Links between metabolism and cancer

~Content Source

Metabolism generates oxygen radicals, which contribute to oncogenic mutations. Activated oncogenes and loss of tumor suppressors in turn alter metabolism and induce aerobic glycolysis. Aerobic glycolysis or the Warburg effect links the high rate of glucose fermentation to cancer. Together with glutamine, glucose via glycolysis provides the carbon skeletons, NADPH, and ATP to build new cancer cells, which persist in hypoxia that in turn rewires metabolic pathways for cell growth and survival. Excessive caloric intake is associated with an increased risk for cancers, while caloric restriction is protective, perhaps through clearance of mitochondria or mitophagy, thereby reducing oxidative stress. Hence, the links between metabolism and cancer are multifaceted, spanning from the low incidence of cancer in large mammals with low specific metabolic rates to altered cancer cell metabolism resulting from mutated enzymes or cancer genes.

Keywords: caloric restriction, cancer, glycolysis, metabolism, obesity, oncogenes, tumor suppressors

 Otto Warburg published a body of work linking metabolism and cancer through enhanced aerobic glycolysis (also known as the Warburg effect) that distinguishes cancer from normal tissues (Warburg 1956Hsu and Sabatini 2008Vander Heiden et al. 2009aKoppenol et al. 2011). The conversion of glucose to lactate, which can occur in hypoxic normal cells, persists in cancer tissues despite the presence of oxygen that would normally inhibit glycolysis through a process termed the Pasteur effect. We now know that sustained aerobic glycolysis (diminished Pasteur effect) in certain cancer cells is linked to activation of oncogenes or loss of tumor suppressors (Vander Heiden et al. 2009aLevine and Puzio-Kuter 2010Cairns et al. 2011Koppenol et al. 2011). However, the Warburg effect in itself does not explain the persistence of mitochondrial respiration in many cancers or the role of aerobic glycolysis in cell mass accumulation and cell proliferation. Furthermore, glucose, which comprises carbon, hydrogen, and oxygen, could not provide all of the building blocks for a growing cell, which is composed of other elements such as nitrogen, phosphorus, and sulfur. In this regard, other nutrients are, a priori, required to build new cells. How growth signaling leads to nutrient uptake and building of a cell is discussed below.

As neoplastic cells accumulate in three-dimensional multicellular masses, local low nutrient and oxygen levels trigger the growth of new blood vessels into the neoplasm. The imperfect neovasculature in the tumor bed is poorly formed and inefficient and hence poses nutrient and hypoxic stress (Carmeliet et al. 1998Bertout et al. 2008Semenza 2010). In this regard, cancer cells and stromal cells can symbiotically recycle and maximize the use of nutrients (Sonveaux et al. 2008). Hypoxic adaptation by cancer cells is essential for survival and progression of a tumor. The role of hypoxia in cancer cell metabolism is discussed in the context of tumorigenesis (Semenza 2010).

In addition to cell-autonomous changes that drive a cancer cell to proliferate and contribute to tumorigenesis, it has also been observed that alterations in whole-organism metabolism such as obesity are associated with heightened risks for a variety of cancers (Khandekar et al. 2011). Although obesity triggers adult-onset diabetes and elevates glucose and insulin resistance, how obesity increases cancer risk is not simply a matter of increased circulating glucose. It stands to reason that the converse—nutrient deprivation—might be true; caloric restriction would be expected to result in protection from cancer risks. Despite the fact that the converse is true, our understanding of how caloric restriction limits tumorigenesis is still rudimentary (Hursting et al. 2010). Our current understanding of how organismal metabolism may be linked to tumorigenesis and major themes linking metabolism to cancer are discussed below in hope of provoking a new dialogue regarding the various connections between metabolism and cancer.Go to:

Negative entropy and building blocks for growing cells

As Erwin Schrodinger noted in What is Life? (Schrodinger 1992), life is a physical system that maintains structure and avoids decay by feeding on negative entropy through metabolism, a term derived from a Greek word describing the exchange of materials. However, a proliferating cell must capture enough energy and mass to replicate, in addition to the energy required to dampen entropy. In this regard, by studying batch cultures of L cells carefully fed and controlled, Kilburn et al. (1969)documented that the amount of additional energy (assuming that glucose is the main substrate) to produce a new cell is 50% above the baseline required to maintain cellular homeostasis. Hence, it is surmised that the amount of ATP in a proliferating cell is not dramatically different from a resting cell, but the proliferating cell must accumulate biomass, replicate DNA, and divide. In this context, glucose and glutamine are regarded as two major substrates for proliferating cells, providing both ATP and carbon skeletons for macromolecular synthesis (Locasale and Cantley 2011).

Building cells with glucose and glutamine

Glucose is transported into cells by facilitative transporters and then trapped intracellularly by glucose phosphorylation (Berg et al. 2002). The hexose phosphate is further phosphorylated and split into three-carbon molecules that are converted to glycerol for lipid synthesis or sequentially transformed to pyruvate. Pyruvate is converted to acetyl-CoA in the tricarboxylic acid (TCA) cycle, is transaminated to alanine, or becomes lactate, particularly under hypoxic conditions. Formation of citrate from acetyl-CoA and oxaloacetate permits a new round of TCA cycling, generating high-energy electrons, CO2, and carbon skeletons that could be used for biosynthesis or anaplerosis. Citrate itself could be extruded into the cytosol and then converted to acetyl-CoA by ATP citrate lyase (ACLY) for fatty acid synthesis and generation of biomembranes. Glucose, through the pentose phosphate pathway (PPP), generates ribose for nucleic acid synthesis and NADPH for reductive biosynthesis (Fig. 1).

An external file that holds a picture, illustration, etc.
Object name is 877fig1.jpg

Figure 1.

Glucose and glutamine feed cell growth and proliferation. Glucose and glutamine are depicted to contribute to glycolysis (conversion of glucose to pyruvate) and the TCA cycle, which is shown as a hybrid cycle comprising glucose and glutamine carbons. Carbon skeletons from glycolysis and the TCA cycle contribute to macromolecular synthesis for the growing cell.

Glutamine, which circulates with the highest concentration among amino acids, serves as a major bioenergetic substrate and nitrogen donor for proliferating cells (DeBerardinis and Cheng 2010). Glucose and glutamine are required for hexosamine biosynthesis (Wellen et al. 2010). Glutamine enters into the TCA via its conversion to glutamate and then to α-ketoglutarate (aKG), a key TCA cycle intermediate that is also a cofactor for dioxygenases (Chowdhury et al. 2011Xu et al. 2011). Once in the TCA cycle, glutamine carbon skeletons contribute to a hybrid TCA cycle comprising carbons from glucose mixed with those of glutamine (Fig. 2). Under hypoxia, the hypoxia-inducible factor HIF-1 activates pyruvate dehydrogenase kinase (PDK1) that inhibits pyruvate dehydrogenase and the conversion of pyruvate to acetyl-CoA, thereby shunting pyruvate to lactate (Kim et al. 2006). In resting cells, this constitutes the canonical anaerobic glycolysis pathway that is well established in the didactic literature.

An external file that holds a picture, illustration, etc.
Object name is 877fig2.jpg

Figure 2.

Hypoxic rewiring of metabolism. While aerobic proliferating cells use glucose and glutamine for biomass production through the TCA cycle, hypoxic cells shunt glucose to lactate and rewire glutamine metabolism. Glutamine can be used to drive the TCA cycle independently of glucose or contribute to lipid synthesis via IDH-mediated reductive carboxylation of ketoglutarate generated from glutamine.

In proliferating cells, hypoxia, which diverts glucose to lactate, does not attenuate glutamine catabolism through the TCA cycle. In fact, glutamine could contribute to citrate and lipid metabolism through the reversal of the TCA cycle or reductive carboxylation of aKG by isocitrate dehydrogenase (IDH) to form citrate or through forward cycling of glutamine carbons (Fig. 2Wise et al. 2011Metallo et al. 2012Mullen et al. 2012). Reductive carboxylation was first documented as a means for normal brown fat cells to synthesize lipids and was subsequently implicated as a way for hypoxic cancer cells to synthesize lipid from glutamine to grow (Yoo et al. 2008). Under glucose limitation, the TCA cycle could also be reprogrammed and driven solely by glutamine, generating citrate that consists of only glutamine carbons (Le et al. 2012). As such, hypoxic proliferating cells (perhaps as in the case of endothelial cells) reprogram the TCA cycle to maximize the use of glutamine for lipid synthesis.

It is notable that certain cells could also take up free fatty acids from media to support their macromolecular needs, whether for fatty acid oxidation (FAO) or direct insertion into the growing cells’ membranes (Samudio et al. 2010Zaugg et al. 2011). Quiescent primary human T cells and resting human B cells use FAO, but upon growth stimulation, these cells switch to glycolysis and glutaminolysis (Wang et al. 2011Le et al. 2012). In this regard, inhibition of FAO in primary human acute myelogenous leukemia (AML) cells decreased quiescent leukemic progenitor cells (Samudio et al. 2010). Since ongoing fatty acid synthesis produces malonyl-CoA that inhibits mitochondrial import of fatty acids by CPT1, it remains unclear whether proliferating cells undergoing fatty acid synthesis could simultaneously use FAO. It is possible, as suggested by studies of human AML cells and of lymphocytes, that FAO may be used by cancer-initiating or resting cancer stem cells.

Oxygen radicals: signals, toxins, and stress

Part and parcel of cellular metabolism is the production of toxic by-products, which must be titrated for cell survival and maintenance of genome integrity (Ray et al. 2012). The major by-products, known collectively as the reactive oxygen species (ROS), comprise H2O2, superoxide O2, and hydroxyl radical OH (Finkel 2011). These ROS, which are produced from the mitochondria or NOX (NADPH oxidases), damage membranes and can be mutagenic and are hence titrated by glutathione and peroxiredoxins. Superoxide dismutases are essential for redox homeostasis through the conversion of superoxide to hydrogen peroxide, which is neutralized by catalase to water and oxygen. Oxidative stress resulting from altered cancer metabolism is expected to change the ability of cancer cells to handle ROS. Increased ROS was documented to modify a critical sulfhydryl group of pyruvate kinase M2 (PKM2), rendering it inactive and resulting in the shunting of glucose away from glycolysis toward the PPP (Anastasiou et al. 2011). The PPP generates NADPH, which reduces glutathione into an active antioxidant that protects the cell. In this manner, the shunting of glucose away from glycolysis toward the PPP is an essential element of redox homeostasis.

In addition to oxidation of PKM2, increased ROS can stabilize HIF-1. HIF-1, in turn, activates target genes such as PDK1, which diverts pyruvate away from mitochondrial oxidation, and 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase 4 (PFKFB4), which degrades 2,6-fructose bisphosphate (2,6-FBP) (Keith et al. 2012Semenza 2012). 2,6-FBP is a powerful allosteric activator of phosphofructose kinase 1 (PFK1), which converts fructose-1-phosphate to fructose-1,6-bisphosphate (1,6-FBP) at a rate-limiting step in glycolysis (Yalcin et al. 2009). Hence, increased PFKFB4, as observed in prostate cancer cell lines, would diminish PFK1 activity and divert glucose into the PPP shunt, elevating NAPDH to titrate ROS (Ros et al. 2012). It is notable, however, that hypoxia also elevates PFKFB3, which drives glycolysis and can oppose PFKFB4; as such, the balance between PFKFB3 and PFKFB4 activities is critical for shunting glucose into glycolysis versus the PPP.

It is also notable that ROS plays a role in intracellular signaling through alterations of the oxidative status of regulatory protein sulfhydryl moieties (Finkel 2011). In this regard, the antioxidant capability of cancer cells may profoundly influence their responses to metabolic stresses, with resistance to therapy linked to increased antioxidant capacity. Hence, a systematic way to measure cellular antioxidant capacity would be instructive and essential for any attempt to target cancer metabolism for therapy.Go to:

Nutrient sensing, signaling, and cell growth

The unicellular baker’s yeast Saccharomyces cerevisiae is programmed to sense nutrients and activate signal transduction pathways that initiate biomass accumulation. Under glucose-limited growth conditions, yeast cells display oscillations in oxygen consumption alternating with reductive glycolytic phases. DNA replication is normally restricted to the oscillating reductive phase such that yeast cell cycle mutants that uncouple DNA replication from the reductive metabolic phase exhibited heightened spontaneous mutations. These observations suggest that coupling of circadian, metabolic, and cell division cycles is essential for genome integrity. (Chen et al. 2007). However, it should be noted that the coupling of these cycles is highly dependent on the experimental conditions because these cycles could be uncoupled under other nutrient-limiting conditions (Silverman et al. 2010Slavov et al. 2011).

Cell growth or biomass accumulation occurs largely through the genesis of ribosomes, which are essential factories for building blocks of the growing cell and account for over half of the cellular dry mass. Mutations that cause constitutive expression of ribosome biogenesis genes result in mutant yeasts that are addicted to nutrients—glucose and glutamine, whose sensing by yeast are transmitted through Ras and mTORC1, respectively (Figs. 3​,4;4Lippman and Broach 2009). With nutrient deprivation, yeast cells withdraw from the cell cycle (Klosinska et al. 2011). In contrast, mammals must feed to survive, unless they are capable of undergoing hibernation or a state of suspended animation with low metabolic rates. In this regard, certain mammals could store up enough energy as fat and slow metabolism sufficiently to survive long winter months (Dark 2005). Hydrogen sulfide, produced from cysteine via cystathione γ-lyase and cystathione β-synthase, has been implicated in reprogramming cellular metabolism by inhibiting cytochrome C oxidase, thereby lowering mitochondrial function for hibernation (Collman et al. 2009). Aside from hibernation, which is limited to certain species, other mammals can adapt to starvation or caloric restriction.

An external file that holds a picture, illustration, etc.
Object name is 877fig3.jpg

Figure 3.

Nutrient signaling for biomass accumulation. (A) Yeasts could transmit nutrient sensing to biomass accumulation without specific growth factors. (B) A large fraction of cellular mass comprises ribosomes that accumulate in the G1- to S-phase period of the cell cycle. (C) Mammalian cells at rest use nutrients to maintain structure and homeostasis of membrane potentials. Upon stimulation with growth factors, signals from nutrients and growth factor receptors are integrated (via an AND logic gate) to stimulate cell growth or biomass accumulation.

An external file that holds a picture, illustration, etc.
Object name is 877fig4.jpg

Open in a separate windowFigure 4.

Nutrient sensing and yeast cell growth. Glucose and glutamine are depicted to signal via Ras and TORC1, respectively, to inhibit repressors (Dot6 and Tod6) of ribosomal biogenesis (Ribi) genes.

The yin-yang nature of AMPK and mTOR pathways

With nutrient deprivation, mammals could mobilize glycogen from the liver and fat stores from adipose tissues to produce glucose for the brain and red cells. Upon starvation, they could mobilize amino acids from muscles, particularly alanine and glutamine (Berg et al. 2002). Glutamine released into the circulation is used by the kidney for gluconeogenesis by conversion to glutamate and then to aKG, which ends up as oxaloacetate and phosphoenol pyruvate for glucose synthesis (Owen et al. 2002). The ammonia released from glutamine is excreted into alkalinized urine. At the cellular level, low glucose or glutamine levels decrease ATP levels, and an increase in the AMP to ATP ratio is sensed by AMPK, which phosphorylates substrates to enhance energy production while diminishing processes that consume energy (Mihaylova and Shaw 2011). AMPK phosphorylates and inhibits acetyl-CoA carboxylase, which consumes ATP and produces malonyl-CoA for fatty acid synthesis. Additionally, AMPK-mediated phosphorylation of ULK-1 triggers autophagy, which recycles cellular components for energy production (Rabinowitz and White 2010Singh and Cuervo 2011). Diminished malonyl-CoA levels relieve allosteric inhibition of CPT-1, which permits the translocation of fatty acids into the mitochondrion for oxidation to produce ATP. Furthermore, AMPK phosphorylates TSC2, which inhibits mTOR, the master stimulator of cell growth downstream from PI3K and AKT. Hence, under conditions of starvation, AMPK plays a critical role for cell survival by stimulating energy production and limiting the use of energy by active biosynthetic pathways usually operating in proliferating cells.

When energy supply is ample, particularly during development, mammalian cells bathed in nutrients must also be stimulated by growth factors to accumulate biomass and proliferate, which contrasts with yeast, which only needs to sense nutrients to trigger cell growth (Figs. 3​,5).5). As such, growth factors such as IGF-1, EGF, or PDGF participate in the stimulation of mammalian cellular biomass accumulation. Downstream from the growth factor-bound receptor tyrosine kinases is the activation of PI3K, which transmits the growth signal to AKT and mTOR (mTORC2) (Fig. 5Zoncu et al. 2010). mTORC1 is activated by the availability of nutrients, particularly glutamine, which is taken up and then exported extracellularly in a fashion that is coupled with the import of leucine, a key amino acid that is necessary for the mobilization of mTORC1 to lysosomal membranes by G proteins for mTORC1 activation. The activated mTORC1 kinase phosphorylates a number of substrates, including S6K1 and eIF4E-BP1, to stimulate translation, ribosome biogenesis, and growth of the cell. mTORC1 phosphorylates ULK1 to inhibit autophagy when cells are replete with nutrients. Activated mTORC2, on the other hand, activates AKT, which phosphorylates a number of substrates, including hexokinase 2 (HK2), to stimulate glycolysis and activates FOXO3a to inhibit apoptosis and increase mitochondrial biogenesis to support a growing cell (Plas and Thompson 2005Huang and Tindall 2007Ferber et al. 2011). Glucose, when converted to glucose-6-phosphate, stimulates MondoA and ChREBP through nuclear translocation (Peterson and Ayer 2012). Under low anaplerotic flux, MondoA represses glucose uptake, whereas when glutamine elevates anaplerosis, MondoA represses TXNIP to stimulate glucose uptake (Fig. 5Kaadige et al. 2009).

An external file that holds a picture, illustration, etc.
Object name is 877fig5.jpg

Figure 5.

Mammalian cell growth requires growth factors and nutrients. Glucose is shown to signal to MondoA, which down-modulates glucose metabolism. Glutamine contributes to mTORC1 activation through import of leucine and production of GTP via the TCA cycle. GTP is required for mTORC1 activation by its association with lysosomal membranes. mTORC1 activation of S6K1 stimulates ribosome biogenesis (Ribi) genes. Growth factor signaling through receptor tyrosine kinase (RTK) activates PI3K and mTORC2, resulting in AKT activation that stimulates glucose metabolism. Signal transduction via MEK to MYC initiates a transcriptional program that stimulates Ribi genes, coupled with increased glucose and glutamine metabolic gene expression.

Nutrients also modify the epigenome through metabolic intermediates such as acetyl-CoA, S-adenosylmethionine, NAD+, and aKG (Katada et al. 2012), thereby modifying gene expression. Furthermore, many metabolic enzymes are documented to be acetylated, and in some cases, their activities are modified (Zhao et al. 2010Guan and Xiong 2011). Hence, metabolic intermediates contribute the complex tapestry of a network that links nutrients to metabolite intermediates, transcription, and regulation of enzyme activities in cell growth, proliferation, and homeostasis.

Growth factor-stimulated transcriptional responses

In addition to the PI3K–AKT–mTORC2 and amino acid–mTORC1 pathways, there is also an orderly growth factor-stimulated transcriptional program with activation of immediate early response genes, such as MYCJUN, and FOS, and delayed genes that are stimulated by the early response transcription factors (Lau and Nathans 1987). It stands to reason, then, that transcriptional response to growth factor stimulation must trigger the expression of genes that are involved in metabolism and biomass accumulation (Fig. 5). Early studies of serum stimulation of fibroblasts documented Myc as an early response gene and lactate dehydrogenase A (LDHA) as a delayed response gene, but the link between MYC as a transcriptional activator and direct stimulation of LDHA as a Myc target gene was documented a number of years later using model cell lines, providing a direct link between a proto-oncogene and regulation of a gene involved in bioenergetics (Tavtigian et al. 1994Shim et al. 1997). Recently, use of primary T cells permitted the molecular dissection of the roles of Myc versus HIF-1 in T-cell mitogenesis stimulated by CD3 and CD28 antibodies (Wang et al. 2011). This study documents that Myc is essential for the activation of genes involved in glycolysis and glutaminolysis for cell growth and proliferation such that conditional deletion of c-Myc in T cells results in cells incapable of mounting a growth program. HIF-1, which also stimulates glycolysis but not glutaminolysis, is not necessary for the early T-cell growth response program. Myc-dependent genes involved in polyamine biosynthesis are also highly stimulated in normal T cells. These findings corroborate early studies that link MYC to the regulation of metabolic genes, including ornithine decarboxylase, which is involved in polyamine synthesis and is the first reported metabolic gene directly regulated by Myc, particularly in cancer cells (Bello-Fernandez and Cleveland 1992).

Through the work of many laboratories, MYC emerges as a central regulator of cell growth and proliferation downstream from receptor signaling pathways and a key human oncogene that when deregulated could drive a constitutive transcriptional program for nutrient uptake and biomass accumulation (Dang 2010). Indeed, Myc target genes comprise those involved in glucose transport and glycolysis as well as genes involved in glutaminolysis and fatty acid synthesis (Morrish et al. 2009). Moreover, Myc stimulates genes that are involved in mitochondrial biogenesis and function. In this regard, the Myc-induced transcriptional metabolic program parallels those that are used to maintain the integrity of nonproliferating cells via other transcription factors, such as NRF1 (mitochondrial biogenesis), MondoA/ChREBP (carbohydrate metabolism), or SREBP (cholesterol and fatty acid synthesis). The switch from nonproliferative to proliferative states could be surmised as a switch from homeostatic E-box transcription factors to Myc, which is envisioned to co-opt the regulation of metabolic genes for a proliferating cell.

Because Myc stimulates genes involved in the acquisition of nutrients and the intermediary metabolism, it is hence not surprising that Myc also directly stimulates genes involved in ribosome biogenesis for biomass accumulation. The ability of Myc to stimulate ribosome biogenesis genes distinguishes it as a unique E-box transcription factor capable of coupling the expression of metabolic genes with genes involved in cell mass accumulation (van Riggelen et al. 2010Ji et al. 2011). Moreover, Myc uniquely activates genes driven by RNA polymerases I and III, which are required for the expression of ribosomal RNAs (Gomez-Roman et al. 2006). Intriguingly, Myc stimulates and p53 opposes the expression of importin 7 (IPO7), which regulates the import of specific ribosomal proteins for ribosomal assembly, suggesting that cellular stresses regulate ribosome biogenesis through p53 (Golomb et al. 2012). In fact, Mdm2 senses nucleolar imbalance in ribosome biogenesis via binding of excess RPL11 and RPL5 with Mdm2, resulting in elevated p53 (Deisenroth and Zhang 2011). A mutation that eliminates Mdm2 binding to ribosomal proteins suppresses p53 tumor suppressor response and accelerates Myc-induced lymphomagenesis, suggesting that overexpression of Myc in cancers induces stress partly via imbalance in ribosomal biogenesis (Macias et al. 2010). Diminished RPL24 expression in mice, on the other hand, decreases Myc-induced lymphomagenesis, indicating that Myc’s induction of ribosomal biogenesis is essential for tumorigenesis (Barna et al. 2008).

Myc further stimulates genes involved in nucleotide metabolism and specifically interacts with the E2F family of transcription factors to drive proliferating cells into S phase for DNA replication (Leone et al. 2001Zeller et al. 2006Rempel et al. 2009). As a pleiotropic transcription factor, Myc also directly stimulates cell cycle regulatory genes and those directly involved in DNA replication, such as CDK4CDK6, and MCM genes (Zeller et al. 2006). To complete its job as a growth regulatory factor, Myc also regulates genes involved in G2 phase and mitosis, permitting the duplication of cells. The ability of Myc to stimulate genes involved in motility and repress genes encoding cell adhesion molecules probably reflects the need for mitotic cells to detach and divide (Dang et al. 2006).Go to:

Metabolism contributes to cancer

Why don’t elephants get cancer?

Somatic mutations resulting in oncogene activation and tumor suppressor inactivation are in part due to ROS produced as by-products of metabolism. The incidence of cancer as it relates to animal body size provides a potential link between metabolism and cancer in animals. The prevailing view of mutagenesis stipulates that mutations acquired with cell division could result in oncogenesis and cancer (Fig. 6A). As such, the number of cell divisions an animal sustains to reach adulthood should parallel the number of mutations acquired. Given that embryos start their developmental journey with similar sizes (Fig. 6B), an elephant or a whale would have to undergo many more cell divisions to reach adulthood than a mouse. It stands to reason, then, that the occurrence of cancer in large animals should be much higher in elephants and whales. Known as Peto’s paradox, it has been observed that whales have been rarely found to have cancers (Nagy et al. 2007Caulin and Maley 2011). Likewise, the veterinary literature notes that elephants also rarely have cancers, but that feral mice, with several orders of magnitude smaller body sizes, are estimated to have a lifetime frequency of cancer of 40%.

An external file that holds a picture, illustration, etc.
Object name is 877fig6.jpg

Figure 6.

(A) Diagram depicting clonal expansion of cancer cells after a hypothetical mutational event. (B) This cartoon illustrates the significantly different number of cell divisions needed to produce an adult elephant versus a mouse from similar-sized embryos. (C) Empirical measurements of specific metabolic rates (energy in watts per gram of tissue) reveal a power law relation with body mass (grams) as illustrated by a linear log–log relation (dashed line). Cartoons of the mouse and elephant are placed over the approximate body mass. Note the significant difference in specific metabolic rates (several orders of magnitude) between the mouse and elephant (see Savage et al. 2007 for details).

The amount of food consumed is inversely proportional to animal body size, which correlates also inversely with specific basal metabolic rates (metabolic rate per unit body mass) (Fig. 6CSavage et al. 2007). Hence, on a unit mass basis, elephant tissues have much lower metabolic rates than those of mice. Studies of large numbers of animals have revealed a power law relationship between body mass (grams) and specific metabolic rates (watts per grams) (Fig. 6C). Because mammals maintain similar body temperatures, increased body surface area to body mass ratios in smaller animals require higher energy to maintain body temperature; the relationship of body surface area to body mass is inadequate, however, to account for the power law relationship between body mass and metabolic rates. A basis for the power law relation between body mass and specific metabolic rates has been derived theoretically by assuming that the cardiovascular tree branches from the heart sequentially as the body increases in size from mice to elephants. Hence, the ends of the vascular branches are separated farther and farther apart as body size increases, resulting in poorly perfused tissues in larger animals (Herman et al. 2011). As such, the tissue metabolic rates would be lower, most likely due to larger areas of hypoxia distal to blood vessels in large animal. With a small body size, well perfused by nutrients, the higher metabolic rate in mice could be linked to a higher incidence of cancer by means of higher oxidative stress and mutational rates.

Intriguingly, the power law relationship between body mass and specific basal metabolic rates also holds true for the correlation with sleep time (Lo et al. 2004Siegel 2005). Mice sleep ∼12 h per day, while elephants sleep ∼4 h. Sleep is believed to provide a repair phase particularly in the brain, whose sizes tracks with animal body masses. Thus, metabolically more active animals require longer sleep or repair time. Intriguingly, disturbance of sleep, particularly in shift workers and night nurses, has been linked to higher incidences of cancers, with night shift nurses having a clear statistically higher incidence of breast cancer (Schernhammer et al. 2006Hansen and Stevens 2011).

Circadian rhythm, metabolism, obesity, and cancer

Animal feeding and metabolism is intimately tied to the rotation of the earth through central and peripheral clocks that regulate metabolic genes, in keeping with the circadian feed and sleep cycle. In addition to the suprachiasmatic optic nuclei in the brain, which senses light and regulates rhythm centrally, individual cells have a transcription factor network, including CLOCK, Bmal, and Per proteins, that generates cyclic expression of genes that are dominated by those involved in metabolism (Sahar and Sassone-Corsi 2009Bass and Takahashi 2010). Hepatic expression of metabolic genes is rhythmically phased with feeding cycles by circadian transcriptional factors. It stands to reason that the feed and sleep cycle would be regulated in a fashion to maximize energy utilization and storage for survival and repair of daily damages from ongoing oxidative phosphorylation and oxidative stresses. The circadian network of transcription factors is hence critical for daily life of an animal.

Intriguingly, disruption of the feeding cycle as it relates to the day–night cycle can contribute to obesity in mice. Mice entrained to light and dark cycles consume ∼80% of food at night when they are active. Alterations in food availability have been documented to have a significant impact on the circadian clock and body weight. When a high-fat diet is only available during the light or sleep cycle, mice gain more weight than those with the same diet available during the dark, active wake cycle. This observation indicates that circadian regulation of organismal and cellular metabolism is related to the availability of nutrients (Sahar and Sassone-Corsi 2009). It is speculated that the disruption of food intake and sleep by artificial light could be key factors contributing to the epidemic of childhood obesity. The old adages “early to bed and early to rise makes a man healthy, wealthy, and wise” (Benjamin Franklin) and “eat breakfast like a king, lunch like a prince, and dinner like a pauper” (Adelle Davis) may both be sage advice with a scientific foundation. Obese animals and human beings are more susceptible to tumorigenesis, linking circadian disruption to obesity to cancer.

Obesity results in fat tissues that produce adipokines, which in turn causes insulin insensitivity in peripheral tissues. Insulin insensitivity leads to elevated blood glucose levels, which stimulate the production of insulin and IGF-1 from pancreatic β cells (Khandekar et al. 2011). The heightened circulating levels of insulin and IGF-1 are thought to provide a tonic growth stimulation of cells, rendering them susceptible to oncogenic mutations. Studies in animal models provide evidence to support this view; however, key mechanisms contributing to increased mutagenesis remain unclear. Intervention at the insulin and IGF-1 level appears to curb tumorigenesis in animal models, suggesting that growth signaling downstream from insulin/IGF contributes to enhanced tumorigenesis in obese animals. Clearly, the simple tonic stimulation of cells must be accompanied by somatic mutations, which bypass cell cycle checkpoints or apoptotic signals, to trigger tumor formation. Detailed understanding of these mechanisms, including inflammation, will require additional studies (Khandekar et al. 2011).

Caloric restriction and cancer risk

The simple perspective that excess calories contribute to obesity, which in turn heightens tumorigenesis, would lead to the oversimplified conclusion that the converse must also be true. Indeed, caloric restriction in a number of animal models and in epidemiologic studies suggests that limited calories prolong life span (Hursting et al. 2010Longo and Fontana 2010). Furthermore, caloric restriction in animal studies inhibits tumorigenesis, possibly through reduced IGF-1 levels. Notably, tumors that have activating PI3K mutations are resistant to caloric restriction, suggesting that diminished calories impact growth factor–receptor tyrosine kinase signaling through reduced IGF-1 levels such that mutations that activate the PI3K pathway render cancer cells resistant to caloric restriction (Kalaany and Sabatini 2009). The basis for diminished tumorigenesis in light of low calories is complex and may also be related to autophagy and mitophagy (the cellular process of lysosomally processing and recycling mitochondrial constituents) triggered through AMPK activation in a lowered energy state (Mihaylova and Shaw 2011). Activation of AMPK diminishes mTOR activity, leading to decreased cell growth. In fact, pharmacological inhibition of mTOR results in prolonged life span as well as diminished tumorigenesis. The effects on tumorigenesis, however, are complex because mTOR inhibition also affects inflammation and immune cells.

Inhibition of autophagy enhances senescence, which could be related to the inability of cells to clear defective mitochondria, thereby increasing oxidative stress and aging (Rabinowitz and White 2010Rubinsztein et al. 2011). Caloric restriction, on the other hand, would stimulate mitophagy, clearing cells of defective mitochondria (Youle and Narendra 2011). Enhanced mitochondrial efficiency, through removal of poorly functioning mitochondria, decreases oxidative stress and mutagenesis that appear to underpin the way by which caloric restriction decreases tumorigenesis. Intriguingly, severe caloric restriction can also lower basal-specific metabolic rates, which is associated with reduced cancer frequency, as discussed above (Colman et al. 2009). Thus, the combination of lowered basal metabolic rates and more efficient mitochondrial function could decrease mutagenic oxidative stress with caloric restriction.Go to:

Oncogenes, tumor suppressors, metabolic enzymes, and tumorigenesis

Metabolic genes as cancer genes

Although the Warburg effect describes altered cancer metabolism, alterations of metabolic genes that could provide a direct genetic link to altered metabolism were not known until the identification of mutant TCA cycle enzymes that are associated with familial cancer syndromes (King et al. 2006). Specifically, mutations in fumarate hydratase were found in families afflicted with leimyomatosis and kidney cancers, and mutations in succinate dehydrogenase were found in patients with pheochromocytoma and paragangliomas. These mutations cause a disruption of the TCA cycle with the accumulation of fumarate or succinate, both of which can inhibit dioxygenases or prolyl hydrolases that mediate the degradation of HIF proteins (King et al. 2006). Elevation of HIF proteins as a consequence is likely to be pro-oncogenic, but it is also notable that these carboxylic acids can also affect dioxygenases that are involved in epigenetic modulation. As such, the contributions of TCA cycle intermediates to tumorigenesis are likely to be multifaceted. More recently, mutations in IDH stemming from cancer genome sequencing efforts uncovered remarkable connections between a mutant metabolic enzyme and tumorigenesis (Parsons et al. 2008Yan et al. 2009). The mutant IDH enzyme possesses a neomorphic activity that converts aKG to 2-hydroxyglutarate (2-HG) as compared with the wild IDH activity, which converts isocitrate to aKG (Dang et al. 2009Gross et al. 2010). 2-HG has been documented to inhibit dioxygenases that are involved in histone and DNA demethylation (Xu et al. 2011). In fact, studies of IDH mutations in AML linked them to a subset of AML that clusters together as a subgroup with a distinct epigenome (Figueroa et al. 2010). Likewise, glioblastomas grouped together according to methylation status correlate with IDH status (Noushmehr et al. 2010). In this regard, the associations provide a compelling case for an oncogenic mutant metabolic enzyme that drives tumorigenesis epigenetically.

Synthetic lethality screens aimed at metabolic enzymes uncovered an unsuspected oncogenic role for PHGDH (phosphoglycerate dehydrogenase), which catalyzes the first step in serine synthesis (Locasale et al. 2011Possemato et al. 2011). PHGDH is involved in channeling glycolytic intermediates into a one-carbon metabolism involved in nucleotide biosynthesis. In fact, PHGDH is amplified in estrogen receptor-negative breast cancers, suggesting that it is an oncogenic enzyme when overexpressed. Loss of PHGDH decreases the level of a key TCA intermediate, aKG, but not serine, suggesting that PHGDH contributes to the TCA cycle anaplerotic flux (Possemato et al. 2011). Glycine decarboxylase (GLDC) is another enzyme that was recently implicated as an oncogenic enzyme, which is involved in glycine/serine metabolism and the one-carbon metabolic pathway (Zhang et al. 2012). Overexpression of GLDC is found in human lung cancer and experimentally promotes tumorigenesis. These two examples underscore the direct genetic evidence that altered metabolism contributes to tumorigenesis.

Mitochondrial DNA (mtDNA) mutations as tumorigenic drivers

In addition to oncogenic mutations in genes encoding enzymes, mutations in mtDNA could also contribute to tumorigenesis. A remarkable study of mtDNA mutations in normal tissues suggested that mtDNA heteroplasmy (a mixture of mutant and wild-type mtDNA in a population of cells) occurs during development without necessarily triggering cancer development (Polyak et al. 1998He et al. 2010). However, when compared with normal tissues, cancer tissue have increased missense mtDNA mutations, suggesting a selective advantage in acquiring these mutations. In this regard, experimental evidence through cybrid (fusing heterologous nuclei and cytoplasm from different cells) experiments supports a role for mtDNA mutations in enhanced tumorigenesis and metastasis (Petros et al. 2005). These findings further underscore a role for mutations that affect metabolism directly in oncogenesis.

Oncogenes and tumor suppressors regulate metabolism

While mutations in metabolic enzymes hardwire metabolism to tumorigenesis, mutations that activate oncogenes or inactivate tumor suppressors appear to “softwire” cancer genes to metabolism, because metabolic enzymes are directly regulated by these cancer genes. Indeed, Myc was first linked to regulation of glycolysis in aerobic cells through the direct activations of LDHA and virtually all glycolytic genes (Shim et al. 1997Dang et al. 2006). Myc was subsequently shown to activate genes involved in mitochondrial biogenesis and function as well as those involved in glutamine metabolism (Li et al. 2005Wise et al. 2008Gao et al. 2009). Mutated Ras also enhances glycolysis, partly through increasing the activity of Myc and HIF (Sears et al. 1999Semenza 2010). HIF-1 could be elevated under aerobic conditions downstream from activated PI3K, which stimulates the synthesis of HIF-1. Loss of the tumor suppressor VHL in kidney cancer also stabilizes HIF-1, permitting it to activate glycolytic genes, which are normally activated by HIF-1 under hypoxic conditions. Intriguingly, HIF-1 could inhibit physiologic Myc function and provide a means to attenuate normal cell growth when oxygen is limited. HIF-2, however, could increase Myc function, which may be relevant in the context of normal cells that could proliferate under hypoxia, such as endothelial cells, which express high levels of HIF-2 rather than HIF-1 in hypoxia (Gordan et al. 20072008). These interactions between Myc and HIFs could explain the existence of subsets of kidney cancers, and the occurrence of HIF-1α mutations in these cancers (Shen et al. 2011). When Myc is overexpressed in cancer cells, however, HIF-1 could not stoichiometrically inhibit the function of Myc (Kim et al. 2007). High levels of Myc not only increase HIF-1 levels, but also allow Myc (and N-Myc) to collaborate with HIF-1 (Qing et al. 2010).

Mutations of PI3K, PTEN, and p53 are prevalent in human cancers. Mutation of PI3K activates its function through the downstream activation of AKT and stabilization of HIF-1. PI3K is opposed by the tumor suppressor PTEN, which is frequently lost in human prostate cancer. Hence, activation of PI3K and loss of PTEN affects cellular metabolism because AKT and HIF-1 both profoundly increase glycolysis (Elstrom et al. 2004). In contrast to Myc, neither AKT nor HIF-1 enhances mitochondrial biogenesis and respiration. Myc is unique in that it drives parallel pathways that all contribute to the overall increased metabolic function of the cancer cell. In this regard, it is notable that resistance to PI3K pathway inhibition in human mammary cells and in a murine model of breast cancer is associated with MYC gene amplification, which bypasses signaling downstream from PI3K (Ilic et al. 2011Liu et al. 2011). Intriguingly, the Myc target gene eIF4E, which is involved in protein synthesis, is also amplified in PI3K inhibition-resistant human mammary cells (Ilic et al. 2011), suggesting that the roles of Myc and eIF4E in biomass accumulation could underpin their lack of dependence on the PI3K pathway.

p53 is another prominent tumor suppressor that is eliminated in many human cancers. In addition to its role in cell cycle control, p53 also directly activates genes such as TIGAR, a PFKFB family member that inhibits glycolysis, shunting glucose into the PPP. p53 also activates genes such as SCO2 that enhance more efficient mitochondrial respiration (Bensaad et al. 2006Matoba et al. 2006Vousden and Ryan 2009Wang et al. 2012). Hence, loss of p53 tends to favor glycolysis. p53 was also documented to activate the expression of the liver form of glutaminase (Gls2), in contrast to Myc, which increases the expression of the kidney form of glutaminase (Gls or Gls1) (Hu et al. 2010Suzuki et al. 2010).

Although the links between oncogenes, tumor suppressors, and metabolism are being established in experimental cell models, oncogenic alterations of metabolism in vivo appear to depend on the specific oncogene and the tissue type. The recent study by Yuneva et al. (2012) illustrates that oncogenic drive and organ site profoundly influence the cellular usage of glucose or glutamine. Myc-driven murine liver cancer depends on high levels of glycolysis and glutaminolysis (Hu et al. 2011), while Met oncogene-driven liver cancer has markedly diminished glutaminolysis and displays an ability to synthesize glutamine (Yuneva et al. 2012). Myc-driven lung cancer cells also have glutamine synthetase activity as well as high glycolytic and glutaminolytic rates. It is notable that Myc-induced liver cancer is associated with an aggressive tumor phenotype and histology, while Met-induced liver cancer is relatively indolent and is associated with a more differentiated phenotype. As such, how oncogenes drive tumorigenesis and the resulting state of cellular differentiation can profoundly affect the metabolic profile of cancer cells.Go to:

Metabolic rewiring and the tumor microenvironment

Genetic alterations in the nuclear and mitochondrial genomes of cancer cells are linked to altered cancer metabolism. However, these cell-autonomous changes are modulated by the environment of the cancer cell, characterized by poor blood perfusion, hypoxia, and nutrient limitations. Hypoxia induces HIF-1 or HIF-2, which in turn activates a transcriptional program that alters the metabolic profile of cancer cells (Bertout et al. 2008Semenza 2010). In particular, HIF-1 induces glycolysis and inhibits mitochondrial biogenesis, thereby superimposing its influence on the cell-autonomous metabolic changes caused by activation of oncogenes or loss of tumor suppressors. In this regard, one could imagine that there would be aerobic cells that undergo oxidative phosphorylation surrounding a blood vessel within a tumor bed (Semenza 2012). Cells distal to the blood vessel, however, would be robbed of an oxygen supply by cells located immediately around the blood vessel (Schroeder et al. 2005). These distal hypoxic cells would have a different metabolic profile than those located around the blood vessel. Indeed, one study supports the view that hypoxic cells distal to the blood vessel convert glucose to lactate, which could then be imported into aerobic cells and converted to pyruvate for oxidation in the mitochondrion (Sonveaux et al. 2008).

This concept of a symbiotic relationship between cells in the tumor microenvironment has been extended to suggest that the Warburg effect occurs in stromal cells, rather than in cancer cells that feed off of stromal cell-generated lactate (Martinez-Outschoorn et al. 2011). While this view is stimulating and provocative, it does not account for many observations that support cell-autonomous changes in cancer cell metabolism as discussed above. An area that needs further study is the occurrence of fibrotic material in the tumor bed and the role of immune cells in the metabolic milieu of the tumor microenvironment (Shiao et al. 2011). Hence, additional studies are necessary to delineate the contributions of the stroma and immune cells to tumor tissue metabolism. Additional insights will likely change our current oversimplified view of tumor metabolism.Go to:

Therapeutic opportunities

Given our current understanding of the contributions of glucose and glutamine to tumor metabolism, is there an opportunity to generate a new class of anti-tumor drugs that target altered metabolism in cancer cells? Are there differences between normal cell metabolism and cancer cell metabolism that provide clinically relevant therapeutic windows? These questions have been addressed by a number of recent excellent reviews (Vander Heiden 2011Jones and Schulze 2012), and here we focus on several key issues.

It appears that normal T cells use metabolic programs very similar to those used by cancer cells to stimulate cell growth and proliferation. It is notable, however, that in the case of Myc oncogene-stimulated tumorigenesis, deregulated Myc renders Myc-transformed cells addicted to glucose and glutamine such that nutrient deprivation triggers Myc-transformed cell death. In contrast, MYCexpression is attenuated in nutrient-deprived normal cells. As proof of concept that Myc-transformed cells’ addiction to nutrients could be targeted, inhibitors of LDHA and glutaminase have been shown to have preclinical anti-tumor effects in vivo (Le et al. 20102012Wang et al. 2010).

The metabolic similarities between normal T cells and cancer cells suggest that anti-cancer metabolic inhibitors could modulate immune cells. It is hence not surprising that cyclosporine, which inhibits TOR, is an effective immunosuppressant. Mycophenolic acid, an inhibitor of IMPDH and pyrimidine biosynthesis, is yet another clinically used immunosuppressant. Both agents also display anti-tumor effects in animal studies. Thus, the question is whether there is a therapeutic window in the absence of mutations in specific metabolic enzymes such as IDH1 or IDH2. An animal model of MYC-induced hepatocellular carcinoma has elucidated one such candidate: In this model, liver tumor tissues have elevated Gls1 (kidney form) expression, while expression of Gls2 (liver form) is depressed in tumors (Hu et al. 2011). BPTES is a potent specific inhibitor of Gls1 but not Gls2, providing rational therapy in liver cancer (Wang et al. 2010Delabarre et al. 2011Cassago et al. 2012Le et al. 2012). In this regard, an isozyme switch could also be targeted. Another example is the switch of pyruvate from PKM1 to PKM2 in tumor tissues; specific inhibitors or, counterintuitively, activators of PKM2 could be tumor-selective (Vander Heiden et al. 2009bJiang et al. 2010).

Mutant IDH1 or IDH2 enzyme poses a more tractable problem, as inhibitors specific for the mutant neoenzyme would conceptually provide a significant therapeutic opportunity because the mutant enzyme possesses a new enzymatic activity that could be specifically targeted. In other cases of increased expression—as in the case of LDHAPHGDH, and GLDC—it is possible that there is a sufficient therapeutic window to target these enzymes. Fatty acid synthase (FASN), which catalyzes the synthesis of palmitate, was noted to be elevated in many human cancers and has been a target of interest for cancer therapy (Kuhajda et al. 1994Zhou et al. 2003). Some cancers have amplicons that involve FASN and hence could provide a therapeutic window. The major metabolic enzyme targets have become key interests for many pharmaceutical companies. In addition, HIF is also another target of great interest (Semenza 2010). In fact, a number of HIF targets, such as carbonic anhydrase IX (CAIX) and the monocarboxylate transporter MCT4 (as well as the non-HIF target MCT1), are also of major interest as therapeutic targets (Brahimi-Horn et al. 2011Morris et al. 2011). Hence, in the next 5–10 years, it is anticipated that we will see a number of metabolic inhibitors making it to the clinic.

Aside from targeted therapies based on tumor metabolic profiles, empirical observations of the effect of metformin on reducing cancer incidences led to intriguing leads for cancer metabolic therapy. Metformin inhibits mitochondrial complex I activity and hence is an example of mitochondrial metabolic inhibitor (Bost et al. 2012). Given the epidemiological evidence of reduction in cancer incidence for patients who took metformin for diabetes as compared with those treated with insulin, there are now a number of clinical trials aimed toward testing whether metformin could have an anti-tumor effect. The anti-malarial drug chloroquine is also being repurposed to block autophagy in cancer prevention and therapeutic clinical trials (Amaravadi et al. 2011). Targeting metabolism hence is a new strategy to develop a new class of anti-cancer drugs.Go to:

Conclusions

Metabolism is part and parcel of life, with plants and photosynthetic microorganisms capturing energy from sunlight to feed all other earth life forms. Development and growth of a mammal is inherently tied to the availability of nutrients such that mechanisms have evolved for animals to survive severe starvation. Intriguingly, energy deprivation prolongs life span, while excess calories are associated with obesity, human cancer, and shortened life span. At the cellular level, normal proliferating cells activate metabolic pathways and couple them with cell mass accumulation and DNA synthesis for cell reproduction. Normal cells sense nutrient cues and evolve mechanisms to diminish macromolecular synthesis and ATP consumption while enhancing ATP production pathways when deprived of nutrients. Autophagy evolved to sustain starved cells through self-eating to recycle cell components for energy production. The by-products of metabolism, specifically ROS, can damage cells and promote oncogenic DNA mutations; thus, metabolism can trigger tumorigenesis. Mutations of oncogenes and tumor suppressors, in turn, drive cell growth and proliferation coupled with import of adequate bioenergetic substrates. In this regard, mutant metabolic enzymes can drive tumorigenesis, and conversely, cancer genes regulate metabolism such that cellular machineries driving cell growth and proliferation are tightly coupled with the cell’s ability to assimilate nutrients and energy.

The therapeutic windows for targeting cancer cell metabolism reside in differences between normal and mutant oncogenic enzymes and addiction of cancer cells to nutrients to support deregulated cell growth programs enforced by cancer genes. Hence, the complex regulatory networks involving cancer genes and metabolic pathways need to be defined for specific cancer types so that targeting of cancer cell metabolism could be strategically guided by somatic genetic changes in cancers. Given the explosion of interest and information on cancer metabolism, it is hoped that new therapies will emerge from the basic sciences of metabolism in the next decade.Go to:

Acknowledgments

I thank Brian Altman for comments. My original work is supported by an AACR Stand-Up-to-Cancer translational grant, Leukemia and Lymphoma Society, and NCI. I am also supported by the Abramson Family Cancer Research Institute at the University of Pennsylvania. Many original articles were omitted due to space limitations; for this, I apologize.Go to:

Footnotes

Article is online at http://www.genesdev.org/cgi/doi/10.1101/gad.189365.112.Go to:

References

  • Amaravadi RK, Lippincott-Schwartz J, Yin XM, Weiss WA, Takebe N, Timmer W, DiPaola RS, Lotze MT, White E 2011. Principles and current strategies for targeting autophagy for cancer treatment. Clin Cancer Res 17: 654–666 [PMC free article] [PubMed]
  • Anastasiou D, Poulogiannis G, Asara JM, Boxer MB, Jiang JK, Shen M, Bellinger G, Sasaki AT, Locasale JW, Auld DS, et al. 2011. Inhibition of pyruvate kinase M2 by reactive oxygen species contributes to cellular antioxidant responses. Science 334: 1278–1283 [PMC free article] [PubMed]
  • Barna M, Pusic A, Zollo O, Costa M, Kondrashov N, Rego E, Rao PH, Ruggero D 2008. Suppression of Myc oncogenic activity by ribosomal protein haploinsufficiency. Nature 456: 971–975 [PMC free article] [PubMed]
  • Bass J, Takahashi JS 2010. Circadian integration of metabolism and energetics. Science 330: 1349–1354 [PMC free article] [PubMed]
  • Bello-Fernandez C, Cleveland JL 1992. c-myc transactivates the ornithine decarboxylase gene. Curr Top Microbiol Immunol 182: 445–452 [PubMed]
  • Bensaad K, Tsuruta A, Selak MA, Vidal MN, Nakano K, Bartrons R, Gottlieb E, Vousden KH 2006.TIGAR, a p53-inducible regulator of glycolysis and apoptosis. Cell 126: 107–120 [PubMed]
  • Berg JM, Tymoczko JL, Stryer L 2002. Biochemistry. W.H. Freeman and Company, New York
  • Bertout JA, Patel SA, Simon MC 2008. The impact of O2 availability on human cancer. Nat Rev Cancer 8: 967–975 [PMC free article] [PubMed]
  • Bost F, Sahra IB, Le Marchand-Brustel Y, Tanti JF 2012. Metformin and cancer therapy. Curr Opin Oncol 24: 103–108 [PubMed]
  • Brahimi-Horn MC, Bellot G, Pouyssegur J 2011. Hypoxia and energetic tumour metabolism. Curr Opin Genet Dev 21: 67–72 [PubMed]
  • Cairns RA, Harris IS, Mak TW 2011. Regulation of cancer cell metabolism. Nat Rev Cancer 11: 85–95 [PubMed]
  • Carmeliet P, Dor Y, Herbert JM, Fukumura D, Brusselmans K, Dewerchin M, Neeman M, Bono F, Abramovitch R, Maxwell P, et al. 1998. Role of HIF-1α in hypoxia-mediated apoptosis, cell proliferation and tumour angiogenesis. Nature 394: 485–490 [PubMed]
  • Cassago A, Ferreira AP, Ferreira IM, Fornezari C, Gomes ER, Greene KS, Pereira HM, Garratt RC, Dias SM, Ambrosio AL 2012. Mitochondrial localization and structure-based phosphate activation mechanism of Glutaminase C with implications for cancer metabolism. Proc Natl Acad Sci 109: 1092–1097 [PMC free article] [PubMed]
  • Caulin AF, Maley CC 2011. Peto’s paradox: Evolution’s prescription for cancer prevention. Trends Ecol Evol 26: 175–182 [PMC free article] [PubMed]
  • Chen Z, Odstrcil EA, Tu BP, McKnight SL 2007. Restriction of DNA replication to the reductive phase of the metabolic cycle protects genome integrity. Science 316: 1916–1919 [PubMed]
  • Chowdhury R, Yeoh KK, Tian YM, Hillringhaus L, Bagg EA, Rose NR, Leung IK, Li XS, Woon EC, Yang M, et al. 2011. The oncometabolite 2-hydroxyglutarate inhibits histone lysine demethylases. EMBO Rep 12: 463–469 [PMC free article] [PubMed]
  • Collman JP, Ghosh S, Dey A, Decreau RA 2009. Using a functional enzyme model to understand the chemistry behind hydrogen sulfide induced hibernation. Proc Natl Acad Sci 106: 22090–22095 [PMC free article] [PubMed]
  • Colman RJ, Anderson RM, Johnson SC, Kastman EK, Kosmatka KJ, Beasley TM, Allison DB, Cruzen C, Simmons HA, Kemnitz JW, et al. 2009. Caloric restriction delays disease onset and mortality in rhesus monkeys. Science 325: 201–204 [PMC free article] [PubMed]
  • Dang CV 2010. Rethinking the Warburg effect with Myc micromanaging glutamine metabolism. Cancer Res 70: 859–862 [PMC free article] [PubMed]
  • Dang CV, O’Donnell KA, Zeller KI, Nguyen T, Osthus RC, Li F 2006. The c-Myc target gene network. Semin Cancer Biol 16: 253–264 [PubMed]
  • Dang L, White DW, Gross S, Bennett BD, Bittinger MA, Driggers EM, Fantin VR, Jang HG, Jin S, Keenan MC, et al. 2009. Cancer-associated IDH1 mutations produce 2-hydroxyglutarate. Nature462: 739–744 [PMC free article] [PubMed]
  • Dark J 2005. Annual lipid cycles in hibernators: Integration of physiology and behavior. Annu Rev Nutr 25: 469–497 [PubMed]
  • DeBerardinis RJ, Cheng T 2010. Q’s next: The diverse functions of glutamine in metabolism, cell biology and cancer. Oncogene 29: 313–324 [PMC free article] [PubMed]
  • Deisenroth C, Zhang Y 2011. The ribosomal protein–Mdm2–p53 pathway and energy metabolism: Bridging the gap between feast and famine. Genes Cancer 2: 392–403 [PMC free article] [PubMed]
  • Delabarre B, Gross S, Fang C, Gao Y, Jha A, Jiang F, Song JJ, Wei W, Hurov JB 2011. Full-length human glutaminase in complex with an allosteric inhibitor. Biochemistry 50: 10764–10770 [PubMed]
  • Elstrom RL, Bauer DE, Buzzai M, Karnauskas R, Harris MH, Plas DR, Zhuang H, Cinalli RM, Alavi A, Rudin CM, et al. 2004. Akt stimulates aerobic glycolysis in cancer cells. Cancer Res 64: 3892–3899 [PubMed]
  • Ferber EC, Peck B, Delpuech O, Bell GP, East P, Schulze A 2011. FOXO3a regulates reactive oxygen metabolism by inhibiting mitochondrial gene expression. Cell Death Differ doi: 10.1038/cdd.2011.179 [PMC free article] [PubMed]
  • Figueroa ME, Abdel-Wahab O, Lu C, Ward PS, Patel J, Shih A, Li Y, Bhagwat N, Vasanthakumar A, Fernandez HF, et al. 2010. Leukemic IDH1 and IDH2 mutations result in a hypermethylation phenotype, disrupt TET2 function, and impair hematopoietic differentiation. Cancer Cell 18: 553–567 [PMC free article] [PubMed]
  • Finkel T 2011. Signal transduction by reactive oxygen species. J Cell Biol 194: 7–15 [PMC free article][PubMed]
  • Gao P, Tchernyshyov I, Chang TC, Lee YS, Kita K, Ochi T, Zeller KI, De Marzo AM, Van Eyk JE, Mendell JT, et al. 2009. c-Myc suppression of miR-23a/b enhances mitochondrial glutaminase expression and glutamine metabolism. Nature 458: 762–765 [PMC free article] [PubMed]
  • Golomb L, Bublik DR, Wilder S, Nevo R, Kiss V, Grabusic K, Volarevic S, Oren M 2012. Importin 7 and exportin 1 link c-Myc and p53 to regulation of ribosomal biogenesis. Mol Cell 45: 222–232 [PMC free article] [PubMed]
  • Gomez-Roman N, Felton-Edkins ZA, Kenneth NS, Goodfellow SJ, Athineos D, Zhang J, Ramsbottom BA, Innes F, Kantidakis T, Kerr ER, et al. 2006. Activation by c-Myc of transcription by RNA polymerases I, II and III. Biochem Soc Symp 2006: 141–154 [PubMed]
  • Gordan JD, Bertout JA, Hu CJ, Diehl JA, Simon MC 2007. HIF-2α promotes hypoxic cell proliferation by enhancing c-myc transcriptional activity. Cancer Cell 11: 335–347 [PMC free article] [PubMed]
  • Gordan JD, Lal P, Dondeti VR, Letrero R, Parekh KN, Oquendo CE, Greenberg RA, Flaherty KT, Rathmell WK, Keith B, et al. 2008. HIF-α effects on c-Myc distinguish two subtypes of sporadic VHL-deficient clear cell renal carcinoma. Cancer Cell 14: 435–446 [PMC free article] [PubMed]
  • Gross S, Cairns RA, Minden MD, Driggers EM, Bittinger MA, Jang HG, Sasaki M, Jin S, Schenkein DP, Su SM, et al. 2010. Cancer-associated metabolite 2-hydroxyglutarate accumulates in acute myelogenous leukemia with isocitrate dehydrogenase 1 and 2 mutations. J Exp Med 207: 339–344 [PMC free article] [PubMed]
  • Guan KL, Xiong Y 2011. Regulation of intermediary metabolism by protein acetylation. Trends Biochem Sci 36: 108–116 [PMC free article] [PubMed]
  • Hansen J, Stevens RG 2011. Case-control study of shift-work and breast cancer risk in Danish nurses: Impact of shift systems. Eur J Cancer doi: 10.1016/j.ejca.2011.07.005 [PubMed]
  • He Y, Wu J, Dressman DC, Iacobuzio-Donahue C, Markowitz SD, Velculescu VE, Diaz LA Jr, Kinzler KW, Vogelstein B, Papadopoulos N 2010. Heteroplasmic mitochondrial DNA mutations in normal and tumour cells. Nature 464: 610–614 [PMC free article] [PubMed]
  • Herman AB, Savage VM, West GB 2011. A quantitative theory of solid tumor growth, metabolic rate and vascularization. PLoS ONE 6: e22973 doi: 10.1371/journal.pone.0022973 [PMC free article][PubMed]
  • Hsu PP, Sabatini DM 2008. Cancer cell metabolism: Warburg and beyond. Cell 134: 703–707 [PubMed]
  • Hu W, Zhang C, Wu R, Sun Y, Levine A, Feng Z 2010. Glutaminase 2, a novel p53 target gene regulating energy metabolism and antioxidant function. Proc Natl Acad Sci 107: 7455–7460 [PMC free article] [PubMed]
  • Hu S, Balakrishnan A, Bok RA, Anderton B, Larson PE, Nelson SJ, Kurhanewicz J, Vigneron DB, Goga A 2011. 13C-pyruvate imaging reveals alterations in glycolysis that precede c-Myc-induced tumor formation and regression. Cell Metab 14: 131–142 [PMC free article] [PubMed]
  • Huang H, Tindall DJ 2007. Dynamic FoxO transcription factors. J Cell Sci 120: 2479–2487 [PubMed]
  • Hursting SD, Smith SM, Lashinger LM, Harvey AE, Perkins SN 2010. Calories and carcinogenesis: Lessons learned from 30 years of calorie restriction research. Carcinogenesis 31: 83–89 [PubMed]
  • Ilic N, Utermark T, Widlund HR, Roberts TM 2011. PI3K-targeted therapy can be evaded by gene amplification along the MYC-eukaryotic translation initiation factor 4E (eIF4E) axis. Proc Natl Acad Sci 108: E699–E708 doi: 10.1073/pnas.1108237108 [PMC free article] [PubMed]
  • Ji H, Wu G, Zhan X, Nolan A, Koh C, De Marzo A, Doan HM, Fan J, Cheadle C, Fallahi M, et al. 2011. Cell-type independent MYC target genes reveal a primordial signature involved in biomass accumulation. PLoS ONE 6: e26057 doi: 10.1371/journal.pone.0026057 [PMC free article][PubMed]
  • Jiang JK, Boxer MB, Vander Heiden MG, Shen M, Skoumbourdis AP, Southall N, Veith H, Leister W, Austin CP, Park HW, et al. 2010. Evaluation of thieno[3,2-b]pyrrole[3,2-d]pyridazinones as activators of the tumor cell specific M2 isoform of pyruvate kinase. Bioorg Med Chem Lett 20: 3387–3393 [PMC free article] [PubMed]
  • Jones NP, Schulze A 2012. Targeting cancer metabolism—aiming at a tumour’s sweet-spot. Drug Discov Today 17: 232–241 [PubMed]
  • Kaadige MR, Looper RE, Kamalanaadhan S, Ayer DE 2009. Glutamine-dependent anapleurosis dictates glucose uptake and cell growth by regulating MondoA transcriptional activity. Proc Natl Acad Sci 106: 14878–14883 [PMC free article] [PubMed]
  • Kalaany NY, Sabatini DM 2009. Tumours with PI3K activation are resistant to dietary restriction. Nature 458: 725–731 [PMC free article] [PubMed]
  • Katada S, Imhof A, Sassone-Corsi P 2012. Connecting threads: Epigenetics and metabolism. Cell 148: 24–28 [PubMed]
  • Keith B, Johnson RS, Simon MC 2012. HIF1α and HIF2α: Sibling rivalry in hypoxic tumour growth and progression. Nat Rev Cancer 12: 9–22 [PMC free article] [PubMed]
  • Khandekar MJ, Cohen P, Spiegelman BM 2011. Molecular mechanisms of cancer development in obesity. Nat Rev Cancer 11: 886–895 [PubMed]
  • Kilburn DG, Lilly MD, Webb FC 1969. The energetics of mammalian cell growth. J Cell Sci 4: 645–654 [PubMed]
  • Kim JW, Tchernyshyov I, Semenza GL, Dang CV 2006. HIF-1-mediated expression of pyruvate dehydrogenase kinase: A metabolic switch required for cellular adaptation to hypoxia. Cell Metab3: 177–185 [PubMed]
  • Kim JW, Gao P, Liu YC, Semenza GL, Dang CV 2007. Hypoxia-inducible factor 1 and dysregulated c-Myc cooperatively induce vascular endothelial growth factor and metabolic switches hexokinase 2 and pyruvate dehydrogenase kinase 1. Mol Cell Biol 27: 7381–7393 [PMC free article] [PubMed]
  • King A, Selak MA, Gottlieb E 2006. Succinate dehydrogenase and fumarate hydratase: Linking mitochondrial dysfunction and cancer. Oncogene 25: 4675–4682 [PubMed]
  • Klosinska MM, Crutchfield CA, Bradley PH, Rabinowitz JD, Broach JR 2011. Yeast cells can access distinct quiescent states. Genes Dev 25: 336–349 [PMC free article] [PubMed]
  • Koppenol WH, Bounds PL, Dang CV 2011. Otto Warburg’s contributions to current concepts of cancer metabolism. Nat Rev Cancer 11: 325–337 [PubMed]
  • Kuhajda FP, Jenner K, Wood FD, Hennigar RA, Jacobs LB, Dick JD, Pasternack GR 1994. Fatty acid synthesis: A potential selective target for antineoplastic therapy. Proc Natl Acad Sci 91: 6379–6383 [PMC free article] [PubMed]
  • Lau LF, Nathans D 1987. Expression of a set of growth-related immediate early genes in BALB/c 3T3 cells: Coordinate regulation with c-fos or c-myc. Proc Natl Acad Sci 84: 1182–1186 [PMC free article] [PubMed]
  • Le A, Cooper CR, Gouw AM, Dinavahi R, Maitra A, Deck LM, Royer RE, Vander Jagt DL, Semenza GL, Dang CV 2010. Inhibition of lactate dehydrogenase A induces oxidative stress and inhibits tumor progression. Proc Natl Acad Sci 107: 2037–2042 [PMC free article] [PubMed]
  • Le A, Lane AN, Hamaker M, Bose S, Gouw A, Barbi J, Tsukamoto T, Rojas CJ, Slusher BS, Zhang H, et al. 2012. Glucose-independent glutamine metabolism via TCA cycling for proliferation and survival in B cells. Cell Metab 15: 110–121 [PMC free article] [PubMed]
  • Leone G, Sears R, Huang E, Rempel R, Nuckolls F, Park CH, Giangrande P, Wu L, Saavedra HI, Field SJ, et al. 2001. Myc requires distinct E2F activities to induce S phase and apoptosis. Mol Cell 8: 105–113 [PubMed]
  • Levine AJ, Puzio-Kuter AM 2010. The control of the metabolic switch in cancers by oncogenes and tumor suppressor genes. Science 330: 1340–1344 [PubMed]
  • Li F, Wang Y, Zeller KI, Potter JJ, Wonsey DR, O’Donnell KA, Kim JW, Yustein JT, Lee LA, Dang CV 2005. Myc stimulates nuclearly encoded mitochondrial genes and mitochondrial biogenesis. Mol Cell Biol 25: 6225–6234 [PMC free article] [PubMed]
  • Lippman SI, Broach JR 2009. Protein kinase A and TORC1 activate genes for ribosomal biogenesis by inactivating repressors encoded by Dot6 and its homolog Tod6. Proc Natl Acad Sci 106: 19928–19933 [PMC free article] [PubMed]
  • Liu P, Cheng H, Santiago S, Raeder M, Zhang F, Isabella A, Yang J, Semaan DJ, Chen C, Fox EA, et al. 2011. Oncogenic PIK3CA-driven mammary tumors frequently recur via PI3K pathway-dependent and PI3K pathway-independent mechanisms. Nat Med 17: 1116–1120 [PMC free article][PubMed]
  • Lo CC, Chou T, Penzel T, Scammell TE, Strecker RE, Stanley HE, Ivanov P 2004. Common scale-invariant patterns of sleep-wake transitions across mammalian species. Proc Natl Acad Sci 101: 17545–17548 [PMC free article] [PubMed]
  • Locasale JW, Cantley LC 2011. Metabolic flux and the regulation of mammalian cell growth. Cell Metab 14: 443–451 [PMC free article] [PubMed]
  • Locasale JW, Grassian AR, Melman T, Lyssiotis CA, Mattaini KR, Bass AJ, Heffron G, Metallo CM, Muranen T, Sharfi H, et al. 2011. Phosphoglycerate dehydrogenase diverts glycolytic flux and contributes to oncogenesis. Nat Genet 43: 869–874 [PMC free article] [PubMed]
  • Longo VD, Fontana L 2010. Calorie restriction and cancer prevention: Metabolic and molecular mechanisms. Trends Pharmacol Sci 31: 89–98 [PMC free article] [PubMed]
  • Macias E, Jin A, Deisenroth C, Bhat K, Mao H, Lindstrom MS, Zhang Y 2010. An ARF-independent c-MYC-activated tumor suppression pathway mediated by ribosomal protein-Mdm2 Interaction. Cancer Cell 18: 231–243 [PMC free article] [PubMed]
  • Martinez-Outschoorn UE, Lin Z, Trimmer C, Flomenberg N, Wang C, Pavlides S, Pestell RG, Howell A, Sotgia F, Lisanti MP 2011. Cancer cells metabolically ‘fertilize’ the tumor microenvironment with hydrogen peroxide, driving the Warburg effect: Implications for PET imaging of human tumors. Cell Cycle 10: 2504–2520 [PMC free article] [PubMed]
  • Matoba S, Kang JG, Patino WD, Wragg A, Boehm M, Gavrilova O, Hurley PJ, Bunz F, Hwang PM 2006. p53 regulates mitochondrial respiration. Science 312: 1650–1653 [PubMed]
  • Metallo CM, Gameiro PA, Bell EL, Mattaini KR, Yang J, Hiller K, Jewell CM, Johnson ZR, Irvine DJ, Guarente L, et al. 2012. Reductive glutamine metabolism by IDH1 mediates lipogenesis under hypoxia. Nature 481: 380–384 [PMC free article] [PubMed]
  • Mihaylova MM, Shaw RJ 2011. The AMPK signalling pathway coordinates cell growth, autophagy and metabolism. Nat Cell Biol 13: 1016–1023 [PMC free article] [PubMed]
  • Morris JC, Chiche J, Grellier C, Lopez M, Bornaghi LF, Maresca A, Supuran CT, Pouyssegur J, Poulsen SA 2011. Targeting hypoxic tumor cell viability with carbohydrate-based carbonic anhydrase IX and XII inhibitors. J Med Chem 54: 6905–6918 [PubMed]
  • Morrish F, Isern N, Sadilek M, Jeffrey M, Hockenbery DM 2009. c-Myc activates multiple metabolic networks to generate substrates for cell-cycle entry. Oncogene 28: 2485–2491 [PMC free article][PubMed]
  • Mullen AR, Wheaton WW, Jin ES, Chen PH, Sullivan LB, Cheng T, Yang Y, Linehan WM, Chandel NS, DeBerardinis RJ 2012. Reductive carboxylation supports growth in tumour cells with defective mitochondria. Nature 481: 385–388 [PMC free article] [PubMed]
  • Nagy JD, Victor EM, Cropper JH 2007. Why don’t all whales have cancer? A novel hypothesis resolving Peto’s paradox. Integr Comp Biol 47: 317–328 [PubMed]
  • Noushmehr H, Weisenberger DJ, Diefes K, Phillips HS, Pujara K, Berman BP, Pan F, Pelloski CE, Sulman EP, Bhat KP, et al. 2010. Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma. Cancer Cell 17: 510–522 [PMC free article] [PubMed]
  • Owen OE, Kalhan SC, Hanson RW 2002. The key role of anaplerosis and cataplerosis for citric acid cycle function. J Biol Chem 277: 30409–30412 [PubMed]
  • Parsons DW, Jones S, Zhang X, Lin JC, Leary RJ, Angenendt P, Mankoo P, Carter H, Siu IM, Gallia GL, et al. 2008. An integrated genomic analysis of human glioblastoma multiforme. Science 321: 1807–1812 [PMC free article] [PubMed]
  • Peterson CW, Ayer DE 2012. An extended Myc network contributes to glucose homeostasis in cancer and diabetes. Front Biosci 17: 2206–2223 [PubMed]
  • Petros JA, Baumann AK, Ruiz-Pesini E, Amin MB, Sun CQ, Hall J, Lim S, Issa MM, Flanders WD, Hosseini SH, et al. 2005. mtDNA mutations increase tumorigenicity in prostate cancer. Proc Natl Acad Sci 102: 719–724 [PMC free article] [PubMed]
  • Plas DR, Thompson CB 2005. Akt-dependent transformation: There is more to growth than just surviving. Oncogene 24: 7435–7442 [PubMed]
  • Polyak K, Li Y, Zhu H, Lengauer C, Willson JK, Markowitz SD, Trush MA, Kinzler KW, Vogelstein B 1998. Somatic mutations of the mitochondrial genome in human colorectal tumours. Nat Genet 20: 291–293 [PubMed]
  • Possemato R, Marks KM, Shaul YD, Pacold ME, Kim D, Birsoy K, Sethumadhavan S, Woo HK, Jang HG, Jha AK, et al. 2011. Functional genomics reveal that the serine synthesis pathway is essential in breast cancer. Nature 476: 346–350 [PMC free article] [PubMed]
  • Qing G, Skuli N, Mayes PA, Pawel B, Martinez D, Maris JM, Simon MC 2010. Combinatorial regulation of neuroblastoma tumor progression by N-Myc and hypoxia inducible factor HIF-1α. Cancer Res 70: 10351–10361 [PMC free article] [PubMed]
  • Rabinowitz JD, White E 2010. Autophagy and metabolism. Science 330: 1344–1348 [PMC free article][PubMed]
  • Ray PD, Huang BW, Tsuji Y 2012. Reactive oxygen species (ROS) homeostasis and redox regulation in cellular signaling. Cell Signal 24: 981–990 [PMC free article] [PubMed]
  • Rempel RE, Mori S, Gasparetto M, Glozak MA, Andrechek ER, Adler SB, Laakso NM, Lagoo AS, Storms R, Smith C, et al. 2009. A role for E2F activities in determining the fate of Myc-induced lymphomagenesis. PLoS Genet 5: e1000640 doi: 10.1371/journal.pgen.1000640 [PMC free article][PubMed]
  • Ros S, Santos CR, Moco S, Baenke F, Kelly G, Howell M, Zamboni N, Schulze A 2012. Functional metabolic screen identifies 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 4 (PFKFB4) as an important regulator of prostate cancer cell survival. Cancer Discovery doi: 10.1158/2159-8290.CD-11-0234 [PubMed]
  • Rubinsztein DC, Marino G, Kroemer G 2011. Autophagy and aging. Cell 146: 682–695 [PubMed]
  • Sahar S, Sassone-Corsi P 2009. Metabolism and cancer: The circadian clock connection. Nat Rev Cancer 9: 886–896 [PubMed]
  • Samudio I, Harmancey R, Fiegl M, Kantarjian H, Konopleva M, Korchin B, Kaluarachchi K, Bornmann W, Duvvuri S, Taegtmeyer H, et al. 2010. Pharmacologic inhibition of fatty acid oxidation sensitizes human leukemia cells to apoptosis induction. J Clin Invest 120: 142–156 [PMC free article] [PubMed]
  • Savage VM, Allen AP, Brown JH, Gillooly JF, Herman AB, Woodruff WH, West GB 2007. Scaling of number, size, and metabolic rate of cells with body size in mammals. Proc Natl Acad Sci 104: 4718–4723 [PMC free article] [PubMed]
  • Schernhammer ES, Kroenke CH, Laden F, Hankinson SE 2006. Night work and risk of breast cancer. Epidemiology 17: 108–111 [PubMed]
  • Schrodinger E. 1992. What is life?: With ‘mind and matter’ and ‘autobiographical sketches.’Cambridge University Press, Cambridge, UK.
  • Schroeder T, Yuan H, Viglianti BL, Peltz C, Asopa S, Vujaskovic Z, Dewhirst MW 2005. Spatial heterogeneity and oxygen dependence of glucose consumption in R3230Ac and fibrosarcomas of the Fischer 344 Rat. Cancer Res 65: 5163–5171 [PubMed]
  • Sears R, Leone G, DeGregori J, Nevins JR 1999. Ras enhances Myc protein stability. Mol Cell 3: 169–179 [PubMed]
  • Semenza GL 2010. HIF-1: Upstream and downstream of cancer metabolism. Curr Opin Genet Dev 20: 51–56 [PMC free article] [PubMed]
  • Semenza GL 2012. Hypoxia-inducible factors in physiology and medicine. Cell 148: 399–408 [PMC free article] [PubMed]
  • Shen C, Beroukhim R, Schumacher SE, Zhou J, Chang M, Signoretti S, Kaelin WG Jr 2011. Genetic and functional studies Implicate HIF1α as a 14q kidney cancer suppressor gene. Cancer Discov 1: 222–235 [PMC free article] [PubMed]
  • Shiao SL, Ganesan AP, Rugo HS, Coussens LM 2011. Immune microenvironments in solid tumors: New targets for therapy. Genes Dev 25: 2559–2572 [PMC free article] [PubMed]
  • Shim H, Dolde C, Lewis BC, Wu CS, Dang G, Jungmann RA, Dalla-Favera R, Dang CV 1997. c-Myc transactivation of LDH-A: Implications for tumor metabolism and growth. Proc Natl Acad Sci 94: 6658–6663 [PMC free article] [PubMed]
  • Siegel JM 2005. Clues to the functions of mammalian sleep. Nature 437: 1264–1271 [PubMed]
  • Silverman SJ, Petti AA, Slavov N, Parsons L, Briehof R, Thiberge SY, Zenklusen D, Gandhi SJ, Larson DR, Singer RH, et al. 2010. Metabolic cycling in single yeast cells from unsynchronized steady-state populations limited on glucose or phosphate. Proc Natl Acad Sci 107: 6946–6951 [PMC free article] [PubMed]
  • Singh R, Cuervo AM 2011. Autophagy in the cellular energetic balance. Cell Metab 13: 495–504 [PMC free article] [PubMed]
  • Slavov N, Macinskas J, Caudy A, Botstein D 2011. Metabolic cycling without cell division cycling in respiring yeast. Proc Natl Acad Sci 108: 19090–19095 [PMC free article] [PubMed]
  • Sonveaux P, Vegran F, Schroeder T, Wergin MC, Verrax J, Rabbani ZN, De Saedeleer CJ, Kennedy KM, Diepart C, Jordan BF, et al. 2008. Targeting lactate-fueled respiration selectively kills hypoxic tumor cells in mice. J Clin Invest 118: 3930–3942 [PMC free article] [PubMed]
  • Suzuki S, Tanaka T, Poyurovsky MV, Nagano H, Mayama T, Ohkubo S, Lokshin M, Hosokawa H, Nakayama T, Suzuki Y, et al. 2010. Phosphate-activated glutaminase (GLS2), a p53-inducible regulator of glutamine metabolism and reactive oxygen species. Proc Natl Acad Sci 107: 7461–7466 [PMC free article] [PubMed]
  • Tavtigian SV, Zabludoff SD, Wold BJ 1994. Cloning of mid-G1 serum response genes and identification of a subset regulated by conditional myc expression. Mol Biol Cell 5: 375–388 [PMC free article] [PubMed]
  • Vander Heiden MG 2011. Targeting cancer metabolism: A therapeutic window opens. Nat Rev Drug Discov 10: 671–684 [PubMed]
  • Vander Heiden MG, Cantley LC, Thompson CB 2009a. Understanding the Warburg effect: The metabolic requirements of cell proliferation. Science 324: 1029–1033 [PMC free article] [PubMed]
  • Vander Heiden MG, Christofk HR, Schuman E, Subtelny AO, Sharfi H, Harlow EE, Xian J, Cantley LC 2009b. Identification of small molecule inhibitors of pyruvate kinase M2. Biochem Pharmacol79: 1118–1124 [PMC free article] [PubMed]
  • van Riggelen J, Yetil A, Felsher DW 2010. MYC as a regulator of ribosome biogenesis and protein synthesis. Nat Rev Cancer 10: 301–309 [PubMed]
  • Vousden KH, Ryan KM 2009. p53 and metabolism. Nat Rev Cancer 9: 691–700 [PubMed]
  • Wang JB, Erickson JW, Fuji R, Ramachandran S, Gao P, Dinavahi R, Wilson KF, Ambrosio AL, Dias SM, Dang CV, et al. 2010. Targeting mitochondrial glutaminase activity inhibits oncogenic transformation. Cancer Cell 18: 207–219 [PMC free article] [PubMed]
  • Wang R, Dillon CP, Shi LZ, Milasta S, Carter R, Finkelstein D, McCormick LL, Fitzgerald P, Chi H, Munger J, et al. 2011. The transcription factor Myc controls metabolic reprogramming upon T lymphocyte activation. Immunity 35: 871–882 [PMC free article] [PubMed]
  • Wang PY, Zhuang J, Hwang PM 2012. p53: Exercise capacity and metabolism. Curr Opin Oncol 24: 76–82 [PMC free article] [PubMed]
  • Warburg O 1956. On the origin of cancer cells. Science 123: 309–314 [PubMed]
  • Wellen KE, Lu C, Mancuso A, Lemons JM, Ryczko M, Dennis JW, Rabinowitz JD, Coller HA, Thompson CB 2010. The hexosamine biosynthetic pathway couples growth factor-induced glutamine uptake to glucose metabolism. Genes Dev 24: 2784–2799 [PMC free article] [PubMed]
  • Wise DR, DeBerardinis RJ, Mancuso A, Sayed N, Zhang XY, Pfeiffer HK, Nissim I, Daikhin E, Yudkoff M, McMahon SB, et al. 2008. Myc regulates a transcriptional program that stimulates mitochondrial glutaminolysis and leads to glutamine addiction. Proc Natl Acad Sci 105: 18782–18787 [PMC free article] [PubMed]
  • Wise DR, Ward PS, Shay JE, Cross JR, Gruber JJ, Sachdeva UM, Platt JM, Dematteo RG, Simon MC, Thompson CB 2011. Hypoxia promotes isocitrate dehydrogenase-dependent carboxylation of α-ketoglutarate to citrate to support cell growth and viability. Proc Natl Acad Sci 108: 19611–19616 [PMC free article] [PubMed]
  • Xu W, Yang H, Liu Y, Yang Y, Wang P, Kim SH, Ito S, Yang C, Xiao MT, Liu LX, et al. 2011.Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of α-ketoglutarate-dependent dioxygenases. Cancer Cell 19: 17–30 [PMC free article] [PubMed]
  • Yalcin A, Telang S, Clem B, Chesney J 2009. Regulation of glucose metabolism by 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatases in cancer. Exp Mol Pathol 86: 174–179 [PubMed]
  • Yan H, Parsons DW, Jin G, McLendon R, Rasheed BA, Yuan W, Kos I, Batinic-Haberle I, Jones S, Riggins GJ, et al. 2009. IDH1 and IDH2 mutations in gliomas. N Engl J Med 360: 765–773 [PMC free article] [PubMed]
  • Yoo H, Antoniewicz MR, Stephanopoulos G, Kelleher JK 2008. Quantifying reductive carboxylation flux of glutamine to lipid in a brown adipocyte cell line. J Biol Chem 283: 20621–20627 [PMC free article] [PubMed]
  • Youle RJ, Narendra DP 2011. Mechanisms of mitophagy. Nat Rev Mol Cell Biol 12: 9–14 [PMC free article] [PubMed]
  • Yuneva MO, Fan TW, Allen TD, Higashi RM, Ferraris DV, Tsukamoto T, Mates JM, Alonso FJ, Wang C, Seo Y, et al. 2012. The metabolic profile of tumors depends on both the responsible genetic lesion and tissue type. Cell Metab 15: 157–170 [PMC free article] [PubMed]
  • Zaugg K, Yao Y, Reilly PT, Kannan K, Kiarash R, Mason J, Huang P, Sawyer SK, Fuerth B, Faubert B, et al. 2011. Carnitine palmitoyltransferase 1C promotes cell survival and tumor growth under conditions of metabolic stress. Genes Dev 25: 1041–1051 [PMC free article] [PubMed]
  • Zeller KI, Zhao X, Lee CW, Chiu KP, Yao F, Yustein JT, Ooi HS, Orlov YL, Shahab A, Yong HC, et al. 2006. Global mapping of c-Myc binding sites and target gene networks in human B cells. Proc Natl Acad Sci 103: 17834–17839 [PMC free article] [PubMed]
  • Zhang WC, Shyh-Chang N, Yang H, Rai A, Umashankar S, Ma S, Soh BS, Sun LL, Tai BC, Nga ME, et al. 2012. Glycine decarboxylase activity drives non-small cell lung cancer tumor-initiating cells and tumorigenesis. Cell 148: 259–272 [PubMed]
  • Zhao S, Xu W, Jiang W, Yu W, Lin Y, Zhang T, Yao J, Zhou L, Zeng Y, Li H, et al. 2010. Regulation of cellular metabolism by protein lysine acetylation. Science 327: 1000–1004 [PMC free article][PubMed]
  • Zhou W, Simpson PJ, McFadden JM, Townsend CA, Medghalchi SM, Vadlamudi A, Pinn ML, Ronnett GV, Kuhajda FP 2003. Fatty acid synthase inhibition triggers apoptosis during S phase in human cancer cells. Cancer Res 63: 7330–7337 [PubMed]
  • Zoncu R, Efeyan A, Sabatini DM 2010. mTOR: From growth signal integration to cancer, diabetes and ageing. Nat Rev Mol Cell Biol 12: 21–35 [PMC free article] [PubMed]

Metformin Alters Microbiota, Improving Insulin Sensitivity

~Content Source

Given the strength of the findings, people who take metformin for their diabetes appear to have an enriched gut microflora that fosters a more efficient response to glucose metabolism.

With Juan S. Escobar, PhD, and  Caroline Apovian, MD

The use of metformin in people with diabetes appears to favorably alter their gut microbiome, resulting in an improved glucose metabolism. The primary effect of metformin aims to stimulate levels of certain bacteria to enrich the microbiota milieu,1according to a team of researchers including the Johns Hopkins Bloomberg School of Public Health in Baltimore, MD.

“In particular, my colleagues and I found that mucin-degrading Akkermansia muciniphila and several butyrate-producing bacteria were positively associated with metformin use,” said study researcher Juan S. Escobar, PhD, of the Vidarium Research Center in Medellin, Colombia. These results echo findings from an earlier study.2

 

“Although we are not the first to demonstrate alterations in the gut microbial community associated with intake of this medication, our study is unique in matching cases and control on sex, age and body mass index, which makes our findings robust,” Dr. Escobar said told EndocrineWeb. Even so, he cannot claim a causal relationship yet, as the study was based on observational data.

However, the findings may have some clinical relevance, he said, both for preventing disease and helping clinicians tailor treatments not only for those with type 2 diabetes but for other diseases associated with dysfunction in the gut microbiota.

“Alterations in the microbiome have been shown to be central in many chronic diseases,” he said, ”including obesity, cardiovascular disease, and diabetes, among others. In the case of type 2 diabetes (T2D), it was demonstrated a few years ago that patients had an altered gut microbiome relative to non-diabetic people.3 What is new with our study is that yes, patients with T2D have an altered microbiota, but most alterations are due to metformin treatment rather than the disease itself.”

Observational Study Bolsters Metformin Benefits

In a community-based, observational study, 28 men and women with type 2 diabetes, were evaluated; half of the participants were taking metformin and half were not.They were compared to individuals without a diagnosis of diabetes. The groups were matched by sex, age, and body mass index (BMI).

All participants gave the researchers fecal samples. The researchers performed gene sequencing to assess the composition of the gut microbiome.

Those taking metformin, in comparison to those without diabetes, had a higher abundance of Akkermansia muciniphila, a microbiota known for degrading mucin, and several microbiotas known to stimulate the production of short chain fatty acids (such as Butyrivibrio).

When the researchers pooled the mucin-degrading microbiomes and those producing short-chain fatty acids, they found A. muciniphila and Butyrivibrio were more abundant, [3.4 and 4.4 times, respectively] in those with type 2 diabetes taking metformin than in those with type 2 diabetes, not on metformin.1

The differences were statistically significant for A muciniphila [P=0.003], but not for Butyrivibrio [p=0.08].

The higher abundance of both types of bacteria in those taking metformin suggested that the benefits of metformin may have developed in response to a improve integrity of the intestinal mucosal barrier, said the researchers. When the mucin layer lining the gut is maintained, the translocation of proinflammatory lipopolysaccharides is reduced, thus controlling fat storage, adipose tissue metabolism, and glucose homeostasis, according to the experts.

Future studies will be needed to see if the bacterial shifts continue to mediate metformin’s glycemic and anti-inflammatory properties, Dr. Escobar told EndocrineWeb.

In another new study in which the microbiome of individuals with type 1 diabetes (T1D) was evaluated,4 a distinct gut microflora was found. Gastrointestinal tissue was extracted by endoscopy and analyzed. The gut lining of patients with T1D showed greater signs of inflammation, then individuals with celiac disease or a healthy gut.3 The significance of this finding pertains to the growing evidence of the anti-inflammatory nature of metformin, the immune dysregulation in the gut of those with diabetes and a distinct gut bacteria, the authors concluded.

Metformin Credited With Improving Insulin Sensitivity

The findings may change some current thinking about how metformin works, says Caroline Apovian, MD, professor of medicine and pediatrics at Boston University School of Medicine and director of nutrition and weight management, Boston Medical Center. She reviewed the findings for Endocrine Web.

“Current thinking is that the metformin works because it improves insulin sensitivity in the liver,” she explained. However, these findings, as well as results from recent studies, suggest that the gut may have an active role in glucose metabolism. Dr. Escobar and his team are ”linking the use of metformin with a beneficial change in the gut microbiota.”

The strength of the new research, Dr. Apovian said, is that the researchers matched the cases by age, gender, and body mass index then compared those taking versus not receiving metformin, and also looked at healthy controls.

Clinically, she said, ”it could mean that metformin not only helps people with diabetes but could help people with prediabetes and maybe even people without diabetes because you are improving the gut microbiome.”

For instance, there has been researching finding that metformin may help treat and prevent breast cancer,5 and it may have an anticancer mechanism for other cancers, including prostate, colorectal and endometrial, according to the National Cancer Institute. 6

Metformin, Gut Microbiome Hold Promise for Disease Prevention

More research is needed, both Dr. Apovian and Dr. Escobar agree. Physicians aren’t to the point where they are testing patient’s stools routinely to assess individual gut bacteria, said Dr. Apovian. However, the study findings do suggest that metformin should be used more broadly than just for people with diabetes, she said.

Dr. Escobar’s lab aims to examine how to restore balance in the gut microbiota to prevent disease onset. However, he also championed the prospect of its use for those who already have a disease.

“For those already sick, our results can inform novel ways in which therapies could potentially be used to treat an assortment of gut microbiota-associated diseases, including type 2 diabetes.”

Future research must also determine if the observed associations are causal, Dr. Escobar said, and of course, that would necessitate a randomized controlled trial.


Sources~

1. de la Cuesta-Zuluaga J, Mueller NT, Corrales-Agudelo V, et al. Metformin Is Associated With Higher Relative Abundance of Mucin-Degrading Akkermansia muciniphila and Several Short-Chain Fatty Acid–Producing Microbiota in the GutDiabetes Care. 2017;40(1):54-62.

http://care.diabetesjournals.org/content/early/2016/10/19/dc16-1324

2. Forslund K, Hildebrand F, Nielen T. Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota. Nature. 2015;528:262-266.

3. Larsen N, Vogensen FK, van den Berg FWJ, et al. Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults. PLoS One 2010;5:e9085.

4. Pellegrini S, Sordi V, Mario Bolla A, et al. Duodenal Mucosa of Patients with Type 1 Diabetes Shows Distinctive Inflammatory Profile and Microbiota. Published online ahead of print. Accessed January 19, 2017. Available at https://academic.oup.com/jcem/article-lookup/doi/10.1210/jc.2016-3222.

5. University of Pennsylvania School of Medicine. Diabetes drug metformin holds promise for cancer treatment and prevention: Results show survival benefit for some breast cancer patients and potential treatment option for patients with endometrial hyperplasia. Science Daily. June 2016.

https://www.sciencedaily.com/releases/2016/06/160604051019.htm

6. National Cancer Institute. Metformin: Can a diabetes drug help prevent cancer? Accessed on January 14, 2017. Available at: https://www.cancer.gov/about-cancer/causes-prevention/research/metformin.

Cancer as a metabolic disease: implications for novel therapeutics

Content Source ~ NIH

Abstract: Emerging evidence indicates that cancer is primarily a metabolic disease involving disturbances in energy production through respiration and fermentation. The genomic instability observed in tumor cells and all other recognized hallmarks of cancer are considered downstream epiphenomena of the initial disturbance of cellular energy metabolism. The disturbances in tumor cell energy metabolism can be linked to abnormalities in the structure and function of the mitochondria. When viewed as a mitochondrial metabolic disease, the evolutionary theory of Lamarck can better explain cancer progression than can the evolutionary theory of Darwin. Cancer growth and progression can be managed following a whole body transition from fermentable metabolites, primarily glucose and glutamine, to respiratory metabolites, primarily ketone bodies. As each individual is a unique metabolic entity, personalization of metabolic therapy as a broad-based cancer treatment strategy will require fine-tuning to match the therapy to an individual’s unique physiology.

Introduction: Cancer is a disease involving multiple time- and space-dependent changes in the health status of cells and tissues that ultimately lead to malignant tumors. Neoplasia (abnormal cell growth) is the biological endpoint of the disease. Tumor cell invasion into surrounding tissues and their spread (metastasis) to distant organs is the primary cause of morbidity and mortality of most cancer patients (). A major impediment in the effort to control cancer has been due in large part to the confusion surrounding the origin of the disease. Contradictions and paradoxes continue to plague the field (). Much of the confusion surrounding cancer origin arises from the absence of a unifying theory that can integrate the many diverse observations on the nature of the disease. Without a clear understanding of how cancer arises, it becomes difficult to formulate a successful strategy for effective long-term management and prevention. The failure to clearly define the origin of cancer is responsible in large part for the failure to significantly reduce the death rate from the disease (). Although cancer metabolism is receiving increased attention, cancer is generally considered a genetic disease (,). This general view is now under serious reevaluation (,). The information in this review comes in part from our previous articles and treatise on the subject (,).

Provocative question: does cancer arise from somatic mutations?

Most of those who conduct academic research on cancer would consider it a type of somatic genetic disease where damage to a cell’s nuclear DNA underlies the transformation of a normal cell into a potentially lethal cancer cell (,,,). Abnormalities in dominantly expressed oncogenes and in recessively expressed tumor suppressor genes have been the dogma driving the field for several decades (,). The discovery of millions of gene changes in different cancers has led to the perception that cancer is not a single disease, but is a collection of many different diseases (,,,). Consideration of cancer as a ‘disease complex’ rather than as a single disease has contributed to the notion that management of the various forms of the disease will require individual or ‘personalized’ drug therapies (,). Tailored therapies, unique to the genomic defects within individual tumors, are viewed as the future of cancer therapeutics (,). This therapeutic strategy would certainly be logical if the nuclear somatic mutations detected in tumors were the drivers of the disease. How certain are we that tumors arise from somatic mutations and that some of these mutations drive the disease? It would therefore be important to revisit the origin of the gene theory of cancer.

The gene theory of cancer originated with Theodor Boveri’s suggestion in 1914 that cancer could arise from defects in the segregation of chromosomes during cell division (,). As chromosomal instability in the form of aneuploidy (extra chromosomes, missing chromosomes or broken chromosomes) is present in many tumor tissues (,), it was logical to extend these observations to somatic mutations within individual genes including oncogenes and tumor suppressor genes (,). Boveri’s hypothesis on the role of chromosomes in the origin of malignancy was based primarily on his observations of chromosome behavior in nematodes (Ascaris) and sea urchins (Paracentrotus) and from his consideration of von Hansemann’s earlier observations of abnormal chromosome behavior in tumors (,,). In contrast to Boveri’s view of aneuploidy as the origin of cancer, von Hansemann considered the abnormal chromosome behavior in tumors as an effect rather than as a cause of the disease (). Although Boveri’s hypothesis emerged as the foundation for the somatic mutation theory of cancer, it appears that he never directly experimented on the disease (,,). The reason for the near universal acceptance of Boveri’s hypothesis for the origin of cancer is not clear but might have been linked to his monumental achievement in showing that Gregor Mendel’s abstract heredity factors resided on chromosomes (). Boveri’s cancer theory was also consistent with the gradual accumulation of evidence showing that DNA abnormalities are abundant in cancer cells.

In his 2002 review, Knudson stated that, ‘considerable evidence has been amassed in support of Boveri’s early hypothesis that cancer is a somatic genetic disease’ (). The seeds of the somatic mutation theory of cancer might have been sowed even before the work of von Hansemann and Boveri. Virchow considered that cancer cells arose from other cancer cells (). Robert Wagner provided a good overview of those early studies leading to the idea that somatic mutations give rise to cancer (). It gradually became clear that almost every kind of genomic defect could be found in tumor cells whether or not the mutations were connected to carcinogenesis (,,,,). The current somatic mutation theory involves a genomic landscape of incomprehensible complexity that also includes mysterious genomic ‘Dark Matter’ (,,,). Although massive evidence exists showing that genomic instability is present to some degree in all tumor cells, it is unclear how this phenotype relates to the origin of the disease. It appears that almost every neoplastic cell within a naturally arising human tumor is heterogeneous in containing a unique genetic architecture ().

Inconsistencies with a nuclear gene origin of cancer

The distinguished British geneticist, C.D.Darlington (), was one of the first to raise concerns regarding the nuclear genetic origin of cancer. Based on several inconsistencies in the association of mutagens with cancer, Darlington argued persuasively that nuclear genomic defects could not be the origin of cancer. Rather, he was convinced that cancer cells arose from defects in cytoplasmic elements, which he referred to as ‘plasmagenes’. Although Darlington did not specifically characterize the nature of the plasmagene, several characteristics of the plasmagenes suggested that they were mitochondria. It was unclear, however, if the radiation damage to the plasmagenes acted alone in causing cancer or also acted in conjunction with mutations in nuclear genes.

Inconsistencies regarding the somatic nuclear gene theory of cancer also come from nuclear/cytoplasmic transfer experiments between tumorigenic and non-tumorigenic cells. Several investigators showed that tumorigenicity is suppressed when cytoplasm from non-tumorigenic cells, containing normal mitochondria, is combined with nuclei from tumor cells (). Moreover, the in vivotumorigenicity of multiple human and animal tumor types is suppressed when the nucleus from the tumor cell is introduced into the cytoplasm of a non-tumorigenic cell (). Tumors generally did not form despite the continued presence of the tumor-associated mutations. The nuclear gene mutations documented in mouse brain tumors and melanomas were also detected in the normal embryonic tissues of the mice derived from the tumor nuclei (,). Some embryos derived from tumor nuclei, which contained major chromosomal imbalances, proceeded through early development forming normal appearing tissues before dying. Despite the presence of tumor-associated aneuploidy and somatic mutations, tumors did not develop from these tumor-derived nuclei (). Boveri also found that sea urchin embryos with chromosomal imbalances developed normally to gastrulation but then aborted (,). Hochedlinger et al. () showed that nuclei derived from melanoma cells were unable to direct complete mouse development due presumably to the chromosomal imbalances and irreversible tumor-associated mutations in the melanoma nucleus. Tumors did not arise in the embryos derived from the melanoma nuclei. These findings suggest that the nuclear genomic defects in these tumor cells have more to do with directing development than with causing tumors.

More recent mitochondrial transfer experiments support the general findings of the nuclear transfer experiments (,). The tumorigenic phenotype is suppressed when normal mitochondria are transferred to the tumor cell cytoplasm. On the other hand, the tumorigenic phenotype is enhanced when tumor mitochondria are transferred to a normal cell cytoplasm. These findings further suggest that tumorigenesis is dependent more on mitochondrial function than on the types of mutations in the nucleus.

In contrast to the suppressive effects of normal mitochondria on tumorigenicity, tumorigenicity is enhanced when nuclei of non-tumorigenic cells are combined with cytoplasm from tumor cells (,). These observations are consistent with the original view of Darlington that tumor cells arise from defects in the cytoplasm rather than from defects in the nucleus (). Wallace et al. () also showed that introduction of mitochondrial DNA mutations into non-tumorigenic cybrids could reverse the anti-tumorigenic effect of normal mitochondria leading to the conclusion that cancer can be best defined as a type of mitochondrial disease. The nuclear transfer studies are summarized in Figure 1, highlighting the role of the mitochondria in suppressing tumorigenesis. These studies also raise questions regarding the role of somatic mutations as drivers of tumorigenesis. Further studies will be needed to determine whether tumors arise from defects in the nuclear genome alone or in the mitochondria alone, or require defects in both the mitochondria and the nuclear genome. Such studies will provide evidence for or against the nuclear gene driver hypothesis of cancer initiation.

Respiratory insufficiency as the origin of cancer and the ‘Warburg effect’

Otto Warburg (,) first proposed that all cancers originate from dysfunctional cellular respiration. Warburg stated,

Just as there are many remote causes of plague, heat, insects, rats, but only one common cause, the plague bacillus, there are a great many remote causes of cancer-tar, rays, arsenic, pressure, urethane- but there is only one common cause into which all other causes of cancer merge, the irreversible injuring of respiration.

The key points of Warburg’s theory are (i) insufficient respiration initiates tumorigenesis and ultimately cancer, (ii) energy through glycolysis gradually compensates for insufficient energy through respiration, (iii) cancer cells continue to ferment lactate in the presence of oxygen and (iv) respiratory insufficiency eventually becomes irreversible (). Efraim Racker () was the first to describe the increased aerobic glycolysis seen in cancer cells as the ‘Warburg effect’. Warburg, however, referred to the phenomenon in cancer cells as ‘aerobic fermentation’ to highlight the abnormal production of lactate in the presence of oxygen (). As lactate production is widely recognized as an indicator of respiratory insufficiency in biological systems (), Warburg also viewed the aerobic production of lactate in tumor cells as an indicator of respiratory insufficiency.

A deficiency in oxidative phosphorylation (OxPhos) energy is responsible for lactate production in most cases (,). For example, muscle cells significantly increase their metabolic rate during intense exercise and as a result oxygen becomes limiting. The oxygen deficiency causes a lack of energy through OxPhos prompting lactate production in an effort to provide compensatory energy from fermentation (glycolytic energy) (). A competing argument would be that OxPhos is not insufficient during intense exercise and that aerobic fermentation is needed to provide more energy and growth metabolites in response to the increased work demand. This would be similar to the suggestion of Weinhouse and others for the increased aerobic glycolysis in tumor cells (,). Indeed, Kopennol et al. () suggest that the increased lactate production in tumor cells arises from damage to the regulation of glycolysis and not to insufficient respiration. However, the competing argument is inconsistent with the observation that the lactate made by muscle cells during intense exercise falls significantly after oxygen is restored to the muscle tissue. This would indicate that the lactate was made primarily because O2 was unavailable for robust OxPhos (). In addition, oxygen deprivation or hypoxia causes all known cultured mammalian cells to increase lactate production (). An increase in lactate is also seen in adequately oxygenated cells when respiration is inhibited either by respiratory poisons or null mutations in key respiratory enzymes (). It is therefore clear from established bioenergetic principles that the excess lactate made by most mammalian cells is needed to sustain fermentation energy in order to compensate for insufficient energy from respiration. It is our view that tumor cells are not an exception to this general principle and that their lactate production results in part from insufficient respiratory activity. It is expected that an upregulation of glycolytic genes would be needed to facilitate compensatory energy production through glycolysis when cellular respiration is deficient for protracted periods (). The reduction of pyruvate to lactate is needed to enhance the glycolytic pathway when respiration becomes insufficient.

It is important to recognize that pyruvate is produced through aerobic glycolysis in most normal cells of the body that use glucose for energy. The reduction of pyruvate to lactate distinguishes the tumor cells from most normal cells, which fully oxidize pyruvate to CO2 and water for adenosine triphosphate (ATP) production through the tricarboxylic acid (TCA) cycle and the electron transport chain (). Aerobic glycolysis with lactate production can occur in normal retina though more ATP is produced through respiration than through glycolysis, as is the case in most respiring tissues (). On the other hand, enhanced aerobic glycolysis without significant lactate production or energy through fermentation can occur in normal cardiac and brain tissues under conditions of increased activity (). The slight transient increase in lactate production under these conditions is not associated with a significant increase in total energy production. As enhanced aerobic glycolysis does not produce significant lactate in normal cells under well-oxygenated conditions, a phenotype of enhanced aerobic glycolysis is therefore not synonymous with a Warburg effect.

Lactate will be produced in normal tissues under low oxygen conditions. Tumor cells also produce lactate under hypoxia through anaerobic glycolysis. Although many investigators of tumor cell energy metabolism use the term ‘aerobic glycolysis’ in referring to the Warburg effect, we consider the term ‘aerobic fermentation’ as a more accurate description of the Warburg effect since aerobic glycolysis occurs in most normal cells of the body. A key issue is whether the lactate produced in tumor cells under aerobic conditions results from insufficient respiration as Warburg proposed or is due to some other phenomenon. The origin of the Warburg effect is an issue of controversy that persists today despite Warburg’s data showing that it arose from insufficient respiration.

According to Warburg and Burk respiratory insufficiency together with lactate production are the key features of tumor cell energy metabolism (,,,). Respiratory insufficiency as the origin of tumorigenesis has remained controversial, however, due to observations of high oxygen consumption rates in many tumor cells (,,). It is generally assumed that oxygen consumption rate is a good indicator of cellular respiration and OxPhos. Although low oxygen consumption rate seen together with high lactate production can be indicative of insufficient respiration, high oxygen consumption might not be indicative of sufficient respiration especially if lactate is also produced. It is now recognized from numerous studies that oxygen consumption rates are not always linked to a normally coupled oxidative phosphorylation (). It can be difficult to determine the degree to which mitochondrial ATP production arises from coupled respiration or from TCA cycle substrate level phosphorylation (). The origin of mitochondrial ATP production in tumor cells requires further clarification in light of these issues.

Mitochondrial structure is intimately connected to mitochondrial function. This fact cannot be overemphasized. We have reviewed substantial evidence of morphological, proteomic, and lipidomic abnormalities in mitochondria of numerous types of cancer cells (,,). Tumor cells can have abnormalities in both the content and composition of their mitochondria. The work of Arismendi-Morillo and Oudard et al. showed that the ultrastructure of tumor tissue mitochondria differs markedly from the ultrastructure of normal tissue mitochondria (,). In contrast to normal mitochondria, which contain numerous cristae, mitochondria from tumor tissue samples showed swelling with partial or total cristolysis (Figure 2). Cristae contain the proteins of the respiratory complexes and play an essential structural role in facilitating energy production through OxPhos (). The structural defects in human glioma mitochondria are also consistent with lipid biochemical defects in murine gliomas (,).

More recent electron micrographic studies from Elliott et al. showed that mitochondria ultrastructure was abnormal to some degree in 778 patients with breast cancer (). Remarkably, mitochondria were severely reduced in number or were undetectable in the tumor tissue from over 80% of the patients. These findings together with the evidence from the Pedersen () review would support Warburg’s central hypothesis that respiration is insufficient in tumor cells. It is obvious that mitochondrial function or OxPhos sufficiency cannot be normal in tumor cells that contain few if any mitochondria. Glycolysis and lactate fermentation would need to be upregulated in these tumor cells in order to compensate for the absence of OxPhos. Furthermore, the degree of malignancy in these breast tumors was correlated directly with the degree of mitochondrial structural abnormality (). The high glycolytic activity and lactate production seen in the most malignant tumors were also linked to the mitochondrial structural abnormalities seen in the tumors (,). In contrast to inherited mitochondriopathies, where glycolysis might not compensate completely for mitochondrial energy failure, fermentation energy appears capable of compensating completely for the respiratory insufficiency in tumor cells (,). Further studies will be needed to distinguish the differences in glycolytic and respiratory energy metabolism in tumor cells and in cells with mitochondriopathies ().

Pedersen () presented massive evidence showing that mitochondria in tumor cells are abnormal compared with mitochondria from normal cells. His review provides a comprehensive discussion of mitochondrial bioenergetics and dysfunction in cancer cells. It was clearly shown that the mitochondria of cancer cells contain numerous qualitative and quantitative abnormalities compared with mitochondria from tissue specific control cells. Summarized here are just a few of the conclusions from the Pedersen review. (i) Tumor mitochondria are abnormal in morphology and ultrastructure and respond differently to changes in growth media than mitochondria from normal cells. (ii) The protein and lipid composition of tumor mitochondria are markedly different from that of normal mitochondria. (iii) Proton leak and uncoupling is greater in tumor mitochondria than in normal mitochondria. (iv) Calcium regulation is impaired in tumor mitochondria. (v) Anion membrane transport systems are abnormal or dysregulated in mitochondria from many tumors. (vi) Defective shuttle systems are not responsible for elevated glucose fermentation in tumor cells. (vii) Pyruvate is not effectively oxidized in tumor mitochondria. (viii) Tumor mitochondria contain a surface-bound, fetal-like hexokinase. (ix) A deficiency in some aspect of respiration can account for excessive lactic acid production in tumor cells. Clearly, substantial evidence exists showing that mitochondrial structure, function and respiratory capacity is defective to some degree in all types of tumor cells. This information should be addressed in discussions of tumor cell energy metabolism.

Besides a generalized defect at the level of the mitochondrial electron transport chain in most tumor cells, numerous other mitochondrial abnormalities do exist that would diminish respiratory function (,). Interestingly, Warburg never stated that a generalized defect in electron transport was responsible for the origin of cancer despite suggestions from others (,). Rather, Warburg stated that insufficient respiration was responsible for aerobic fermentation and the origin of cancer (,,,,). We know from the work of numerous investigators that electron transport may not be coupled to ATP synthesis in cancer cells (,). Any mitochondrial defect that would uncouple electron transport from OxPhos could reduce respiratory sufficiency and thus contribute to lactate formation or a Warburg effect.

Influence of unnatural growth environment on cellular energy metabolism

Much of the evidence arguing against Warburg’s central theory that respiratory insufficiency is the origin of the aerobic fermentation seen in cancer cells (Warburg effect) was derived from investigations of tumor cells grown in vitro(,,,). In contrast to the structural defects, reduced numbers or the absence of mitochondria observed in human cancerous tissues, such mitochondrial abnormalities are not generally seen in many human and animal tumor cells when they are grown in the in vitro environment. It is interesting that oxygen consumption rate can be similar or even greater in cultured tumor cells than in non-tumorigenic cells (,,). The presence of mitochondria and robust oxygen consumption rates in tumor cells grown in vitro suggested to some that mitochondria are normal in tumor cells and that Warburg’s central theory was incorrect (,,). As mentioned above, however, oxygen consumption rate is not always an indicator of coupled respiration. Some tumor cells consume oxygen while importing and hydrolyzing glycolytically derived ATP through the mitochondrial adenine nucleotide transporter 2 in order to maintain the proton motive gradient (). We also showed that the growth of tumorigenic and non-tumorigenic cells in typical cell culture media changes the content and fatty acid composition of lipids especially cardiolipin, the signature phospholipid of the inner mitochondrial membrane that regulates OxPhos (). No tumor cells have yet been described with a normal content and composition of cardiolipin (,,). Cells cannot respire effectively if the content or composition of their cardiolipin is abnormal (,,). This point cannot be overemphasized.

It is not clear why mitochondria might appear functionally normal in many types of cultured tumor cells but appear structurally abnormal when evaluated in the tumor cells of many primary malignant cancers. Cultured cell lines are usually derived from only a single cell or a few cells of a heterogeneous tumor. Is it possible that only those tumor cells with some level of mitochondrial function are capable of growing in vitro? Also the in vitro environment forces many cells into a state of aerobic fermentation whether or not they are tumorigenic. We showed that the typical culture environment produces immature cardiolipin in non-tumorigenic glial cells, which reduces the activity of mitochondrial respiratory chain complexes (). Further studies are needed on the structure and function of mitochondria in tumor tissue and their derived cell lines.

Lactate production should be minimal in adequately oxygenated cells that have the capacity to respire normally. However, significant lactate production is often observed in proliferating non-tumorigenic cells grown in well-oxygenated cultures (,,). It is not likely that the high aerobic fermentation seen in normal cells grown in culture is due to deregulated glycolysis, as suggested for tumor cells (). Enhanced glycolysis in tumor cells cannot be considered only as deregulated but can also be considered as necessary to compensate for respiratory insufficiency.

Some investigators consider lactate production as necessary for normal cell proliferation (,). It is important to consider the differences in the metabolic requirements of tumorigenic and non-tumorigenic cells when grown in the in vivoand in vitro environments (,). In contrast to what is seen in cultured cells, no lactate production is seen in the rapidly growing embryonic chorion under aerobic conditions (). Moreover, lactate production is minimal in rapidly growing hepatocytes during liver regeneration (,). Instead, regenerating liver cells use fatty acids rather than glucose to fuel proliferation. Fatty acid metabolism produces mostly water and CO2, but not lactate. In contrast to hepatomas, which have abnormal cardiolipin composition, the content and composition of cardiolipin is similar in resting liver cells and in proliferating liver cells during regeneration (,). These findings suggest that respiration can occur normally in rapidly proliferating liver cells during liver regeneration. Viewed together, these findings indicate that lactate production is not required for rapid cell proliferation in vivo. Tumor cells are an exception in this regard, as lactate production in these cells arises as a consequence of abnormal respiration, which can be linked to either the structural defects seen in tumor tissue mitochondria or to reduced number of mitochondria. If lactate production is not required for rapid cell growth, why are significant amounts of lactate produced in many types of rapidly growing tumorigenic and non-tumorigenic cells when grown in culture?

The ‘Crabtree effect’ can confound the interpretation of energy metabolism in cultured cells. The Crabtree effect involves a glucose-induced suppression of respiration leading to lactate production whether or not mitochondria are damaged (,,,). The Crabtree effect differs from the Warburg effect, which involves lactate production arising from insufficient respiration. In other words, the aerobic lactate produced under the Crabtree effect arises from a suppressed respiration rather than from insufficient respiration as occurs in the Warburg effect. It can be difficult to determine with certainty, however, whether the aerobic fermentation (aerobic glycolysis) observed in cultured cells arises from a Crabtree effect, a Warburg effect or some combination of these effects (). We consider the Crabtree effect as an artifact of the in vitro environment that causes some non-tumorigenic mammalian cells to ferment lactate even in the presence of oxygen. It would therefore be important for investigators to exclude the influence of a Crabtree effect on the assessment of energy measurements in cultured cells. Although a Crabtree effect might suppress OxPhos, the TCA cycle should remain functional and produce ATP through substrate level phosphorylation (). Under certain conditions (hypoxia), the tumor TCA cycle can work in both forward and reverse (reductive) directions (,). Although some tumor cells can have a functional TCA cycle linked to insufficient respiration, sufficient respiration is unlikely to occur without a functional TCA cycle. Support for this comes from findings that some rare cancers can arise from inherited mutations in TCA enzymes, e.g. fumarate hydratase and succinate dehydrogenase, which impede the TCA cycle (,). Based on the data presented over many years by numerous investigators, we consider that OxPhos is universally insufficient to some degree in all tumor cells. However, the Crabtree effect and the unnatural conditions of the in vitro environment can obscure this insufficiency. Although respiratory insufficiency might be more profound in some tumor cells than in others, most if not all tumor cells will express some degree of OxPhos insufficiency compared with appropriate controls matched for species, age and tissue type.

Besides the confounding influence of the in vitro environment on energy metabolism, abnormalities and misinformation can be obtained when human tumor cells are grown in non-syngeneic hosts (). This is especially relevant with respect to the mouse xenograft models including the ‘patient-derived xenografts’. We found that human U87MG brain cancer cells express mouse carbohydrates on their surface when grown as a xenograft in immune deficient mice (). Over 65% of the sialic acid composition on the U87MG tumor cells consisted of the nine-carbon sugar, N-glycolylneuraminic acid. Humans, however, are unable to synthesize N-glycolylneuraminic acid due to a mutation in the gene that encodes a common mammalian hydroxylase enzyme (,). The hydroxylase mutation occurred in the human genome sometime after our evolutionary split with the great apes (). The acquisition of murine carbohydrates and lipids will likely occur in any human tumor cell grown in the body of a mouse or rat. N-glycolylneuraminic acid alters the characteristics of human embryonic stem cells when grown on non-human feeder cells (). The influence of the murine host on gene expression in human tumor cells is a confounding variable that can create difficulties for data interpretation in tumor cells. Few investigators address these issues.

Expression of mouse carbohydrates and lipids on human tumor cells when grown as xenografts can alter gene expression patterns and growth behavior of the tumor cells, thus altering their response to changes in the microenvironment. It might be reasonable to view the human xenograft tumor models as a type of human-mouse centaur (). In addition, the basal metabolic rate of the mouse is 7- to 8-fold greater than that of humans (,). The basal metabolic rate is the energy needed for the maintenance of all physiological processes under rest. Little attention is given to differences in metabolic rate when comparing metabolism among human and animal tumors (). The difference in metabolic rate could cause the human tumor cells to grow slow or not at all in xenografts due to competition for energy metabolites with mouse host stromal cells that have a higher metabolic rate than the human tumor cells. This could account in part for the low incidence of systemic metastasis seen in xenograft models implanted with tumor cells taken from human metastases. Solid tumors that do not metastasize or are not invasive are generally considered benign (). Further studies will be needed to determine if the human tumor cells that are selected to grow in the mouse have a metabolic rate more similar to that of the mouse than to that of the human.

Many human tumor cells or tissues are grown in mice that are Non-Obese Diabetic and have Severely Compromised Immuno-Deficiency (NOD-SCID) (). These mice not only have a compromised innate and/or adaptive immune system but also express characteristics of both type-1 diabetes and type-2 diabetes (). This is not a usual situation for most cancer patients. Despite some limited success, it is naive to assume that the growth behavior and response to therapies of human tumors grown as xenografts would be similar to the situation in the natural host. The evaluation of cancer drugs against tumor cells grown in unnatural environments together with the misunderstanding on the origin of cancer is responsible in large part for widespread failure in developing new cancer therapies (). The use of syngeneic mouse tumor models will be more representative of the natural physiological state in humans than will the xenograft models.

Connecting the links from respiratory insufficiency to cancer origin

The path from normal cell physiology to malignant behavior, where all major cancer hallmarks are expressed, is depicted in Figure 3. Any unspecific condition that damages a cell’s respiratory capacity but is not severe enough to kill the cell can potentially initiate the path to a malignant cancer. Reduced respiratory capacity could arise from damage to any mitochondrial protein, lipid or mtDNA. Some of the many unspecific conditions that can diminish a cell’s respiratory capacity thus initiating carcinogenesis include inflammation, carcinogens, radiation (ionizing or ultraviolet), intermittent hypoxia, rare germline mutations, viral infections and age. The evidence supporting this statement also addresses Szent Giorgy’s ‘oncogenic paradox’, as was described in a recent treatise on the subject (). The paradox addresses the difficulty in knowing how a plethora of disparate carcinogenic agents might produce cancer through a common mechanism. Some of the rare germline mutations that increase risk for cancer through an effect on cellular respiration include p53BRACA1RB and xeroderma pigmentosum (). Cancer-causing viruses can be linked to mitochondrial dysfunction (). If respiratory damage is acute, the cell will die. On the other hand, if damage is mild and protracted, the cell will elevate lactate or amino acid fermentation in order to compensate for insufficient OxPhos. Recent evidence also shows that mitochondrial dysfunction is the initial event in the path to tumorigenesis induced by the mutated Ras oncogene and is closely linked to the action of the BRAF oncogene (,,). Cells will enter their default state of proliferation following loss of respiratory control (,). Several cancer hallmarks can be linked to the transition from quiescence to proliferation (Figure 3). Unbridled proliferation is linked to fermentation, which was the dominant form of energy metabolism during the oxygen deficient α period of earth’s history (). OxPhos insufficiency in fusion hybrids between immune cells (mostly macrophages) and cancer stem cells can underlie the ability of tumor cells to intravasate the circulation locally and to extravasate the circulation at distant sites (,). As macrophages are already mesenchymal and naturally capable of systemic tissue dispersion, it is not necessary to explain the phenomenon of metastasis in terms of complicated gene-linked epithelial to mesenchymal and mesenchymal to epithelial transitions. Metastasis in our view would arise from the dysregulation of normal macrophage functions in fusion hybrids including intravasation and extravasation (). All major hallmarks of cancer including genomic instability can be linked directly or indirectly to the respiratory dysfunction and the compensatory fermentation of the tumor cell.

Are mutations in the P53 and the Ras genes primary or secondary causes of cancer?

Although germline or somatic mutations in the P53 tumor suppressor gene and somatic mutations the Ras oncogene occur frequently in many tumor cells and cancers (,), it is not clear if these genes or their products are primary or secondary causes of cancer. Hwang et al. showed that p53 regulates mitochondrial respiration through its transcriptional target gene Synthesis of Cytochrome c Oxidase 2 (SCO2) (). In these studies the Warburg effect was linked directly to impaired respiration. Singh et al. showed that mitochondrial energy metabolism is impaired in human cancer cells containing defects in p53 (). Huang et al. recently showed that the common K-RasG12V mutation causes a metabolic switch from OxPhos to glycolysis (Warburg effect) due to mitochondrial dysfunction (Figure 4). Lee et al. showed that transfection of human diploid cells with V12Ras significantly increased damaging oxygen species in mitochondria (), whereas Weinberg et al. () showed that mitochondrial reactive oxygen species (ROS) generation and damage to complex III was essential for K-Ras-induced cell proliferation and tumorigenesis. Moreover, Yang et al. () showed that H-Ras transformation of mouse fibroblasts damaged respiration, thus forcing the cells into a glycolytic metabolism. This is notable since activated RAS has been proposed to induce MYC activity and to enhance non-hypoxic levels of HIF-1α (). As MYC and HIF-1 drive glycolysis, their upregulation would be necessary to prevent senescence following respiratory impairment (,). As constitutive Rasactivation is incompatible with prenatal development, a disruption of mitochondrial energy metabolism could underlie tumor formation in mice cloned from melanoma nuclei following the inadvertent expression of the Ras oncogene (). Viewed collectively, these and other observations are consistent with Warburg’s theory and suggest that mutations in the P53 and Ras genes initiate cancer through their adverse effects on respiratory function. It will be up to each investigator to determine whether they consider these mutations as primary or secondary causes of cancer according to Warburg’s central theory (,,). It is our view that all roads to the origin and progression of cancer pass through the mitochondria (Figure 3).

Can tumor somatic mutations arise as a downstream epiphenomenon of abnormal energy metabolism?

How might protracted respiratory insufficiency cause somatic mutations and the nuclear genomic instability seen in tumor cells? The integrity of the nuclear genome is dependent to a large extent on the efficiency of mitochondrial respiratory function (). Evidence indicates that a persistent retrograde response or mitochondrial stress response leads to abnormalities in DNA repair mechanisms and to the upregulation of fermentation pathways (,). Oncogene upregulation becomes essential for increased glucose and glutamine metabolism following respiratory impairment (,). The metabolic waste products of fermentation can destabilize the morphogenetic field of the tumor microenvironment thus contributing to inflammation, angiogenesis and progression (). Normal mitochondrial function is necessary for maintaining intracellular calcium homeostasis, which is required for chromosomal integrity and the fidelity of cell division. Aneuploidy can arise during cell division from abnormalities in calcium homeostasis (). In this general picture, the abnormal genomic landscape seen in tumor cells is considered a downstream epiphenomenon of dysfunctional respiration and protracted oncogene-driven fermentation. In other words, the somatic mutations arise as effects rather than as causes of tumorigenesis. The nuclear transfer experiments support this view (Figure 1). In light of this perspective, it would be important for those working in cancer genomics field to justify the logic of their experimental approach to the cancer problem (,).

Cancer progression is more consistent with Lamarckian than Darwinian evolution

When viewed as a mitochondrial metabolic disease cancer progression is more in line with the evolutionary theory of Lamarck than with the theory of Darwin (). Many investigators in the cancer field have attempted to link the Darwinian theory of evolution to the phenomenon of tumor progression (). The attempt to link cancer progression to Darwinian evolution is based largely on the view that nuclear somatic mutations are drivers of the disease. According to Lamarck’s theory, it is the environment that produces changes in biological structures (). Through adaptation and differential use, these changes lead to modifications in the structures. The modifications of structures would then be passed on to successive generations as acquired traits. Lamarck’s evolutionary synthesis was based on his belief that the degree of use or disuse of biological structures shaped evolution along with the inheritance of acquired adaptability. Lamarck’s ideas could also accommodate a dominant role for epigenetics and horizontal gene transfer as factors that could facilitate tumor progression (,). In addition to nuclear epigenetic events involving acetylation and phosphorylations, mitochondria are also recognized as a powerful extra nuclear epigenetic system (,). Other epigenetic phenomena such as cytomegalovirus infection, cell fusion and horizontal gene transfer can also contribute to cancer progression and metastasis (,,).

Considering the dynamic behavior of mitochondria involving regular fusions and fissions, abnormalities in mitochondrial structure can be rapidly disseminated throughout the cellular mitochondrial network and passed along to daughter cells somatically, through cytoplasmic inheritance (,). The capacity for mitochondrial respiratory function becomes progressively less with each cell division as adaptability to substrate level phosphorylation increases (Figure 3). The somatic progression of cancer would therefore embody the concept of the somatic inheritance of an acquired trait. The acquired trait in this case is alteration to mitochondrial structure. The most malignant cancer cells would sustain the near-complete replacement of their respiration with fermentation. This is obvious in those tumor cells with quantitative and qualitative abnormalities in their mitochondria (Figure 2). The somatic inheritance of mitochondrial dysfunction in tumor cells could contribute in part to the appearance of a clonal origin, but not directly involving the nuclear genome. However, the degree of nuclear genomic instability can be linked to mitochondrial dysfunction and both defects together can contribute to tumor progression. A Lamarckian view can account for the non-uniform accumulation of mutations and drug resistance seen during cancer progression. Drug resistance is linked to enhanced lactate fermentation, which is acquired during tumor progression (,). It is our opinion that the evolutionary concepts of Lamarck can better explain the phenomena of tumor progression than can the evolutionary concepts of Darwin. We encourage further research on this perspective of tumor progression.

Exploiting mitochondrial dysfunction for the metabolic management of cancer

If cancer is primarily a disease of energy metabolism, then rational strategies for cancer management should be found in those therapies that specifically target tumor cell energy metabolism. These therapeutic strategies should be applicable to the majority of cancers regardless of tissue origin, as nearly all cancers suffer from a common malady, i.e. insufficient respiration with compensatory fermentation (,,,). As glucose is the major fuel for tumor energy metabolism through lactate fermentation, the restriction of glucose becomes a prime target for management. However, most normal cells of the body also need glycolytic pathway products, such as pyruvate, for energy production through OxPhos. It therefore becomes important to protect normal cells from drugs or therapies that disrupt glycolytic pathways or cause systemic reduction of glucose. It is well known that ketones can replace glucose as an energy metabolite and can protect the brain from severe hypoglycemia (). Hence, the shift in energy metabolism associated with a low carbohydrate, high-fat ketogenic diet administered in restricted amounts (KD-R) can protect normal cells from glycolytic inhibition and the brain from hypoglycemia.

When systemic glucose availability becomes limiting, most normal cells of the body will transition their energy metabolism to fats and ketone bodies. Ketone bodies are generated almost exclusively in liver hepatocytes largely from fatty acids of triglyceride origin during periods of fasting (,). There are no metabolic pathways described that can produce ketone bodies from carbohydrates despite suggestions to the contrary (). A restriction of total caloric intake will facilitate a reduction in blood glucose and insulin levels and an elevation in ketone bodies (β-hydroxybutyrate and acetoacetate). Most tumor cells are unable to use ketone bodies for energy due to abnormalities in mitochondria structure or function (,). Ketone bodies can also be toxic to some cancer cells (,). Nutritional ketosis induces metabolic stress on tumor tissue that is selectively vulnerable to glucose deprivation (). Hence, metabolic stress will be greater in tumor cells than in normal cells when the whole body is transitioned away from glucose and to ketone bodies for energy.

The metabolic shift from glucose metabolism to ketone body metabolism creates an anti-angiogenic, anti-inflammatory and pro-apoptotic environment within the tumor mass (,). The general concept of a survival advantage of tumor cells over normal cells occurs when fermentable fuels are abundant, but not when they are limited (). Figure 5 illustrates the changes in whole body levels of blood glucose and ketone bodies (β-hydroxybutyrate) that will metabolically stress tumor cells while enhancing the metabolic efficiency of normal cells. This therapeutic strategy was illustrated previously in cancer patients and in preclinical models ().

Implications for novel therapeutics

Once the whole body enters the metabolic zone described in Figure 5, relatively low doses of a variety of drugs can be used to further target energy metabolism in any surviving tumor cells (). It is interesting that the therapeutic success of imatinib (Gleevec) and trastuzumab (Herceptin) in managing BCR-ABL leukemia cells and ErbB2-positive breast cancers, respectively, is dependent on their ability to target signaling pathways linked to glucose metabolism (,). In contrast to these drugs, which target energy metabolism primarily in those individuals with mutations in specific receptors linked to the IGF-1/PI3K/Akt pathway, calorie-restricted KDs will target similar pathways in any cancer cell regardless of the mutations involved (,). Dietary energy reduction will simultaneously target multiple metabolic signaling pathways without causing adverse effects or toxicity (). Non-toxic metabolic therapies might also be a preferable alternative to toxic immunotherapies for cancer management especially if both therapies target the same pathways. It must be emphasized that the therapeutic efficacy of the KD is strongly dependent on restricted intake, as consumption of the KD in unrestricted amounts can cause insulin insensitivity and glucose elevation despite the complete absence of carbohydrates in the diet (). Elevated consumption of the KD is not often seen, however, as humans usually restrict intake due to the high fat content of the diet.

Poff et al. also recently showed a synergistic interaction between the KD and hyperbaric oxygen therapy (HBO2T) (Figure 6). The KD reduces glucose for glycolytic energy while also reducing NADPH levels for anti-oxidant potential through the pentose-phosphate pathway. HBO2T will increase ROS in the tumor cells, whereas the ketones will protect normal cells against ROS damage and from the potential for central nervous system oxygen toxicity (,). Glucose deprivation will enhance oxidative stress in tumor cells, whereas increased oxygen can reduce tumor cell proliferation (,). A dependency on glucose and an inability to use ketones for energy makes tumor cells selectively vulnerable to this therapy. Although this metabolic therapy is effective against those tumor cells that contain mitochondria, it remains to be determined if this therapy would be equally effective against those tumor cells containing few or no mitochondria (). In contrast to radiation therapy, which also kills tumor cells through ROS production (), the KD + HBO2T will kill tumor cells without causing toxic collateral damage to normal cells. Cancer patients and their oncologists should know about this. Some KDs might also enhance the therapeutic action of radiation therapy against brain and lung tumors (,). It will be important to compare and contrast the therapeutic efficacy of conventional radiation therapy with HBO2T when used with the KD-R. Although radiation is widely used as a cancer therapy, it should be recognized that radiation damages respiration in normal cells and can itself cause cancer (). Radiation therapy for malignant brain cancer creates a necrotic microenvironment that can facilitate recurrence and progression through enhanced glucose and glutamine metabolism (,).

Besides drugs that target glucose, drugs that target glutamine can also be effective in killing systemic metastatic cancer cells (,,). Many metastatic cancers express multiple characteristics of macrophages (,). Glutamine is a major fuel of macrophages and other cells of the immune system (,). As glutamine is the most abundant amino acid in the body and is used in multiple metabolic reactions, targeting glutamine without toxicity might be more difficult than targeting glucose (,). Although glutamine interacts synergistically with glucose to drive energy metabolism in cultured tumor cells, there are reports suggesting that glutamine can have chemo-preventive effects (). Further studies are needed to evaluate the role of glutamine as a facilitator of tumor energy metabolism in vivo.

The novelty of the metabolic approach to cancer management involves the implementation of a synergistic combination of nutritional ketosis, cancer metabolic drugs and HBO2T. This therapeutic approach would be similar to the ‘Press-Pulse’ scenario for the mass extinction of organisms in ecological communities (,). The KD-R would act as a sustained ‘Press’, whereas HBO2T and metabolic drugs would act as a ‘Pulse’ for the mass elimination of tumor cells in the body. Some of the cancer metabolic drugs could include 2-deoxyglucose, 3-bromopyruvate and dichloroacetate (,,). This therapeutic strategy produces a shift in metabolic physiology that will not only kill tumor cells but also enhance the general health and metabolic efficiency of normal cells, and consequently the whole body (,). We view this therapeutic approach as a type of ‘mitochondrial enhancement therapy’ (). As we consider OxPhos insufficiency with compensatory fermentation as the origin of cancer, enhanced OxPhos efficiency would be anti-carcinogenic.

Many cancers are infected with human cytomegalovirus, which acts as an oncomodulator of tumor progression (). Products of the virus can damage mitochondria in the infected tumor cells, thus contributing to a further dependence on glucose and glutamine for energy metabolism (,). The virus often infects cells of monocyte/macrophage origin, which are considered the origin of many metastatic cancers (,,,). We predict that the KD-R used together with anti-viral therapy will also be an effective Press-Pulse strategy for reducing progression of those cancers infected with human cytomegalovirus ().

Advanced metastatic cancers can become manageable when their access to fermentable fuels becomes restricted. The metabolic shift associated with the KD-R involves ‘keto-adaptation’. However, the adaptation to this new metabolic state can be challenging for some people. The administration of ketone esters could conceivably enable patients to circumvent the dietary restriction generally required for sustained nutritional ketosis. Ketone ester-induced ketosis would make sustained hypoglycemia more tolerable and thus assist in metabolic management of cancer (,). As each person is a unique metabolic entity, personalization of metabolic therapy as a broad-based cancer treatment strategy will require fine-tuning based on an understanding of individual human physiology. Also, personalized molecular therapies developed through the genome projects could be useful in targeting and killing those tumor cells that might survive the non-toxic whole body metabolic therapy. The number of molecular targets should be less in a few survivor cells of a small tumor than in a heterogeneous cell population of a large tumor. We would therefore consider personalized molecular therapy as a final strategy rather than as an initial strategy for cancer management. Non-toxic metabolic therapy should become the future of cancer treatment if the goal is to manage the disease without harming the patient. Although it will be important for researchers to elucidate the mechanistic minutia responsible for the therapeutic benefits, this should not impede an immediate application of this therapeutic strategy for cancer management or prevention.

Glossary

Abbreviations:

ATP adenosine triphosphate
HBO2T hyperbaric oxygen therapy
KD ketogenic diet
OxPhos oxidative phosphorylation
ROS reactive oxygen species
SLP substrate level phosphorylation
TCA tricarboxylic acid.
1. Sporn M.B. (1996). The war on cancerLancet347, 1377–1381 [PubMed]
2. Seyfried T.N. (2012). Cancer As a Metabolic Disease: On the Origin, Management, and Prevention of Cancer. John Wiley & Sons, Hoboken, NJ
3. Fidler I.J. (2003). The pathogenesis of cancer metastasis: the ‘seed and soil’ hypothesis revisitedNat. Rev. Cancer3, 453–458 [PubMed]
4. Lazebnik Y. (2010). What are the hallmarks of cancer? Nat. Rev. Cancer10, 232–233 [PubMed]
5. Tarin D. (2011). Cell and tissue interactions in carcinogenesis and metastasis and their clinical significanceSemin. Cancer Biol.21, 72–82 [PubMed]
6. Seyfried T.N. (2012). Confusion surrounds the origin of cancer. In Cancer As a Metabolic Disease: On the Origin, Management, and Prevention of Cancer. John Wiley & Sons, Hoboken, NJ, pp. 15–29
7. Hanahan D., et al. (2011). Hallmarks of cancer: the next generationCell144, 646–674 [PubMed]
8. Baker S.G., et al. (2007). Paradoxes in carcinogenesis: new opportunities for research directionsBMC Cancer7, 151. [PMC free article] [PubMed]
9. Soto A.M., et al. (2004). The somatic mutation theory of cancer: growing problems with the paradigm? Bioessays26, 1097–1107 [PubMed]
10. Vogelstein B., et al. (2013). Cancer genome landscapesScience339, 1546–1558 [PMC free article] [PubMed]
11. Alexandrov L.B., et al. (2013). Signatures of mutational processes in human cancerNature500, 415–421 [PMC free article] [PubMed]
12. Soto A.M., et al. (2012). Is systems biology a promising approach to resolve controversies in cancer research? Cancer Cell Int.12, 12. [PMC free article][PubMed]
13. Seyfried T.N., et al. (2012). Is the restricted ketogenic diet a viable alternative to the standard of care for managing malignant brain cancer? Epilepsy Res.100, 310–326 [PubMed]
14. Seyfried T.N. (2013). Cancer as a metabolic disease: implications for novel therapeuticsAmer. Assoc. Cancer Res. Education Book2013, 31–36
15. Seyfried T.N., et al. (2011). Metabolic management of brain cancerBiochim. Biophys. Acta1807, 577–594 [PubMed]
16. Seyfried T.N., et al. (2005). Targeting energy metabolism in brain cancer: review and hypothesisNutr. Metab. (Lond).2, 30. [PMC free article] [PubMed]
17. Seyfried T.N., et al. (2010). Cancer as a metabolic diseaseNutr. Metab. (Lond).7, 7. [PMC free article] [PubMed]
18. Seyfried T.N. (2012). Genes, respiration, viruses, and cancer. In Cancer As a Metabolic Disease: On the Origin, Management, and Prevention of Cancer. John Wiley & Sons, Hoboken, NJ, pp. 145–176
19. Stratton M.R. (2011). Exploring the genomes of cancer cells: progress and promiseScience331, 1553–1558 [PubMed]
20. Seyfried T.N. (2012). Nothing in cancer biology makes sense except in the light of evolution. In Cancer As a Metabolic Disease: On the Origin, Management, and Prevention of Cancer. John Wiley & Sons, Hoboken, NJ, pp. 261–275
21. Nowell P.C. (1976). The clonal evolution of tumor cell populationsScience,194, 23–28 [PubMed]
22. Fojo T., et al. (2010). Biologically targeted cancer therapy and marginal benefits: are we making too much of too little or are we achieving too little by giving too much? Clin. Cancer Res.16, 5972–5980 [PubMed]
23. Rosell R., et al. (2009). Customized treatment in non-small-cell lung cancer based on EGFR mutations and BRCA1 mRNA expressionPLoS One4, e5133. [PMC free article] [PubMed]
24. McLeod H.L. (2013). Cancer pharmacogenomics: early promise, but concerted effort neededScience339, 1563–1566 [PMC free article] [PubMed]
25. Hardy P.A., et al. . (2005) Reappraisal of the Hansemann-Boveri hypothesis on the origin of tumorsCell Biol. Int.29, 983–992 [PubMed]
26. Gibbs W.W. (2003). Untangling the roots of cancerSci. Am.289, 56–65[PubMed]
27. Hameroff S.R. (2004). A new theory of the origin of cancer: quantum coherent entanglement, centrioles, mitosis, and differentiationBiosystems.77, 119–136[PubMed]
28. Manchester K. (1997). The quest by three giants of science for an understanding of cancerEndeavour21, 72–76 [PubMed]
29. Wolf U. (1974). Theodor Boveri and his book, on the problem of the origin of malignant tumors. In German J, editor. (ed.) Chromosomes and Cancer, John Wiley & Sons, New York, pp. 1–20
30. Duesberg P., et al. (2000). Aneuploidy, the somatic mutation that makes cancer a species of its ownCell Motil. Cytoskeleton47, 81–107 [PubMed]
31. Salk J.J., et al. (2010). Mutational heterogeneity in human cancers: origin and consequencesAnnu. Rev. Pathol.5, 51–75 [PMC free article] [PubMed]
32. Cairns J. (1981). The origin of human cancersNature289, 353–357 [PubMed]
33. Loeb L.A. (2001). A mutator phenotype in cancerCancer Res.61, 3230–3239[PubMed]
34. Whitman R.C. (1919). Somatic mutations as a factor in the production of cancer; a critical review of von Hansemanns’s theory of anaplasia in light of modern knowledge of geneticsJ. Cancer Res.4, 181–202
35. Nigro J.M., et al. (1989). Mutations in the p53 gene occur in diverse human tumour typesNature342, 705–708 [PubMed]
36. Fearon E.R., et al. (1990). A genetic model for colorectal tumorigenesisCell,61, 759–767 [PubMed]
37. Knudson A.G. (2002). Cancer geneticsAm. J. Med. Genet.111, 96–102[PubMed]
38. Wagner R.P. (1999). Anecdotal, historical and critical commentaries on genetics. Rudolph Virchow and the genetic basis of somatic ecologyGenetics,151, 917–920 [PMC free article] [PubMed]
39. Darlington C.D. (1948) The plasmagene theory of the origin of cancerBr. J. Cancer2, 118–126 [PMC free article] [PubMed]
40. Koura M., et al. (1982). Suppression of tumorigenicity in interspecific reconstituted cells and cybridsGann73, 574–580 [PubMed]
41. Israel B.A., et al. (1987). Cytoplasmic suppression of malignancyIn Vitro Cell. Dev. Biol.23, 627–632 [PubMed]
42. Shay J.W., et al. (1988). Cytoplasmic suppression of tumorigenicity in reconstructed mouse cellsCancer Res.48, 830–833 [PubMed]
43. Howell A.N., et al. (1978). Tumorigenicity and its suppression in cybrids of mouse and Chinese hamster cell linesProc. Natl Acad. Sci. U. S. A.75, 2358–2362 [PMC free article] [PubMed]
44. Jonasson J., et al. (1977). The analysis of malignancy by cell fusion. VIII. Evidence for the intervention of an extra-chromosomal elementJ. Cell Sci.24, 255–263 [PubMed]
45. McKinnell R.G., et al. (1969). Transplantation of pluripotential nuclei from triploid frog tumorsScience165, 394–396 [PubMed]
46. Mintz B., et al. (1975). Normal genetically mosaic mice produced from malignant teratocarcinoma cellsProc. Natl Acad. Sci. U. S. A.72, 3585–3589 [PMC free article] [PubMed]
47. Li L., et al. (2003). Mouse embryos cloned from brain tumorsCancer Res.63, 2733–2736 [PubMed]
48. Hochedlinger K., et al. (2004). Reprogramming of a melanoma genome by nuclear transplantationGenes Dev.18, 1875–1885 [PMC free article] [PubMed]
49. Seyfried T.N. (2012). Mitochondria: the ultimate tumor suppressor. In Cancer As a Metabolic Disease: On the Origin, Management, and Prevention of Cancer. John Wiley & Sons, Hoboken, NJ, pp. 195–205
50. Kaipparettu B.A., et al. (2013). Crosstalk from non-cancerous mitochondria can inhibit tumor properties of metastatic cells by suppressing oncogenic pathways.PLoS One8, e61747. [PMC free article] [PubMed]
51. Elliott R.L., et al. . (2012) Mitochondria organelle transplantation: introduction of normal epithelial mitochondria into human cancer cells inhibits proliferation and increases drug sensitivityBreast Cancer Res. Treat.136, 347–354 [PubMed]
52. Israel B.A., et al. (1988). Cytoplasmic mediation of malignancyIn Vitro Cell. Dev. Biol.24, 487–490 [PubMed]
53. Petros J.A., et al. (2005). mtDNA mutations increase tumorigenicity in prostate cancerProc. Natl Acad. Sci. U. S. A.102, 719–724 [PMC free article] [PubMed]
54. Warburg O. (1931). The Metabolism of Tumours. Richard R. Smith, New York
55. Warburg O. (1956). On the origin of cancer cellsScience123, 309–314[PubMed]
56. Pedersen P.L. (2007). Warburg, me and hexokinase 2: multiple discoveries of key molecular events underlying one of cancers’ most common phenotypes, the “Warburg Effect”, i.e., elevated glycolysis in the presence of oxygenJ. Bioenerg. Biomembr.39, 211–222 [PubMed]
57. Warburg O. (1956). On respiratory impairment in cancer cellsScience124, 269–270 [PubMed]
58. Warburg O. (1969). Revidsed Lindau lectures: the prime cause of cancer and prevention – Parts 1 & 2. In Burk D, editor. (ed.) Meeting of the Nobel-Laureates. K.Triltsch, Lindau, Lake Constance, Germany
59. Racker E. (1972) Bioenergetics and the problem of tumor growthAm. Sci.60, 56–63 [PubMed]
60. Nelson D.L., et al. (2008) Lehninger Principles of Biochemistry W. H. Freeman, New York
61. Cuezva J.M., et al. (2002). The bioenergetic signature of cancer: a marker of tumor progressionCancer Res.62, 6674–6681 [PubMed]
62. Acebo P., et al. (2009). Cancer abolishes the tissue type-specific differences in the phenotype of energetic metabolismTransl. Oncol.2, 138–145 [PMC free article] [PubMed]
63. Weinhouse S. (1956). On respiratory impairment in cancer cellsScience124, 267–269 [PubMed]
64. Koppenol W.H., et al. (2011). Otto Warburg’s contributions to current concepts of cancer metabolismNat. Rev. Cancer11, 325–337 [PubMed]
65. Stellingwerff T., et al. . (2006) Hyperoxia decreases muscle glycogenolysis, lactate production, and lactate efflux during steady-state exerciseAm. J. Physiol. Endocrinol. Metab.290, E1180–E1190 [PubMed]
66. Gatenby R.A., et al. (2004). Why do cancers have high aerobic glycolysis? Nat. Rev. Cancer4, 891–899 [PubMed]
67. Pedersen P.L. (1978). Tumor mitochondria and the bioenergetics of cancer cells.Prog. Exp. Tumor Res.22, 190–274 [PubMed]
68. Chevrollier A., et al. (2005) ANT2 expression under hypoxic conditions produces opposite cell-cycle behavior in 143B and HepG2 cancer cellsMol. Carcinog.42, 1–8 [PubMed]
69. Wijburg F.A., et al. (1989) Studies on the formation of lactate and pyruvate from glucose in cultured skin fibroblasts: implications for detection of respiratory chain defectsBiochem. Int.19, 563–570 [PubMed]
70. Tiefenthaler M., et al. (2001) Increased lactate production follows loss of mitochondrial membrane potential during apoptosis of human leukaemia cellsBr. J. Haematol.114, 574–580 [PubMed]
71. Donnelly M., et al. (1976). Energy metabolism in respiration-deficient and wild type Chinese hamster fibroblasts in cultureJ. Cell. Physiol.89, 39–51 [PubMed]
72. Fiske B.P., et al. (2012) Seeing the Warburg effect in the developing retinaNat. Cell Biol.14, 790–791 [PubMed]
73. Prichard J., et al. (1991) Lactate rise detected by 1H NMR in human visual cortex during physiologic stimulationProc. Natl Acad. Sci. U. S. A.88, 5829–5831 [PMC free article] [PubMed]
74. Fox P.T., et al. (1988). Nonoxidative glucose consumption during focal physiologic neural activityScience241, 462–464 [PubMed]
75. Krasnow N., et al. (1962) Myocardial lactate and pyruvate metabolismJ. Clin. Invest.41, 2075–2085 [PMC free article] [PubMed]
76. Burk D., et al. (1956). On respiratory impairment in cancer cellsScience124, 270–272 [PubMed]
77. Burk D., et al. (1967). On the significance of glucolysis for cancer growth, with special reference to Morris rat hepatomasJ. Natl Cancer Inst.38, 839–863[PubMed]
78. Vaupel P., et al. (2012) Availability, not respiratory capacity governs oxygen consumption of solid tumorsInt. J. Biochem. Cell Biol.44, 1477–1481 [PubMed]
79. Moreno-Sánchez R., et al. (2007). Energy metabolism in tumor cellsFEBS J.,274, 1393–1418 [PubMed]
80. Haq R., et al. (2013) Oncogenic BRAF regulates oxidative metabolism via PGC1α and MITFCancer Cell23, 302–315 [PMC free article] [PubMed]
81. Weinhouse S. (1976). The Warburg hypothesis fifty years laterZ. Krebsforsch. Klin. Onkol. Cancer Res. Clin. Oncol.87, 115–126 [PubMed]
82. Ferreira L.M. (2010). Cancer metabolism: the Warburg effect todayExp. Mol. Pathol.89, 372–380 [PubMed]
83. Hall A., et al. (2013). Dysfunctional oxidative phosphorylation makes malignant melanoma cells addicted to glycolysis driven by the (V600E)BRAF oncogeneOncotarget4, 584–599 [PMC free article] [PubMed]
84. Hochachka P.W., et al. (2002). Biochemical Adaptation: Mechanism and Process in Physiological Evolution. Oxford Press, New York
85. Seyfried T.N. (2012). Is respiration normal in cancer cells? In Cancer As a Metabolic Disease: On the Origin, Management, and Prevention of Cancer. John Wiley & Sons, Hoboken, NJ, pp. 119–132
86. Ramanathan A., et al. (2005). Perturbational profiling of a cell-line model of tumorigenesis by using metabolic measurementsProc. Natl Acad. Sci. U. S. A.,102, 5992–5997 [PMC free article] [PubMed]
87. Seyfried T.N. (2012). Is mitochondrial glutamine fermentation a missing link in the metabolic theory of cancer? In Cancer As a Metabolic Disease: On the Origin, Management, and Prevention of Cancer. John Wiley & Sons, Hoboken, NJ, pp. 133–144
88. Chinopoulos C., et al. (2010) Forward operation of adenine nucleotide translocase during F0F1-ATPase reversal: critical role of matrix substrate-level phosphorylationFASEB J.24, 2405–2416 [PMC free article] [PubMed]
89. Phillips D., et al. (2009). Succinyl-CoA synthetase is a phosphate target for the activation of mitochondrial metabolismBiochemistry48, 7140–7149 [PMC free article] [PubMed]
90. Schwimmer C., et al. (2005). Increasing mitochondrial substrate-level phosphorylation can rescue respiratory growth of an ATP synthase-deficient yeast.J. Biol. Chem.280, 30751–30759 [PubMed]
91. Seyfried T.N. (2012). Respiratory dysfunction in cancer cells. In Cancer As a Metabolic Disease: On the Origin, Management, and Prevention of Cancer. John Wiley & Sons, Hoboken, NJ, pp. 73–105
92. Arismendi-Morillo G. (2011) Electron microscopy morphology of the mitochondrial network in gliomas and their vascular microenvironmentBiochim. Biophys. Acta1807, 602–608 [PubMed]
93. Arismendi-Morillo G. (2009). Electron microscopy morphology of the mitochondrial network in human cancerInt. J. Biochem. Cell Biol.41, 2062–2068[PubMed]
94. Arismendi-Morillo G.J., et al. (2008). Ultrastructural mitochondrial pathology in human astrocytic tumors: potentials implications pro-therapeutics strategiesJ. Electron Microsc. (Tokyo).57, 33–39 [PubMed]
95. Galluzzi L., et al. (2010) Mitochondrial gateways to cancerMol. Aspects Med.31, 1–20 [PubMed]
96. Kiebish M.A., et al. (2009). In vitro growth environment produces lipidomic and electron transport chain abnormalities in mitochondria from non-tumorigenic astrocytes and brain tumoursASN Neuro1, e00011. [PMC free article] [PubMed]
97. Kiebish M.A., et al. (2008). Cardiolipin and electron transport chain abnormalities in mouse brain tumor mitochondria: lipidomic evidence supporting the Warburg theory of cancerJ. Lipid Res.49, 2545–2556 [PMC free article][PubMed]
98. Gonzalez M.J., et al. (2012) The bio-energetic theory of carcinogenesisMed. Hypotheses79, 433–439 [PubMed]
99. Benard G., et al. (2008) Ultrastructure of the mitochondrion and its bearing on function and bioenergeticsAntioxid. Redox Signal.10, 1313–1342 [PubMed]
100. Shapovalov Y., et al. (2011) Mitochondrial dysfunction in cancer cells due to aberrant mitochondrial replicationJ. Biol. Chem.286, 22331–22338 [PMC free article] [PubMed]
101. Alirol E., et al. (2006). Mitochondria and cancer: is there a morphological connection? Oncogene25, 4706–4716 [PubMed]
102. Oudard S., et al. (1997). Gliomas are driven by glycolysis: putative roles of hexokinase, oxidative phosphorylation and mitochondrial ultrastructureAnticancer Res.17, 1903–1911 [PubMed]
103. Wu S.B., et al. (2012). AMPK-mediated increase of glycolysis as an adaptive response to oxidative stress in human cells: implication of the cell survival in mitochondrial diseasesBiochim. Biophys. Acta1822, 233–247 [PubMed]
104. Fulda S., et al. (2010) Targeting mitochondria for cancer therapyNat. Rev. Drug Discov.9, 447–464 [PubMed]
105. Shapovalov Y., et al. (2011) Mitochondrial dysfunction in cancer cells due to aberrant mitochondrial replicationJ. Biol. Chem.286, 22331–22338 [PMC free article] [PubMed]
106. Chance B., et al. (1959). Spectroscopic evidence of metabolic control.Science129, 700–708 [PubMed]
107. Colowick S.P. (1961). The status of Warburg’s theory of glycolysis and respiration in tumorsQuart. Rev. Biol.36, 273–276
108. Cairns R.A., et al. (2011) Regulation of cancer cell metabolismNat. Rev. Cancer11, 85–95 [PubMed]
109. Ward P.S., et al. (2012). Metabolic reprogramming: a cancer hallmark even warburg did not anticipateCancer Cell21, 297–308 [PMC free article] [PubMed]
110. Vander Heiden M.G., et al. (2009). Understanding the Warburg effect: the metabolic requirements of cell proliferationScience324, 1029–1033 [PMC free article] [PubMed]
111. Rossignol R., et al. (2004). Energy substrate modulates mitochondrial structure and oxidative capacity in cancer cellsCancer Res.64, 985–993 [PubMed]
112. Chevrollier A., et al. (2011) Adenine nucleotide translocase 2 is a key mitochondrial protein in cancer metabolismBiochim. Biophys. Acta1807, 562–567 [PubMed]
113. Jahnke V.E., et al. (2010). Evidence for mitochondrial respiratory deficiency in rat rhabdomyosarcoma cellsPLoS One5, e8637. [PMC free article] [PubMed]
114. Schild L., et al. (2012) Composition of molecular cardiolipin species correlates with proliferation of lymphocytesExp. Biol. Med. (Maywood).237, 372–379[PubMed]
115. Kocherginsky N. (2009). Acidic lipids, H(+)-ATPases, and mechanism of oxidative phosphorylation. Physico-chemical ideas 30 years after P. Mitchell’s Nobel Prize awardProg. Biophys. Mol. Biol.99, 20–41 [PubMed]
116. Claypool S.M., et al. (2012) The complexity of cardiolipin in health and diseaseTrends Biochem. Sci.37, 32–41 [PMC free article] [PubMed]
117. Zu X.L., et al. (2004). Cancer metabolism: facts, fantasy, and fiction.Biochem. Biophys. Res. Commun.313, 459–465 [PubMed]
118. Wang T., et al. (1976). Aerobic glycolysis during lymphocyte proliferation.Nature261, 702–705 [PubMed]
119. Lunt S.Y., et al. (2011) Aerobic glycolysis: meeting the metabolic requirements of cell proliferationAnnu. Rev. Cell Dev. Biol.27, 441–464[PubMed]
120. Papandreou I., et al. (2011) Anticancer drugs that target metabolism: is dichloroacetate the new paradigm? Int. J. Cancer128, 1001–1008 [PubMed]
121. Burk D., et al. (1941). Metabolism of butter yellow rat liver cancersCanc. Res.1, 733–734
122. Simek J., et al. (1965). Effect of glucose administered in vivo or in vitro on the respiratory quotient of rat liver tissue after partial hepatectomyNature207, 761–762 [PubMed]
123. Diatlovitskaia E.V., et al. (1972). [Cardiolipins of mitochondria and microsomes of Jensen’s sarcoma]Dokl. Akad. Nauk SSSR206, 737–739[PubMed]
124. Diatlovitskaia E.V., et al. (1976). [Positional distribution of fatty acids in the phospholipids of regenerating rat liver]Biokhimiia.41, 538–542 [PubMed]
125. Crabtree H.G. (1929). Observations on the carbohydrate metabolism of tumoursBiochem. J.23, 536–545 [PMC free article] [PubMed]
126. Redman E.K., et al. (2013) Role of p90(RSK) in regulating the Crabtree effect: implications for cancerBiochem. Soc. Trans.41, 124–126 [PMC free article][PubMed]
127. Díaz-Ruiz R., et al. (2008) Mitochondrial oxidative phosphorylation is regulated by fructose 1,6-bisphosphate. A possible role in Crabtree effect induction? J. Biol. Chem.283, 26948–26955 [PubMed]
128. Diaz-Ruiz R., et al. (2011) The Warburg and Crabtree effects: on the origin of cancer cell energy metabolism and of yeast glucose repressionBiochim. Biophys. Acta1807, 568–576 [PubMed]
129. Holleran A.L., et al. (1995) Glutamine metabolism in AS-30D hepatoma cells. Evidence for its conversion into lipids via reductive carboxylationMol. Cell. Biochem.152, 95–101 [PubMed]
130. Fendt S.M., et al. (2013) Reductive glutamine metabolism is a function of the α-ketoglutarate to citrate ratio in cellsNat. Commun.4, 2236. [PMC free article][PubMed]
131. Pollard P.J., et al. (2003). The TCA cycle and tumorigenesis: the examples of fumarate hydratase and succinate dehydrogenaseAnn. Med.35, 632–639[PubMed]
132. Gottlieb E., et al. (2005). Mitochondrial tumour suppressors: a genetic and biochemical updateNat. Rev. Cancer5, 857–866 [PubMed]
133. Seyfried T.N. (2012). Cancer models. In Cancer As a Metabolic Disease: On the Origin, Management, and Prevention of Cancer. John Wiley & Sons, Hoboken, NJ, pp. 31–46
134. Ecsedy J.A., et al. (1999). Expression of mouse sialic acid on gangliosides of a human glioma grown as a xenograft in SCID miceJ. Neurochem.73, 254–259[PubMed]
135. Chou H.H., et al. (1998). A mutation in human CMP-sialic acid hydroxylase occurred after the Homo-Pan divergenceProc. Natl Acad. Sci. U. S. A.95, 11751–11756 [PMC free article] [PubMed]
136. Martin M.J., et al. (2005). Human embryonic stem cells express an immunogenic nonhuman sialic acidNat. Med.11, 228–232 [PubMed]
137. Davies B., et al. (1993) Physiological parameters in laboratory animals and humansPharm. Res.10, 1093–1095 [PubMed]
138. Mahoney L.B., et al. (2006). Caloric restriction in C57BL/6J mice mimics therapeutic fasting in humansLipids Health Dis.5, 13. [PMC free article][PubMed]
139. Tentler J.J., et al. (2012) Patient-derived tumour xenografts as models for oncology drug developmentNat. Rev. Clin. Oncol.9, 338–350 [PMC free article][PubMed]
140. Chaparro R.J., et al. (2006). Nonobese diabetic mice express aspects of both type 1 and type 2 diabetesProc. Natl Acad. Sci. U. S. A.103, 12475–12480 [PMC free article] [PubMed]
141. Seyfried T.N. (2012). Mitochondrial respiratory dysfunction and the extrachromosomal origin of cancer. In Cancer As a Metabolic Disease: On the Origin, Management, and Prevention of Cancer. John Wiley & Sons, Hoboken, NJ, pp. 253–259
142. Hu Y., et al. (2012). K-ras(G12V) transformation leads to mitochondrial dysfunction and a metabolic switch from oxidative phosphorylation to glycolysis.Cell Res.22, 399–412 [PMC free article] [PubMed]
143. Neuzil J., et al. (2012) K-Ras and mitochondria: dangerous liaisonsCell Res.,22, 285–287 [PMC free article] [PubMed]
144. Szent-Györgyi A. (1977). The living state and cancerProc. Natl Acad. Sci. U. S. A.74, 2844–2847 [PMC free article] [PubMed]
145. Pawelek J.M., et al. (2008). The cancer cell–leukocyte fusion theory of metastasisAdv. Cancer Res.101, 397–444 [PubMed]
146. Seyfried T.N., et al. (2013) On the origin of cancer metastasisCrit. Rev. Oncog.18, 43–73 [PMC free article] [PubMed]
147. Powell A.E., et al. (2011). Fusion between Intestinal epithelial cells and macrophages in a cancer context results in nuclear reprogrammingCancer Res.,71, 1497–1505 [PMC free article] [PubMed]
148. Pawelek J.M. (2005). Tumour-cell fusion as a source of myeloid traits in cancerLancet Oncol.6, 988–993 [PubMed]
149. Malkin D., et al. (1990). Germ line p53 mutations in a familial syndrome of breast cancer, sarcomas, and other neoplasmsScience250, 1233–1238 [PubMed]
150. Funes J.M., et al. (2007). Transformation of human mesenchymal stem cells increases their dependency on oxidative phosphorylation for energy production.Proc. Natl Acad. Sci. U. S. A.104, 6223–6228 [PMC free article] [PubMed]
151. Sung H.J., et al. (2011). Mitochondrial respiration protects against oxygen-associated DNA damageNat Commun1, 1–8 [PMC free article] [PubMed]
152. Lago C.U., et al. (2011) p53, aerobic metabolism, and cancerAntioxid. Redox Signal.15, 1739–1748 [PMC free article] [PubMed]
153. Matoba S., et al. (2006). p53 regulates mitochondrial respirationScience312, 1650–1653 [PubMed]
154. Zhou S., et al. (2003). Mitochondrial impairment in p53-deficient human cancer cellsMutagenesis18, 287–292 [PubMed]
155. Lee A.C., et al. (1999). Ras proteins induce senescence by altering the intracellular levels of reactive oxygen speciesJ. Biol. Chem.274, 7936–7940[PubMed]
156. Weinberg F., et al. (2010). Mitochondrial metabolism and ROS generation are essential for Kras-mediated tumorigenicityProc. Natl Acad. Sci. U. S. A.107, 8788–8793 [PMC free article] [PubMed]
157. Yang D., et al. (2010). Impairment of mitochondrial respiration in mouse fibroblasts by oncogenic H-RAS(Q61L)Cancer Biol. Ther.9, 122–133 [PMC free article] [PubMed]
158. Moiseeva O., et al. (2009). Mitochondrial dysfunction contributes to oncogene-induced senescenceMol. Cell. Biol.29, 4495–4507 [PMC free article][PubMed]
159. Seyfried T.N. (2012). Respiratory insufficiency, the retrograde response, and the origin of cancer. In Cancer As a Metabolic Disease: On the Origin, Management, and Prevention of Cancer. John Wiley & Sons, Hoboken, NJ, pp. 177–194
160. Guha M., et al. (2013) Mitochondrial retrograde signaling at the crossroads of tumor bioenergetics, genetics and epigeneticsMitochondrion13, 577–591 [PMC free article] [PubMed]
161. Singh K.K., et al. (2005). Inter-genomic cross talk between mitochondria and the nucleus plays an important role in tumorigenesisGene354, 140–146[PubMed]
162. Jazwinski S.M. (2005). The retrograde response links metabolism with stress responses, chromatin-dependent gene activation, and genome stability in yeast agingGene354, 22–27 [PubMed]
163. Nargund A.M., et al. (2012). Mitochondrial import efficiency of ATFS-1 regulates mitochondrial UPR activationScience337, 587–590 [PMC free article][PubMed]
164. Al Mamun A.A., et al. (2012). Identity and function of a large gene network underlying mutagenic repair of DNA breaksScience338, 1344–1348 [PMC free article] [PubMed]
165. Dang C.V. (2010). Glutaminolysis: supplying carbon or nitrogen or both for cancer cells? Cell Cycle9, 3884–3886 [PubMed]
166. Bissell M.J., et al. (2011). Why don’t we get more cancer? A proposed role of the microenvironment in restraining cancer progressionNat. Med.17, 320–329 [PMC free article] [PubMed]
167. Gatenby R.A., et al. (2007). Glycolysis in cancer: a potential target for therapyInt. J. Biochem. Cell Biol.39, 1358–1366 [PubMed]
168. Husain Z., et al. (2013) Tumor-derived lactate modifies antitumor immune response: effect on myeloid-derived suppressor cells and NK cellsJ. Immunol.,191, 1486–1495 [PubMed]
169. Liu E.T. (2013). Grappling with cancerScience339, 1493. [PubMed]
170. Pennisi E. (2013). Steering cancer genomics into the fast laneScience339, 1540–1542 [PubMed]
171. Stratton M.R., et al. (2009). The cancer genomeNature458, 719–724 [PMC free article] [PubMed]
172. Crespi B., et al. (2005). Evolutionary biology of cancerTrends Ecol. Evol.,20, 545–552 [PubMed]
173. Merlo L.M., et al. (2006). Cancer as an evolutionary and ecological process.Nat. Rev. Cancer6, 924–935 [PubMed]
174. Davies P.C., et al. (2011). Cancer tumors as Metazoa 1.0: tapping genes of ancient ancestorsPhys. Biol.8, 015001. [PMC free article] [PubMed]
175. Mayer E. (1982). Evolution before Darwin. In The Growth of Biological Thought: Diversity, Evolution, and Inheritance. Belknap Harvard, Cambridge, MA, pp. 343–362
176. Handel A.E., et al. (2010). Is Lamarckian evolution relevant to medicine?BMC Med. Genet.11, 73. [PMC free article] [PubMed]
177. Koonin E.V., et al. (2009). Is evolution Darwinian or/and Lamarckian? Biol. Direct4, 42. [PMC free article] [PubMed]
178. Smiraglia D.J., et al. (2008). A novel role for mitochondria in regulating epigenetic modification in the nucleusCancer Biol. Ther.7, 1182–1190 [PMC free article] [PubMed]
179. Minocherhomji S., et al. (2012) Mitochondrial regulation of epigenetics and its role in human diseasesEpigenetics7, 326–334 [PMC free article] [PubMed]
180. Feinberg A.P., et al. (2004). The history of cancer epigeneticsNat. Rev. Cancer4, 143–153 [PubMed]
181. Pawelek J.M. (2000). Tumour cell hybridization and metastasis revisited.Melanoma Res.10, 507–514 [PubMed]
182. Huysentruyt L.C., et al. (2010). Perspectives on the mesenchymal origin of metastatic cancerCancer Metastasis Rev.29, 695–707 [PMC free article][PubMed]
183. Holmgren L., et al. (1999). Horizontal transfer of DNA by the uptake of apoptotic bodiesBlood93, 3956–3963 [PubMed]
184. Dziurzynski K., et al. ; HCMV and Gliomas Symposium (2012) Consensus on the role of human cytomegalovirus in glioblastomaNeuro. Oncol.14, 246–255 [PMC free article] [PubMed]
185. Detmer S.A., et al. (2007). Functions and dysfunctions of mitochondrial dynamicsNat. Rev. Mol. Cell Biol.8, 870–879 [PubMed]
186. Xu R.H., et al. (2005). Inhibition of glycolysis in cancer cells: a novel strategy to overcome drug resistance associated with mitochondrial respiratory defect and hypoxiaCancer Res.65, 613–621 [PubMed]
187. VanItallie T.B., et al. (2003). Ketones: metabolism’s ugly ducklingNutr. Rev.,61, 327–341 [PubMed]
188. Drenick E.J., et al. (1972) Resistance to symptomatic insulin reactions after fastingJ. Clin. Invest.51, 2757–2762 [PMC free article] [PubMed]
189. Veech R.L. (2004). The therapeutic implications of ketone bodies: the effects of ketone bodies in pathological conditions: ketosis, ketogenic diet, redox states, insulin resistance, and mitochondrial metabolismProstaglandins. Leukot. Essent. Fatty Acids70, 309–319 [PubMed]
190. Krebs H.A., et al. (1971). The role of ketone bodies in caloric homeostasis.Adv. Enzyme Reg.9, 387–409
191. Bonuccelli G., et al. (2010). Ketones and lactate “fuel” tumor growth and metastasis: evidence that epithelial cancer cells use oxidative mitochondrial metabolismCell Cycle9, 3506–3514 [PMC free article] [PubMed]
192. Seyfried T.N. (2012). Metabolic management of cancer. In Cancer As a Metabolic Disease: On the Origin, Management, and Prevention of Cancer. John Wiley & Sons, Hoboken, NJ, pp. 291–354
193. Maurer G.D., et al. (2011). Differential utilization of ketone bodies by neurons and glioma cell lines: a rationale for ketogenic diet as experimental glioma therapy.BMC Cancer11, 315. [PMC free article] [PubMed]
194. Skinner R., et al. (2009). Ketone bodies inhibit the viability of human neuroblastoma cellsJ. Pediatr. Surg.44, 212–6; discussion 216 [PubMed]
195. Seyfried T.N., et al. (2003). Role of glucose and ketone bodies in the metabolic control of experimental brain cancerBr. J. Cancer89, 1375–1382 [PMC free article] [PubMed]
196. Jiang Y.S., et al. (2013) Caloric restriction reduces edema and prolongs survival in a mouse glioma modelJ. Neurooncol.114, 25–32 [PubMed]
197. Mukherjee P., et al. (2004). Antiangiogenic and proapoptotic effects of dietary restriction on experimental mouse and human brain tumorsClin. Cancer Res.10, 5622–5629 [PubMed]
198. Mukherjee P., et al. (2002). Dietary restriction reduces angiogenesis and growth in an orthotopic mouse brain tumour modelBr. J. Cancer86, 1615–1621 [PMC free article] [PubMed]
199. Mulrooney T.J., et al. (2011). Influence of caloric restriction on constitutive expression of NF-κB in an experimental mouse astrocytomaPLoS One6, e18085. [PMC free article] [PubMed]
200. Simone B.A., et al. (2013). Selectively starving cancer cells through dietary manipulation: methods and clinical implicationsFuture Oncol.9, 959–976[PubMed]
201. Stafford P., et al. (2010). The ketogenic diet reverses gene expression patterns and reduces reactive oxygen species levels when used as an adjuvant therapy for gliomaNutr. Metab. (Lond).7, 74. [PMC free article] [PubMed]
202. Fine E.J., et al. (2012). Targeting insulin inhibition as a metabolic therapy in advanced cancer: a pilot safety and feasibility dietary trial in 10 patientsNutrition,28, 1028–1035 [PubMed]
203. Zuccoli G., et al. (2010). Metabolic management of glioblastoma multiforme using standard therapy together with a restricted ketogenic diet: Case ReportNutr. Metab. (Lond).7, 33. [PMC free article] [PubMed]
204. Nebeling L.C., et al. (1995). Effects of a ketogenic diet on tumor metabolism and nutritional status in pediatric oncology patients: two case reportsJ. Am. Coll. Nutr.14, 202–208 [PubMed]
205. Zhou W., et al. (2007). The calorically restricted ketogenic diet, an effective alternative therapy for malignant brain cancerNutr. Metab. (Lond).4, 5. [PMC free article] [PubMed]
206. Gottschalk S., et al. (2004) Imatinib (STI571)-mediated changes in glucose metabolism in human leukemia BCR-ABL-positive cellsClin. Cancer Res.10, 6661–6668 [PubMed]
207. Zhao Y., et al. (2011). Overcoming trastuzumab resistance in breast cancer by targeting dysregulated glucose metabolismCancer Res.71, 4585–4597 [PMC free article] [PubMed]
208. Marsh J., et al. (2008). Akt-dependent proapoptotic effects of dietary restriction on late-stage management of a phosphatase and tensin homologue/tuberous sclerosis complex 2-deficient mouse astrocytomaClin. Cancer Res.14, 7751–7762 [PubMed]
209. Veech R.L., et al. (2001). Ketone bodies, potential therapeutic usesIUBMB Life51, 241–247 [PubMed]
210. Chen Y., et al. (2009). Oxygen consumption can regulate the growth of tumors, a new perspective on the Warburg effectPLoS One4, e7033. [PMC free article] [PubMed]
211. Spitz D.R., et al. (2000). Glucose deprivation-induced oxidative stress in human tumor cells. A fundamental defect in metabolism? Ann. N. Y. Acad. Sci.,899, 349–362 [PubMed]
212. Harrison L., et al. (2004). Hypoxia and anemia: factors in decreased sensitivity to radiation therapy and chemotherapy? Oncologist9 (suppl. 5), 31–40 [PubMed]
213. Allen B.G., et al. (2013) Ketogenic diets enhance oxidative stress and radio-chemo-therapy responses in lung cancer xenograftsClin. Cancer Res.19, 3905–3913 [PMC free article] [PubMed]
214. Abdelwahab M.G., et al. (2012). The ketogenic diet is an effective adjuvant to radiation therapy for the treatment of malignant gliomaPLoS One7, e36197. [PMC free article] [PubMed]
215. Seyfried T.N., et al. (2010). Does the existing standard of care increase glioblastoma energy metabolism? Lancet Oncol.11, 811–813 [PubMed]
216. Yuneva M. (2008). Finding an “Achilles’ heel” of cancer: the role of glucose and glutamine metabolism in the survival of transformed cellsCell Cycle7, 2083–2089 [PubMed]
217. DeBerardinis R.J., et al. (2010). Q’s next: the diverse functions of glutamine in metabolism, cell biology and cancerOncogene29, 313–324 [PMC free article][PubMed]
218. Lazova R., et al. (2013). A melanoma brain metastasis with a donor-patient hybrid genome following bone marrow transplantation: first evidence for fusion in human cancerPLoS One8, e66731. [PMC free article] [PubMed]
219. Newsholme P. (2001). Why is L-glutamine metabolism important to cells of the immune system in health, postinjury, surgery or infection? J. Nutr.131(suppl. 9), 2515S–2522S; discussion 2523S. [PubMed]
220. Mates J.M., et al. (2012). Glutaminase isoenzymes as key regulators in metabolic and oxidative stress against cancerCurrent Mol. Med.12, 1–21[PubMed]
221. Shelton L.M., et al. (2010). Glutamine targeting inhibits systemic metastasis in the VM-M3 murine tumor modelInt. J. Cancer127, 2478–2485 [PMC free article] [PubMed]
222. Lim V., et al. (2009). Glutamine prevents DMBA-induced squamous cell cancerOral Oncol.45, 148–155 [PubMed]
223. Vincent M.D. (2011) Cancer: beyond speciationAdv. Cancer Res.112, 283–350 [PubMed]
224. Arens N.C., et al. (2008). Press-pulse: a general theory of mass extinction?Paleobiology34, 456–471
225. Ko Y.H., et al. (2004). Advanced cancers: eradication in all cases using 3-bromopyruvate therapy to deplete ATPBiochem. Biophys. Res. Commun.324, 269–275 [PubMed]
226. Bonnet S., et al. (2007). A mitochondria-K+ channel axis is suppressed in cancer and its normalization promotes apoptosis and inhibits cancer growthCancer Cell11, 37–51 [PubMed]
227. Marsh J., et al. (2008). Drug/diet synergy for managing malignant astrocytoma in mice: 2-deoxy-D-glucose and the restricted ketogenic dietNutr. Metab. (Lond).,5, 33. [PMC free article] [PubMed]
228. Michaelis M., et al. (2009). The story of human cytomegalovirus and cancer: increasing evidence and open questionsNeoplasia11, 1–9 [PMC free article][PubMed]
229. Yu Y., et al. (2013) Genome-wide identification and characterization of polygalacturonase genes in Cucumis sativus and Citrullus lanatusPlant Physiol. Biochem.74C, 263–275 [PubMed]
230. Bozidis P., et al. (2010) Trafficking of UL37 proteins into mitochondrion-associated membranes during permissive human cytomegalovirus infectionJ. Virol.84, 7898–7903 [PMC free article] [PubMed]
231. Williamson C.D., et al. (2009) Access of viral proteins to mitochondria via mitochondria-associated membranesRev. Med. Virol.19, 147–164 [PMC free article] [PubMed]
232. Dziurzynski K., et al. (2011) Glioma-associated cytomegalovirus mediates subversion of the monocyte lineage to a tumor propagating phenotypeClin. Cancer Res.17, 4642–4649 [PMC free article] [PubMed]
233. Munzarová M., et al. (1991). Do some malignant melanoma cells share antigens with the myeloid monocyte lineage? Neoplasma38, 401–405 [PubMed]
234. Söderberg-Nauclér C., et al. (2013) Survival in patients with glioblastoma receiving valganciclovirN. Engl. J. Med.369, 985–986 [PubMed]
235. Clarke K., et al. (2012) Kinetics, safety and tolerability of ®-3-hydroxybutyl ®-3-hydroxybutyrate in healthy adult subjectsRegul. Toxicol. Pharmacol.63, 401–408 [PMC free article] [PubMed]
236. D’Agostino D.P., et al. (2013) Therapeutic ketosis with ketone ester delays central nervous system oxygen toxicity seizures in ratsAm. J. Physiol. Regul. Integr. Comp. Physiol.304, R829–R836 [PubMed]
237. Lu W., et al. (2012). Novel role of NOX in supporting aerobic glycolysis in cancer cells with mitochondrial dysfunction and as a potential target for cancer therapyPLoS Biol.10, e1001326. [PMC free article] [PubMed]
238. de Groof A.J., et al. (2009). Increased OXPHOS activity precedes rise in glycolytic rate in H-RasV12/E1A transformed fibroblasts that develop a Warburg phenotypeMol. Cancer8, 54. [PMC free article] [PubMed]
239. Baracca A., et al. (2010) Mitochondrial Complex I decrease is responsible for bioenergetic dysfunction in K-ras transformed cellsBiochim. Biophys. Acta1797, 314–323 [PubMed]
240. Roskelley R.C., et al. (1943). Studies in cancer. VII. Enzyme deficiency in human and experimental cancerJ. Clin. Invest.22, 743–751 [PMC free article][PubMed]
241. Seyfried T.N., et al. (2008). Targeting energy metabolism in brain cancer with calorically restricted ketogenic dietsEpilepsia49 Suppl 8, 114–116 [PubMed]
242. Huysentruyt L.C., et al. (2008). Metastatic cancer cells with macrophage properties: evidence from a new murine tumor modelInt. J. Cancer123, 73–84[PubMed]
243. Poff A.M., et al. (2013). The ketogenic diet and hyperbaric oxygen therapy prolong survival in mice with systemic metastatic cancerPLoS One8, e65522. [PMC free article] [PubMed]

The Impact of Iron and Selenium Deficiencies on Iodine and Thyroid Metabolism

Several minerals and trace elements are essential for normal thyroid hormone metabolism, e.g., iodine, iron, selenium, and zinc. Coexisting deficiencies of these elements can impair thyroid function. Iron deficiency impairs thyroid hormone synthesis by reducing activity of heme-dependent thyroid peroxidase. Iron-deficiency anemia blunts and iron supplementation improves the efficacy of iodine supplementation. Combined selenium and iodine deficiency leads to myxedematous cretinism.

The normal thyroid gland retains high selenium concentrations even under conditions of inadequate selenium supply and expresses many of the known selenocysteine-containing proteins. Among these selenoproteins are the glutathione peroxidase, deiodinase, and thioredoxine reductase families of enzymes. Adequate selenium nutrition supports efficient thyroid hormone synthesis and metabolism and protects the thyroid gland from damage by excessive iodide exposure. In regions of combined severe iodine and selenium deficiency, normalization of iodine supply is mandatory before initiation of selenium supplementation in order to prevent hypothyroidism. Selenium deficiency and disturbed thyroid hormone economy may develop under conditions of special dietary regimens such as long-term total parenteral nutrition, phenylketonuria diet, cystic fibrosis, or may be the result of imbalanced nutrition in children, elderly people, or sick patients.

Cancer Cell ‘Ferment’ Sugar to Speed Their Metabolism and Spread

~ Content Source

Cancer cells are known to be able to speed up their metabolism, reprogramming it so they can proliferate more quickly. Now, researchers have identified one way that tumors alter their metabolism — fermenting rather than burning up glucose for energy, called the Warburg Hypothesis — a finding that may lead to a new way of treating virtually all cancers.

Indeed, the study, “Addiction to Coupling of the Warburg Effect with Glutamine Catabolism in Cancer Cells,” published in Cell Reports, shows that inhibiting one of the enzymes required for this skewed metabolism was sufficient to slow or halt the growth of colon cancer cells.

The researchers also identified, for the first time, how cancer-causing mutations can alter the way cancer cells metabolize specific nutrient sources in order to replicate.

“Every tissue or cell type in the body has different metabolic needs but as cells become cancerous their metabolism shifts in ways that are very different from normal cells,” Joshua Munger, PhD, an associate professor of Biochemistry and Biophysics, said in a press release. “Being able to identify those differences is critical for developing treatment targets.”

Scientists have known for decades that cancer cells take up the glucose in the blood at alarming rates. But these cells addiction to sugar is only one part of the story, said Hucky Land, PhD, the Robert and Dorothy Markin professor and chair of Biomedical Genetics, and director of research at the URMC’s Wilmot Cancer Institute, who closely collaborated with Munger on this project.

While sugar is the primary source of energy and biosynthesis for healthy cells, in cancer cells it is metabolized differently; instead of burning sugar to produce large amounts of energy, cancer cells ferment sugar, to give them a more continual source of energy for fast cell division and proliferation.

Cancer-causing mutations are responsible for this change in these cells’ metabolism, the researchers discovered. And they found that fermented glucose also allows cancer cells to increase their consumption of glutamine, another nutrient source that is abundant in the bloodstream.

“Our paper demonstrates that cancer cells, but not normal cells, depend on this link between sugar fermentation and glutamine consumption,” Land said. “This suggests a novel way that we might be able to intervene with treatment.”

To test their hypothesis, the researchers used colon cancer cell lines resulting from two specific cancer-causing mutations. They found that the glutamine uptake was critical for the cancer cell malignant transformation, and that inhibiting an enzyme involved in glutamine consumption prevented the growth of these cancer cells.

A number of early clinical trials are now testing ways to target cancer cells’ altered metabolism. This research may have found a key mechanism to apply to this concept, but further studies are required.

“Is it possible to apply this to other cancers? That’s our next question,” Munger said. “We’re testing how this could be broadly applied in the clinic.”