Cancer: linking metabolism to genetics

The currently accepted, mainstream theory of cancer

Cancer is taken to be a ‘genetic disease’ at heart. This is because the currently accepted Somatic Mutation Theory (SMT) posits that mutations in the nuclear genome are the fundamental etiological drivers of the disease. These mutation are thought to arise when “an individual mutant clone of cells begins by prospering at the expense of its neighbors through a microevolutionary process of clonal selection. The nuclear genomes of cancer cells are mutated, disorganized and unstable, and outside their nucleus metabolism is abnormal. Under the SMT umbrella, this metabolic abnormality is assumed to be a downstream symptom of the mutated nuclear genome, a hallmark of the disease but not its causal agent.

A much less popular but competing theory of cancer

A competing theory, the Metabolic Theory (MT) of cancer, effectively reverses this arrow of causality. From nuclear mutations causing abnormal metabolism we got to abnormal metabolism causing nuclear mutations. It postulates that faulty oxidative phosphorylation (OxPhos) – the end stage of cellular respiration – is the root cause of cancer. Consequently, the 6 hallmarks of the disease, angiogenesis, evasion of the immune system, evasion of death, evasion of growth suppressors, invasion and metastasis, and finally sustained proliferative signaling, all follow on from this metabolic abnormality. What the latter presents as is the continued expression of glycolysis in the presence of oxygen, also known as the Warburg effect.

Linking abnormal OxPhos to gene regulatory mechanisms

Whether mutations cause cancer or simply emerge in the cancerous cell as a result of defective OxPhos, it remains important to investigate the links between our genetic profile, both in terms of our base DNA code, gene regulatory networks and epigenetic fingerprints. Initially, genetic features of cancer was limited to abnormal karyotypes, like a different number of chromosomes (or aneuploidy), and somatic mutations. With the advent of epigenetics and a deeper understanding of gene regulatory phenomena, we have at least two additional avenues down which we may potentially learn to better profile cancer cells. This is true regardless of which theory of cancer one operates under.

The question I wish to explore here is Which gene regulatory mechanisms are linked to dysfunctional OxPhos in cancer? The relevant laboratory and software techniques are discussed first, followed by the particular mechanisms underlying the disease, hopefully helping to further elucidate the merits and demerits of both theories.

Definitions: genetic vs epigenetic changes

Before delving into data gathering techniques, a clear and parsimonious exploration of the question necessitates defining genetic, epigenetic and broader gene regulatory phenomena.

Genetic changes

Genetic changes or mutations refer to alterations in base genetic code, whether that be different nucleotides, their order in a sequence, the orientation of a sequence, the translocation of a sequence or the number of times a sequence repeats.

Epigenetic changes

As for epigenetics, in 1952 Waddington used the term quite broadly “to refer in general to what we now know to be changing patterns of gene expression that underlie development and that are oſten triggered by signals sent from other cells. According to the 2014 6th edition of Molecular Biology of the Cell, the covalent modification of histones in nucleosomes falls under an epigenetic “form of inheritance that is superimposed on the genetic inheritance based on DNA. Mark Ptashne argues that the covalent modifications of histones is not an epigenetic mechanism given that “the enzymes that impose such modifications lack requisite specificity; the modified states are not self-perpetuating; and the roles played by the modifications remain for the most part obscure. Experimentation tells us that “histone modifications are not maintained as cells divide. These histone modifying enzymes are part of a response to epigenetic regulation and not a cause thereof. According Ptashne’s criteria, histone modifications fall under the more general category of gene regulation, leading to a more narrow definition of epigenetics. This definition includes the phenomena of memory (“continual activities of the specific regulators to maintain that state of expression”) and specificity (“activating one gene or set of genes and not another”). One epigenetic mechanism may employ a positive feedback loop (such as the auto-activation of the cl gene) and another, a negative feedback loop (like the auto-repression of the cl gene). Examples of epigenetic in nature include viral immunity passed down to the next generation or transient inflammatory stimuli causing chronic inflammation via feedback-loops mediated by sequence-specific microRNAs (or other regulatory proteins).

Gene regulatory changes

Gene regulatory changes result from the activity of gene regulatory networks governing the gene expression levels as seen in mRNA and proteins. These networks respond to environmental cues that could be anything from food and light to psychosocial events and drugs.

Detecting cancer

Now that we’ve got our definitions lets talk about about techniques to detect cancer. An early cancer diagnosis, or better yet anticipating the transition of a benign tumor to a malignant one, is of utmost importance in reducing cancer associated deaths. For this reason, assays detecting DNA methylation patterns regulating gene expression and activities of their upstream enzymatic effectors have become of great interest. They are the subject of Shinjo and Kondo’s 2015 paper upon which most of the following analysis is based. A point of note, unlike Mark Ptashne these authors consider DNA methylation to be an epigenetic phenomenon.

DNA methylation

DNA methylation pattern assays first require differentiating methylated DNA from unmethylated DNA, which can be done physically, using a methyl-binding column, or by inducing sequence changes through bisulfite treatment, for instance. Other techniques based on sequence changes include the use of restriction enzymes of varying sensitivity to DNA methylation sites, as well as methylated DNA enrichment with anti-cytosine or methyl-binding anti-bodies. DNA methylation appears to be stable in cancers and can thus be relied upon to establish methylation patters related to gene expression.

DNA methylation pattern assays can be conducted on samples of cell-free DNA (cfDNA) found in blood, stool, urine, tissue and other bodily fluids. Although cancer cells resist apoptosis, the disease process results in higher overall rates of apoptosis and tissue necrosis. This leads to increased levels of cfDNA circulating in the blood which can be indicative of a loss of heterozygosity and the presence of mutations. For example, blood samples of cfDNA have shown RASSF1A DNA demethylation associated with increased sensitivity to cancer treatment. The converse is also true, decreased sensitivity to treatment is associated with increased methylation.

Methylation tests on fecal, urine and sputum samples each use different biomarkers and do not all perform equally well. For stool samples, Cologuard™ uses NDRG4, BMP3 and KRAS mutation methylation biomarkers showing 92.3% sensitivity and 86.6% specificity. For urine samples, the GSTP1 methylation biomarker shows 88% sensitivity and 60% specificity. For sputum samples, the Epi prolung test uses the SHOX2 methylation biomarker showing 60% sensitivity and 90% specificity.

Gene regulatory imprints

Cancer treatments directly targeting gene regulatory mechanisms broadly cover 3 areas; histone modifications, DNA methylation associated pathways and readers of gene regulation.

Regarding the first area, there are 18 known histone deacetylase inhibitors (HDIs) divided into classes 1 through 4 with which to work with. They stop the deacetylation of lysine (K) and are associated with the restoration of silenced genes, the induction of growth arrest, the interruption of differentiation and the prompting of tumor cell apoptosis. HDI based cancer treatments are still quite new. Currently there are only 3 FDA approved HDIs in the United States of America: Vorinostate, Romidespine and Belinostat.

Regarding the second area, DNA methyltransferase inhibitors (DNMT1 inhibitors) are equally novel and only one has been approved for myelodysplastic syndromes (MDS) therapy – bone marrow cancers. The mechanism of action of another such molecule is illustrated in Figure 1 below, taken from Shinjo and Kondo’s paper. IDH1 usually catalyzes the oxidatively decarboxylation of isocitrate to α-ketoglutarate (α-KG) which has for effect of replenishing the TCA cycle. IDH-1 mutants divert α-KG towards the catalysis of oncometabolite 2-HG. As the latter accumulates it inhibits α-KG-dependent dioxygenases, histone demethylases and TET family proteins. IDH-1 inhibitors therefore interfere with 2-HG accumulation.

The third area is concerned with cancer treatments exploiting molecules capable of interfering with gene regulatory ‘reading’. Bromo and Extra Terminal proteins (BETs) read the code of histone modification, particularly acetylated histones. BET inhibitors bind particular residues of histone modification, effectively out-competing bromodomain-competing proteins (BRDs) of the BET family. For example, fusion oncoprotein BRD4 is displaced from chromatin by BET inhibitor I-BET151, thereby decreasing the oncogenic transcription potential of BCL2, C-MYC (cytoplasmic myelocytomatosis oncogene) and CDK6.

IDH1-mutant

Figure 1. IDH1-mutant

Chromatin Immunoprecipitation Sequencing (ChIP-seq) assays are used to map the genome-wide binding of gene regulatory proteins. For example, this technique reveals the different binding patterns of the Sirtuin1 protein (Silent Information Regulator 1) in the nucleus accumbens of rats before and after the administration of cocaine over 7 days. ChIP-seq in conjunction with RNA and immunoblotting assays can link posttranslational modifications made to newly synthesized histones and the subsequent patterns of gene expression found at specific genomic loci affected by this chromatin assembly. Yang et al. applied this combination of techniques to show ”how one modification that occurs on newly synthesized histone H3, acetylation of K56, influences gene expression at epigenetically regulated loci in Saccharomyces cerevisiae. Essential information about cellular behavior is obtained with ChIP-seq. Other programs are then used to map relationships between these patterns of immuno precipitated chromatin.For example, RNA-seq visualization tool Cascade does just that for copy number variants (CNVs) and the MAP2K4 pathway of ovarian cancers, visible in Figure 2 below. It can then form the basis of further experimentation involving the in vivo alteration of chromatin patterns associated with malignancy, in the hopes of impeding tumor progression.

RNA-Seq Cascade

Figure 2. RNA-seq visualization tool Cascade for ovarian cancer CNVs & MAP2K4 pathway

Sirtuins

The first mechanism explored here involves sirtuin proteins 1 to 7. According to Mark Ptashne’s their criteria fall under the category of gene regulation. Amongst the 7 sirtuin proteins, those of particular note are sirtuins 3, 4, 6 (and 7 to a lesser degree) because of their pronounced ability to suppress the Warburg effect as a function of their gene regulatory capacities. Sirtuins are NAD+-dependent class III histone deacetylases (HDACs) catalyzing ADP-ribosylation reactions which can loosen chromatin. This effectively makes DNA more or less accessible, as well as facilitate or hinder the activities of histone effector proteins. These sirtuins are most directly involved in cancer via their action on the Warburg effect. This is because their activities depend on the NAD+/NADH ratio, a general indicator of metabolism, and more specifically cellular redox state and energy status. NAD (the reduced form of NAD+) and NADH are physiological sirtuin inhibitors whilst NAD+ and resveratrol are sirtuin-activating compounds (STACs). The following discussion of sirtuins 1 to 7 is based on Kleszcz et al.’s 2015 paper as well as Douglas Wallace’s 2014 NIH presentation “A Mitochondrial Etiology of Metabolic and Degenerative Diseases, Cancer and Aging.

Sirt6

SIRT6 is found only in the nucleus and is particularly interesting amongst sirtuins, in large part because of its co-repression of transcription factor MYC (myelocytomatosis oncogene). This repression is associated with both the inhibitions of glycolysis and ribosomal activity. In cancer cells, the nucleoli containing ribosomes have the striking morphological feature of being engorged due to increased biosynthetic demand. Non-transformed cells lacking SIRT6 become tumors when glycolysis is intact but fail to do so when it is abolished, a pattern which strongly argues that the Warburg effect drives tumorigenesis. Like for most sirtuins, SIRT6’s tumor-suppressing effect depends on the cell type and disease stage. Nevertheless, SIRT6 over-expression affects chromatin structure such that cancer cells will apoptose but normal cells won’t. One way this is thought to occur is through the H3K9 deacetylation of the Hypoxia-Inducible Factor-1α (HIF-1α) gene promoter. When HIF-1α is stable in cancer cells pseudorespiration is ongoing. This occurs when ATP is produced through mitochondrial fermentation involving substrate-level phosphorylation. The cancer cell is less sensitive to apoptotic signals when the HIF-1α complex is stabilized. Fortunately, SIRT6 over-expression can destabilize it. Furthermore, mouse models of liver cancer have shown that the ‘genome guardian tumor suppressor p53 can induce SIRT6 expression so as to inhibit hepatic gluconeogenesis. This underscores a mechanism for p53 in the maintenance of glucose homeostasis.

Sirt3

Other sirtuins affect HIF-1α stability such as SIRT3 which is found both within the mitochondrial matrix and nucleus under normal growth conditions. Downregulation of its activity effectively reprograms metabolism such that an increased level of reactive oxygen species (ROSs) signals HIF-1α stabilization. This in turn upregulates glycolytic enzymes. SIRT3 impedes aerobic glycolysis and thus the production of lactate through an additional pathway involving pyruvate dehydrogenase E1α (PDHA1). The deacetylation of lysine 321 on PDHA1 will increase its activity, diverting and increasing glucose utilization through the Citric Acid Cycle (TCA). Like SIRT6, SIRT3 appears to suppress or promote tumorigenesis depending on the cell type as well as the confluence of stress and apoptotic stimuli. Inflammation is one such stressor typically present in tumors and can be attenuated by fasting in human subjects. SIRT3 is NAD-dependent (or ‘nutrient sensing’) and when fasting, its activity diminishes. This has for consequence of blunting the response of the NLRP3 (NOD-Like Receptor family Protein 3) inflammasome.

Sirt4

Metabolism is inextricably interwoven with biosynthetic demand given their functional interdependency. This is exemplified in the interaction of the mammalian target of rapamycin complex 1 (mTORC1) and SIRT4. The latter is only located in the mitochondrial matrix and is involved in balancing the oxidation and synthesis of fatty acids. mTORC1 however is a general growth promoter. Its activation will upregulate glutamate dehydrogenase (GDH) via SIRT4 repression and in so doing enable cancer progression. This enhanced glutamine metabolism both replenishes TCA cycle intermediates required for biosynthesis as well as serve as fermentable substrate contributing to filling the energy gap resulting from the cancer cell’s defective oxidative phosphorylation. Interestingly, sufficiently extensive DNA damage can induce SIRT4 expression and shut down glutamine metabolism, a requisite process for cellular repair. This sirtuin appears to suppress the formation of tumors by inhibiting excessive glutamine metabolism and maintaining genomic stability.

Sirt1

SIRT1 is the most highly conserved sirtuin in mammals and is found both in the nucleus and cytoplasm. It modulates the metabolism of lipids and glucose in the liver, insulin secretion in the pancreas and engenders fat mobilization in adipose tissue. All of these features together point to SIRT1 as a key metabolic sensor. SIRT1 negatively regulates phosphoglycerate mutase 1 (PGAM1) which is upregulated in many cancers and occupies an important point in the glycolytic pathway where many glycolytic intermediates upstream of it serve as biosynthetic precursors. SIRT1-mediated deacetylation of PGAM1 will thus reduce glycolysis, flux down the pentose phosphate pathway (PPP). The levels of the aforementioned biosynthetic intermediates will thus be lower too. This all serves to inhibit tumor growth given the tumor’s reliance on these factors. Like other sirtuins, SIRT1 also demonstrates tumor suppressive action mediated by HIF-1α deacetylation. This sirtuin, like others in its family, has its tumor suppressing capacities contrasted by context-dependent tumor promoting ones. Through its deacetylating activities it can promote tumorigenesis by inhibiting p53, p73 and HIC1 (Hypermethylated In Cancer 1). Given how common it is for genes and gene regulating molecules to both suppress and promote tumorigenesis, they should not be viewed as solely doing one or the other, but rather as sitting at the intersections in cell pathways leading towards or away from growth. The same analogy can be applied to the gene themselves, implying that terming them ‘oncogenic’ may have been premature and now thoroughly confusing.

Sirt2

Along with SIRT1, SIRT2 is also located in both the cytoplasm and mitochondria. It is yet another sirtuin that, when overexpressed, can destabilize HIF-1α under hypoxic conditions. Experiments with cells that do not express SIRT2 corroborate this fact given that they fail to affect HIF-1α levels. SIRT2 positively regulates PGAM as opposed to SIRT1’s negative regulation. SIRT2 deacetylates K100 (lysine100) on PGAM, thereby upregulating its activity and thus glycolysis. This sirtuin is mainly found in the cytoplasm and shuttles back and forth to the nucleus. The significance of sirtuin localization is not yet known. However it is interesting to consider the possibility that the direction in which they carry out their activities (either from nucleus to cytoplasm or cytoplasm to nucleus) might explain their context-dependent pro- or anti-tumorigenic effects. During the study of breast tumors, SIRT2 was shown to have both tumor suppressive and promoting capabilities. Here however, tumor grade appeared decisive rather than cell type.

Sirt5 and sirt7

Both SIRT5 and SIRT7 are lesser studied sirtuins. The former is only found in mitochondria where it acts as a global regulator of succinylation. Through its dessucinylation of superoxide dismutase (SOD1) it can lower the level of ROS produced by cancer cells. These ROS are thought to result form increased glycolysis, mitochondrial fermentation in defective mitochondria with poor oxidative phosphorylation. Found only in the nucleus, lysine deacetylase SIRT7 targets H3K18. The latter is found in the vicinity of multiple gene promoters involved in tumor suppression. Similar to the SIRT6, it attenuates engorged nucleoli containing ribosomes in a MYC-dependent manner by deacetylating MYC transcript targets of ribosomal proteins. SIRT7’s maintenance of H3K18 acetylation patterns appears important in keeping this morphological cancer phenotype. Enhanced rRNA production is such a conspicuous feature of cancer that it has been proposed as the 7th hallmark.

Returning to the idea of sirtuin localization being able to potentially explain opposing actions of sirtuins, SIRT7 is present and highly active in the ribosome-containing engorged nucleoli. This suggests its activity may promote rRNA synthesis and thus ribosome biogenesis. Finding a compound capable of inhibiting SIRT7 compound is of great interest. Nevertheless, STACS may be generally preferable to to sirtuin inhibitors for 3 reasons. Activators need not be as potent as inhibitors due to downstream signal amplification, they are more selective due to their ability to bind non-catalytic sites of target proteins, and their mimicry of natural activators is liable to induce fewer side-effects. Unfortunately, Kleszcz et al. make clear that until now (2015) “it has been a conundrum that such a diverse set of small molecules can activate SIRT1, but so far no activators of SIRT2-7 have been described”.

The sooner we learn to exploit endogenous sirtuin activation, improvements in cancer prevention as wellaas palliative and adjunctive cancer care may be attainable. Much of this may stem from appreciating  how dietary choices and sleep patterns, for instance, affect the expression of sirtuins. Diet is always front and center as a lifestyle factor and interestingly, multiple long-chain fatty acids have been shown to induce a 35-fold increase in SIRT6 activity at physiological concentrations. Furthermore, mice given nicotinamide riboside benefitted from increased insulin sensitivity, an effect that may stem from nicotinamide riboside’s ability to increase NAD+ levels, an endogenous sirtuin activator. This effect correlated with SIRT1 and SIRT3 upregulation.

Talking about ‘oncogenic activity’ makes more sense than talking about ‘oncogenes’

When cancer is viewed through the genetic paradigm, a parallel between the inconsistent tumorigenic effects of sirtuins and those of oncogenes emerges. A particular sirtuin might flip from being anti-tumorigenic to tumorigenic depending on the tissue type or grade of cancer. An oncogene can be both pro-tumorigenic and suppress tumors without a satisfying explanation as to why. Supporting this latter point is Soto and Sonneschein’s observation that “a mutation that should have produced uncontrolled cell proliferation resulted in cell death or arrest of cell proliferation. The significance of this parallel is that the opposing actions of both (onco)genes and sirtuins in the genesis and progression of cancer highlights cracks in the framework of SMT. For instance, genetic analyses of BRCA variants only explain about 10% of breast cancer susceptibility and amount to our best current predictions as of 2016. Fortunately, BRCA1’s known interaction with enzyme acetyl coenzyme A carboxylase alpha (ACCA) provides a clearer path for exploiting a metabolic vulnerability than purely genetic analyses of BRCA1 do.

The oncogenic paradox

SMT suffers from poor predictive power in terms of cancer occurrence and treatment outcomes. This led some to wonder how such a specific process (cancer) can stem from a number of unspecific mutation-inducing events (radiation, viruses, inflammation etc.). Albert Szent-Györgi termed the latter phenomenon the “oncogenic paradox. Fortunately, this paradox and oncogenic inconsistency can be stress-tested by exploring a prediction of SMT:

transferring transformed (cancerous) nuclei into non-transformed (normal) cytoplasm will induce tumorigenesis in the latter

Such nuclear-cytoplasmic transfer experiments have been carried out. They show that nuclei from cancerous cells transferred into normal ones do not reliably transform the cell. The converse of that experiment should yield similar results, whereby cells with tumor nuclei should revert back to a normal non-cancerous state when cytoplasmic contents of normal cells, specifically their respiration competent mitochondria, are transferred to them. In 1988 Israel and Schaeffer showed exactly that. He used cytoplasmic hybrid, also known as cybrids, from preparations of rat liver epithelial cells. Both kind of transfer experiments are depicted in Figure 3 below.

transfer experiments

Figure 3. Nuclear/cytoplasm transfer experiments

Kulesa et al. demonstrated “the ability of adult human metastatic melanoma cells to respond to chick embryonic environmental cues, a subset of which may undergo a reprogramming of their metastatic phenotype. Thomas Seyfried of Boston College summarizes results from multiple nuclear-cytoplasmic experiments, saying “nuclei from cancer cells can be reprogrammed to form normal tissues when transplanted into normal cytoplasm despite the continued presence of the tumor-associated genomic defects in the cells of the derived tissues. This suggests that something in the cytoplasm, rather than something in the nucleus is driving tumorigenesis. It is this in addition to Warburg’s nearly century old observations of cancer cells displaying some degree of defective OxPhos, that begs the following question

how do gene regulatory elements link defective mitochondria and impaired respiration to highly unstable, disorganized and mutated nuclear genome?

Impaired respiration

ROS

One manifestation of impaired respiration is excessive reactive oxygen species (ROSs). The electron transport chain (ETC) in the inner mitochondrial membrane (IMM) uses electron carrying molecules to synthesize ATP and some of these electrons also (fully) reduce water. This imperfect process also partially reduces water, whereby electrons become unpaired in oxygen’s outer orbital and form multiple ROS compounds, such superoxide anions, hydrogen peroxides and hydroxyl radicals. Hydroxides (OH) for example may ‘steal’ electrons from membrane lipids and thus initiate a chain-reaction of neighboring lipids stealing electrons from one another. This changes the properties of membranes in an uncontrolled manner. ROS are physiologically unavoidable and participate in cell signaling. Yet because they are inherently damaging to cellular components they must be managed to avoid disease and accelerated ageing. Additional manifestations of impaired respiration include abnormalities in mtDNA, the proton motive gradient (ΔΨm) and the TCA cycle.

The Retrograde Response

Yeast and animal cells have ‘surveillance systems’ to react to these signs of impaired respiration. One of these signs is called the retrograde (RTG) response.  The RTP “responds to mitochondrial dysfunction by adapting cell metabolism to the loss of tricarboxylic acid (TCA) cycle activity. Thomas Seyfried correctly categorizes the RTG response as an epigenetic mechanism because it fulfills the criteria of specificity and memory: the basic helix-loop-helix-leucine zippers Rtg1/Rtg2 transcriptional factors complex demonstrate specificity when binding to the DNA R Box binding site for the transcription of a particular set of genes, as well as memory given that yeast maintains  those changes during cellular division when extending their lifespan. The RTG response is a signaling pathway relaying information about the organelle’s status to the nucleus. It’s response determines whether or not the major cell-quality control mechanisms of mitophagy and autophagy are induced.

The RTG response is a central mechanism underlying the MT of cancer because it links the hypothesized metabolic origin to the characteristic abnormally unstable and mutated nuclear genome. Essentially, the RTG response upregulates non-oxidative metabolic networks (or oncogenes from the gene-centric perspective) which shifts the cell’s energy yielding pathways to a predominant mix of glycolysis and glutamine fermentation so as to maintain ATP homeostasis (stable ΔG’ATP) despite insufficient respiration. Figure 4 below is Thomas Seyfried’s illustration (adapted from Michal Jazwinski’s work in yeast) of how the mammalian RTG response occurs.

RTG Response

Figure 4. RTG Response

Normally respiring cells have a dormant RTG response located in the cytoplasm. The RTG is actually a complex composed of Rtg1 dimerized to a strongly phosphorylated Rtg3. When a cell experiences defective or insufficient respiration, cytoplasmic Rtg2 partially dephosphorylates the Rtg1/Rtg3 complex, prompting both proteins to enter the nucleus so that Rtg3 may bind the R Box, followed by Rtg1 re-engaging Rtg3, effectively awakening the RTG response. This leads to the targeted transcription of multiple metabolic and antiapoptotic genes including CHOP, MYC, TOR, NF-𝜅B, Ras and CREB. This non-exhaustive set of genes has multiple associations with  cancer initiation, maintenance and metastasis. For one, MYC has been associated with increased levels of ROS and the inhibition of tumor suppressor p53. An example pertaining to metastatic behavior links the RTG response to increased levels of Matrix Metalloproteinase 2 (MMP2), as seen in activated macrophages hybridizing to neoplastic epithelia.

It is important to note that RTG response mediated destabilization of the nuclear genome, as well as the induction of aneuploidy and somatic mutations, all strong favor  the MT rather than SMT theory of cancer. Furthermore, the RTG response is also associated with multi-drug cancer resistant phenotypes, increased cytoplasmic calcium, increased ROS, iron-sulfur complex abnormalities, decreased mitochondrial ATP production as well as a lowered ΔΨm. Although there is no direct equivalent in higher eukaryotes of the yeast Rtg2 mitochondrial sensor transducing mitochondrial signals, authors Srinivasan et al. explain that “strong homologies between inhibitors and pathways of both [RTG genes and NF-κB] leads one to believe that the retrograde response is a potential predecessor of the now-central stress-regulator, NF-κB. In that same paper by Srinivasan et al., reproduced here in Figure 5, one can see the nearly identical RTG and NF-κB activity levels as they relate to 6 major metrics of cellular behavior.

RTG NF-kB

Figure 5. RTG vs NF-kB

Jazwinski also comments on the many similarities between yeast and human RTG responses, adding that “mammalian cells not only display many of the molecular features of yeast retrograde signaling, but they also present the cellular outcome of extended life span that characterizes the retrograde response. Lifespan extension mechanisms are inextricably tied to tumorigenic control ones. In figure 6 below Klement and Champ illustrate the mechanistic overlap between ketogenic diets (KDs), which can suppress tumors, and calorie restriction (CR), which has been shown to extend lifespan in multiple animal models.

cr kd

Figure 6. CR & a KD target the same molecular pathways

Figure 7 below illustrates the integrated circuits of a cell. What is interesting is that cellular circuitry is obviously drawn through the lens of the SMT. Pathways (arrows) leaving mitochondria towards ‘DNA Damage Sensors’ are nowhere to be seen. There seems to be little acknowledgement of how defective OxPhos leads to direct or indirect upregulation of glycolytic and fermentative networks. Rather, this shift in energy metabolism is deemed to originate from nuclear mutations.

Re-imagining Figure 7 through the MT lens, the RTG response would constitute a ‘Mitochondrial Damage Sensor’ with an arrow leading to NF-κB and integrating back into the web of arrows already present. Furthermore, there would be an increase in the proportion of arrows going from the mitochondria to the nuclear genome (and back), highlighting the metabolic origin as well as the bi-directional cross-talk enabling nuclear genomes to upregulate aforementioned metabolic networks. This is not a baseless hypothetical. For instance, the classic view of p53 as solely regulating tumorigenesis (and thus genomic stability) by inducing mitochondrial apoptosis or via transcriptional factor response elements must be updated, because it is now known to also regulate transcriptional target SCO2 (Synthesis of Cytochrome c Oxidase 2) through which mitochondrial energy production is influenced. Genomic stability, by way of p53, is thus highly dependent upon OxPhos status. Integrating this into Figure 7 once again, this would look like an arrow leaving the mitochondria to SCO2 and then on to p53.

cellular circuitry

Figure 7. Cellular Circuitry (as of 2000)

Returning to Jazwinski’s paper on the RTG response, another gene regulatory (not epigenetic) mechanism lending support to MT of cancer can be inferred from exploring how ceramide synthase activity found in the endoplasmic reticulum (ER) relates to mitochondrial dysfunction. The hydrolysis of sphingomyelin by sphingomyelinase (Smase) is a catalyzing reaction generating ceramide, a structural and signaling cellular component of mammalian cells. Ceramide appears to be stimulated by a variety of stressors such as TNF-α/matrix metalloproteinases/ROSs, cannabinoids and ionizing radiation. Ceramide is linked to retrograde signaling by way of it prompting Isc1 (Inositol phosphosphingolipase C), leading to autophagy. Jazwinski explains that “sphingosine and ceramide are precursors of complex sphingolipids [which] suggests that the balance in sphingolipid biosynthetic activity can tip the scale in autophagy from quality control to wholesale degradation and remodeling”.

Cannabinoids

In fact, phytocannabinoid THC ((−)-trans-Δ9-tetrahydrocannabinol) was shown to induce apoptosis in vitro. Authors explain this, saying the “first step in the apoptotic pathway was ceramide production, and that this led to loss of membrane potential, and caspase activation, respectively. Lesser known phytocannabinoid CBD (cannabidiol) was shown by McAllister et al. to reduce the aggressiveness of breast cancer cell proliferation, invasion, and metastasis by affecting mitochondrial ROS production in vitro. This CBD-mediated effect appears to occur down 2 pathways: ERK (extracellular signal-regulated kinase) activation and increasing ROSs further. Both of these pathways can decrease Id-1 (Inhibitor of DNA Binding 1) gene expression, leading to reduced cell proliferation and invasion. The way in which these cannabinoids seem to work adds to the evidence supporting a theory of cancer based in metabolism. One way these cannabinoids exert effects on metabolism involves ceramide, as “ceramide generated upon CB1 cannabinoid receptor activation may enhance ketone body production by [rat] astrocytes independently of MAPK.

Cannabinoids to ketone bodies

Interestingly, this line of investigation leads to promising in vitro and in vivo experiments highlighting the emerging role of ketone bodies as alluring metabolic fuels. They appear capable of simultaneously stressing cancer cells and supporting normal ones. The link between the MT of cancer and gene regulatory effects of ketones are apparent when considering some of the properties of endogenously produced ones, such as d-β-hydroxybutyrate (βOHB) (chemically not a ketone but a carboxylic acid). βOHB specifically inhibits class I HDACs. This βOHB-induced HDAC action “correlated with global changes in transcription, including that of the genes encoding oxidative stress resistance factors FOXO3A and MT2 […] consistent with increased FOXO3A and MT2 activity, treatment of mice with βOHB conferred substantial protection against oxidative stress. The shared mechanisms via which both cannabinoids and ketones place metabolic stress on cancer cells whilst protecting normal ones strongly support a MT of cancer.

Conclusion

In conclusion, it is worth pausing for a moment and reflecting on the fact that ketones and cannabinoids, 2 highly non-toxic compounds endogenous to humans, have been unfairly maligned. The former because of its conflation with diabetic ketoacidosis and the latter because of harms associated with drug abuse. Yet, both are now resurfacing in medical research as highly promising compounds, especially for treating the emperor of all maladies, cancer.

It is also worth pondering how the range of new cancer therapies like HBOT (hyperbaric oxygen therapy), ketogenic diets and deuterium (2H) depleted water (DDW) share overlapping mechanisms directly impacting metabolism by influencing mitochondrial status – especially OxPhos activity. The latter therapy, DDW, delayed prostate cancer progression in a 4-month phase 2 clinical trial that was double-blind and randomized. The mechanism of action of DDW as explained by Boros et al. de facto serves as further evidence of a metabolic origin of cancer:

The excessive appearance, i.e. accumulation of ‘‘metabolically dry” oncometabolites [such as 2-HG] is consistent with our hypothesis that cancer is formed on the basis of mitochondrial defects that lack hydration of TCA cycle intermediates with low deuterium matrix water as the result of such defects. Such claim is supported by the fact that restoring hydratase function of mitochondria reverses tumor cells back to their genetically stable non-proliferating normal phenotype [37] with normal matrix water content, composition and morphology

It is time for SMT-centric mainstream cancer researchers to reconsider the fundamental mechanisms of action of the few marginally successful gene-based therapies on the market. Rather than viewing genetic, epigenetic and gene regulatory phenomena as epicentres of action of ‘gene-based therapies’, these might actually be downstream of metabolic disturbances. This is a major distinction in how one thinks cancer is caused.

 

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Thoughts on Cancer

Edit (26/01/2016)

The problem of cancer is not to explain life, but to discover the differences between cancer cells and normal growing cells. Fortunately this can be done without knowing what life really is. Imagine two engines, the one being driven by complete and the other by incomplete combustion of coal. A man who knows nothing at all about engines, their structure, and their purpose, may discover the difference. He may, for example, smell it.” – Otto Warburg 1956

If one could only learn about human health studying a single disease, I would pick cancer hands down. Its study boils down to askying why and how some cells either live or die. The distilled question is simple, yet cancer is everything but. It forces us to confront its behavior which is easily anthropomorphized: why are these cancer cells malcontent with simply being alive? What is this insatiable need for invading other body parts? Stranger yet, cancer is synonymous with death even though it is part and parcel with biological life – even trees get cancer or at least they also manifest uncontrolled cell growth. Stringent definitions are hard and tedious to establish but they really matter, so for the sake of clarity lets use the Hallmarks of Cancer. It embodies the 6 behavioral traits characterizing the disease:

  • Evading death
  • Ignoring anti-growth signals
  • Self-directing growth
  • Literally being blood-thirsty
  • Invading other tissues
  • Unlimited replication

The currently accepted Somatic Mutation Theory of cancer (SMT) is based in genetics. Basically, it asserts that a single cell suffering 1 or more random mutations conferring it with a growth advantage deleterious to its host, can cause cancer. In other words “it is a disease in which an individual mutant clone of cells begins by prospering at the expense of its neighbors” (Molecular Biology of The Cell, 6th Edition, page 1091). Progress towards cures for this still enigmatic disease has been thoroughly underwhelming. In my view, this is mostly because mainstream cancer researchers place too much confidence in SMT. To be fair, cancer cells are 1 big tangle of mutations. But they are not just that. They are also deformed (abnormal morphology). Maybe most importantly, how they make their energy changes. More specifically, their respiration is damaged. Or maybe not – and this is where the bone of contention lies. Some SMT proponents will argue that respiration is not actually broken, that it is just not used as much nor necessarily for the same purpose. Others, that it does not matter either way. The Metabolic Theory of cancer (MT) argues that the functional state of respiration in a cell really matters because broken respiration can cause cancer. The mutations seen in cancers thus result from, rather than cause, damaged respiration. MT is thus based in metabolism rather than genetics. MT proponents say that all cancer cells are characterized by faulty energy production systems. Theys can no longer produce their share of energy (ATP) by respiring and that respiratory function is substantially decoupled from ATP production. By analogy, the cell is stomping on both the accelerator and clutch simultaneously. This is not good for cars or cells. MT argues that such respiratory dysfunction instantiates changes (many of which are genetic) leading to the 6 behavioral traits somehow exhibited by the disease.

Mainstream research has primarily dimissed MT because of 2 observations. 1) A normal cell can be reliably turned cancerous upon suffering certain mutations. This is undeniable. Consequently MT proponents argue that such mutations leads to cancer to the extent that they interfere with normal respiration. 2) Not all cancer cells have a broken respiration system. This is disputed. MT proponents say respiration only appears functional because the cell is in fact ‘pseudo-respiring’. Pseudo-respiration is the generation ATP using the mitochondria’s respiratory apparatus for fermentation, but without consuming oxygen. Mitochondrial fermenatation involves a process called substrate-level phosphorylation.

Given that the first observation supporting SMT over MT suffers from a pesky alternative causal explanation and the accuracy of the second one is disputed, a good clarifying question to pose at this is point is whether it is easier to identify a cancer cell based on its profile of mutations or on the integrity of its respiratory apparatus? I would venture the latter. Consider the thousands of mutated genes strongly associated with cancer (oncogenes) that, when woven together into clinical interventions duly fail to save lives by and large. At this juncture it would be sound to question the entire conceptual premise upon which these interventions were conceived. Instead we do what so many health gurus excel at: polishing turds. We dress up our failure as success and give it a sexy name, ’personalized cancer genomics’. Tilt your head to the left and it is the most exciting, cutting-edge approach that is truly tailored to the special snow-flakes that we all are. Tilt your head to the right and it is an implicit admission that our interventions do not work to any significant extent  on a population level because the SMT underpinning them is plain wrong. Similarly, the notion that cancer is not just 1 disease but many different ones may stem from the same reluctance of recognizing failure. See the fascinating success story of treating Chronic Myeloid Leukemia (CML) with Imatinib (Gleevec). It is all the more interesting given how plausible MT-derived alternative explanations are.

There are many finer theoretical and experimental points that can and should be debated. However, the final point I wish to make is somewhat different. Consider the phenomenon of Epithelial to Mesenchymal Transition (EMT) which proposes a mechanism for metastases within the SMT framework: clonal selection (natural selection) acts upon a series of genomic alterations (mutations) such that a cell acquires invasive (metastatic) behavior. Simple, right? Not quite. Especially not when considering what metastases actually involve. Thomas Seyfried explains this best (bold highlights & numbering are my additions):

“It is difficult to understand how a collection of gene mutations, many of which are random, could produce cells with the capacity to [1] detach from the primary tumor, [2] intravasate into the circulation and lymphatic systems, [3] evade immune attack, [4] extravasate at distant capillary beds, and [5] recapitulate epithelial characteristics following invasion and proliferation in distant organs. This would be quite a feat for a cell with a disorganized genome.” (Metabolic Theory of Cancer, Chapter 13.2.1)

Yes, cancer cells are very clever but their genomes are also very messy. They are successful but not happy. Ultimately the ‘mutations all the way down’ explanation for their malicious behavior is unsatisfying. A better although incomplete explanation is tentatively available: damaged respiration usually forces a cell to (1) repair itself or (2) commit suicide. Things go awry when it ignores options 1 and 2. It is in the adaptation to (3) staying alive without proper repairs that cancer emerges. Adapting to alternative methods of energy production due to damaged respiration forces a cell to survive through different means. These different surival strategies call for a lot of glucose, glutamine, always more vasculature and tissues capable of sustaining the engendered momentum. Does MT do a better job of explaining the seemingly calculated behavior of metastases? Somewhat. The ‘energy seeking tumor’ explanation is more plausible in my mind than the one of ‘random mutations conferring super-powers’.

Regardless, cancer is a bitch.

Rebuttal of 14 claims about metabolism, genetics, paleoanthropology & stable isotope analyses in Hardy et al.’s 2015 paper “The Importance of Dietary Carbohydrate in Human Evolution”

Abstract

The evolutionary selective pressures which drove human encephalization are passionately debated, largely because the brain’s function accounts for much of our ill-defined and ever-changing ‘human uniqueness’. Apportioning individual contributions from the multitude of factors ranging from climate change to food and socialization dynamics requires a truly multidisplinary approach encompassing evolutionary biology, genetics, medicine, archeology, chemistry, physics, climatology and many more scientific fields. It is with this wider perspective that evidence for how food contributed to human encephalization is assessed. Clues from human metabolism, anatomy and food web positioning in addition to stable isotope analyses do not generally support the hypothesis that cooked starches were a major driver of human encephalization. Land and marine life as wells as birds and insects seem to have contributed substantially more to it. 11 points on metabolism, 1 on genetics, 1 on paleoanthropology and 1 on stable isotope analyses are individually rebutted.

In their paper, The importance of dietary carbohydrate in human evolution, Hardy, Brand-Miller, Brown, Thomas and Copeland argue for the importance of dietary carbohydrate (mainly in the form of cooked starches) in human evolution and particularly encephalization. One way they do this is by drawing an association between the supposed advent of controlled fire use (cooking) by hominims with increases in AMY1 copy numbers. Neither the timeline for the emergence of cooking or the AMY1 copy number increase are supported by their citations or by more recent evidence discrediting this purported association. Much of their argument is thus based on genetics, paleoanthropology and both general and specific claims of human metabolism as well as stable isotope anlayses, all of which can be individually rebutted.

Stable istope analysis

Hardy et al. severely misquote a 2009 paper by Richards and Trinkauss – in which stable isotope analyses of Oase 1 humans and Neanderthals were performed – because it is used to support the notion that human diets likely included substantial amounts of starch given the variations in  δ15N and δ13C ratios.

[1]“a wider range of isotopic values have been observed in contemporary Middle Pleistocene H. sapiens (Richards and Trinkaus 2009), indicating that considerable differences in the levels of starch consumption existed between these two species”

The 2009 paper by Richards & Trinkauss actually found that “early modern humans (~40,000 to ~27,000 cal BP) exhibited a wider range of isotopic values, and a number of individuals had evidence for the consumption of aquatic (marine and freshwater) resources […] The other early modern humans all have δ13C values < –18.5‰ (see Fig. 1 and Table S2), which indicate that their protein came from terrestrial C3 (or freshwater) foods, yet many of them have high δ15N values, at or above the highest Neanderthal values”. It is unequivocal that the δ15N and δ13C variations refer to the dietary apportioning of land versus marine protein, not to the ratio of dietary carbohydrate versus fat. In fact, the authors clearly state that “The Oase I δ15N value is also above those of the hyena (11.1‰), and the highest wolf value (11.5‰) from the same site and dating to about the same time”. This also unequivocally contradicts the notion that starches were a significant dietary contributor for these hominins given that this evidence suggests that they were more carnivorous than Neanderthals, hyenas and wolves as evidenced by their Figure 2 represented here.

Isotope Analysis of Oase 1 humans & Neanderthals vs other animals

Genetics

Hardy et al. cite 2 papers to substantiate the claim that the copy number increase of AMY1 occured less than 1 million years ago despite neither paper supporting it.

[2]“it [multiplication of the AMY1 genes] is thought to be less than 1 million years ago (Samuelson et al. 1996; Lazaridis et al. 2014)”

  • The first paper from 1996 by Samuelson et al. gives no specific date concerning the emergence of AMY1 copy number increase since it was not the objective; their objective was to “infer the structures of common ancestors and trace the evolution of the modem human amylase promoters”. The second is a 2014 paper by Lazaridis et al. which also does not mention a date for AMY1 copy number increase since it is focused on issues of lineage by studying 7-8kya Neolithic skeletons from La Braña (Spain), Motala (Sweden) & Loschbour (Germany). Only once does Lazaradis et al. briefly reference a hypothesized association between AMY1 copy number increase and high starch diets by citing Perry et al. 2007. Interestingly, the latter reference contradicts Hardy et al.’s purported timeline for AMY1 gene copies increase as, in their words, it was mosty likely of “a relatively recent origin that may be within the timeframe of modern human origins (i.e., within the last ∼200,000 years”.
  • Irrespective of when the when copy numbers of AMY1 increased, the significance of this is still unclear. It has been hypothesized that more copies of the AMY genes would improve glucose homeostasis on higher starch diets and protect against obesity (1, 2, 3). Nevertheless, Nature Genetics in June 2015 published a study by Usher et al. where the authors did “not observe even a nominal association between obesity and the copy number of any amylase gene (P = 0.70 for AMY1)” nor did they in diabetic cohorts where “AMY1 copy number did not associate with BMI in any group (P = 0.31 for GoT2D controls, P = 0.24 for GoT2D cases and P = 0.53 for InCHIANTI samples)”. Usher et al. explain why previous studies may have found associations that were not there given the use of ”lower-precision molecular methods, such as RT-PCR and array comparative genomic hybridization (CGH), or lower-precision analyses of whole-genome sequencing data to measure copy number”. It would be prudent to first understand the significance of the AMY genes in humans before using them as a mechanistic foundation in arguments relating to the evolution of humans and their encephalization.
  • In June 2015 Perry et al. avoided using “lower-precision molecular methods […] to measure copy number”, unlike Carpenter et al.’s group in March of that same year. This improved copy number assessment enabled Perry et al. to confidently conclude that “AMY1 gene duplications are likely human-specific and that they occurred following the divergence of our lineage from the Neandertal/Denisovan lineage ~550-590 kya”, contradicting Hardy et al.’s less than 1 million years ago timeline.

Paleoanthropology

Hardy et al. correctly cite the only paper to date supporting their view of hominim cooking emerging less than 800kya. However, the natural event confounding the interpretation provided by this paper and more recent evidence to the contrary are not mentioned as a counterbalance. Furthermore, Hardy et al. do not provide the reader with a representative view of the balance of evidence which currently is heavily biased towards the hypothesis of fire emerging 400-300kya.

[3]”Gesher Benot Ya’aqov, in Israel, which dates to around 780,000 bp, has charcoal, plant remains, and burned microartifacts in concentrations that the excavators believe suggests evidence for hearths (Alperson-Afil 2008)”

  • A 2008 paper by Alperson-Afil is cited as evidence of when hominin cooking emerged 780kya as evidenced by the Gesher Benot Ya’aqov (GBY) site in Israel. It does in fact conclude that “as the scenario of a natural fire is unlikely, we conclude that the concentrations of burned flint microartifacts in the different occupational surfaces of GBY represent phantom hearths, i.e. remnants of hominins’ use of fire”.
  • This conclusion is probelmatic for 2 major reasons. The first is addressed by Shimelmitz et al. in 2014, where it is explained that “consistent evidence for fire is found not just in the Tabun sequence but at every Acheulo-Yabrudian cave site where good information is available. The near-absence of burnt flints in the lower 8m of the sequence at Tabun (composed of 19 layers) also indicates that the scarcity of fire evidence before 350 kya is not just a matter of spotty preservation, or cave sites versus open air-sites (e.g., Gowlett and Wrangham, 2013). Rather, the negative evidence from the early layers is genuine, and there is a significant and permanent increase in the frequency of evidence for burning between 357 and 324 kya […] our best estimate for the onset of regular fire use at Tabun is between 357 and 324 kya”.
  • The second problem is that lava probably invaded the GBY site, as correlated with the Matuyama-Brunhes chron boundary event taking place 781kya. This occurence further substantially confounds Alperson-Afil’s interpretation. Evidence for this event at GBY stems from “artefacts in fluvial conglomerates, organic-rich calcareous muds and coquinas that accumulated along the shorelines of the palaeo-Hula lake (Goren-Ibar et al. 2000)”.

Metabolism

A lot of Hardy et al.’s argument for the important role of dietary carbohydrate in human evolution and the spectacular encephalization is based upon claims about metabolism. These 11 points are at best taken out of context or at worse entirely false.

[4]“There is debate on whether dietary carbohydrates are actually essential for human nutrition”

  • Micronutrients and macronutrients have been defined as essential when their absence causes a deficiency syndrome. No such ‘carbohydrate deficiency’ has been found to date and, to the best of my knowledge, nor has any suggestive evidence surfaced in the last century.
  • The 1999 report by the IDECG Working Group, led by DM Bier, recognizes that “the theoretical minimal level of carbohydrate (CHO) intake is zero”, before following on about its importance in human biological function.
  • Glucose is essential for cells to function but it does not have to originate from dietary sources due to an evolved gluconeogenetic capacity capable of providing 150 grams per day for CNS functions. This lack of reliance on dietary glycose has been validated since at least 1975 by Cahill and Owen’s 2 month starvation experiment. Depicted in their Figure 1, they found that the human brain always requires at least 35% of its energy from glucose (not necessarily of dietary origin).brain usage of glucose & ketones
  • In 1972 Drenick et al. stress-tested human reliance on endogenous glucose showing that “after fasting 2 months, administration of weight-adjusted doses of insulin […] no insulin reactions nor significant rises in catecholamine excretion occurred despite equal extent and rate of glucose fall. Glucose concentrations as low as 0.5 mmoles/liter (9 mg/100 ml) failed to precipitate hypoglycemic reactions.”
  • When dietary carbohydrates are avoided entirely and protein is moderated the human brain will use ketone bodies as its primary energy substrate. In such a metabolic state, Vanitalie and Nufert say that “although these data need confirmation, they suggest an increase in the metabolic efficiency in human brains using ketoacids as their principal energy source in place of glucose”.

[5]“a more realistic recommendation is that at least one-third of dietary energy should be supplied from carbohydrates (Bier et al. 1999)”

  • For this Hardy et al. quote, the 1999 report by the IDECG Working Group, led by DM Bier, does not identify a carbohydrate deficiency syndrome but advises at least 150g per day for “practical reasons”.
  • Dr.Eric Westman summarizes his findings about carbohydrates being non-essential saying “although there is certainly no evidence from which to conclude that extreme restriction of dietary carbohydrate is harmless, I was surprised to find that there is similarly little evidence to conclude that extreme restriction of carbohydrate is harmful.”

[6]“Glucose is the only energy source for sustaining running speeds above 70% of maximal oxygen consumption (Romijn et al. 1993)”

  • Brook et al., who developed the Cross-Over Point hypothesis, did not state that glucose was the only energy source above 70% VO2 max, only that it and glycogen were the main sources and free fatty acids the minor source. Hardy et al. essentially describe a binary change in energy substrate use when in fact the change is quantitative.
  • It is an unproven assumption that carbohydrates of dietary origin are necessary to use glycogen and glucose as the predominant substrate for instances of near maximal VO2. Even if it were true that glucose use always predominates across all individuals at >70% VO2 max, this does not automatically imply that dietary glucose is the necessary fuelling strategy for sustaining such intense efforts. These are separate claims.
  • In 2015 Hetlelid et al. showed that well-trained runners performing high intensity training at 85% VO2 max, nearly one third of the total energy expenditure comes from fat oxidation. Furthermore, the lower intensity, steady state equations of indirect calorimetry used here and elsewhere overestimate carbohydrate oxidation and underestimate fat oxidation.
  • In 2014 Noakes, Volek and Phinney characterize this quantitative change in energy substrates according to effort intensity, saying “some highly adapted runners consuming less than 10% of energy from carbohydrate are able to oxidise fat at greater than 1.5 g/min during progressive intensity exercise and consistently sustain rates of fat oxidation exceeding 1.2 g/min during exercise at ∼65% VO2max, thereby providing 56 kJ/min during prolonged exercise. The remaining energy would comfortably be covered by the oxidation of blood lactate, ketone bodies and glucose derived from gluconeogenesis”
  • Preliminary results from Volek et al.’s soon to be published FASTER study (Fat Adaptated Substrate Oxidation in Trained Elite Runners) have been reported at www.ultrarunning.com. Maximal fat oxidation rates higher above 1.54g per minute with 1 subject reaching 1.8g were shown. Classic sports physiology literature performed in non-ketogenic dieters with sub-optimal fatty acid oxidation capacities previously found maximal fat oxidation rates of only 1g min. These findings will, quite literally, require re-writing text books.
  • Elite ultra-runner and FASTER study participant Zach Bitter shared his personal data. At 75% VO2 max he used 98% fat and 2% carbohydrate. At 84% VO2 max he used 76% fat and 24% carbohydrate. Finally, at 96% VO2 max he was still using 23% fat and 77% carbohydrate.

[7]“In an evolutionary context, large stores of glycogen must be generated in order to provide sources of glucose for periods of sustained fasting or hardship. To build these reserves, the diet must consistently provide energy surplus to basal metabolic requirements”

  • The human gluconeogenetic capacity mentioned above disqualifies this imperative statement. Red blood cells, immune cells and the brain, as well as the more extended CNS, all function properly with glucose solely of endogenous origin.
  • The average lean male has tens of thousands of stored calories available to him in adipose tissue in contrast to his glycogen storage capacity of approximately 15 g/kg. Furthermore, his adipose tissue contains all the glycerol precursors required for endogenous production of glucose when combined with amino acids.

[8]“The diets of traditional Arctic populations are sometimes given as examples of successful high-protein diets (Lindeberg 2009)”

  • It is a common mistake to assume that the Inuit ate high-protein diets or it may simply be a misnomer arising from its association with the consumption of animal protein. In humans, high-protein diets lead to protein poisoning, otherwise known as ‘rabbit starvation’ (4, 5). The protein ceiling is 35-40% of calories or 200-300g of protein a day. The Inuit ate high-fat diets and their protein intake was moderate. Unlike the livers and kidneys of lions or wolves, human livers have substantially lower functional hepatic nitrogen clearances (FHNC) and urea nitrogen synthesis rates (UNSR) (6, 7).

[9]“15–20% from carbohydrate principally in the form of glycogen from the meat they consume (Ho et al. 1972)”

[10] “Meat frozen soon after slaughter will retain much of its muscle glycogen (Varmin and Sutherland 1995)”

  • Points 9 and 10 can be addressed together. The citation for point 7 should be “Varnam and Sutherland 1995”.
  • Greenberg et al. recognize the Inuit diet as one of “80–85% fat, 15–20% protein, and, apart from a little muscle glycogen, almost no carbohydrate” by citing Phinney’s 2004 paper.
  • Ho et al.’s 1972 study conduced in Point hope, Alaska, does not provide evidence of how this estimate is arrived except that it is based off of a 3,000-4,500kcal diet. Presumably, the reported glycogen levels are those of live animals.
  • Raw meat from a dead seal contains 0 grams of carbohydrate. In fact, in 1995 Varnam and Sutherland themselves explain that “if meat is frozen before ATP and glycogen levels are depleted post-mortem glycolysis is suspended. On thawing, however, the meat undergoes severe contraction with associated toughening and loss of large quantities of drip (thaw rigor)”. Simply stated “in response glycogen, the main energy store in the muscle, is converted to lactic acid by anaerobic, post-mortem glycolysis”. Momentarily and drastically slowing post-mortem glycolysis by flash-freezing meat will not stop glycolysis from depleting glycogen when the meat is finally thawed for consumption. The resulting lacate is a glucose element but is not counted into the percentage of dietary carbohydrate in a diet.
  • Flash-frozen meat does not contain glycogen levels anywhere near those necessary to support Hardey et al.’s statement. In 1976 Hamm explains how “the regulatory enzymes which control ATP metabolism and glycolysis in the living tissue are still active in the muscle postmortem, but these enzymic mechanisms are not able to maintain the ante-mortem levels of ATP and glycogen because the oxygen supply of the cell is stopped as soon as the blood circulation is interrupted by death of the animal. The lack of the aerobic ATP synthesis from ADP in the muscle mitochondria results in an anaerobic depletion of glycogen and consequently in a disappearance of ATP within a few hours p.m.”
  • In 1936 Sharp related glycogen’s conversion to lactic acid over time as a function of temperature (°C) saying that “in fish-muscle in the frozen state the maximum rate of glycogenolysis occurs in the interval -3.2° to -3.7 [and] freezing at -2° and lower temperatures for a period of 4 hours causes injury to the muscle, resulting in very rapid lactic acid formation on thawing. Freezing at 1.6° has no such effect, and on thawing the normal rate of lactic acid formation is resumed.” Figure 2 and 3 from his paper graphically illustrate this relationship.Lactic acid & glycogen in frozen muscle

[11]“the derived A-allele [CPT1A gene] has been shown to associate associate with hypoketotic hypoglycemia and high infant mortality […] suggests that it is an important adaptation to high meat, low- carbohydrate diets”

  • The association between hypoketotic hypoglycemia and high infant mortality with the CPT1A allele is from Clemente et al.’s 2014 paper which references a 2009 paper by Greenberg et al. entitled “The paradox of the carnitine palmitoyltransferase type Ia P479L variant in Canadian Aboriginal populations” in which 3 familes for a total of 7 patients were studied. The conclusion was that “severe clinical effects have been observed in only some, but not all, infants and young children [and] the occurrence of hypoglycemia, the main initial clinical effect of CPT-I deficiency, is dependent upon many environmental factors, including infection, feeding history and long-chain fat content of the diet, glycogen stores in the liver, and perhaps even climate“.
  • Clemente et al. found “strong evidence in favor of selection from a de novo mutation P(SDN) = 0.98, as opposed to selection on standing variation”. In simple terms, this means it was strongly positively selected for in high latitude populations eating very high-fat diets. Clemente et al. characterize these CPT1A mutations as “strong deviations from mutation-drift equilibrium”. Interestingly, Greenberg et al. describe the CPT1A mutations as ‘a paradox’ whilst Clemente et al. as ‘deleterious’. Patient 2 in the study of the former, for example, was most likely on a Westernized, relatively high carbohydrate diet described as a “regular diet and skim milk”. Such a diet underpins many ‘diseases of civilization’ and most likely contributed to the hypoketotic hypoglycemia and high infant mortality that is associated with these particular alleles.
  • Neither Hardy et al. nor Clemente et al. considered the evidence of compensatory mechanisms paralleling the drop in ketogenesis provided in Greenberg et al.’s paper. Veterinarian Petro Dobromylskyj from the Royal Veterinary College explains it best, saying “there is also evidence that the mutation decreases the inhibitory effect of malonyl-CoA on fatty-acid β-oxidation in mitochondria, thereby partially compensating for the drop in ketogenesis associated with reduced CPT1A activity”.
  • Finally, Greenberg et al. mention their “results of detailed β-oxidation studies in family C showed that oxidation was low at 37°C and were further decreased when measurements were conducted at a higher temperature”. These mutations may well be an adaptation to the freezing temperatures of the environments in which they arose.

[12] “high levels ketones in the blood, which can compromise reproductive function (Kim and Felig 1972)”

[13] “larger infants are born to women with higher blood glucose (Butte 2000), while a link has been made between maternal gestational ketonemia and a reduced off-spring IQ (Rizzo et al. 1991)”

  • Points 12 and 13 can be addressed together. Hardey al. quote a 1972 study by Kim and Felig that studied metabolic responses in pregnant women fasting for 84-90hrs. Specifically, their interests lay in the interplay between amino acids, glucose and insulin. They describe their interest saying “the influence of pregnancy on the changes in plasma glycine, threonine, and serine during fasting are of interest in as much as these amino acids are unique in demonstrating a delayed increase during prolonged starvation of obese nonpregnant subjects”. In fact they recognize the importance and adequacy of gluconeogenesis saying “maternal hepatic gluconeogenic mechanisms are capable of responding to increased substrate [amino acids] delivery during starvation in pregnancy”. Nowhere in their paper are ketones suggested to compromise reproductive function. This study looked at the effects of multi-day fasts – not ketogenic diets – in the context of gestation.
  • In another paper from 1972, Kim and Felig also note that in pregnant mothers, “starvation resulted in significant hypoglycemia and hyperketonemia and in an elevation of free fatty acid and glycerol concentrations. In 13 of 18 fasted subjects, blood glucose levels fell below 50 mg/100 ml. No specific symptoms or signs of hypoglycemia were noted.” Furthermore, the evidence was suggestive “that ketones may become an important fetal fuel during maternal caloric deprivation”.
  • In a 2015 retrospective cohort study of 906 pregnant mothers, Deschamps et al. found that “infants from mothers with a FBG [fasting blood glucose] >95 mg/dL were fatter both in relative (18.7 vs. 14.9%; p<0.05) and absolute (803 vs. 543g; p<0.01) terms. Further, over 50% of infants from mothers with FBG >95 mg/dL had a %fat greater than the 90th %fat percentile”. Increased adiposity may partially account account for the higher birthweight infants of mothers with higher blood glucose levels. This casts a less positive light on Butte’s findings from 2000 than Hardy et al. have.
  • In a 1980 study of calorie-restricted diabetic pregnant mothers, Coetzee et al. found that “neonates born to diabetic mothers with ketonuria had no fetal distress or asphyxia neonatorum [and] positive Ketostix tests in urine samples do not indicate toxic levels in the blood”.
  • It appears that Hardy et al. are confusing the pathological state of diabetic ketoacidosis – a simultaneous and excessive rise in the blood of both glucose and ketones – with simple nutritional ketosis. The latter arises naturally as a result of restricting carbohydrates and moderating protein (or simply fasting).  Hardy et al. quote papers by Nancy Butte and by Rizzo et al. who both looked at gestational diabetes and ketoacidosis, not nutritional ketosis. Rizzo et al. concluded that “the associations between gestational ketonemia in the mother and a lower IQ in the child warrant continued efforts to avoid ketoacidosis and accelerated starvation in all pregnant women”. Butte recommend avoiding ketonemia from her study of gestational diabetes mellitus, not ketogenic dieters. In fact, she recognizes how “the ADA states that the percentage of carbohydrate in the diet is dependent on individual eating habits and that the effect on blood glucose and percentage fat depends on assessment and treatment goals”. She also goes on to emphasize how “the lower percentage of carbohydrate blunts the postprandial hyperglycemia”.

[14] “can also be obtained directly from other dietary sources, or it can be synthesized from other fatty acids such as α-linolenic acid (ALA), which is present in oils from ocean fish, eggs, seed oils, and various leafy plant foods”

  • It is suprising that Hardy et al. do not mention how inefficiently humans convert α-linoleic acid (ALA) into the bioavailable long chain forms, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). In 1998 Gerster H. used radioisotopes to show how adults “with a background diet high in saturated fat conversion to long-chain metabolites is approximately 6% for EPA and 3.8% for DHA. With a diet rich in n-6 PUFA, conversion is reduced by 40 to 50%”. Western diets are excessively rich in omega-6 polyunsaturated fatty acids. Consequently, specifically targeting plant foods as a meaningful source of EPA and DHA is not recommended, especially in light of the 2006 estimate by Simopoulos whereby people eating a Westernized diet have a 15:1 to 16.7:1 ratio of omega-6 to omega-3 (EPA and DHA) fatty acids.