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Review

Warburg and Beyond: The Power of Mitochondrial Metabolism to Collaborate or Replace Fermentative Glycolysis in Cancer

by
Shamir Cassim
1,*,
Milica Vučetić
1,
Maša Ždralević
2,† and
Jacques Pouyssegur
1,2,*
1
Department of Medical Biology, Centre Scientifique de Monaco, CSM, 98000 Monaco, Monaco
2
Centre A. Lacassagne, University Côte d’Azur, IRCAN, CNRS, 06189 Nice, France
*
Authors to whom correspondence should be addressed.
Present address: Faculty of Medicine, University of Montenegro, Kruševac bb, 81000 Podgorica, Montenegro.
Cancers 2020, 12(5), 1119; https://doi.org/10.3390/cancers12051119
Submission received: 16 April 2020 / Revised: 27 April 2020 / Accepted: 29 April 2020 / Published: 30 April 2020
(This article belongs to the Special Issue Metabolic Pathways and Redox Homeostasis in Cancer)

Abstract

:
A defining hallmark of tumor phenotypes is uncontrolled cell proliferation, while fermentative glycolysis has long been considered as one of the major metabolic pathways that allows energy production and provides intermediates for the anabolic growth of cancer cells. Although such a vision has been crucial for the development of clinical imaging modalities, it has become now evident that in contrast to prior beliefs, mitochondria play a key role in tumorigenesis. Recent findings demonstrated that a full genetic disruption of the Warburg effect of aggressive cancers does not suppress but instead reduces tumor growth. Tumor growth then relies exclusively on functional mitochondria. Besides having fundamental bioenergetic functions, mitochondrial metabolism indeed provides appropriate building blocks for tumor anabolism, controls redox balance, and coordinates cell death. Hence, mitochondria represent promising targets for the development of novel anti-cancer agents. Here, after revisiting the long-standing Warburg effect from a historic and dynamic perspective, we review the role of mitochondria in cancer with particular attention to the cancer cell-intrinsic/extrinsic mechanisms through which mitochondria influence all steps of tumorigenesis, and briefly discuss the therapeutic potential of targeting mitochondrial metabolism for cancer therapy.

1. Introduction

These past decades have been marked by a growing number of studies dealing with cancer and have led to a better overall understanding of this disease, in particular the fact that (1) cancer is not a disease that could only originate from genetic and epigenetic modifications [1,2,3,4], and (2) tumor cells do not exclusively depend on aerobic glycolysis to satisfy their bioenergetic and anabolic demands [5,6,7,8]. Indeed, mitochondria have now been recognized as important mediators of cancer behavior in all steps of tumorigenesis [9,10]. These long-standing misconceptions actually stem from the “self/non-self” discrimination—which suggests that the immune system can only recognize foreign entities [11,12]—and the so-called “Warburg effect”, referring to Otto Warburg, who described in 1927 an increased ability of tumors to uptake glucose [6,13,14,15]. Nevertheless, these correct, but incomplete assumptions led to a wave of investigations that have revolutionized modern medicine, including the rationale for the development of the [18F]-fluorodeoxyglucose-positron emission tomography (FDG-PET) clinical imaging tool in the detection of tumor and metastatic foci [15,16].
As will be detailed hereafter, Warburg’s seminal observation that tumor cells sustain aerobic glycolysis, which corresponds to the fermentation of glucose into lactate when oxygen is present (in contrast to the complete oxidation of glucose by mitochondria), gave prominence to the role of mitochondria in cancer [14]. While the “Warburg effect” is an undeniable characteristic displayed by a majority of tumor cells, Warburg himself suggested that the capacity of neoplastic cells to sustain enhanced glycolytic rates would stem from primary mitochondrial defects [17], thus obscuring the role of mitochondria in cancer for almost 80 years. However, in the mid-1990s, a renewed interest in the relevance of mitochondria in cancer has attributed several pleiotropic roles during tumorigenesis [9,10]. For example, mitochondrial outer membrane permeabilization (MOMP) has been revealed as a critical step in the execution of regulated cell death (RCD) [18,19] and has led to the identification that most cancer cells exhibit an increased resistance to RCD [1,3]. Considerable efforts to identify and develop molecules that would efficiently target these mitochondrial control points have thus been made as a strategy for chemo/radio-sensitization [20,21,22]. From a metabolic perspective, mitochondria attracted renewed attention as it became clear that they can favor cancer reprogramming in imparting substantial metabolic flexibility, thereby allowing tumor cell growth and survival under fluctuating microenvironmental conditions. For example, mitochondrial uncoupling—which is the abrogation of ATP generation in response to the mitochondrial membrane’s potential—has been shown to favor the Warburg effect in tumor cells (for further details on mitochondrial uncoupling and its function in cancer cell metabolism, please refer to [23]). In the same vein, some mitochondrial metabolites have been shown to be sufficient to drive oncogenesis [24], and some mitochondrial metabolic pathways could adapt to serve bioenergetic or anabolic functions, such as during nutrient restriction, low levels of oxygen tension (hypoxia), and cancer treatments [25,26,27,28,29]. Hence, targeting mitochondrial metabolism remains a major but very challenging approach for the establishment of promising cancer therapeutics [30,31,32].
However, one of the biggest challenging issues with targeting mitochondria as a relevant approach to efficiently eradicate tumor cells (or at least make them vulnerable after treatment exposure) is that all differentiated tissues are dependent on oxidative phosphorylation (OXPHOS) to survive [33,34,35]. This would then lead to the establishment of refined therapeutic strategies, whereby tumor cells would be selectively targeted, while non-tumor/normal differentiated cells would be spared from—or unresponsive to—the treatment-derived effects. Here, after revisiting the Warburg effect from a historic/dynamic perspective, and seeing whether or not it is dispensable for cancer, we will discuss the role of mitochondria in cancer by detailing the mechanisms through which they can impact on tumorigenicity, and we will briefly highlight the therapeutic opportunities of targeting mitochondrial metabolism as an anticancer strategy.

2. The Warburg Effect: From Myth to Reality

2.1. Historical Perspectives

Otto Warburg and colleagues noticed, in the 1920s, that tumors were able to uptake massive amounts of glucose in comparison with normal surrounding tissues. Furthermore, it has been observed that glucose fermentation could occur in these tumors in order to generate lactate even under oxygen non-limiting conditions, thus the term “aerobic glycolysis” [36,37]. However, it was also noticed that respiration alone could preserve tumor cell survival, and it was thus suggested that to proficiently eradicate cancer cells by siphoning them of their energy, both glucose and oxygen had to be removed [13]. In 1925, Cori and Cori extended Warburg’s work and revealed the in situ lactic acid levels displayed by mouse and rat tumors to be very much lower than those observed in the in vitro experiments of Warburg [13,37,38]. Notably, Cori and Cori proved that the blood drawn that emanates from a tumor had considerably reduced glucose and increased lactic acid than the blood passing through the non-tumoral tissues, and finally concluded that this initial excess of lactic acid generation displayed by tumors was washed out by the blood flow through the tissue [38]. In 1929, the English biochemist Herbert Crabtree studied the glycolytic activity of different tumor types and noticed some heterogeneity. While confirming Warburg’s seminal findings, Crabtree further revealed a heterogeneity in the magnitude of respiration exhibited by tumors, with many tumors showing an important capacity to sustain respiration [39]. Hence, Crabtree suggested that not only do cancer cells display enhanced aerobic glycolysis, but that significant differences were also observed during fermentation according to the environmental or genetic variations.
Warburg later proposed, in 1956, that “the respiration of all cancer cells is damaged”, thereby promoting the incorrect assumption that impaired respiration was the sine qua non that causes the increased fermentation of glucose in tumors, even though observations from his own laboratory and those of others indicated otherwise [14]. The observations of Chance and Weinhouse indeed controverted Warburg’s hypothesis of mitochondrial defects in tumors [17,40], as rat hepatoma cells were evidenced to have active mitochondria and respiratory capacity [41]. However, Warburg used to say that “science progresses not because scientists change their minds, but because scientists attached to erroneous views die, and are replaced” [42]. Warburg actually assumed that respiration must be damaged in cancers because high levels of O2 were unable to abrogate the lactic acid production by tumor cells [43]. Nonetheless, in 1962, Warburg attempted to justify the conclusions he had drawn and admitted that the description he made based on insufficient (rather than damaged) respiration had led to “fruitless controversy”. In the early 1970s, Efraim Racker termed this phenomenon the “Warburg effect” and also pinpointed prior findings demonstrating that tumors were able to sustain respiration, and developed his own ideas about the Warburg effect origins: ranging from intracellular pH disparities to ATPase activity alterations [44,45]. Later on, Jeffrey Flier, Racker and Morris Birnbaum confirmed that aerobic glycolysis was a well-regulated process controlled by growth factor signaling [46,47,48,49]. However, at that time, the discovery of oncogenes led to the assumption that aberrant regulation of growth factor signaling was an initiating event in tumorigenesis, shedding new light on Warburg’s hypothesis. Therefore, it remained uncertain whether the Warburg effect was just a mere by-product of aberrant growth factor signaling until recently, when several studies dealing with genetics demonstrated that the Warburg effect was actually the best fit for tumor growth (but still dispensable under certain conditions as will be developed in Section 2.3) [50,51,52,53,54,55]. Furthermore, as a proof of principle showing the renewed interest in studying tumor cell metabolism during these last years, the number of publications referring to the “Warburg effect” term has increased exponentially since the 2000s [56].

2.2. The Warburg Effect and Cellular Growth: A Fine-Tuned Nexus

Per unit of glucose, aerobic glycolysis is an unproductive way to favor ATP production in comparison with the amount produced by mitochondrial respiration (2 versus 33.45 molecules of ATP according to the recent observations of Mookerjee et al. [57]), so why would rapidly proliferating cells be dependent on such an unproductive pathway to produce energy? Lactate production from glucose occurs up to 100 times faster than the complete oxidation of glucose that takes place in the mitochondria [58], and simple calculations indicated that the ATP demand may then never reach limiting values in rapidly growing tumor cells [59,60]. Thus, this enhanced glucose consumption is rather used as a source of carbon for anabolic processes and biomass that are needed to favor the growth of rapidly proliferating cells [15,28,29,61,62]. This excess carbon is used for the de novo building-up of nucleotides, lipids, and proteins, and can be redirected into several pathways that arise from glycolysis [15,51,63] (Figure 1). One example is the deviation of the glycolytic flux into the de novo biosynthesis of serine through the phosphoglycerate dehydrogenase (PHGDH) enzyme [59,64]. In addition, it is now admitted that rather than having a rate-limiting demand for ATP, highly dividing cells are in great need of reducing equivalents in the form of NADPH (nicotinamide adenine dinucleotide phosphate) [65,66]. Then, the accrued uptake of glucose allows for a greater synthesis of these reducing equivalents through the oxidative branch of the pentose phosphate pathway (PPP) and the serine synthesis pathway followed by the tetrahydrofolate cycle, which are then used 1) for the maintenance of reduced glutathione (the major cellular antioxidant), and 2) in reductive biosynthesis (most notably in the de novo synthesis of fatty acids) [65,67] (Figure 1). Lastly, the final step of fermentative glycolysis, conducted by lactate dehydrogenase A in reducing pyruvate into lactate with a regeneration of NAD+ (nicotinamide adenine dinucleotide), is cardinal by ensuring a glycolytic flux. Lactate serves as a substantial source of energy in rapidly growing tissues/tumors, but also in differentiated organs/tissues subjected to important physiological, nutritional, and energetic demands (such as embryonic and immune cells or regenerating tissues) [51]. For example, during physical exercise, more than half of the energy turnover rate in the heart muscle is recruited from lactate oxidation [68]. In the brain, besides its capacity to support adequate energy levels and the optimal synaptic function [69], lactate per se (and not glucose) was revealed as a key player in alleviating the hypoxia-induced damages of neurons [70]. In rapidly proliferating cancer cells, including lung and pancreatic tumors, lactate could feed the tricarboxylic acid (TCA) cycle; lactate’s contribution as a respiratory fuel exceeded that of glucose, especially in rapidly growing tumors [71,72]. Pyruvate can also be redirected into the mitochondria and converted to acetyl-CoA for entry into the tricarboxylic acid cycle (TCA) [22]. The TCA cycle intermediates are then either oxidized for catabolic purposes or transformed into amino acids or citrate for export back to the cytosol (further details are provided in the following sections).
Consequently, this originally thought to be “wasteful” system is ultimately shown to be extremely efficient once one may understand that the ultimate goal of a tumor cell is nothing more than cellular growth and division. Given that the Warburg effect is also noticed during the rapid proliferation of the primary cells, it is more generally perceived as a characteristic of cell proliferation than as a privilege of oncogenic transformation, and can thus be perceived as an important player that contributes to anabolic metabolism (see Figure 2 for a rapid overview) [73,74].

2.3. Is the Warburg Effect Dispensable for Cancer?

Cells that sustain high glycolytic rates do not catabolize the totality of their pyruvate into lactate, but rather a significant amount of the pyruvate is oxidized and metabolized in the TCA cycle, thus delivering energy through respiration and the metabolic intermediates for the anabolic pathways that stem from TCA cycle [75]. Hence, as previously reported by Crabtree [39], mitochondrial respiration can actually occur in tumor cells and a key question then arises: is the Warburg effect dispensable for cancer? In other words, would the inhibition of the Warburg effect push tumor cells to rapidly rewire their metabolism towards mitochondria and oxidative phosphorylation (OXPHOS) to survive and proliferate? Our laboratory has even pushed the question further, could full suppression of the Warburg effect arrest tumor growth? We addressed this fundamental question by using two tumorigenic cancer cell lines, derived from human colon adenocarcinoma (LS174T) and mouse B16-F10 melanoma, in which we genetically disrupted the Warburg effect at either one of the three fermentative glycolytic steps: (1) glucose 6 phosphate isomerase, (2) lactate dehydrogenase A, B or both A/B, and (3) lactate/H+ symporters monocarboxylate transporter (MCT) 1 and 4 (see Figure 1).
Glucose 6 phosphate isomerase (GPI) is a cytosolic enzyme involved in the reversible inter-conversion between glucose 6 phosphate (G6P) and fructose 6 phosphate (F6P), and its genetic disruption using the CRISPR/Cas9 technique is associated with major metabolic and growth modifications. Indeed, both the LS174T and B16-F10 GPI-KO cell lines, which had no measurable GPI enzymatic activity and secretion of lactic acid, rewired their metabolism towards the PPP and OXPHOS as supported by their augmented respiratory capacity [54]. Remarkably, the highly glycolytic LS174T tumor cell line (with a low respiratory capacity when cultured under standard conditions) displayed a strong reactivation of OXPHOS when challenged by a GPI ablation, thus creating an augmented and exclusive reliance on oxygen [54]. This phenotype explained 1) the inability of the LS174T GPI-KO cells to grow in hypoxia (1% O2), and 2) their increased sensitivity to OXPHOS inhibition by phenformin or oligomycin [54]. This vulnerability created by such metabolic rewiring is in line with the observations described for ovarian and hepatocarcinoma cancer cell lines, where GPI silencing completely abolished cancer cell growth in combination with OXPHOS inhibition [76].
Lactate dehydrogenase (LDH) is a family of NAD+-dependent enzymes that catalyze the reversible conversion between pyruvate and lactate, with a simultaneous oxidation/reduction of the cofactor (NAD+/NADH) [77,78]. Active LDH is a homo/heterotetramer assembled from two different subunits: M (muscle) and H (heart), encoded by two separate genes, LDHA (M) and LDHB (H), respectively [77,78]. The important role of LDHA in maintaining a Warburg phenotype and promoting the tumorigenic potential of malignancies was confirmed by numerous findings showing that LDHA inhibition, gene silencing, or knockdown considerably decreased the tumorigenic potential in several types of cancer [50,79,80]. Hence, we used the same genetic approach to create LDHA-KO LS174T and B16-F10 cells and showed that the complete abrogation of the LDHA gene results in only about a 30% decrease in the secreted lactate levels [55]. Interestingly, the LDHA-KO cells revealed an augmented OXPHOS capacity, thus pointing to (1) an increased reliance on OXPHOS for the production of energy, and (2) an amplified vulnerability to respiratory chain inhibitors including phenformin, which significantly reduced the clonal growth [55]. This unexpected low 30% decrease in the secreted lactate levels was corroborated by the finding that the lack of LDHA did not significantly influence in vitro cell growth under normoxic conditions [55]. This could at least partially be explained by the retained ability of LDHA-KO cells to catalyze a pyruvate conversion to lactate, although at a reduced rate compared with the wild type (WT) cells, but at levels sufficient to drive glycolysis, lactate production, and growth. We therefore hypothesized that this activity might be due to the presence of a LDHB isoform in both cell lines, capable of catalyzing the reverse reaction when LDHA is no longer present. However, alone LDHB-KO cells did not significantly impact on the cells’ growth and viability, neither in normoxia nor hypoxia (1% O2) [55]. Rather, they behaved essentially like WT cells in terms of lactate secretion, glycolytic and mitochondrial activity, and sensitivity to OXPHOS inhibitors [55]. It was only when both the LDHA and LDHB isoforms were disrupted that a distinct phenotype with no detectable lactate secretion and a complete metabolic redirection toward OXPHOS was observed [55]. It is of importance to note that the genetic LDHA/B-double KO cell phenotype was mimicked in vitro by the dual first specific LDHA, the LDHB inhibitor GNE140 [55], killing the possibility of aberrant emergence during the genetic selection. Again, this increased reliance on OXPHOS displayed by these LDHA/B-double KO cells was marked by an increased vulnerability to the inhibitors that target the mitochondrial respiratory chain (phenformin) in comparison with the WT or LDHA/B-KO cells [55]. Importantly, in vivo, only a delay and not an abrogation of tumor growth could be observed, thus suggesting that at least in immunodeficient mice, the Warburg effect can be replaced by OXPHOS [55].
MCTs (1–4) facilitate the transport of lactate and protons into and out of cells and both MCT1 and MCT4 expression levels were evidenced to be increased in tumors [51,81,82,83,84,85]. Having a strong interest in studying these different intracellular pH (pHi)-regulating systems, we investigated the effects of the pharmacological/genetic inhibition of lactic acid export on tumor cells to see whether these cells could sustain metabolic rewiring in order to strive. Pharmacological inhibition with the specific AstraZeneca MCT1/2 inhibitor (AR-C155858) was reported to impede glycolysis and tumor growth of the RAS-transformed fibroblasts expressing only MCT1/2 [86]. Importantly, this compound was shown to be ineffective in preventing the growth of tumor cells lacking glycolytic activity that only rely on OXPHOS to strive [86]. Reciprocally, the expression of MCT4 in respiration-deficient RAS-transformed fibroblasts was shown to favor in vivo tumor growth [83]. In non-small cell lung cancer cells, the genetic disruption of the MCT’s chaperone CD174 was described to lower the glycolytic rate 2.0- to 3.5-fold, and to stimulate mitochondrial respiration, thereby making CD174-null cells particularly sensitive to inhibitors of mitochondrial respiration both in vitro and in vivo [87,88]. Finally, a combined inhibition/disruption of MCT1/4, which severely reduces the lactic acid export, imposes a strong reduction in tumor growth [88,89]. The reason for this growth arrest is due to the intracellular acidification that is known to block mTORC1 [90,91]. Now, this growth arrest/cytostatic effect can be transformed into cell death (energy crisis) when an MCT inhibition is combined with a short exposure to the mitochondrial complex I inhibitor phenformin [88,92,93,94].
These three examples point to a common feature: an extraordinary metabolic plasticity displayed by tumor cells. In all three cases, the disruption of the glycolytic flux resulted in an abolishment of the lactic acid secretion and augmented the reliance on OXPHOS for the energetic needs and survival. Coming back to Otto Warburg’s original findings, it has become now evident that the involvement of mitochondrial metabolism to cancer formation and development are of paramount importance. In the following sections, we will specifically focus on mitochondria, by detailing the cancer cell-intrinsic/extrinsic mechanisms through which they can impact on malignant transformation and progression, and briefly emphasize the therapeutic potential of targeting mitochondrial metabolism in cancer therapy.

3. Mitochondrial Metabolism in Cancer

3.1. Carcinogenesis

Mitochondria whose name was derived from the Greek “mito”, meaning thread, and “chondria”, due to their granulosity [95], may favor a malignant transformation by at least two major mechanisms that include (1) the mitochondrial reactive oxygen species (ROS) that support the accumulation of oncogenic DNA alterations and activation of oncogenic pathways [96], and (2) the abnormal increase in the specific mitochondrial metabolites including fumarate, succinate, and 2-hydroxyglutarate (2-HG), which has important transforming properties [97].

3.1.1. Reactive Oxygen Species (ROS)

ROS, in the form of superoxide anion radical and/or hydroxyl radical are produced from physiological metabolic reactions and were described for the first time by Poul K. Jensen in 1966, who proved that they originate from the respiratory chain [98,99]. Later on, Chance and co-workers also reported that isolated mitochondria produce H2O2 [100,101,102]. Indeed, through the mitochondrial complexes I, II and III, OXPHOS has been identified as the main source of ROS production, thus making mitochondria the major contributors of cellular redox homeostasis [98,103]. Their participation during a malignant transformation is shown by the fact that mice deficient in p53 that are maintained under hypoxic conditions (10% O2) display a reduced level of tumorigenesis, and thus a survival advantage in comparison with those exposed to the standard atmospheric conditions (21% O2) [104]. In line with this, the autophagic removal of damaged mitochondria overproducing ROS led to a reduced potential of oncogenesis, since the specific knockdown or knockout of autophagic genes (such as Atg5 or Atg7) have been shown to promote cancer transformation [105,106,107]. ROS are also involved in oncogenic signal transduction cascades via cysteine oxidation, as demonstrated with H2O2, which can inactivate the tumor suppressor phosphatase and tensin homolog (PTEN) by oxidizing the active site’s cysteine residues [103,108]; this leads to the formation of a disulfide bond and prevents PTEN from inactivating the phosphoinositide 3 kinase (PI3K) pathway [96,109]. ROS may have several yet to be discovered consequences on the diverse mitogen-activated pathways that are usually abrogated by phosphatases [109,110]. Kamata et al. indeed demonstrated that the accumulation of intracellular H2O2 could inactivate mitogen-activated protein kinase (MAPK) phosphatases through oxidation of their catalytic cysteine, and thus maintains the MAPK pathway in an active state [111,112]. In line with this, RAS and RAC small GTP-binding proteins appeared to be directly linked to the production of superoxide anion radical O2 in transformed fibroblasts; an ROS-mediated neo-transformation of these cells could then be evidenced since treatment with antioxidants was associated with a block in the RAS-induced cellular transformation [113]. Further, the accumulation of ROS can directly affect DNA integrity and it has been shown that ROS-mediated DNA damages could favor the initiation stage of tumorigenesis. For example, the capacity of hydroxyl radicals to attack DNA is well known and was shown to trigger single and/or double strand breaks which can then affect genome integrity [114]. In addition to causing genetic modifications, ROS have also been associated with epigenetic alterations that favor oncogenic transformation; indeed, a ROS-induced hypermethylation of the promoter region of tumor suppressor genes has been shown to promote carcinogenesis, as exemplified in liver cancer, where hepatocellular carcinoma (HCC) cells exposed to H2O2 had increased hypermethylation levels of the promoter region of the E-cadherin gene (a hallmark of an epithelial-to-mesenchymal transition (EMT) that is lost during this process), leading then to its down-regulation [115].

3.1.2. Oncometabolites

Dominant mutations in mitochondrial enzymes allowed the discovery of mitochondrial-derived signaling molecules that are called oncometabolites. Succinate dehydrogenase complex iron sulfur subunit B (SDHB), fumarate hydratase (FH), and the cytosolic and mitochondrial isocitrate dehydrogenase (IDH) isoforms 1 and 2 have been shown to be mutated in various types of cancer [97]. While SDHB and FH enzymes are generally affected by the loss-of-function mutations, with augmented levels of fumarate and/or succinate, IDH1 and IDH2 often display gain-of-function mutations that lead to the production of 2-HG [116]. Behaving as bona fide oncometabolites, the accumulation of fumarate, succinate, and 2-HG may be enough to enhance tumor transformation [116]. The structural similarity of these oncometabolites to α-ketoglutarate (α-KG) makes them of interest as they can act as competitive inhibitors of the α-KG-dependent enzymes that regulate gene expression levels through epigenetic modifications, including the Jumonji domain (JMJ) histone lysine demethylases and ten-eleven translocation (TET) dioxygenases [117,118]. For example, TET activity abrogation was reported to increase the hypermethylation of CpG islands, leading then to the silencing of genes [117]. 2-HG and succinate were shown to alter the α-KG-dependent HIF-prolyl oxidase activity of the egl-9/PHD family hypoxia inducible factor 1α and 2 (EGLN1/PHD2—EGLN2/PHD1), hence favoring neo-transformation through a mechanism associated with the stability of the hypoxia inducible factors 1 and 2 [119,120,121]. Fumarate can also promote a non-enzymatic post-translational protein modification known as “succination”, most likely due to the inactivation of the succinate dehydrogenase enzyme complex, and augments the kelch-like ECH-associated protein 1 (KEAP1), enabling the activation of the transcription factor’s nuclear factor erythroid 2-related factor 2 (NRF2) and consequent upregulation of antioxidant pathways [122]. The same post-translational modification also seems to affect the non-enzymatic antioxidant glutathione, thereby preventing its recognition by glutathione reductase and resulting in decreased NADPH and an augmented ROS production [123]. Altogether, these observations perfectly represent the critical influence that mitochondria can exert at the different stages of malignant transformation.

3.2. Cancer Progression

3.2.1. A Biosynthetic Hub

As progressing tumors can rely on the reversibility of various TCA cycle reactions and the existence of multiple anaplerotic circuitries centered on mitochondria to survive, the following paragraphs will discuss the different TCA cycle intermediates that are involved in this phenomenon to see how mitochondria represent a powerhouse from which anabolism is fed [124,125]. (see Figure 1 for a general and non-exhaustive overview)
Located at a central position, citrate is a key intermediate that operates as a major node of flexibility [126] (Figure 1). Besides replenishing the oxidative mode of the TCA, citrate can also be transformed into acetyl-CoA for export to the cytosol and nucleus, where it can be used as a substrate either for the synthesis of fatty acids and cholesterol, or for acetylation reactions [127]. Indeed, upregulation of lipogenesis was proposed as a characteristic of rapidly growing tumors to support the membrane need associated with an intense proliferation [128]. The inhibition of ATP-citrate lyase (ACLY), which catalyzes mitochondrial-derived citrate into acetyl-CoA, has been shown to reduce tumorigenesis in several models [128]. In contrast, certain cancers rely on mitochondrial fatty acid oxidation (FAO) for ATP generation [129]. Further, FAO may be a favored fuel choice for cancers undergoing stress as evidenced in HCC, where highly tumorigenic HCC cells increased FAO to favor ATP generation when cultured under glucose-restricted conditions [28,29]. Beyond ATP production, increased FAO in some cases may also confer benefits in maintaining redox homeostasis [129]. It was also reported that an epigenetic remodeling of chromatin could result from the production of FAO-derived acetyl-CoA, subsequently causing gene expression modifications, leading ultimately to enhanced cell proliferation [130]. In line with this, an ACLY-dependent production of acetyl-CoA from mitochondrial-derived citrate is also used for epigenetic modifications: (1) with the modification of histone acetylation patterns that ultimately leads to chromatin modification via histone acetyl transferases (HATs), and (2) for the acetylation of many cytosolic and mitochondrial proteins, thereby modifying their structural conformation and activity [127,131].
Glutamine can be oxidized through the TCA cycle and represents an important source for the synthesis of macromolecules [75] (Figure 1). The amide nitrogen on glutamine is used in purine synthesis, whereas glutamine-derived carbons are used in pyrimidine, amino acid and lipid synthesis. Glutaminolysis, which corresponds to glutamine catabolism, was reported to be (1) augmented in numerous tumors that are addicted to glutamine, and (2) often induced by MYC upregulation of glutaminase (GLS), which catabolizes glutamine into glutamate and ammonia [75,132]. Glutamate is then oxidized to α-KG by glutamate dehydrogenase (GDH), thus allowing the entry into the TCA cycle. For example, the expression of Sirtuin 4 (SIRT4) in B cell lymphoma, which is a mitochondrial-localized tumor suppressor protein that inhibits a glutamate-to-α-KG conversion, was associated with a decreased glutamine uptake and cellular growth; conversely, its loss increased glutamine consumption and hastened tumorigenesis [133]. In parallel, it was indicated that, in comparison to quiescent cells, proliferating cells (normal and tumor) primarily use glutamate via transaminases to couple non-essential amino acid synthesis to α-KG production and TCA cycle anaplerosis, pinpointing the relevance of this pathway in supporting biosynthesis during tumor cell proliferation [134]. Glutamine also acts as another source of carbons for acetyl-CoA production, which can then serve lipid biosynthesis through reductive carboxylation under hypoxia or when the mitochondria are damaged [135,136]. Experiments using a [5-13C]-glutamine tracer could indeed demonstrate that, through reductive carboxylation, an up to 25% formation of lipogenic acetyl-CoA came from glutamine in several types of tumor cells [135]. In addition, via malic enzyme activity, glutamine-derived malate is also metabolized into pyruvate, which can then be converted into oxaloacetate/acetyl-CoA for reentry into the TCA cycle [137]. In line with this, cytosolic malic enzyme 1 was demonstrated to sustain NADPH generation from glutamate in pancreatic and breast cancers, thereby participating in redox homeostasis [134,138]. Furthermore, NADPH production can also be achieved via the IDH1-dependent reductive carboxylation of glutamine, thereby reducing the levels of mitochondrial ROS [136] (for further details on glutamine metabolism and redox homeostasis, refer to [136,139,140]). Importantly, while several studies could provide strong evidence that the requirements for glutamine were substantial for numerous types of tumors [141], it is important to note that the dispensability of glutamine was also noted under certain circumstances, as evidenced by lung tumor cells, which lost their glutamine dependency when grown in vivo [142].
Mitochondria also participate to malignant progression through nucleotide synthesis via one-carbon metabolism [143]. The mitochondrial folate synthesis pathway consists of serine hydroxylmethyltransferase (SHMT2) and the bifunctional methylenetetrahydrofolate dehydrogenase/cyclohydrolase (MTHFD2) [144,145]. Gene expression profiling could indeed identify many types of MTHFD2-overexpressing tumors and further studies revealed MTHFD2 as an important determinant of cancer cell survival [145]. Further, SHMT2 expression was detected in ischaemic tumor regions, thereby procuring a proliferative advantage under hypoxia [146]. Using isotope labeling, Kim et al. demonstrated that while inhibition of SHMT2 is associated with an improved pyruvate kinase (PKM2) activity and carbon flux into the TCA cycle, cells that display greater levels of SHMT2 activity limit that of PKM2 and flux into the TCA. This action decreases oxygen consumption and confers to cells localized in weakly vascularized tumor zones a survival benefit [146]. Additionally, SHMT2 regulation of serine metabolism is also involved in the generation of NADPH, and thus the subsequent detoxification of ROS under hypoxia, which is an essential function for survival of MYC-driven cancers [144]. Altogether, these observations emphasize the crucial role of mitochondria in allowing cancer cells to thrive during malignant progression.

3.2.2. Resistance to RCD

As aforementioned, progressing tumors encounter fluctuating microenvironmental conditions and this would commonly create an accrued sensitivity to mitochondrial regulated cell death (RCD) via a mitochondrial outer membrane permeabilization (MOMP) or a mitochondrial permeability transition (MPT) [147]. The pro-apoptotic BCL-2 family members BAX (BCL-2-associated X protein) and BAK (BCL-2 homologous antagonist killer) are recruited to the mitochondrial outer membrane and oligomerize to mediate MOMP, resulting in a pore formation and cytochrome c release from mitochondria into the cytosol to initiate caspases activation [148]. While BAX/BAK is inhibited by anti-apoptotic proteins under physiological conditions, neoplastic cells evade this via the downregulation of pro-apoptotic and/or upregulation of anti-apoptotic genes by several mechanisms (for further details see [149]). Therefore, the balance of pro- and anti-apoptotic proteins impacts a tumor cell’s vulnerability in response to apoptotic signals. Additionally, since some tumors sustain an increased mitochondrial transmembrane potential (ΔΨm) associated with high glycolytic rates and increased resistance to RCD, restoring pyruvate consumption via a chemical inhibition of PDK1 was not only reported to augment RCD sensitivity, but also inhibit in vivo tumor growth [150]. In line with this, detaching mitochondrial-bound hexokinase II (enzyme involved in the first step of glycolysis by converting glucose into G6P) from mitochondria has been suggested to trigger MOMP in different types of cancer cells [151]. The maintenance of optimal antioxidant defenses is also crucial for tumor cells to evade ROS-driven MPT as evidenced by Vaughn et al., who demonstrated that both normal/tumor cells thoroughly impede cytochrome c-mediated apoptosis via a mechanism that relies on glucose metabolism; cytochrome c is indeed reduced and held inactive by the PPP-derived NADPH [152]. Mitochondrial dynamics also dictate apoptotic susceptibility, as the loss of dynamin-related protein 1 (DRP1) (a fundamental component of mitochondrial fission) was shown to delay cytochrome c release and apoptotic induction [153]; similarly, a decreased DRP1 expression was shown to enhance resistance to an oncogenic V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS)-induced cellular transformation [154]. The relevance of mitochondrial dynamics in apoptosis is further evidenced by the induction of mitochondrial hyperfragmentation secondary to mitofusin 1 (MFN1) ablation—an essential component of mitochondrial fusion—resulting in an augmented resistance to apoptotic stimuli owing to the loss of the interaction between BAX and the mitochondrial membranes [155]. Moreover, the inhibition of DRP1 was shown to restore sensitivity to apoptotic stimuli through the reestablishment of a balanced and adequate mitochondrial network [155].

3.2.3. Metastatic Dissemination

Metastases generally refers to the dissemination of tumor cells to distant organ sites [156]. One of the initial changes of the metastatic cascade is EMT induced under hypoxia, which bestows tumor cells with augmented invasive properties [157,158,159]. Multiple mitochondrial metabolites have been shown to support the EMT process, and especially fumarate, which could counteract the transcription of anti-metastatic microRNAs upon the inhibition of TET dioxygenases [160,161,162]. Mitochondrial biogenesis and OXPHOS have also been suggested to support metastatic dissemination, as demonstrated when the peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PGC-1α) was silenced in breast cancer models [163]; PGC-1α is a central regulator of mitochondrial biogenesis whose levels are often associated with tumor reliance on mitochondrial respiration (for further details refer to [164]). While circulating cancer cells originating from orthotopic mammary tumors displayed greater mitochondrial biogenesis and respiration, the silencing of PGC-1α resulted in a reduced migratory phenotype and metastatic potential [163]. Moreover, rotenone, which is a mitochondrial complex I inhibitor, mirrored the PGC-1α silencing effects on tumor cells, with reduced mitochondria respiration and invasive properties, thereby pinpointing the crucial role of mitochondrial-derived ATP on the capacity of tumor cells to be invasive; these results brought newfound significance to the role of PGC-1α in supporting tumor metastasis [163]. ROS were also evidenced to activate multiple signal transduction cascades associated with increased metastatic capabilities, such as proto-oncogene tyrosine-protein kinase SRC and protein tyrosine kinase 2 beta (PTK2B) signaling [165,166]. Indeed, the inhibition of SRC was evidenced to impede tumor cell migration and mitochondrial ROS scavenging to block metastatic take in rodents [165]. Imbalances in the mitochondrial shape also dictate the metastatic susceptibility as a consequence of mild ROS overproduction. Indeed, an augmented expression of DRP1 was associated with a migratory phenotype in several types of cancer cells [167]. In contrast, under severe oxidative stress conditions, ROS have been shown to abrogate metastasis mainly as a straight consequence of weakened fitness, RCD, and/or cellular senescence [168,169]. OXPHOS and subsequent ROS generation are therefore required for the metastatic cascade, and collectively these observations highlight the fundamental role held by mitochondria in supporting cancer progression and metastasis.
As discussed in the above sections, the diversity of the carbon substrates fueling tumor cells thus perfectly exemplifies the concept of metabolic heterogeneity, which is also and importantly mirrored by the different components found in the tumor microenvironment. To take the reasoning further, carcinoma-associated fibroblasts (CAFs) have indeed been evidenced to dynamically participate in the metabolic needs of tumor cells, thereby favoring tumor initiation and progression [170,171,172]. Of note, an elegant work from Mechta-Grigoriou’s group recently identified two particular subsets of CAFs having prominent roles in inducing tumor cell migration and invasion in breast cancer [173].

4. Therapeutic Challenges

The final objective of traditional chemotherapeutics and anti-cancer agents is to prompt the death of tumor cells [174]. Since mitochondria play a crucial role in the control of regulated cell death (RCD), emerging evidence has suggested that targeting mitochondrial metabolism could potentially be a promising area for cancer treatment. As previously stated, tumor cells can interchangeably use glycolysis and OXPHOS as a source of ATP production (see Section 2.2 and Section 2.3). Hence, although targeting mitochondrial ATP generation might not be an appealing strategy for cancer treatment, we however, propose that there are at least three reasons to envision it as a potential target since (1) the interiors of various solid tumors remain weakly perfused and the ETC is still functioning; a drug preventing mitochondrial ATP generation would then favor the cell death of these weakly oxygenated tumors [175,176], (2) there are tumors that heavily rely on OXPHOS to generate ATP, and that these cancer cells are likely to be imaged by 18F-BnTP, a recently reported promising imaging tool sensitive to drugs that restrict mitochondrial ATP production due to a lack of glycolytic compensation [86,88,177,178,179]; important to mention as well is IACS-010759, a selective inhibitor of mitochondrial complex I [180], and (3) preventing mitochondrial ATP generation would synergize with therapeutic strategies that reduce glycolysis. However, one of the main challenging issues with targeting mitochondria is to not impact on normal cells; the prerequisite here, would be whether tumors preferentially uptake the drugs that prevent the production of mitochondrial ATP in comparison with normal cells. In this regard, we speculate that a metformin/phenformin drug may be a promising anti-cancer agent that targets mitochondrial ATP generation without increasing the toxicity in normal tissues. Similarly, it has also been proposed that decreasing the mitochondrial protein translation and stability may offer another opportunity to obstruct mitochondrial bioenergetics. Indeed, tetracycline treatment was shown to impede mitochondrial protein translation and potentiate anti-tumor effects in several preclinical models of leukemia; dismantling the translation of ETC-related proteins resulted in major defects in mitochondrial respiration [181]. As said, glutamine is an important carbon source for cancer cells. Targeting glutamine metabolism and transport becomes of great interest [27], as evidenced with two specific GLS inhibitors: compound 968 and bis-2-(5-phenylacetamido-1,2,4-thiadiazol-2-yl)ethyl sulfide, which reduced glutamine catabolism and delayed in vivo tumor growth in experimental models of cancer [137,182]. Similarly, inhibiting the glutamate-to-α-KG conversion by aminotransferases also decreased tumor growth [183,184]. Notably, one may keep in mind that not all malignancies display an addiction to glutamine catabolism, and using [13C]-glutamine infusion in patients may help in predicting which tumors will respond to therapies that target glutamine metabolism [185]. As stated above, mitochondria and the signaling pathways that are responsive to ROS are intrinsically linked and targeting mitochondrial ROS through antioxidants has shown to efficiently hamper tumorigenesis both in vitro and in vivo [22]. However, many clinical studies showed that the effects of antioxidant treatment on the onset and progression of tumors are extraordinarily difficult to anticipate. It has indeed been reported that moderate/high increases of ROS could unexpectedly act as cancer suppressors by maintaining senescence-induced tumor suppression and sensitizing tumor cells to chemotherapeutic drugs, thus making the use of antioxidant treatments very limited and most of the time ineffective [22,186]. On the other side, to counterbalance the enhanced ROS production, tumor cells require NADPH and one way to achieve this is using one-carbon metabolism [22]. In this regard, beyond the critical identified role of SHMT2 in regulating redox homeostasis (via NADPH production) [144], MTHFD2 was also reported to be essential since its loss resulted in an improved capacity of sensitizing tumor cells to oxidant-induced cell death [145]. Targeting mitochondrial metabolic enzymes in combination with other therapies known to augment the production of ROS should then be considered and may eventually offer new promising therapeutic avenues.
In line with these last observations, ferroptosis has recently been described as an iron-dependent form of non-apoptotic cell death that can be activated in cancer cells by natural stimuli, synthetic agents, or the disruption of the cystine/glutamate antiporter xCT [66,187] (Figure 1). Three key hallmarks define ferroptosis, namely the oxidation of polyunsaturated fatty acid (PUFA)-containing phospholipids, the availability of redox-active iron and the loss of the glutathione peroxidase 4 (GPX4) [188,189,190] (Figure 1). Although it is uncertain whether mitochondria could have a function in this process, recent evidence could bring new findings on novel functions that impact on ferroptosis such as the status of ferroptosis suppressor protein 1 (FSP1) in the control of the reduced co-enzyme Q10 [191], which may potentially highlight the role of ferroptosis as a novel attractive therapeutic concept in cancer biology [192,193]. However, since no consensus on the role of mitochondria during ferroptosis has been reached, further investigations are still required.
Finally, altogether, these observations exemplify the intricate contribution of mitochondria during malignant transformation and progression, and how targeting tumor mitochondrial metabolism actually remains a big challenge.

5. Conclusions

In contrast to what Otto Warburg stated almost a century ago, the respiration of all cancer cells is not damaged and even more, it has become evident that mitochondrial metabolism does influence the functionality and aggressiveness of tumor cells. Mitochondria are indeed multifaceted organelles that impact on malignant initiation, growth, and survival, and multiple aspects of mitochondrial biology beyond ATP generation dynamically support the onset and development of tumors. Furthermore, the substantial flexibility that mitochondria confer to neoplastic cells, such as modifications in fuel choice utilization, bioenergetics, oxidative stress, and susceptibility to cell death, allows the survival of these cells in the face of hostile fluctuating microenvironmental conditions. The rapid metabolic shift of tumor cells towards OXPHOS when the Warburg effect is abrogated perfectly exemplifies this mitochondrial-induced flexibility and remarkably highlights the existence of a metabolic/bioenergetic continuum shared between glycolysis and mitochondria (OXPHOS). Importantly, tumor cell metabolism should not be perceived as a binary concept in which tumor cells only rely on the Warburg effect on one side or on OXPHOS on the other, but rather to an integrative system that displays different metabolic phenotypes and adaptations according to the location within the tumor microenvironment. Indeed, new evidence could reveal a dual capacity of tumor cells in sustaining both glycolysis and OXPHOS [172]. Finally, mitochondrial metabolism has brought significant attention as a target for the expansion of innovative anti-cancer agents. However, significant issues in translating these preclinical drugs (that were evidenced to be highly effective in eradicating tumorigenic cancer cells) towards clinical settings still remain, as their use would necessarily affect normal cells, including beneficial anti-cancer immune cells. Therefore, sophisticated therapeutic strategies in order to precisely modulate mitochondrial functions in a distinct cellular type will have to be defined in the future.

Author Contributions

Conceived and designed: S.C., M.V., M.Ž., J.P. Wrote the paper: S.C., M.V., M.Ž., J.P. Read, revised the manuscript and accepted the final version: S.C., M.V., M.Ž., J.P. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by “Le Groupement des Entreprises Monégasques dans la Lutte contre le cancer” (GEMLUC), the Centre Scientifique de Monaco (CSM) and University Côte d’Azur, Nice, France.

Acknowledgments

We thank all the members of our laboratory for providing helpful suggestions in order to enhance clarity of the manuscript.

Conflicts of Interest

The authors declare no conflict of interest. The funder had no role in the design of the study; in the collection, analysis, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

2-HG2-Hydroxyglutarate
ACLYATP-citrate lyase
CAFsCarcinoma-associated fibroblasts
DRP1Dynamin-related protein 1
EMTEpithelial-to-mesenchymal transition
F6PFructose-6-phosphate
FAOFatty acid oxidation
FDG-PETFluorodeoxyglucose-positron emission tomography
FHFumarate hydratase
FSP1Ferroptosis Suppressor Protein 1
G6PGlucose-6-phosphate
GDHGlutamate dehydrogenase
GLSGlutaminase
GPIGlucose-6-phosphate isomerase
GPX4Glutathione peroxidase 4
HATsHistone acetyl transferases
HCCHepatocellular carcinoma
HIFHypoxia Inducible Factors
IDHIsocitrate dehydrogenase
JMJJumonji domain
KEAP1Kelch like ECH-associated protein 1
KRASV-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog
LDHLactate dehydrogenase
MAPKMitogen-activated protein kinase
MCTMonocarboxylate transporter
MFN1Mitofusin 1
MOMPMitochondrial outer membrane permeabilization
MPTMitochondrial permeability transition
MTHFD2Methylenetetrahydrofolate dehydrogenase/cyclohydrolase
NAD+Nicotinamide adenine dinucleotide
NADPHNicotinamide adenine dinucleotide phosphate
NRF2Nuclear factor erythroid 2-related factor 2
OXPHOSOxidative phosphorylation
PGC-1αPeroxisome proliferator-activated receptor gamma coactivator-1 alpha
PHGDHPhosphoglycerate dehydrogenase
pHiIntracellular pH
PI3KPhosphoinositide 3 kinase
PKM2Pyruvate kinase
PPPPentose phosphate pathway
PTENPhosphatase and tensin homolog
PTK2BProtein tyrosine kinase 2 beta
PUFAPolyunsaturated fatty acid
RCDRegulated cell death
ROSReactive oxygen species
SDHSuccinate dehydrogenase complex iron sulfur subunit
SHMT2Serine hydroxylmethyltransferase
SIRT4Sirtuin 4
TCA cycleTricarboxylic acid cycle
TET dioxygenasesTen-eleven translocation dioxygenases
WTWild Type
α-KGα-Ketoglutarate

References

  1. Hanahan, D.; Weinberg, R.A. The hallmarks of cancer. Cell 2000, 100, 57–70. [Google Scholar] [CrossRef] [Green Version]
  2. Bui, J.D.; Schreiber, R.D. Cancer immunosurveillance, immunoediting and inflammation: Independent or interdependent processes? Curr. Opin. Immunol. 2007, 19, 203–208. [Google Scholar] [CrossRef] [PubMed]
  3. Hanahan, D.; Weinberg, R.A. Hallmarks of cancer: The next generation. Cell 2011, 144, 646–674. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Kroemer, G.; Senovilla, L.; Galluzzi, L.; Andre, F.; Zitvogel, L. Natural and therapy-induced immunosurveillance in breast cancer. Nat. Med. 2015, 21, 1128–1138. [Google Scholar] [CrossRef] [PubMed]
  5. Hsu, P.P.; Sabatini, D.M. Cancer cell metabolism: Warburg and beyond. Cell 2008, 134, 703–707. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Kroemer, G.; Pouyssegur, J. Tumor cell metabolism: Cancer’s Achilles’ heel. Cancer Cell 2008, 13, 472–482. [Google Scholar] [CrossRef]
  7. Erez, A.; DeBerardinis, R.J. Metabolic dysregulation in monogenic disorders and cancer—Finding method in madness. Nat. Rev. Cancer 2015, 15, 440–448. [Google Scholar] [CrossRef] [PubMed]
  8. Danhier, P.; Banski, P.; Payen, V.L.; Grasso, D.; Ippolito, L.; Sonveaux, P.; Porporato, P.E. Cancer metabolism in space and time: Beyond the Warburg effect. Biochim. Biophys. Acta Bioenergy 2017, 1858, 556–572. [Google Scholar] [CrossRef]
  9. Wallace, D.C. Mitochondria and cancer. Nat. Rev. Cancer 2012, 12, 685–698. [Google Scholar] [CrossRef] [Green Version]
  10. Vyas, S.; Zaganjor, E.; Haigis, M.C. Mitochondria and Cancer. Cell 2016, 166, 555–566. [Google Scholar] [CrossRef] [PubMed]
  11. Burgio, G.R. Commentary on the biological self: Toward a “Biological Ego”. From Garrod’s “chemical individuality” to Burnet’s “self”. Thymus 1990, 16, 99–117. [Google Scholar] [PubMed]
  12. Soares, M.P.; Teixeira, L.; Moita, L.F. Disease tolerance and immunity in host protection against infection. Nat. Rev. Immunol. 2017, 17, 83–96. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Warburg, O.; Wind, F.; Negelein, E. The metabolism of tumors in the body. J. Gen. Physiol. 1927, 8, 519–530. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Warburg, O. On the origin of cancer cells. Science 1956, 123, 309–314. [Google Scholar] [CrossRef] [PubMed]
  15. Vander Heiden, M.G.; Cantley, L.C.; Thompson, C.B. Understanding the Warburg effect: The metabolic requirements of cell proliferation. Science 2009, 324, 1029–1033. [Google Scholar] [CrossRef] [Green Version]
  16. Miles, K.A.; Williams, R.E. Warburg revisited: Imaging tumour blood flow and metabolism. Cancer Imaging 2008, 8, 81–86. [Google Scholar] [CrossRef] [Green Version]
  17. Weinhouse, S. On respiratory impairment in cancer cells. Science 1956, 124, 267–269. [Google Scholar] [CrossRef]
  18. Zamzami, N.; Marchetti, P.; Castedo, M.; Decaudin, D.; Macho, A.; Hirsch, T.; Susin, S.A.; Petit, P.X.; Mignotte, B.; Kroemer, G. Sequential reduction of mitochondrial transmembrane potential and generation of reactive oxygen species in early programmed cell death. J. Exp. Med. 1995, 182, 367–377. [Google Scholar] [CrossRef]
  19. Zamzami, N.; Marchetti, P.; Castedo, M.; Zanin, C.; Vayssiere, J.L.; Petit, P.X.; Kroemer, G. Reduction in mitochondrial potential constitutes an early irreversible step of programmed lymphocyte death In Vivo. J. Exp. Med. 1995, 181, 1661–1672. [Google Scholar] [CrossRef] [Green Version]
  20. Pathania, D.; Millard, M.; Neamati, N. Opportunities in discovery and delivery of anticancer drugs targeting mitochondria and cancer cell metabolism. Adv. Drug Deliv. Rev. 2009, 61, 1250–1275. [Google Scholar] [CrossRef]
  21. Fulda, S.; Galluzzi, L.; Kroemer, G. Targeting mitochondria for cancer therapy. Nat. Rev. Drug Discov. 2010, 9, 447–464. [Google Scholar] [CrossRef] [PubMed]
  22. Weinberg, S.E.; Chandel, N.S. Targeting mitochondria metabolism for cancer therapy. Nat. Chem. Biol. 2015, 11, 9–15. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Samudio, I.; Fiegl, M.; Andreeff, M. Mitochondrial uncoupling and the Warburg effect: Molecular basis for the reprogramming of cancer cell metabolism. Cancer Res. 2009, 69, 2163–2166. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Dang, L.; White, D.W.; Gross, S.; Bennett, B.D.; Bittinger, M.A.; Driggers, E.M.; Fantin, V.R.; Jang, H.G.; Jin, S.; Keenan, M.C.; et al. Cancer-associated IDH1 mutations produce 2-hydroxyglutarate. Nature 2009, 462, 739–744. [Google Scholar] [CrossRef] [Green Version]
  25. Wise, D.R.; Ward, P.S.; Shay, J.E.; Cross, J.R.; Gruber, J.J.; Sachdeva, U.M.; Platt, J.M.; DeMatteo, R.G.; Simon, M.C.; Thompson, C.B. Hypoxia promotes isocitrate dehydrogenase-dependent carboxylation of alpha-ketoglutarate to citrate to support cell growth and viability. Proc. Natl. Acad. Sci. USA 2011, 108, 19611–19616. [Google Scholar] [CrossRef] [Green Version]
  26. Fendt, S.M.; Bell, E.L.; Keibler, M.A.; Olenchock, B.A.; Mayers, J.R.; Wasylenko, T.M.; Vokes, N.I.; Guarente, L.; Vander Heiden, M.G.; Stephanopoulos, G. Reductive glutamine metabolism is a function of the alpha-ketoglutarate to citrate ratio in cells. Nat. Commun. 2013, 4, 2236. [Google Scholar] [CrossRef] [Green Version]
  27. Cormerais, Y.; Massard, P.A.; Vucetic, M.; Giuliano, S.; Tambutte, E.; Durivault, J.; Vial, V.; Endou, H.; Wempe, M.F.; Parks, S.K.; et al. The glutamine transporter ASCT2 (SLC1A5) promotes tumor growth independently of the amino acid transporter LAT1 (SLC7A5). J. Biol. Chem. 2018, 293, 2877–2887. [Google Scholar] [CrossRef] [Green Version]
  28. Lacoste, B.; Raymond, V.A.; Cassim, S.; Lapierre, P.; Bilodeau, M. Highly tumorigenic hepatocellular carcinoma cell line with cancer stem cell-like properties. PLoS ONE 2017, 12, e0171215. [Google Scholar] [CrossRef] [Green Version]
  29. Cassim, S.; Raymond, V.A.; Dehbidi-Assadzadeh, L.; Lapierre, P.; Bilodeau, M. Metabolic reprogramming enables hepatocarcinoma cells to efficiently adapt and survive to a nutrient-restricted microenvironment. Cell Cycle 2018, 17, 903–916. [Google Scholar] [CrossRef]
  30. Galluzzi, L.; Kepp, O.; Vander Heiden, M.G.; Kroemer, G. Metabolic targets for cancer therapy. Nat. Rev. Drug Discov. 2013, 12, 829–846. [Google Scholar] [CrossRef]
  31. Martinez-Outschoorn, U.E.; Peiris-Pages, M.; Pestell, R.G.; Sotgia, F.; Lisanti, M.P. Cancer metabolism: A therapeutic perspective. Nat. Rev. Clin. Oncol. 2017, 14, 11–31. [Google Scholar] [CrossRef] [PubMed]
  32. Dong, L.; Neuzil, J. Targeting mitochondria as an anticancer strategy. Cancer Commun. 2019, 39, 63. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Chang, C.H.; Qiu, J.; O’Sullivan, D.; Buck, M.D.; Noguchi, T.; Curtis, J.D.; Chen, Q.; Gindin, M.; Gubin, M.M.; van der Windt, G.J.; et al. Metabolic Competition in the tumor microenvironment is a driver of cancer progression. Cell 2015, 162, 1229–1241. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Pearce, E.L.; Poffenberger, M.C.; Chang, C.H.; Jones, R.G. Fueling immunity: Insights into metabolism and lymphocyte function. Science 2013, 342, 1242454. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Cassim, S.; Pouyssegur, J. Tumor Microenvironment: A metabolic player that shapes the immune response. Int. J. Mol. Sci. 2019, 21, 157. [Google Scholar] [CrossRef] [Green Version]
  36. Warburg, O. The metabolism of carcinoma cells. Cancer Res. 1925, 9, 148–163. [Google Scholar] [CrossRef] [Green Version]
  37. Warburg, O.; Wind, F.; Negelein, E. Über den stoffwechsel von tumoren im körper. Klin. Wochenschr. 1926, 5, 829–832. [Google Scholar] [CrossRef]
  38. Cori, C.F.; Cori, G.T. The carbohydrate metabolism of tumors. II. Changes in the sugar, lactic acid, and co-combining power of blood passing through a tumor. J. Biol. Chem. 1925, 65, 397–405. [Google Scholar]
  39. Crabtree, H.G. Observations on the carbohydrate metabolism of tumours. Biochem. J. 1929, 23, 536–545. [Google Scholar] [CrossRef]
  40. Chance, B.; Castor, L.N. Some patterns of the respiratory pigments of ascites tumors of mice. Science 1952, 116, 200–202. [Google Scholar] [CrossRef]
  41. Weinhouse, S. Hepatomas. Science 1967, 158, 542–543. [Google Scholar] [CrossRef] [PubMed]
  42. Foletti, A.; Fais, S. Unexpected discoveries should be reconsidered in science—A look to the past? Int. J. Mol. Sci. 2019, 20, 3973. [Google Scholar] [CrossRef] [Green Version]
  43. Koppenol, W.H.; Bounds, P.L.; Dang, C.V. Otto Warburg’s contributions to current concepts of cancer metabolism. Nat. Rev. Cancer 2011, 11, 325–337. [Google Scholar] [CrossRef]
  44. Racker, E. Bioenergetics and the problem of tumor growth. Am. Sci. 1972, 60, 56–63. [Google Scholar] [PubMed]
  45. Liberti, M.V.; Locasale, J.W. The warburg effect: How does it benefit cancer cells? Trends Biochem. Sci. 2016, 41, 211–218. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Boerner, P.; Resnick, R.J.; Racker, E. Stimulation of glycolysis and amino acid uptake in NRK-49F cells by transforming growth factor beta and epidermal growth factor. Proc. Natl. Acad. Sci. USA 1985, 82, 1350–1353. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Flier, J.S.; Mueckler, M.M.; Usher, P.; Lodish, H.F. Elevated levels of glucose transport and transporter messenger RNA are induced by ras or src oncogenes. Science 1987, 235, 1492–1495. [Google Scholar] [CrossRef]
  48. Birnbaum, M.J.; Haspel, H.C.; Rosen, O.M. Transformation of rat fibroblasts by FSV rapidly increases glucose transporter gene transcription. Science 1987, 235, 1495–1498. [Google Scholar] [CrossRef]
  49. Hiraki, Y.; Rosen, O.M.; Birnbaum, M.J. Growth factors rapidly induce expression of the glucose transporter gene. J. Biol. Chem. 1988, 263, 13655–13662. [Google Scholar]
  50. Fantin, V.R.; St-Pierre, J.; Leder, P. Attenuation of LDH-A expression uncovers a link between glycolysis, mitochondrial physiology, and tumor maintenance. Cancer Cell 2006, 9, 425–434. [Google Scholar] [CrossRef] [Green Version]
  51. Parks, S.K.; Mueller-Klieser, W.; Pouyssegur, J. Lactate and acidity in the cancer microenvironment. Annu. Rev. Cancer Biol. 2020, 4, 141–158. [Google Scholar] [CrossRef]
  52. Pouyssegur, J.; Franchi, A.; Salomon, J.C.; Silvestre, P. Isolation of a Chinese hamster fibroblast mutant defective in hexose transport and aerobic glycolysis: Its use to dissect the malignant phenotype. Proc. Natl. Acad. Sci. USA 1980, 77, 2698–2701. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Pouyssegur, J.; Franchi, A.; Silvestre, P. Relationship between increased aerobic glycolysis and DNA synthesis initiation studied using glycolytic mutant fibroblasts. Nature 1980, 287, 445–447. [Google Scholar] [CrossRef] [PubMed]
  54. de Padua, M.C.; Delodi, G.; Vucetic, M.; Durivault, J.; Vial, V.; Bayer, P.; Noleto, G.R.; Mazure, N.M.; Zdralevic, M.; Pouyssegur, J. Disrupting glucose-6-phosphate isomerase fully suppresses the “Warburg effect” and activates OXPHOS with minimal impact on tumor growth except in hypoxia. Oncotarget 2017, 8, 87623–87637. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Zdralevic, M.; Brand, A.; Di Ianni, L.; Dettmer, K.; Reinders, J.; Singer, K.; Peter, K.; Schnell, A.; Bruss, C.; Decking, S.M.; et al. Double genetic disruption of lactate dehydrogenases A and B is required to ablate the “Warburg effect” restricting tumor growth to oxidative metabolism. J. Biol. Chem. 2018, 293, 15947–15961. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Otto, A.M. Warburg effect(s)-a biographical sketch of Otto Warburg and his impacts on tumor metabolism. Cancer Metab. 2016, 4, 5. [Google Scholar] [CrossRef] [Green Version]
  57. Mookerjee, S.A.; Gerencser, A.A.; Nicholls, D.G.; Brand, M.D. Quantifying intracellular rates of glycolytic and oxidative ATP production and consumption using extracellular flux measurements. J. Biol. Chem. 2017, 292, 7189–7207. [Google Scholar] [CrossRef] [Green Version]
  58. Shestov, A.A.; Liu, X.; Ser, Z.; Cluntun, A.A.; Hung, Y.P.; Huang, L.; Kim, D.; Le, A.; Yellen, G.; Albeck, J.G.; et al. Quantitative determinants of aerobic glycolysis identify flux through the enzyme GAPDH as a limiting step. Elife 2014, 3, e00342. [Google Scholar] [CrossRef]
  59. Locasale, J.W.; Cantley, L.C. Metabolic flux and the regulation of mammalian cell growth. Cell Metab. 2011, 14, 443–451. [Google Scholar] [CrossRef] [Green Version]
  60. Lunt, S.Y.; Vander Heiden, M.G. Aerobic glycolysis: Meeting the metabolic requirements of cell proliferation. Annu. Rev. Cell Dev. Biol. 2011, 27, 441–464. [Google Scholar] [CrossRef] [Green Version]
  61. Zdralevic, M.; Marchiq, I.; de Padua, M.M.C.; Parks, S.K.; Pouyssegur, J. Metabolic plasiticy in cancers-distinct role of glycolytic enzymes GPI, LDHs or membrane transporters MCTs. Front. Oncol. 2017, 7, 313. [Google Scholar] [CrossRef] [PubMed]
  62. Cassim, S.; Raymond, V.A.; Lacoste, B.; Lapierre, P.; Bilodeau, M. Metabolite profiling identifies a signature of tumorigenicity in hepatocellular carcinoma. Oncotarget 2018, 9, 26868–26883. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Palm, W.; Thompson, C.B. Nutrient acquisition strategies of mammalian cells. Nature 2017, 546, 234–242. [Google Scholar] [CrossRef] [PubMed]
  64. DeNicola, G.M.; Chen, P.H.; Mullarky, E.; Sudderth, J.A.; Hu, Z.; Wu, D.; Tang, H.; Xie, Y.; Asara, J.M.; Huffman, K.E.; et al. NRF2 regulates serine biosynthesis in non-small cell lung cancer. Nat. Genet. 2015, 47, 1475–1481. [Google Scholar] [CrossRef] [Green Version]
  65. Semenza, G.L. Hypoxia-inducible factors: Coupling glucose metabolism and redox regulation with induction of the breast cancer stem cell phenotype. EMBO J. 2017, 36, 252–259. [Google Scholar] [CrossRef]
  66. Daher, B.; Parks, S.K.; Durivault, J.; Cormerais, Y.; Baidarjad, H.; Tambutte, E.; Pouyssegur, J.; Vucetic, M. Genetic ablation of the cystine transporter xCT in PDAC cells inhibits mTORC1, growth, survival, and tumor formation via nutrient and oxidative stresses. Cancer Res. 2019, 79, 3877–3890. [Google Scholar] [CrossRef] [Green Version]
  67. Ward, P.S.; Thompson, C.B. Metabolic reprogramming: A cancer hallmark even warburg did not anticipate. Cancer Cell 2012, 21, 297–308. [Google Scholar] [CrossRef] [Green Version]
  68. Jafri, M.S.; Dudycha, S.J.; O’Rourke, B. Cardiac energy metabolism: Models of cellular respiration. Annu. Rev. Biomed. Eng. 2001, 3, 57–81. [Google Scholar] [CrossRef]
  69. Schurr, A.; West, C.A.; Rigor, B.M. Lactate-supported synaptic function in the rat hippocampal slice preparation. Science 1988, 240, 1326–1328. [Google Scholar] [CrossRef]
  70. Schurr, A.; Payne, R.S.; Miller, J.J.; Rigor, B.M. Brain lactate, not glucose, fuels the recovery of synaptic function from hypoxia upon reoxygenation: An In Vitro study. Brain Res. 1997, 744, 105–111. [Google Scholar] [CrossRef]
  71. Faubert, B.; Li, K.Y.; Cai, L.; Hensley, C.T.; Kim, J.; Zacharias, L.G.; Yang, C.; Do, Q.N.; Doucette, S.; Burguete, D.; et al. Lactate metabolism in human lung tumors. Cell 2017, 171, 358–371.e9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  72. Hui, S.; Ghergurovich, J.M.; Morscher, R.J.; Jang, C.; Teng, X.; Lu, W.; Esparza, L.A.; Reya, T.; Le, Z.; Yanxiang Guo, J.; et al. Glucose feeds the TCA cycle via circulating lactate. Nature 2017, 551, 115–118. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  73. Wang, T.; Marquardt, C.; Foker, J. Aerobic glycolysis during lymphocyte proliferation. Nature 1976, 261, 702–705. [Google Scholar] [CrossRef]
  74. DeBerardinis, R.J. Is cancer a disease of abnormal cellular metabolism? New angles on an old idea. Genet. Med. 2008, 10, 767–777. [Google Scholar] [CrossRef] [Green Version]
  75. DeBerardinis, R.J.; Mancuso, A.; Daikhin, E.; Nissim, I.; Yudkoff, M.; Wehrli, S.; Thompson, C.B. Beyond aerobic glycolysis: Transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis. Proc. Natl. Acad. Sci. USA 2007, 104, 19345–19350. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  76. Pusapati, R.V.; Daemen, A.; Wilson, C.; Sandoval, W.; Gao, M.; Haley, B.; Baudy, A.R.; Hatzivassiliou, G.; Evangelista, M.; Settleman, J. mTORC1-dependent metabolic reprogramming underlies escape from glycolysis addiction in cancer cells. Cancer Cell 2016, 29, 548–562. [Google Scholar] [CrossRef] [Green Version]
  77. Krieg, A.F.; Rosenblum, L.J.; Henry, J.B. Lactate dehydrogenase isoenzymes a comparison of pyruvate-to-lactate and lactate-to-pyruvate assays. Clin. Chem. 1967, 13, 196–203. [Google Scholar] [CrossRef] [PubMed]
  78. Koen, A.L.; Goodman, M. Lactate dehydrogenase isozymes: Qualitative and quantitative changes during primate evolution. Biochem. Genet. 1969, 3, 457–474. [Google Scholar] [CrossRef] [PubMed]
  79. Miao, P.; Sheng, S.; Sun, X.; Liu, J.; Huang, G. Lactate dehydrogenase A in cancer: A promising target for diagnosis and therapy. IUBMB Life 2013, 65, 904–910. [Google Scholar] [CrossRef] [PubMed]
  80. Mishra, D.; Banerjee, D. Lactate dehydrogenases as metabolic links between tumor and stroma in the tumor microenvironment. Cancers 2019, 11, 750. [Google Scholar] [CrossRef] [Green Version]
  81. Halestrap, A.P. Monocarboxylic acid transport. Compr. Physiol. 2013, 3, 1611–1643. [Google Scholar] [CrossRef] [PubMed]
  82. Brahimi-Horn, M.C.; Bellot, G.; Pouyssegur, J. Hypoxia and energetic tumour metabolism. Curr. Opin. Genet. Dev. 2011, 21, 67–72. [Google Scholar] [CrossRef] [PubMed]
  83. Chiche, J.; Le Fur, Y.; Vilmen, C.; Frassineti, F.; Daniel, L.; Halestrap, A.P.; Cozzone, P.J.; Pouyssegur, J.; Lutz, N.W. In Vivo pH in metabolic-defective Ras-transformed fibroblast tumors: Key role of the monocarboxylate transporter, MCT4, for inducing an alkaline intracellular pH. Int. J. Cancer 2012, 130, 1511–1520. [Google Scholar] [CrossRef]
  84. Doyen, J.; Trastour, C.; Ettore, F.; Peyrottes, I.; Toussant, N.; Gal, J.; Ilc, K.; Roux, D.; Parks, S.K.; Ferrero, J.M.; et al. Expression of the hypoxia-inducible monocarboxylate transporter MCT4 is increased in triple negative breast cancer and correlates independently with clinical outcome. Biochem. Biophys. Res. Commun. 2014, 451, 54–61. [Google Scholar] [CrossRef] [PubMed]
  85. Granja, S.; Tavares-Valente, D.; Queiros, O.; Baltazar, F. Value of pH regulators in the diagnosis, prognosis and treatment of cancer. Semin. Cancer Biol. 2017, 43, 17–34. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  86. Le Floch, R.; Chiche, J.; Marchiq, I.; Naiken, T.; Ilc, K.; Murray, C.M.; Critchlow, S.E.; Roux, D.; Simon, M.P.; Pouyssegur, J. CD147 subunit of lactate/H+ symporters MCT1 and hypoxia-inducible MCT4 is critical for energetics and growth of glycolytic tumors. Proc. Natl. Acad. Sci. USA 2011, 108, 16663–16668. [Google Scholar] [CrossRef] [Green Version]
  87. Granja, S.; Marchiq, I.; Le Floch, R.; Moura, C.S.; Baltazar, F.; Pouyssegur, J. Disruption of BASIGIN decreases lactic acid export and sensitizes non-small cell lung cancer to biguanides independently of the LKB1 status. Oncotarget 2015, 6, 6708–6721. [Google Scholar] [CrossRef] [Green Version]
  88. Marchiq, I.; Le Floch, R.; Roux, D.; Simon, M.P.; Pouyssegur, J. Genetic disruption of lactate/H+ symporters (MCTs) and their subunit CD147/BASIGIN sensitizes glycolytic tumor cells to phenformin. Cancer Res. 2015, 75, 171–180. [Google Scholar] [CrossRef]
  89. Zdralevic, M.; Vucetic, M.; Daher, B.; Marchiq, I.; Parks, S.K.; Pouyssegur, J. Disrupting the ‘Warburg effect’ re-routes cancer cells to OXPHOS offering a vulnerability point via ‘ferroptosis’-induced cell death. Adv. Biol. Regul. 2018, 68, 55–63. [Google Scholar] [CrossRef]
  90. Balgi, A.D.; Diering, G.H.; Donohue, E.; Lam, K.K.; Fonseca, B.D.; Zimmerman, C.; Numata, M.; Roberge, M. Regulation of mTORC1 signaling by pH. PLoS ONE 2011, 6, e21549. [Google Scholar] [CrossRef]
  91. Chambard, J.C.; Pouyssegur, J. Intracellular pH controls growth factor-induced ribosomal protein S6 phosphorylation and protein synthesis in the G0→G1 transition of fibroblasts. Exp. Cell Res. 1986, 164, 282–294. [Google Scholar] [CrossRef]
  92. Benjamin, D.; Robay, D.; Hindupur, S.K.; Pohlmann, J.; Colombi, M.; El-Shemerly, M.Y.; Maira, S.M.; Moroni, C.; Lane, H.A.; Hall, M.N. Dual inhibition of the lactate transporters MCT1 and MCT4 is synthetic lethal with metformin due to NAD+ depletion in cancer cells. Cell Rep. 2018, 25, 3047–3058.e4. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  93. Parks, S.K.; Chiche, J.; Pouyssegur, J. Disrupting proton dynamics and energy metabolism for cancer therapy. Nat. Rev. Cancer 2013, 13, 611–623. [Google Scholar] [CrossRef] [PubMed]
  94. Parks, S.K.; Mazure, N.M.; Counillon, L.; Pouyssegur, J. Hypoxia promotes tumor cell survival in acidic conditions by preserving ATP levels. J. Cell Physiol. 2013, 228, 1854–1862. [Google Scholar] [CrossRef]
  95. Anderson, R.G.; Ghiraldeli, L.P.; Pardee, T.S. Mitochondria in cancer metabolism, an organelle whose time has come? Biochim. Biophys. Acta Rev. Cancer 2018, 1870, 96–102. [Google Scholar] [CrossRef]
  96. Sabharwal, S.S.; Schumacker, P.T. Mitochondrial ROS in cancer: Initiators, amplifiers or an Achilles’ heel? Nat. Rev. Cancer 2014, 14, 709–721. [Google Scholar] [CrossRef] [Green Version]
  97. Gaude, E.; Frezza, C. Defects in mitochondrial metabolism and cancer. Cancer Metab. 2014, 2, 10. [Google Scholar] [CrossRef] [Green Version]
  98. Murphy, M.P. How mitochondria produce reactive oxygen species. Biochem. J. 2009, 417, 1–13. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  99. Jensen, P.K. Antimycin-insensitive oxidation of succinate and reduced nicotinamide-adenine dinucleotide in electron-transport particles. I. pH dependency and hydrogen peroxide formation. Biochim. Biophys. Acta 1966, 122, 157–166. [Google Scholar] [CrossRef]
  100. Loschen, G.; Flohe, L.; Chance, B. Respiratory chain linked H2O2 production in pigeon heart mitochondria. FEBS Lett. 1971, 18, 261–264. [Google Scholar] [CrossRef] [Green Version]
  101. Boveris, A.; Chance, B. The mitochondrial generation of hydrogen peroxide. General properties and effect of hyperbaric oxygen. Biochem. J. 1973, 134, 707–716. [Google Scholar] [CrossRef] [PubMed]
  102. Chance, B.; Sies, H.; Boveris, A. Hydroperoxide metabolism in mammalian organs. Physiol. Rev. 1979, 59, 527–605. [Google Scholar] [CrossRef] [PubMed]
  103. Moreno-Sanchez, R.; Hernandez-Esquivel, L.; Rivero-Segura, N.A.; Marin-Hernandez, A.; Neuzil, J.; Ralph, S.J.; Rodriguez-Enriquez, S. Reactive oxygen species are generated by the respiratory complex II—Evidence for lack of contribution of the reverse electron flow in complex I. FEBS J. 2013, 280, 927–938. [Google Scholar] [CrossRef] [PubMed]
  104. Sung, H.J.; Ma, W.; Starost, M.F.; Lago, C.U.; Lim, P.K.; Sack, M.N.; Kang, J.G.; Wang, P.Y.; Hwang, P.M. Ambient oxygen promotes tumorigenesis. PLoS ONE 2011, 6, e19785. [Google Scholar] [CrossRef] [Green Version]
  105. Park, S.M.; Ou, J.; Chamberlain, L.; Simone, T.M.; Yang, H.; Virbasius, C.M.; Ali, A.M.; Zhu, L.J.; Mukherjee, S.; Raza, A.; et al. U2AF35(S34F) promotes transformation by directing aberrant ATG7 pre-mRNA 3′ end formation. Mol. Cell 2016, 62, 479–490. [Google Scholar] [CrossRef] [Green Version]
  106. Galluzzi, L.; Pietrocola, F.; Bravo-San Pedro, J.M.; Amaravadi, R.K.; Baehrecke, E.H.; Cecconi, F.; Codogno, P.; Debnath, J.; Gewirtz, D.A.; Karantza, V.; et al. Autophagy in malignant transformation and cancer progression. EMBO J. 2015, 34, 856–880. [Google Scholar] [CrossRef]
  107. Rosenfeldt, M.T.; O’Prey, J.; Morton, J.P.; Nixon, C.; MacKay, G.; Mrowinska, A.; Au, A.; Rai, T.S.; Zheng, L.; Ridgway, R.; et al. p53 status determines the role of autophagy in pancreatic tumour development. Nature 2013, 504, 296–300. [Google Scholar] [CrossRef]
  108. Rhee, S.G. Cell signaling. H2O2, a necessary evil for cell signaling. Science 2006, 312, 1882–1883. [Google Scholar] [CrossRef]
  109. Sullivan, L.B.; Chandel, N.S. Mitochondrial reactive oxygen species and cancer. Cancer Metab. 2014, 2, 17. [Google Scholar] [CrossRef] [Green Version]
  110. Weinberg, F.; Hamanaka, R.; Wheaton, W.W.; Weinberg, S.; Joseph, J.; Lopez, M.; Kalyanaraman, B.; Mutlu, G.M.; Budinger, G.R.; Chandel, N.S. Mitochondrial metabolism and ROS generation are essential for Kras-mediated tumorigenicity. Proc. Natl. Acad. Sci. USA 2010, 107, 8788–8793. [Google Scholar] [CrossRef] [Green Version]
  111. Kamata, H.; Honda, S.; Maeda, S.; Chang, L.; Hirata, H.; Karin, M. Reactive oxygen species promote TNFalpha-induced death and sustained JNK activation by inhibiting MAP kinase phosphatases. Cell 2005, 120, 649–661. [Google Scholar] [CrossRef] [Green Version]
  112. Davis, R.J. Signal transduction by the JNK group of MAP kinases. Cell 2000, 103, 239–252. [Google Scholar] [CrossRef] [Green Version]
  113. Irani, K.; Xia, Y.; Zweier, J.L.; Sollott, S.J.; Der, C.J.; Fearon, E.R.; Sundaresan, M.; Finkel, T.; Goldschmidt-Clermont, P.J. Mitogenic signaling mediated by oxidants in Ras-transformed fibroblasts. Science 1997, 275, 1649–1652. [Google Scholar] [CrossRef] [PubMed]
  114. Ziech, D.; Franco, R.; Pappa, A.; Panayiotidis, M.I. Reactive oxygen species (ROS)—Induced genetic and epigenetic alterations in human carcinogenesis. Mutat. Res. 2011, 711, 167–173. [Google Scholar] [CrossRef] [PubMed]
  115. Lim, S.O.; Gu, J.M.; Kim, M.S.; Kim, H.S.; Park, Y.N.; Park, C.K.; Cho, J.W.; Park, Y.M.; Jung, G. Epigenetic changes induced by reactive oxygen species in hepatocellular carcinoma: Methylation of the E-cadherin promoter. Gastroenterology 2008, 135, 2128–2140. [Google Scholar] [CrossRef]
  116. Sullivan, L.B.; Gui, D.Y.; Vander Heiden, M.G. Altered metabolite levels in cancer: Implications for tumour biology and cancer therapy. Nat. Rev. Cancer 2016, 16, 680–693. [Google Scholar] [CrossRef]
  117. Nowicki, S.; Gottlieb, E. Oncometabolites: Tailoring our genes. FEBS J. 2015, 282, 2796–2805. [Google Scholar] [CrossRef]
  118. Letouze, E.; Martinelli, C.; Loriot, C.; Burnichon, N.; Abermil, N.; Ottolenghi, C.; Janin, M.; Menara, M.; Nguyen, A.T.; Benit, P.; et al. SDH mutations establish a hypermethylator phenotype in paraganglioma. Cancer Cell 2013, 23, 739–752. [Google Scholar] [CrossRef] [Green Version]
  119. Xu, W.; Yang, H.; Liu, Y.; Yang, Y.; Wang, P.; Kim, S.H.; Ito, S.; Yang, C.; Wang, P.; Xiao, M.T.; et al. Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of alpha-ketoglutarate-dependent dioxygenases. Cancer Cell 2011, 19, 17–30. [Google Scholar] [CrossRef] [Green Version]
  120. Koivunen, P.; Lee, S.; Duncan, C.G.; Lopez, G.; Lu, G.; Ramkissoon, S.; Losman, J.A.; Joensuu, P.; Bergmann, U.; Gross, S.; et al. Transformation by the (R)-enantiomer of 2-hydroxyglutarate linked to EGLN activation. Nature 2012, 483, 484–488. [Google Scholar] [CrossRef]
  121. Favier, J.; Buffet, A.; Gimenez-Roqueplo, A.P. HIF2A mutations in paraganglioma with polycythemia. N. Engl. J. Med. 2012, 367, 2161. [Google Scholar] [CrossRef] [PubMed]
  122. Adam, J.; Hatipoglu, E.; O’Flaherty, L.; Ternette, N.; Sahgal, N.; Lockstone, H.; Baban, D.; Nye, E.; Stamp, G.W.; Wolhuter, K.; et al. Renal cyst formation in Fh1-deficient mice is independent of the Hif/Phd pathway: Roles for fumarate in KEAP1 succination and Nrf2 signaling. Cancer Cell 2011, 20, 524–537. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  123. Sullivan, L.B.; Martinez-Garcia, E.; Nguyen, H.; Mullen, A.R.; Dufour, E.; Sudarshan, S.; Licht, J.D.; Deberardinis, R.J.; Chandel, N.S. The proto-oncometabolite fumarate binds glutathione to amplify ROS-dependent signaling. Mol. Cell 2013, 51, 236–248. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  124. Pavlova, N.N.; Thompson, C.B. The emerging hallmarks of cancer metabolism. Cell Metab. 2016, 23, 27–47. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  125. Porporato, P.E.; Filigheddu, N.; Pedro, J.M.B.; Kroemer, G.; Galluzzi, L. Mitochondrial metabolism and cancer. Cell Res. 2018, 28, 265–280. [Google Scholar] [CrossRef]
  126. Rohrig, F.; Schulze, A. The multifaceted roles of fatty acid synthesis in cancer. Nat. Rev. Cancer 2016, 16, 732–749. [Google Scholar] [CrossRef]
  127. Wellen, K.E.; Hatzivassiliou, G.; Sachdeva, U.M.; Bui, T.V.; Cross, J.R.; Thompson, C.B. ATP-citrate lyase links cellular metabolism to histone acetylation. Science 2009, 324, 1076–1080. [Google Scholar] [CrossRef] [Green Version]
  128. Currie, E.; Schulze, A.; Zechner, R.; Walther, T.C.; Farese, R.V., Jr. Cellular fatty acid metabolism and cancer. Cell Metab. 2013, 18, 153–161. [Google Scholar] [CrossRef] [Green Version]
  129. Carracedo, A.; Cantley, L.C.; Pandolfi, P.P. Cancer metabolism: Fatty acid oxidation in the limelight. Nat. Rev. Cancer 2013, 13, 227–232. [Google Scholar] [CrossRef]
  130. Kinnaird, A.; Zhao, S.; Wellen, K.E.; Michelakis, E.D. Metabolic control of epigenetics in cancer. Nat. Rev. Cancer 2016, 16, 694–707. [Google Scholar] [CrossRef]
  131. Lee, J.V.; Carrer, A.; Shah, S.; Snyder, N.W.; Wei, S.; Venneti, S.; Worth, A.J.; Yuan, Z.F.; Lim, H.W.; Liu, S.; et al. Akt-dependent metabolic reprogramming regulates tumor cell histone acetylation. Cell Metab. 2014, 20, 306–319. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  132. Stine, Z.E.; Walton, Z.E.; Altman, B.J.; Hsieh, A.L.; Dang, C.V. MYC, metabolism, and cancer. Cancer Discov. 2015, 5, 1024–1039. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  133. Jeong, S.M.; Lee, A.; Lee, J.; Haigis, M.C. SIRT4 protein suppresses tumor formation in genetic models of Myc-induced B cell lymphoma. J. Biol. Chem. 2014, 289, 4135–4144. [Google Scholar] [CrossRef] [Green Version]
  134. Coloff, J.L.; Murphy, J.P.; Braun, C.R.; Harris, I.S.; Shelton, L.M.; Kami, K.; Gygi, S.P.; Selfors, L.M.; Brugge, J.S. Differential glutamate metabolism in proliferating and quiescent mammary epithelial cells. Cell Metab. 2016, 23, 867–880. [Google Scholar] [CrossRef] [PubMed]
  135. Metallo, C.M.; Gameiro, P.A.; Bell, E.L.; Mattaini, K.R.; Yang, J.; Hiller, K.; Jewell, C.M.; Johnson, Z.R.; Irvine, D.J.; Guarente, L.; et al. Reductive glutamine metabolism by IDH1 mediates lipogenesis under hypoxia. Nature 2011, 481, 380–384. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  136. Jiang, L.; Shestov, A.A.; Swain, P.; Yang, C.; Parker, S.J.; Wang, Q.A.; Terada, L.S.; Adams, N.D.; McCabe, M.T.; Pietrak, B.; et al. Reductive carboxylation supports redox homeostasis during anchorage-independent growth. Nature 2016, 532, 255–258. [Google Scholar] [CrossRef]
  137. Le, A.; Lane, A.N.; Hamaker, M.; Bose, S.; Gouw, A.; Barbi, J.; Tsukamoto, T.; Rojas, C.J.; Slusher, B.S.; Zhang, H.; et al. Glucose-independent glutamine metabolism via TCA cycling for proliferation and survival in B cells. Cell Metab. 2012, 15, 110–121. [Google Scholar] [CrossRef] [Green Version]
  138. Son, J.; Lyssiotis, C.A.; Ying, H.; Wang, X.; Hua, S.; Ligorio, M.; Perera, R.M.; Ferrone, C.R.; Mullarky, E.; Shyh-Chang, N.; et al. Glutamine supports pancreatic cancer growth through a KRAS-regulated metabolic pathway. Nature 2013, 496, 101–105. [Google Scholar] [CrossRef]
  139. Gorrini, C.; Harris, I.S.; Mak, T.W. Modulation of oxidative stress as an anticancer strategy. Nat. Rev. Drug Discov. 2013, 12, 931–947. [Google Scholar] [CrossRef]
  140. Boroughs, L.K.; DeBerardinis, R.J. Metabolic pathways promoting cancer cell survival and growth. Nat. Cell Biol. 2015, 17, 351–359. [Google Scholar] [CrossRef] [Green Version]
  141. Cluntun, A.A.; Lukey, M.J.; Cerione, R.A.; Locasale, J.W. Glutamine metabolism in cancer: Understanding the heterogeneity. Trends Cancer 2017, 3, 169–180. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  142. Davidson, S.M.; Papagiannakopoulos, T.; Olenchock, B.A.; Heyman, J.E.; Keibler, M.A.; Luengo, A.; Bauer, M.R.; Jha, A.K.; O’Brien, J.P.; Pierce, K.A.; et al. Environment impacts the metabolic dependencies of ras-driven non-small cell lung cancer. Cell Metab. 2016, 23, 517–528. [Google Scholar] [CrossRef] [PubMed]
  143. Fan, J.; Ye, J.; Kamphorst, J.J.; Shlomi, T.; Thompson, C.B.; Rabinowitz, J.D. Quantitative flux analysis reveals folate-dependent NADPH production. Nature 2014, 510, 298–302. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  144. Ye, J.; Fan, J.; Venneti, S.; Wan, Y.W.; Pawel, B.R.; Zhang, J.; Finley, L.W.; Lu, C.; Lindsten, T.; Cross, J.R.; et al. Serine catabolism regulates mitochondrial redox control during hypoxia. Cancer Discov. 2014, 4, 1406–1417. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  145. Nilsson, R.; Jain, M.; Madhusudhan, N.; Sheppard, N.G.; Strittmatter, L.; Kampf, C.; Huang, J.; Asplund, A.; Mootha, V.K. Metabolic enzyme expression highlights a key role for MTHFD2 and the mitochondrial folate pathway in cancer. Nat. Commun. 2014, 5, 3128. [Google Scholar] [CrossRef] [Green Version]
  146. Kim, D.; Fiske, B.P.; Birsoy, K.; Freinkman, E.; Kami, K.; Possemato, R.L.; Chudnovsky, Y.; Pacold, M.E.; Chen, W.W.; Cantor, J.R.; et al. SHMT2 drives glioma cell survival in ischaemia but imposes a dependence on glycine clearance. Nature 2015, 520, 363–367. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  147. Czabotar, P.E.; Lessene, G.; Strasser, A.; Adams, J.M. Control of apoptosis by the BCL-2 protein family: Implications for physiology and therapy. Nat. Rev. Mol. Cell Biol. 2014, 15, 49–63. [Google Scholar] [CrossRef]
  148. Green, D.R.; Galluzzi, L.; Kroemer, G. Cell biology. Metabolic control of cell death. Science 2014, 345, 1250256. [Google Scholar] [CrossRef] [Green Version]
  149. Lopez, J.; Tait, S.W. Mitochondrial apoptosis: Killing cancer using the enemy within. Br. J. Cancer 2015, 112, 957–962. [Google Scholar] [CrossRef] [Green Version]
  150. Bonnet, S.; Archer, S.L.; Allalunis-Turner, J.; Haromy, A.; Beaulieu, C.; Thompson, R.; Lee, C.T.; Lopaschuk, G.D.; Puttagunta, L.; Bonnet, S.; et al. A mitochondria-K+ channel axis is suppressed in cancer and its normalization promotes apoptosis and inhibits cancer growth. Cancer Cell 2007, 11, 37–51. [Google Scholar] [CrossRef] [Green Version]
  151. Goldin, N.; Arzoine, L.; Heyfets, A.; Israelson, A.; Zaslavsky, Z.; Bravman, T.; Bronner, V.; Notcovich, A.; Shoshan-Barmatz, V.; Flescher, E. Methyl jasmonate binds to and detaches mitochondria-bound hexokinase. Oncogene 2008, 27, 4636–4643. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  152. Vaughn, A.E.; Deshmukh, M. Glucose metabolism inhibits apoptosis in neurons and cancer cells by redox inactivation of cytochrome c. Nat. Cell Biol. 2008, 10, 1477–1483. [Google Scholar] [CrossRef] [PubMed]
  153. Suen, D.F.; Norris, K.L.; Youle, R.J. Mitochondrial dynamics and apoptosis. Genes Dev. 2008, 22, 1577–1590. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  154. Kashatus, J.A.; Nascimento, A.; Myers, L.J.; Sher, A.; Byrne, F.L.; Hoehn, K.L.; Counter, C.M.; Kashatus, D.F. Erk2 phosphorylation of Drp1 promotes mitochondrial fission and MAPK-driven tumor growth. Mol. Cell 2015, 57, 537–551. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  155. Renault, T.T.; Floros, K.V.; Elkholi, R.; Corrigan, K.A.; Kushnareva, Y.; Wieder, S.Y.; Lindtner, C.; Serasinghe, M.N.; Asciolla, J.J.; Buettner, C.; et al. Mitochondrial shape governs BAX-induced membrane permeabilization and apoptosis. Mol. Cell 2015, 57, 69–82. [Google Scholar] [CrossRef] [Green Version]
  156. Valastyan, S.; Weinberg, R.A. Tumor metastasis: Molecular insights and evolving paradigms. Cell 2011, 147, 275–292. [Google Scholar] [CrossRef] [Green Version]
  157. Nieto, M.A.; Huang, R.Y.; Jackson, R.A.; Thiery, J.P. Emt: 2016. Cell 2016, 166, 21–45. [Google Scholar] [CrossRef] [Green Version]
  158. Pouyssegur, J.; Dayan, F.; Mazure, N.M. Hypoxia signalling in cancer and approaches to enforce tumour regression. Nature 2006, 441, 437–443. [Google Scholar] [CrossRef]
  159. Rofstad, E.K.; Galappathi, K.; Mathiesen, B.; Ruud, E.B. Fluctuating and diffusion-limited hypoxia in hypoxia-induced metastasis. Clin. Cancer Res. 2007, 13, 1971–1978. [Google Scholar] [CrossRef] [Green Version]
  160. Frezza, C. Mitochondrial metabolites: Undercover signalling molecules. Interface Focus 2017, 7, 20160100. [Google Scholar] [CrossRef]
  161. Sciacovelli, M.; Goncalves, E.; Johnson, T.I.; Zecchini, V.R.; da Costa, A.S.; Gaude, E.; Drubbel, A.V.; Theobald, S.J.; Abbo, S.R.; Tran, M.G.; et al. Fumarate is an epigenetic modifier that elicits epithelial-to-mesenchymal transition. Nature 2016, 537, 544–547. [Google Scholar] [CrossRef] [PubMed]
  162. Sciacovelli, M.; Frezza, C. Fumarate drives EMT in renal cancer. Cell Death Differ. 2017, 24, 1–2. [Google Scholar] [CrossRef] [PubMed]
  163. LeBleu, V.S.; O’Connell, J.T.; Gonzalez Herrera, K.N.; Wikman, H.; Pantel, K.; Haigis, M.C.; de Carvalho, F.M.; Damascena, A.; Domingos Chinen, L.T.; Rocha, R.M.; et al. PGC-1alpha mediates mitochondrial biogenesis and oxidative phosphorylation in cancer cells to promote metastasis. Nat. Cell Biol. 2014, 16, 992–1003. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  164. Tan, Z.; Luo, X.; Xiao, L.; Tang, M.; Bode, A.M.; Dong, Z.; Cao, Y. The role of PGC1alpha in cancer metabolism and its therapeutic implications. Mol. Cancer Ther. 2016, 15, 774–782. [Google Scholar] [CrossRef] [Green Version]
  165. Porporato, P.E.; Payen, V.L.; Perez-Escuredo, J.; De Saedeleer, C.J.; Danhier, P.; Copetti, T.; Dhup, S.; Tardy, M.; Vazeille, T.; Bouzin, C.; et al. A mitochondrial switch promotes tumor metastasis. Cell Rep. 2014, 8, 754–766. [Google Scholar] [CrossRef] [Green Version]
  166. Park, J.H.; Vithayathil, S.; Kumar, S.; Sung, P.L.; Dobrolecki, L.E.; Putluri, V.; Bhat, V.B.; Bhowmik, S.K.; Gupta, V.; Arora, K.; et al. Fatty acid oxidation-driven src links mitochondrial energy reprogramming and oncogenic properties in triple-negative breast cancer. Cell Rep. 2016, 14, 2154–2165. [Google Scholar] [CrossRef] [Green Version]
  167. Senft, D.; Ronai, Z.A. Regulators of mitochondrial dynamics in cancer. Curr. Opin. Cell Biol. 2016, 39, 43–52. [Google Scholar] [CrossRef] [Green Version]
  168. Piskounova, E.; Agathocleous, M.; Murphy, M.M.; Hu, Z.; Huddlestun, S.E.; Zhao, Z.; Leitch, A.M.; Johnson, T.M.; DeBerardinis, R.J.; Morrison, S.J. Oxidative stress inhibits distant metastasis by human melanoma cells. Nature 2015, 527, 186–191. [Google Scholar] [CrossRef] [Green Version]
  169. Sayin, V.I.; Ibrahim, M.X.; Larsson, E.; Nilsson, J.A.; Lindahl, P.; Bergo, M.O. Antioxidants accelerate lung cancer progression in mice. Sci. Transl. Med. 2014, 6, 221ra215. [Google Scholar] [CrossRef]
  170. Costa, A.; Scholer-Dahirel, A.; Mechta-Grigoriou, F. The role of reactive oxygen species and metabolism on cancer cells and their microenvironment. Semin. Cancer Biol. 2014, 25, 23–32. [Google Scholar] [CrossRef]
  171. Toullec, A.; Gerald, D.; Despouy, G.; Bourachot, B.; Cardon, M.; Lefort, S.; Richardson, M.; Rigaill, G.; Parrini, M.C.; Lucchesi, C.; et al. Oxidative stress promotes myofibroblast differentiation and tumour spreading. EMBO Mol. Med. 2010, 2, 211–230. [Google Scholar] [CrossRef] [PubMed]
  172. Gentric, G.; Mieulet, V.; Mechta-Grigoriou, F. Heterogeneity in cancer metabolism: New concepts in an old field. Antioxid. Redox Signal. 2017, 26, 462–485. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  173. Pelon, F.; Bourachot, B.; Kieffer, Y.; Magagna, I.; Mermet-Meillon, F.; Bonnet, I.; Costa, A.; Givel, A.M.; Attieh, Y.; Barbazan, J.; et al. Cancer-associated fibroblast heterogeneity in axillary lymph nodes drives metastases in breast cancer through complementary mechanisms. Nat. Commun. 2020, 11, 404. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  174. Galluzzi, L.; Buque, A.; Kepp, O.; Zitvogel, L.; Kroemer, G. Immunological effects of conventional chemotherapy and targeted anticancer agents. Cancer Cell 2015, 28, 690–714. [Google Scholar] [CrossRef] [Green Version]
  175. Jain, R.K.; Munn, L.L.; Fukumura, D. Dissecting tumour pathophysiology using intravital microscopy. Nat. Rev. Cancer 2002, 2, 266–276. [Google Scholar] [CrossRef]
  176. Rumsey, W.L.; Schlosser, C.; Nuutinen, E.M.; Robiolio, M.; Wilson, D.F. Cellular energetics and the oxygen dependence of respiration in cardiac myocytes isolated from adult rat. J. Biol. Chem. 1990, 265, 15392–15402. [Google Scholar]
  177. Caro, P.; Kishan, A.U.; Norberg, E.; Stanley, I.A.; Chapuy, B.; Ficarro, S.B.; Polak, K.; Tondera, D.; Gounarides, J.; Yin, H.; et al. Metabolic signatures uncover distinct targets in molecular subsets of diffuse large B cell lymphoma. Cancer Cell 2012, 22, 547–560. [Google Scholar] [CrossRef] [Green Version]
  178. Vazquez, F.; Lim, J.H.; Chim, H.; Bhalla, K.; Girnun, G.; Pierce, K.; Clish, C.B.; Granter, S.R.; Widlund, H.R.; Spiegelman, B.M.; et al. PGC1alpha expression defines a subset of human melanoma tumors with increased mitochondrial capacity and resistance to oxidative stress. Cancer Cell 2013, 23, 287–301. [Google Scholar] [CrossRef] [Green Version]
  179. Momcilovic, M.; Jones, A.; Bailey, S.T.; Waldmann, C.M.; Li, R.; Lee, J.T.; Abdelhady, G.; Gomez, A.; Holloway, T.; Schmid, E.; et al. In Vivo imaging of mitochondrial membrane potential in non-small-cell lung cancer. Nature 2019, 575, 380–384. [Google Scholar] [CrossRef]
  180. Molina, J.R.; Sun, Y.; Protopopova, M.; Gera, S.; Bandi, M.; Bristow, C.; McAfoos, T.; Morlacchi, P.; Ackroyd, J.; Agip, A.A.; et al. An inhibitor of oxidative phosphorylation exploits cancer vulnerability. Nat. Med. 2018, 24, 1036–1046. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  181. Skrtic, M.; Sriskanthadevan, S.; Jhas, B.; Gebbia, M.; Wang, X.; Wang, Z.; Hurren, R.; Jitkova, Y.; Gronda, M.; Maclean, N.; et al. Inhibition of mitochondrial translation as a therapeutic strategy for human acute myeloid leukemia. Cancer Cell 2011, 20, 674–688. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  182. Wang, J.B.; Erickson, J.W.; Fuji, R.; Ramachandran, S.; Gao, P.; Dinavahi, R.; Wilson, K.F.; Ambrosio, A.L.; Dias, S.M.; Dang, C.V.; et al. Targeting mitochondrial glutaminase activity inhibits oncogenic transformation. Cancer Cell 2010, 18, 207–219. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  183. Thornburg, J.M.; Nelson, K.K.; Clem, B.F.; Lane, A.N.; Arumugam, S.; Simmons, A.; Eaton, J.W.; Telang, S.; Chesney, J. Targeting aspartate aminotransferase in breast cancer. Breast Cancer Res. 2008, 10, R84. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  184. Qing, G.; Li, B.; Vu, A.; Skuli, N.; Walton, Z.E.; Liu, X.; Mayes, P.A.; Wise, D.R.; Thompson, C.B.; Maris, J.M.; et al. ATF4 regulates MYC-mediated neuroblastoma cell death upon glutamine deprivation. Cancer Cell 2012, 22, 631–644. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  185. Hensley, C.T.; Wasti, A.T.; DeBerardinis, R.J. Glutamine and cancer: Cell biology, physiology, and clinical opportunities. J. Clin. Investig. 2013, 123, 3678–3684. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  186. Yang, Y.; Karakhanova, S.; Werner, J.; Bazhin, A.V. Reactive oxygen species in cancer biology and anticancer therapy. Curr. Med. Chem. 2013, 20, 3677–3692. [Google Scholar] [CrossRef] [PubMed]
  187. Dixon, S.J.; Lemberg, K.M.; Lamprecht, M.R.; Skouta, R.; Zaitsev, E.M.; Gleason, C.E.; Patel, D.N.; Bauer, A.J.; Cantley, A.M.; Yang, W.S.; et al. Ferroptosis: An iron-dependent form of nonapoptotic cell death. Cell 2012, 149, 1060–1072. [Google Scholar] [CrossRef] [Green Version]
  188. Gaschler, M.M.; Hu, F.; Feng, H.; Linkermann, A.; Min, W.; Stockwell, B.R. Determination of the Subcellular Localization and Mechanism of Action of Ferrostatins in Suppressing Ferroptosis. ACS Chem. Biol. 2018, 13, 1013–1020. [Google Scholar] [CrossRef]
  189. Doll, S.; Proneth, B.; Tyurina, Y.Y.; Panzilius, E.; Kobayashi, S.; Ingold, I.; Irmler, M.; Beckers, J.; Aichler, M.; Walch, A.; et al. ACSL4 dictates ferroptosis sensitivity by shaping cellular lipid composition. Nat. Chem. Biol. 2017, 13, 91–98. [Google Scholar] [CrossRef]
  190. Dixon, S.J.; Stockwell, B.R. The hallmarks of ferroptosis. Annu. Rev. Cancer Biol. 2019, 3, 35–54. [Google Scholar] [CrossRef]
  191. Doll, S.; Freitas, F.P.; Shah, R.; Aldrovandi, M.; da Silva, M.C.; Ingold, I.; Grocin, A.G.; Xavier da Silva, T.N.; Panzilius, E.; Scheel, C.H.; et al. FSP1 is a glutathione-independent ferroptosis suppressor. Nature 2019, 575, 693–698. [Google Scholar] [CrossRef] [PubMed]
  192. Wang, W.; Green, M.; Choi, J.E.; Gijon, M.; Kennedy, P.D.; Johnson, J.K.; Liao, P.; Lang, X.; Kryczek, I.; Sell, A.; et al. CD8+ T cells regulate tumour ferroptosis during cancer immunotherapy. Nature 2019, 569, 270–274. [Google Scholar] [CrossRef] [PubMed]
  193. Badgley, M.A.; Kremer, D.M.; Maurer, H.C.; DelGiorno, K.E.; Lee, H.J.; Purohit, V.; Sagalovskiy, I.R.; Ma, A.; Kapilian, J.; Firl, C.E.M.; et al. Cysteine depletion induces pancreatic tumor ferroptosis in mice. Science 2020, 368, 85–89. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Note from the top—glucose to lactic acid—the three enzymatic steps that have been genetically disrupted in our studies by CRISPR-Cas9 (red horizontal triangles). Red dotted arrows represent the Hypoxia Inducible Factors (HIF)-induced genes that are upregulated during tumor hypoxia including GLUT1, HK, GPI, LDHA, MCT4 and PDK1, thereby allowing tumors to have a sustained fermentative glycolysis capacity. Glutathione peroxidase 4 (GPX4) and ferroptosis suppressor protein 1 (FSP1), which is a novel glutathione-independent ferroptosis suppressor, are also depicted in this scheme; both of them prevent the generation of membrane lipid peroxides.
Figure 1. Note from the top—glucose to lactic acid—the three enzymatic steps that have been genetically disrupted in our studies by CRISPR-Cas9 (red horizontal triangles). Red dotted arrows represent the Hypoxia Inducible Factors (HIF)-induced genes that are upregulated during tumor hypoxia including GLUT1, HK, GPI, LDHA, MCT4 and PDK1, thereby allowing tumors to have a sustained fermentative glycolysis capacity. Glutathione peroxidase 4 (GPX4) and ferroptosis suppressor protein 1 (FSP1), which is a novel glutathione-independent ferroptosis suppressor, are also depicted in this scheme; both of them prevent the generation of membrane lipid peroxides.
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Figure 2. Key conclusions issued from the analysis of fermentative glycolysis (Warburg effect) in normal tissues and cancers [51].
Figure 2. Key conclusions issued from the analysis of fermentative glycolysis (Warburg effect) in normal tissues and cancers [51].
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Cassim, S.; Vučetić, M.; Ždralević, M.; Pouyssegur, J. Warburg and Beyond: The Power of Mitochondrial Metabolism to Collaborate or Replace Fermentative Glycolysis in Cancer. Cancers 2020, 12, 1119. https://doi.org/10.3390/cancers12051119

AMA Style

Cassim S, Vučetić M, Ždralević M, Pouyssegur J. Warburg and Beyond: The Power of Mitochondrial Metabolism to Collaborate or Replace Fermentative Glycolysis in Cancer. Cancers. 2020; 12(5):1119. https://doi.org/10.3390/cancers12051119

Chicago/Turabian Style

Cassim, Shamir, Milica Vučetić, Maša Ždralević, and Jacques Pouyssegur. 2020. "Warburg and Beyond: The Power of Mitochondrial Metabolism to Collaborate or Replace Fermentative Glycolysis in Cancer" Cancers 12, no. 5: 1119. https://doi.org/10.3390/cancers12051119

APA Style

Cassim, S., Vučetić, M., Ždralević, M., & Pouyssegur, J. (2020). Warburg and Beyond: The Power of Mitochondrial Metabolism to Collaborate or Replace Fermentative Glycolysis in Cancer. Cancers, 12(5), 1119. https://doi.org/10.3390/cancers12051119

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