to their non-transformed counterpart. All these modifications are associated with unlimited cell growth, inhibition of apoptosis and intense anabolism. Transformation from a normal cell to a malignant cancer cell is a multi-step pathogenic process which includes a permanent interaction between cancer gene activation (oncogenes and/or tumor-suppressor genes), metabolic reprogramming and tumor-induced changes in microenvironment. As for the individual genetic mapping of human tumors, their metabolic characterization (metabolic–bioenergetic profiling) has evidenced a cancer cell-type bioenergetic signature which depends on the history of the tumor, as composed by the sequence of oncogenes activated and the confrontation to intermittent changes in oxygen, glucose and amino-acid delivery.

In the last decade, bioenergetic studies have highlighted the variability among cancer types and even inside a cancer type as regards to the mechanisms and the substrates preferentially used for deriving the vital energy. The more popular metabolic remodeling described in tumor cells is an increase in glucose uptake, the enhancement of glycolytic capacity and a high lactate production, along with the absence of respiration despite the presence of high oxygen concentration (Warburg effect) [1]. To explain this abnormal bioenergetic phenotype pioneering hypotheses proposed the impairment of mitochondrial function in rapidly growing cancer cells [2].

Although the increased consumption of glucose by tumor cells was confirmed in vivo by positron emission tomography (PET) using the glucose analog 2-(18F)-fluoro-2-deoxy-d-glucose (FDG), the actual utilization of glycolysis and oxidative phosphorylation (OXPHOS) cannot be evaluated with this technique. Nowadays, Warburg’s “aerobic-glycolysis” hypothesis has been challenged by a growing number of studies showing that mitochondria in tumor cells are not inactive per se but operate at low capacity [3] or, in striking contrast, supply most of the ATP to the cancer cells [4]. Intense glycolysis is effectively not observed in all tumor types. Indeed not all cancer cells grow fast and intense anabolism is not mandatory for all cancer cells. Rapidly growing tumor cells rely more on glycolysis than slowly growing tumor cells. This is why a treatment with bromopyruvate, for example is very efficient only on rapidly growing cells and barely useful to decrease the growth rate of tumor cells when their normal proliferation is slow. Already in 1979, Reitzer and colleagues published an article entitled “Evidence that glutamine, not sugar, is the major energy source for cultured Hela cells”, which demonstrated that oxidative phosphorylation was used preferentially to produce ATP in cervical carcinoma cells [5]. Griguer et al. also identified several glioma cell lines that were highly dependent on mitochondrial OXPHOS pathway to produce ATP [6]. Furthermore, a subclass of glioma cells which utilize glycolysis preferentially (i.e., glycolytic gliomas) can also switch from aerobic glycolysis to OXPHOS under limiting glucose conditions  [7] and [8], as observed in cervical cancer cells, breast carcinoma cells, hepatoma cells and pancreatic cancer cells [9][10] and [11]. This flexibility shows the interplay between glycolysis and OXPHOS to adapt the mechanisms of energy production to microenvironmental changes as well as differences in tumor energy needs or biosynthetic activity. Herst and Berridge also demonstrated that a variety of human and mouse leukemic and tumor cell lines (HL60, HeLa, 143B, and U937) utilize mitochondrial respiration to support their growth [12]. Recently, the measurement of OXPHOS contribution to the cellular ATP supply revealed that mitochondria generate 79% of the cellular ATP in HeLa cells, and that upon hypoxia this contribution is reduced to 30% [4]. Again, metabolic flexibility is used to survive under hypoxia. All these studies demonstrate that mitochondria are efficient to synthesize ATP in a large variety of cancer cells, as reviewed by Moreno-Sanchez [13]. Despite the observed reduction of the mitochondrial content in tumors [3][14][15][16][17][18] and [19], cancer cells maintain a significant level of OXPHOS capacity to rapidly switch from glycolysis to OXPHOS during carcinogenesis. This switch is also observed at the level of glutamine oxidation which can occur through two modes, “OXPHOS-linked” or “anoxic”, allowing to derive energy from glutamine or serine regardless of hypoxia or respiratory chain reduced activity [20].
While glutamine, glycine, alanine, glutamate, and proline are typically oxidized in normal and tumor mitochondria, alternative substrate oxidations may also contribute to ATP supply by OXPHOS. Those include for instance the oxidation of fatty-acids, ketone bodies, short-chain carboxylic acids, propionate, acetate and butyrate (as recently reviewed in [21]).

  1. Varying degree of mitochondrial utilization during tumorigenesis

In vivo metabolomic analyses suggest the existence of a continuum of bioenergetic remodeling in rat tumors according to tumor size and its rate of growth [22]. Peter Vaupel’s group showed that small tumors were characterized by a low conversion of glucose to lactate whereas the conversion of glutamine to lactate was high. In medium sized tumors the flow of glucose to lactate as well as oxygen utilization was increased whereas glutamine and serine consumption were reduced. At this stage tumor cells started with glutamate and alanine production. Large tumors were characterized by a low oxygen and glucose supply but a high glucose and oxygen utilization rate. The conversion of glucose to glycine, alanine, glutamate, glutamine, and proline reached high values and the amino acids were released [22]. Certainly, in the inner layers constituting solid tumors, substrate and oxygen limitation is frequently observed. Experimental studies tried to reproduce these conditions in vitro and revealed that nutrients and oxygen limitation does not affect OXPHOS and cellular ATP levels in human cervix tumor [23]. Furthermore, the growth of HeLa cells, HepG2 cells and HTB126 (breast cancer) in aglycemia and/or hypoxia even triggered a compensatory increase in OXPHOS capacity, as discussed above. Yet, the impact of hypoxia might be variable depending on cell type and both the extent and the duration of oxygen limitation.
In two models of sequential oncogenesis, the successive activation of specific oncogenes in non-cancer cells evidenced the need for active OXPHOS to pursue tumorigenesis. Funes et al. showed that the transformation of human mesenchymal stem cells increases their dependency on OXPHOS for energy production [24], while Ferbeyre et al. showed that cells expressing oncogenic RAS display an increase in mitochondrial mass, mitochondrial DNA, and mitochondrial production of reactive oxygen species (ROS) prior to the senescent cell cycle arrest [25]. Such observations suggest that waves of gene regulation could suppress and then restore OXPHOS in cancer cells during tumorigenesis [20]. Therefore, the definition of cancer by Hanahan and Weinberg [26] restricted to six hallmarks (1—self-sufficiency in growth signals, 2—insensitivity to growth-inhibitory (antigrowth) signals, 3—evasion of programmed cell death (apoptosis), 4—limitless replicative potential, 5—sustained angiogenesis, and 6—tissue invasion and metastases) should also include metabolic reprogramming, as the seventh hallmark of cancer. This amendment was already proposed by Tennant et al. in 2009 [27]. In 2006, the review Science published a debate on the controversial views of Warburg theory [28], in support of a more realistic description of cancer cell’s variable bioenergetic profile. The pros think that high glycolysis is an obligatory feature of human tumors, while the cons propose that high glycolysis is not exclusive and that tumors can use OXPHOS to derive energy. A unifying theory closer to reality might consider that OXPHOS and glycolysis cooperate to sustain energy needs along tumorigenesis [20]. The concept of oxidative tumors, against Warburg’s proposal, was introduced by Guppy and colleagues, based on the observation that breast cancer cells can generate 80% of their ATP by the mitochondrion [29]. The comparison of different cancer cell lines and excised tumors revealed a variety of cancer cell’s bioenergetic signatures which raised the question of the mechanisms underlying tumor cell metabolic reprogramming, and the relative contribution of oncogenesis and microenvironment in this process. It is now widely accepted that rapidly growing cancer cells within solid tumors suffer from a lack of oxygen and nutrients as tumor grows. In such situation of compromised energy substrate delivery, cancer cell’s metabolic reprogramming is further used to sustain anabolism (Fig. 1), through the deviation of glycolysis, Krebs cycle truncation and OXPHOS redirection toward lipid and protein synthesis, as needed to support uncontrolled tumor growth and survival [30] and [31]. Again, these features are not exclusive to all tumors, as Krebs cycle truncation was only observed in some cancer cells, while other studies indicated that tumor cells can maintain a complete Krebs cycle [13] in parallel with an active citrate efflux. Likewise, generalizations should be avoided to prevent over-interpretations.
Fig. 1. Energy metabolism at the crossroad between catabolism and anabolism.

Energy metabolism at the crossroad between catabolism and anabolism.

Energy metabolism at the crossroad between catabolism and anabolism.

The oncogene C-MYC participate to these changes via the stimulation of glutamine utilization through the coordinate expression of genes necessary for cells to engage in glutamine catabolism [30]. According to Newsholme EA and Board M [32] both glycolysis and glutaminolysis not only serve for ATP production, but also provide precious metabolic intermediates such as glucose-6-phosphate, ammonia and aspartate required for the synthesis of purine and pyrimidine nucleotides (Fig. 1). In this manner, the observed apparent excess in the rates of glycolysis and glutaminolysis as compared to the requirement for energy production could be explained by the need for biosynthetic processes. Yet, one should not reduce the shift from glycolysis to OXPHOS utilization to the sole activation of glutaminolysis, as several other energy substrates can be used by tumor mitochondria to generate ATP [21]. The contribution of these different fuels to ATP synthesis remains poorly investigated in human tumors.

  1. The metabolism of pre-cancer cells and its ongoing modulation by carcinogenesis

At the beginning of cancer, there might have been a cancer stem cell hit by an oncogenic event, such as alterations in mitogen signaling to extracellular growth factor receptors (EGFR), oncogenic activation of these receptors, or oncogenic alterations of downstream targets in the pathways that leads to cell proliferation (RAS–Raf–ERK and PI3K–AKT, both leading to m-TOR activation stimulating cell growth). Alterations of checkpoint genes controlling the cell cycle progression like Rb also participate in cell proliferation (Fig. 2) and this re-entry in the cell cycle implies three major needs to fill in: 1) supplying enough energy to grow and 2) synthesize building blocks de novo and 3) keep vital oxygen and nutrients available. However, the bioenergetic status of the pre-cancer cell could determine in part the evolution of carcinogenesis, as shown on mouse embryonic stem cells. In this study, Schieke et al. showed that mitochondrial energy metabolism modulates both the differentiation and tumor formation capacity of mouse embryonic stem cells [37]. The idea that cancer derives from a single cell, known as the cancer stem cell hypothesis, was introduced by observations performed on leukemia which appeared to be organized as origination from a primitive hematopoietic cell [38]. Nowadays cancer stem cells were discovered for all types of tumors [39][40][41] and [42], but little is known of their bioenergetic properties and their metabolic adaptation to the microenvironment. This question is crucial as regards the understanding of what determines the wide variety of cancer cell’s metabolic profile.

Impact of different oncogenes on tumor progression and energy metabolism remodeling.

Impact of different oncogenes on tumor progression and energy metabolism remodeling.

Fig. 2. Impact of different oncogenes on tumor progression and energy metabolism remodeling.

The analysis of the metabolic changes that occur during the transformation of adult mesenchymal stem cells revealed that these cells did not switch to aerobic glycolysis, but their dependency on OXPHOS was even increased [24]. Hence, mitochondrial energy metabolism could be critical for tumorigenesis, in contrast with Warburg’s hypothesis. As discussed above, the oncogene C-MYC also stimulates OXPHOS [30]. Furthermore, it was recently demonstrated that cells chronically treated with oligomycin repress OXPHOS and produce larger tumors with higher malignancy [19]. Likewise, alteration of OXPHOS by mutations in mtDNA increases tumorigenicity in different types of cancer cells [43][44] and [45].

Recently, it was proposed that mitochondrial energy metabolism is required to generate reactive oxygen species used for the carcinogenetic process induced by the K-RAS mutation [46]. This could explain the large number of mitochondrial DNA mutations found in several tumors. The analysis of mitochondria in human embryonic cells which derive energy exclusively from anaerobic glycolysis have demonstrated an immature mitochondrial network characterized by few organelles with poorly developed cristae and peri-nuclear distribution [47] and [48]. The generation of human induced pluripotent stem cell by the introduction of different oncogenes as C-MYC and Oct4 reproduced this reduction of mitochondrial OXPHOS capacity[49] and [50]. This indicates again the impact of oncogenes on the control of OXPHOS and might explain the existence of pre-cancer stem cells with different bioenergetic backgrounds, as modeled by variable sequences of oncogene activation. Accordingly, the inhibition of mitochondrial respiratory chain has been recently found associated with enhancement of hESC pluripotency [51].

Based on the experimental evidence discussed above, one can argue that 1) glycolysis is indeed a feature of several tumors and associates with faster growth in high glucose environment, but 2) active OXPHOS is also an important feature of (other) tumors taken at a particular stage of carcinogenesis which might be more advantageous than a “glycolysis-only” type of metabolism in conditions of intermittent shortage in glucose delivery. The metabolic apparatus of cancer cells is not fixed during carcinogenesis and might depend both on the nature of the oncogenes activated and the microenvironment. It was indeed shown that cancer cells with predominant glycolytic metabolism present a higher malignancy when submitted to carcinogenetic induction and analysed under fixed experimental conditions of high glucose [19]. Yet, if one grows these cells in a glucose-deprived medium they shift their metabolism toward predominant OXPHOS, as shown in HeLa cells and other cell types [9]. Therefore, one might conclude that glycolytic cells have a higher propensity to generate aggressive tumors when glucose availability is high. However, these cells can become OXPHOS during tumor progression [24] and [52]. All these observations indicate again the importance of maintaining an active OXPHOS metabolism to permit evolution of both embryogenesis and carcinogenesis, which emphasizes the importance of targeting mitochondria to alter this malignant process.

  1. Oncogenes and the modulation of energy metabolism

Several oncogenes and associated proteins such as HIF-1α, RAS, C-MYC, SRC, and p53 can influence energy substrate utilization by affecting cellular targets, leading to metabolic changes that favor cancer cell survival, independently of the control of cell proliferation. These oncogenes stimulate the enhancement of aerobic glycolysis, and an increasing number of studies demonstrate that at least some of them can also target directly the OXPHOS machinery, as discussed in this article (Fig. 2). For instance, C-MYC can concurrently drive aerobic glycolysis and/or OXPHOS according to the tumor cell microenvironment, via the expression of glycolytic genes or the activation of mitochondrial oxidation of glutamine [53]. The oncogene RAS has been shown to increase OXPHOS activity in early transformed cells [24][52] and [54] and p53 modulates OXPHOS capacity via the regulation of cytochrome c oxidase assembly [55]. Hence, carcinogenic p53 deficiency results in a decreased level of COX2 and triggers a shift toward anaerobic metabolism. In this case, lactate synthesis is increased, but cellular ATP levels remain stable [56]. The p53-inducible isoform of phosphofructokinase, termed TP53-induced glycolysis and apoptotic regulator, TIGAR, a predominant phosphatase activity isoform of PFK-2, has also been identified as an important regulator of energy metabolism in tumors [57].

  1. Tumor specific isoforms (or mutated forms) of energy genes

Tumors are generally characterized by a modification of the glycolytic system where the level of some glycolytic enzymes is increased, some fetal-like isozymes with different kinetic and regulatory properties are produced, and the reverse and back-reactions of the glycolysis are strongly reduced [60]. The GAPDH marker of the glycolytic pathway is also increased in breast, gastric, lung, kidney and colon tumors [18], and the expression of glucose transporter GLUT1 is elevated in most cancer cells. The group of Cuezva J.M. developed the concept of cancer bioenergetic signature and of bioenergetic index to describe the metabolic profile of cancer cells and tumors [18], [61], [64], [65]. This signature describes the changes in the expression level of proteins involved in glycolysis and OXPHOS, while the BEC index gives a ratio of OXPHOS protein content to glycolytic protein content, in good correlation with cancer prognostic[61]. Recently, this group showed that the beta-subunit of the mitochondrial F1F0-ATP synthase is downregulated in a large number of tumors, thus contributing to the Warburg effect [64] and [65]. It was also shown that IF1 expression levels were increased in hepatocellular carcinomas, possibly to prevent the hydrolysis of glytolytic ATP [66]. Numerous changes occur at the level of OXPHOS and mitochondrial biogenesis in human tumors, as we reviewed previously [67]. Yet the actual impact of these changes in OXPHOS protein expression level or catalytic activities remains to be evaluated on the overall fluxes of respiration and ATP synthesis. Indeed, the metabolic control analysis and its extension indicate that it is often required to inhibit activity beyond a threshold of 70–85% to affect the metabolic fluxes [68] and [69]. Another important feature of cancer cells is the higher level of hexokinase II bound to mitochondrial membrane (50% in tumor cells). A study performed on human gliomas (brain) estimated the mitochondrial bound HK fraction (mHK) at 69% of total, as compared to 9% for normal brain [70]. This is consistent with the 5-fold amplification of the type II HK gene observed by Rempel et al. in the rapidly growing rat AS-30D hepatoma cell line, relative to normal hepatocytes [71]. HKII subcellular fractionation in cancer cells was described in several studies [72][73] and [74]. The group led by Pete Pedersen explained that mHK contributes to (i) the high glycolytic capacity by utilizing mitochondrially regenerated ATP rather than cytosolic ATP (nucleotide channelling) and (ii) the lowering of OXPHOS capacity by limiting Pi and ADP delivery to the organelle [75] and [76].

All these observations are consistent with the increased rate of FDG uptake observed by PET in living tumors which could result from both an increase in glucose transport, and/or an increase in hexokinase activity. However, FDG is not a complete substrate for glycolysis (it is only transformed into FDG-6P by hexokinase before to be eliminated) and cannot be used to evidence a general increase in the glycolytic flux. Moreover, FDG-PET scan also gives false positive and false negative results, indicating that some tumors do not depend on, or do not have, an increased glycolytic capacity. The fast glycolytic system described above is further accommodated in cancer cells by an increase in the lactate dehydrogenase isoform A (LDH-A) expression level. This isoform presents a higher Vmax useful to prevent the inhibition of high glycolysis by its end product (pyruvate) accumulation. Recently, Fantin et al. showed that inhibition of LDH-A in tumors diminishes tumorigenicity and was associated with the stimulation of mitochondrial respiration [79]. The preferential expression of the glycolytic pyruvate kinase isoenzyme M2 (PKM2) in tumor cells, determines whether glucose is converted to lactate for regeneration of energy (active tetrameric form, Warburg effect) or used for the synthesis of cell building blocks (nearly inactive dimeric form) [80]. In the last five years, mutations in proteins of the respiratory system (SDH, FH) and of the TCA cycle (IDH1,2) leading to the accumulation of metabolite and the subsequent activation of HIF-1α were reported in a variety of human tumors [81], [82] and [83].

  1. Tumor microenvironment modulates cancer cell’s bioenergetics

It was extensively described how hypoxia activates HIF-1α which stimulates in turn the expression of several glycolytic enzymes such as HK2, PFK, PGM, enolase, PK, LDH-A, MCT4 and glucose transporters Glut 1 and Glut 3. It was also shown that HIF-1α can reduce OXPHOS capacity by inhibiting mitochondrial biogenesis [14] and [15], PDH activity [87] and respiratory chain activity [88]. The low efficiency and uneven distribution of the vascular system surrounding solid tumors can lead to abrupt changes in oxygen (intermittent hypoxia) but also energy substrate delivery. .. The removal of glucose, or the inhibition of glycolysis by iodoacetate led to a switch toward glutamine utilization without delay followed by a rapid decrease in acid release. This illustrates once again how tumors and human cancer cell lines can utilize alternative energy pathway such as glutaminolysis to deal with glucose limitation, provided the presence of oxygen. It was also observed that in situations of glucose limitation, tumor derived-cells can adapt to survive by using exclusively an oxidative energy substrate [9] and [10]. This is typically associated with an enhancement of the OXPHOS system. … In summary, cancer cells can survive by using exclusively OXPHOS for ATP production, by altering significantly mitochondrial composition and form to facilitate optimal use of the available substrate (Fig. 3). Yet, glucose is needed to feed the pentose phosphate pathway and generate ribose essential for nucleotide biosynthesis. This raises the question of how cancer cells can survive in the growth medium which do not contain glucose (so-called “galactose medium” with dialysed serum [9]). In the OXPHOS mode, pyruvate, glutamate and aspartate can be derived from glutamine, as glutaminolysis can replenish Krebs cycle metabolic pool and support the synthesis of alanine and NADPH [31]. Glutamine is a major source for oxaloacetate (OAA) essential for citrate synthesis. Moreover, the conversion of glutamine to pyruvate is associated with the reduction of NADP+ to NADPH by malic enzyme. Such NADPH is a required electron donor for reductive steps in lipid synthesis, nucleotide metabolism and GSH reduction. In glioblastoma cells the malic enzyme flux was estimated to be high enough to supply all of the reductive power needed for lipid synthesis [31].

Fig. 3. Interplay between energy metabolism, oncogenes and tumor microenvironment during tumorigenesis (the “metabolic wave model”).

Interplay between energy metabolism, oncogenes and tumor microenvironment

Interplay between energy metabolism, oncogenes and tumor microenvironment

While the mechanisms leading to the enhancement of glycolytic capacity in tumors are well documented, less is known about the parallel OXPHOS changes. Both phenomena could result from a selection of pre-malignant cells forced to survive under hypoxia and limited glucose delivery, followed by an adaptation to intermittent hypoxia, pseudo-hypoxia, substrate limitation and acidic environment. This hypothesis was first proposed by Gatenby and Gillies to explain the high glycolytic phenotype of tumors [91], [92] and [93], but several lines of evidence suggest that it could also be used to explain the mitochondrial modifications observed in cancer cells.

  1. Aerobic glycolysis and mitochondria cooperate during cancer progression

Metabolic flexibility considers the possibility for a given cell to alternate between glycolysis and OXPHOS in response to physiological needs. Louis Pasteur found that in most mammalian cells the rate of glycolysis decreases significantly in the presence of oxygen (Pasteur effect). Moreover, energy metabolism of normal cell can vary widely according to the tissue of origin, as we showed with the comparison of five rat tissues[94]. During stem cell differentiation, cell proliferation induces a switch from OXPHOS to aerobic glycolysis which might generate ATP more rapidly, as demonstrated in HepG2 cells [95] or in non-cancer cells[96] and [97]. Thus, normal cellular energy metabolism can adapt widely according to the activity of the cell and its surrounding microenvironment (energy substrate availability and diversity). Support for this view came from numerous studies showing that in vitro growth conditions can alter energy metabolism contributing to a dependency on glycolysis for ATP production [98].

Yet, Zu and Guppy analysed numerous studies and showed that aerobic glycolysis is not inherent to cancer but more a consequence of hypoxia[99].

Table 1. Impact of different oncogenes on energy metabolism

Impact of different oncogenes on energy metabolism.

Impact of different oncogenes on energy metabolism.

2.1.2.5 Mitohormesis

Yun J, Finkel T
Cell Metab May 2014; 19(5):757–766
http://dx.doi.org/10.1016/j.cmet.2014.01.011

For many years, mitochondria were viewed as semiautonomous organelles, required only for cellular energetics. This view has been largely supplanted by the concept that mitochondria are fully integrated into the cell and that mitochondrial stresses rapidly activate cytosolic signaling pathways that ultimately alter nuclear gene expression. Remarkably, this coordinated response to mild mitochondrial stress appears to leave the cell less susceptible to subsequent perturbations. This response, termed mitohormesis, is being rapidly dissected in many model organisms. A fuller understanding of mitohormesis promises to provide insight into our susceptibility for disease and potentially provide a unifying hypothesis for why we age.

Figure 1. The Basis of Mitohormesis. Any of a number of endogenous or exogenous stresses can perturb mitochondrial function. These perturbations are relayed to the cytosol through, at present, poorly understood mechanisms that may involve mitochondrial ROS as well as other mediators. These cytoplasmic signaling pathways and subsequent nuclear transcriptional changes induce various long-lasting cytoprotective pathways. This augmented stress resistance allows for protection from a wide array of subsequent stresses.

Figure 2. Potential Parallels between the Mitochondrial Unfolded Protein Response and Quorum Sensing in Gram-Positive Bacteria. In the C. elegans UPRmt response, mitochondrial proteins (indicated by blue swirls) are degraded by matrix proteases, and the oligopeptides that are generated are then exported through the ABC transporter family member HAF-1. Once in the cytosol, these peptides can influence the subcellular localization of the transcription factor ATFS-1. Nuclear ATFS-1 is capable of orchestrating a broad transcriptional response to mitochondrial stress. As such, this pathway establishes a method for mitochondrial and nuclear genomes to communicate. In some gram-positive bacteria, intracellularly generated peptides can be similarly exported through an ABC transporter protein. These peptides can be detected in the environment by a membrane-bound histidine kinases (HK) sensor. The activation of the HK sensor leads to phosphorylation of a response regulator (RR) protein that, in turn, can alter gene expression. This program allows communication between dispersed gram-positive bacteria and thus coordinated behavior of widely dispersed bacterial genomes.

Figure 3. The Complexity of Mitochondrial Stresses and Responses. A wide array of extrinsic and intrinsic mitochondrial perturbations can elicit cellular responses. As detailed in the text, genetic or pharmacological disruption of electron transport, incorrect folding of mitochondrial proteins, stalled mitochondrial ribosomes, alterations in signaling pathways, or exposure to toxins all appear to elicit specific cytoprotective programs within the cell. These adaptive responses include increased mitochondrial number (biogenesis), alterations in metabolism, increased antioxidant defenses, and augmented protein chaperone expression. The cumulative effect of these adaptive mechanisms might be an extension of lifespan and a decreased incidence of age-related pathologies.

2.1.2.6 Mitochondrial function and energy metabolism in cancer cells. Past overview and future perspectives

Mayevsky A
Mitochondrion. 2009 Jun; 9(3):165-79
http://dx.doi.org:/10.1016/j.mito.2009.01.009

The involvements of energy metabolism aspects of mitochondrial dysfunction in cancer development, proliferation and possible therapy, have been investigated since Otto Warburg published his hypothesis. The main published material on cancer cell energy metabolism is overviewed and a new unique in vivo experimental approach that may have significant impact in this important field is suggested. The monitoring system provides real time data, reflecting mitochondrial NADH redox state and microcirculation function. This approach of in vivo monitoring of tissue viability could be used to test the efficacy and side effects of new anticancer drugs in animal models. Also, the same technology may enable differentiation between normal and tumor tissues in experimental animals and maybe also in patients.

 Energy metabolism in mammalian cells

Fig. 1. Schematic representation of cellular energy metabolism and its relationship to microcirculatory blood flow and hemoglobin oxygenation.

Fig. 2. Schematic representation of the central role of the mitochondrion in the various processes involved in the pathology of cancer cells and tumors. Six issues marked as 1–6 are discussed in details in the text.

In vivo monitoring of tissue energy metabolism in mammalian cells

Fig. 3. Schematic presentation of the six parameters that could be monitored for the evaluation of tissue energy metabolism (see text for details).

Optical spectroscopy of tissue energy metabolism in vivo

Multiparametric monitoring system

Fig. 4. (A) Schematic representation of the Time Sharing Fluorometer Reflectometer (TSFR) combined with the laser Doppler flowmeter (D) for blood flow monitoring. The time sharing system includes a wheel that rotates at a speed of3000 rpm wit height filters: four for the measurements of mitochondrial NADH(366 nm and 450 nm)and four for oxy-hemoglobin measurements (585 nm and 577 nm) as seen in (C). The source of light is a mercury lamp. The probe includes optical fibers for NADH excitation (Ex) and emission (Em), laser Doppler excitation (LD in), laser Doppler emission (LD out) as seen in part E The absorption spectrum of Oxy- and Deoxy- Hemoglobin indicating the two wave length used (C).

Fig. 7. Comparison between mitochondrial metabolic states in vitro and the typical tissue metabolic states in vivo evaluated by NADH redox state, tissue blood flow and hemoglobin oxygenation as could be measured by the suggested monitoring system.

(very important)

2.1.2.7 Metabolic Reprogramming. Cancer Hallmark Even Warburg Did Not Anticipate

Ward PS, Thompson CB.
Cancer Cell 2012; 21(3):297-308
http://dx.doi.org/10.1016/j.ccr.2012.02.014

Cancer metabolism has long been equated with aerobic glycolysis, seen by early biochemists as primitive and inefficient. Despite these early beliefs, the metabolic signatures of cancer cells are not passive responses to damaged mitochondria but result from oncogene-directed metabolic reprogramming required to support anabolic growth. Recent evidence suggests that metabolites themselves can be oncogenic by altering cell signaling and blocking cellular differentiation. No longer can cancer-associated alterations in metabolism be viewed as an indirect response to cell proliferation and survival signals. We contend that altered metabolism has attained the status of a core hallmark of cancer.

The propensity for proliferating cells to secrete a significant fraction of glucose carbon through fermentation was first elucidated in yeast. Otto Warburg extended these observations to mammalian cells, finding that proliferating ascites tumor cells converted the majority of their glucose carbon to lactate, even in oxygen-rich conditions. Warburg hypothesized that this altered metabolism was specific to cancer cells, and that it arose from mitochondrial defects that inhibited their ability to effectively oxidize glucose carbon to CO2. An extension of this hypothesis was that dysfunctional mitochondria caused cancer (Koppenol et al., 2011). Warburg’s seminal finding has been observed in a wide variety of cancers. These observations have been exploited clinically using 18F-deoxyglucose positron emission tomography (FDG-PET). However, in contrast to Warburg’s original hypothesis, damaged mitochondria are not at the root of the aerobic glycolysis exhibited by most tumor cells. Most tumor mitochondria are not defective in their ability to carry out oxidative phosphorylation. Instead, in proliferating cells mitochondrial metabolism is reprogrammed to meet the challenges of macromolecular synthesis. This possibility was never considered by Warburg and his contemporaries.

Advances in cancer metabolism research over the last decade have enhanced our understanding of how aerobic glycolysis and other metabolic alterations observed in cancer cells support the anabolic requirements associated with cell growth and proliferation. It has become clear that anabolic metabolism is under complex regulatory control directed by growth factor signal transduction in non-transformed cells. Yet despite these advances, the repeated refrain from traditional biochemists is that altered metabolism is merely an indirect phenomenon in cancer, a secondary effect that pales in importance to the activation of primary proliferation and survival signals (Hanahan and Weinberg, 2011). Most proto-oncogenes and tumor suppressor genes encode components of signal transduction pathways. Their roles in carcinogenesis have traditionally been attributed to their ability to regulate the cell cycle and sustain proliferative signaling while also helping cells evade growth suppression and/or cell death (Hanahan and Weinberg, 2011). But evidence for an alternative concept, that the primary functions of activated oncogenes and inactivated tumor suppressors are to reprogram cellular metabolism, has continued to build over the past several years. Evidence is also developing for the proposal that proto-oncogenes and tumor suppressors primarily evolved to regulate metabolism.

We begin this review by discussing how proliferative cell metabolism differs from quiescent cell metabolism on the basis of active metabolic reprogramming by oncogenes and tumor suppressors. Much of this reprogramming depends on utilizing mitochondria as functional biosynthetic organelles. We then further develop the idea that altered metabolism is a primary feature selected for during tumorigenesis. Recent advances have demonstrated that altered metabolism in cancer extends beyond adaptations to meet the increased anabolic requirements of a growing and dividing cell. Changes in cancer cell metabolism can also influence cellular differentiation status, and in some cases these changes arise from oncogenic alterations in metabolic enzymes themselves.

Metabolism in quiescent vs. proliferating cells nihms-360138-f0001

Metabolism in quiescent vs. proliferating cells: both use mitochondria.
(A) In the absence of instructional growth factor signaling, cells in multicellular organisms lack the ability to take up sufficient nutrients to maintain themselves. Neglected cells will undergo autophagy and catabolize amino acids and lipids through the TCA cycle, assuming sufficient oxygen is available. This oxidative metabolism maximizes ATP production. (B) Cells that receive instructional growth factor signaling are directed to increase their uptake of nutrients, most notably glucose and glutamine. The increased nutrient uptake can then support the anabolic requirements of cell growth: mainly lipid, protein, and nucleotide synthesis (biomass). Excess carbon is secreted as lactate. Proliferating cells may also use strategies to decrease their ATP production while increasing their ATP consumption. These strategies maintain the ADP:ATP ratio necessary to maintain glycolytic flux. Green arrows represent metabolic pathways, while black arrows represent signaling.

Metabolism is a direct, not indirect, response to growth factor signaling nihms-360138-f0002

Metabolism is a direct, not indirect, response to growth factor signaling nihms-360138-f0002

Metabolism is a direct, not indirect, response to growth factor signaling.
(A) The traditional demand-based model of how metabolism is altered in proliferating cells. In response to growth factor signaling, increased transcription and translation consume free energy and decrease the ADP:ATP ratio. This leads to enhanced flux of glucose carbon through glycolysis and the TCA cycle for the purpose of producing more ATP. (B) Supply-based model of how metabolism changes in proliferating cells. Growth factor signaling directly reprograms nutrient uptake and metabolism. Increased nutrient flux through glycolysis and the mitochondria in response to growth factor signaling is used for biomass production. Metabolism also impacts transcription and translation through mechanisms independent of ATP availability.

Alterations in classic oncogenes directly reprogram cell metabolism to increase nutrient uptake and biosynthesis. PI3K/Akt signaling downstream of receptor tyrosine kinase (RTK) activation increases glucose uptake through the transporter GLUT1, and increases flux through glycolysis. Branches of glycolytic metabolism contribute to nucleotide and amino acid synthesis. Akt also activates ATP-citrate lyase (ACL), promoting the conversion of mitochondria-derived citrate to acetyl-CoA for lipid synthesis. Mitochondrial citrate can be synthesized when glucose-derived acetyl-CoA, generated by pyruvate dehydrogenase (PDH), condenses with glutamine-derived oxaloacetate (OAA) via the activity of citrate synthase (CS). mTORC1 promotes protein synthesis and mitochondrial metabolism. Myc increases glutamine uptake and the conversion of glutamine into a mitochondrial carbon source by promoting the expression of the enzyme glutaminase (GLS). Myc also promotes mitochondrial biogenesis. In addition, Myc promotes nucleotide and amino acid synthesis, both through direct transcriptional regulation and through increasing the synthesis of mitochondrial metabolite precursors.

Pyruvate kinase M2 (PKM2) expression in proliferating cells is regulated by signaling and mitochondrial metabolism to facilitate macromolecular synthesis. PKM2 is a less active isoform of the terminal glycolytic enzyme pyruvate kinase. It is also uniquely inhibited downstream of tyrosine kinase signaling. The decreased enzymatic activity of PKM2 in the cytoplasm promotes the accumulation of upstream glycolytic intermediates and their shunting into anabolic pathways. These pathways include the serine synthetic pathway that contributes to nucleotide and amino acid production. When mitochondrial metabolism is excessive, reactive oxygen species (ROS) from the mitochondria can feedback to inhibit PKM2 activity. Acetylation of PKM2, dependent on acetyl-CoA availability, may also promote PKM2 degradation and further contribute to increased flux through anabolic synthesis pathways branching off glycolysis.

IDH1 and IDH2 mutants convert glutamine carbon to the oncometabolite 2-hydroxyglutarate to dysregulate epigenetics and cell differentiation. (A) α-ketoglutarate, produced in part by wild-type isocitrate dehydrogenase (IDH), can enter the nucleus and be used as a substrate for dioxygenase enzymes that modify epigenetic marks. These enzymes include the TET2 DNA hydroxylase enzyme which converts 5-methylcytosine to 5-hydroxymethylcytosine, typically at CpG dinucleotides. 5-hydroxymethylcytosine may be an intermediate in either active or passive DNA demethylation. α-ketoglutarate is also a substrate for JmjC domain histone demethylase enzymes that demethylate lysine residues on histone tails. (B) The common feature of cancer-associated mutations in cytosolic IDH1 and mitochondrial IDH2 is the acquisition of a neomorphic enzymatic activity. This activity converts glutamine-derived α-ketoglutarate to the oncometabolite 2HG. 2HG can competitively inhibit α-ketoglutarate-dependent enzymes like TET2 and the JmjC histone demethylases, thereby impairing normal epigenetic regulation. This results in altered histone methylation marks, in some cases DNA hypermethylation at CpG islands, and dysregulated cellular differentiation.

Hypoxia and HIF-1 activation promote an alternative pathway for citrate synthesis through reductive metabolism of glutamine. (A) In proliferating cells under normoxic conditions, citrate is synthesized from both glucose and glutamine. Glucose carbon provides acetyl-CoA through the activity of PDH. Glutamine carbon provides oxaloacetate through oxidative mitochondrial metabolism dependent on NAD+. Glucose-derived acetyl-CoA and glutamine-derived oxaloacetate condense to form citrate via the activity of citrate synthase (CS). Citrate can be exported to the cytosol for lipid synthesis. (B) In cells proliferating in hypoxia and/or with HIF-1 activation, glucose is diverted away from mitochondrial acetyl-CoA and citrate production. Citrate can be maintained through an alternative pathway of reductive carboxylation, which we propose to rely on reverse flux of glutamine-derived α-ketoglutarate through IDH2. This reverse flux in the mitochondria would promote electron export from the mitochondria when the activity of the electron transport chain is inhibited because of the lack of oxygen as an electron acceptor. Mitochondrial reverse flux can be accomplished by NADH conversion to NADPH by mitochondrial transhydrogenase and the resulting NADPH use in α-ketoglutarate carboxylation. When citrate/isocitrate is exported to the cytosol, some may be metabolized in the oxidative direction by IDH1 and contribute to a shuttle that produces cytosolic NADPH.

A major paradox remaining with PKM2 is that cells expressing PKM2 produce more glucose-derived pyruvate than PKM1-expressing cells, despite having a form of the pyruvate kinase enzyme that is less active and more sensitive to inhibition. One way to get around the PKM2 bottleneck and maintain/enhance pyruvate production may be through an proposed alternative glycolytic pathway, involving an enzymatic activity not yet purified, that dephosphorylates PEP to pyruvate without the generation of ATP (Vander Heiden et al., 2010). Another answer to this paradox may emanate from the serine synthetic pathway. The decreased enzymatic activity of PKM2 can promote the accumulation of the 3-phosphoglycerate glycolytic intermediate that serves as the entry point for the serine synthetic pathway branch off glycolysis. The little studied enzyme serine dehydratase can then directly convert serine to pyruvate. A third explanation may lie in the oscillatory activity of PKM2 from the inactive dimer to active tetramer form. Regulatory inputs into PKM2 like tyrosine phosphorylation and ROS destabilize the tetrameric form of PKM2 (Anastasiou et al., 2011; Christofk et al., 2008b; Hitosugi et al., 2009), but other inputs present in glycolytic cancer cells like fructose-1,6-bisphosphate and serine can continually allosterically activate and/or promote reformation of the PKM2 tetramer (Ashizawa et al., 1991; Eigenbrodt et al., 1983). Thus, PKM2 may be continually switching from inactive to active forms in cells, resulting in an apparent upregulation of flux through anabolic glycolytic branching pathways while also maintaining reasonable net flux of glucose carbon through PEP to pyruvate. With such an oscillatory system, small changes in the levels of any of the above-mentioned PKM2 regulatory inputs can cause exquisite, rapid, adjustments to glycolytic flux. This would be predicted to be advantageous for proliferating cells in the setting of variable extracellular nutrient availability. The capability for oscillatory regulation of PKM2 could also provide an explanation for why tumor cells do not select for altered glycolytic metabolism upstream of PKM2 through deletions and/or loss of function mutations of other glycolytic enzymes.

IDH1 mutations at R132 are not simply loss-of-function for isocitrate and α-ketoglutarate interconversion, but also acquire a novel reductive activity to convert α-ketoglutarate to 2-hydroxyglutarate (2HG), a rare metabolite found at only trace amounts in mammalian cells under normal conditions (Dang et al., 2009). However, it still remained unclear if 2HG was truly a pathogenic “oncometabolite” resulting from IDH1 mutation, or if it was just the byproduct of a loss of function mutation. Whether 2HG production or the loss of IDH1 normal function played a more important role in tumorigenesis remained uncertain.

A potential answer to whether 2HG production was relevant to tumorigenesis arrived with the study of mutations in IDH2, the mitochondrial homolog of IDH1. Up to this point a small fraction of gliomas lacking IDH1 mutations were known to harbor mutations at IDH2 R172, the analogous residue to IDH1 R132 (Yan et al., 2009). However, given the rarity of these IDH2 mutations, they had not been characterized for 2HG production. The discovery of IDH2 R172 mutations in AML as well as glioma samples prompted the study of whether these mutations also conferred the reductive enzymatic activity to produce 2HG. Enzymatic assays and measurement of 2HG levels in primary AML samples confirmed that these IDH2 R172 mutations result in 2HG elevation (Gross et al., 2010; Ward et al., 2010).

It was then investigated if the measurement of 2HG levels in primary tumor samples with unknown IDH mutation status could serve as a metabolite screening test for both cytosolic IDH1 and mitochondrial IDH2 mutations. AML samples with low to undetectable 2HG were subsequently sequenced and determined to be IDH1 and IDH2 wild-type, and several samples with elevated 2HG were found to have neomorphic mutations at either IDH1 R132 or IDH2 R172 (Gross et al., 2010). However, some 2HG-elevated AML samples lacked IDH1 R132 or IDH2 R172 mutations. When more comprehensive sequencing of IDH1 and IDH2 was performed, it was found that the common feature of this remaining subset of 2HG-elevated AMLs was another mutation in IDH2, occurring at R140 (Ward et al., 2010). This discovery provided additional evidence that 2HG production was the primary feature being selected for in tumors.

In addition to intensifying efforts to find the cellular targets of 2HG, the discovery of the 2HG-producing IDH1 and IDH2 mutations suggested that 2HG measurement might have clinical utility in diagnosis and disease monitoring. While much work is still needed in this area, serum 2HG levels have successfully correlated with IDH1 R132 mutations in AML, and recent data have suggested that 1H magnetic resonance spectroscopy can be applied for 2HG detection in vivo for glioma (Andronesi et al., 2012; Choi et al., 2012; Gross et al., 2010; Pope et al., 2012). These methods may have advantages over relying on invasive solid tumor biopsies or isolating leukemic blast cells to obtain material for sequencing of IDH1 and IDH2. Screening tumors and body fluids by 2HG status also has potentially increased applicability given the recent report that additional IDH mutations can produce 2HG (Ward et al., 2011). These additional alleles may account for the recently described subset of 2HG-elevated chondrosarcoma samples that lacked the most common IDH1 or IDH2 mutations but were not examined for other IDH alterations (Amary et al., 2011). Metabolite screening approaches can also distinguish neomorphic IDH mutations from SNPs and sequencing artifacts with no effect on IDH enzyme activity, as well as from an apparently rare subset of loss-of-function, non 2HG-producing IDH mutations that may play a secondary tumorigenic role in altering cellular redox (Ward et al., 2011).

Will we find other novel oncometabolites like 2HG? We should consider basing the search for new oncometabolites on those metabolites already known to cause disease in pediatric inborn errors of metabolism (IEMs). 2HG exemplifies how advances in research on IEMs can inform research on cancer metabolism, and vice versa. Methods developed by those studying 2HG aciduria were used to demonstrate that R(-)-2HG (also known as D-2HG) is the exclusive 2HG stereoisomer produced by IDH1 and IDH2 mutants (Dang et al., 2009; Ward et al., 2010). Likewise, following the discovery of 2HG-producing IDH2 R140 mutations in leukemia, researchers looked for and successfully found germline IDH2 R140 mutations in D-2HG aciduria. IDH2 R140 mutations now account for nearly half of all cases of this devastating disease (Kranendijk et al., 2010). While interest has surrounded 2HG due to its apparent novelty as a metabolite not found in normal non-diseased cells, there are situations where 2HG appears in the absence of metabolic enzyme mutations. For example, in human cells proliferating in hypoxia, α-ketoglutarate can accumulate and be metabolized through an enhanced reductive activity of wild-type IDH2 in the mitochondria, leading to 2HG accumulation in the absence of IDH mutation (Wise et al., 2011). The ability of 2HG to alter epigenetics may reflect its evolutionary ancient status as a signal for elevated glutamine/glutamate metabolism and/or oxygen deficiency.

With this broadened view of what constitutes an oncometabolite, one could argue that the discoveries of two other oncometabolites, succinate and fumarate, preceded that of 2HG. Loss of function mutations in the TCA cycle enzymes succinate dehydrogenase (SDH) and fumarate hydratase (FH) have been known for several years to occur in pheochromocytoma, paraganglioma, leiomoyoma, and renal carcinoma. It was initially hypothesized that these mutations contribute to cancer through mitochondrial damage producing elevated ROS (Eng et al., 2003). However, potential tumorigenic effects were soon linked to the elevated levels of succinate and fumarate arising from loss of SDH and FH function, respectively. Succinate was initially found to impair PHD2, the α-ketoglutarate-dependent enzyme regulating HIF stability, through product inhibition (Selak et al., 2005). Subsequent work confirmed that fumarate could inhibit PHD2 (Isaacs et al., 2005), and that succinate could also inhibit the related enzyme PHD3 (Lee et al., 2005). These observations linked the elevated HIF levels observed in SDH and FH deficient tumors to the activity of the succinate and fumarate metabolites. Recent work has suggested that fumarate may have other important roles that predominate in FH deficiency. For example, fumarate can modify cysteine residues to inhibit a negative regulator of the Nrf2 transcription factor. This post-translational modification leads to the upregulation of antioxidant response genes (Adam et al., 2011; Ooi et al., 2011).

There are still many unanswered questions regarding the biology of SDH and FH deficient tumors. In light of the emerging epigenetic effects of 2HG, it is intriguing that succinate has been shown to alter histone demethylase activity in yeast (Smith et al., 2007). Perhaps elevated succinate and fumarate resulting from SDH and FH mutations can promote tumorigenesis in part through epigenetic modulation.

Despite rapid technological advances in studying cell metabolism, we remain unable to reliably distinguish cytosolic metabolites from those in the mitochondria and other compartments. Current fractionation methods often lead to metabolite leakage. Even within one subcellular compartment, there may be distinct pools of metabolites resulting from channeling between metabolic enzymes. A related challenge lies in the quantitative measurement of metabolic flux; i.e., measuring the movement of carbon, nitrogen, and other atoms through metabolic pathways rather than simply measuring the steady-state levels of individual metabolites. While critical fluxes have been quantified in cultured cancer cells and methods for these analyses continue to improve (DeBerardinis et al., 2007; Mancuso et al., 2004; Yuan et al., 2008), many obstacles remain such as cellular compartmentalization and the reliance of most cell culture on complex, incompletely defined media.

Over the past decade, the study of metabolism has returned to its rightful place at the forefront of cancer research. Although Warburg was wrong about mitochondria, he was prescient in his focus on metabolism. Data now support the concepts that altered metabolism results from active reprogramming by altered oncogenes and tumor suppressors, and that metabolic adaptations can be clonally selected during tumorigenesis. Altered metabolism should now be considered a core hallmark of cancer. There is much work to be done.

2.1.2.8 A Role for the Mitochondrial Pyruvate Carrier as a Repressor of the Warburg Effect and Colon Cancer Cell Growth

Schell JC, Olson KA, …, Xie J, Egnatchik RA, Earl EG, DeBerardinis RJ, Rutter J.
Mol Cell. 2014 Nov 6; 56(3):400-13
http://dx.doi.org:/10.1016/j.molcel.2014.09.026

Cancer cells are typically subject to profound metabolic alterations, including the Warburg effect wherein cancer cells oxidize a decreased fraction of the pyruvate generated from glycolysis. We show herein that the mitochondrial pyruvate carrier (MPC), composed of the products of the MPC1 and MPC2 genes, modulates fractional pyruvate oxidation. MPC1 is deleted or underexpressed in multiple cancers and correlates with poor prognosis. Cancer cells re-expressing MPC1 and MPC2 display increased mitochondrial pyruvate oxidation, with no changes in cell growth in adherent culture. MPC re-expression exerted profound effects in anchorage-independent growth conditions, however, including impaired colony formation in soft agar, spheroid formation, and xenograft growth. We also observed a decrease in markers of stemness and traced the growth effects of MPC expression to the stem cell compartment. We propose that reduced MPC activity is an important aspect of cancer metabolism, perhaps through altering the maintenance and fate of stem cells.

Figure 2. Re-Expressed MPC1 and MPC2 Form a Mitochondrial Complex (A and B) (A) Western blot and (B) qRT-PCR analysis of the indicated colon cancer cell lines with retroviral expression of MPC1 (or MPC1-R97W) and/or MPC2. (C) Western blots of human heart tissue, hematologic cancer cells, and colon cancer cell lines with and without MPC1 and MPC2 re-expression. (D) Fluorescence microscopy of MPC1-GFP and MPC2-GFP overlaid with Mitotracker Red in HCT15 cells. Scale bar: 10 mm. (E) Blue-native PAGE analysis of mitochondria from control and MPC1/2-expressing cells. (F) Western blots of metabolic and mitochondrial proteins across four colon cancer cell lines with or without MPC1/2 expression

Figure 3. MPC Re-Expression Alters Mitochondrial Pyruvate Metabolism (A) OCR at baseline and maximal respiration in HCT15 (n = 7) and HT29 (n = 13) with pyruvate as the sole carbon source (mean ± SEM). (B and C) Schematic and citrate mass isotopomer quantification in cells cultured with D-[U-13C]glucose and unlabeled glutamine for 6 hr (mean ± SD, n = 2). (D) Glucose uptake and lactate secretion normalized to protein concentration (mean ± SD, n = 3). (E–G) (E) Western blots of PDH, phospho-PDH, and PDK1; (F) PDH activity assay and (G) CS activity assay with or without MPC1 and MPC2 expression (mean ± SD, n = 4). (H and I) Effects of MPC1/2 re-expression on mitochondrial membrane potential and ROS production (mean ± SD, n = 3). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

Figure 4. MPC Re-Expression Alters Growth under Low-Attachment Conditions (A) Cell number of control and MPC1/2 re-expressing cell lines in adherent culture (mean ± SD, n = 7). (B) Cell viability determined by trypan blue exclusion and Annexin V/PI staining (mean ± SD, n = 3). (C–F) (C) EdU incorporation of MPC re-expressing cell lines at 3 hr post EdU pulse. Growth in 3D culture evaluated by (D) soft agar colony formation (mean ± SD, n = 12, see also Table S1) and by ([E] and [F]) spheroid formation ± MPC inhibitor UK5099 (mean ± SEM, n = 12). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

Figure 7. MPC Re-Expression Alters the Cancer Initiating Cell Population (A) Western blot quantification of ALDHA and Lin28A from control or MPC re-expressing HT29 xenografts (mean ± SEM, n = 10). (B and C) Percentage of ALDHhi (n = 3) and CD44hi (n = 5) cells as determined by flow cytometry (mean ± SEM). (D) Western blot analysis of stem cell markers in control and MPC re-expressing cell lines. (E) Relative MPC1 and MPC2 mRNA levels in ALDH sorted HCT15 cells (n = 4,mean ± SEM). 2D growth of (F) whole-population HCT15 cells and (G) ALDH sorted cells. Area determined by ImageJ after crystal violet staining (mean ± SD, n = 6). (H and I) (H) Adherent and (I) spheroid growth of main population (MP) versus side population (SP) HCT15 cells. (mean ± SD, n = 6). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001

Our demonstration that the MPC is lost or underexpressed in many cancers might provide clarifying context for earlier attempts to exploit metabolic regulation for cancer therapeutics. The PDH kinase inhibitor dichloroacetate, which impairs PDH phosphorylation and increases pyruvate oxidation, has been explored extensively as a cancer therapy (Bonnet et al., 2007; Olszewski et al., 2010). It has met with mixed results, however, and has typically failed to dramatically decrease tumor burden as a monotherapy (Garon et al., 2014;
Sanchez-Arago et al., 2010; Shahrzadetal.,2010). Is one possible reason for these failures that the MPC has been lost or inactivated, thereby limiting the metabolic effects of PDH activity? The inclusion of the MPC adds additional complexity to targeting cancer metabolism for therapy but has the potential to explain why treatments may be more effective in some studies than in others (Fulda et al., 2010; Hamanaka and Chandel, 2012; Tennant et al., 2010; Vander Heiden, 2011). The redundant measures to limit pyruvate oxidation make it easy to understand why expression of the MPC leads to relatively modest metabolic changes in cells grown in adherent culture conditions. While subtle, we observed a number of changes in metabolic parameters, all of which are consistent with enhanced mitochondrial pyruvate entry and oxidation. There are at least two possible explanations for the discrepancy that we observed between the impact on adherent and nonadherent cell proliferation. One hypothesis is that the stress of nutrient deprivation and detachment combines with these subtle metabolic effects to impair survival and proliferation.

2.1.2.9  ECM1 promotes the Warburg effect through EGF-mediated activation of PKM2

Lee KM, Nam K, Oh S, Lim J, Lee T, Shin I.
Cell Signal. 2015 Feb; 27(2):228-35
http://dx.doi.org:/10.1016/j.cellsig.2014.11.004

The Warburg effect is an oncogenic metabolic switch that allows cancer cells to take up more glucose than normal cells and favors anaerobic glycolysis. Extracellular matrix protein 1 (ECM1) is a secreted glycoprotein that is overexpressed in various types of carcinoma. Using two-dimensional digest-liquid chromatography-mass spectrometry (LC-MS)/MS, we showed that the expression of proteins associated with the Warburg effect was upregulated in trastuzumab-resistant BT-474 cells that overexpressed ECM1 compared to control cells. We further demonstrated that ECM1 induced the expression of genes that promote the Warburg effect, such as glucose transporter 1 (GLUT1), lactate dehydrogenase A (LDHA), and hypoxia-inducible factor 1 α (HIF-1α). The phosphorylation status of pyruvate kinase M2 (PKM-2) at Ser37, which is responsible for the expression of genes that promote the Warburg effect, was affected by the modulation of ECM1 expression. Moreover, EGF-dependent ERK activation that was regulated by ECM1 induced not only PKM2 phosphorylation but also gene expression of GLUT1 and LDHA. These findings provide evidence that ECM1 plays an important role in promoting the Warburg effect mediated by PKM2.

Fig. 1.ECM1 induces a metabolic shift toward promoting Warburg effect. (A) The levels of glucose uptake were examined with a cell-based assay. (B) Levels of lactate production were measured using a lactate assay kit. (C) Cellular ATP content was determined with a Cell Titer-Glo luminescent cell viability assay. Error bars represent mean ± SD of triplicate experiments (*p b 0.05, ***p b 0.0005).

Fig.2. ECM1 up-regulates expression of gene sassociated with the Warburg effect. (A) Cell lysates were analyzed by western blotting using antibodies specific for ECM1, LDHA, GLUT1,and actin (as a loading control). The intensities of the bands were quantified using 1D Scan software and plotted. (BandC) mRNA levels of each gene were determined by real-time PCR using specific primers. (D) HIF-1α-dependent transcriptional activities were examined using a hypoxia response element (HRE) reporter indual luciferase assays. Error bars represent mean ± SD of triplicate experiments (*p b 0.05, **p b 0.005, ***p b 0.0005).

Fig.3. ECM1-dependent upregulation of gene expression is not mediated byEgr-1.

Fig.4. ECM1 activates PKM2 via EGF-mediated ERK activation

Fig. 5. TheWarburg effect is attenuated by silencing of PKM2 in breast cancer cells

Recently, a non-glycolytic function of PKM2 was reported. Phosphorylated PKM2 at Ser37 is translocated into the nucleus after EGFR and ERK activation and regulates the expression of cyclin D1, c-Myc, LDHA, and GLUT1[19,37]. Here, we showed that ECM1 regulates the phosphorylation level and translocation of PKM2 via the EGFR/ ERK pathway. As we previously showed that ECM1 enhances the EGF response and increases EGFR expression through MUC1-dependent stabilization [17], it seemed likely that activation of the EGFR/ERK pathway by ECM1 is linked to PKM2 phosphorylation. Indeed, we show here that ECM1 regulates the phosphorylation of PKM2 at Ser37 and enhances the Warburg effect through the EGFR/ERK pathway. HIF-1α is known to be responsible for alterations in cancer cell metabolism [38] and our current studies showed that the expression level of HIF-1α is up-regulated by ECM1 (Fig. 2C and D). To determine the mechanism by which ECM1 upregulated HIF-1α expression, we focused on the induction of Egr-1 by EGFR/ERK signaling [39]. However, although Egr-1 expression was regulated by ECM1 we failed to find evidence that Egr-1 affected the expression of genes involved in the Warburg effect (Fig. 3C). Moreover, ERK-dependent PKM2 activation did not regulate HIF-1α expression in BT-474 cells (Fig. 4D and5B). These results suggested that the upregulation of HIF-1α by ECM1 is not mediated by the EGFR/ERK pathway.

Conclusions

In the current study we showed that ECM1 altered metabolic phenotypes of breast cancer cells toward promoting the Warburg effect.

Phosphorylation and nuclear translocation of PKM2 were induced by ECM1 through the EGFR/ERK pathway. Moreover, phosphorylated PKM2 increased the expression of metabolic genes such as LDHA and GLUT1, and promoted glucose uptake and lactate production. These findings provide a new perspective on the distinct functions of ECM1 in cancer cell metabolism. Supplementary data to this article can be found online at
http://dx.doi.org/10.1016/j.cellsig.2014.11.004

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2.1.2.10 Glutamine Oxidation Maintains the TCA Cycle and Cell Survival during impaired Mitochondrial Pyruvate Transport

Chendong Yang, B Ko, CT. Hensley,…, J Rutter, ME. Merritt, RJ. DeBerardinis
Molec Cell  6 Nov 2014; 56(3):414–424
http://dx.doi.org/10.1016/j.molcel.2014.09.025

Highlights

  • Mitochondria produce acetyl-CoA from glutamine during MPC inhibition
    •Alanine synthesis is suppressed during MPC inhibition
    •MPC inhibition activates GDH to supply pools of TCA cycle intermediates
    •GDH supports cell survival during periods of MPC inhibition

Summary

Alternative modes of metabolism enable cells to resist metabolic stress. Inhibiting these compensatory pathways may produce synthetic lethality. We previously demonstrated that glucose deprivation stimulated a pathway in which acetyl-CoA was formed from glutamine downstream of glutamate dehydrogenase (GDH). Here we show that import of pyruvate into the mitochondria suppresses GDH and glutamine-dependent acetyl-CoA formation. Inhibiting the mitochondrial pyruvate carrier (MPC) activates GDH and reroutes glutamine metabolism to generate both oxaloacetate and acetyl-CoA, enabling persistent tricarboxylic acid (TCA) cycle function. Pharmacological blockade of GDH elicited largely cytostatic effects in culture, but these effects became cytotoxic when combined with MPC inhibition. Concomitant administration of MPC and GDH inhibitors significantly impaired tumor growth compared to either inhibitor used as a single agent. Together, the data define a mechanism to induce glutaminolysis and uncover a survival pathway engaged during compromised supply of pyruvate to the mitochondria.

Yang et al, Graphical Abstract

Yang et al, Graphical Abstract

Graphical abstract

Figure 1. Pyruvate Depletion Redirects Glutamine Metabolism to Produce AcetylCoA and Citrate (A) Top: Anaplerosis supplied by [U-13C]glutamine. Glutamine supplies OAA via a-KG, while acetylCoA is predominantly supplied by other nutrients, particularly glucose. Bottom: Glutamine is converted to acetyl-CoA in the absence of glucosederived pyruvate. Red circles represent carbons arising from [U-13C]glutamine, and gray circles are unlabeled. Reductive carboxylation is indicated by the green dashed line. (B) Fraction of succinate, fumarate, malate, and aspartate containing four 13C carbons after culture of SFxL cells for 6 hr with [U-13C]glutamine in the presence or absence of 10 mM unlabeled glucose (Glc). (C) Mass isotopologues of citrate after culture of SFxL cells for 6 hr with [U-13C]glutamine and 10 mM unlabeled glucose, no glucose, or no glucose plus 6 mM unlabeled pyruvate (Pyr). (D) Citrate m+5 and m+6 after culture of HeLa or Huh-7 cells for 6 hr with [U-13C]glutamine and 10 mM unlabeled glucose, no glucose, or no glucose plus 6 mM unlabeled pyruvate. Data are the average and SD of three independent cultures. *p < 0.05; **p < 0.01; ***p < 0.001.

Figure 2. Isolated Mitochondria Convert Glutamine to Citrate (A) Western blot of whole-cell lysates (Cell) and preparations of isolated mitochondria (Mito) or cytosol from SFxL cells. (B) Oxygen consumption in a representative mitochondrial sample. Rates before and after addition of ADP/GDP are indicated. (C) Mass isotopologues of citrate produced by mitochondria cultured for 30 min with [U-13C] glutamine and with or without pyruvate.

Figure 3. Blockade of Mitochondrial Pyruvate Transport Activates Glutamine-Dependent Citrate Formation (A) Dose-dependent effects of UK5099 on citrate labeling from [U-13C]glucose and [U-13C]glutamine in SFxL cells. (B) Time course of citrate labeling from [U-13C] glutamine with or without 200 mM UK5099. (C) Abundance of total citrate and citrate m+6 in cells cultured in [U-13C]glutamine with or without 200 mM UK5099. (D) Mass isotopologues of citrate in cells cultured for 6 hr in [U-13C]glutamine with or without 10 mM CHC or 200 mM UK5099. (E) Effect of silencing ME2 on citrate m+6 after 6 hr of culture in [U-13C]glutamine. Relative abundances of citrate isotopologues were determined by normalizing total citrate abundance measured by mass spectrometry against cellular protein for each sample then multiplying by the fractional abundance of each isotopologue. (F) Effect of silencing MPC1 or MPC2 on formation of citrate m+6 after 6 hr of culture in [U-13C]glutamine. (G) Citrate isotopologues in primary human fibroblasts of varying MPC1 genotypes after culture in [U-13C]glutamine. Data are the average and SD of three independent cultures. *p < 0.05; **p < 0.01; ***p < 0.001. See also Figure S1.

Figure 4. Kinetic Analysis of the Metabolic Effects of Blocking Mitochondrial Pyruvate Transport (A) Summation of 13C spectra acquired over 2 min of exposure of SFxL cells to hyperpolarized [1-13C] pyruvate. Resonances are indicated for [1-13C] pyruvate (Pyr1), the hydrate of [1-13C]pyruvate (Pyr1-Hydr), [1-13C]lactate (Lac1), [1-13C]alanine (Ala1), and H[13C]O3 (Bicarbonate). (B) Time evolution of appearance of Lac1, Ala1, and bicarbonate in control and UK5099-treated cells. (C) Relative 13C NMR signals for Lac1, Ala1, and bicarbonate. Each signal is summed over the entire acquisition and expressed as a fraction of total 13C signal. (D) Quantity of intracellular and secreted alanine in control and UK5099-treated cells. Data are the average and SD of three independent cultures. *p < 0.05; ***p < 0.001. See also Figure S2.

Figure 5. Inhibiting Mitochondrial Pyruvate Transport Enhances the Contribution of Glutamine to Fatty Acid Synthesis (A) Mass isotopologues of palmitate extracted from cells cultured with [U-13C] glucose or [U-13C]glutamine, with or without 200 mM UK5099. For simplicity, only even-labeled isotopologues (m+2, m+4, etc.) are shown. (B) Fraction of lipogenic acetyl-CoA derived from glucose or glutamine with or without 200 mM UK5099. Data are the average and SD of three independent cultures. ***p < 0.001. See also Figure S3.

Figure 6. Blockade of Mitochondrial Pyruvate Transport Induces GDH (A) Two routes by which glutamate can be converted to AKG. Blue and green symbols are the amide (g) and amino (a) nitrogens of glutamine, respectively. (B) Utilization and secretion of glutamine (Gln), glutamate (Glu), and ammonia (NH4+) by SFxL cells with and without 200 mM UK5099. (C) Secretion of 15N-alanine and 15NH4+ derived from [a-15N]glutamine in SFxL cells expressing a control shRNA (shCtrl) or either of two shRNAs directed against GLUD1 (shGLUD1-A and shGLUD1-B). (D) Left: Phosphorylation of AMPK (T172) and acetyl-CoA carboxylase (ACC, S79) during treatment with 200 mM UK5099. Right: Steady-state levels of ATP 24 hr after addition of vehicle or 200 mM UK5099. (E) Fractional contribution of the m+6 isotopologue to total citrate in shCtrl, shGLUD1-A, and shGLUD1-B SFxL cells cultured in [U-13C]glutamine with or without 200 mM UK5099. Data are the average and SD of three independent cultures. *p < 0.05; **p < 0.01; ***p < 0.001. See also Figure S4.

Figure 7. GDH Sustains Growth and Viability during Suppression of Mitochondrial Pyruvate Transport (A) Relative growth inhibition of shCtrl, shGLUD1A, and shGLUD1-B SFxL cells treated with 50 mM UK5099 for 3 days. (B) Relative growth inhibition of SFxL cells treated with combinations of 50 mM of the GDH inhibitor EGCG, 10 mM of the GLS inhibitor BPTES, and 200 mM UK5099 for 3 days. (C) Relative cell death assessed by trypan blue staining in SFxL cells treated as in (B). (D) Relative cell death assessed by trypan blue staining in SF188 cells treated as in (B) for 2 days. (E) (Left) Growth of A549-derived subcutaneous xenografts treated with vehicle (saline), EGCG, CHC, or EGCG plus CHC (n = 4 for each group). Data are the average and SEM. Right: Lactate abundance in extracts of each tumor harvested at the end of the experiment. Data in (A)–(D) are the average and SD of three independent cultures. NS, not significant; *p < 0.05; **p < 0.01; ***p < 0.001. See also Figure S5.

Mitochondrial metabolism complements glycolysis as a source of energy and biosynthetic precursors. Precursors for lipids, proteins, and nucleic acids are derived from the TCA cycle. Maintaining pools of these intermediates is essential, even under circumstances of nutrient limitation or impaired supply of glucose-derived pyruvate to the mitochondria. Glutamine’s ability to produce both acetyl-CoA and OAA allows it to support TCA cycle activity as a sole carbon source and imposes a greater cellular dependence on glutamine metabolism when MPC function or pyruvate supply is impaired. Other anaplerotic amino acids could also supply both OAA and acetyl-CoA, providing flexible support for the TCA cycle when glucose is limiting. Although fatty acids are an important fuel in some cancer cells (Caro et al., 2012), and fatty acid oxidation is induced upon MPC inhibition, this pathway produces acetyl-CoA but not OAA. Thus, fatty acids would need to be oxidized along with an anaplerotic nutrient in order to enable the cycle to function as a biosynthetic hub. Notably, enforced MPC overexpression also impairs growth of some tumors (Schell et al., 2014), suggesting that maximal growth may require MPC activity to be maintained within a narrow window. After decades of research on mitochondrial pyruvate transport, molecular components of the MPC were recently reported (Halestrap, 2012; Schell and Rutter, 2013). MPC1 and MPC2 form a heterocomplex in the inner mitochondrial membrane, and loss of either component impairs pyruvate import, leading to citrate depletion (Bricker et al., 2012; Herzig et al., 2012). Mammalian cells lacking functional MPC1 display normal glutamine-supported respiration (Bricker et al., 2012), consistent with our observation that glutamine supplies the TCA cycle in absence of pyruvate import. We also observed that isolated mitochondria produce fully labeled citrate from glutamine, indicating that this pathway operates as a self-contained mechanism to maintain TCA cycle function. Recently, two well-known classes of drugs have unexpectedly been shown to inhibit MPC. First, thiazolidinediones, commonly used as insulin sensitizers, impair MPC function in myoblasts (Divakaruni et al.,2013). Second, the phosphodiesterase inhibitor Zaprinast inhibits MPC in the retina and brain (Du et al., 2013b). Zaprinast also induced accumulation of aspartate, suggesting that depletion of acetyl-CoA impaired the ability of a new turn of the TCA cycle to be initiated from OAA; as a consequence, OAA was transaminated to aspartate. We noted a similar phenomenon in cancer cells, suggesting that UK5099 elicits a state in which acetyl-CoA supply is insufficient to avoid OAA accumulation. Unlike UK5099, Zaprinast did not induce glutamine-dependent acetyl-CoA formation. This may be related to the reliance of isolated retinas on glucose rather than glutamine to supply TCA cycle intermediates or the exquisite system used by retinas to protect glutamate from oxidation (Du et al., 2013a). Zaprinast was also recently shown to inhibit glutaminase (Elhammali et al., 2014), which would further reduce the contribution of glutamine to the acetyl-CoA pool.

Comment by reader –

The results from these studies served as a good
reason to attempt the vaccination of patients using p53-
derived peptides, and a several clinical trials are currently
in progress. The most advanced work used a long
synthetic peptide mixture derived from p53 (p53-SLP; ISA
Pharmaceuticals, Bilthoven, the Netherlands) (Speetjens
et al., 2009; Shangary et al., 2008; Van der Burg et al.,
2001). The vaccine is delivered in the adjuvant setting
and induces T helper type cells.

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Expanding the Genetic Alphabet and Linking the Genome to the Metabolome


English: The citric acid cycle, also known as ...

English: The citric acid cycle, also known as the tricarboxylic acid cycle (TCA cycle) or the Krebs cycle. Produced at WikiPathways. (Photo credit: Wikipedia)

Expanding the Genetic Alphabet and Linking the Genome to the Metabolome

 

Reporter& Curator:  Larry Bernstein, MD, FCAP

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Unlocking the diversity of genomic expression within tumorigenesis and “tailoring” of therapeutic options

1. Reshaping the DNA landscape between diseases and within diseases by the linking of DNA to treatments

In the NEW York Times of 9/24,2012 Gina Kolata reports on four types of breast cancer and the reshaping of breast cancer DNA treatment based on the findings of the genetically distinct types, which each have common “cluster” features that are driving many cancers.  The discoveries were published online in the journal Nature on Sunday (9/23).  The study is considered the first comprehensive genetic analysis of breast cancer and called a roadmap to future breast cancer treatments.  I consider that if this is a landmark study in cancer genomics leading to personalized drug management of patients, it is also a fitting of the treatment to measurable “combinatorial feature sets” that tie into population biodiversity with respect to known conditions.   The researchers caution that it will take years to establish transformative treatments, and this is clearly because in the genetic types, there are subsets that have a bearing on treatment “tailoring”.   In addition, there is growing evidence that the Watson-Crick model of the gene is itself being modified by an expansion of the alphabet used to construct the DNA library, which itself will open opportunities to explain some of what has been considered junk DNA, and which may carry essential information with respect to metabolic pathways and pathway regulation.  The breast cancer study is tied to the  “Cancer Genome Atlas” Project, already reported.  It is expected that this work will tie into building maps of genetic changes in common cancers, such as, breast, colon, and lung.  What is not explicit I presume is a closely related concept, that the translational challenge is closely related to the suppression of key proteomic processes tied into manipulating the metabolome.

Saha S. Impact of evolutionary selection on functional regions: The imprint of evolutionary selection on ENCODE regulatory elements is manifested between species and within human populations. 9/12/2012. PharmaceuticalIntelligence.Wordpress.com

Hawrylycz MJ, Lein ES, Guillozet-Bongaarts AL, Shen EH, Ng L, et al. An anatomically comprehensive atlas of the adult human brain transcriptome. Nature  Sept 14-20, 2012

Sarkar A. Prediction of Nucleosome Positioning and Occupancy Using a Statistical Mechanics Model. 9/12/2012. PharmaceuticalIntelligence.WordPress.com

Heijden et al.   Connecting nucleosome positions with free energy landscapes. (Proc Natl Acad Sci U S A. 2012, Aug 20 [Epub ahead of print]).  http://www.ncbi.nlm.nih.gov/pubmed/22908247

2. Fiddling with an expanded genetic alphabet – greater flexibility in design of treatment (pharmaneogenesis?)

Diagram of DNA polymerase extending a DNA stra...

Diagram of DNA polymerase extending a DNA strand and proof-reading. (Photo credit: Wikipedia)

A clear indication of this emerging remodeling of the genetic alphabet is a new
study led by scientists at The Scripps Research Institute appeared in the
June 3, 2012 issue of Nature Chemical Biology that indicates the genetic code as
we know it may be expanded to include synthetic and unnatural sequence pairing (Study Suggests Expanding the Genetic Alphabet May Be Easier than Previously Thought, Genome). They infer that the genetic instructions for living organisms
that is composed of four bases (C, G, A and T)— is open to unnatural letters. An expanded “DNA alphabet” could carry more information than natural DNA, potentially coding for a much wider range of molecules and enabling a variety of powerful applications. The implications of the application of this would further expand the translation of portions of DNA to new transciptional proteins that are heretofore unknown, but have metabolic relavence and therapeutic potential. The existence of such pairing in nature has been studied in Eukariotes for at least a decade, and may have a role in biodiversity. The investigators show how a previously identified pair of artificial DNA bases can go through the DNA replication process almost as efficiently as the four natural bases.  This could as well be translated into human diversity, and human diseases.

The Romesberg laboratory collaborated on the new study and his lab have been trying to find a way to extend the DNA alphabet since the late 1990s. In 2008, they developed the efficiently replicating bases NaM and 5SICS, which come together as a complementary base pair within the DNA helix, much as, in normal DNA, the base adenine (A) pairs with thymine (T), and cytosine (C) pairs with guanine (G). It had been clear that their chemical structures lack the ability to form the hydrogen bonds that join natural base pairs in DNA. Such bonds had been thought to be an absolute requirement for successful DNA replication, but that is not the case because other bonds can be in play.

The data strongly suggested that NaM and 5SICS do not even approximate the edge-to-edge geometry of natural base pairs—termed the Watson-Crick geometry, after the co-discoverers of the DNA double-helix. Instead, they join in a looser, overlapping, “intercalated” fashion that resembles a ‘mispair.’ In test after test, the NaM-5SICS pair was efficiently replicable even though it appeared that the DNA polymerase didn’t recognize it. Their structural data showed that the NaM-5SICS pair maintain an abnormal, intercalated structure within double-helix DNA—but remarkably adopt the normal, edge-to-edge, “Watson-Crick” positioning when gripped by the polymerase during the crucial moments of DNA replication. NaM and 5SICS, lacking hydrogen bonds, are held together in the DNA double-helix by “hydrophobic” forces, which cause certain molecular structures (like those found in oil) to be repelled by water molecules, and thus to cling together in a watery medium.

The finding suggests that NaM-5SICS and potentially other, hydrophobically bound base pairs could be used to extend the DNA alphabet and that Evolution’s choice of the existing four-letter DNA alphabet—on this planet—may have been developed allowing for life based on other genetic systems.

3.  Studies that consider a DNA triplet model that includes one or more NATURAL nucleosides and looks closely allied to the formation of the disulfide bond and oxidation reduction reaction.

This independent work is being conducted based on a similar concep. John Berger, founder of Triplex DNA has commented on this. He emphasizes Sulfur as the most important element for understanding evolution of metabolic pathways in the human transcriptome. It is a combination of sulfur 34 and sulphur 32 ATMU. S34 is element 16 + flourine, while S32 is element 16 + phosphorous. The cysteine-cystine bond is the bridge and controller between inorganic chemistry (flourine) and organic chemistry (phosphorous). He uses a dual spelling, using  sulfphur to combine the two referring to the master catalyst of oxidation-reduction reactions. Various isotopic alleles (please note the duality principle which is natures most important pattern). Sulfphur is Methionine, S adenosylmethionine, cysteine, cystine, taurine, gluthionine, acetyl Coenzyme A, Biotin, Linoic acid, H2S, H2SO4, HSO3-, cytochromes, thioredoxin, ferredoxins, purple sulfphur anerobic bacteria prokaroytes, hydrocarbons, green sulfphur bacteria, garlic, penicillin and many antibiotics; hundreds of CSN drugs for parasites and fungi antagonists. These are but a few names which come to mind. It is at the heart of the Krebs cycle of oxidative phosphorylation, i.e. ATP. It is also a second pathway to purine metabolism and nucleic acids. It literally is the key enzymes between RNA and DNA, ie, SH thiol bond oxidized to SS (dna) cysteine through thioredoxins, ferredoxins, and nitrogenase. The immune system is founded upon sulfphur compounds and processes. Photosynthesis Fe4S4 to Fe2S3 absorbs the entire electromagnetic spectrum which is filtered by the Allen belt some 75 miles above earth. Look up chromatium vinosum or allochromatium species.  There is reasonable evidence it is the first symbiotic species of sulfphur anerobic bacteria (Fe4S4) with high potential mvolts which drives photosynthesis while making glucose with H2S.
He envisions a sulfphur control map to automate human metabolism with exact timing sequences, at specific three dimensional coordinates on Bravais crystalline lattices. He proposes adding the inosine-xanthosine family to the current 5 nucleotide genetic code. Finally, he adds, the expanded genetic code is populated with “synthetic nucleosides and nucleotides” with all kinds of customized functional side groups, which often reshape nature’s allosteric and physiochemical properties. The inosine family is nature’s natural evolutionary partner with the adenosine and guanosine families in purine synthesis de novo, salvage, and catabolic degradation. Inosine has three major enzymes (IMPDH1,2&3 for purine ring closure, HPGRT for purine salvage, and xanthine oxidase and xanthine dehydrogenase.

English: DNA replication or DNA synthesis is t...

English: DNA replication or DNA synthesis is the process of copying a double-stranded DNA molecule. This process is paramount to all life as we know it. (Photo credit: Wikipedia)

3. Nutritional regulation of gene expression,  an essential role of sulfur, and metabolic control 

Finally, the research carried out for decades by Yves Ingenbleek and the late Vernon Young warrants mention. According to their work, sulfur is again tagged as essential for health. Sulfur (S) is the seventh most abundant element measurable in human tissues and its provision is mainly insured by the intake of methionine (Met) found in plant and animal proteins. Met is endowed with unique functional properties as it controls the ribosomal initiation of protein syntheses, governs a myriad of major metabolic and catalytic activities and may be subjected to reversible redox processes contributing to safeguard protein integrity.

Consuming diets with inadequate amounts of methionine (Met) are characterized by overt or subclinical protein malnutrition, and it has serious morbid consequences. The result is reduction in size of their lean body mass (LBM), best identified by the serial measurement of plasma transthyretin (TTR), which is seen with unachieved replenishment (chronic malnutrition, strict veganism) or excessive losses (trauma, burns, inflammatory diseases).  This status is accompanied by a rise in homocysteine, and a concomitant fall in methionine.  The ratio of S to N is quite invariant, but dependent on source.  The S:N ratio is typical 1:20 for plant sources and 1:14.5 for animal protein sources.  The key enzyme involved with the control of Met in man is the enzyme cystathionine-b-synthase, which declines with inadequate dietary provision of S, and the loss is not compensated by cobalamine for CH3- transfer.

As a result of the disordered metabolic state from inadequate sulfur intake (the S:N ratio is lower in plants than in animals), the transsulfuration pathway is depressed at cystathionine-β-synthase (CβS) level triggering the upstream sequestration of homocysteine (Hcy) in biological fluids and promoting its conversion to Met. They both stimulate comparable remethylation reactions from homocysteine (Hcy), indicating that Met homeostasis benefits from high metabolic priority. Maintenance of beneficial Met homeostasis is counterpoised by the drop of cysteine (Cys) and glutathione (GSH) values downstream to CβS causing reducing molecules implicated in the regulation of the 3 desulfuration pathways

4. The effect on accretion of LBM of protein malnutrition and/or the inflammatory state: in closer focus

Hepatic synthesis is influenced by nutritional and inflammatory circumstances working concomitantly and liver production of  TTR integrates the dietary and stressful components of any disease spectrum. Thus we have a depletion of visceral transport proteins made by the liver and fat-free weight loss secondary to protein catabolism. This is most accurately reflected by TTR, which is a rapid turnover protein, but it is involved in transport and is essential for thyroid function (thyroxine-binding prealbumin) and tied to retinol-binding protein. Furthermore, protein accretion is dependent on a sulfonation reaction with 2 ATP.  Consequently, Kwashiorkor is associated with thyroid goiter, as the pituitary-thyroid axis is a major sulfonation target. With this in mind, it is not surprising why TTR is the sole plasma protein whose evolutionary patterns closely follow the shape outlined by LBM fluctuations. Serial measurement of TTR therefore provides unequaled information on the alterations affecting overall protein nutritional status. Recent advances in TTR physiopathology emphasize the detecting power and preventive role played by the protein in hyper-homocysteinemic states.

Individuals submitted to N-restricted regimens are basically able to maintain N homeostasis until very late in the starvation processes. But the N balance study only provides an overall estimate of N gains and losses but fails to identify the tissue sites and specific interorgan fluxes involved. Using vastly improved methods the LBM has been measured in its components. The LBM of the reference man contains 98% of total body potassium (TBK) and the bulk of total body sulfur (TBS). TBK and TBS reach equal intracellular amounts (140 g each) and share distribution patterns (half in SM and half in the rest of cell mass). The body content of K and S largely exceeds that of magnesium (19 g), iron (4.2 g) and zinc (2.3 g).

TBN and TBK are highly correlated in healthy subjects and both parameters manifest an age-dependent curvilinear decline with an accelerated decrease after 65 years. Sulfur Methylation (SM) undergoes a 15% reduction in size per decade, an involutive process. The trend toward sarcopenia is more marked and rapid in elderly men than in elderly women decreasing strength and functional capacity. The downward SM slope may be somewhat prevented by physical training or accelerated by supranormal cytokine status as reported in apparently healthy aged persons suffering low-grade inflammation or in critically ill patients whose muscle mass undergoes proteolysis.

5.  The results of the events described are:

  • Declining generation of hydrogen sulfide (H2S) from enzymatic sources and in the non-enzymatic reduction of elemental S to H2S.
  • The biogenesis of H2S via non-enzymatic reduction is further inhibited in areas where earth’s crust is depleted in elemental sulfur (S8) and sulfate oxyanions.
  • Elemental S operates as co-factor of several (apo)enzymes critically involved in the control of oxidative processes.

Combination of protein and sulfur dietary deficiencies constitute a novel clinical entity threatening plant-eating population groups. They have a defective production of Cys, GSH and H2S reductants, explaining persistence of an oxidative burden.

6. The clinical entity increases the risk of developing:

  • cardiovascular diseases (CVD) and
  • stroke

in plant-eating populations regardless of Framingham criteria and vitamin-B status.
Met molecules supplied by dietary proteins are submitted to transmethylation processes resulting in the release of Hcy which:

  • either undergoes Hcy — Met RM pathways or
  • is committed to transsulfuration decay.

Impairment of CβS activity, as described in protein malnutrition, entails supranormal accumulation of Hcy in body fluids, stimulation of activity and maintenance of Met homeostasis. The data show that combined protein- and S-deficiencies work in concert to deplete Cys, GSH and H2S from their body reserves, hence impeding these reducing molecules to properly face the oxidative stress imposed by hyperhomocysteinemia.

Although unrecognized up to now, the nutritional disorder is one of the commonest worldwide, reaching top prevalence in populated regions of Southeastern Asia. Increased risk of hyperhomocysteinemia and oxidative stress may also affect individuals suffering from intestinal malabsorption or westernized communities having adopted vegan dietary lifestyles.

Ingenbleek Y. Hyperhomocysteinemia is a biomarker of sulfur-deficiency in human morbidities. Open Clin. Chem. J. 2009 ; 2 : 49-60.

7. The dysfunctional metabolism in transitional cell transformation

A third development is also important and possibly related. The transition a cell goes through in becoming cancerous tends to be driven by changes to the cell’s DNA. But that is not the whole story. Large-scale techniques to the study of metabolic processes going on in cancer cells is being carried out at Oxford, UK in collaboration with Japanese workers. This thread will extend our insight into the metabolome. Otto Warburg, the pioneer in respiration studies, pointed out in the early 1900s that most cancer cells get the energy they need predominantly through a high utilization of glucose with lower respiration (the metabolic process that breaks down glucose to release energy). It helps the cancer cells deal with the low oxygen levels that tend to be present in a tumor. The tissue reverts to a metabolic profile of anaerobiosis.  Studies of the genetic basis of cancer and dysfunctional metabolism in cancer cells are complementary. Tomoyoshi Soga’s large lab in Japan has been at the forefront of developing the technology for metabolomics research over the past couple of decades (metabolomics being the ugly-sounding term used to describe research that studies all metabolic processes at once, like genomics is the study of the entire genome).

Their results have led to the idea that some metabolic compounds, or metabolites, when they accumulate in cells, can cause changes to metabolic processes and set cells off on a path towards cancer. The collaborators have published a perspective article in the journal Frontiers in Molecular and Cellular Oncology that proposes fumarate as such an ‘oncometabolite’. Fumarate is a standard compound involved in cellular metabolism. The researchers summarize that shows how accumulation of fumarate when an enzyme goes wrong affects various biological pathways in the cell. It shifts the balance of metabolic processes and disrupts the cell in ways that could favor development of cancer.  This is of particular interest because “fumarate” is the intermediate in the TCA cycle that is converted to malate.

Animation of the structure of a section of DNA...

Animation of the structure of a section of DNA. The bases lie horizontally between the two spiraling strands. (Photo credit: Wikipedia)

The Keio group is able to label glucose or glutamine, basic biological sources of fuel for cells, and track the pathways cells use to burn up the fuel.  As these studies proceed, they could profile the metabolites in a cohort of tumor samples and matched normal tissue. This would produce a dataset of the concentrations of hundreds of different metabolites in each group. Statistical approaches could suggest which metabolic pathways were abnormal. These would then be the subject of experiments targeting the pathways to confirm the relationship between changed metabolism and uncontrolled growth of the cancer cells.

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