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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

References

[1] R.A. Cairns, I.S. Harris, T.W. Mak, Cancer 11 (2011) 85–95.
[2] O. Warburg, Science 123 (1956) 309–314.
[3] G.L. Semenza, D.Artemov, A.Bedi, …, J. Simons, P. Taghavi, H. Zhong, Novartis Found. Symp. 240 (2001) 251–260 (discussion 260–254).
[4] N.C. Denko, Cancer 8 (2008) 705–713.
[5] C. Chen, N. Pore, A. Behrooz, F. Ismail-Beigi, A. Maity, J. Biol. Chem. 276 (2001) 9519–9525.
[6] J.Lum, T.Bui, M.Gruber, J.D.Gordan, R.J.DeBerardinis,.. ,C.B. Thompson, Genes Dev. 21 (2007) 1037–1049.
[7] J.T. Chi, Z. Wang, D.S. Nuyten, E.H. Rodriguez, .., P.O. Brown, PLoS Med.
3 (2006) e47.
[8] G.L. Semenza, Cancer 3 (2003) 721–732.

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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Mitochondrial Metabolism and Cardiac Function

Curator: Larry H Bernstein, MD, FACP

This article is the SECOND in a four-article Series covering the topic of the Roles of the Mitochondria in Cardiovascular Diseases. They include the following;

The mitochondrion serves a critical role as a platform for
  • energy transduction,
  • signaling, and
  • cell death pathways
relevant to common diseases of the myocardium such as heart failure. This review focuses on the molecular regulatory events involved in mitochondrial energy metabolism.
This is followed by the derangements known to occur in the development of heart failure.

 Cardiac Energy Metabolism

All cellular processes are driven by ATP-dependent pathways. The heart has perpetually high energy demands related to
  • the maintenance of specialized cellular processes, including
    • ion transport,
    • sarcomeric function, and
    • intracellular Ca2+ homeostasis.
Myocardial workload (energy demand) and energy substrate availability (supply) are in continual flux. Thus, ATP-generating pathways must

  • respond proportionately to dynamic fluctuations in physiological demands and fuel delivery.
In order to support contractile activity, the human heart requires
  • a daily synthesis of approximately 30kg of ATP, via
    • oxidative phosphorylation at
    • the inner mitochondrial membrane.
These metabolic  processes are regulated, involving
  • allosteric control of enzyme activity,
  • signal transduction events, and
  • the activity of genes encoding
    • rate-limiting enzymes and proteins.
Catabolism of exogenous substrates ,such as
  • fatty acids,
  • glucose,
  • pyruvate,
  • lactate and
  • ketone bodies,
generates most of the reduced compounds,
  • NADH (nicotinamide adenine dinucleotide, reduced) and
  • FADH2 (flavin adenine dinucleotide, reduced),
which are necessary for mitochondrial electron transport (Fig. 1).
Fig 1  Fatty acid beta-oxidation and the Krebs cycle produce
  1. nicotinamide adenine dinucleotide, reduced (NADH) and
  2. flavin adenine dinucleotide, reduced(FADH2),
which are oxidized by complexes I and II, respectively, of
Electrons are transferred through the chain to the final acceptor, namely oxygen(O2).
The free energy from electron transfer
  1. is used to pump hydrogen out of the mitochondria and
  2. generate an electrochemical gradient across the inner mitochondrial membrane.
This gradient is the driving force for ATP synthesis via the ATP synthase. Alternatively,
H can enter the mitochondria by a mechanism not coupled to ATP synthesis, via
  • the uncoupling proteins(UCPs), which results in the dissipation of energy.

[ANT, adenine nucleotide translocase; CoA, coenzymeA; FAT, fatty acid transporter; GLUT, glucose transporter;

NAD, nicotinamide adenine dinucleotide; TCA, tricarboxylic acid].

Cardiac Energy Metabolic Pathways

 Oxidation of free fatty acids (FFAs) and glucose in mitochondria
  • accounts for the vast majority of ATP generation in the healthy adult heart.
FFAs are the preferred substrate in the adult myocardium,
  • supplying 70-90% of total ATP.
FAs derived from circulating triglyceride-rich lipoproteins and albumin bound nonesterified FAs
  • are oxidized in the mitochondrial matrix by the process of beta-oxidation (FAO), whereas
pyruvate derived from glucose and lactate
  • is oxidized by the pyruvate-dehydrogenase (PDH) complex,
    • localized within the inner mitochondrial membrane.
Acetyl-CoA, derived from both pathways,
  • enters the tricarboxylic acid (TCA) cycle.
Reduced flavin adenine dinucleotide (FADH2) and NADH are generated, respectively, via
  • substrate flux through the
The reducing equivalents enter the electron transport (ET) chain,
  • producing an electrochemical gradient across the mitochondrial membrane
  • that drives ATP synthesis in the presence of molecular oxygen (oxidative phosphorylation).
The relative contributions of each of these substrates are determined
  • by their availability
  • cardiac workload and
  • hormonal status
In the healthy, normal heart, the ATP requirement is largely met in the actively metabolic mitochondria by
  • the catabolism of free fatty acids (FFAs) via beta-oxidation,
  • the tricarboxylic acid cycle and
  • oxidative phosphorylation
giving rise to a greater ATP yield per C2 unit than with glucose.
The relative contribution of glucose to the mitochondrial acetyl-coenzyme A (CoA) pool increases
  • during the postprandial period,
    • when the heart is insulin stimulated, and
  • during exercise
  • hypoxia, or
  • ischemia
when glucose is favored as a more oxygen-efficient substrate than
  • FFAs (greater ATP yield per oxygen molecule consumed).
Substrate switching in the heart can also be achieved by
  • acute alterations in transcriptional regulation of key metabolic enzymes
  • in response to alterations in substrate levels and oxygen availability, or
  • indeed by the intracellular circadian clock.
This continual process of fine adjustment in fuel selection
  • allows cardiac mitochondria to function
  • under a range of metabolic conditions to meet the high energy demands of the heart.
Mitochondrial enzymes are encoded by both nuclear and mitochondrial genes.
All of the enzymes of
  1. beta-oxidation and the TCA cycle, and
  2. most of the subunits of Electron Transfer/Oxidative Phosphorylation,
    • are encoded by nuclear genes.
The mitochondrial genome is comprised of
  • 1 circular double-stranded chromosome that encodes
  • 13 ET chain subunits within complexes I, III, and IV.
Since mitochondrial number and function require both nuclear and mitochondrial-encoded genes,
  • coordinated mechanisms exist to regulate the 2 genomes and
  • determine overall cardiac oxidative capacity.
In addition, distinct pathways exist to coordinately regulate
  • nuclear genes encoding component mitochondrial pathways.

Early Postnatal Low-protein Nutrition, Metabolic Programming and
the Autonomic Nervous System in Adult Life.

JC de Oliveira, S Grassiolli, C Gravena, PCF de Mathias  Nutr Metab. 2012;9(80)

The developmental origins of health and disease (DOHaD) hypothesis stipulates that adult metabolic disease

  • may be programmed during the perinatal stage.

A large amount of evidence suggests that the etiology of obesity is not only related to food abundance

  • but also to food restriction during early life.

Protein restriction during lactation has been used as a rat model of metabolic programming

  • to study the impact of perinatal malnutrition on adult metabolism.

In contrast to protein restriction during fetal life, protein restriction during lactation did not appear to cause

  • either obesity or the hallmarks of metabolic syndrome, such as hyperinsulinemia, when individuals reached adulthood.

Protein restriction provokes body underweight and hypoinsulinemia.
Hypoinsulinemia programs adult rats to maintain normoglycemia,

  • pancreatic β-cells are less sensitive to secretion stimuli:
  1.  glucose and
  2. cholinergic agents.

These pancreatic dysfunctions are attributed to an imbalance of ANS activity

  • recorded in adult rats that experienced maternal protein restriction

Several studies have reported that the ANS activity is altered in under- or malnourished organisms. After weaning,

  • rats fed a chronically protein-deficient diet exhibited low activity of the vagus nerve,
  • whereas high sympathetic activity was recorded

These data were in agreement with a low insulin response to glucose.
Pancreatic islets isolated from protein-restricted rats showed

  • weak glucose and cholinergic insulin tropic responses
  • suggesting that pancreatic β-cell dysfunction may be attributed to altered ANS activity

Food abundance or restriction with regard to body weight control involves changes in

  • metabolic homeostasis and ANS balance activity.

Although the secretion of insulin by the pancreatic β-cells is increased in people who were overweight,

  • it is diminished in people who were underweight.

Changes in the ANS activity may constitute the mechanisms underlying the β-cell dysfunction:

  • the high PNS tonus observed in obese individuals constantly potentiates insulin secretion,
  • whereas the low activity reported in underweight individuals is associated with a weak cholinergic insulin tropic effect.

Under Nutrition Early in Life and Epigenetic Modifications, Association With Metabolic Diseases Risk

relevant to this issue is the role of epigenetic changes in the increased risk of developing metabolic diseases,

  • such as type 2 diabetes and obesity, later in life.

Epigenetic mechanisms, such as DNA methylation and/or nucleoprotein acetylation/methylation, are

  • crucial to the normal/physiological development of several tissues in mammals, and
  • they involve several mechanisms to guarantee fluctuations of enzymes and other proteins that regulate the metabolism.

The intrauterine phase of development is particularly important for the genomic processes related to genes associated with metabolic pathways.
This phase of life may be particularly important for nutritional disturbance. In humans who experienced the Dutch famine Winter in 1944–1945 and
in rats that were deprived of food in utero, epigenetic modifications were detected in

  • the insulin-like growth factor 2 (IGF2) and
  • pancreatic and duodenal home box 1 (Pdx1),

the major factors involved in pancreas development and pancreatic β-cell maturation.
The pancreas and the pancreatic β-cells develop during the embryonic phase, but the postnatal life is also crucial for

  • the maintenance processes that control the β-cell mass:
  1. proliferation,
  2. neogenesis
  3. apoptosis.

Nutritional Restriction to the Fetus: A Risk of Obesity Onset

If an abundant diet is offered to people who have been undernourished during the perinatal life,

  • this opportunity induces a metabolic shift toward the storage of energy and high fat tissue accumulation

The concept of Developmental Origins of Health and Disease extends to any type of stressful situations that may

  • predispose babies or pups to develop metabolic disorders when they reach adulthood.

Programmed Metabolism and Insulin Secretion-coupling Process

What are the mechanisms involved in the low glucose insulin tropic response observed in low protein-programmed lean rats?
The pancreatic β-cells secrete insulin when stimulated mostly by glucose. However, several nutrients, such as

  • amino acids,
  • fatty acids,
  • and their metabolites,

stimulate cellular metabolism and increase ATP production.

ATP-sensitive potassium channels (KATP) are inactivated by an increased ATP/ADP ratio. This provokes

  • membrane depolarization and
  • the activation of voltage-dependent calcium channels.

These ionic changes increase the intracellular calcium concentration, which is involved in

  • the export of insulin to the bloodstream.

Glucose may also stimulate insulin secretion by alternative pathways involving KATP channels.

Programmed Metabolism and Insulin Tropic Effects of Neurotransmitters

Insulin release is modulated by non-nutrient secretagogues, such as neurotransmitters, which

  • enhance or inhibit glucose-stimulated insulin secretion.

Pancreatic β-cells contain several receptors for neurotransmitters and Neuropeptide, such as

  • adrenoceptors and cholinergic muscarinic receptors (mAChRs).

These receptors are stimulated by efferent signals from the central nervous system, including the ANS,

  • throughout their neural ends for pancreatic β-cells.

During blood glucose level oscillations, the β-cells receive inputs from

  • the parasympathetic and sympathetic systems to participate in glycemic regulation.

Overall, acetylcholine promotes the potentiation of glucose-induced insulin secretion,

  • whereas noradrenaline and adrenaline inhibit this response.

Functional studies of mAChR subtypes have revealed that M1 and particularly M3 are the receptors that are involved in

  • the insulin tropic effect of acetylcholine.

Interestingly, it was reported that M3mAChR gene knockout mice are

  • underweight,
  • hypophagic and
  • hypoinsulinemic,

as are adult rats that were protein-restricted during lactation.
The pancreatic islets from M3mAChR mice (-/-) showed a reduced secretory response to cholinergic agonists.
In studies using transgenic mice in which the pancreatic β-cell M3mAChRs are chronically stimulated,

  • an improvement of glycemic control has been observed

Adult male rat offspring from whose mothers were protein-restricted during lactation

  • exhibit a low PNS activity.

Evidence suggests that ANS changes may contribute to the impairment of glycemic homeostasis in metabolically programmed rats.

Pathways involved in cardiac energy metabolism.

FA and glucose oxidation are the main ATP-generating pathways in the adult mammalian heart.
Acetyl-CoA derived from FA and glucose oxidation is
  • further oxidized in the TCA cycle to generate NADH and FADH2, which
  • enter the ET/oxidative phosphorylation pathway and drive ATP synthesis.
Genes encoding enzymes involved at multiple steps of these metabolic pathways
  1. uptake,
  2. esterification,
  3. mitochondrial transport,
  4. and oxidation
are transcriptionally regulated by PGC-1a
  • with its nuclear receptor partners, including PPARs and ERRs .
Glucose uptake/oxidation and electron transport/oxidative phosphorylation pathways are also regulated by PGC-1a via
  • other transcription factors, such as MEF-2 and NRF-1.

[Cyt c, cytochrome c]

 Fetal metabolism of carbohydrate utilization

This reviewer poses the question of whether the fetal cardiac metabolism, which is characterized by a (facultative) anaerobic glycolysis,
  • results in lactate production that is not redirected into the TCA cycle.
An unexamined, but related question is whether there is an associated change in the ratio of
  • mitochondrial to cytoplasmic malate dehydrogenase isoenzyme activity (m-MDH:c-MDH).
The fetal heart operates without oxygenation from a functioning lung, bathed in amniotic fluid.
An enzymatic feature might be expressed in a facultative anaerobic cytplasmic glycolytic pathway characterized by
  • a decrease in the h-type lactate dehydrogenase (LD) isoenzyme(s) (LD1, LD2) with a predominance of
  • the m-type LD isoenzymes (LD3, LD4, LD5).
The observation here is that the heart muscle is a syncytium, and it functions at a highly regulated rate,
  • not with the spurts of activity seen in skeletal muscle.
In another article in this series, there are morphological changes that occur in the heart mitochondria, and
  • there are three locations, as if the organelle itself were an organ.
The normal functioning myocardium can utilize lactic acid accumulated in the bloodstream during extreme exercise as fuel.
This is a virtue of mitochondrial function.  There is a significant functional difference between the roles of the h- and m-type LD isoenzymes.
The h-type is a regulatory enzyme that forms a complex as NADH is converted to NAD+ between the
  • LD (H4, H3M; LD1, LD2),
  • oxidized pyridine nucleotide coenzyme, and
  • pyruvate
The complex forms in 200 msec as observed in the Aminco-Morrow stop-flow analyzer.  This is not the case for the m-type isoenzyme.
I presume that it is not a factor in embryonic heart.  It would become a factor after birth with the expansion of the lungs.
This would also bring to the discussion the effect of severe restrictive lung disease on cardiac metabolism.

Related References:

LH Bernstein,  patents: Malate dehydrogenase method,  The lactate dehydrogenase method
LH Bernstein, J Everse. Determination of the isoenzyme levels of lactate dehydrogenase. Methods Enzymol 1975; 41 47-52    ICID: 825516
LH Bernstein, J Everse, N Shioura, PJ Russell. Detection of cardiac damage using a steady state assay for lactate dehydrogenase isoenzymes in serum.   J Mol Cell Cardiol 1974; 6(4):297-315  ICID: 825597
LH Bernstein, MB Grisham, KD Cole, J Everse . Substrate inhibition of the mitochondrial and cytoplasmic malate dehydrogenases. J Biol Chem 1978; 253(24):8697-8701. ICID: 825513
R Belding, L Bernstein, G Reynoso. An evaluation of the immunochemical LD1 method in routine clinical practice. Clin Chem 1981; 27(10):1027-1028.   ICID: 844981
J Adan, L H Bernstein, J Babb. Lactate dehydrogenase isoenzyme-1/total ratio: accurate for determining the existence of myocardial infarction. Clin Chem 1986; 32(4):624-628.  ICID: 825540
MB Grisham, LH Bernstein, J Everse. The cytoplasmic malate dehydrogenase in neoplastic tissues; presence of a novel isoenzyme? Br J Cancer 1983; 47(5):727-731. ICID: 825551
LH Bernstein, P Scinto. Two methods compared for measuring LD-1/total LD activity in serum. Clin Chem 1986; 32(5):792-796.   ICID: 825581

PGC-1a: an inducible integrator of transcriptional circuits

 The PPAR³ coactivator-1 (PGC-1) family of transcriptional coactivators is involved in regulating mitochondrial metabolism and biogenesis.
PGC-1a was the first member discovered through its functional interaction with the nuclear receptor PPAR³ in brown adipose tissue (BAT).
There are two PGC-1a related coactivators,
  1. PGC-1² (also called PERC) and
  2. PGC-1–related coactivator (PRC).
PRC coactivates transcription in mitochondrial biogenesis, with PGC-1a and PGC-1² . Both are expressed in tissues with high oxidative capacity, such as
  1. heart
  2. slow-twitch skeletal muscle, and
  3. BAT
They serve critical roles in the regulation of mitochondrial functional capacity. PGC-1a  also regulates
  • hepatic gluconeogenesis and
  • skeletal muscle glucose uptake.
PGC-1² appears to be important in regulating energy metabolism in the heart, but
  • PGC-1a is distinct from other PGC-1 family members, indeed from most coactivators, in its broad responsiveness to
  1. developmental alterations in energy metabolism and
  2. physiological and pathological cues at the level of expression and transactivation.
In the heart, PGC-1a expression increases at birth coincident with an increase in cardiac oxidative capacity and
  • a perinatal shift from reliance on glucose metabolism to the oxidation of fats for energy.
PGC-1a is induced by physiological stimuli that increase ATP demand and
  • stimulate mitochondrial oxidation, including
  1. cold exposure,
  2. fasting, and
  3. exercise.
Activation of this regulatory cascade increases cardiac mitochondrial oxidative capacity in the heart. In cardiac myocytes in culture, it
  1. increases mitochondrial number,
  2. upregulates expression of mitochondrial enzymes, and
  3. increases rates of FA oxidation and coupled respiration.
Thus, PGC-1a is an inducible coactivator that coordinately regulates
  • cardiac fuel selection and
  • mitochondrial ATP-producing capacity.
 PGC-1a activates expression of nuclear respiratory factor-1 (NRF-1) and NRF-2 and
  • directly coactivates NRF-1 on its target gene promoters.
NRF-1 and NRF-2 regulate expression of mitochondrial transcription factor A (Tfam),
  • a nuclear-encoded transcription factor that binds regulatory sites on mitochondrial DNA and is essential for
  1. replication,
  2. maintenance, and
  3. transcription of the mitochondrial genome.
Furthermore, NRF-1 and NRF-2 regulate the expression of nuclear genes encoding
  • respiratory chain subunits and other proteins required for mitochondrial function.
PGC-1a  also
  • coactivates the PPAR and ERR nuclear receptors, critical regulators of myocardial FFA utilization.
  • regulates genes involved in the cellular uptake and mitochondrial oxidation of FFAs.
  • is an integrator of the transcriptional network regulating mitochondrial biogenesis and function.
Numerous signaling pathways, by increasing either PGC-1a expression or activity, such as –
  • Ca2+-dependent,
  • NO,
  • MAPK, and
  • beta-adrenergic pathways (beta3/cAMP),
    • activate the PGC-1a directly
Additionally, the p38_MAPK pathway
  • selectively activates PPARa, which may bring about synergistic activation in the presence of PGC-1a,
  • whereas ERK-MAPK has the opposite effect.
These signaling pathways transduce physiological stimuli to the PGC-1a pathway:
  1. stress
  2. fasting
  3. exercise
PGC-1a, in turn, coactivates transcriptional partners,which regulate mitochondrial biogenesis and FA-oxidation pathways:
  • NRF-1 and -2,
  • ERRa, and
  • PPARa,
 Insights into the physiological responsiveness of the PGC-1a pathway come from
  • identification of signal transduction pathways that modulate the activity of PGC-1a and its downstream partners.
PGC-1a is upregulated in response to beta-adrenergic signaling, consistent with the involvement of this pathway in thermogenesis.
The stress-activated  p38_MAPK activates PGC-1a by increasing PGC-1a protein stability and promoting dissociation of a repressor.
p38 increases mitochondrial FAO through selective activation of the PGC-1a partner, PPARa. Conversely, the ERK-MAPK pathway
  • inactivates the PPARa/RXRa complex via direct phosphorylation.
Therefore, distinct limbs of the MAPK pathway exert
  • opposing regulatory influences on the PGC-1a cascade.
Recently, NO has emerged as a novel signaling molecule proposed to integrate pathways involved in
  • regulating mitochondrial biogenesis by inducing mitochondrial proliferation.

 A Paradox

Mitochondria are like little cells within our cells. They are the energy producing organelles of the body. The more energy a certain tissue requires
  • such as the brain and the heart
    • the more mitochondria those cells contain.
Conventional transmission electron microscopy of mammalian cardiac tissue reveals mitochondria to be
  1. elliptical individual organelles situated either in clusters beneath the sarcolemma (subsarcolemmal mitochondria, SSM) or
  2. in parallel, longitudinal rows ensconced within the contractile apparatus (interfibrillar mitochondria, IFM).
The two mitochondrial populations differ in their cristae morphology, with
  1. a lamelliform orientation in SSM, whereas
  2. the cristae orientation in IFM is tubular.
The morphology of mitochondria is responsive to changes in cardiomyocytes.
 Mitochondrial oxidative phosphorylation relies
  • not only on the activities of individual complexes, but also on
  • the coordinated action of supramolecular assemblies (respirasomes) of the electron transport chain (ETC) complexes
in both normal and failing heart.
Mitochondria have their own set of DNA and
  • the more energy they generate,
  • the more DNA-damaging free radicals they produce.
Mitochondrial DNA damage is incurred by generation of energy in ATP production, so that
  • the process that sustains life also is the source of toxic damage that causes the dysfunction and mitogeny in the cell.
In human mtDNA mutant cybrids with impaired mitochondrial respiration, the recovery of mitochondrial function
  • correlates with the formation of respirasomes suggesting that
  • respirasomes represent regulatory units of mitochondrial oxidative phosphorylation
    • by facilitating the electron transfer between the catalytic sites of the ETC.
We recently reported a decrease in mitochondrial respirasomes in CHF that fits in the category of a new mitochondrial cytopathy.
 ATP utilized by the heart is synthesized mainly by means of oxidative phosphorylation in the inner mitochondrial membrane,
  • a process that involves the coupling of electron transfer and oxygen consumption with phosphorylation of ADP to ATP.
The catabolism of exogenous substrates (FAs, glucose, pyruvate, lactate, and ketone bodies) provides the reduced intermediates,
  1. NADH (nicotinamide adenine dinucleotide, reduced) and
  2. FADH2 (flavin adenine dinucleotide, reduced),
as donors for mitochondrial electron transport.
The contribution of glucose to the acetyl CoA pool in the heart is
  • increased by insulin during the postprandial period and during exercise.
 All cells and tissues require
  • adenine,
  • pyridine, and
  • flavin nucleotides for energy
by way of Krebs cycle metabolism of fatty acids and carbohydrate substrates.
If DNA holds the blueprint for the proper function of a cell, then any change in the blueprint will change how the cell functions.
If the mitochondria do not function properly, then they cannot fulfill their role in producing energy:
  •  the cell will lose its ability to function adequately.

 Related articles

 References

Mitochondrial dynamics and cardiovascular diseases    Ritu Saxena
https://pharmaceuticalintelligence.com/2012/11/14/mitochondrial-dynamics-and-cardiovascular-diseases/
Mitochondrial Damage and Repair under Oxidative Stress   larryhbern
https://pharmaceuticalintelligence.com/2012/10/28/mitochondrial-damage-and-repair-under-oxidative-stress/
Mitochondria: Origin from oxygen free environment, role in aerobic glycolysis, metabolic adaptation   larryhbern
http://pharmaceuticalintelligence.com/2012/09/26/mitochondria-origin-from-oxygen-free-environment-role-in-aerobic-glycolysis-metabolic-adaptation/ Ca2+ signaling: transcriptional control     larryhbern
http://pharmaceuticalintelligence.com/2013/03/06/ca2-signaling-transcriptional-control/ MIT Scientists on Proteomics: All the Proteins in the Mitochondrial Matrix identified  Aviva Lev-Ari
http://pharmaceuticalintelligence.com/2013/02/03/mit-scientists-on-proteomics-all-the-proteins-in-the-mitochondrial-matrix-identified/
Nitric Oxide has a ubiquitous role in the regulation of glycolysis -with a concomitant influence on mitochondrial function    larryhbern
http://pharmaceuticalintelligence.com/2012/09/16/nitric-oxide-has-a-ubiquitous-role-in-the-regulation-of-glycolysis-with-a-concomitant-influence-on-mitochondrial-function/
Ubiquinin-Proteosome pathway, autophagy, the mitochondrion, proteolysis and cell apoptosis  larryhbern
http://pharmaceuticalintelligence.com/2013/02/14/ubiquinin-proteosome-pathway-autophagy-the-mitochondrion-proteolysis-and-cell-apoptosis-reconsidered/
Low Bioavailability of Nitric Oxide due to Misbalance in Cell Free Hemoglobin in Sickle Cell Disease – A Computational Model   Anamika Sarkar
http://pharmaceuticalintelligence.com/2012/11/09/low-bioavailability-of-nitric-oxide-due-to-misbalance-in-cell-free-hemoglobin-in-sickle-cell-disease-a-computational-model/
The rationale and use of inhaled NO in Pulmonary Artery Hypertension and Right Sided Heart Failure    larryhbern
http://pharmaceuticalintelligence.com/2012/08/20/the-rationale-and-use-of-inhaled-no-in-pulmonary-artery-hypertension-and-right-sided-heart-failure/
Mitochondria and Cardiovascular Disease: A Tribute to Richard Bing, Larry H Bernstein, MD, FACP
https://pharmaceuticalintelligence.com/2013/04/14/chapter-5-mitochondria-and-cardiovascular-disease/
Mitochondrial Metabolism and Cardiac Function, Larry H Bernstein, MD, FACP
https://pharmaceuticalintelligence.com/2013/04/14/mitochondrial-metabolism-and-cardiac-function/
Mitochondrial Dysfunction and Cardiac Disorders, Larry H Bernstein, MD, FACP
https://pharmaceuticalintelligence.com/2013/04/14/mitochondrial-dysfunction-and-cardiac-disorders/
Reversal of Cardiac mitochondrial dysfunction, Larry H Bernstein, MD, FACP
https://pharmaceuticalintelligence.com/2013/04/14/reversal-of-cardiac-mitochondrial-dysfunction/
Clinical Trials Results for Endothelin System: Pathophysiological role in Chronic Heart Failure, Acute Coronary Syndromes and MI – Marker of Disease Severity or Genetic Determination? Aviva Lev-Ari, PhD, RN 10/19/2012
https://pharmaceuticalintelligence.com/2012/10/19/clinical-trials-results-for-endothelin-system-pathophysiological-role-in-chronic-heart-failure-acute-coronary-syndromes-and-mi-marker-of-disease-severity-or-genetic-determination/
Endothelin Receptors in Cardiovascular Diseases: The Role of eNOS Stimulation, Aviva Lev-Ari, PhD, RN 10/4/2012
https://pharmaceuticalintelligence.com/2012/10/04/endothelin-receptors-in-cardiovascular-diseases-the-role-of-enos-stimulation/
Inhibition of ET-1, ETA and ETA-ETB, Induction of NO production, stimulation of eNOS and Treatment Regime with PPAR-gamma agonists (TZD): cEPCs Endogenous Augmentation for Cardiovascular Risk Reduction – A Bibliography, Aviva Lev-Ari, PhD, RN 10/4/2012
https://pharmaceuticalintelligence.com/2012/10/04/inhibition-of-et-1-eta-and-eta-etb-induction-of-no-production-and-stimulation-of-enos-and-treatment-regime-with-ppar-gamma-agonists-tzd-cepcs-endogenous-augmentation-for-cardiovascular-risk-reduc/
Genomics & Genetics of Cardiovascular Disease Diagnoses: A Literature Survey of AHA’s Circulation Cardiovascular Genetics, 3/2010 – 3/2013, L H Bernstein, MD, FACP and Aviva Lev-Ari,PhD, RN  3/7/2013
https://pharmaceuticalintelligence.com/2013/03/07/genomics-genetics-of-cardiovascular-disease-diagnoses-a-literature-survey-of-ahas-circulation-cardiovascular-genetics-32010-32013/
Cardiovascular Disease (CVD) and the Role of agent alternatives in endothelial Nitric Oxide Synthase (eNOS) Activation and Nitric Oxide Production, Aviva Lev-Ari, PhD, RN 7/19/2012
https://pharmaceuticalintelligence.com/2012/07/19/cardiovascular-disease-cvd-and-the-role-of-agent-alternatives-in-endothelial-nitric-oxide-synthase-enos-activation-and-nitric-oxide-production/
Cardiovascular Risk Inflammatory Marker: Risk Assessment for Coronary Heart Disease and Ischemic Stroke – Atherosclerosis. Aviva Lev-Ari, PhD, RN 10/30/2012
https://pharmaceuticalintelligence.com/2012/10/30/cardiovascular-risk-inflammatory-marker-risk-assessment-for-coronary-heart-disease-and-ischemic-stroke-atherosclerosis/
Cholesteryl Ester Transfer Protein (CETP) Inhibitor: Potential of Anacetrapib to treat Atherosclerosis and CAD, Aviva Lev-Ari, PhD, RN 4/7/2013
https://pharmaceuticalintelligence.com/2013/04/07/cholesteryl-ester-transfer-protein-cetp-inhibitor-potential-of-anacetrapib-to-treat-atherosclerosis-and-cad/
Hypertriglyceridemia concurrent Hyperlipidemia: Vertical Density Gradient Ultracentrifugation a Better Test to Prevent Undertreatment of High-Risk Cardiac Patients, Aviva Lev-Ari, PhD, RN  4/4/2013 https://pharmaceuticalintelligence.com/2013/04/04/hypertriglyceridemia-concurrent-hyperlipidemia-vertical-density-gradient-ultracentrifugation-a-better-test-to-prevent-undertreatment-of-high-risk-cardiac-patients/
Fight against Atherosclerotic Cardiovascular Disease: A Biologics not a Small Molecule – Recombinant Human lecithin-cholesterol acyltransferase (rhLCAT) attracted AstraZeneca to acquire AlphaCore, Aviva Lev-Ari, PhD, RN 4/3/2013
https://pharmaceuticalintelligence.com/2013/04/03/fight-against-atherosclerotic-cardiovascular-disease-a-biologics-not-a-small-molecule-recombinant-human-lecithin-cholesterol-acyltransferase-rhlcat-attracted-astrazeneca-to-acquire-alphacore/
High-Density Lipoprotein (HDL): An Independent Predictor of Endothelial Function & Atherosclerosis, A Modulator, An Agonist, A Biomarker for Cardiovascular Risk, Aviva Lev-Ari, PhD, RN 3/31/2013 

https://pharmaceuticalintelligence.com/2013/03/31/high-density-lipoprotein-hdl-an-independent-predictor-of-endothelial-function-artherosclerosis-a-modulator-an-agonist-a-biomarker-for-cardiovascular-risk/
Peroxisome proliferator-activated receptor (PPAR-gamma) Receptors Activation: PPARγ transrepression for Angiogenesis in Cardiovascular Disease and PPARγ transactivation for Treatment of Diabetes, Aviva Lev-Ari, PhD, RN 11/13/2012
https://pharmaceuticalintelligence.com/2012/11/13/peroxisome-proliferator-activated-receptor-ppar-gamma-receptors-activation-pparγ-transrepression-for-angiogenesis-in-cardiovascular-disease-and-pparγ-transactivation-for-treatment-of-dia/
Sulfur-Deficiciency and Hyperhomocysteinemia, L H Bernstein, MD, FACP
https://pharmaceuticalintelligence.com/2013/04/04/sulfur-deficiency-and-hyperhomocusteinemia/

 

 

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Directions for Genomics in Personalized Medicine

Author: Larry H. Bernstein, MD, FCAP

 

J. Craig Venter

J. Craig Venter (Photo credit: Wikipedia)

Otto Heinrich Warburg

Otto Heinrich Warburg (Photo credit: Wikipedia)

Purpose

This discussion will identify the huge expansion of genomic technology in the search for  biopharmacotherapeutic targets that continue to be explored involving different levels and interacting signaling pathways.   There are several methods of analyzing gene expression that will be discussed. Great primary emphasis required investigation of combinations of mutations expressed in different cancer types.  James Watson has proposed a major hypothesis that expresses the need to focus on “central” “driver mutations” that correspond with the regulation of gene expression, cell proliferation, and cell metabolism eith a critical rejection of antioxiant benefits.  What hasn’t been know is why drug resistance develops and whether the cellular migration and aerobic glycolysis can be redirected after cell metastasis occurs.  I attempt to bring out the complexities of current efforts.

.Introduction

  • This discussion is a continuation of a previous discussion on the role of genomics if discovery of therapeutic targets for cancer, each somewhat different, but all related to:
  • The reversal of carcinoma by targeting a key driver of multiple signaling pathways that activate cell proliferation
  • Pinpointing a stage in a multistage process at which tumor progression links to changes in morphology from basal cells to invasive carcinoma with changes in polarity and loss of glandular architecture
  • Reversal of the carcinoma through using a small molecule that either is covalently bound to a nanoparticle delivery system that blocks or reverses tumor development
  • Synthesis of a small molecule that interacts with the translation of the genome either by substitution of a key driver molecule or by blocking at the mRNA stage of translation
  • Blocking more than one signaling pathway that are links to carcinogenesis and cellular proliferation and invasion

Difficulty of the problem

A problem expressed by James Watson is that the investigations that are ongoing

  • are following a pathway that is not driven by attacking the “primary” driver of carcinogenesis.

He uses the Myc gene as an example, as noted in the previous discussion. The problem may be more complicated than he envisions.

  • The most consistent problem in chemotherapy, irrespective of the design and the target has been cancer remission for a short time followed by recurrence, and then
  • switching to another drug, or combination chemotherapy.

It is common to “clean” the field at the time of resection using radiotherapy before chemotherapy.

  • But the goal is understood to be “palliation”, not cure.

This raises a serious issue in the hypothesis posed by Watson. The issue is

  • whether there is a core locus of genetic regulation that is common to carcinogenesis irrespective of tissue metabolic expression.
  • This is supported by the observation that tissue specific express is lost in cancer cells by de-differentiation.

Historical Perspective

AEROBIC GLYCOLYSIS

In 1967 Otto Warburg published his view in a paper “The prime cause and prevention of cancer”.
There are primary and secondary causes of all diseases

  • plague – primary: plague bacillus
  • plague – secondary: filth, rats, and fleas

cancer, above all diseases,

  • has countless seconday causes
  • primary – replacement of respiration of oxygen in normal body tissue by fermentation of glucose with conversion from obligate aerobic to anaerobic, as in bacterial cells

The cornerstone to understanding cancer is in study of the energetics of life

This thinking came out of decades of work in the Dahlem Institute Kaiser Wilhelm pre WWII and Max Planck Institute after WWII, supported by the Rockefeller Foundation.

  • The oxygen- and hydrogen-transferring enzymes were discovered and isolated.
  • The methods were elegant for that time, using a manometer that improved on the method used by Haldane, that did not allow the leakage of O2 or CO2.
  • The interest was initiated by the increased growth of Sea Urchin eggs after fertization, which turned out to be not comparable to the rapid growth of cancer cells.
  • Warburg used both normal and cancer tissue and measured the utilization of O2. He found
    • that the normal tissue did not accumulate lactic acid.
    • Cancer tissue generated lactic acid
    • the rate of O2 consumption the same as normal tissue, but
    • the rate of lactate formation far exceeded any tissue, except the retina.
    • This was a discovery studied by “Pasteur” 60 years earlier (facultative aerobes), which he called the Pasteur effect.
    • Hematopoietic cells of bone marrow develop aerobic glycolysis when exposed to a low oxygen condition.

He then followed on an observation by Otto Meyerhoff (Embden-Myerhoff cycle) that in muscle

  • the consumption of one molecule of oxygen generates two molecules of lactate, but in aerobic glycolysis, the relationship disappears.
  • He expressed the effectiveness of respiration by the ‘Meyerhoff quotient’.
  • He found that cancer cells didn’t have a quotient of ‘2’

The role of the allosteric enzyme phosphofructokinase (PFK) not then known, would tie together the glycolytic and gluconeogenic pathways.
He used a heavy metal ion chelator ethylcarbylamine to

  • sever the link and turn on aerobic glycolysis.

The explanation for this was provided years later by the work fleshed out by Lynen, Bucher, Lowry, Racker, and Sols.

  • The rate-limiting enzyme, PFK is regulated by the concentrations of ATP, ADP, and inorganic phosphate. The ethylcarbylamide was an ‘uncoupler’ of oxidative phosphorylation.

Warburg understood that when normal cells switched to aerobic glycolysis

  • it is a re-orientation of normal cell expression.
  • this provides the basis for the inference that neoplastic cells become more like each other than their cell of origin.
  • embryonic cells can be transformed into cancer cells under hypoxic conditions
  • re-exposure to higher oxygen did not cause reversion back to normal cells.

Warburg publically expressed the rejected view in 1954 (at age 83) that restriction of chemical wastes, food additives, and air pollution would substantially reduce cancer rates.

His emphasis on the impairment of respiration was inadequate.

  • the prevailing view today is loss of controlled growth of normal cells in cancer cells.

Otto Warburg: Cell Physiologist, Biochemist, and Eccentric. Hans Krebs, in collaboration with Roswitha Schmid. Clarendon Press, Oxford. 1991.ISBN 0-19-858171-8.

The Human Genome Project

The Human Genome Project, driven by Francis Collins at NIH, and by Craig Venter at the Institute for Genome Research (TIGR) had parallel projects to map the human chromosome, completed in 2003. It originally aimed to map the nucleotides contained in a human haploid reference genome (more than three billion). TIGR was the first complete genomic sequencing of a free living organism, Haemophilus influenzae, in 1995. This used a shotgun sequencing technique pioneered earlier, but which had never been used for a whole bacterium.
Venter broke away from the HGP and started Celera in 1998 because of resistance to the shotgun sequency method, and his team completed the genome sequence in three years – seven years’ less time than the HGP timetable (using the gene of Dr. Venter). TIGR eventually sequenced and analyzed more than 50 microbial genomes. Its bioinformatics group developed

  • pioneering software algorithms that were used to analyze these genomes,
  • including the automatic gene finder GLIMMER and
  • the sequence alignment program MUMmer.

In 2002, Venter created and personally funded the J. Craig Venter Institute (JCVI) Joint Technology Center (JTC), which specialized in high throughput sequencing.  The JTC, in the top ranks of scientific institutions worldwide, sequenced nearly 100 million base pairs of DNA per day for its affiliated institutions (JCVI) .

He received his his Ph.D. degree in physiology and pharmacology from the University of California, San Diego in 1975 under biochemist Nathan O. Kaplan. A full professor at the State University of New York at Buffalo, he joined the National Institutes of Health in 1984. There he learned of a technique for rapidly identifying all of the mRNAs present in a cell and began to use it to identify human brain genes. The short cDNA sequence fragments discovered by this method are called expressed sequence tags (ESTs), a name coined by Anthony Kerlavage at TIGR.
Venter believed that shotgun sequencing was the fastest and most effective way to get useful human genome data. There was a belief that shotgun sequencing was less accurate than the clone-by-clone method chosen by the HGP, but the technique became widely accepted by the scientific community and is still the de facto standard used today.

References

Shreeve, James (2004). The Genome War: How Craig Venter Tried to Capture the Code of Life and Save the World. Knopf. ISBN 0375406298.
Sulston, John (2002). The Common Thread: A Story of Science, Politics, Ethics and the Human Genome. Joseph Henry Press. ISBN 0309084091.
“The Human Genome Project Race”. Center for Biomolecular Science & Engineering, UC Santa Cruz. Retrieved 20 March 2012.
Venter, J. Craig (2007). A Life Decoded: My Genome: My Life. Viking Adult. ISBN 0670063584.

Use of a Fluorophor Probe

An article has been discussed by Dr.  Tilda Barilya on use of a sensitive fluorescent probe in the near IR spectrum at > 700 nm to identify malignant ovarian cells in-vivo in abdominal exploration by tagging an overexpressed FR-α (folate-FITA)
The author makes the point that:

  • In ovarian cancer, the FR-α appears to constitute a good target because it is overexpressed in 90–95% of malignant tumors, especially serous carcinomas.
  • Targeting ligand, folate, is attractive as it is nontoxic, inexpensive and relatively easily conjugated to a fluorescent dye to create a tumor-specific fluorescent contrast agent.
  • The report is identified as “ the first in-human proof-of-principle of the use of intraoperative tumor-specific fluorescence imaging in staging and debulking surgery for ovarian cancer using the systemically administered targeted fluorescent agent folate-FITC.”

While this does invoke possibilities for prognosis, the decision to perform the surgery, whether laparoscopic or open, is late in the discovery process. However, it does suggest the possibility that the discovery and the treatment might be combined if the biomarker itself had the fluorescence to identify the overexpression, but it also is combined with a tag to block the overexpession. This hypothetical possibility is now expressed below.
https://pharmaceuticalintelligence.com/2013/01/19/ovarian-cancer-and-fluorescence-guided-surgery-a-report/

Gene Editing

Dr. Aviva Lev-Ari reports that a new technique developed at MIT Broad Institute and the Rockefeller University can edit DNA in precise locations taken from Science News titled Editing Genome With High Precision: New Method to Insert Multiple Genes in Specific Locations, Delete Defective Genes”.

Using this system, scientists can alter

  • several genome sites simultaneously and
  • can achieve much greater control over where new genes are inserted

According to Feng Zhang, this is an improvement beyond splicing the gene in specific locations and insertion of complexes difficult to assemble known as transcription activator-like effector nucleases (TALENs).

  • The researchers create DNA-editing complexes
  • using naturally occurring bacterial protein-RNA systems
  • that recognize and snip viral DNA, including
  • a nuclease called Cas9 bound to short RNA sequences.
  • they target specific locations in the genome, and
  • when they encounter a match, Cas9 cuts the DNA.

This approach can be used either to

  • disrupt the function of a gene or
  • to replace it with a new one.
  • To replace the gene, a DNA template for the new gene has to be copied into the genome after the DNA is cut. The method is also very precise —
  • if there is a single base-pair difference between the RNA targeting sequence and the genome sequence, Cas9 is not activated.

In its first iteration, it appears comparable in efficiency to what zinc finger nucleases and TALENs have to offer.
The research team has deposited the necessary genetic components with a nonprofit called Addgene, and they have also created a website with tips and tools for using this new technique.
The above story is reprinted from materials provided by Massachusetts Institute of Technology. The original article was written by Anne Trafton.
Le Cong, F. Ann Ran, David Cox, Shuailiang Lin, Robert Barretto, Naomi Habib, Patrick D. Hsu, Xuebing Wu, Wenyan Jiang, Luciano Marraffini, and Feng Zhang. Multiplex Genome Engineering Using CRISPR/Cas Systems. Science, 3 January 2013 DOI: 10.1126/science.1231143. http://Science.com. Editing genome with high precision: New method to insert multiple genes in specific locations, delete defective genes. ScienceDaily. Retrieved January 20, 2013, from http://www.sciencedaily.com­ /releases/2013/01/130103143205.htm?goback=%2Egde_4346921_member_205356312.

Dr. Lev-Ari also reports on a study of early detection of breast cancer in “Mechanism involved in Breast Cancer Cell Growth: Function in Early Detection & Treatment“, by Dr. Rotem Karni and PhD student Vered Ben Hur at the Institute for Medical Research Israel-Canada of the Hebrew University. https://pharmaceuticalintelligence.com/2013/01/17/mechanism-involved-in-breast-cancer-cell-growth-function-in-early-detection-treatment/
These researchers have discovered a new mechanism by which breast cancer cells switch on their aggressive cancerous behavior. The discovery provides a valuable marker for the early diagnosis and follow-up treatment of malignant growths.
The method they use is

  • RNA splicing and insertion.
  • The information needed for the production of a mature protein is encoded in segments called exons .
  • In the splicing process, the non-coding segments of the RNA (introns) are spliced from the pre-mRNA and
  • the exons are joined together.

Alternative splicing is when a specific ”scene” (or exon) is either inserted or deleted from the movie (mRNA), thus changing its meaning.

  • Over 90 percent of the genes in our genome undergo alternative splicing of one or more of their exons, and
  • the resulting changes in the proteins encoded by these different mRNAs are required for normal function.
  • the normal process of alternative splicing is altered in cancer, and
  • ”bad” protein forms are generated that aid cancer cell proliferation and survival.

The researchers reported in online Cell Reports that breast cancer cells

  • change the alternative splicing of an important enzyme, called S6K1, which is
  • a protein involved in the transmission of information into the cell.
  • when this happens, breast cancer cells start to produce shorter versions of this enzyme and
  • these shorter versions transmit signals ordering the cells to grow, proliferate, survive and invade other tissues (otherwise proliferation is suppressed)

The application to biotherapeutics would be to ”reverse” the alternative splicing of S6K1 in cancer cells back to the normal situation as a novel anti-cancer therapy.

Additional Developments:

A*STAR Scientists Pinpoint Genetic Changes that Spell Cancer: Fruit flies light the way for scientists to uncover genetic changes.

With a new approach, researchers may rapidly distinguish the range of

  • genetic changes that are causally linked to cancer (i.e. “driver” mutations)
  • versus those with limited impact on cancer progression.

This study published in the prestigious journal Genes & Development could pave the way to design more targeted treatment against different cancer types, based on the specific cancer-linked mutations present in the patient, an advance in the development of personalized medicine.

Signaling pathways involved in tumour formation are conserved from fruit flies to humans. In fact, about 75 percent of known human disease genes have a recognizable match in the genome of fruit flies.
Leveraging on their genetic similarities, Dr Hector Herranz, a post-doctorate from the Dr. Stephen Cohen’s team developed an innovative strategy to genetically screen the whole fly genome for “cooperating” cancer genes.

  • These genes appear to have little or no impact on cancer.
  • However, they cooperate with other cancer genes, so that
  • the combination causes aggressive cancer, which
  • neither would cause alone.

In this study, the team was specifically looking for genes that

  • could cooperate with EGFR “driver” mutation,
  • a genetic change commonly associated with breast and lung cancers in humans.
  • SOCS5 (reported in this paper) is one of the several new “cooperating” cancer genes to be identified.

Already, there are indications that levels of SOCS5 expression are

  • reduced in breast cancer, and
  • patients with low levels of SOCS5 have poor prognosis.”

The IMCB team is preparing to explore the use of SOCS5 as a biomarker in diagnosis for cancer.
http://genes&development.com

Probing What Fuels Cancer

‘Altered cellular metabolism is a hallmark of cancer,’ says Dr Patrick Pollard, in the Nuffield Department of Clinical Medicine at Oxford. Most cancer cells get the energy they need predominantly through a high rate of glycolysis, allowing cancer cells deal with the low oxygen levels that tend to be present in a tumour.

But whether dysfunctional metabolism causes cancer, as Warburg believed, or is something that happens afterwards is a different question. In the meantime, gene studies rapidly progressed and indicated that genetic changes occur in cancer.

DNA mutations spring up all the time in the body’s cells, but

  • most are quickly repaired.
  • Alternatively the cell might shut down or be killed off (apoptosis) before any damage is caused. However, the repair machinery is not perfect.
  • If changes occur that bypass parts of the repair machinery or sabotage it,
  • the cell can escape the body’s normal controls on growth and
  • DNA changes can begin to accumulate as the cell becomes cancerous.

Patrick believes certain changes in cells can’t always be accounted for by ‘genetics.’
He is now collaborating with Professor Tomoyoshi Soga’s large lab at Keio University in Japan, which has been at the forefront of developing the technology for metabolomics research over the past couple of decades.

The Japanese lab’s ability to

  • screen samples for thousands of compounds and metabolites at once, and
  • the access to tumour material and cell and animal models of disease
  • enables them to probe the metabolic changes that occur in cancer.

There is reason to believe that

  • dysfunctional cell metabolism is important in cancer.
  • genes with metabolic functions are associated with some cancers
  • changes in the function of a metabolic enzyme have been implicated in the development of gliomas.

These 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.

Patrick Pollard and colleagues have now 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 evidence 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 favour development of cancer.

Patrick and colleagues write in their latest article that the shift in focus of cancer research to include cancer cell metabolism ‘has highlighted how woefully ignorant we are about the complexities and interrelationships of cellular metabolic pathways’.

http://FrontiersMolecularCellularOncology.com

Extensive Promoter-Centered Chromatin Interactions Provide a Topological Basis for Transcription Regulation
(Li G, Ruan X, Auerbach RK, Sandhu KS, et al.) Cell 2012; 148(1-2): 84-98. http://cell.com

Using genome-wide Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIA-PET),
mapped long-range chromatin interactions associated with RNA polymerase II in human cells
uncovered widespread promoter-centered intragenic, extragenic, and intergenic interactions.

  • These interactions further aggregated into higher-order clusters
  • proximal and distal genes were engaged through promoter-promoter interactions.
  • most genes with promoter-promoter interactions were active and transcribed cooperatively
  • some interacting promoters could influence each other implying combinatorial complexity of transcriptional controls.

Comparative analyses of different cell lines showed that

  • cell-specific chromatin interactions could provide structural frameworks for cell-specific transcription,
  • and suggested significant enrichment of enhancer-promoter interactions for cell-specific functions.
  • genetically-identified disease-associated noncoding elements were spatially engaged with corresponding genes through long-range interactions.

Overall, our study provides insights into transcription regulation by

  • three-dimensional chromatin interactions for both housekeeping and
  • cell-specific genes in human cells.

New Nucleoporin: Regulator of Transcriptional Repression and Beyond.

(NJ Sarma and K Willis) Nucleus 2012; 3(6): 1–8; http://Nucleus.com © 2012 Landes Bioscience

Transcriptional regulation is a complex process that requires the integrated action of many multi-protein complexes.
The way in which a living cell coordinates the action of these complexes in time and space is still poorly understood.

  • nuclear pores, well known for their role in 3′ processing and export of transcripts, also participate in the control of transcriptional initiation.
  • nuclear pores interface with the well-described machinery that regulates initiation.

This work led to the discovery that

  • specific nucleoporins are required for binding of the repressor protein Mig1 to its site in target promoters.
  • Nuclear pores are involved in repressing, as well as activating, transcription.

Here we discuss in detail the main models explaining our result and consider what each implies about the roles that nuclear pores play in the regulation of gene expression.

Prediction of Breast Cancer Metastasis by Gene Expression Profiles: A Comparison of Metagenes and Single Genes.

(M Burton, M Thomassen, Q Tan, and TA Kruse.) Cancer Informatics 2012:11 193–217 doi: 10.4137/CIN.S10375

The popularity of a large number of microarray applications has in cancer research led to the development of predictive or prognostic gene expression profiles. However, the diversity of microarray platforms has made the full validation of such profiles and their related gene lists across studies difficult and, at the level of classification accuracies, rarely validated in multiple independent datasets. Frequently, while the individual genes between such lists may not match, genes with same function are included across such gene lists. Development of such lists does not take into account the fact that

  • genes can be grouped together as metagenes (MGs) based on common characteristics such as pathways, regulation, or genomic location.

In this study we compared the performance of either metagene- or single gene-based feature sets and classifiers using random forest and two support vector machines for classifier building. The performance

  • within the same dataset,
  • feature set validation perfor­mance, and
  • validation performance of entire classifiers in strictly independent datasets

were assessed by

  • 10 times repeated 10-fold cross validation,
  • leave-one-out cross validation, and
  • one-fold validation, respectively.

To test the significance of the performance difference between MG- and SG-features/classifiers, we used a repeated down-sampled binomial test approach.

MG- and SG-feature sets are transferable and perform well for training and testing prediction of metastasis outcome

  • in strictly independent data sets, both
  • between different and
  • within similar microarray platforms, while
  • classifiers had a poorer performance when validated in strictly independent datasets.

The study showed that MG- and SG-feature sets perform equally well in classifying indepen­dent data. Furthermore, SG-classifiers significantly outperformed MG-classifier

  • when validation is conducted between datasets using similar platforms, while
  • no significant performance difference was found when validation was performed between different platforms.

Prediction of metastasis outcome in lymph node–negative patients by MG- and SG-classifiers showed that SG-classifiers performed significantly better than MG-classifiers when validated in independent data based on the same microarray platform as used for developing the classifier. However, the MG- and SG-classifiers had similar performance when conducting classifier validation in independent data based on a different microarray platform. The latter was also true when only validating sets of MG- and SG-features in independent datasets, both between and within similar and different platforms.

Identification and Insilico Analysis of Retinoblastoma Serum microRNA Profile and Gene Targets Towards Prediction of Novel Serum Biomarkers.

M Beta, A Venkatesan, M Vasudevan, U Vetrivel, et al. Identification and Insilico Analysis of Retinoblastoma Serum microRNA Profile and Gene Targets Towards Prediction of Novel Serum Biomarkers.

http://Bioinformatics and Biology Insights 2013:7 21–34. doi: 10.4137/BBI.S10501

This study was undertaken

  • to identify the differentially expressed miRNAs in the serum of children with RB in comparison with the normal age matched serum,
  • to analyze its concurrence with the existing RB tumor miRNA profile,
  • to identify its novel gene targets specific to RB, and
  • to study the expression of a few of the identified oncogenic miRNAs in the advanced stage primary RB patient’s serum sample.

MiRNA profiling performed on 14 pooled serum from chil­dren with advanced RB and 14 normal age matched serum samples

  • 21 miRNAs found to be upregulated (fold change > 2.0, P < 0.05) and
  • 24 downregulated (fold change > 2.0, P < 0.05).

Intersection of 59 significantly deregulated miRNAs identified from RB tumor profiles with that of miRNAs detected in serum profile revealed that

  • 33 miRNAs had followed a similar deregulation pattern in RB serum.

Later we validated a few of the miRNAs (miRNA 17-92) identified by microarray in the RB patient serum samples (n = 20) by using qRT-PCR.

Expression of the oncogenic miRNAs, miR-17, miR-18a, and miR-20a by qRT-PCR was significant in the serum samples

  • exploring the potential of serum miRNAs identification as noninvasive diagnosis.

Moreover, from miRNA gene target prediction, key regulatory genes of

  • cell proliferation,
  • apoptosis, and
  • positive and negative regulatory networks

involved in RB progression were identified in the gene expression profile of RB tumors.
Therefore, these identified miRNAs and their corresponding target genes could give insights on

  • potential biomarkers and key events involved in the RB pathway.

Computational Design of Targeted Inhibitors of Polo-Like Kinase 1 ( lk1).

(KS Jani and DS Dalafave) Bioinformatics and Biology Insights 2012:6 23–31.doi: 10.4137/BBI.S8971.

Computational design of small molecule putative inhibitors of Polo-like kinase 1 (Plk1) is presented. Plk1, which regulates the cell cycle, is often over expressed in cancers.

  • Down regulation of Plk1 has been shown to inhibit tumor progression.
  • Most kinase inhibitors interact with the ATP binding site on Plk1, which is highly conserved.
  • This makes the development of Plk1-specific inhibitors challenging, since different kinases have similar ATP sites.

However, Plk1 also contains a unique region called the polo-box domain (PBD), which is absent from other kinases.

  • the PBD site was used as a target for designed Plk1 putative inhibitors.
  • Common structural features of several experimentally known Plk1 ligands were first identified.
  • The findings were used to design small molecules that specifically bonded Plk1.
  • Drug likeness and possible toxicities of the molecules were investigated.
  • Molecules with no implied toxicities and optimal drug likeness values were used for docking studies.
  • Several molecules were identified that made stable complexes only with Plk1 and LYN kinases, but not with other kinases.
  • One molecule was found to bind exclusively the PBD site of Plk1.

Possible utilization of the designed molecules in drugs against cancers with over expressed Plk1 is discussed.

Conclusions

The previous discussions reviewed the status of an evolving personalized medicine multicentered and worldwide enterprise.  It is also clear from these reports that the search for targeted drugs matched to a cancer profile or signature has identified several approaches that show great promise.

  • We know considerably  more about metabolic pathways and linked changes in transcription that occur in neoplastic development.
  • There are several methods used to do highly accurate  insertions in gene sequences that are linked to specific metabolic changes, and
  • some may have significant implications for therapeutics, if
    • the link is a change that is associated with a driver mutation
    • the link can be identified by a fluorescent or other probe
    • the link is tied to a mRNA or peptide product that is a biomarker measured in the circulation
  • We have probes to genetic links to the control of many and interacting signaling pathways.
  • We know more about transcription through mRNA.
  • We are closer to the possibility that metabolic substrates, like ‘fumarate’ (a key intermediate in the TCA cycle), may provide a means to reverse regulate the neoplastic cells.
  • We may also find metabolic channels that drive the cells from proliferation to apoptosis or normal activity.

Summary

This discussion identified the huge expansion of genomic technology in the investigation of biopharmacotherapeutic targets that have been identified involving different levels and interacting signaling pathways.   There are several methods of analyzing gene expression, and a primary emphasis is given to combinations of mutations expressed in different cancer types.  There is a major hypothesis that expresses the need to focus on “central” “driver mutations” that correspond with the regulation of gene expression, cell proliferation, and cell metabolism.  What hasn’t been know is why drug resistance develops and whether the cellular migration and aerobic glycolysis can be redirected after cell metastasis occurs.

.

A slight mutation in the matched nucleotides c...

A slight mutation in the matched nucleotides can lead to chromosomal aberrations and unintentional genetic rearrangement. (Photo credit: Wikipedia)

Deutsch: Regulation der Phosphofructokinase

Deutsch: Regulation der Phosphofructokinase (Photo credit: Wikipedia)

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The Molecular Pathology of Breast Cancer Progression,  T. Bailiya`
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https://pharmaceuticalintelligence.com/2012/10/28/mitochondrial-damage-and-repair-under-oxidative-stress/

Mitochondria: More than just the “powerhouse of the cell” R. Saxena
https://pharmaceuticalintelligence.com/2012/07/09/mitochondria-more-than-just-the-powerhouse-of-the-cell/

Mitochondria and Cancer: An overview of mechanisms, R. Saxena
https://pharmaceuticalintelligence.com/2012/09/01/mitochondria-and-cancer-an-overview/

Mitochondrial fission and fusion: potential therapeutic targets?  R. Saxena
https://pharmaceuticalintelligence.com/2012/10/31/mitochondrial-fission-and-fusion-potential-therapeutic-target/

Mitochondrial mutation analysis might be “1-step” away, R. Saxena
https://pharmaceuticalintelligence.com/2012/08/14/mitochondrial-mutation-analysis-might-be-1-step-away/

β Integrin emerges as an important player in mitochondrial dysfunction associated Gastric Cancer,       R. Saxena
https://pharmaceuticalintelligence.com/2012/09/10/%CE%B2-integrin-emerges-as-an-important-player-in-mitochondrial-dysfunction-associated-gastric-cancer/

mRNA interference with cancer expression, LHB
https://pharmaceuticalintelligence.com/2012/10/26/mrna-interference-with-cancer-expression/

What can we expect of tumor therapeutic response?  LHB
https://pharmaceuticalintelligence.com/2012/12/05/what-can-we-expect-of-tumor-therapeutic-response/

Expanding the Genetic Alphabet and linking the genome to the metabolome, LHB
https://pharmaceuticalintelligence.com/2012/09/24/expanding-the-genetic-alphabet-and-linking-the-genome-to-the-metabolome/

Breast Cancer, drug resistance, and biopharmaceutical targets, LHB
https://pharmaceuticalintelligence.com/2012/09/18/breast-cancer-drug-resistance-and-biopharmaceutical-targets/

Breast Cancer: Genomic Profiling to Predict Survival: Combination of Histopathology and Gene Expression Analysis, A. Lev-Ari
https://pharmaceuticalintelligence.com/2012/12/24/breast-cancer-genomic-profiling-to-predict-survival-combination-of-histopathology-and-gene-expression-analysis/

Ubiquinin-Proteosome pathway, autophagy, the mitochondrion, proteolysis and cell apoptosis,   LHB
https://pharmaceuticalintelligence.com/2012/10/30/ubiquinin-proteosome-pathway-autophagy-the-mitochondrion-proteolysis-and-cell-apoptosis/

Identification of Biomarkers that are Related to the Actin Cytoskeleton, LHB
https://pharmaceuticalintelligence.com/2012/12/10/identification-of-biomarkers-that-are-related-to-the-actin-cytoskeleton/

Nitric Oxide has a ubiquitous role in the regulation of glycolysis -with a concomitant influence on mitochondrial function, LHB
https://pharmaceuticalintelligence.com/2012/09/16/nitric-oxide-has-a-ubiquitous-role-in-the-regulation-of-glycolysis-with-a-concomitant-influence-on-mitochondrial-function/

Genomic Analysis: FLUIDIGM Technology in the Life Science and Agricultural Biotechnology,  A. Lev-Ari https://pharmaceuticalintelligence.com/2012/08/22/genomic-analysis-fluidigm-technology-in-the-life-science-and-agricultural-biotechnology/

Nanotechnology: Detecting and Treating metastatic cancer in the lymph node, T. Barliya
https://pharmaceuticalintelligence.com/2012/12/19/nanotechnology-detecting-and-treating-metastatic-cancer-in-the-lymph-node/

 

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Mitochondria: Origin from oxygen free environment, role in aerobic glycolysis, metabolic adaptation


 

English: A diagram of cellular respiration inc...

English: A diagram of cellular respiration including glycolysis, Krebs cycle, citric acid cycle, and the electron transport chain (Photo credit: Wikipedia)

English: Figure from Journal publication of sc...

English: Diagram showing regulation of the enz...

Reporter and Curator: Larry H Bernstein, MD, FACP

Introduction

Mitochondria are essential for life, and are critical for the generation of ATP. Otto Warburg won the Nobel Prize in 1918 for his studies of respiration and he described a situation of impaired respiration in cancer cells causing them to produce lactic acid, like bacteria. This has been termed facultative anaerobic glycolysis. The metabolic explanation for mitochondrial respiration had to await the Nobel discoveries of the Krebs cycle and high energy ~P in acetyl CoA by Fritz Lippman. The Krebs cycle generates 16 ATPs I respiration compared to 2 ATPs through glycolysis. The discovery of the genetic code with the “Watson-Crick” model and the identification of DNA polymerase opened a window for contuing discovery leading to the human genome project at 20th century end that has now been followed by “ENCODE” in the 21st century. This review opens a rediscovery of the metabolic function of mitochondria and adaptive functions with respect to cancer and other diseases.

Function in aerobic and anaerobic metabolism

Two-carbon compounds – the TCA, the pentose phosphate pathway, together with gluconeogenesis and the glyoxylate cycle are essential for the provision of anabolic precursors. Yeast environmental diversity mostly leads to a vast metabolic complexity driven by carbon and the energy available in environmental habitats. This resulted in much early research on analysis of yeast metabolism associated with glucose catabolism in Saccharomyces cerevisiae, under both aerobic and anaerobic environments. Yeasts may be physiologically classified with respect to the type of energy-generating process involved in sugar metabolism, namely non-, facultative- or obligate fermentative. The nonfermentative yeasts have exclusively a respiratory metabolism and are not capable of alcoholic fermentation from glucose, while the obligate-fermentative yeasts – “natural respiratory mutants” – are only capable of metabolizing glucose through alcoholic fermentation. Most of the yeasts identified are facultative-fermentative ones, and depending on the growth conditions, the type and concentration of sugars and/or oxygen availability, may display either a fully respiratory or a fermentative metabolism or even both in a mixed respiratory-fermentative metabolism (e.g., S. cerevisiae). The sugar composition of the media and oxygen availability are the two main environmental conditions that have a strong impact on yeast metabolic physiology, and three frequently observed effects associated with the type of energy-generating processes involved in sugar metabolism and/or oxygen availability are Pasteur, Crabtree and Custer. In modern terms the Pasteur effect refers to an activation of anaerobic glycolysis in order to meet cellular ATP demands owing to the lower efficiency of ATP production by fermentation compared with respiration. In 1861 Pasteur observed that S. cerevisiae consume much more glucose in the absence of oxygen than in its presence. S. cerevisiae only shows a Pasteur at low growth rates and at resting-cell conditions, where a high contribution of respiration to sugar catabolism occurs owing to the loss of fermentative capacity. The Crabtree effect is defined as the occurrence of alcoholic fermentation under aerobic conditions, explained by a theory involving “limited respiratory capacities” in the branching point of pyruvate metabolism. The Custer effect is known as the inhibition of alcoholic fermentation by the absence of oxygen. It is thought that the Custer effect is caused by reductive stress.

Glycolysis

Once inside the cell, glucose is phosphorylated by kinases to glucose 6-phosphate and then isomerized to fructose 6-phosphate, by phosphoglucose isomerase. The next enzyme is phospho-fructokinase, which is subject to regulation by several metabolites, and further phosphorylates fructose 6-phosphate to fructose 1,6-bisphosphate. These steps of glycolysis require energy in the form of ATP. Glycolysis leads to pyruvate formation associated with a net production of energy and reducing equivalents. Approximately 50% of glucose 6-phosphate is metabolized via glycolysis and 30% via the pentose phosphate pathway in Crabtree negative yeasts. However, about 90% of the carbon going through the pentose phosphate pathway reentered glycolysis at the level of fructose 6-phosphate or glyceraldehyde 3-phosphate. The pentose phosphate pathway in Crabtree positive yeasts (S. cerevisiae) is predominantly used for NADPH production but not for biomass production or catabolic reactions.
Pyruvate branch point. At the pyruvate (the end product of glycolysis) branching point, pyruvate can follow three different metabolic fates depending on the yeast species and the environmental conditions. On the other hand, the carbon flux may be distributed between the respiratory and fermentative pathways. Pyruvate might be directly converted to acetyl–cofactor A (CoA) by the mitochondrial multienzyme complex pyruvate dehydrogenase (PDH) after its transport into the mitochondria by the mitochondrial pyruvate carrier. Alternatively, pyruvate can also be converted to acetyl–CoA in the cytosol via acetaldehyde and to acetate by the so-called PDH-bypass pathway. Compared with cytosolic pyruvate decarboxylase, the mitochondrial PDH complex has a higher affinity for pyruvate and therefore most of the pyruvate will flow through the PDH complex at low glycolytic rates. However, at increasing glucose concentrations, the glycolytic rate will increase and more pyruvate is formed, saturating the PDH bypass and shifting the carbon flux through ethanol production. In the yeast S. cerevisiae, the external glucose level controls the switch between respiration and fermentation.

Rodrigues F, Ludovico P and Leão C. Sugar Metabolism in Yeasts: an Overview of Aerobic and Anaerobic Glucose Catabolism. In Molecular and Structural Biology. Chapter 6. qxd 07/23/05 P117
Eriksson P, Andre L, Ansell R, Blomberg A, Adler L (1995) Cloning and characterization of GPD2, a second gene encoding sn-glycerol 3-phosphate dehydrogenase (NAD+) in Saccharomyces cerevisiae, and its comparison with GPD1. Mol Microbiol 17:95–107.
Flikweert MT, van der Zanden L, Janssen WM, Steensma HY, van Dijken JP, Pronk JT (1996)Pyruvate decarboxylase: an indispensable enzyme for growth of Saccharomyces cerevisiae on glucose. Yeast 12:247–257.

Biogenesis of mitochondrial structures from aerobically grown S. cerevisiae

Under aerobic conditions S. cerevisiae forms mitochondria which are classical in their properties,
but the number, morphology, and enzyme activity of these mitochondria are also affected by catabolite repression, but it cannot respire under anaerobic conditions and lacks cytochromes. These structures were isolated from anaerobically grown yeast cells and contain malate and succinate dehydrogenases, ATPase, and DNA characteristic of yeast mitochondria. These lipid-complete structures consist predominantly of double-membrane vesicles enclosing a dense matrix which contains a folded inner membrane system bordering electron-transparent regions similar to the cristae of mitochondria.

  • The morphology of the structures is critically dependent on their lipid composition
  • Their unsaturated fatty acid content is similar to that of mitochondria from aerobically grown cells
  • The structures from cells grown without lipid supplements have simpler morphology – a dense granular matrix surrounded by a double membrane but have no obvious folded inner membrane system within the matrix
  • The lipid-depleted structures are only isolated in intact form from protoplasts
  • The synthesis of ergosterol and unsaturated fatty acids is oxygen-dependent and anaerobically grown cells may be depleted of these lipid components
  • The cytology of anaerobically grown yeast cells is profoundly affected by both lipid-depletion and catabolite repression
  • Lipid-depleted anaerobic cells, membranous mitochondrial profiles were not demonstrable
  • The structures from the aerobically and anaerobically grown cells are markedly different in morphology and fatty acid composition, but both contain mitochondrial DNA and a number of mitochondrial enzymes

The phospholipid composition of various strains of Saccharomyces cerevisiae, wild type and petite (cytoplasmic respiratory deficient) yeasts and derived mitochondrial mutants grown under conditions designed to induce variations in the complement of mitochondrial were fractionated into various subcellular fractions and analyzed for cytochrome oxidase (in wild type) and phospholipid composition . 90% or more of the phospholipid, cardiolipin was found in the mitochondrial membranes of wild type and petite yeast . Cardiolipin content differed markedly under various growth conditions .

  • Stationary yeast grown in glucose had better developed mitochondria and more cardiolipin than repressed log phase yeast .
  • Aerobic yeast contained more cardiolipin than anaerobic yeast .
  • Respiration-deficient cytoplasmic mitochondrial mutants, both suppressive and neutral, contained less cardiolipin than corresponding wild types .
  • A chromosomal mutant lacking respiratory function had normal cardiolipin content .
  • Log phase cells grown in galactose and lactate, which do not readily repress the development of mitochondrial membranes, contained as much cardiolipin as stationary phase cells grown in glucose .
  • Cytoplasmic mitochondrial mutants respond to changes in the glucose concentration of the growth medium by variations in their cardiolipin content in the same way as wild type yeast does under similar growth conditions.
  • It is of interest that the chromosomal petite, which as far as can be ascertained has qualitatively normal mitochondrial DNA and a normal cardiolipin content when grown under maximally derepressed conditions .

Thus, the genetic defect in this case probably does not diminish the mass of inner mitochondrial membrane under appropriate conditions . This suggests the cardiolipin content of yeast is a good indicator of the state of development of mitochondrial membrane.
Jakovcic S, Getz Gs, Rabinowitz M, Jakob H, Swift H. Cardiolipin Content Of Wild Type and Mutant Yeasts in Relation to Mitochondrial Function and Development. JCB 1971. jcb.rupress.org
Jakovcic S, Haddock J, Getz GS, Rabinowitz M, Swift H. Biochem J. 1971; 121 :341 .
EPHRUSSI, B . 1953 . Nucleocytoplasmic Relations in Microorganisms . Clarendon Press, Oxford.

Mitochondria, hydrogenosomes and mitosomes

Before and after the publication of an unnoticed article in 1905 by Mereschkowsky there were many publications dealing with plant “chimera’s” and cytoplasmic inheritance in plants, which should have favoured the interpretation of plastids as “semi-autonomous” symbiotic entities in the cytoplasm of the eukaryotic plant cell. Twenty years after Mereschkowsky’s plea for an endosymbiotic origin of plastids, Wallin (1925, 1927) postulated the “bacterial nature of mitochondria”. And so it is one of the mysteries of the 20th century that an endosymbiotic origin of plastids had not been generally accepted before the 1970s, primarily because one cannot experience the consequences of mutations in the mitochondrial genome by naked eye.

  • Mitochondrial DNA is usually present in multiple copies in one and the same mitochondrion and those in the hundreds to thousands of mitochondria in a single cell are not necessarily identical.
  • The random partitioning of the mitochondria in mitosis (and meiosis) frequently results in a more or less biased distribution of the diverent mitochondria in the daughter cells, eventually causing diverent phenotypes in different tissues obscuring the maternal inheritance
  • It was not until the 1990s that certain diseases—which had been interpreted as being X-chromosomal with incomplete penetrance—eventually turned out to be

Lastly, the vast majority of mitochondrial proteins are encoded in the nucleus and, consequently, mutations in the corresponding genes exhibit a Mendelian, and not a cytoplasmic, maternal inheritance
In the 1970s and 1980s the unequivocal demonstration of mitochondrial DNA occurred
and mitochondrial mutations at the DNA level provided the final proof for the role of such mutations in a wealth of hereditary diseases in man.

  • The genomics era provided the tools to prove the endosymbiont-hypothesis for the origin of the eukaryotic cell

Since DNA does not arise de novo, the genomes of organisms and organelles provide a historical record for the evolution of the eukaryotic cell and its organelles. The DNA sequences of two to three genomes of the eukaryotic cell turned out to be a record of the evolution of the eukaryotic life on earth. The analysis of organelle genomes unequivocally revealed a cyanobacterial origin for plastids and an -proteobacterial origin for mitochondria. Both plastids and mitochondria appear to be monophyletic, i.e. plastids derived from one and the same cyanobacterial ancestor, and mitochondria from one and the same -proteobacterial ancestor.
The evolution of the eukaryotic cell appears to have involved one (in the case of animals) or two (in the case of plants) events that took place 1.5 to 2 billion years ago. However, it appears that symbioses involving one or the other eubacterium arose repeatedly during the billions of years available. For example, photosynthetic algae by phagotrophic eukaryotes, negating the hypothesis of a single eukaryotic event, rather than stringent selection shaping the diversity of present-day life. Recent hypotheses for the origin of the nucleus have postulated that introns, which could be acquired by the uptake of the -proteobacterial endosymbiont, forced the nucleus-cytosol compartmentalization. Lateral gene transfer among eukaryotes is more frequent than was assumed earlier, and “mitochondrial genes” in the nuclear genomes of amitochondrial organisms are not necessarily the consequence of a transient presence of a DNA-containing mitochondrial-like organelle.
To cope with the obvious ubiquity of “mitochondrial” genes and the chimerism of the DNA of present day eukaryotes, the hydrogen hypothesis postulates that an archaeal host took up a eubacterial symbiont that became the ancestor of mitochondria and hydrogenosomes. The hydrogen hypothesis has the potential to explain both the monophyly of the mitochondria, and the existence of “anaerobic” and “aerobic” variants of one and the same original organelle. Based on these observations we have only the terms “mitochondrion”, “hydrogenosome” and “mitosome” to classify the various variants of the mitochondrial family.
Hackstein JHP, Joachim Tjaden J , Huynen M. Mitochondria, hydrogenosomes and mitosomes: products of evolutionary tinkering! Curr Genet (2006) 50:225–245. DOI 10.1007/s00294-006-0088-8.

Lineages

A look at the phylogenetic distribution of characterized anaerobic mitochondria among animal lineages shows that these are not clustered but spread across metazoan phylogeny. The biochemistry and the enzyme equipment used in the facultatively anaerobic mitochondria of metazoans is nearly identical across lineages, strongly indicating a common origin from an archaic metazoan ancestor. The organelles look like hydrogenosomes – anaerobic forms of mitochondria that generate H2 and adenosine triphosphate (ATP) from pyruvateoxidation and which were previously found only in unicellular eukaryotes. The animals harbor structures resembling prokaryotic endosymbionts, reminiscent of the methanogenic endosymbionts found in some hydrogenosome-bearing protists; fluorescence of F420, a typical methanogen cofactor, or lack thereof, will bring more insights as to what these structures are. If we follow the anaerobic lifestyle further back into evolutionary history, beyond the origin of the metazoans, we see that the phylogenetic distribution of eukaryotes with facultative anaerobic mitochondria, eukaryotes with hydrogenosomes and eukaryotes that possess mitosomes (reduced forms of mitochondria with no direct role in ATP synthesis) the picture is similar to that seen for animals. In all six of the major lineages (or supergroups) of eukaryotes that are currently recognized, forms with anaerobic mitochondria have been found. The newest additions to the growing collection of anaerobic mitochondrial metabolisms are the denitrifying foraminiferans. A handful of about a dozen enzymes make the difference between a ‘normal’ O2-respiring mitochondrion found in mammals, and the energy metabolism of eukaryotes with anaerobic mitochondria, hydrogenosomes or mitosomes. Notably, the full complement of those enzymes, once thought to be specific to eukaryotic anaerobes, surprisingly turned up in the green alga Chlamydomonas reinhardtii , which produces O2 in the light, has typical O2-respiring mitochondria but, within about 30 min of exposure to heterotrophic, anoxic and dark conditions, expresses its anaerobic biochemistry to make H2 in the same way as trichomonads, the group in which hydrogenosomes were discovered. Chlamydomonas provides evidence which indicates that the ability to inhabit oxygen-harbouring, as well as anoxic environments, is an ancestral feature of eukaryotes and their mitochondria. The prokaryote inhabitants have existed for well over a billion years, and have reached this new habitat by dispersal, not by adaptive evolution de novo and in situ. Indeed, geochemical evidence has shown that methanogenesis and sulphate reduction, and the niches in which they occur, are truly ancient.
Mentel and Martin. Anaerobic mitochondria: more common all the time. BMC Biology 2010; 8:32. BioMed Central Ltd. http://www.biomedcentral.com/1741-7007/8/32.

Anaerobic mitochondrial enzymes

Mitochondria from the muscle of the parasitic nematode Ascaris lumbricoides var. suum function anaerobically in electron transport-associated phosphorylations under physiological conditions. These helminth organelles have been fractionated into inner and outer membrane, matrix, and inter-membrane space fractions. The distributions of enzyme systems were determined and compared with corresponding distributions reported in mammalian mitochondria. Succinate and pyruvate dehydrogenases as well as NADH oxidase, Mg++-dependent ATPase, adenylate kinase, citrate synthase, and cytochrome c reductases were determined to be distributed as in mammalian mitochondria. In contrast with the mammalian systems, fumarase and NAD-linked “malic” enzyme were isolated primarily from the intermembrane space fraction of the worm mitochondria. These enzymes are required for the anaerobic energy-generating system in Ascaris and would be expected to give rise to NADH in the intermembrane space.
Pyruvate kinase activity is barely detectable in Ascaris muscle. Therefore, rather than giving rise to cytoplasmic pyruvate, CO2 is fixed into phosphoenolpyruvate, resulting in the formation of oxalacetate which, in turn, is reduced by NADH to form malate regenerating glycolytic NAD . Ascaris muscle mitochondria utilize malate anaerobically as their major substrate by means of a dismutation reaction. The “malic” enzyme in the mitochondrion catalyzes theoxidation of malate to form pyruvate, CO2, and NADH. This reaction serves to generate intramitochondrial reducing power in the form of NADH. Concomitantly, fumarase catalyzes thedehydration of an equivalent amount of malate to form fumarate which, in turn, is reduced by an NADH-linked fumarate reductase to succinate. The flavin-linked fumarate reductase reaction results in a site I electron transport-associated phosphorylation of ADP, giving rise to ATP. This identifies a proton translocation system to obtain energy generation.
Rew RS, Saz HJ. Enzyme Localization in the Anaerobic Mitochondria Of Ascaris Lumbricoides. The Journal Of Cell Biology 1974; 63: 125-135. jcb.rupress.org

Mitochondrial redox status

Tumor cells are characterized by accelerated growth usually accompanied by up-regulated pathways that ultimately increase the rate of ATP production. These cells can suffer metabolic reprogramming, resulting in distinct bioenergetic phenotypes, generally enhancing glycolysis channeled to lactate production. These investigators showed metabolic reprogramming by means of inhibitors of histone deacetylase (HDACis), sodium butyrate and trichostatin. This treatment was able to shift energy metabolism by activating mitochondrial systems such as the respiratory chain and oxidative phosphorylation that were largely repressed in the untreated controls.
Amoêdo ND, Rodrigues MF, Pezzuto P, Galina A, et al. Energy Metabolism in H460 Lung Cancer Cells: Effects of Histone Deacetylase Inhibitors. PLoS ONE 2011; 6(7): e22264. doi:10.1371/ journal.pone.0022264
Antioxidant pathways that rely on NADPH are needed for the reduction of glutathione and maintenance of proper redox status. The mitochondrial matrix protein isocitrate dehydrogenase 2 (IDH2) is a major source of NADPH. NAD+-dependent deacetylase SIRT3 is essential for the prevention of age related hearing loss of caloric restricted mice. Oxidative stress resistance by SIRT3 was mediated through IDH2. Inserting SIRT3 Nε-acetyl-lysine into position 413 of IDH2 and has an activity loss by as much as 44-fold. Deacetylation by SIRT3 fully restored maximum IDH2 activity. The ability of SIRT3 to protect cells from oxidative stress was dependent on IDH2, and the deacetylated mimic, IDH2K413R variant was able to protect Sirt3-/- MEFs from oxidative stress through increased reduced glutathione levels. The increased SIRT3 expression protects cells from oxidative stress through IDH2 activation. Together these results uncover a previously unknown mechanism by which SIRT3 regulates IDH2 under dietary restriction. Recent findings demonstrate that IDH2 activities are a major factor in cancer, and as such, these results implicate SIRT3 as a potential regulator of IDH2-dependent functions in cancer cell metabolism.
Wei Yu, Dittenhafer-Reed KE and JM Denu. SIRT3 Deacetylates Isocitrate Dehydrogenase 2 (IDH2) and Regulates Mitochondrial Redox Status. JBC Papers in Press. Published on March 13, 2012 as Manuscript M112.355206. http://www.jbc.org
Computationally designed drug small molecules targeted for metabolic processes: a bridge from the genome to repair of dysmetabolism
New druglike small molecules with possible anticancer applications were computationally designed. The molecules formed stable complexes with antiapoptotic BCL-2, BCL-W, and BFL-1 proteins. These findings are novel because, to the best of the author’s knowledge, molecules that bind all three of these proteins are not known. A drug based on them should be more economical and better tolerated by patients than a combination of drugs, each targeting a single protein. The calculated drug-related properties of the molecules were similar to those found in most commercial drugs. The molecules were designed and evaluated following a simple, yet effective procedure. The procedure can be used efficiently in the early phases of drug discovery to evaluate promising lead compounds in time- and cost-effective ways.
Keywords: small molecule mimetics, antiapoptotic proteins, computational drug design.

Tardigrades

Tardigrades have unique stress-adaptations that allow them to survive extremes of cold, heat, radiation and vacuum. To study this, encoded protein clusters and pathways from an ongoing transcriptome study on the tardigrade Milnesium tardigradum were analyzed using bioinformatics tools and compared to expressed sequence tags (ESTs) from Hypsibius dujardini, revealing major pathways involved in resistance against extreme environmental conditions. ESTs are available on the Tardigrade Workbench along with software and databank updates. Our analysis reveals that RNA stability motifs for M. tardigradum are different from typical motifs known from higher animals. M. tardigradum and H. dujardini protein clusters and conserved domains imply metabolic storage pathways for glycogen, glycolipids and specific secondary metabolism as well as stress response pathways (including heat shock proteins, bmh2, and specific repair pathways). Redox-, DNA-, stress- and protein protection pathways complement specific repair capabilities to achieve the strong robustness of M. tardigradum. These pathways are partly conserved in other animals and their manipulation could boost stress adaptation even in human cells. However, the unique combination of resistance and repair pathways make tardigrades and M. tardigradum in particular so highly stress resistant.
Keywords: RNA, expressed sequence tag, cluster, protein family, adaptation, tardigrada, transcriptome

Epicrisis

This discussion has disparate pieces that are tied together by dysfunctional changes that are

  • adaptations from metabolic process in the channeling of energy dependent of mitochondrial enzymes in interaction with three to 6 carbon carbohydrates, high energy phosphate, oxygen and membrane lipid structures, as well as
  • proteins rich or poor in sulfur linked with genome specific targets, and semisynthetic modifications, oxidative stress
  • leading to a new approach to pharmaceutical targeted drug design.

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