Sometimes, even a tiny cut can have serious and unexpected consequences. New research reveals that even a minor flesh wound can cause previously dormant cancer cells to develop into tumors.
The study, published in the Proceedings of the National Academy of Sciences, focuses on basal cell carcinoma, a variety of skin cancer associated with hair follicle cells. Basal cell carcinoma is the most common type of skin cancer, and while it rarely metastasizes or kills it’s still considered malignant.
Biochemists Sunny Wong and Jeremy Reiter, from the University of California, San Francisco, wanted to see how tumors develop from cancerous mutations. To do that, they genetically modified mice so that their hair follicle stem cells expressed the human basal cell carcinoma gene. After giving some of the mice a small cut, and leaving others alone, they discovered that tumors only formed on the hurt mice.
When skin is cut, hair-follicle stem cells migrate to the injury. Wong says pre-cancerous cells can lie dormant in the body until a trigger, such as radiation or a build up of mutations, pushes them into forming a tumour. “In this case, wounding got cancerous cells out of their resting phase,” he says. [New Scientist]
Although the experiment was short-term, the implication is that the same processes can play out if cells get damaged over time, and if a wound then rouses the sleeping cancer:
The study suggests that, after DNA in the skin’s stem cells is damaged to create a mutation in an oncogene, the mutated cells might rest for years without causing cancer, and might cause problems only when a wound prompts them to act. [Nature]
Scientists have been investigating this wound-cancer trend for several years now.
Reiter said that over the past 10 years, more and more scientists have begun to think that “cancers are wounds gone awry.” Normally, the hair follicle represses the tumor-generating potential of the stem cells, he said, “but when these cells leave their niche, the reins that are supplied by the [follicle] come off. ” [The Scientist]
For some scientists, this study is an exciting development in the fight against cancer.
The work is “pioneering,” said Ervin Epstein, a cancer researcher at the Children’s Hospital Oakland Research Institute in California, who was not involved in the research. “What could be more important than identifying the cell of origin of the most common of human cancers?” [The Scientist]
But not everyone is convinced of the link between wounds and basal cell carcinoma.
[Critics] say that most basal cell carcinomas do not develop at the sites of injury, so the finding is of limited significance. “This is certainly not a major mechanism underlying basal cell carcinoma formation in humans,” says Sabine Werner, a cell biologist at the Swiss Federal Institute of Technology in Zurich. [Nature]
‘Most,’ though, doesn’t mean all–and when it comes to battling cancer, every little step forward counts.
Pancreatic cancers use the sugar fructose, very common in the Western diet, to activate a key cellular pathway that drives cell division, helping the cancer grow more quickly, a study by researchers at UCLA’s Jonsson Comprehensive Cancer Center has found.
Although it is widely known that cancers use glucose, a simple sugar, to fuel their growth, this is the first time a link has been shown between fructose and cancer proliferation, said the study’s senior author, Dr. Anthony Heaney, an associate professor of medicine and neurosurgery and a Jonsson Cancer Center researcher.
“The bottom line is the modern diet contains a lot of refined sugar including fructose, and it’s a hidden danger implicated in a lot of modern diseases, such as obesity, diabetes and fatty liver,” said Heaney, who also serves as co-director of the Pituitary Tumor and Neuroendocrine Program at UCLA. “In this study, we show that cancers can use fructose just as readily as glucose to fuel their growth.
“The study is published in the Aug. 1 issue of the peer-reviewed journal Cancer Research.
Sources of fructose in the Western diet include cane sugar (sucrose) and high-fructose corn syrup (HFCS), a corn-based sweetener that has been on the market since about 1970. HFCS accounts for more than 40 percent of the caloric sweeteners added to foods and beverages, and it is by far the most frequently used sweetener in American soft drinks.
Between 1970 and 1990, the consumption of HFCS in the U.S. increased by more than 1,000 percent, according to an article in the April 2004 issue of the American Journal of Clinical Nutrition. Food companies use HFCS — a mixture of fructose and glucose — because it is inexpensive, easy to transport and keeps foods moist. And because of its excessive sweetness, it is cost-effective for companies to use small quantities of HCFS in place of more expensive sweeteners or flavorings.
In his study, Heaney and his team took pancreatic tumors from patients and cultured and grew the malignant cells in Petri dishes. They then added glucose to one set of cells and fructose to another. Using mass spectrometry, they were able to follow the carbon-labeled sugars in the cells to determine what, exactly, they were being used for and how.
Heaney found that the pancreatic cancer cells could easily distinguish between glucose and fructose, which are very similar structurally, and contrary to conventional wisdom, the cancer cells metabolized the sugars in very different ways. In the case of fructose, the pancreatic cancer cells used the sugar in the transketolase-driven non-oxidative pentose phosphate pathway to generate nucleic acids, the building blocks of RNA and DNA, which the cancer cells need to divide and proliferate.
“Traditionally, glucose and fructose have been considered as interchangeable monosaccharide substrates that are similarly metabolized, and little attention has been given to sugars other than glucose,” the study states. “However, fructose intake has increased dramatically in recent decades and cellular uptake of glucose and fructose uses distinct transporters … These findings show that cancer cells can readily metabolize fructose to increase proliferation. They have major significance for cancer patients, given dietary refined fructose consumption.”
As in anti-smoking campaigns, a federal effort should be launched to reduce refined fructose intake, Heaney said.
“I think this paper has a lot of public health implications,” Heaney said. “Hopefully, at the federal level, there will be some effort to step back on the amount of HFCS in our diets.”
Heaney said that while this study was done in pancreatic cancer, these finding may not be unique to that cancer type.
Going forward, Heaney and his team are exploring whether it is possible to block the uptake of fructose in the cancer cells with a small molecule, taking away one of the fuels they need to grow. The work is being done in cell lines and in mice, Heaney said. The study was funded by the National Institutes of Health, the Hirschberg Foundation and the Jonsson Cancer Center.
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.
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 1956; Hsu and Sabatini 2008; Vander Heiden et al. 2009a; Koppenol 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. 2009a; Levine and Puzio-Kuter 2010; Cairns et al. 2011; Koppenol 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. 1998; Bertout et al. 2008; Semenza 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).
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. 2011; Xu 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.
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. 2; Wise et al. 2011; Metallo et al. 2012; Mullen 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. 2010; Zaugg 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. 2011; Le 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. 2012; Semenza 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. 2010; Slavov 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;4; Lippman 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.
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.
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 2010; Singh 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. 5; Zoncu 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 2005; Huang and Tindall 2007; Ferber 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. 5; Kaadige et al. 2009).
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. 2010; Guan 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.
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 MYC, JUN, 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. 1994; Shim 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. 2010; Ji 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. 2001; Zeller et al. 2006; Rempel 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 CDK4, CDK6, 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. 2007; Caulin 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%.
(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. 6C; Savage 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. 2004; Siegel 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. 2006; Hansen 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 2009; Bass 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. 2010; Longo 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 2010; Rubinsztein 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. 2008; Yan 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. 2009; Gross 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. 2011; Possemato 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. 1998; He 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. 1997; Dang 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. 2005; Wise et al. 2008; Gao et al. 2009). Mutated Ras also enhances glycolysis, partly through increasing the activity of Myc and HIF (Sears et al. 1999; Semenza 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. 2007, 2008). 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. 2011; Liu 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. 2006; Matoba et al. 2006; Vousden and Ryan 2009; Wang 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. 2010; Suzuki 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. 2008; Semenza 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:
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 2011; Jones 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. 2010, 2012; Wang 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. 2010; Delabarre et al. 2011; Cassago et al. 2012; Le 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. 2009b; Jiang 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 LDHA, PHGDH, 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. 1994; Zhou 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. 2011; Morris 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:
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:
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:
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]
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]
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]
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]
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]
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.1 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.
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.
Data from 2007 suggest that approximately 1.4 million men and women in the U.S. population are likely to be diagnosed with cancer, and approximately 566,000 American adults are likely to die from cancer in 2008.1 Data collected between 1996 and 2004 indicate that the overall 5-year survival rate for cancers from all sites, relative to the expected survival from a comparable set of people without cancer, is 65.3%.1 However, survival and recurrence rates following diagnosis vary greatly as a function of cancer type and the stage of development at diagnosis. For example, in 2000, the relative survival rate five years following diagnosis of melanoma (skin cancer) was greater than 90%; that of cancers of the brain and nervous system was 35%. Once a cancer has metastasized (or spread to secondary sites via the blood or lymph system), however, the survival rate usually declines dramatically. For example, when melanoma is diagnosed at the localized stage, 99% of people will survive more than five years, compared to 65% of those diagnosed with melanoma that has metastasized regionally and 15% of those whose melanoma has spread to distant sites.2
The term “cancer” describes a group of diseases that are characterized by uncontrolled cellular growth, cellular invasion into adjacent tissues, and the potential to metastasize if not treated at a sufficiently early stage. These cellular aberrations arise from accumulated genetic modifications, either via changes in the underlying genetic sequence or from epigenetic alterations (e.g., modifications to geneactivation- or DNA-related proteins that do not affect the genetic sequence itself).3,4Cancers may form tumors in solid organs, such as the lung, brain, or liver, or be present as malignancies in tissues such as the blood or lymph. Tumors and other structures that result from aberrant cell growth, contain heterogeneous cell populations with diverse biological characteristics and potentials. As such, a researcher sequencing all of the genes from tumor specimens of two individuals diagnosed with the same type of lung cancer will identify some consistencies along with many differences. In fact, cancerous tissues are sufficiently heterogeneous that the researcher will likely identify differences in the genetic profiles between several tissue samples from the same specimen. While some groupings of genes allow scientists to classify organ-or tissue-specific cancers into subcategories that may ultimately inform treatment and provide predictive information, the remarkable complexity of cancer biology continues to confound treatment efforts.
Once a cancer has been diagnosed, treatments vary according to cancer type and severity. Surgery, radiation therapy, and systemic treatments such as chemotherapy or hormonal therapy represent traditional approaches designed to remove or kill rapidly-dividing cancer cells. These methods have limitations in clinical use. For example, cancer surgeons may be unable to remove all of the tumor tissue due to its location or extent of spreading. Radiation and chemotherapy, on the other hand, are non-specific strategies—while targeting rapidly-dividing cells, these treatments often destroy healthy tissue as well. Recently, several agents that target specific proteins implicated in cancer-associated molecular pathways have been developed for clinical use. These include trastuzumab, a monoclonal antibody that targets the protein HER2 in breast cancer,5 gefitinib and erlotnib, which target epidermal growth factor receptor (EGFR) in lung cancer,6 imatinib, which targets the BCR-ABL tyrosine kinase in chronic myelogenous leukemia,7 the monoclonal antibodies bevacizumab, which targets vascular endothelial growth factor in colorectal and lung cancer,8 and cetuximab and panitumumab, which target EGFR in colorectal cancer.8 These agents have shown that a targeted approach can be successful, although they are effective only in patients who feature select subclasses of these respective cancers.
All of these treatments are most successful when a cancer is localized; most fail in the metastatic setting.9–11 This article will discuss the CSC hypothesis and its supporting evidence and provide some perspectives on how CSCs could impact the development of future cancer therapy.
Defining The “Cancer Stem Cell”
A consensus panel convened by the American Association of Cancer Research has defined a CSC as “a cell within a tumor that possesses the capacity to self-renew and to cause the heterogeneous lineages of cancer cells that comprise the tumor.”12 It should be noted that this definition does not indicate the source of these cells—these tumor-forming cells could hypothetically originate from stem, progenitor, or differentiated cells.13 As such, the terms “tumor-initiating cell” or “cancer-initiating cell” are sometimes used instead of “cancer stem cell” to avoid confusion. Tumors originate from the transformation of normal cells through the accumulation of genetic modifications, but it has not been established unequivocally that stem cells are the origin of all CSCs. The CSC hypothesis therefore does not imply that cancer is always caused by stem cells or that the potential application of stem cells to treat conditions such as heart disease or diabetes, as discussed in other chapters of this report, will result in tumor formation. Rather, tumor-initiating cells possess stem-like characteristics to a degree sufficient to warrant the comparison with stem cells; the observed experimental and clinical behaviors of metastatic cancer cells are highly reminiscent of the classical properties of stem cells.9
The CSC Hypothesis And The Search For CSCs
The CSC hypothesis suggests that the malignancies associated with cancer originate from a small population of stem-like, tumor-initiating cells. Although cancer researchers first isolated CSCs in 1994,14 the concept dates to the mid-19th century. In 1855, German pathologist Rudolf Virchow proposed that cancers arise from the activation of dormant, embryonic-like cells present in mature tissue.15 Virchow argued that cancer does not simply appear spontaneously; rather, cancerous cells, like their non-cancerous counterparts, must originate from other living cells. One hundred and fifty years after Virchow’s observation, Lapidot and colleagues provided the first solid evidence to support the CSC hypothesis when they used cell-surface protein markers to identify a relatively rare population of stemlike cells in acute myeloid leukemia (AML).14 Present in the peripheral blood of persons with leukemia at approximately 1:250,000 cells, these cells could initiate human AML when transplanted into mice with compromised immune systems. Subsequent analysis of populations of leukemia-initiating cells from various AML subtypes indicated that the cells were relatively immature in terms of differentiation.16 In other words, the cells were “stem-like”—more closely related to primitive blood-forming (hematopoietic) stem cells than to more mature, committed blood cells.
The identification of leukemia-inducing cells has fostered an intense effort to isolate and characterize CSCs in solid tumors. Stem cell-like populations have since been characterized using cell-surface protein markers in tumors of the breast,17 colon,18 brain,19 pancreas,20,21 and prostate.22,23 However, identifying markers that unequivocally characterize a population of CSCs remains challenging, even when there is evidence that putative CSCs exist in a given solid tumor type. For example, in hepatocellular carcinoma, cellular analysis suggests the presence of stem-like cells.24Definitive markers have yet to be identified to characterize these putative CSCs, although several potential candidates have been proposed recently.25,26 In other cancers in which CSCs have yet to be identified, researchers are beginning to link established stem-cell markers with malignant cancer cells. For instance, the proteins Nanog, nucleostemin, and musashi1, which are highly expressed in embryonic stem cells and are critical to maintaining those cells’ pluripotency, are also highly expressed in malignant cervical epithelial cells.27 While this finding does not indicate the existence of cervical cancer CSCs, it suggests that these proteins may play roles in cervical carcinogenesis and progression.
Do CSCs Arise From Stem Cells?
Given the similarities between tumor-initiating cells and stem cells, researchers have sought to determine whether CSCs arise from stem cells, progenitor cells, or differentiated cells present in adult tissue. Of course, different malignancies may present different answers to this question. The issue is currently under debate,9,12 and this section will review several theories about the cellular precursors of cancer cells (see Fig. 9.1).
Figure 9.1. How Do Cancer Stem Cells Arise? The molecular pathways that maintain “stem-ness” in stem cells are also active in numerous cancers. This similarity has led scientists to propose that cancers may arise when some event produces a mutation in a stem cell, robbing it of the ability to regulate cell division. This figure illustrates 3 hypotheses of how a cancer stem cell may arise: (1) A stem cell undergoes a mutation, (2) A progenitor cell undergoes two or more mutations, or (3) A fully differentiated cell undergoes several mutations that drive it back to a stem-like state. In all 3 scenarios, the resultant cancer stem cell has lost the ability to regulate its own cell division.
Cancer Cells Arise from Stem Cells. Stem cells are distinguished from other cells by two characteristics: (1) they can divide to produce copies of themselves, or self-renew, under appropriate conditions and (2) they are pluripotent, or able to differentiate into most, if not all, mature cell types. If CSCs arise from normal stem cells present in the adult tissue, de-differentiation would not be necessary for tumor formation. In this scenario, cancer cells could simply utilize the existing stem-cell regulatory pathways to promote their self-renewal. The ability to self-renew gives stem cells long lifespans relative to those of mature, differentiated cells.30 It has therefore been hypothesized that the limited lifespan of a mature cell makes it less likely to live long enough to undergo the multiple mutations necessary for tumor formation and metastasis.
Several characteristics of the leukemia-initiating cells support the stem-cell origin hypothesis. Recently, the CSCs associated with AML have been shown to comprise distinct, hierarchically-arranged classes (similar to those observed with hematopoietic stem cells) that dictate distinct fates.31 To investigate whether these CSCs derive from hematopoietic stem cells, researchers have used a technique known as serial dilution to determine the CSCs’ ability to self-renew. Serial dilution involves transplanting cells (usually hematopoietic stem cells, but in this case, CSCs) into a mouse during a bone-marrow transplant. Prior to the transplant, this “primary recipient” mouse’s natural supply of hematopoietic stem cells is ablated. If the transplant is successful and if the cells undergo substantial self-renewal, the primary recipient can then become a successful donor for a subsequent, or serial, transplant. Following cell division within primary recipients, a subset of the AML-associated CSCs divided only rarely and underwent self-renewal instead of committing to a lineage. This heterogeneity in self-renewal potential supports the hypothesis that these CSCs derive from normal hematopoietic stem cells.31 It should be noted, however, that the leukemia-inducing cells are the longest-studied of the known CSCs; the identification and characterization of other CSCs will allow researchers to understand more about the origin of these unique cells.
Hypothesis #2: Cancer Cells Arise from Progenitor Cells.
The differentiation pathway from a stem cell to a differentiated cell usually involves one or more intermediate cell types. These intermediate cells, which are more abundant in adult tissue than are stem cells, are called progenitor or precursor cells. They are partly differentiated cells present in fetal and adult tissues that usually divide to produce mature cells. However, they retain a partial capacity for self-renewal. This property, when considered with their abundance relative to stem cells in adult tissue, has led some researchers to postulate that progenitor cells could be a source of CSCs.32,33
Hypothesis #3: Cancer Cells Arise from Differentiated Cells.
Some researchers have suggested that cancer cells could arise from mature, differentiated cells that somehow de-differentiate to become more stem celllike. In this scenario, the requisite oncogenic (cancer causing) genetic mutations would need to drive the de-differentiation process as well as the subsequent self-renewal of the proliferating cells. This model leaves open the possibility that a relatively large population of cells in the tissue could have tumorigenic potential; a small subset of these would actually initiate the tumor. Specific mechanisms to select which cells would de-differentiate have not been proposed. However, if a tissue contains a sufficient population of differentiated cells, the laws of probability indicate that a small portion of them could, in principle, undergo the sequence of events necessary for de-differentiation. Moreover, this sequence may contain surprisingly few steps; researchers have recently demonstrated that human adult somatic cells can be genetically “re-programmed” into pluripotent human stem cells by applying only four stem-cell factors (see the chapter, “Alternate Methods for Preparing Pluripotent Stem Cells” for detailed discussion of inducing pluripotent stem cells).28,29
How Cancer Stem Cells Could Support Metastasis
Metastasis is a complex, multi-step process that involves a specific sequence of events; namely, cancer cells must escape from the original tumor, migrate through the blood or lymph to a new site, adhere to the new site, move from the circulation into the local tissue, form micrometastases, develop a blood supply, and grow to form macroscopic and clinically relevant metastases.9,34,35 Perhaps not surprisingly, metastasis is highly inefficient.9 It has been estimated that less than 2% of solitary cells that successfully migrate to a new site are able to initiate growth once there.34,36,37 Moreover, less than 1% of cells that initiate growth at the secondary site are able to maintain this growth sufficiently to become macroscopic metastases.36These observations suggest that a small, and most likely specialized, subset of cancer cells drives the spread of disease to distant organs.
Some researchers have proposed that these unique cells may be CSCs.9,30,32,33,38 In this hypothesis, metastatic inefficiency may reflect the relative rarity of CSCs combined with the varying compatibilities of these cells with destination microenvironments. Researchers have demonstrated that stem cells and metastatic cancer cells share several properties that are essential to the metastatic process, including the requirement of a specific microenvironment (or “niche”) to support growth and provide protection, the use of specific cellular pathways for migration, enhanced resistance to cell death, and an increased capacity for drug resistance.9There is emerging, albeit limited, evidence that these properties may also hold for CSCs.9 Metastatic sites for a given cancer type could therefore represent those tissues that provide or promote the development of a compatible CSC niche, from which CSCs could expand through normal or dysregulated cellular signaling. Moreover, normal stem cells tend to be quiescent unless activated to divide.39 If the CSC hypothesis holds true, then undifferentiated, dormant CSCs would be relatively resistant to chemotherapeutic agents, which act mainly on dividing cells.10 As such, this subpopulation could form the kernel of cells responsible for metastasis and cancer recurrence following treatment and remission.
How The CSC Model Could Affect Cancer Therapy
As noted previously, most contemporary cancer treatments have limited selectivity — systemic therapies and surgeries remove or damage normal tissue in addition to tumor tissue. These methods must therefore be employed judiciously to limit adverse effects associated with treatment. Moreover, these approaches are often only temporarily effective; cancers that appear to be successfully eliminated immediately following treatment may recur at a later time and often do so at a new site. Agents that target molecules implicated in cancer pathways have illustrated the power of a selective approach, and many researchers and drug developers are shifting toward this paradigm. If the CSC hypothesis proves to be correct, then a strategy designed to target CSCs selectively could potentially stop the “seeds” of the tumor before they have a chance to germinate and spread.
The CSC hypothesis accounts for observed patterns of cancer recurrence and metastasis following an apparently successful therapeutic intervention. In clinical practice, however, some cancers prove quite aggressive, resisting chemotherapy or radiation even when administered at relatively early stages of tumor progression. These tumors therefore have an increased likelihood of metastasizing, confounding further treatment strategies while compromising the cancer patient’s quality of life. The presence of CSC in some malignancies may account for some of these metastases. So why do some tumors succumb to therapy, while others resist it? Some scientists have suggested that the tumor aggressiveness may correlate with the proportion of CSCs within a corresponding tumor.40–42 In this scenario, less aggressive cancers contain fewer CSCs and a greater proportion of therapy-sensitive non-CSCs.9
There is also some evidence to suggest that CSCs may be able to selectively resist many current cancer therapies, although this property has yet to be proven in the clinic.9 For example, normal stem cells and metastatic cancer cells over-express several common, known drug-resistance genes.43 As a result, breast cancer CSCs express increased levels of several membrane proteins implicated in resistance to chemotherapy 17 These cells have also been shown to express intercellular signaling molecules such as Hedgehog and Bmi-1,44 which are essential for promoting self-renewal and proliferation of several types of stem cells.45 Moreover, experiments in cell lines from breast cancer46 and glioma40 have shown that CSCs (as identified by cell-surface markers) are more resistant to radiotherapy than their non-CSC counterparts. In the face of radiation, the CSCs appear to survive preferentially, repair their damaged DNA more efficiently, and begin the process of self-renewal.
These discoveries have led researchers to propose several avenues for treating cancer by targeting molecules involved in CSC renewal and proliferation pathways. Potential strategies include interfering with molecular pathways that increase drug resistance, targeting proteins that may sensitize CSCs to radiation, or restraining the CSCs’ self-renewal capacity by modifying their cell differentiation capabilities.9 In each case, successful development of a therapy would require additional basic and clinical research. Researchers must characterize the CSCs associated with a given tumor type, identify relevant molecules to target, develop effective agents, and test the agents in pre-clinical models, such as animals or cell lines. However, by targeting fundamental CSC cellular signaling processes, it is possible that a given treatment could be effective against multiple tumor types.
Cancer represents a major health challenge for the 21st century. Governed by an intricate, complex interplay of molecular signals, cancers often resist systemic treatments. Yet the uncontrolled cellular growth that characterizes cancers may paradoxically hold the key to understanding the spread of disease. It has long been postulated that tumors form and proliferate from the actions of a small population of unique cells. The observation that metastatic cancer cells exhibit experimental and clinical behaviors highly reminiscent of the classical properties of stem cells has led researchers to search for and to characterize “cancer stem cells” believed to be implicated in the cancer process.
The discovery of CSCs in some tumor types has ushered in a new era of cancer research. Cancer stem cell science is an emerging field that will ultimately impact researchers’ understanding of cancer processes and may identify new therapeutic strategies. However, much remains to be learned about these unique cells, which as of yet have not been identified in all tumor types. At present, evidence continues to mount to support a CSC Hypothesis—that cancers are perpetuated by a small population of tumor-initiating cells that exhibit numerous stem cell-like properties. Whether or not the Hypothesis ultimately proves true in all cases, understanding the similarities between cancer cells and stem cells will illuminate many molecular pathways that are triggered in carcinogenesis. Thus, the question, “Are stem cells involved in cancer?” has no simple answer. However, the characterization of CSCs will likely play a role in the development of novel targeted therapies designed to eradicate the most dangerous tumor cells, that may be resistant to current chemotherapy regimens, thereby providing researchers and clinicians with additional targets to alleviate the burden of cancer.
National Cancer Institute. Surveillance Epidemiology and End Results: SEER stat fact sheets. http://seer.cancer.gov/data/. Accessed February 15, 2009.
Feinberg AP, Ohlsson R, Henikoff S. The epigenetic progenitor origin of human cancer. Rev Genet. 2006; 7:21–33.
Jones PA, Baylin SB. The epigenomics of cancer. Cell. 2007;128:683–692.
Slamon DJ, Leyland-Jones B, Shak S, et al. Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N Engl J Med. 2001;344:783–792.
Silvestri GA, Rivera MP. Targeted therapy for the treatment of advanced non-small cell lung cancer: a review of the epidermal growth factor receptor antagonists. Chest. 2005;128:3975–3984.
Sherbenou DW, Druker BJ. Applying the discovery of the Philadelphia chromosome. J Clin Invest. 2007; 117:2067–2074.
Hedge SR, Sun W, Lynch JP. Systemic and targeted therapy for advanced colon cancer. Expert Rev Gastroenterol Hepatol. 2008;2:135–149.
Croker AK, Allan AL. Cancer stem cells: implications for the progression and treatment of metastatic disease. J Cell Mol Med. 2008;12:374–390.
Gil J, Stembalska A, Pesz KA, Sasiadek MM. Cancer stem cells: the theory and perspectives in cancer therapy. J App Genet. 2008;49:193–199.
Reya T, Morrison SJ, Clarke MF, Weissman IL. Stem cells, cancer, and cancer stem cells. Nature. 2001;414:105–111.
Clarke MF, Dick JE, Dirks PB, et al. Cancer Stem Cells—Perspectives on Current Status and Future Directions: AACR Workshop on Cancer Stem Cells. Cancer Res. 2006; 66:9339–9344.
Rapp UR, Ceteci F, Schreck R. Oncogene-induced plasticity and cancer stem cells. Cell Cycle. 2008;7:45–51.
Lapidot T, Sirard C, Vormoor J, et al. A cell initiating human acute myeloid leukaemia after transplantation into SCID mice. Nature. 1994;367:645–648.
Huntly BJP, Gilliland DG. Leukemia stem cells and the evolution of cancer stem cells. Nat Rev Cancer. 2005;5:311–321.
Bonnet D, Dick JE. Human myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat Med. 1997;3:730–737.
Al-Hajj M, Wicha MS, Benito-Hernandez A, Morrison SJ, Clarke MF. Prospective identification of tumorigenic breast cancer cells. Proc Natl Acad Sci USA. 2003;100:3983–3988.
O’Brien CA, Pollett A, Gallinger S, Dick JE. A human colon cancer cell capable of initiating tumour growth in immunodeficient mice. Nature. 2007;445:106–110.
Singh SK, Hawkins C, Clarke ID, et al. Identification of human brain tumor initiating cells. Nature. 2004; 432:396–401.
Li C, Heidt DG, Dalerba P, et al. Identification of pancreatic cancer stem cells. Cancer Res. 2007;67:1030–1037.
Hermann PC, Huber SL, Herrler T, et al. Distinct populations of cancer stem cells determine tumor growth and metastatic activity in human pancreatic cancer. Cancer Stem Cell. 2007;1:313–323.
Collins AT, Berry PA, Hyde C, Stower MJ, Maitland MJ. Prospective identification of tumorigenic prostate cancer stem cells. Cancer Res. 2005;65:10946–10951.
Patrawala L, Calhoun T, Schneider-Broussard R, et al. Highly purified CD44+ prostate cancer cells from xenograft human tumors are enriched in tumorigenic and metastatic progenitor cells. Oncogene. 2006;25:1696–1708.
Luzzi KJ, MacDonald IC, Schmidt EE, et al. Multistep nature of metastatic inefficiency: dormancy of solitary cells after successful extravasation and limited survival of early micrometastases. Am J Pathol. 1998;153:865–873.
Weiss L. Metastatic inefficiency. Adv Cancer Res. 1990;54:159–211.
Vaidya JS. An alternative model of cancer cell growth and metastasis. Int J Surg. 2007;5:73–75.
Pardal R, Clarke MF, Morrison SJ. Applying the principles of stem-cell biology to cancer. Nat Rev Cancer. 2003; 3:895-902.
Bao S, Wu Q, McLendon RE, et al. Glioma stem cells promote radioresistance by preferential activation of the DNA damage response. Nature. 2006;444:756–760.
Diehn M, Clarke MF. Cancer stem cells and radiotherapy: new insights into tumor radioresistance. J Natl Cancer Inst. 2006;98:1755–1757.
Smalley M, Ashworth A. Stem cells and breast cancer: a field in transit. Nat Rev Cancer. 2003;3:832–844.
Dean M, Fojo T, Bates S. Tumour stem cells and drug resistance. Nat Rev Cancer. 2005;5:275–284.
Liu S, Dontu G, Mantle ID, et al. Hedgehog signaling and Bmi-1 regulate self-renewal of normal and malignant human mammary stem cells. Cancer Res. 2006;66:6063–6071.
Park I-K, Morrison SJ, Clarke MF. Bmi1, stem cells, and senescence regulation. J Clin Invest. 2004;113:175–179.
Phillips TM, McBride WH, Pajonk F. The response of CD24-/low/CD44+ breast cancer-initiating cells to radiation. J Natl Cancer Inst. 2006;98:1777–1785.
Cutaneous T-cell lymphoma (CTCL), also known as mycosis fungoides, is a rare type of lymphocytic cancer in which certain cells of the lymphatic system, called T-lymphocytes or T-cells, become cancerous (malignant) and affect the skin.
The lymphatic system is part of the immune system. It is made up of tiny tubes that branch, like blood vessels, into all parts of the body, including the skin.
These vessels, called lymph vessels, carry lymph (a milky body fluid that contains lymphocytes, proteins and fats) into and out of the lymph nodes (lymph glands) which are located in the underarm, pelvis, neck and abdomen.
The lymph nodes’ main function is to act as a barrier to the spread of infection and destroy or filter out bacteria before it can pass into the bloodstream. Within the lymph nodes are lymphocytes (white blood cells) whose purpose is to ambush and destroy the foreign bacteria.
There are two types of lymphocytes: B-lymphocytes (B-cells) and T-lymphocytes (T-cells). B-cells work chiefly by secreting antibodies into the body’s fluids. T-cells destroy the abnormal cells.
There are two types of T-cells: helper T-cells and killer T-cells. Helper T-cells enhance the activities of the killer T-cells, as well as regulate the antibody production of the B-cells. Killer T-cells attack and destroy infected or cancerous cells.
CTCL is the result of an uncontrolled growth of helper T-cells.
Clinically, patients with CTCL fall into three prognostic groups: good risk, intermediate risk and poor risk.
Good risk (median survival over 12 years): Only patch or plaque skin lesions and no lymph node, blood or internal organ involvement.
Intermediate risk (median survival about five years): Skin tumors, plaques or abnormal redness over a large portion of the body, with affected lymph node and blood involvement, but no internal organ has succumbed to the disease.
Poor risk (median survival about two to four years): Internal organs and lymph nodes affected.
Genetic predisposition is the main cause, but other causative agents such as long-term exposure to industrial or environmental metals, organic solvents, chemical carcinogens, pesticides and herbicides are also under consideration from the research community.
Patients with CTCL can take many years to progress through the three cancerous phases of CTCL. These three phases are listed below:
Premycotic and patch phase: can last between a few years and several decades. The first symptoms are usually a generalized itching (pruritus) and patches of raised, reddened skin that can appear anywhere on the body. This reddened skin often closely resembles benign inflammatory skin problems such as eczema (itching skin disease), psoriasis (a chronic skin condition characterized by red, scaly skin patches), drug reactions, fungal infections or parapsoriases (a group of slowly developing, persistent, red, scaly elevated skin lesions), or poikiloderma (a condition characterized by pigmentary and atrophic changes in the skin, giving it a mottled appearance).
Infiltrative plaque phase: during this phase the patches of skin present in the premycotic and patch phase become elevated, thicker, denser, darker red, and develop into horseshoe or bizarre patterns. Itching persists, as well as hair loss, in the areas of and surrounding the patches. These patches of skin are now called plaques, because they have gone from surface lesions to raised lesions.
Tumor phase: during this phase, the patches and plaques present in the prior two phases become massive (mushroom in appearance) and spread. These tumors tend to ulcerate and appear on the skin as an open sore. As more and more of the skin becomes ulcerated, the skin may become infected. Additionally, the disease can spread to lymph nodes, causing them to become enlarged, or to other organs in the body, such as the spleen, lungs or liver. When large number of tumor cells are found in the blood, the condition is called Sezary Syndrome.
It is hard to diagnosis CTCL early in its development because the skin lesions closely mimic skin conditions, such as eczema and psoriasis. Therefore, physicians may have to wait years until the condition is more discernible.
However, if parapsoriasis appears as faint pink to yellowish tan patches with scaling and wrinkling, or poikiloderma appears as large, flat pinkish brown patches with spider-like tendencies, the doctor may suspect the onset of CTCL.
Conditions such as follicular mucinosis, lymphomatoid papulosis, Schamberg’s disease or Woringer-Kolopp disease can also be precursors to CTCL.
If CTCL is suspected, the doctor will do a skin biopsy (a diagnostic test in which tissue or cells are removed from the body for examination under a microscope), a whole body mapping of skin lesions, a complete medical history and a physical examination, as well as complete blood count (CBC) testing, serum chemistries (including liver and renal function tests, calcium, phosphorus and uric acid) and a chest x-ray.
If the CTCL is in the premycotic and patch-phase, bland emollients, gentle skin care, topical antipruritic agents and gradual exposures to sunlight will help.
In the infiltrative plaque phase, topical mustard applications (mechlorethamine HCl) is applied daily or if PUVA photochemotherapy is suggested. PUVA therapy involves taking a drug called psoralen and then being exposed to ultraviolet A light. The drug makes the cancer cells sensitive to light and in turn, the light kills the cancer cells.
In another type of phototherapy, called extracorporeal photochemotherapy, a drug called 8-methoxypsoralen is taken, then some of the blood cells are taken from the patient’s body, put under a special UVA light and put back into the patient’s body.
In the tumor stage, a cyclic treatment method is done. In the first treatment method, a total skin electron beam (TSEB) radiation therapy is done. TSEB radiation therapy uses special high-energy rays of tiny electron particles to kill the cancer cells. The effects of this therapy will kill the existing tumors and allow the healing of the ulcerations. This therapy usually lasts only a few months. During this remission period, a second treatment method of topical chemotherapy (skin drugs) is introduced.
The condition will reoccur as either the premycotic and patch phase or infiltrative plaque phase. As stated above, the third treatment method will be bland emollients, gentle skin care, topical antipruritic agents, and gradual exposures to sunlight if the patch phase is present, or topical mustard applications and PUVA photochemotherapy if the plaque phase is present. As the condition progresses, the treatment starts all over again.
Hypercalcemia occurs in up to 4% of the population in association with malignancy, primary hyperparathyroidism, ingestion of excessive calcium and/or vitamin D, ectopic production of 1,25-dihydroxyvitamin D [1,25(OH)2D], and impaired degradation of 1,25(OH)2D. The ingestion of excessive amounts of vitamin D3 (or vitamin D2) results in hypercalcemia and hypercalciuria due to the formation of supraphysiological amounts of 25-hydroxyvitamin D [25(OH)D] that bind to the vitamin D receptor, albeit with lower affinity than the active form of the vitamin, 1,25(OH)2D, and the formation of 5,6-trans 25(OH)D, which binds to the vitamin D receptor more tightly than 25(OH)D. In patients with granulomatous disease such as sarcoidosis or tuberculosis and tumors such as lymphomas, hypercalcemia occurs as a result of the activity of ectopic 25(OH)D-1-hydroxylase (CYP27B1) expressed in macrophages or tumor cells and the formation of excessive amounts of 1,25(OH)2D. Recent work has identified a novel cause of non-PTH-mediated hypercalcemia that occurs when the degradation of 1,25(OH)2D is impaired as a result of mutations of the 1,25(OH)2D-24-hydroxylase cytochrome P450 (CYP24A1). Patients with biallelic and, in some instances, monoallelic mutations of the CYP24A1 gene have elevated serum calcium concentrations associated with elevated serum 1,25(OH)2D, suppressed PTH concentrations, hypercalciuria, nephrocalcinosis, nephrolithiasis, and on occasion, reduced bone density. Of interest, first-time calcium renal stone formers have elevated 1,25(OH)2D and evidence of impaired 24-hydroxylase-mediated 1,25(OH)2D degradation. We will describe the biochemical processes associated with the synthesis and degradation of various vitamin D metabolites, the clinical features of the vitamin D-mediated hypercalcemia, their biochemical diagnosis, and treatment.
Dr. Weeks’ Comment: Inexcusably, when patients are referred or self-refer to me from nationally renown cancer cancer centers like Mass General, Johns Hopkins, MD Anderson etc over the past 20 years, the oncologists there NEVER did a 25-OH D3 test. How many peer-reviewed scientific articles at PubMed teach about the causal relationship between low vitamin D3 and Cancer? Only 10,369!
Vitamin D Deficiency Elevates Colorectal Cancer Risk
David A. Johnson, MD
November 15, 2018
Hello. I’m Dr David Johnson, professor of medicine and chief of gastroenterology at Eastern Virginia Medical School in Norfolk, Virginia. Welcome back to another GI Common Concerns.
How many of you talk to your patients about vitamin D as a supplement? My message for you today is that I think we should. I certainly have changed my practice to reflect that.
We traditionally recognize vitamin D as the key vitamin for regulation of bone metabolism and homeostasis, but I want you to think out of the box here. This is incredibly important because vitamin D has a profound effect on the immune system and the intestinal barrier function. We know that vitamin D receptors regulate an active metabolite of vitamin D highly expressed in both the small and large bowel. It’s critical to regulatory actions in the gut, as it relates to proliferation and differentiation, intestinal barrier function, innate immunity, and host response. We know that vitamin D expression declines in particular as it relates to late-stage colon cancer, and it’s absent in colorectal cancer metastasis.[1,2]
Vitamin D affects the microbiome. There’s a mechanistic role in T-cell trafficking and a significant effect as it relates to the immune function. Regarding the potential for promotion of synthesis and the bad things that upregulate cancers and inflammation, we know that vitamin D actually inhibits the response of tumor necrosis factor-alpha. There’s an anti-inflammatory response with cytokine interleukin-10.[1,2]
In mouse models with vitamin D receptor overexpression, you actually can reduce the animal-related colitis. If you knock out that receptor, they get spontaneous enterocolitis. If you see this knockout in humans, they really don’t respond well to any therapy other than stem cell transplant.
Vitamin D Levels and Colorectal Cancer
I wanted to share with you an article that is going to be published in the Journal of National Cancer Institute in 2019, but I think it’s ready for primetime and needs to be understood now. It relates to the risk reduction for vitamin D and potential for vitamin D replacement.
This new study supports the idea that vitamin D deficiency makes a difference. Researchers pooled data from 17 study cohorts (5706 colorectal cancer patients and 7107 controls) to determine colorectal cancer risk at various ranges of vitamin D. They used the traditional measure for vitamin D deficiency of < 30 nmol/L. The threshold for sufficient bone health is around 50 to < 62.5 nmol/L. Vitamin D levels in this range were associated with a risk reduction for colorectal cancer of 19%, while those in the range of 87.5 to < 100 nmol/L were associated with a 27% risk reduction.
The results essentially show that the more vitamin D you get, the better. However, there seemed to be a plateau effect at 100 nmol/L. It didn’t mean that more was better forever; there wasn’t a linear relationship. Nonetheless, it raises the bar for vitamin D supplementation in our patients.
Putting It Into Practice
I’ve also used supplementation in patients with diverticulitis, which we know to occur more frequently in patients with lower vitamin D. When you get into some of the anti-inflammatory effects of vitamin D on proliferation, differentiation, barrier function, and immune response, it makes sense to start looking at this in inflammatory/infectious disease as well.
In summary, vitamin D is really essential in homeostasis and signaling. It affects the microbiome and has a direct effect on host intestinal inflammation. We do know that this certainly plays out in inflammatory bowel disease.
It remains to be determined whether supplementation makes a big difference as far as clinical outcomes. However, to me, there’s clear evidence that it modulates inflammation, maintains epithelial integrity, and reduces intestinal proliferation. In my practice, it’s ready for primetime. I think it should be in yours as well.
Start to look at supplementation; perhaps measure the patient’s vitamin D levels, and monitor and target it in patients—particularly those at risk. I do think this represents translational, bench-to-bedside research that is ready for primetime now.
I hope this leads you in the next discussion with your patients about ways to use vitamin D beyond bone homeostasis.
Special Issue: Yeasts as a Model for Human Diseases Volume 10, Issue 8, pages 1060-1069, December 2010
The ultimate goal of therapeutic vaccines is to activate and exploit the patient’s own immune system to vigorously and dynamically seek and eradicate established malignant or virally infected cells. Therapeutic vaccines also offer the potential for preventing disease recurrence. Saccharomyces cerevisiae-based vaccines, where the yeast is engineered to express viral or tumor antigens, represent an ideal therapeutic approach due to their ability to stimulate tumor- or viral-specific CD4+ and CD8+ T-cell responses that are capable of reducing disease burden. This review describes preclinical and clinical studies supporting the development of S. cerevisiae-based therapeutic vaccines for the treatment of cancer and viral diseases, as well as multimodal strategies in which therapeutic vaccines are combined with cytotoxic drugs to achieve a greater clinical response.
Saccharomyces cerevisiae, commonly known as baker’s yeast, is a nonpathogenic yeast strain mainly used in the making of beer and bread. It is the first eukaryotic organism whose genome was sequenced and has since become a preclinical model and valuable tool for unraveling the fundamental cellular processes in higher eukaryotes (Galao et al., 2007). Saccharomyces cerevisiae is an effective vector in therapeutic vaccines. Stubbs et al. (2001) have demonstrated that whole recombinant S. cerevisiae expressing foreign antigens can activate dendritic cells (DCs), elicit robust antigen-specific cytotoxic T lymphocyte (CTL) responses, and confer protective cell-mediated immunity against tumor challenge in mice (Stubbs et al., 2001). Lu et al. (2004) demonstrated that a yeast-based vaccine can generate antigen-specific immune responses independent of the viability of the yeast itself. Additionally, it has been demonstrated that heat-killed and live yeast elicit equivalent protective immunity (Franzusoff et al., 2005). These findings, and further studies performed by our laboratory and others, make heat-killed S. cerevisiae an attractive vaccine vehicle, offering many key benefits such as: (1) the ability to express one or more antigens; (2) cost-effectiveness in large-scale manufacturing; (3) expression of cell-surface ligands (”˜danger signals’) that lead to DC maturation without the need for additional adjuvants; (4) efficient antigen presentation via major histocompatibility complex (MHC) class I and class II pathways, generating antigen-specific T-cell immune responses; (5) lack of yeast-induced host-neutralizing immune responses, allowing multiple vaccinations; and (6) the ability to mount immune responses and protective immunity similar to those of live yeast, eliminating the potential safety risks associated with the use of live cells, especially in immunocompromised patients (Franzusoff et al., 2005; Munson et al., 2008). Here, we review multiple preclinical and clinical studies supporting the use of heat-killed whole recombinant S. cerevisiae (hereafter referred to simply as yeast) as a therapeutic vaccine to treat cancer and infectious diseases.
The goal of prophylactic vaccines is to prevent infectious diseases by activating humoral immune responses and subsequently producing neutralizing antibodies capable of blocking pathogens from infecting host cells. In contrast, therapeutic vaccines seek to eliminate abnormal cells (such as virally infected or malignant cells) by generating T-cell-mediated immunity. Elimination of established abnormal cells via a therapeutic vaccine is largely dependent on cell-mediated cytotoxicity executed by CD8+ CTLs. Ideally, however, a therapeutic vaccine must also be able to induce CD4+ T helper responses, because CD4+ T cells can release numerous immunomodulatory cytokines to further drive the generation and proliferation of the robust CD8+ CTL responses essential to the efficacy of a therapeutic vaccine.
Although it is nonpathogenic, yeast has been shown to induce immunologic responses in mammals and is avidly taken up by DCs and macrophages (Fig. 1) (Stubbs et al., 2001; Heintel et al., 2003). The phagocytosis of yeast by DCs is driven by the immunogenicity of yeast cell-wall components, such as Î²-1,3-d-glucan and mannan, that can transmit ”˜danger signals’ normally associated with microbial infection. These components have strong adjuvant properties and can be detected by pattern recognition receptors such as Toll-like receptors and mannan receptors on DCs (Munson et al., 2008). DCs are the most efficient antigen-presenting cells (APCs). Their unique ability to efficiently process antigens to MHC class I and class II pathways through cross-presentation makes them crucial for initiating both humoral responses and cell-mediated cytotoxicity. Therefore, once inside the host, yeast expressing viral or tumor antigen is easily recognized and subjected to receptor-mediated phagocytosis by DCs for presentation to both MHC class I and class II pathways.
Figure 1. ”‚Proposed mechanism of action of the yeast-CEA vaccine. After injection, yeast-CEA is avidly taken up by DCs and macrophages, driven by the immunogenicity of yeast cell-wall components that transmit ”˜danger signals’ normally associated with microbial infection. The DCs efficiently process antigens to MHC class I and class II pathways through cross-presentation and initiate T cells involved in cell-mediated cytotoxicity. Adapted from GlobImmune, Inc., Louisville, CO.
Yeast expressing tumor or viral antigens can be degraded in proteasomes, presented through MHC class I, and recognized by CD8+ CTLs. This subsequently induces the proliferation, maturation, and activation of antigen-specific CD8+ CTLs. Yeast can also be degraded in endosomes, presented to MHC class II, and recognized by CD4+ T helper cells. Engagement of the T-cell receptor and the peptide-MHC complex is the first signal necessary to activate T-cell immunity. The second signal involves the interaction of DC costimulatory molecules with their ligands expressed on the T cell. Yeast vaccine enhances both signals, as increased expression of both MHC class I and class II molecules and increased expression of costimulatory molecules on DCs have been observed (Bernstein et al., 2008; Remondo et al., 2009). In sum, the use of yeast-based vaccines leads to the recruitment and activation of antigen-specific CD4+ and CD8+ T cells (Stubbset al., 2001; Franzusoff et al., 2005; Munson et al., 2008).
The activation of CD4+ and CD8+ T cells is required to induce the therapeutic immune responses needed to treat malignant or virally infected cells. Specifically, CD4+ T cells release immunostimulatory Th-1 type inflammatory cytokines, such as interleukin-2 (IL-2), interferon-Î³ (IFN-Î³), and tumor necrosis factor-Î± (TNF-Î±), that further induce the activation and proliferation of CD8+ CTLs. These CD8+CTLs kill abnormal cells via two main mechanisms of action. The first is the release of the cytotoxins perforin and granzymes. Perforin forms holes in the target cell’s plasma membrane, allowing granzymes to enter and kill the target cell. Granzymes activate caspase enzymes and induce the production of reactive oxygen species, both of which lead to cell death. Secondly, CD8+ CTLs kill target cells through the interaction of surface protein Fas ligands on activated CTLs and Fas receptors on target cells, which also induces apoptotic cell death (Stenger et al., 1998). Yeast is thus able to activate and inducing maturation of DCs, leading to the generation of antigen-specific CD4+ and CD8+ T-cell responses capable of killing virally infected or malignant cells.
Yeast-based vaccines for cancer immunotherapy
For a therapeutic yeast-based vaccine to effectively generate the CD8+ CTLs necessary to recognize and kill malignant cells, the yeast must be engineered to express the tumor-specific or tumor-associated antigens selectively expressed or overexpressed on malignant cells. Numerous tumor antigens are currently being investigated in preclinical and clinical studies. However, the yeast-based cancer vaccines reviewed here target two main tumor antigens: yeast-ras targets ras oncogenes and yeast-carcinoembryonic antigen (CEA) targets oncofetal CEA.
Ras, a family of genes that activates the signaling pathway for cell proliferation, acts downstream of receptor tyrosine kinases such as epidermal growth factor receptor (Lu et al., 2004). Ras activation leads to cell proliferation, differentiation, and survival. Mutations in the ras proto-oncogene family, such as K-, H-, or N-ras, are common and are consistently expressed in many types of solid tumors, including pancreatic (90-100%), colorectal (30-50%), ovarian (20-25%), melanoma (50%), and nonsmall-cell lung (20-30%) cancers (Franzusoff et al., 2005).
In 2004, Lu and colleagues generated whole recombinant yeast-ras vaccines expressing mammalian mutant K-ras proteins and tested their ability to generate the immune responses required for tumor killing in carcinogen-induced lung tumors in mice. Mice exposed to urethane, a chemical carcinogen, develop single amino acid mutations in codon 61 in the ras oncoprotein. Following urethane exposure, lung hyperplasias occur within 2 weeks, adenomas occur in approximately 5 weeks, adenocarcinomas by 16 weeks, and death from respiratory failure within 12 months (Forkert et al., 1992; Horio et al., 1996; Lu et al., 2004). Studies have been conducted with yeast vaccines expressing different mammalian ras proteins, representing some of the most frequent mutations responsible for the constitutive activation of ras oncoprotein. The use of these vaccines to immunize mice in a carcinogen-induced lung tumor model led to two important findings (Bos, 1989; Lu et al., 2004): (1) yeast-ras vaccines can generate regression of established ras mutation-bearing lung tumors in a dose-dependent and antigen-specific manner and (2) dosing regimens that include multiple boosts lead to optimum tumor killing (Lu et al., 2004; Franzusoff et al., 2005). The safety of the yeast-ras vaccine was further evaluated in five preclinical toxicity studies in a rabbit model. Rabbits were injected weekly with 0.5-100 yeast units (YU) for up to 13 weeks. Histopathologic analyses revealed no major side effects in the rabbits. Increased levels of circulatory neutrophils were observed, along with minor injection-site reactions that resolved on their own after 2 weeks (Munson et al., 2008).
These preclinical findings led to the initiation of an open-label, dose-escalation, phase I clinical trial of monotherapy with yeast-ras. The trial enrolled 33 patients with advanced ras mutation+ pancreatic, colorectal, and nonsmall-cell lung cancer (NSCLC). All patients underwent ras genotyping to match each patient’s individual mutation with the appropriate yeast-ras vaccine. Most patients had metastatic disease at the time of enrollment and had received an average of three previous therapy regimens before participating in this phase I trial. Subjects received 0.1, 1, 5, 10, 20, or 40 YU of the mutation-matched yeast-ras vaccine (Q61R+Q61L+G12V or Q61R+Q61L+G12C or Q61R+Q61L+G12D), administered subcutaneously for 5 weeks. The overall safety, injection-site reactions, and antigen-specific immune responses were monitored. After 5 weeks of yeast-ras vaccine therapy, no dose-limiting toxicities, therapy-related serious adverse events, or clinically significant laboratory abnormalities were observed at any of the dose levels tested. Approximately 90% of subjects exhibited ras-specific T-cell responses, as demonstrated by lymphocyte proliferation and/or intracellular cytokine staining assays (Franzusoff et al., 2005; Munson et al., 2008).
Oncofetal CEA, the first cell-surface tumor-associated antigen to be described (Gold & Freedman, 1965; Huang & Kaufman, 2002), is a 180-kDa glycoprotein normally expressed in limited areas of the adult human body. However, CEA is overexpressed in nearly 50% of all human tumor types and 80-90% of most colorectal cancers. In cancer patients, significantly elevated cell-surface expression of CEA is associated with more advanced disease and with increased rates of recurrence compared with patients with lower levels of CEA expression. Additionally, upon transformation of epithelial cells, CEA can lose its apical polarity on the cell surface and thus be secreted into the capillaries. It can then be used as a serologic circulating tumor marker in certain cancers (Huang & Kaufman, 2002).
CEA is an attractive target for immunotherapy because it is expressed minimally in normal tissues, but overexpressed in a wide variety of malignant epithelial tissues. Our laboratory has recently developed a recombinant yeast vaccine expressing human CEA antigen (yeast-CEA) (Bernstein et al., 2008).
Yeast vaccine combined with chemotherapy
In recent years, the field of cancer immunotherapy has achieved several significant milestones due to the success of trials of the cancer vaccines sipuleucel-T and PROSTVAC-VF. Sipuleucel-T is an autologous DC-based vaccine. In a recent phase III clinical trial, patients with advanced prostate cancer (n=225) randomized to receive sipuleucel-T demonstrated a 33% reduction in the risk of death and a significant increase in the median survival of 4.3 months compared with patients receiving placebo (23.2 vs. 18.9) (Higano et al., 2009). PROSTVAC-VF is a viral-based vaccine composed of two recombinant viral vectors, each encoding transgenes for prostate-specific antigen, and three immune costimulatory molecules (B7.1, ICAM-1, and LFA-3). Recently published data from PROSTVAC-VF phase II trials in metastatic castration-resistant prostate cancer (n=125) demonstrate that this vaccine is well tolerated and is associated with a 44% reduction in the death rate and an 8.5-month improvement in the median overall survival compared with placebo (Kantoff et al., 2010).
Although both the sipuleucel-T and the PROSVAC-VF clinical trials have yielded significant clinical benefits, a mounting body of evidence suggests that cancer vaccines would probably be of the greatest benefit in the adjuvant or the neoadjuvant setting and/or where tumor burden is minimal (Schlom et al., 2007; Gulley et al., 2009). Large tumors have multiple, often redundant pathways to escape immune surveillance and mediate immune suppression, making them poor targets for immunotherapy. There is thus increasing interest in combining cancer vaccines with conventional standard-of-care (SOC) therapies, such as chemotherapy, that directly reduce tumor burden (Emens & Jaffee, 2005; Gulley et al., 2009). Chemotherapeutic agents are known to be immunosuppressive; therefore, the traditional thinking has been that chemotherapy and immunotherapy would not be an effective combination. Yet, while counterintuitive, recent evidence suggests that some chemotherapeutic agents can work synergistically to augment the antitumor effect of some immunotherapeutic agents, and thus generate superior antitumor activity than either modality alone (Zitvogel et al., 2008; Gulley et al., 2009; Higgins et al., 2009). The induction of tumor-cell apoptosis by certain cytotoxic agents not only activates DCs but also provides them with an increased supply of tumor-specific antigens for presentation and cross-presentation to T cells. Additionally, several other immunostimulatory properties of cytotoxic drugs can work with immunotherapeutic agents to generate more robust immune-mediated cytotoxicity against malignant cells (Lake & Robinson, 2005). Furthermore, chemotherapy drugs are metabolized and eliminated, while the tumor-specific immunity induced by a therapeutic cancer vaccine is active, dynamic, and, more importantly, able to persist long after vaccination. Cancer vaccines thus have tremendous potential to confer protection against tumor recurrence. Altogether, the combination of chemotherapy and immunotherapy (particularly cancer vaccines) has many attractive benefits (Lake & Robinson, 2005; Higgins et al., 2009). Ultimately, optimal dosage and scheduling of immunotherapy and chemotherapy are pivotal to the success of this multimodal therapy.
Yeast-ras and gemcitabine
Gemcitabine, a nucleoside analog, has been SOC for patients with advanced, inoperable pancreatic cancer for the last decade. Importantly, gemcitabine has been shown to modulate immune responses by reducing the frequency of myeloid suppressor cells and enhancing DC-dependent cross-presentation of tumor antigens to T cells (Nowak et al., 2003a; Zitvogel et al., 2008). The immunostimulatory benefits of gemcitabine have been demonstrated by enhanced tumor-specific CTLs and overall improvement in objective response rates in patients with pancreatic cancer, NSCLC, and colon cancer who received a combination of vaccines and recombinant IL-2 and granulocyte-macrophage colony-stimulating factor (Nowak et al., 2003b; Levitt et al., 2004; Plate et al., 2005; Zitvogel et al., 2008). Ongoing phase II clinical trials are evaluating the effect of combining yeast-ras and chemotherapy. A phase II double-blind, placebo-controlled, multicenter trial comparing yeast-ras vaccine plus six cycles of gemcitabine adjuvant vs. gemcitabine alone in patients with nonmetastatic, resected, ras-mutation+ pancreatic cancer is ongoing and carrying out recruitment (NCI Clinical Trial 00300950, http://www.clinicaltrials.gov). An important enrollment criterion is that patients’ tumor resection status must either be R0 (resection margin completely free of microscopic disease) or R1 (evidence of microscopic disease at the resection margin, but no macroscopic disease). This small tumor burden provides more time for both chemotherapy and immunotherapy to be efficacious. Prospective ras genotyping is performed to identify and match a patient’s specific ras mutation with a yeast-ras vaccine. After tumor resection and before the initiation of gemcitabine therapy, patients receive three weekly doses of mutation-matched yeast-ras vaccine or placebo. Patients then receive six cycles of gemcitabine, with monthly injections of yeast-ras vaccine or placebo administered between gemcitabine cycles. The primary endpoint of this trial is recurrence-free survival, with overall survival as a key secondary endpoint (Brittonet al., 2009). This trial will determine whether gemcitabine and the yeast-ras vaccine can work synergistically to provide a meaningful clinical benefit to patients with ras+ pancreatic cancers.
Yeast-CEA and cisplatin/vinorelbine
Cisplatin is a platinum-based chemotherapy drug that causes DNA cross-linking, interferes with mitosis, and results in apoptosis. It is used to treat various types of cancers, including NSCLC. Vinorelbine is another antimitotic chemotherapeutic drug used in NSCLC. Combinations of both drugs have been used as adjuvant chemotherapy following surgery in patients with NSCLC and have been shown to increase 5-year survival by 10-15% compared with no chemotherapy treatment (Gameiro et al., 2008). A recent preclinical study in our laboratory demonstrated that appropriate scheduling of yeast-CEA and cisplatin/vinorelbine administration is crucial in this multimodal therapy (Gameiro et al., 2008). The study showed that the yeast-CEA vaccine was most effective when not administered concurrently with cisplatin and vinorelbine, as both drugs can modulate the expression of immune cells. In particular, the study demonstrated a significant reduction in the population of CD4+ and CD8+ T cells, natural killer (NK) cells, and B cells 2 days after the administration of cisplatin/vinorelbine, compared with control-treated groups. However, after about 4 days, cell populations returned to baseline, indicating that this effect is transient and that these cells proliferated around 3 or 4 days after drug administration. The population of T-regulatory cells (Tregs), a subpopulation of T cells that suppresses the activation of the immune system and thereby maintains immune system homeostasis and tolerance to self-antigens, was also significantly reduced 2 days after the administration of cisplatin/vinorelbine. Interestingly, it appeared that the Treg population was more adversely affected by these drugs, because the cells did not return to baseline on day 4. This result demonstrated that appropriate scheduling is important for both the yeast-CEA vaccine and chemotherapeutic drugs. Clearly, the first yeast-CEA vaccination should be administered before chemotherapy is initiated, to prime and activate the immune system. A second booster injection of yeast-CEA should be administered along with cisplatin/vinorelbine to take advantage of the approximately 3- to 4-day window when CD4+ and CD8+ T cells, NK cells, and B cells are proliferating and the Treg population is reduced. Using this scheduling strategy in an NSCLC mouse model demonstrated that the combination of cisplatin/vinorelbine and yeast-CEA vaccination was superior to either modality alone. Given this encouraging result, a phase II trial of yeast-CEA in combination with cisplatin/vinorelbine in patients with NSCLC is being planned. Patients with stages I-III NSCLC will undergo resection, and then receive three cycles of yeast-CEA during the 6-week rest period before adjuvant cisplatin/vinorelbine regimens. Patients will receive a yeast-CEA boost once a month during or between cisplatin/vinorelbine regimens for the duration of this trial. The primary endpoint is time to progression, with a secondary endpoint of overall survival and CEA-specific T-cell responses.
While prophylactic vaccines provide protection against infectious diseases, therapeutic vaccines seek to eliminate established infected or malignant cells and prevent future recurrence. Yeast is a promising therapeutic vaccine vehicle due to its ability to generate robust cellular immune responses against malignant or virally infected cells.This review looked at two cancer vaccines that use yeast: yeast-ras and yeast-CEA. The yeast-ras vaccine demonstrated preclinical antitumor activity and induction of ras-specific T-cell responses in a majority of patients in a phase I trial (Franzusoff et al., 2005; Munson et al., 2008). A phase II trial of the combination of yeast-ras and gemcitabine is ongoing (Munson et al., 2008). Similarly, preclinical data on yeast-CEA led to the initiation of a phase I clinical trial evaluating the yeast-CEA vaccine in patients with CEA+ tumors. A phase II trial of yeast-CEA plus cisplatin/vinorelbine in patients with NSCLC is ongoing and recruiting patients (Gameiro et al., 2008). Additionally, vaccination of HCV-infected patients with yeast-HCV led to the induction of HCV-specific T-cell responses (Schiff et al., 2007; McHutchison et al., 2009). Together, these data demonstrate that yeast can direct a therapeutic immune response to potentially improve outcomes for patients with cancer or chronic infections.
In the future, therapeutic yeast vaccines may be used to target other cancers or infectious diseases, such as melanoma and HIV (Barron et al., 2006; Riemann et al., 2007). As SOC treatments for cancers and infectious diseases change, there is a rationale for the strategic combination of treatments such as small molecule inhibitors, radiotherapy, antiangiogenesis, and hormone therapy with yeast vaccine to optimize clinical outcomes (Reits et al., 2006; Arlen et al., 2007; Chakraborty et al., 2008a, b; Hodge et al., 2008; Ferrara et al., 2009; Higgins et al., 2009; Kamrava et al., 2009). In addition, it has been shown that concurrent administration of yeast- and viral-based vaccines targeting the same antigen induces a more diverse T-cell population that leads to enhanced antitumor efficacy. This provides the rationale for future clinical studies investigating the concurrent administration of different vaccine platforms targeting a single antigen to enhance antigen-specific immune responses (Boehm et al., 2010). Finally, accumulating evidence suggests that using a cancer vaccine in the early stages of disease is much more effective at inducing antitumor immune responses and improving the overall survival compared with the use of vaccine in later-stage disease (Gulley et al., 2009). Given the favorable safety profile of yeast, treatment of cancer patients at earlier stages of disease would appear to be a reasonable approach.
Bromelain belongs to a group of protein digesting enzymes obtained commercially from the fruit or stem of pineapple. Fruit bromelain and stem bromelainare prepared differently and they contain different enzymatic composition. “Bromelain” refers usually to the “stem bromelain.” Bromelain is a mixture of different thiol endopeptidases and other components like phosphatase, glucosidase, peroxidase, cellulase, escharase, and several protease inhibitors. In vitro and in vivo studies demonstrate that bromelain exhibits various fibrinolytic, antiedematous, antithrombotic, and anti-inflammatory activities. Bromelain is considerably absorbable in the body without losing its proteolytic activity and without producing any major side effects. Bromelain accounts for many therapeutic benefits like the treatment of angina pectoris, bronchitis, sinusitis, surgical trauma, and thrombophlebitis, debridement of wounds, and enhanced absorption of drugs, particularly antibiotics. It also relieves osteoarthritis, diarrhea, and various cardiovascular disorders. Bromelain also possesses some anticancerous activities and promotes apoptotic cell death. This paper reviews the important properties and therapeutic applications of bromelain, along with the possible mode of action.
Pineapple is the common name of Ananas comosus (syns. A. sativus, Ananassa sativa, Bromelia ananas, B. comosa). Pineapple is the leading edible member of the family Bromeliaceae, grown in several tropical and subtropical countries including Philippines, Thailand, Indonesia, Malaysia, Kenya, India, and China. It has been used as a medicinal plant in several native cultures  and these medicinal qualities of pineapple are attributed to bromelain (EC 22.214.171.124), which is a crude extract from pineapple that contains, among other compounds, various closely related proteinases, exhibiting various fibrinolytic, antiedematous, antithrombotic, and anti-inflammatory activities in vitro and in vivo. Bromelain has been chemically known since 1875 and is used as a phytomedical compound . Bromelain concentration is high in pineapple stem, thus necessitating its extraction because, unlike the pineapple fruit which is normally used as food, the stem is a waste byproduct and thus inexpensive . A wide range of therapeutic benefits have been claimed for bromelain, such as reversible inhibition of platelet aggregation, sinusitis, surgical traumas , thrombophlebitis, pyelonephriti angina pectoris, bronchitis , and enhanced absorption of drugs, particularly of antibiotics [6, 7]. Several studies have been carried out indicating that bromelain has useful phytomedical application. However, these results are yet to be amalgamated and critically compared so as to make out whether bromelain will gain wide acceptance as a phytomedical supplement . Bromelain acts on fibrinogen giving products that are similar, at least in effect, to those formed by plasmin . Experiment in mice showed that antacids such as sodium bicarbonate preserve the proteolytic activity of bromelain in the gastrointestinal tract . Bromelain is considered as a food supplement and is freely available to the general public in health food stores and pharmacies in the USA and Europe . Existing evidence indicates that bromelain can be a promising candidate for the development of future oral enzyme therapies for oncology patients . Bromelain can be absorbed in human intestines without degradation and without losing its biological activity [12, 13].
2. Biochemical Properties
The crude aqueous extract from stem and fruit of pineapple is known as bromelain. It is a mixture of different thiol endopeptidases and other components like phosphatases, glucosidase, peroxidases, cellulases, glycoproteins, carbohydrates, and several protease inhibitors . Stem bromelain (EC.126.96.36.199) is different from fruit bromelain (EC.188.8.131.52) . The enzymatic activities of bromelain comprise a wide spectrum with pH range of 5.5 to 8.0 . Different protein fractions were obtained by mean of various “biochemical techniques as sodium dodecyl sulphate polyacrylamide gel electrophoresis” (SDS-PAGE), isoelectric focusing (IEF), and multicathodal-PAGE [17, 18]. Nowadays, bromelain is prepared from cooled pineapple juice by centrifugation, ultrafiltration, and lyophilization. The process yields a yellowish powder, the enzyme activity of which is determined with different substrates such as casein (FIP unit), gelatin (gelatin digestion units), or chromogenic tripeptides [7, 17, 19, 20].
3. Absorption and Bioavailability
The body can absorb significant amount of bromelain; about 12 gm/day of bromelain can be consumed without any major side effects . Bromelain is absorbed from the gastrointestinal tract in a functionally intact form; approximately 40% of labeled bromelain is absorbed from intestine in high molecular form . In a study carried out by Castell et al.  bromelain was detected to retain its proteolytic activity in plasma and was also found linked with alpha 2-macroglobulin and alpha1-antichymotrypsin, the two antiproteinases of blood. In a recent study, it was demonstrated that 3.66 mg/mL of bromelain was stable in artificial stomach juice after 4 hrs of reaction and also 2.44 mg/mL of bromelain remained in artificial blood after 4 hrs of reaction .
4. Medicinal Uses
Clinical studies have shown that bromelain may help in the treatment of several disorders.
4.1. Effects of Bromelain on Cardiovascular and Circulation
Bromelain prevents or minimizes the severity of angina pectoris and transient ischemic attack (TIA). It is useful in the prevention and treatment of thrombophlebitis. It may also break down cholesterol plaques and exerts a potent fibrinolytic activity. A combination of bromelain and other nutrients protect against ischemia/reperfusion injury in skeletal muscle . Cardiovascular diseases (CVDs) include disorders of the blood vessels and heart, coronary heart disease (heart attacks), cerebrovascular disease (stroke), raised blood pressure (hypertension), peripheral artery disease, rheumatic heart disease, heart failure, and congenital heart disease . Stroke and heart disease are the main cause of death, about 65% of people with diabetes die from stroke or heart disease. Bromelain has been effective in the treatment of CVDs as it is an inhibitor of blood platelet aggregation, thus minimizing the risk of arterial thrombosis and embolism . King et al.  reported that administration of medication use to control the symptoms of diabetes, hypertension, and hypercholesteromia increased by 121% from 1988–1994 to 2001–2006 (P < 0.05) and was greater for patients with fewer healthy lifestyle habits. Bromelain supplement could reduce any of risk factors that contribute to the development of cardiovascular disease. In a recent research, Bromelain was found to attenuate development of allergic airway disease (AAD), while altering CD4+ to CD8+T lymphocyte populations. From this reduction in AAD outcomes it was suggested that bromelain may have similar effects in the treatment of human asthma and hypersensitivity disorders . In another study, carried out by Juhasz et al., Bromelain was proved to exhibit the ability of inducing cardioprotection against ischemia-reperfusion injury through Akt/Foxo pathway in rat myocardium .
4.2. Bromelain Relieves Osteoarthritis
Osteoarthritis is the most common form of arthritis in Western countries; in USA prevalence of osteoarthritis ranges from 3.2 to 33% dependent on the joint . A combination of bromelain, trypsin, and rutin was compared to diclofenac in 103 patients with osteoarthritis of the knee. After six weeks, both treatments resulted in significant and similar reduction in the pain and inflammation . Bromelain is a food supplement that may provide an alternative treatment to nonsteroidal anti-inflammatory drug (NSAIDs) . It plays an important role in the pathogenesis of arthritis . Bromelain has analgesic properties which are thought to be the result of its direct influence on pain mediators such as bradykinin [33, 34]. The earliest reported studies investigating bromelain were a series of case reports on 28 patients, with moderate or severe rheumatoid or osteoarthritis .
4.3. Effect of Bromelain on Immunogenicity
Bromelain has been recommended as an adjuvant therapeutic approach in the treatment of chronic inflammatory, malignant, and autoimmune diseases . In vitro experiments have shown that Bromelain has the ability to modulate surface adhesion molecules on T cells, macrophages, and natural killer cells and also induce the secretion of IL-1β, IL-6, and tumour necrosis factor α (TNFα) by peripheral blood mononuclear cells (PBMCs) [37–43]. Bromelain can block the Raf-1/extracellular-regulated-kinase- (ERK-) 2 pathways by inhibiting the T cell signal transduction . Treatment of cells with bromelain decreases the activation of CD4 (+) T cells and reduce the expression of CD25 . Moreover, there is evidence that oral therapy with bromelain produces certain analgesic and anti-inflammatory effects in patients with rheumatoid arthritis, which is one of the most common autoimmune diseases .
4.4. Effect of Bromelain on Blood Coagulation and Fibrinolysis
Bromelain influences blood coagulation by increasing the serum fibrinolytic ability and by inhibiting the synthesis of fibrin, a protein involved in blood clotting . In rats, the reduction of serum fibrinogen level by bromelain is dose dependent. At a higher concentration of bromelain, both prothrombin time (PT) and activated partial thromboplastin time (APTT) are markedly prolonged . In vitro and in vivostudies have suggested that bromelain is an effective fibrinolytic agent as it stimulates the conversion of plasminogen to plasmin, resulting in increased fibrinolysis by degrading fibrin [49, 50].
4.5. Effects of Bromelain on Diarrhea
Evidence has suggested that bromelain counteracts some of the effects of certain intestinal pathogens like Vibrio cholera and Escherichia coli, whose enterotoxin causes diarrhoea in animals. Bromelain appears to exhibit this effect by interacting with intestinal secretory signaling pathways, including adenosine 3′ : 5′-cyclic monophosphatase, guanosine 3′ : 5′-cyclic monophosphatase, and calcium-dependent signaling cascades . Other studies suggest a different mechanism of action. In E. coli infection, an active supplementation with bromelain leads to some antiadhesion effects which prevent the bacteria from attaching to specific glycoprotein receptors located on the intestinal mucosa by proteolytically modifying the receptor attachment sites [52, 53].
4.6. Effect of Bromelain on Cancer Cells
Recent studies have shown that bromelain has the capacity to modify key pathways that support malignancy. Presumably, the anticancerous activity of bromelain is due to its direct impact on cancer cells and their microenvironment, as well as on the modulation of immune, inflammatory, and haemostatic systems . Most of the in vitro and in vivo studies on anticancer activity of bromelain are concentrated on mouse and human cells, both cancerous and normal, treated with bromelain preparations. In an experiment conducted by Beez et al chemically induced mouse skin papillomas were treated with bromelain and they observed that it reduced tumor formation, tumor volume and caused apoptotic cell death . In one study related to bromelain treatment of gastric carcinoma Kato III cell lines, significant reduction of cell growth was observed  while in another study bromelain reduced the invasive capacity of glioblastoma cells and reduced de novo protein synthesis . Bromelain is found to increase the expression of p53 and Bax in mouse skin, the well-known activators of apoptosis . Bromelain also decreases the activity of cell survival regulators such as Akt and Erk, thus promoting apoptotic cell death in tumours. Different studies have demonstrated the role of NF-κB, Cox-2, and PGE2 as promoters of cancer progression. Evidence shows that the signaling and overexpression of NF-κB plays an important part in many types of cancers [57, 58]. Cox-2, a multiple target gene of NF-κB, facilitates the conversion of arachidonic acid into PGE2 and thus promotes tumour angiogenesis and progression [59, 60]. It is considered that inhibiting NF-κB, Cox-2, and PGE2 activity has potential as a treatment of cancer. Bromelain was found to downregulate NF-κB and Cox-2 expression in mouse papillomas  and in models of skin tumourigenesis . Bromelain was also shown to inhibit bacterial endotoxin (LPS)-induced NF-κB activity as well as the expression of PGE2 and Cox-2 in human monocytic leukemia and murine microglial cell lines [62, 63]. Bromelain markedly has in vivo antitumoural activity for the following cell lines: P-388 leukemia, sarcoma (S-37), Ehrlich ascetic tumour, Lewis lung carcinoma, and ADC-755 mammary adenocarcinoma. In these studies, intraperitoneal administration of bromelain after 24 hours of tumour cell inoculation resulted in tumour regression .
4.7. Role of Bromelain in Surgery
Administration of bromelain before a surgery can reduce the average number of days for complete disappearance of pain and postsurgery inflammation [64, 65]. Trials indicate that bromelain might be effective in reducing swelling, bruising, and pain in women having episiotomy . Nowadays, bromelain is used for treating acute inflammation and sports injuries .
4.8. Role of Bromelain in Debridement Burns
The removal of damaged tissue from wounds or second/third degree burns is termed as debridement. Bromelain applied as a cream (35% bromelain in a lipid base) can be beneficial for debridement of necrotic tissue and acceleration of healing. Bromelain contains escharase which is responsible for this effect. Escharase is nonproteolytic and has no hydrolytic enzyme activity against normal protein substrate or various glycosaminoglycan substrates. Its activity varies greatly with different preparations . In two different enzymatic debridement studies carried out in porcine model, using different bromelain-based agents, namely, Debriding Gel Dressing (DGD) and Debrase Gel Dressing showed rapid removal of the necrotic layer of the dermis with preservation of the unburned tissues [68, 69]. In another study on Chinese landrace pigs, enzymatic debridement using topical bromelain in incised wound tracks accelerated the recovery of blood perfusion, pO2in wound tissue, controlled the expression of TNF-α, and raised the expression of TGT-β . Enzymatic debridement using bromelain is better than surgical debridement as surgical incision is painful, nonselective and exposes the patients to the risk of repeated anaesthesia and significant bleeding [71–74].
4.9. Toxicity of Bromelain
According to Taussig et al.  bromelain has very low toxicity with an LD50(lethal doses) greater than 10 g/kg in mice, rates, and rabbits. Toxicity tests on dogs, with increasing level of bromelain up to 750 mg/kg administered daily, showed no toxic effects after six months. Dosages of 1500 mg/kg per day when administered to rats showed no carcinogenic or teratogenic effects and did not provoke any alteration in food intake, histology of heart, growth, spleen, kidney, or hematological parameters . Eckert et al.  after giving bromelain (3000 FIP unit/day) to human over a period of ten days found no significant changes in blood coagulation parameters.
Bromelain has a wide range of therapeutic benefits, but the mode of its action is not properly understood. It is proved that bromelain is well absorbed in body after oral administration and it has no major side effects, even after prolonged use. All the evidences reviewed in this paper suggest that bromelain can be used as an effective health supplement to prevent cancer, diabetes, and various cardiovascular diseases in the long run.
6. Future Trends and Perspectives
Bromelain can be a promising candidate for the development of oral enzyme therapies for oncology patients. It is clear from this paper that bromelain is a multiaction enzyme; however, more research is required to understand the proper mechanism of action of bromelain so that the multiaction activities of bromelain can be harnessed efficiently.
The authors are grateful to DEAN, Department of Biotechnology, IBMER, Mangalayatan University, Aligarh, India, for providing necessary facilities and encouragement. They are also thankful to all faculty members of the Institute of Biomedical Education and Research, Mangalayatan University, Aligarh, India, for their generous help and suggestions during the paper preparation.
1. Mondal S, Bhattacharya S, Pandey JN, Biswas M. Evaluation of acute anti-inflametry effect of Ananas Comosus leaf extract in Rats. Pharmocologyonline. 2011;3:1312–1315.
2. Taussig SJ, Batkin S. Bromelain, the enzyme complex of pineapple (Ananas comosus) and its clinical application: an update. Journal of Ethnopharmacology. 1988;22(2):191–203. [PubMed]
3. Heinicke RM, Gortner WA. Stem bromelain: a new protease preparation from pineapple plants. Economic Botany. 1957;11(3):225–234.
4. Livio M, Gaetano GDe, Donati MB. Effect of bromelain of fibrinogen level, protrombin complex and platelet aggregation in the rat-a preliminary report. Drugs under Experimental and Clinical Research. 1978;1:49–53.
5. Neubauer RA. A plant protease for potentiation of and possible replacement of antibiotics. Experimental Medicine and Surgery. 1961;19:143–160. [PubMed]
6. Renzini G, Varego M. Die resorsption von tetrazyklin ingenenwart von Bromelain bei oraler application. Arzneimittel-Forschung Drug Research. 1972;2:410–412. [PubMed]
7. Maurer HR. Bromelain: biochemistry, pharmacology and medical use. Cellular and Molecular Life Sciences. 2001;58(9):1234–1245. [PubMed]
8. Tochi BN, Wang Z, Xu SY, Zhang W. Therapeutic application of pineapple protease (Bromelain): a review. Pakistan Journal of Nutrition. 2008;7(4):513–520.
9. Taussig SJ. The mechanism of the physiological action of bromelain. Medical Hypotheses. 1980;6(1):99–104. [PubMed]
10. Hale LP. Proteolytic activity and immunogenicity of oral bromelain within the gastrointestinal tract of mice. International Immunopharmacology. 2004;4(2):255–264. [PubMed]
11. Ley CM, Tsiami A, Ni Q, Robinson N. A review of the use of bromelain in cardiovascular diseases. Journal of Chinese Integrative Medicine. 2011;9(7):702–710. [PubMed]
12. Chobotova K, Vernallis AB, Majid FAA. Bromelain’s activity and potential as an anti-cancer agent: current evidence and perspectives. Cancer Letters. 2010;290(2):148–156. [PubMed]
13. Castell JV, Friedrich G, Kuhn CS, Poppe GE. Intestinal absorption of undegraded proteins in men: presence of bromelain in plasma after oral intake. American Journal of Physiology. 1997;273(1):G139–G146. [PubMed]
14. Bhattacharyya BK. Bromelain: an overview. Natural Product Radiance. 2008;7(4):359–363.
16. Yoshioka K Izutsa S, Asa Y, Takeda Y. Inactivation kineticsof enzyme pharmaceuticals in aqueous solutions. Pharmaceutical Research. 1991;4:480–485.[PubMed]
17. Harrach T, Eckert K, Schulze-Forster K, Nuck R, Grunow D, Maurer HR. Isolation and partial characterization of basic proteinases from stem bromelain. Journal of Protein Chemistry. 1995;14(1):41–52. [PubMed]
18. Napper AD, Bennet SP, Borowski M, et al. Purification and characterization of multiple forms of the pineapple-stem-derived cysteine proteinases ananain and comosain. Biochemical Journal. 1994;301(3):727–735. [PMC free article][PubMed]
19. Cooreman W. Bromelain. In: Ruyssen R, Lauwers A, editors. Pharmaceutical Enzymes- Properties and Assay Methods. Gent, Belgium: E. Story-Scientia Scientific Publishing Co.; 1978. pp. 107–121.
21. Seifert J, Ganser R, Brendel W. Absorption of a proteolytic enzyme originating from plants out of the gastro-intestinal tract into blood and lymph of rats. Zeitschrift fur Gastroenterologie. 1979;17(1):1–8. [PubMed]
22. Shiew PS, Fang YL, Majid FAA. In vitro study ofbromelain activity inartificial stomach juiceand blood. Proceedings of the 3rd International Conference on Biotechnology for the Wellness Industry; 2010; PWTC;
23. Neumayer C, Fügl A, Nanobashvili J, et al. Combined enzymatic and antioxidative treatment reduces ischemia-reperfusion injury in rabbit skeletal muscle. Journal of Surgical Research. 2006;133(2):150–158. [PubMed]
25. Heinicke RM, van der Wal L, Yokoyama M. Effect of bromelain (Ananase) on human platelet aggregation. Experientia. 1972;28(10):844–845. [PubMed]
26. King DE, Ellis TM, Everett CJ, Mainous AG. Medication use for diabetes, hypertension, and hypercholesterolemia from1988–1994 to 2001–2006. Southern Medical Journal. 2009;102(11):1127–1132. [PubMed]
27. Secor ER, Jr., William FC, Michelle MC, et al. Bromelain exerts anti-inflammatory effects in an ovalbumin-induced murin model of allergic disease. Cellular Immunology. 2005;237:68–75. [PMC free article][PubMed]
28. Juhasz B, Thirunavukkarasu M, Pant R, et al. Bromelain induces cardioprotection against ischemia-reperfusion injury through Akt/FOXO pathway in rat myocardium. American Journal of Physiology. 2008;294(3):H1365–H1370.[PMC free article][PubMed]
29. Lawrence RC, Helmich CG, Arnett F, et al. Estimates of prevalence of arthritis and selected musculoskeletal disorders in the United States. Arthritis & Rheumatism. 1998;41:778–799. [PubMed]
30. Akhtar NM, Naseer R, Farooqi AZ, Aziz W, Nazir M. Oral enzyme combination versus diclofenac in the treatment of osteoarthritis of the knee—a double-blind prospective randomized study. Clinical Rheumatology. 2004;23(5):410–415. [PubMed]
31. Brien S, Lewith G, Walker A, Hicks SM, Middleton D. Bromelain as a treatment for osteoarthritis: a review of clinical studies. Evidence-Based Complementary and Alternative Medicine. 2004;1(3):251–257. [PMC free article][PubMed]
32. Mojcik CF, Shevach EM. Adhesion molecules: a rheumatologic perspective. Arthritis and Rheumatism. 1997;40(6):991–1004. [PubMed]
33. Bodi T. The effects of oral bromelains on tissue permeability to antibiotics and pain responseto bradykinin: double blind studies on human subjects. Clinical Medicine. 1966;73:61–65.
34. Kumakura S, Yamashita M, Tsurufuji S. Effect of bromelain on kaolin-induced inflammation in rats. European Journal of Pharmacology. 1988;150(3):295–301.[PubMed]
35. Cohen A, Goldman J. Bromelain therapy in rheumatoid arthritis. Pennsylvania Medical Journal. 1964;67:27–30. [PubMed]
36. Barth H, Guseo A, Klein R. In vitro study on the immunological effect of bromelain and trypsin on mononuclear cells from humans. European Journal of Medical Research. 2005;10(8):325–331. [PubMed]
37. Hale LP, Haynes BF. Bromelain treatment of human T cells removes CD44, CD45RA, E2/MIC2, CD6, CD7, CD8, and Leu 8/LAM1 surface molecules and markedly enhances CD2-mediated T cell activation. Journal of Immunology. 1992;149(12):3809–3816. [PubMed]
39. Desser L, Rehberger A, Kokron E, Paukovits W. Cytokine synthesis in human peripheral blood mononuclear cells after oral administration of polyenzyme preparations. Oncology. 1993;50(6):403–407. [PubMed]
40. Desser L, Rehberger A, Paukovits W. Proteolytic enzymes and amylase induce cytokine production in human peripheral blood mononuclear cells in vitro. Cancer Biotherapy. 1994;9(3):253–263. [PubMed]
41. Eckert K, Grabowska E, Stange R, Schneider U, Eschmann K, Maurer HR. Effects of oral bromelain administration on the impaired immunocytotoxicity of mononuclear cells from mammary tumor patients. Oncology Reports. 1999;6(6):1191–1199. [PubMed]
42. Engwerda CR, Andrew D, Murphy M, Mynott TL. Bromelain activates murine macrophages and natural killer cells in vitro. Cellular Immunology. 2001;210(1):5–10. [PubMed]
43. Engwerda CR, Andrew D, Ladhams A, Mynott TL. Bromelain modulates T cell and B cell immune responses in vitro and in vivo. Cellular Immunology. 2001;210(1):66–75. [PubMed]
44. Mynott TL, Ladhams A, Scarmato P, Engwerda CR. Bromelain, from pineapple stems, proteolytically blocks activation of extracellular regulated kinase-2 in T cells. Journal of Immunology. 1999;163(5):2568–2575. [PubMed]
45. Secor ER, Jr., Singh A, Guernsey LA, et al. Bromelain treatment reduces CD25 expression on activated CD4+ T cells in vitro. International Immunopharmacology. 2009;9(3):340–346. [PMC free article][PubMed]
46. Leipner J, Iten F, Saller R. Therapy with proteolytic enzymes in rheumatic disorders. BioDrugs. 2002;15(12):779–789. [PubMed]
47. Lotz-Winter H. On the pharmacology of bromelain: an update with special regard to animal studies on dose-dependent effects. Planta Medica. 1990;56(3):249–253. [PubMed]
48. Livio M, De Gaetano G, Donati MB. Effect of bromelain on fibrinogen level, prothrombin complex factors and platelet aggregation in rat: a preliminary report. Drugs under Experimental and Clinical Research. 1978;4:21–23.
49. De-Guili M, Pirotta F. Bromelain: interaction with some protease inhibitors and rabbit specific antiserum. Drugs under Experimental and Clinical Research. 1978;4:21–23.
50. Taussig SJ, Batkin S. Bromelain, the enzyme complex of pineapple (Ananas comosus) and its clinical application: an update. Journal of Ethnopharmacology. 1988;22(2):191–203. [PubMed]
51. Mynott TL, Guandalini S, Raimondi F, Fasano A. Bromelain prevents secretion caused by Vibrio cholerae and Escherichia coli enterotoxins in rabbit ileum in vitro. Gastroenterology. 1997;113(1):175–184. [PubMed]
52. Chandler DS, Mynott TL. Bromelain protects piglets from diarrhoea caused by oral challenge with K88 positive enterotoxigenic Escherichia coli. Gut. 1998;43(2):196–202. [PMC free article][PubMed]
53. Mynott TL, Luke RKJ, Chandler DS. Oral administration of pro tease inhibits enterotoxigenic Escherichia coli receptor activity in piglet small intestine. Gut. 1996;38(1):28–32. [PMC free article][PubMed]
54. Béez R, Lopes MTP, Salas CE, Hernández M. In vivo antitumoral activity of stem pineapple (Ananas comosus) bromelain. Planta Medica. 2007;73(13):1377–1383. [PubMed]
55. Taussig SJ, Szekerczes J, Batkin S. Inhibition of tumour growth in vitro by bromelain, an extract of the pineapple plant (Ananas comosus) Planta Medica. 1985;6:538–539. [PubMed]
57. Mantovani A, Allavena P, Sica A, Balkwill F. Cancer-related inflammation. Nature. 2008;454(7203):436–444. [PubMed]
58. Ferris RL, Grandis JR. NF-κB gene signatures and p53 mutations in head and neck squamous cell carcinoma. Clinical Cancer Research. 2007;13(19):5663–5664.[PubMed]
59. Hussain SP, Harris CC. Inflammation and cancer: an ancient link with novel potentials. International Journal of Cancer. 2007;121(11):2373–2380. [PubMed]
60. Wang MT, Honn KV, Nie D. Cyclooxygenases, prostanoids, and tumor progression. Cancer and Metastasis Reviews. 2007;26(3-4):525–534. [PubMed]
61. Bhui K, Prasad S, George J, Shukla Y. Bromelain inhibits COX-2 expression by blocking the activation of MAPK regulated NF-kappa B against skin tumor-initiation triggering mitochondrial death pathway. Cancer Letters. 2009;282(2):167–176. [PubMed]
62. Huang JR, Wu CC, Hou RCW, Jeng KC. Bromelain inhibits lipopolysaccharide-induced cytokine production in human THP-1 monocytes via the removal of CD14. Immunological Investigations. 2008;37(4):263–277.[PubMed]
63. Hou RCW, Chen YS, Huang JR, Jeng KCG. Cross-linked bromelain inhibits lipopolysaccharide-induced cytokine production involving cellular signaling suppression in rats. Journal of Agricultural and Food Chemistry. 2006;54(6):2193–2198. [PubMed]
64. Tassman GC, Zafran JN, Zayon GM. Evaluation of a plate proteolytic enzyme for the control of inflammation and pain. Journal of Dental Medicine. 1964;19:73–77.
65. Tassman GC, Zafran JN, Zayon GM. A double-blind crossover study of a plant proteolytic enzyme in oral surgery. The Journal of Dental Medicine. 1965;20:51–54. [PubMed]
66. Howat RCL, Lewis GD. The effect of bromelain therapy on episiotomy wounds—a double blind controlled clinical trial. Journal of Obstetrics and Gynaecology of the British Commonwealth. 1972;79(10):951–953. [PubMed]
67. Houck JC, Chang CM, Klein G. Isolation of an effective debriding agent from the stems of pineapple plants. International Journal of Tissue Reactions. 1983;5(2):125–134. [PubMed]
68. Rosenberg L, Krieher Y, Silverstain E, et al. Selectivity of a Bromelain Based Enzymatic Debridement Agent: A Porcine Study. Elsevier; 2012. [PubMed]
69. Singer AJ, McClain SA, Taira BR, Rooney J, Steinhauff N, Rosenberg L. Rapid and selective enzymatic debridement of porcine comb burns with bromelain-derived Debrase: acute-phase preservation of noninjured tissue and zone of stasis. Journal of Burn Care and Research. 2010;31(2):304–309. [PubMed]
70. Wu SY, Hu W, Zhang B, Liu S, Wang JM, Wang AM. Bromelain ameliorates the wound microenvironment and improves the healing of firearm wounds. Journal of Surgical Research. 2012;176:503–509. [PubMed]
71. Hu W, Wang AM, Wu SY, et al. Debriding effect of bromelain on firearm wounds in pigs. The Journal of Trauma. 2011;71(4):966–972. [PubMed]
72. Miller JG, Carruthers HR, Burd DAR. An algorithmic approach to the management of cutaneous burns. Burns. 1992;18(3):200–211. [PubMed]
73. Sheridan RL, Tompkins RG, Burke JF. Management of burn wounds with prompt excision and immediate closure. Journal of Intensive Care Medicine. 1994;237:68–75. [PubMed]