Metabolic reprogramming: the emerging concept and associated therapeutic strategies

Oncogene-Driven Metabolic Alterations in Cancer

Cancer metabolic reprogramming: importance, main features, and potentials for precise targeted anti-cancer therapies | Phan | Cancer Biology & Medicine
http://www.cancerbiomed.org/index.php/cocr/article/view/629/655

Abstract
Cancer is the leading cause of human deaths worldwide. Understanding the biology underlying the evolution of cancer is important for reducing the economic and social burden of cancer. In addition to genetic aberrations, recent studies demonstrate metabolic rewiring, such as aerobic glycolysis, glutamine dependency, accumulation of intermediates of glycolysis, and upregulation of lipid and amino acid synthesis, in several types of cancer to support their high demands on nutrients for building blocks and energy production. Moreover, oncogenic mutations are known to be associated with metabolic reprogramming in cancer, and these overall changes collectively influence tumor-microenvironment interactions and cancer progression. Accordingly, several agents targeting metabolic alterations in cancer have been extensively evaluated in preclinical and clinical settings. Additionally, metabolic reprogramming is considered a novel target to control cancers harboring un-targetable oncogenic alterations such as KRAS. Focusing on lung cancer, here, we highlight recent findings regarding metabolic rewiring in cancer, its association with oncogenic alterations, and therapeutic strategies to control deregulated metabolism in cancer.

Keywords: Cancer, Non-small cell lung cancer, Cancer metabolism, Metabolic reprogramming, Aerobic glycolysis, Oncogenic alteration

INTRODUCTION
Despite numerous efforts for cancer treatment, cancer is the leading cause of human deaths worldwide (Mathers and Loncar, 2006; Torre et al., 2015). Thus, understanding the biology underlying the evolution of cancer is important for reducing the economic and social burden of cancer. Recent investigations have demonstrated the impact of metabolic reprogramming on the development and progression of several types of human cancer, and deregulated metabolism is now regarded as one of the hallmarks of cancer (Hanahan and Weinberg, 2011; Pavlova and Thompson, 2016). Moreover, several findings demonstrate that mutations in oncogenes and/or tumor suppressor genes can mediate metabolic rewiring in cancer cells to support the high demands for building blocks and energy production in these cells (Iurlaro et al., 2014; Nagarajan et al., 2016; Kerr and Martins, 2017). Because cancer cells are prone to several oncogenic mutations such as RAS, EGFR, MYC, and BRAF mutations, these genes could also influence the metabolic changes in cancer. Based on several studies on the association of oncogenic alterations with the metabolic reprogramming (Kroemer and Pouyssegur, 2008; Hanahan and Weinberg, 2011; Iurlaro et al., 2014; Nagarajan et al., 2016; Kerr and Martins, 2017), here, we summarize recent findings on the association of oncogenic alterations with metabolic reprogramming in cancer, focusing on lung cancer due to its great contribution to cancer incidence and mortality rates. Further, we discuss the impact of metabolic alterations on the tumor-microenvironment interaction and possible therapeutic options targeting metabolic reprogramming.


GENERAL FEATURES OF METABOLIC REPROGRAMMING IN CANCER
Cancer cells have been known to possess markedly different metabolic features compared with those of corresponding normal tissues (Tennant et al., 2010). Unlike normal cells, cancer cells rearrange their cellular metabolic networks to fulfill their high demands for building blocks and energy production to support extensive proliferation and growth (Tennant et al., 2010; Kerr and Martins, 2017) (Fig. 1). The first defined cancer-specific metabolic alteration is the Warburg effect, an aerobic glycolytic process discovered by Otto Warburg in 1926 (Warburg, 1956). In this process, cancer cells are dependent on glycolysis for glucose metabolism even in the presence of oxygen, thereby producing high levels of lactate and reducing the use of the tricarboxylic acid (TCA) cycle (Levine and Puzio-Kuter, 2010). Because the TCA cycle and subsequent oxidative phosphorylation produce cellular energy more efficiently than glycolysis, this metabolic rewiring has been suggested as an alternative to compensate for mitochondrial dysfunction in cancer cells (Warburg, 1956; Kerr and Martins, 2017). Indeed, mutations in the TCA cycle-associated enzymes, such as succinate dehydrogenase (SDH), fumarate hydratase (FH), and isocitrate dehydrogenase (IDH), have been found in several types of cancer including paraganglioma (mutations in SDH), phaeochromocytoma (mutations in SDH), renal carcinoma (mutations in FH), leiomyomatosis (mutations in FH), acute myeloid leukemia (mutations in IDH), and glioblastoma (mutations in IDH), and these alterations have been suggested to contribute to mitochondrial dysfunction in cancer and tumorigenesis (King et al., 2006; Dang et al., 2010; Galluzzi et al., 2013; Parker and Metallo, 2015). However, several recent findings have suggested the essential role of functional mitochondria in cancer cells (Magda et al., 2008; Whitaker-Menezes et al., 2011; Wallace, 2012). The upregulation of oxidative phosphorylation has been noted in cancer cells (Whitaker-Menezes et al., 2011), and the tumorigenic potential of cancer cells has also been shown to be significantly reduced by depletion of mitochondrial DNA (Magda et al., 2008). Therefore, in addition to ATP synthesis, metabolic switching to aerobic glycolysis appears to be a means of supplying cancer cells with the precursors of proteins, lipids, amino acids, and nucleic acids for building their cellular structure and maintaining their upregulated proliferation. Thus, mitochondria still play important roles in bioenergetics and biosynthesis in cancer cells (Wallace, 2012).

Fig. 1.
Metabolic reprogramming in cancer cells compared with normal cells.

Recent findings demonstrate the additional metabolic rewiring in cancer cells and consequent alterations in cellular signaling pathways and the tumor microenvironment, including changes in the metabolism of glucose, lipids, and amino acids; regulation of the cellular redox state to tolerate reactive oxygen species (ROS)-mediated damage in cellular compartments; and remodeling of the extracellular matrix surrounding cancer cells. For instance, cancer cells display elevated expression of the alternatively spliced form of pyruvate kinase (PK), PK muscle isozyme M2 (PKM2) (Kroemer and Pouyssegur, 2008; Dong et al., 2016). PK mediates the conversion of phosphoenolpyruvate (PEP) to pyruvate, the rate-limiting step of glycolysis (Dong et al., 2016). Owing to the reduced enzymatic activity of PKM2, the phosphorylated metabolites upstream of pyruvate in the glycolytic pathway accumulate and are finally diverted into several anabolic pathways to synthesize glycogen, triglycerides, phospholipids, nucleotides, and amino acids (Gatenby and Gillies, 2004; Kroemer and Pouyssegur, 2008; Dong et al., 2016). In addition, cancer cells introduce acetyl-CoA into a truncated TCA cycle, resulting in the export of acetyl-CoA into the cytosol, where it serves as a precursor of fatty acids, cholesterol, and isoprenoids, which are utilized for cell proliferation and growth (Kroemer and Pouyssegur, 2008). Fatty acid synthase and choline kinase, which mediate biosynthesis of long-chain fatty acids and phosphatidylcholines, respectively, are also known to be upregulated and activated in many types of cancer cells (Ramirez de Molina et al., 2002; Menendez and Lupu, 2007; Kroemer and Pouyssegur, 2008). In the case of amino acid metabolism, cancer cells express sensors of amino acid deficiency, such as GATOR1, folliculin, and the Ras-like small GTPase Rag complex, to ensure a sufficient supply of amino acids to activate rapamycin complex I (mTORC1) (Bar-Peled and Sabatini, 2014; Tsun and Possemato, 2015). The upregulated uptake of glutamine, a nonessential amino acid, through elevated expression of glutamine transporters such as SLC1A5 and SLC38A2 has been thought to play important roles in the supply of nitrogen, the uptake of essential amino acids, and the maintenance of mTORC1 activation in cancer cells (Wise and Thompson, 2010). Consistent with these hypotheses, elevated expression of these glutamine transporters is correlated with poor clinical outcomes in breast and lung cancers (Hassanein et al., 2015; Jeon et al., 2015). Cancer cells also display extensive conversion of glutamine to glutamate and upregulation of several metabolic enzymes responsible for amino acid biosynthesis, including glutaminase (GLS), phosphoglycerate dehydrogenase (PHG-DH), and asparagine synthetase (ASNS) (Gao et al., 2009; Locasale et al., 2011; Possemato et al., 2011; Zhang et al., 2014a; Tsun and Possemato, 2015). Moreover, the generation of nicotinamide adenine dinucleotide phosphate (NADPH) by metabolizing glucose through the pentose phosphate pathway (PPP) supports the defense of cancer cells against oxidative or cellular stresses and the synthesis of fatty acids in cancer cells (Gatenby and Gillies, 2004; Kroemer and Pouyssegur, 2008; Levine and Puzio-Kuter, 2010). Further, the acidic tumor microenvironment is constructed through the overproduction of lactate through aerobic glycolysis, facilitating the invasion of tumor cells and blood vessels via matrix remodeling and suppressing anticancer immunity (Fischer et al., 2007; Hunt et al., 2007; Swietach et al., 2007; Kroemer and Pouyssegur, 2008; Levine and Puzio-Kuter, 2010). Collectively, these complex processes allow cancer cells to survive and proliferate, but the details are known to be context dependent and differentially regulated by various factors such as oncogenes/tumor suppressor genes, microenvironments, and tissue of origin (Levine and Puzio-Kuter, 2010; Yuneva et al., 2012; Hensley et al., 2016; Mayers et al., 2016; Kerr and Martins, 2017). Thus, understanding the influence of cellular or environmental factors, such as oncogene-induced metabolic switches, on cancer cell metabolism is important for the development of better anticancer therapeutics targeting altered metabolism in cancer cells.

METABOLIC ALTERATIONS IN NON-SMALL CELL LUNG CANCER
Lung cancer is one of the main types of cancer due to its high prevalence and poor survival rates (Mathers and Loncar, 2006; Torre et al., 2015). Approximately 85% of all cases of lung cancer are non-small cell lung cancer (NSCLC) (Molina et al., 2008). The three major types of NSCLC (adenocarcinoma (ADC), squamous cell carcinoma (SQCC), and large cell carcinoma) are classified based on histological and molecular/genetic features (Clinical Lung Cancer Genome Project (CLCGP) and Network Genomic Medicine (NGM), 2013; Pikor et al., 2013). Mutations in KRAS and EGFR as well as ALK rearrangements, among others, are mainly found in lung ADC, which accounts for 30–40% of NSCLCs (Pikor et al., 2013). Lung ADCs carrying these genetic alterations are addicted to the associated signaling pathways for cell proliferation, growth, and survival and thus can be vulnerable to the disruption of these signaling pathways (Hrustanovic et al., 2015; Lin and Shaw, 2016). Indeed, several anticancer drugs specifically targeting EGFR or ALK have been clinically used as a first-line therapy for patients with lung ADC harboring these mutations (Saintigny and Burger, 2012). However, none of these drugs have shown remarkable clinical benefits, and drug resistance is still a large obstacle for efficient anticancer treatment using these regimens (Lin and Shaw, 2016). Moreover, there is no therapeutic option to control lung ADC carrying mutant KRAS. Although several alternative approaches have been suggested, including targeting the functional outputs of mutant KRAS or cellular addiction caused by mutant KRAS (Kerr and Martins, 2017), it is important to develop novel therapeutic strategies to meet clinical needs for the treatment of lung cancer, especially lung ADC carrying mutations in oncogenes such as KRAS.

In line with the general metabolic reprogramming in cancer cells that has been described previously, recent studies have demonstrated metabolic alterations in NSCLC. Studies using NSCLC tumors surgically resected from patients after radioisotope-labeled glucose (13C-glucose) infusion, NSCLC cells displayed enhancements in glycolysis and the TCA cycle and subsequent enrichment of TCA cycle intermediates compared with adjacent normal or benign lung tissues (Fan et al., 2009; Hensley et al., 2016). In addition, the activity of pyruvate carboxylase (PC), an enzyme mediating the irreversible carboxylation of pyruvate to generate oxaloacetate (Gray et al., 2014), was elevated in NSCLC tumors (Sellers et al., 2015; Hensley et al., 2016). Because upregulated PC activity plays a role in the replenishment of TCA intermediates that have been utilized in biosynthetic reactions (Kerr and Martins, 2017), this enhancement indicates the rewiring of glucose metabolism to meet the high metabolic demands of cancer cells. Moreover, silencing PC expression significantly reduced the proliferative, colony-forming, and tumorigenic abilities of NSCLC cells, suggesting that NSCLC cells are addicted to PC-mediated anaplerosis (the reduction of TCA intermediates due to biosynthetic reactions). Thus, PC has the potential to be a novel cellular target for anticancer drug development (Sellers et al., 2015). A recent study shows that a subset of NSCLC cells utilizes glycolysis for energy production and that these high glycolytic cells possess elevated hexokinase 2 expression (Wu et al., 2015). Another recent study also demonstrates the utilization of lactate as the main carbon source for the TCA cycle in tumors from NSCLC patients and NSCLC tumor xenografts (Faubert et al., 2017).

In addition to these changes in glucose metabolism, NSCLC cells exhibit alterations in the metabolism of lipids, amino acids, and nucleic acids. For example, the expression of acetyl-CoA carboxylase 1 (ACC1), one of the key regulators of fatty acid synthesis, was elevated in NSCLC cells. Further, pharmacological inhibition of ACC1 displayed significant antitumor effects in a preclinical model of NSCLC (Svensson et al., 2016; Svensson and Shaw, 2016). The expression and activity of ATP citrate lyase (ACLY), another key fatty acid synthesis enzyme involved in the generation of cytosolic acetyl-CoA and oxaloacetate, were also upregulated in NSCLC (Migita et al., 2008) and are associated with poor clinical outcomes in NSCLC patients (Migita et al., 2008). Consistent with the results of experiments targeting ACC1, siRNA-based ablation of ACLY expression exhibited significant inhibitory effects on proliferation and lipogenesis (Migita et al., 2008). Glycine decarboxylase (GLDC), a component of a multienzyme complex responsible for glycine decarboxylation and serine biosynthesis (Go et al., 2014) and involved in pyrimidine metabolism (Newman and Maddocks, 2017), was also upregulated in lung tumor-initiating cells and promoted cell transformation and tumorigenesis (Zhang et al., 2012). Elevated GLDC expression was associated with poor survival in patients with NSCLC (Zhang et al., 2012).

However, compared to altered glucose metabolism in NSCLC, the rewiring of other metabolic pathways in NSCLC is still unclear and needs to be further elucidated. Additionally, despite commonalities in metabolic reprogramming, the metabolic alterations in individual NSCLC cells or tumors are highly heterogeneous (Brunelli et al., 2014; Chen et al., 2014; Wu et al., 2015; Hensley et al., 2016). Considering a high mutation burden in lung cancer, especially lung ADC (Cancer Genome Atlas Research Network, 2014; Swanton and Govindan, 2016; Kerr and Martins, 2017), and the association of alterations in oncogenes or tumor suppressor genes with metabolic reprogramming (Levine and Puzio-Kuter, 2010; Iurlaro et al., 2014; Nagarajan et al., 2016; Kerr and Martins, 2017), the genetic heterogeneity of NSCLC appears to influence these metabolic diversities.

ROLE OF ONCOGENIC MUTATIONS IN METABOLIC REPROGRAMMING IN LUNG CANCER
Alterations in several oncogenes, such as MYC, RAS, and BRAF, have been known to play a role in metabolic reprogramming (Iurlaro et al., 2014; Nagarajan et al., 2016; Kerr and Martins, 2017). Briefly, MYC transcriptionally regulates some metabolic enzymes involved in DNA synthesis and glycolysis, including thymidylate kinase and lactate dehydrogenase A, respectively (Pusch et al., 1997; Shim et al., 1997). MYC is also involved in the metabolic reprogramming of fatty acids, glutamine, proline, and nucleic acids by direct transcriptional regulation or indirect regulation utilizing microRNAs (Mannava et al., 2008; Gao et al., 2009; Liu et al., 2012; Edmunds et al., 2014). In addition, increases in the uptake and interconversion of a polyamine spermine, the metabolism of inositol phospholipids, and aerobic glycolysis were observed in RAS-transformed cells (Huang et al., 1988; Pakala et al., 1988; Chiaradonna et al., 2006). Further, mutated RAS was found to mediate metabolic reprogramming in pancreatic cancer by stimulating glucose uptake, channeling glycolytic intermediates into the hexosamine biosynthesis pathway or pentose phosphate pathway, and directly regulating aspartate transaminases (Ying et al., 2012; Son et al., 2013; Nagarajan et al., 2016). BRAF is also known to regulate glucose and glutamine metabolism in melanoma (Scott et al., 2011; Haq et al., 2013).

In the case of lung cancer, previous reports have suggested a link between genetic mutations and metabolic rewiring in NSCLC, especially lung ADC. The association of alterations in KRAS, EGFR, ALK, and STK11 genetic abnormalities in lung ADC (Ji et al., 2007; Pikor et al., 2013) with metabolic changes is described as follows (Fig. 2).


Fig. 2.
Contribution of genetic alterations to metabolic reprogramming in cancer.

Role of KRAS mutation in metabolic reprogramming in NSCLC
Mutations in the RAS oncogene are known to be a major driver of tumorigenesis (Cox and Der, 2010; Pylayeva-Gupta et al., 2011; Hobbs et al., 2016). Three isoforms of the RAS gene [Kirsten rat sarcoma viral oncogene homolog (KRAS), neuroblastoma RAS viral (v-ras) oncogene homolog (NRAS) and Harvey rat sarcoma viral oncogene homolog (HRAS)] encode four RAS proteins (KRAS4A, KRAS4B, NRAS, and HRAS) (Pylayeva-Gupta et al., 2011; Hobbs et al., 2016). The two KRAS isoforms arise from alternative RNA splicing of the KRAS gene (Pylayeva-Gupta et al., 2011; Hobbs et al., 2016). Activating mutations have been identified at three hotspots within the RAS protein (G12, G13, and Q61), but the mutation frequency at each of the hotspots in the RAS isoform is known to be quite different in each isoform (Pylayeva-Gupta et al., 2011; Hobbs et al., 2016). The RAS protein is a small G protein whose activity is regulated by the GDP/GTP cycle (Cox and Der, 2010; Pylayeva-Gupta et al., 2011; Hobbs et al., 2016). The GTP-bound RAS, an activated form of the RAS protein, binds to downstream effectors and triggers activation of signal transduction pathways, such as the Raf-MEK-ERK pathway and the PI3K/Akt pathway, responsible for cell proliferation, survival, and growth (Cox and Der, 2010; Pylayeva-Gupta et al., 2011).

Mutations in the KRAS gene, including G12C, G12V, G12D, and G12A, are found in approximately 30% of NSCLC patients with ADC histology (Kempf et al., 2016). These mutations are found more frequently in smokers than in nonsmokers (25–35% in smokers and 5% in nonsmokers) (Mao et al., 2010; Dearden et al., 2013; Kempf et al., 2016). The KRAS mutation (G12D) is common in never-smokers, whereas the KRAS mutation (G12C) is the most common mutation in NSCLC patients with a history of smoking (Kempf et al., 2016). Mutations in KRAS and EGFR are mutually exclusive (Kempf et al., 2016), but mutations in STK11 or TP53 are positively correlated with KRAS mutations (Kempf et al., 2016). Although a recent report describes the weak prognostic impact of the KRAS mutations in NSCLC (Roberts and Stinchcombe, 2013), recent findings suggest a close association of the KRAS mutations with poor prognosis of patients with NSCLC (Meng et al., 2013; Renaud et al., 2015; Kempf et al., 2016). Accordingly, several anticancer approaches targeting the RAS protein, including farnesyltransferase inhibitors, competitors disrupting the RAS-chaperone interaction, and inhibitors of the RAS effector or downstream signaling such as the MAPK pathway, mTOR, and Hsp90, have been evaluated in preclinical and clinical settings. None, however, has shown clinical benefits for anticancer treatment (Cox and Der, 2010; Kempf et al., 2016), emphasizing the necessity of procuring alternative approaches to treat cancer carrying RAS mutations.

Numerous findings demonstrate the involvement of mutant KRAS in the metabolic rewiring of several types of human cancer (Pylayeva-Gupta et al., 2011; Kimmelman, 2015; Lv et al., 2016; Kawada et al., 2017; Kerr and Martins, 2017), including upregulation of glucose uptake, glutamine utilization, and aerobic glycolysis (Onetti et al., 1997; Ying et al., 2012; Son et al., 2013). Using patient-derived NSCLC tumors, cell lines, and animal models, several studies have consistently identified the influence of mutant KRAS on metabolic reprogramming in NSCLC. A recent study demonstrated the metabolism-related proteomic profiles of NSCLC cell lines carrying intrinsic mutant KRAS (A549 and H460) in comparison with those of normal bronchial epithelial cells (Martin-Bernabe et al., 2014). These NSCLC cells expressed elevated levels of enzymes involved in glycolysis (GAPDH, PKM2, LDHA, and LDHB) and PPP (G6PD, TKT, and 6PGD) compared with normal cells, suggesting alterations in glucose metabolism in NSCLC cells carrying mutant KRAS. It is known that these two cell lines carry different KRAS mutations (G12S for A549; Q61H for H460) (Mahoney et al., 2009; Acquaviva et al., 2012) and that the different amino acid substitutions display distinct biological properties in terms of signaling activation and sensitivity to anticancer agents (Garassino et al., 2011; Stolze et al., 2015). Thus, cellular metabolism could be influenced by different KRAS mutations. In line with this notion, a recent study demonstrated the impact of different KRAS mutations on changes in metabolomic profiles (Brunelli et al., 2014). In this study, different KRAS mutations at codon 12 (G12C, G12D, and G12V) were evaluated. NSCLC cells carrying each of these mutations displayed differential metabolic remodeling, including differences in redox buffering systems and glutamine dependency (Brunelli et al., 2014). Among these mutations, mutant KRAS (G12C) showed the most prominent metabolic changes in vitro. Of note, these metabolic changes were maintained in a tumor xenograft model bearing the same NSCLC cell line (Brunelli et al., 2014, 2016), suggesting that the in vitro cell line model can be utilized to investigate metabolic alterations in NSCLC patients. However, another independent study demonstrated discrepancies in glucose metabolism using in vitro versus in vivo models (Davidson et al., 2016). In this study, several mouse models, including two autochthonous mouse models that develop spontaneous lung tumors (the KrasLA2/+ mouse model and the KrasLSL-G12D/+;Trp53fl/fl (KP) mouse model with intratracheal delivery of adenoviral Cre), a syngeneic xenograft model involving intratracheal inoculation with lung tumor cells derived from the KP mouse model, and a tumor xenograft model involving subcutaneous inoculation with human lung cancer cell lines, were used for determining metabolic changes in vivo. Tumor cells arising in the KP mouse model were used for in vitro determination of metabolic alterations (Davidson et al., 2016). Both in vitro and in vivo models exhibited upregulated lactate production. However, in contrast to a dependence on glutamine for TCA cycle entry in vitro, lung tumors from these in vivo mouse models minimally utilized glutamine as a carbon source for TCA cycle entry. Additionally, some oxidative glucose metabolic enzymes, including pyruvate carboxylase and pyruvate dehydrogenase (which generate oxaloacetate and acetyl-CoA, respectively), were necessary for tumor formation and growth in these mouse models (Davidson et al., 2016). Therefore, the environmental context needs to be taken into consideration in the investigation of physiologically relevant metabolic alterations, especially in the case of glucose metabolism.

Additional studies also suggest that mutant KRAS mediates the changes in the metabolism of amino acids, lipids, and folates. In a recent study using a mutant Kras-driven model of spontaneous lung tumorigenesis (the KP mouse model), the uptake and utilization of branched-chain amino acids (BCAAs), such as leucine and valine, were elevated in KP mice possessing lung tumors (Mayers et al., 2016). The expression of enzymes responsible for the catabolism of BCAAs, including SLC7A5, BCAT, and BCKDH, was also upregulated in human NSCLC tumors, and ablation of Bcat expression resulted in decreases in in vitro NSCLC cell proliferation and in vivo NSCLC tumor growth (Mayers et al., 2016), indicating the requirement of BCAA metabolism in NSCLC. In the same study, pancreatic ductal adenocarcinoma (PDAC) carrying the same genetic alterations did not utilize BCAA as a nitrogen source (Mayers et al., 2016), suggesting the influence of tissue microenvironment-specific differences on metabolic reprogramming over genetic mutations. In addition to amino acid metabolism, mutant KRAS activated lipogenesis in lung ADC via induction of fatty acid synthase through the ERK2-mediated pathway (Gouw et al., 2017). NSCLC cells carrying mutant KRAS also showed a tendency to be dependent on the folate metabolism pathway compared with those carrying wild-type KRAS (Moran et al., 2014). Consistent with these findings, KRAS mutant NSCLC cells were sensitive to antifolates such as methotrexate and pemetrexed, and the expression level of enzymes related to folate metabolism, such as methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) was positively (Moran et al., 2014).

Moreover, despite the metabolic switch to aerobic glycolysis in cancer cells, mitochondria are known to have a functional role in cell proliferation and tumorigenesis (Magda et al., 2008; Whitaker-Menezes et al., 2011; Wallace, 2012). Likewise, deregulation of mitochondrial function through the ablation of the expression of mitochondrial transcription factor A (TFAM) significantly suppressed mutant Kras-driven lung tumor formation (Weinberg et al., 2010). In this study, mitochondrial ROS generated through Complex III was essential for mutant KRAS-induced anchorage-independent growth of cancer cells (Weinberg et al., 2010). A previous report demonstrated the reduced expression of components of Complex I in KRAS-transformed cells (Baracca et al., 2010). Considering that both Complex I and Complex II mediate electron transfer to Complex III (Mailloux, 2015), presumably, NSCLC cells expressing mutant KRAS might acquire an alternative method (e.g., upregulation of Complex II) of compensating for the KRAS-induced decrease in Complex I activity in order to maintain mitochondrial function.

Role of EGFR mutations in metabolic reprogramming in NSCLC
Approximately 15–30% of NSCLC patients carry abnormalities in EGFR (Gridelli et al., 2015). EGFR mutations are frequently observed in lung ADCs derived from Asian patients with no smoking history (Gridelli et al., 2015). The most common mutations in EGFR are a deletion at exon 19 (E746–A750) and substitutions at exon 18 (G719C, G719S, G719A) and exon 21 (L858R), all of which are sensitive to EGFR-targeted therapy (Pao and Miller, 2005; Gridelli et al., 2015). Aberrantly activated EGFR activates signaling pathways driving the mitogenic, prosurvival, and proinvasive phenotypes of the cancer cells (Zhang et al., 2010). In addition to the direct modulation of signal transduction, aberrant EGFR mediates metabolic reprogramming in NSCLC. For instance, global metabolic reprogramming, such as enhanced aerobic glycolysis and upregulation of PPP, alters pyrimidine biosynthesis and redox metabolism in EGFR mutant lung ADC cell lines (Makinoshima et al., 2014). Combination treatment with erlotinib and a glutaminase inhibitor (CB-839) drives EGFR mutant NSCLC cells to undergo metabolic crisis, thereby leading to enhanced cell death, decreased cell viability in vitro, and a rapid tumor regression in vivo (Momcilovic et al., 2017), indicating the necessity of glutamine as a source for bioenergetics and biosynthesis in NSCLCs carrying mutant EGFR. Moreover, EGFR increases monounsaturated fatty acid (MUFA) synthesis by phosphorylating stearoyl-CoA desaturase-1 (SCD1) via direct interaction and via maintaining the stability of the SCD1 protein (Zhang et al., 2017). The level of phosphorylated SCD1 expression was found to be an independent prognostic factor for poor survival in patients with NSCLC (Zhang et al., 2017). These results collectively indicate that targeting alterations in glucose or lipid metabolism would be an alternative combinatorial therapeutic approach for treatment of lung ADCs harboring mutant EGFR.

Role of ALK rearrangement in metabolic reprogramming in NSCLC
ALK rearrangement accounts for approximately 3–7% of NSCLC cases (Katayama et al., 2015). The most frequently observed ALK rearrangement is the EML4-ALK fusion (Katayama et al., 2015). Several ALK inhibitors, including crizotinib and ceritinib, have been clinically used for the treatment of patients with lung ADC harboring alterations in ALK (Katayama et al., 2015). The impact of ALK aberrations on metabolism in lung ADC has not been well characterized, but a recent report indicates presence of upregulated glucose metabolism and highly metastatic phenotypes in lung ADCs carrying ALK rearrangements (Choi et al., 2013).

Role of LKB1 loss in metabolic reprogramming in NSCLC
LKB1, encoded by the STK11 gene, is a tumor suppressor gene which plays an important role in the regulation of cellular growth and metabolism by phosphorylation and activation of AMP-activated kinase (AMPK), an upstream kinase controlling the mammalian target of rapamycin (mTOR) pathway, MARK/par-1, and other AMPK-related kinases (Shackelford and Shaw, 2009). Approximately 15–35% of NSCLC patients harbor mutations in STK11 (Ji et al., 2007; Shackelford and Shaw, 2009), which is more frequently observed in lung ADC than in lung SQCC (Sanchez-Cespedes et al., 2002; Ji et al., 2007). According to its primary role in the regulation of cellular metabolism, loss of LKB1 leads to deregulation of cellular metabolism under conditions of energy stress (Carretero et al., 2007), causing enhanced sensitivity to therapies targeting metabolism such as phenformin (Shackelford et al., 2013) or therapies that induce energetic stress such as erlotinib (Whang et al., 2016). In addition, metabolic reprogramming in NSCLC harboring altered LKB1 has been demonstrated in a recently published study. Using NSCLC cell lines carrying either KRAS mutations alone or both KRAS mutations and loss of LKB1, this study identified that the additional loss of LKB1 resulted in the accumulation of metabolites associated with the urea cycle through upregulation of carbamoyl phosphate synthetase-1 (CPS1) (Kim et al., 2017). Silencing of CPS1 expression suppressed the growth of tumor xenografts derived from KRAS/STK11-mutant NSCLC cells through reduction of the pyrimidine to purine ratio, thereby disrupting DNA replication (Kim et al., 2017). These results indicate the existence of alterations in pyrimidine metabolism in LKB1-deficient NSCLC cells and provides a novel therapeutic target for the treatment of NSCLCs harboring loss of LKB1 expression.


TUMOR MICROENVIRONMENT-MEDIATED METABOLIC REPROGRAMMING IN CANCER
The interaction between tumors and the surrounding stromal cells that make up the tumor microenvironment has been known to be implicated in cancer development and progression (Quail and Joyce, 2013). Given the role of metabolic alterations in cancer, the tumor-microenvironment interaction could be affected by metabolic alterations in cancer cells and vice versa. For example, the differences in BCAA metabolism between lung cancer and PDAC (Mayers et al., 2016) and in glutamine dependent metabolism between in vitro and in vivo models (Davidson et al., 2016) appear to be influenced by the environmental context. Nutrient sharing, nutrient competition, and metabolite exchange between tumor and stromal cells are known to influence and shape the tumor-microenvironment interaction (Lyssiotis and Kimmelman, 2017). Indeed, lactate, amino acids, and fatty acids act as signaling molecules that can be exchanged between tumor and stromal cells, resulting in the regulation of signal transduction, gene expression, and characteristics of neighboring cells (Lyssiotis and Kimmelman, 2017). Macromolecules or organelles released from stromal cells can also support the biosynthetic and bioenergetic needs of cancer cells (Spees et al., 2006; Chaudhri et al., 2013; Lyssiotis and Kimmelman, 2017). Specifically, compared with normal fibroblasts, basal autophagy was elevated in lung cancer-associated fibroblasts (CAFs) through the influence of high glycolytic lung cancer cells, leading to the release of dipeptides that could support surrounding cancer cells (Chaudhri et al., 2013). Additionally, interactions with bone marrow-derived nonhematopoietic stem/progenitor cells or skin fibroblasts rescued lung cancer cells with mitochondrial defects and led to reactivation of their mitochondrial function including electron transport chain activity (Spees et al., 2006). These phenomena occurred through the transfer of mitochondria or mitochondrial DNA from stem/progenitor cells or fibroblasts to lung cancer cells (Spees et al., 2006). Collectively, these findings suggest a crucial association between metabolic reprogramming and the tumor-microenvironment interaction. However, details regarding mechanisms of action, the lung microenvironment-specific consequences of these interactions, and their clinical impacts need to be explored in further studies.


TARGETING METABOLIC REPROGRAMMING FOR THE TREATMENT OF CANCER
According to the importance of metabolic alterations in the development and progression of cancer, several agents targeting cancer metabolism have been developed and evaluated under preclinical and clinical studies (Kroemer and Pouyssegur, 2008; Tennant et al., 2010; Nagarajan et al., 2016). Some metabolism-targeting agents, such as mTOR inhibitors [rapamycin (sirolimus), everolimus, and temsirolius] and metformin (AMPK activator and mitochondrial Complex I inhibitor) are now approved for clinical use (Carracedo et al., 2013; Nagarajan et al., 2016) (Table 1). Strategies targeting metabolic alterations for anticancer therapy are detailed in the following sections (Nagarajan et al., 2016).

Table 1.
Compounds targeting cancer metabolism in clinical studies

Name Target Clinical development stage Cancer types targeted
Agents targeting deregulated signaling pathways
  Rapamycin (Sirolimus) mTOR Phase I/II Glioblastoma, Advanced cancer
  Everolimus (RAD001) mTOR FDA approved Advanced renal cell carcinoma, Pancreatic neuroendocrine tumors, Subependymal giant cell astrocytoma
  Temsirolimus (CCI-779) mTOR FDA approved Advanced renal cell carcinoma
  Ridaforolimus mTOR Phase I/II/III Advanced solid tumors
  AZD8055 (MK-8669) mTOR Phase I Advanced solid tumors
  Metformin AMPK Phase I/II/III Various advanced solid tumors
Agents targeting metabolic enzymes
  2-Deoxygluose (2-DG) HK Phase I/II Various advanced solid tumors
  TCD-717 CK Phase I Advanced solid tumors
  Dichloroacetate PDK1 Phase I/II Advanced solid tumors, Head and neck carcinoma, Brain tumor
  Indoximod IDO Phase I/II Adult solid tumors, Advanced solid tumors, Acute myeloid leukemia
  Ivosidenib (AG-120) IDH1 Phase I/II Acute myeloid leukemia, Glioma, Advanced cholangiocarcinoma, Advanced solid tumors
  Enasidenib mesylate (AG-221) IDH2 Phase I/II Acute myeloid leukemia, Glioma, Advanced solid tumors
  AG-881 IDH1 or IDH2 Phase I Acute myeloid leukemia, Glioma
  IDH1 peptide vaccine IDH1 Phase I Glioma
  PEPIDH1M IDH1 Phase I Glioma
Agents depleting metabolites using recombinant enzymes (PEG-conjugated)
  Arginase 1 Arginine Phase I/II Acute myeloid leukemia, Hepatocellular carcinoma, Other solid tumors
  Arginine deiminase Arginine Phase I/II/III Advanced solid tumors, mesothelioma, small cell lung cancer, skin cancer
  Asparaginase Asparagine Phase I/II/III Various types of leukemia and lymphoma

mTOR: mammalian target of rapamycin, AMPK: AMP activated protein kinase, HK: hexokinase, CK: choline kinase, PDK1: pyruvate dehydrogenase kinase 1, IDO: indoleamine 2,3-dioxygenase.

Targeting deregulated signaling pathways
Recent studies demonstrate the effectiveness of targeting the signaling pathways downstream of oncogenes such as AMPK and mTOR, alone or in combination, in several types of cancer. For example, metformin, an AMPK activator, inhibited the biosynthesis of fatty acids and nucleic acids (Li et al., 2015), suppressed the proliferation of lung cancer and the self-renewal capacity of hepatocellular carcinoma stem cells by inducing apoptosis (Saito et al., 2013; Storozhuk et al., 2013), and increased the radiosensitivity of lung and breast cancer cells (Storozhuk et al., 2013; Zhang et al., 2014b). The mTOR inhibitor rapamycin also inhibited the cell proliferation in several types of cancer including colorectal cancer, glioma, pancreatic cancer, and recurrent glioblastoma (Houchens et al., 1983; Eng et al., 1984; Grewe et al., 1999; Cloughesy et al., 2008). In a phase I clinical trial, rapamycin showed anticancer activity in PTEN-deficient glioblastoma (Cloughesy et al., 2008). Rapamycin analogs with improved water solubility, such as everolimus and temsirolimus, also exhibited potent anticancer effects on several types of cancer alone or in combination with other anticancer agents (Vignot et al., 2005) and have been clinically used for the treatment of advanced renal cell carcinoma, pancreatic neuroendocrine tumors, and subependymal giant cell astrocytoma (Benjamin et al., 2011).

Targeting metabolic enzymes
2-Deoxyglucose (2-DG) has a similar structure to glucose and is unable to be metabolized in mammals (Nagarajan et al., 2016). Thus, 2-DG can inhibit multiple glycolytic steps by competitively acting with glucose (Nagarajan et al., 2016). 2-DG is phosphorylated by HK2 and phosphorylated 2-DG acts an inhibitor of HK2 (Wick et al., 1957). In addition, various inhibitors targeting metabolic enzymes, including lonidamine and 3-bromopyruvate (hexokinase inhibitors), TLN-232 (a pyruvate kinase inhibitor), orlistat and cerulenin (fatty acid synthase inhibitors), dichloroacetate (a PDK1 inhibitor), MN58b and TCD-717 (choline kinase inhibitors), soraphen A (an acetyl-CoA carboxylase inhibitor), indoximod [an indoleamine 2,3-dioxygenase (IDO) inhibitor], ivosidenib (AG-120), enasidenib mesylate (AG-221 mesylate), AG-881, IDH305, PEPIDH1M (IDH1R132H-specific peptide vaccine) (inhibitors targeting mutated IDH1 or IDH2), and SB-2049990 (an ATP citrate lyase inhibitor), have been evaluated in preclinical and clinical studies (Table 1) (Hatzivassiliou et al., 2005; Wang et al., 2005; Al-Saffar et al., 2006; Beckers et al., 2007; Kroemer and Pouyssegur, 2008; Tennant et al., 2010; Mondesir et al., 2016; Nagarajan et al., 2016).

Depleting metabolites using recombinant enzymes
Strategies to inhibit a specific metabolic pathway using recombinant enzymes to reduce a specific oncogenic metabolite have been developed recently (Nagarajan et al., 2016). For instance, recombinant arginine deiminase and arginase I (which degrade and deplete arginine) conjugated with polyethylene glycol (PEG) (pegylated arginine deiminase and pegylated arginase 1, respectively) have been evaluated in phase I/II clinical trials for the treatment of advanced melanoma and advanced hepatocellular carcinoma (Izzo et al., 2004; Glazer et al., 2010; Yang et al., 2010; Ott et al., 2013; Yau et al., 2013; Nagarajan et al., 2016). Recombinant l-asparaginase (which degrades and depletes asparagine) conjugated with PEG (PEG-asparaginase) is also in clinical trials for the treatment of pediatric and adult acute lymphoblastic leukemia, multiple myeloma, and advanced solid tumors (Taylor et al., 2001; Agrawal et al., 2003; Fu and Sakamoto, 2007; Kurtzberg et al., 2011).

Specifically, in lung cancer, despite the various anticancer approaches targeting cancer metabolism described above, no metabolism-targeted drugs have been approved for lung cancer treatment. Currently, most metabolism-targeting agents for lung cancer are still under preclinical evaluation (Nagarajan et al., 2016). Of note, agents targeting unique oncogene-driven metabolic rewiring have been relatively poorly developed and should be investigated in further studies. For lung cancer treatment, cellular markers specifically elevated in NSCLC cells harboring oncogenic alterations, including BCAT (Mayers et al., 2016), SCD1 (Zhang et al., 2017), and CPS1 (Kim et al., 2017), could be potential candidates for developing novel anticancer agents specifically disrupting oncogene-driven metabolic reprogramming in NSCLC. In addition, metabolic synthetic lethality can be a valuable therapeutic approach considering the metabolic vulnerabilities of NSCLC carrying oncogenic mutations (Bensaad and Harris, 2013; Megchelenbrink et al., 2015; Kerr and Martins, 2017).


CONCLUSION
Cancer cells demand large nutrient supplies and thus reprogram their metabolic pathways to ensure metabolic flexibility, cellular homeostasis, energy production, cell proliferation, and survival. In addition to direct modulation of signal transduction pathways causing oncogenic addiction, alterations in oncogenes also contribute to metabolic rewiring in cancer cells, resulting in the promotion of cancer cell proliferation, survival, and metastatic dissemination. Accordingly, metabolic reprogramming is now considered an important characteristic of several types of cancer, including NSCLC. Despite several ongoing approaches to target cancer metabolism, metabolic reprogramming should be therapeutically explored in additional studies. In addition, the influence of metabolic rewiring on the interaction between cancer cells and the tumor microenvironment needs to be extensively investigated to comprehensively understand the course of cancer development and progression, providing mechanistic insights on several anticancer therapies targeting metabolism, microenvironmental interactions, and evasion of anticancer immunity. However, metabolic heterogeneity may reduce the responsiveness of metabolism-targeting anticancer drugs; thus, an in-depth exploration of metabolic status in cancer cells will be necessary to determine detailed metabolic changes at the cellular and molecular levels. Further, the clinical impact of metabolic alterations on cancer and the relevant biomarkers to predict or diagnose metabolic reprogramming should also be identified to develop tailored precision medicine targeting metabolic rewiring for the treatment of cancer.

Oncogene-Driven Metabolic Alterations in Cancer
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5746037/

Cancer metabolic reprogramming: importance, main features, and potentials for precise targeted anti-cancer therapies

1Department of Molecular and Cellular Oncology, 2Department of General Internal Medicine, Ambulatory Treatment and Emergency Care, 3Department of Endocrine Neoplasia and Hormonal Disorders, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, Texas, TX77030, USA

Abstract

Cancer cells are well documented to rewire their metabolism and energy production networks to support and enable rapid proliferation, continuous growth, survival in harsh conditions, invasion, metastasis, and resistance to cancer treatments. Since Dr. Otto Warburg’s discovery about altered cancer cell metabolism in 1930, thousands of studies have shed light on various aspects of cancer metabolism with a common goal to find new ways for effectively eliminating tumor cells by targeting their energy metabolism. This review highlights the importance of the main features of cancer metabolism, summarizes recent remarkable advances in this field, and points out the potentials to translate these scientific findings into life-saving diagnosis and therapies to help cancer patients.

Keywords: Cell cycle; energy metabolism; glycolysis; glutaminolysis; mitochondria biogenesis

Cancer metabolism: major remodeling of cellular energy production and metabolic pathways in tumors

Cancer metabolic reprogramming has been recognized as one of the ten cancer hallmarks by Drs. Hanahan and Weinberg in their seminal review paper published in 20111. Some of the most striking changes of tumor cellular bioenergetics include elevation of glycolysis, increase in glutaminolytic flux, upregulation of amino acid and lipid metabolism, enhancement of mitochondrial biogenesis, induction of pentose phosphate pathway and macromolecule biosynthesis1-17.

Glycolysis
Compared to normal cells, cancer cells prefer using glycolysis even in normoxic condition18-20. This phenomenon is often referred as the Warburg effect because Dr. Otto Warburg discovered and reported these metabolic alterations in tumors in 1930 and 195618-20. Many decades later, numerous studies have provided additional insights into the abnormality of cancer metabolism.

In normal cells, glucose is catabolized to pyruvate, which can be later converted to acetyl-CoA to fuel the tricarboxylic acid cycle (TCA cycle, or Krebs cycle). TCA cycle generates NADH and FADH2 to provide mitochondrial respiratory chain with electrons for energy production. This is an effective energy production mode since each glucose molecule can produce up to 36 ATP, largely thanks to mitochondrial respiration. In normal cells, glycolysis is prioritized only when oxygen supply is limited. In contrast, cancer cells preferentially use glycolysis even in the abundance of oxygen2,3,5,7,18-21. This is why tumor glycolysis is often called “aerobic glycolysis”, or the Warburg effect, to distinguish from the normal anaerobic glycolysis of healthy cells.

However, cancer cells have to compensate for the 18-fold lower efficacy of energy generation (glycolysis only makes 2 ATP per glucose molecule consumed while mitochondrial respiration can produce up to 36 ATP for each glucose molecule catabolized). Part of the solution is to upregulate glucose transporters, especially Glut1, Glut2, Glut3, and Glut4, to uptake more glucose5,22-24. In fact, the increase in glucose uptake is a major feature distinguishing tumor cells from normal cells. This difference has been widely exploited in Positron Emission Tomography (PET) imaging modality using radiolabeled analogs of glucose such as 18F-fluorodeoxyglucose as a tracer to visualize tumors.

In addition, tumors remarkably elevate the expression of the majority of glycolytic enzymes. Major oncogenes such as Ras, Myc, and HIF-1α are reported to be master inducers of cancer glycolysis3,5,24. Many glycolytic enzymes are also upregulated in tumors because of elevated c-Myc and HIF-1α transcriptional activity and insufficient p53-mediated control. Indeed, c-Myc and HIF-1α are well recognized as two master inducers of glycolysis through direct or indirect transactivation of cancer glycolytic genes. These two transcription factors coordinate to promote the expression of key glycolytic enzymes such as HK2, PFK1, TPI1, LDHA, among others, in tumors2,3,5,7,21,25,26. In fact, most of glycolytic gene promoter areas contain consensus Myc and HIF-1α binding motifs. While HIF-1α is mainly functional in hypoxia, c-Myc is well known to promote its glycolytic target genes’ expression in normoxia. This coordination allows tumors to continuously drive glycolysis for supporting their rapid proliferation and accelerated biosynthesis2,3,7,11,15,16,21.

In contrast, p53 is known to suppress glucose uptake by directly inhibiting the transcription of glucose transporter Glut1 and Glut427,28 and suppressing the expression of Glut328. Glut3 is an NF-κB target gene and p53 is found to block NF-κB activation, thereby considerably reducing Glut3 transcription and expression28. p53 also induces the expression of TIGAR to slow down cancer glycolytic flux29,30. Fructose 2,6-bisphosphate is an important allosteric activator of PFK1, a major glycolytic enzyme. Fructose 2,6-bisphosphate is produced by PFK2 from fructose 1-phosphate. By converting fructose 2,6-bisphosphate back to fructose 1-phosphate, TIGAR significantly slows down tumor glycolysis29,30.

The interaction among p53, c-Myc and HIF-1α has a decisive impact on the status of cancer glycolysis2,5,7,16,21,30. Many studies have characterized the communication between these three master regulators of cancer glycolysis and how the balance among these factors control the status of cancer metabolism.

On the other hand, the way tumor cells process pyruvate, the end product of glycolysis, is also different from normal cells. In normal cells, most of pyruvate is converted to acetyl-CoA to fuel the TCA cycle. Some pyruvate is used to produce alanine or lactate. In contrast, pyruvate-to-lactate is a preferred reaction in tumor cells due to the upregulation of lactate dehydrogenase A (LDHA). This reaction is beneficial for cancer cells as it helps regenerate NADH to accelerate glycolysis2,3,5,11,25. Furthermore, lactate is secreted into tumor microenvironment via MCT4 transporter to fuel other cancer cells that do not have frequent access to nutrient supplies from blood stream. Lactate could be uptaken by MCT1 transporter and used by the TCA cycle for metabolism. The symbiosis of lactate-producing cancer cells and lactate-consuming tumor cells is an effective way for tumors’ adaptation to the diverse and constantly changing conditions in tumors, which is caused by the leaky and poorly formed tumor blood vessel network7,31-33. Furthermore, converting pyruvate to lactate also reduces reactive oxygen species’ levels, thereby diminishing the intracellular oxidative stress in cancer cells and promoting tumors’ survival2,7. Moreover, lactate also lowers the pH of extracellular microenvironment and facilitates the activity of metalloproteases for breaking down extracellular matrix. Thus, lactate is an inducer of cancer invasion and metastasis34,35.

Importantly, glycolysis provides cancer cells with not only energy but also necessary precursors for biosynthesis, which is similar to stem cells’ metabolic profiles. Several glycolytic metabolites such as glucose-6-phosphate, dihydroxyacetone phosphate, among others, could be diverted into other metabolic pathways. For instance, glucose-6-phosphate is often consumed by pentose phosphate pathway to synthesize nucleotides and NADPH (a major reducing agent important for redox homeostasis and drug detoxifying reactions). Dihydroxyacetone phosphate could be used for lipid synthesis, which is important for assembling new organelles and cells to promote tumor growth and proliferation. Metabolites from glycolysis are also important materials for amino acid production and macromolecules synthesis, which is required for active cell division and large-scale biosynthetic programs2,3,5,7,16,36,37. In addition to their metabolic function, glycolytic enzymes play active roles in promoting cancer survival, metastasis, invasion, chromatin remodeling, gene expression regulation, and other essential cellular processes2,38. Thus targeting glycolytic enzymes’ activities could be useful strategies for cancer therapy.

Glutaminolysis
In addition to glycolysis, many tumors also rely on glutaminolysis to fuel their cellular bioenergetics and metabolism. Glutaminolysis is a series of biochemical reactions catabolizing glutamine into downstream metabolites such as glutamate, α-ketoglutarate. The products of glutaminolysis are very important to fuel the TCA cycle of tumors. The intermediates of TCA cycles could be used for the synthesis of lipid, cholesterol, amino acids and other essential metabolites. Moreover, NADH and FADH2 from the TCA cycle provide electrons for the electron transport chain of mitochondria to generate ATP. Thus, similar to glycolysis, glutaminolysis supplies cancer cells with not only ATP but also crucial precursors for continuous biosynthesis and accelerated proliferation3,5,13,15,16,22,25.

Glutaminolysis upregulation in tumors is mediated by c-Myc4,9,13,39. Multiple studies demonstrate that c-Myc promotes both glutamine uptake and the catabolic process of glutamine. In fact, c-Myc transactivates ASCT2 and SN2, two important glutamine transporters on cellular membrane9,40. c-Myc also suppresses miR-23a/b to upregulate GLS1 expression41,42. GLS1 is a major enzyme for glutaminolysis. Therefore, c-Myc is an important inducer of glutaminolysis in tumors. Interestingly, while promoting cancer metabolic reprogramming, c-Myc also renders cancer cells addicted to glutaminolysis, which opens a new therapeutic window to selectively suppress and eliminate cancer cells9,13-15,39,43. Therefore, targeting tumor glutaminolysis and c-Myc-induced-glutamine addiction is a promising anti-cancer metabolism therapy.

Pentose phosphate pathway
Pentose phosphate pathway (PPP) is a classical metabolic pathway consisting of two branches. In the oxidative arm, PPP converts glucose-6-phosphate, a glycolytic intermediate, into ribulose-5-phosphate and generates NADPH. NADPH is then used for glutathione production, detoxification reactions, and biosynthesis of lipids as well as other macromolecules. The non-oxidative PPP branch involves reversible carbon-exchanging reactions with the final products as fructose-6-phosphate and glyceraldehyde-3-phosphate. These metabolites can participate in glycolysis and downstream metabolic pathways44. PPP is commonly viewed as a line of defense counteracting reactive oxidative stress and producing ribose-5-phosphate for nucleotide synthesis. However, new studies suggest that PPP has important impacts on various aspects of cancer, including proliferation, apoptosis, invasion, drug resistance, and metastasis44. These exciting findings unveil PPP as a potential target for anti-cancer metabolism therapies.

Rapidlyproliferating cancer cells constantly demand nucleotides and other materials for biosynthesis. Therefore, by providing NAPDH and pentose phosphate for nucleotide synthesis, PPP is important and frequently upregulated in many types of tumors5,44. In fact, the activity of glucose-6-phosphate dehydrogenase (G6PD), a major PPP enzyme, increases in proliferating cancer cells45. G6PD, transketolase (TK) and other PPP enzymes are elevated in multiple types of cancer and facilitated tumors’ accelerated proliferation44,46,47. In addition, G6PD also promotes cancer survival by producing NADPH, a key tool for tumor cells to defend against oxidative stress, chemotherapy-induced cytotoxic damage, as well as for promoting biosynthesis44. Hence, G6PD function is tightly controlled by the tumor suppressor p53. Indeed, p53 associates with G6PD and prevents this enzyme from forming active dimer complexes48. It is noteworthy that G6PD is directly transactivated by HIF-1α49. The function of G6PD is strictly regulated in normal cells but highly activated in cancer cells, making G6PD a strong oncogene candidate44. Interestingly, G6PD and TK functions are both suppressed by resveratrol50, suggesting the usage of this natural product in cancer treatment and prevention.

While normal cells frequently rely on the oxidative branch of PPP for ribose-5-phosphate production; cancer cells use both arms, e.g., oxidative and non-oxidative, of PPP to generate ribose-5-phosphate for nucleic acid synthesis51-53. Furthermore, cancer cells can use ribose-5-phosphate in both de novo and salvage pathways to synthesize nucleotides. These flexible metabolic programs help cancer cells effectively adapt to constantly changing nutritional conditions of tumor microenvironment.

In addition, PPP also protects tumor cells from apoptosis by counteracting oxidative stress and facilitating DNA damage repair. In fact, nonsteroidal anti-inflammatory medications induce apoptosis and shrinkage of colon carcinoma and polyps by regulating PPP54. Moreover, G6PD inhibitors, e.g., DHEA and 6-AN, promote apoptosis in mouse fibroblasts and PC-12 neural cells while overexpression of G6PD protects cells from H2O2-induced cell death55. Knocking down of G6PD also increases oxidative stress-mediated toxicity in melanoma cells56. The vital role of PPP in protecting cells from programmed cell death is additionally proven in vivo such as in stem cells and peripheral blood mononuclear cells of patients lacking G6PD55,57,58. Interestingly, the cytoprotective function of PPP is not limited to defending against reactive oxygen species but also expands to helping DNA damage repair. Indeed, upon DNA damage, ATM quickly activates G6PD functions to accelerate PPP for quenching reactive oxygen species, increasing nucleotide synthesis and enabling effective DNA repair. Therefore, knocking down G6PD significantly impairs DNA damage repair ability59,60. Some other studies describe the impact of PPP on regulation of autophagy61, but the molecular mechanism is still not completely understood.

Surprisingly, PPP also induces tumor angiogenesis. Leopold et al.62 and Pan et al.63 reported the crosstalk between G6PD and VEGF and tight association between G6PD and angiogenesis. These studies show that VEGF stimulate G6PD expression via Src signaling and G6PD is important for VEGF-induced-endothelial cell migration by increasing the phosphorylation of VEGR receptor Flk-1/KDR. G6PD also increases the proangiogenic activity of endothelial NO by providing NADPH and stimulates Akt-induced activation of endothelial nitric oxide synthase (eNOS)62.

PPP additionally promotes tumor resistance to chemotherapy and radiation by multiple mechanisms. First, PPP provides cancer cells with NAPDH, a potent anti-oxidative agent that protects cancer cells from reactive oxygen species-induced cell death caused by chemotherapy and radiation44; Second, PPP facilitates DNA damage repair by providing material for nucleotide synthesis; Third, by shifting cancer metabolism away from mitochondrial respiration, PPP lowers the intracellular concentrations of reactive oxygen species, thereby increasing tumor endurance and survival during chemotherapy and radiation treatment; Fourth, NAPDH derived from PPP, is an important element for glutathione (GSH) generation. GSH is frequently used in detoxification reactions, enabling cancer resistance to a variety of chemotherapeutic agents. GSH conjugation to these xenobiotics also facilitates the activity of MDR1 and MDR2 to discard cytotoxic substances. Therefore, increase in G6PD expression and PPP flux increase intracellular GSH levels and reduce drug accumulation in cancer cells64. However, there are still many exceptions where PPP neither significantly contributes to drug resistance nor promotes the effect of certain chemotherapeutic agents in several cancer cell lines. This complexity requires more study to fully elucidate the contribution of PPP in protecting cells from anti-cancer treatments44.

In short, PPP is an important metabolic pathway providing cancer cells with NADPH, ribose-5-phosphate and other essential intermediates. NAPDH is crucial for counteracting oxidative stress and biosynthesis reactions. Ribose-5-phosphate is a major element for nucleotide synthesis. Interestingly, the impact of PPP on cancer cells is well beyond oxidative defense. Indeed, PPP upregulation promotes cancer cell survival, angiogenesis, proliferation, invasion, metastasis, and resistance to radiation and chemotherapies. Therefore, elevated and active PPP enzymes, for instance, TKTL or G6PD, are frequently observed in malignant, aggressive, proliferative and drug-resistant cancer cells44. The new exciting discoveries about PPP open new therapeutic windows but also require more study to refine rational approaches for precise and effective targeting of this vital metabolic pathway in cancer cells.

Mitochondrial biogenesis
Another major change in cancer metabolism is the enhancement of mitochondrial biogenesis. In contrast to conventional concepts, mitochondria play very important roles in cancer because these vital organelles are the nexus of many essential metabolic pathways65. Mitochondria are not only the energy generators but also the factories synthesizing many indispensable molecules for cellular biosynthesis, growth and proliferation. Moreover, mitochondria additionally control the redox balance and Ca2+ concentration, which is essential for cellular homeostasis65. Therefore, impairment of mitochondrial function or lack of mitochondrial biogenesis seriously suppresses tumorigenesis, tumor formation and growth65-71. Furthermore, in comparison with healthy and well differentiated cells, cancer cells frequently rewire their mitochondria to switch from a maximal energy production by mitochondrial electron transport chain to a well-adjusted balance among constant energy requirement, large-scale biogenesis programs and rapid cell proliferation65. Therefore, mitochondrial biogenesis and mitochondria are truly essential for tumor cells65. Hence, increase in mitochondria biogenesis is a significant advantage for cancer.

It is well established that c-Myc is a strong promoter of mitochondrial synthesis. In fact, c-Myc induces the expression of many nuclear-encoded mitochondrial genes. More importantly, c-Myc directly transactivates mitochondrial transcription factor A (TFAM). TFAM is a transcription factor that is indispensable for mitochondrial genes transcription and mitochondrial DNA replication72. In reality, TFAM promotes the right formation of mitochondrial transcription and replication complexes and facilitates the correct positioning of mitochondrial DNA for optimal gene transcription and proper mitochondrial DNA duplication65. As the synthesis of new mitochondrial components and replication of mitochondrial DNA are vital for de novo mitochondrial formation, c-Myc, indeed, plays a crucial role in elevating the number of mitochondria. As a consequence, lack of Myc expression and transactivational activity remarkably reduces mitochondrial mass as well as mitochondrial biogenesis, resulting in a severely suppressive impact on many metabolic pathways of cancer cells and tumorigenesis ultimately72.

Lipid synthesis
Increase in lipid metabolism is another remarkable feature of cancer metabolism. Lipids are important building blocks of new organelles and cells. Lipid synthesis is a multiple step process involving several enzymes such as ATP citrate lyase (ACLY), acetyl-CoA carboxylase (ACC), fatty acid synthase (FASN), and stearoyl-CoA desaturase (SCD). This procedure starts with converting acetyl-CoA to malonyl-CoA by ACC. A series of condensation reactions by FASN results in saturated fatty acids. Fatty acids could be desaturated by SCD. Cancer cells frequently upregulate de novo fatty acid synthesis to satisfy their demands for lipids73-75. FASN elevation is observed in breast, prostate and other types of cancer73,76-79. FASN is a target gene of HIF-1α and frequently overexpressed in an Akt and SREBP1-dependent manner80. ACLY, often activated by Akt81, is indispensable for tumor transformation and formation both in vitro and in vivo81,82. ACC is also very important for tumorigenesis as inhibition of ACC stops cancer growth and induces apoptosis of prostate cancer cells83. Furthermore, cancer cells often have higher lipid accumulation in form of lipid droplets in relative to normal cells84.

Cholesterol synthesis, or the mevalonate pathway, is also an important aspect of lipid biosynthesis because cholesterol is a major component of membranes controlling the membrane fluidity and formation of lipid rafts. Cholesterol is vital for activation of Ras-Raf signaling pathway85 and deregulation of cholesterol synthesis is correlated with tumorigenic transformation86. Interestingly, statin-mediated inhibition of HMGCR, an important enzyme of the mevalonate pathway, considerably ameliorates the effectiveness of chemotherapies in acute myeloid leukemia87, hepatocellular carcinoma88, and other types of cancer through epigenetic pattern modification89.

The sterol regulatory element-binding proteins (SREBPs) are the main transcription factors controlling the expression of most of enzymes involved in fatty acid and cholesterol synthesis. SREBPs are helix-loop-helix 125 kDa proteins that require a protein cleavage at the endoplasmic reticulum for activation73. While SREBP1 controls fatty acid, triacylglycerol and phospholipid synthesis, SREBP2 regulates cholesterol generation90. SREBPs are controlled by tumor suppressors and oncogenes. AMPK, for instance, inhibits SREBP activation91 and suppresses ACC91, thereby keeping lipid synthesis in check. Loss of pRb upregulates SREBP1 and SREBP2, thereby activating Ras signaling92. p53 mutants, on the other hand, coordinates with SREBP to transactivate cholesterol-synthesizing enzymes93. Of note, SREBP1 and SREBP2 are often overexpressed in cancer76 and play an important role in cancer cell survival94.

At the organism level, excessive lipid synthesis contributes to tumorigenesis. It has been well documented that obesity increases the risk of cancer73. In fact, excessive lipid concentrations in liver and muscle cells induce insulin resistance by impairing insulin signaling and reducing glucose uptake. Insulin resistance forces pancreatic cells to secrete more insulin and insulin-like growth factors, which is very beneficial for cancer proliferation and survival95-97. Obesity also increases inflammation, which contributes to insulin resistance and tumorigenesis98. Dietary restriction may reverse these tumorigenic trends but in certain scenarios, especially when PI3K/Akt signaling is overactivated, the tumor-suppressing impact of dietary limitation decreased99. A possible explanation is that nutrient restriction may reduce the levels of circulating insulin and insulin-like growth factors. However, the constitutive activation of PI3K/Akt may compensate for that insulin signaling decrease100.

Fatty acid oxidation
While glycolysis, glutaminolysis, fatty acid synthesis have been well characterized during the past few decades; fatty acid oxidation (FAO) still remains a little known metabolic pathway. However, recent studies have demonstrated the important contribution of FAO to tumorigenesis101.

Fatty acids are a rich energy source that can yield to up to two times more ATP than carbohydrates when needed. Fatty acids could be oxidized in mitochondria or by cytoplasmic lipophagy, a new fatty acid catabolic process102. FAO is a repeated multi-round process leading to the production of acetyl CoA, NADH, and FADH2 in each cycle. Acetyl-CoA can be imported into TCA cycle to generate more NADH and FADH2, which subsequently fuel mitochondrial respiration chain for ATP production. Acetyl-CoA can also fuel TCA cycle for synthesis of citrate. Citrate-derived isocitrate and malate can be respectively converted to α-ketoglutarate by IDH1 or pyruvate by malic enzyme (ME1)102. Both reactions generate NADPH, which plays a very important role in maintaining redox homeostasis, inducing cell survival, enabling xenobiotics detoxification and promoting biosynthesis for cell growth and division103. Of note, NAPDH is crucial for the function of many anabolic enzymes to sustain large-scale biosynthetic programs in many cancer cells.

NAPDH derived from FAO is very important for cancer cells to quench reactive oxidative stress. For instance, blocking glioma tumor’s FAO leads to rapid depletion of NADPH, surge of reactive oxidative species’ concentrations and increase in apoptosis104. NADPH produced by FAO is also relevant to the maintenance of hematopoietic stem cells because these cells are very sensitive and vulnerable to reactive oxidative stress. In fact, increased reactive oxygen species levels inhibit hematopoietic stem cells’ self-renewal and leads to cell differentiation105-107. Jeon et al.108 reported that LKB1-APMK regulates the balance between NADPH consumption by fatty acid synthesis and NAPDH production by FAO. In fact, AMPK blocks fatty acid synthesis in tumors by phosphorylating and inactivating acetyl-CoA carboxylase (ACC)109, antagonizing PPAR signal transduction110 and regulating CTP1C expression111. Therefore, AMPK is a potent inhibitor of fatty acid synthesis in cancer cells.

Needless for further emphasis, ATP is by large one of the most important molecules for cancer cells. Due to its rapid proliferation and accelerated activities, tumors are almost constantly in high demand for ATP. ATP is the most frequently used energy currency and a major material for phosphorylation reactions, an essential mode of cellular signal transduction and protein modification. ATP is also an indispensable element for DNA and RNA replication and repair. The function of MDR1 and other ABC pumps on cellular membrane, a major tumors’ line of defense against chemotherapy, absolutely requires ATP.

Recently, ATP production by FAO has been shown to prevent anoikis, a type of cell death due to loss of attachment to extracellular matrix although the molecular mechanism still remains unclear and warrants more study103,112. The Pandolfi group113 also reported that the promyelocytic leukemia (PML) protein induced FAO by activating peroxisome-proliferator-activated receptors (PPARs), leading to poor survival and clinical outcomes of breast cancer patients. Moreover, Tak Mak’s lab111 additionally found that carnitine palmitoyl-transferase 1 isoform C (CPT1C) is an oncogene that induces cancer growth, ATP production, FAO and confers resistance to mTORC1 inhibitors. CPT1 proteins mediate the import of fatty acids into mitochondria for FAO reactions. CPT1 links carnitine to fatty acids and transports the conjugated products (acyl-carnitines) into mitochondria. Therefore, the oncogenic property of CPT1C is a good example illustrating the potential of FAO in tumorigenesis.

FAO is also important in ensuring cancer cell survival in a manner that is independent of ATP production101. In fact, CPT1 proteins suppress the pro-apoptotic function of Bax and Bak by modulating the formation of mitochondrial permeability transition pores and reducing cytochrome c release114,115. The results from Samudio et al.116 and Vickers group117 additionally indicate that FAO can promote cancer cell survival by preventing a cytotoxic intracellular surge of fatty acid concentrations. On the other hand, several groups show that the increase in reactive oxygen species due to FAO-induced mitochondrial respiration could be harmful for leukemia cells. However, this toxicity could be resolved by upregulating uncoupling protein 2 and 3 (UCP2, UCP3) that effectively dissipate the gradient proton in mitochondria and decrease mitochondrial oxidative phosphorylation efficiency118.

Thus, fatty acid oxidation promotes cancer cell survival, and provides tumors with necessary energy and precursors. The new findings about FAO reveal fascinating understandings about cancer metabolic reprogramming and unveil very promising opportunities for anti-cancer therapeutic approaches. However, additional knowledge is needed to successfully develop effective therapies targeting this important catabolic process in cancer.

Interestingly, Hu et al.119 has recently completed a massive meta-analysis of over 2,500 microarrays including 22 types of cancer to compare the metabolic gene expression landscape of tumors relative to that of corresponding normal tissues. From this comprehensive transcriptomics analysis, three important observations have been reported: (1) despite the process of tumor evolution, there is still a significant degree of similarity in the gene expression metabolic profiles of tumors in comparison with those of the normal tissues where tumors originate; (2) the metabolic gene expression landscape across different types of tumors is heterogeneous. However, glycolysis, nucleotide synthesis, aminoacyl-tRNA synthesis, and pentose phosphate pathway are consistently upregulated and increasingly important in actively proliferating cancer cells; (3) hundreds of metabolic isoenzymes demonstrate remarkable and cancer-specific expression alterations, representing new significant therapeutic opportunities for anti-cancer metabolism therapies. These isoenzymes are important for cancer. Some enzymes such as isocitrate dehydrogenase and fumarate dehydratase, may even imitate or aggravate the impact of tumorigenic genetic mutations119.

In short, metabolic reprogramming is an important cancer hallmark characterized by the upregulation of glycolysis, glutaminolysis, lipid metabolism, mitochondrial biogenesis, pentose phosphate pathway as well as other biosynthetic and bioenergetic pathways. These cancer metabolic programs provide tumor cells with not only necessary energy but also crucial materials to support large-scale biosynthesis, rapid proliferation, survival, invasion, metastasis and resistance to anti-cancer therapies. Therefore, exploiting the unique features of cancer metabolism for cancer detection, treatment and monitoring is a very promising trend in cancer therapeutics, diagnosis and prevention.

Cancer metabolism and diagnostic imaging
The distinguished features of cancer metabolism have been extensively exploited for initial diagnosis, staging disease, monitoring tumor responses to therapies, and detecting cancer recurrence120. Therefore, nowadays, metabolic molecular imaging plays an indispensable role in clinical oncology. These diagnostic methods are non-invasive and can accurately detect the changes in selective biologic processes of tumors compared to normal surrounding tissues both at the initial tumor sites and metastatic locations over an extended period of time. The information provided by advanced imaging modalities such as PET, magnetic resonance spectroscopy imaging (MRSI), magnetic resonance imaging (MRI), is very valuable for cancer detection, prevention, and treatment120.

Positron emission tomography(PET)
PET is frequently combined with X-ray computed tomography (CT) to provide detailed information about cancer and anatomic locations of tumors. PET measures the signals of radiolabeled tracers taken up by cancer cells. PET is safe and widely used in clinics because the small amount of imaging probes doesn’t interfere with normal physiological processes. 18F-fluoro-2-deoxyglucose (FDG) is the most commonly used PET imaging material. Since most of tumors have a high glycolytic flux, elevated glucose uptake and increased hexokinase function, they will often have higher FDG signals relative to normal tissues. After being imported into tumor cells, FDG is phosphorylated by hexokinase but phosphorylated FDG cannot be further catabolized by glycolytic pathway. Therefore, phosphorylated FDG molecules are accumulated in tumors and can be detected by PET scanners. In clinics, FDG-PET scan is commonly used for determining cancer stages, identifying cancer recurrence and assessing tumor response to anti-cancer therapies121,122.

In addition to upregulated glycolysis, other patterns of cancer metabolism are also used for molecular oncology imaging using PET scan. Choline, for example, is frequently absorbed by tumor cells and used for new cellular membrane biosynthesis, an important process for cell division. Therefore 11C and 18F radiolabeled choline tracers have been successfully applied in hepatocellular carcinoma, lung, brain, and prostate cancer diagnosis123-126. Similarly, 3'-deoxy-3'-18F-fluorothymidine is often used to monitor cancer cell proliferation in vivo. 3'-deoxy-3'-18F-fluorothymidine is a thymidine analog and frequently phosphorylated by thymidine kinase 1. This enzyme is highly active in rapidly dividing cells, e.g., tumor cells, especially in S phase. Thus, 3'-deoxy-3'-18F-fluorothymidine PET can identify and measure tumor malignancy, tracking the efficacy of anti-cancer therapies127. Many other tracers are also used in PET imaging modality to monitor specific biological processes of tumors. For instance, 68Ga-DOTATOC, a high-affinity ligand for somatostatin receptor 2, is used to detect neuroendocrine cancer masses128. 16-α-18F-fluoro-17β-estradiol is used to quantify ERα and ERβ expression129. Tumor angiogenesis and the effectiveness of anti-angiogenic therapeutic agents are measured by tracers containing arginine-glycine-aspartic acid-peptide ligands. These ligands associate with αvβ3 integrin whose expression is elevated on newly formed blood vessels130. Nitroimidazole is also exploited to image hypoxic areas where tumors are frequently located131.

In summary, PET with radiolabeled metabolic tracers is certainly a valuable and powerful imaging method with vast applications in clinical oncology. This diagnostic modality is continuously improved and more advanced tracers are in development. However, radiation is still a major concern for PET and its tracers. The radiation containment and safety are also other significant issues for PET application in clinics120. In addition, a complete understanding about cancer metabolic patterns and bioenergetics programs is crucial to continuously innovate metabolic tracers-based PET scan imaging.

The combination of MRI and MRSI
MRI and MRSI are often combined in clinical oncology diagnostics because 1H MRSI is easily compatible with currently available MRI scanners in clinics132-134. 1H MRSI has a high sensitivity and could be applied on a number of tracers120. During the past few years, MRSI has made significant advances and rapidly become a reliable imaging modality. A number of 1H tracers have been successfully developed. For instance, 1H choline-containing metabolites are employed to measure tumor malignancy. Choline is an important component of cellular membrane. Higher choline concentrations are detected in aggressive and malignant tumors in comparison with benign and normal tissues135,136. In fact, many breast tumors contain a large amount of choline while benign tumor masses often have low levels of choline135,136. Since the accumulation of choline is associated with increased cell proliferation in brain, breast, cervical and prostate cancers133,137-139, choline availability could be used as a marker for predicting tumor histologic grade, aggressiveness, and even response to anti-cancer therapies with low unspecific detection rates120,139. Moreover, as brain tumors often have increased choline concentrations and diminished levels of N-acetyl aspartate, the ratio of choline/N-acetyl aspartate has been used to evaluate the aggressiveness of several types of brain tumors140-142. Choline/creatinine ratio measurement is also a valuable indicator of oligodendroglial cancer grade143.

13C tracers are emerging important diagnostic probes although their application is still at early stages. Recently, Nelson et al.144 reported a successful preclinical study and phase I clinical trial results with 31 prostate cancer patients. This is a pioneer project examining the applicability and safety of hyperpolarized 13C pyruvate tracers to monitor and evaluate the metabolic changes, especially 13C pyruvate-to-13C lactate flux, of prostate tumors in patients. This technique enabled a 10,000-fold increase in signals compared to regular MRI. Results were very promising with excellent safety profiles and accurate detection of 13C pyruvate-to-13C lactate flux in tumor areas that were subsequently proven by biopsy-based pathological and histological analyses. The success of this pioneer study paves a new way for non-invasive, safe, precise, and sensitive cancer diagnosis as well as tumor monitoring. A number of new types of 13C metabolic tracers are under development and will certainly play a major role in cancer detection and imaging in future.

Poor spatial resolution used to be a challenge for MRSI133,138,145,146, but new advances and ongoing technological improvements are addressing this limiting factor, making MRSI a promising adjunct to MRI. Combining conventional MRI with MRSI will enable accurate, safe and non-invasive characterization of tumors. This new diagnostic strategy is especially important when collecting lesion biopsies is risky, painful and difficult. Thus, in future, this new combinatory imaging modality will reduce patients’ discomfort, concern, risk, pain, and avoid unnecessary invasive diagnostic procedures while increasing the accuracy, reliability and sensitivity of diagnosis120.

In summary, diagnostic imaging plays a crucial role in cancer detection and treatment. Exploiting the unique features of cancer metabolism is a very promising direction for developing novel diagnosis methods to accurately detect cancer lesions even at early stages and precisely monitor tumors’ responses to therapies.

Therapeutic implications
Given the vital role of metabolic reprogramming for tumorigenesis, targeting cancer bioenergetics is a very promising and rapidly rising direction for anti-cancer therapy development nowadays. Many compounds have been developed to selectively and effectively inhibit metabolic enzymes that are important for tumors. These inhibitors are currently at various stages of clinical trial process and we expect to see them in clinics within five to ten years from now.

One of the most common trends in anti-cancer metabolism therapies is to inhibit enzymes that are exclusively or mostly expressed or used in tumor cells. This therapeutic strategy would effectively eliminate tumors while minimizing damage to normal cells. Several groups have successfully developed inhibitors for Glutaminase 1 (GLS1), a glutaminase isoform that is highly upregulated in cancer cells, and proved the efficacy of blocking GLS1 in cancer treatment147,148. This tactic bases on previous studies showing a significant dependence of c-Myc-overexpressing cancer cells on glutaminolysis9,11-15,25,149. Similarly, modulating the activity of PKM2, a glycolytic enzyme that is frequently elevated in tumors, is also a promising therapy150,151. Fatty synthase (FASN) is important for palmitate synthesis and this enzyme’s expression is elevated in many tumors. Therefore, several groups have developed FASN inhibitors to target tumorigenesis75,152. Many inhibitors for HIF and HIF targets, for instance monocarboxylate transporter MCT4 and carbonic anhydrase IX (CAIX) are also potential anti-cancer drugs in future153-156. Similarly, MCT1 and carbonic anhydrase XII are targets of great potential153,154. MCT1 and MCT4 suppressors inhibit cancer growth in vitro and in vivo and invasion in vitro157-160. In fact, interfering with lactate transport by MCT1 and MCT4 inhibitors has been shown to induce tumor cell starvation and subsequent apoptosis158.

Blocking lactate production using dichloroacetate (DCA) shows promising results with minor side effects in early phase clinical trials, especially in glioblastoma patients161,162. DCA is found to promote pyruvate-to-acetyl-CoA flux and reduce pyruvate-to-lactate conversion, thereby inducing tumor shrinkage and apoptosis in vivo161-163. Clinical trial data show that DCA also suppresses tumor angiogenesis, blocks HIF1-α signaling and activates p53 in glioblastoma multiforme patients161. Initial studies additionally find that DCA inhibits pyruvate dehydrogenase kinase 1 (PDK1) activity and thereby activating the function of pyruvate dehydrogenase 1 (PDH1), an important enzyme catalyzing the pyruvate-to-acetyl-CoA biochemical reaction162,163. However, more and larger clinical studies are needed to fully elucidate the mechanism of action of this interesting compound and further evaluate its efficacy in cancer patients.

Glycolysis inhibitors are also of interest for many groups and pharmaceutical companies. For instance, FX11, a selective suppressor of lactate dehydrogenase A (LDHA) activity, was tested by Le et al.164 and is currently studied by National Cancer Institute’s Experimental Therapeutics Program (NExT). 2-deoxyglucose (2-DG) is among the most advanced cancer metabolism inhibitors in clinical trials (Phase II). 2-DG reversibly inhibits hexokinase to block glycolysis. 2-DG usage in combination with radiation demonstrates a good safety profile and slightly improves survival of glioblastoma multiforme patients165,166. However, the effects of 2-DG may be limited by high concentration of glucose because 2-DG-mediated inhibition of hexokinase is reversible.

Inhibiting mutant isocitrate dehydrogenase 1 (IDH1) and isocitrate dehydrogenase 2 (IDH2) is a remarkable therapeutic approach because these mutant enzymes have distinct activities compared to normal IDH1 and IDH2 in the healthy cells. On the other hand, metformin, a common anti-diabetics medication, has demonstrated very promising impact in cancer treatment. It is well known that metformin inhibits mitochondrial complex I of liver cells, thereby decreasing ATP production. Lack of ATP subsequently stimulates LKB1-AMPK pathway and blocks gluconeogenesis, leading to lower blood glucose concentrations, improved sensitivity to insulin and diminished insulin production167. It is currently unclear whether metformin improves cancer patient clinical outcomes by lowering blood glucose levels and insulin/insulin-like growth factors generation or by directly targeting cancer cells. Nevertheless, the usage of metformin has been well documented to ameliorate cancer patient survival168,169 and metformin are harmful for cancer stem cells170. Clinical trials testing the impact of metformin on cancer in patients are ongoing (Table 1).

Table 1
Table 1 List of several potential anti-cancer metabolism compounds
Full table
Importantly, there is also an urgent need to develop effective inhibitors to target the key inducers of cancer metabolic reprogramming such as c-Myc and Ras. Ras mutations and c-Myc upregulation are frequent in many common types of cancer and these dysregulations are major drivers of tumorigenesis and resistance to therapies171,172. However, despite our relentless efforts, effectively and directly inhibiting Ras and c-Myc still requires a lot more study because these two proteins are currently undruggable targets. Interestingly, several preclinical research projects show that targeting metabolic enzymes significantly inhibits tumors carrying Ras mutation and c-Myc overexpression9,173. In fact, suppressing glycolysis and glutaminolysis remarkably antagonizes the growth of tumors bearing those genetic alterations9,164,174,175. These observations imply a new way to treat tumors carrying genetic mutations that can’t be directly targeted.

Another striking example of successful anti-cancer metabolism therapies is L-asparaginase. L-asparaginase mediates deamination reactions to degrade asparagine into aspartic acid176, thereby reducing asparagine availability to cancer cells and suppressing their growth177,178. This therapy is very effective for acute lymphoblastic leukemia (ALL) and related leukemia subtypes because ALL cells are unable to synthesize asparagine179. Therefore, these cancer cells have to rely on extracellular asparagine sources and become very vulnerable when asparagine supplies are limited.

However, lymphocytes, especially T cells, have similar metabolic programs as those in tumor cells. For instance, lymphocytes also depends on glutamine metabolism180, suggesting that systematically targeting glutaminolysis for cancer treatment may severely affect adaptive immune responses and also innate immunity to a certain degree. These metabolic similarities between cancer cells and lymphocytes explain why many agents targeting cancer metabolism are also strong immunosuppressants. For instance, cyclosporine, a potent anti-cancer drug that inhibits mTOR, significantly suppresses immune system. Suppressor of nicotinamide phosphoribosyltransferase (NAMPT), an enzyme responsible for nicotinamide adenine dinucleotide (NAD+) regeneration, is poisonous to lymphocytes181. In fact, early clinical trials data show that FK866, a NAD+synthesis inhibitor, leads to mild lymphopenia and severe thrombocytopenia182.

These findings suggest that immunosuppression could be a challenge for therapies designed to target cancer cells’ bioenergetics as the Achilles’ heel of tumors. Nevertheless, there is still a significant therapeutic window for anti-cancer metabolic therapies. We just need to identify the key differences in the bioenergetics patterns of tumors and those of healthy cells in order to optimize our therapies for precisely inhibiting the unique metabolic targets in cancer cells. A significant example is to use BPTES to selectively block GLS1, a glutaminase enzyme isoform that is crucial for cancer cells and specifically upregulated in tumors147,148.

Conclusion
Metabolic reprogramming is a major hallmark of cancer, which is characterized by upregulated glycolysis, glutaminolysis, lipid metabolism, pentose phosphate pathway, mitochondrial biogenesis, among others. These metabolic programs provide cancer cells with not only energy but also vital metabolites to support large-scale biosynthesis, continuous proliferation and other major processes of tumorigenesis. Potent oncogenes as c-Myc, HIF1α, Ras and PI3K/Akt are important promoters of cancer metabolic alterations. In contrast, major tumor suppressors such as p53 and LKB1/AMPK antagonize those changes and keep cellular metabolism in check (Figure 1 and Figure 2). Rfewiring metabolism is very beneficial for tumor survival, invasion, metastasis, growth, angiogenesis, proliferation and resistance to anti-cancer therapies. Although there is still much to study and discover, recent remarkable advances in this field have unveiled exciting therapeutic windows to precisely and effectively target cancer metabolism and bioenergetics (Figure 3). It is expected that anti-cancer metabolism therapies will play an important role in clinical oncology within five or ten years.


Figure 1 The impacts of tumor suppressors and oncogenes on cancer metabolic reprogramming, an important cancer hallmark. Cancer metabolic alterations are the results of oncogene activation and mutant metabolic enzymes. Cancer metabolic reprogramming promotes tumorigenesis by facilitating and enabling rapid proliferation, survival, invasion, metastasis, resistance to therapies and other central cellular processes of tumorigenesis. On the other hand, as tumorigenesis advances, cancer cells acquire more mutations and changes that further enhance metabolic reprogramming and, in turn, accelerate tumor growth, proliferation and progression. Tumor suppressors, for instance, p53, and AMPK, exert their suppressive regulation on cancer metabolic alterations by blocking the function, activation and expression of essential cancer metabolic genes. Our recent results also show that 14-3-3σ, a downstream target gene of p53, effectively opposes and reverses cancer metabolic reprogramming. Our data indicate that 14-3-3σ accelerates the degradation of c-Myc, an important transcription factor promoting cancer metabolic reprogramming183. In contrast, oncogenes such as c-Myc, HIF-1α, Ras, and Akt are major inducers of tumor bioenergetics alterations by upregulating the expression or activation of key metabolic enzymes such as HK2, GLS1, LDHA, among others. The balance between tumor suppressors and oncogenes has a decisive impact on the status of cancer metabolism.

Figure 2 Summary of key changes in cancer metabolic reprogramming. Cancer metabolic reprogramming is characterized by enhanced glycolysis, PPP, lipid metabolism, glutaminolysis, mitochondrial biogenesis, among others. These pathways provide cancer cells with not only essential energy but also important precursors to support large-scale biosynthesis, rapid proliferation, continuous growth, tissue invasion, metastasis, survival and resistance to anti-cancer therapies. For instance, glycolysis generates 2 ATP per glucose consumed and provides materials for PPP and other biosynthetic programs. Similarly, PPP supplies tumors with ribose-5-phosphate and NADPH. Ribose-5-phosphate is a major element for nucleotide synthesis, which is used in DNA replication, RNA synthesis, and DNA damage repair, among others. NADPH is a key line of defense counteracting oxidative stress and a crucial metabolite for a number of biosynthesis reactions. NADPH is produced by 4 biochemical reactions mediated by G6PD, 6PLGD, ME1 and IDH1. In addition, fatty acid synthesis is indispensable for formation of new cellular membranes and proliferation. A number of fatty acid synthesis enzymes such as ACC, ACLY and FASN are upregulated or activated by oncogenes such as c-Myc, HIF-1α, Akt, among others. On the other hand, FAO is also important for cancer cells because it generates energy, NADPH and other necessary metabolites. Fatty acids are imported into mitochondria by CPT1 and oxidized to generate acetyl-CoA. Acetyl-CoA fuels the TCA cycle to generate NADH and FADH2. The latter metabolites donate electrons to mitochondrial ETC for ATP generation. CPT1 also antagonizes Bax and Bad-mediated apoptosis by preventing the formation of mitochondrial membrane transition pores and reducing cytochrome c release. Citrate produced by the TCA cycle can be transported from mitochondria to cytosol. Cytosolic citrate is used in a number of reactions to produce acetyl-CoA, oxaloacetate and isocitrate. These metabolites are important for lipid synthesis, NAPDH production, and many other central cellular processes. Mitochondrial biogenesis is also a striking feature of cancer metabolic reprogramming. Mitochondria are not only the energy generators but also the factories for synthesizing many essential metabolites for cancer growth, proliferation and metastasis. In addition, the metabolic lactate-based symbiosis is another remarkable characteristic of cancer metabolism. Cancer cells frequently upregulate LDHA to facilitate the conversion of pyruvate to lactate. Lactate is then secreted to tumor microenvironment via MCT4 transporters and can be taken by neighboring cancer cell thanks to MCT1 importers. Lactate is thereafter used for other metabolic pathways in tumors. This metabolic symbiosis facilitates the survival of cancer cells in harsh conditions. Thus, metabolic reprogramming is a major cancer hallmark. It is characterized by the upregulation of a number of inter-connected metabolic pathways providing cancer cells with vital energy and metabolites. This metabolic plasticity is essentially important because it allows cancer cells to effectively and rapidly adapt to the rapidly changing conditions of tumor microenvironment. In addition, the flexibility of cancer bioenergetics also enables rapid proliferation, continuous growth, invasion, metastasis and resistance to anti-cancer therapies. Therefore, further knowledge about cancer metabolic reprogramming is very important for successful development of precise and efficacious anti-cancer metabolism therapies. Dashed arrows indicate indirect effects or multi-step processes. Abbreviations: HK2, hexokinase 2; LDHA, lactate dehydrogenase A; G6PD, glucose-6-phosphate dehydrogenase; 6PGLD, 6-phosphogluconate dehydrogenase; ACC, acetyl-CoA carboxylase; ACLY, ATP citrate lyase; FASN: fatty acid synthase, SCD, stearoyl-CoA desaturase; CPT, carnitine palmitoyltransferase; CPT1C, carnitine palmitoyltransferase 1C; PDH, pyruvate dehydrogenase; PDK, pyruvate dehydrogenase kinase; UCP, uncoupling proteins; MCT, monocarboxylic acid transporter; ME1, malic enzyme; IDH1, isocitrate dehydrogenase1; GLS1, glutaminase; GLUD, glutamate dehydrogenase; FAO, fatty acid oxidation; ETC, electron transport chain; PPP, pentose phosphate pathway; TCA, tricarboxylic acid cycle; α-KG, alpha-ketoglutarate.

Figure 3 Summary of the mechanism of several important drug candidates for anti-cancer metabolism therapies. Phloretin inhibits the import of glucose, a major source of nutrient for cancer cells. 2DG, 3BrPA, and Lonidamine inhibit HK2, a rate-limiting step of glycolytic pathway. 3PO blocks PFK1 activation by inhibiting PFKFB3 (PFK2). FX11 selectively inhibits LDHA, a major metabolic enzyme of cancer. BPTES and 968 suppress the function of GLS1. GLS1 is a glutaminolytic enzyme that is highly and selectively upregulated in cancer. DCA inactivates PDH kinase (PDK), thereby increasing PDH activity and enhances the conversion of pyruvate to acetyl-CoA and decreases cancer glycolysis. Metformin blocks energy production of cancer cells by inhibiting mitochondrial complex I, suppresses lipid and protein synthesis, modulates glycolysis. At the organism level, by lowering blood glucose concentration, metformin decreases glucose supply, as well as insulin and insulin-like growth factor signaling availability for tumor cells. MCT inhibitors impair the metabolic lactate-based symbiosis of cancer cells. Many other anti-cancer metabolism compounds are under development. Targeting cancer metabolism is a very promising direction for anti-cancer therapies. It is expected that inhibitors of tumor metabolism will play an important role in clinical oncology within five or ten years. These medications could be used alone or in combination with other current anti-cancer therapies to increase efficacy. Abbreviations: 2DG, 2-deoxyglucose; 3BrPA, 3-bromopyruvate; HK2, hexokinase 2; PFK1, phosphofructose kinase 1; LDHA, lactate dehydrogenase A; GLS1, glutaminase 1; DCA, dicholoroacetate; PDH, pyruvate dehydrogenase; PDK, pyruvate dehydrogenase kinase; MCT, monocarboxylic acid transporter.

However, the efficacy of anti-cancer metabolism therapies will need to be carefully evaluated because cancer cells are well known for their metabolic plasticity and heterogeneity1,2,11,21,119,184. That may enable tumors to bypass certain inhibition mediated by therapeutic agents. Furthermore, as we have seen during the past decades, inhibiting individual enzymes or blocking single pathways seldom leads to effective cancer treatment. Therefore, it is highly likely that anti-cancer metabolism approaches need to be combined with other therapies to improve therapeutic effects and clinical outcomes. Further understanding about cancer metabolic reprogramming is certainly needed for effective therapy development. Nevertheless, exploiting the unique features and weakness of tumor metabolism for cancer treatment, detection and monitoring is clearly a very promising direction.

Cancer metabolic reprogramming: importance, main features, and potentials for precise targeted anti-cancer therapies | Phan | Cancer Biology & Medicine
http://www.cancerbiomed.org/index.php/cocr/article/view/629/655

Metabolic reprogramming: the emerging concept and associated therapeutic strategies
Go J. Yoshida
Journal of Experimental & Clinical Cancer Research volume 34, Article number: 111 (2015) Cite this article



Abstract
Tumor tissue is composed of cancer cells and surrounding stromal cells with diverse genetic/epigenetic backgrounds, a situation known as intra-tumoral heterogeneity. Cancer cells are surrounded by a totally different microenvironment than that of normal cells; consequently, tumor cells must exhibit rapidly adaptive responses to hypoxia and hypo-nutrient conditions. This phenomenon of changes of tumor cellular bioenergetics, called “metabolic reprogramming”, has been recognized as one of 10 hallmarks of cancer. Metabolic reprogramming is required for both malignant transformation and tumor development, including invasion and metastasis. Although the Warburg effect has been widely accepted as a common feature of metabolic reprogramming, accumulating evidence has revealed that tumor cells depend on mitochondrial metabolism as well as aerobic glycolysis. Remarkably, cancer-associated fibroblasts in tumor stroma tend to activate both glycolysis and autophagy in contrast to neighboring cancer cells, which leads to a reverse Warburg effect. Heterogeneity of monocarboxylate transporter expression reflects cellular metabolic heterogeneity with respect to the production and uptake of lactate. In tumor tissue, metabolic heterogeneity induces metabolic symbiosis, which is responsible for adaptation to drastic changes in the nutrient microenvironment resulting from chemotherapy. In addition, metabolic heterogeneity is responsible for the failure to induce the same therapeutic effect against cancer cells as a whole. In particular, cancer stem cells exhibit several biological features responsible for resistance to conventional anti-tumor therapies. Consequently, cancer stem cells tend to form minimal residual disease after chemotherapy and exhibit metastatic potential with additional metabolic reprogramming. This type of altered metabolic reprogramming leads to adaptive/acquired resistance to anti-tumor therapy. Collectively, complex and dynamic metabolic reprogramming should be regarded as a reflection of the “robustness” of tumor cells against unfavorable conditions. This review focuses on the concept of metabolic reprogramming in heterogeneous tumor tissue, and further emphasizes the importance of developing novel therapeutic strategies based on drug repositioning.

Introduction
Tumor tissue consists of a heterogeneous cellular population. Stromal cells such as neurons, vascular endothelial cells, fibroblasts, and macrophages in cancer tissue drive chemotherapy resistance [1] as well as tumor survival and progression [2, 3]. Even in pure populations of tumor cells, heterogeneity is present as a result of genetic mutation and epigenetic modulations. This cellular heterogeneity can be explained by a hierarchical model, in which cancer stem-like cells (CSCs) can provide transient amplifying cells and differentiated non-CSCs involved in establishing the tumor tissue [4, 5]. CSCs possess several biological features of “stemness”, a combination of phenotypes including plasticity in the transition between quiescent (G0 phase) and proliferative states [6] and resistance to redox stress and chemotherapeutic agents [7, 8]. Importantly, accumulating evidence suggests that metabolic reprogramming is crucial in order for CSCs to maintain unlimited self-renewal potential and hyper-adaptation to drastic changes in the tumor microenvironment [9–11].

Intra-tumoral heterogeneity due to the presence of CSCs is primarily responsible for our inability to induce the same therapeutic effect among cancer cells as a whole [12, 13]. CSCs are very likely to contribute to the formation of minimal residual disease (MRD) [1]. The term ‘MRD’ is most often used in the context of hematological malignant disorders [14], but the underlying concept is quite convenient in discussion of clinically undetectable resistant clones after conventional anti-tumor therapies [1]. Thus, MRD is expected to contribute prominently to latent relapse and distant metastasis (Fig. 1).

Fig. 1
figure1
Cancer stem cells and MRD formation. Heterogeneous tumor tissue with combined-modality therapy leads to the formation of MRD, which is clinically undetectable. Transiently reduced heterogeneity is observed in MRD, which is enriched in CSCs. Relapse or metastasis results in re-acquisition of a heterogeneous population that is more potentially aggressive in terms of its degree of “stemness”

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Aberrant proliferation of cancer cells is supported by enhanced adaptation to nutrient microenvironment mediated by alterations in energy metabolism. Consequently, metabolic reprogramming is believed to be one of the hallmarks of tumor cells in parallel with genomic instability, tumor-provoking chronic inflammation, escape from the immune system, etc. [5]. Although aerobic glycolysis, termed the Warburg effect, is a characteristic metabolic feature of cancer cells [15, 16], recent investigations revealed that other metabolic features, in particular, the reverse Warburg effect [17, 18], metabolic symbiosis [19, 20], and addiction to glutamine metabolism [21, 22], create challenges for anti-cancer treatment due to adaptive or acquired chemoresistance. This review article focuses on the relationship between metabolic reprogramming and tumor heterogeneity, as well as on the development of promising therapeutic strategies by drug repositioning targeting metabolic reprogramming.

Conventional Warburg effect and emerging concepts
In 1924, Otto Warburg discovered that tumor cells tend to produce large amounts of lactate from glucose, regardless of the available oxygen level [15, 16]. This situation is similar to anaerobic glycolysis, implying that oxidative phosphorylation (OXPHOS) is replaced by glycolysis in normal differentiated cells under hypoxia [23, 24]. However, cancer cells appear to engage in glycolytic metabolism before they are exposed to hypoxic conditions [15, 16]. OXPHOS in mitochondria generates as many as 36 mol ATP from 1 mol glucose, whereas the conversion of glucose to pyruvate or lactate produces only 2 or 4 mol ATP, respectively [25, 26]. It remains unclear why cancer cells largely depend on this “inefficient” metabolic pathway, even when enough oxygen is available [27, 28]. In striking contrast to normal cells, cancer cells preferentially uptake and convert glucose into lactate even in the presence of sufficient oxygen [29]. This seemingly “inefficient” metabolic characteristic relies largely on aberrant upregulation of GLUT1, a glucose transporters abundantly expressed in cancer cells [30, 31], although one contradictory study reported that GLUT1 is not necessarily involved in the Warburg effect depending on the degree of tumor invasiveness [32]. Inefficient ATP synthesis becomes an obstacle for cancer cells only when their energy resources are scarce. However, this is not the case in proliferating cancer cells with aberrant angiogenesis [29]. Tumor cells finely regulate ATP synthesis by regulating substrate uptake, as well as enzymes related to glycolysis, which enables them adapt to the nutrient microenvironment [33]. Moreover, the regulation of adenosine monophosphate-activated protein kinase (AMPK) signal transduction, a sensor of energy status, is intimately connected to the Warburg effect, one form of metabolic reprogramming of cancer cells [34, 35]. Indeed, genetic ablation of AMPK activates mammalian target of rapamycin (mTOR) signal with ectopic expression of hypoxia-inducible factor-1 alpha (HIF-1 alpha), resulting in rapid cellular proliferation accompanied by activation of aerobic glycolysis [35]. This strongly suggests the importance of cancer metabolic reprogramming in maintaining the interaction between the oxygen-sensing transcription factor and the nutrient-sensing signal pathway.

Metabolic reprogramming in response to chemotherapy
Tumor heterogeneity in regard to mitochondrial metabolism, in seeming contradiction to the Warburg effect, is considered to induce the diversity in activated metabolic pathways [36] (Fig. 2). Notably, MRD in several kinds of cancers is enriched in CSCs, leading to intra-tumoral heterogeneity and poor prognosis [1, 9, 10, 37]. Non-CSCs of bladder cancer, for instance, release prostaglandin E2 (PGE2) when they undergo apoptosis during the course of chemotherapy. PGE2 promotes the awakening of dormant G0-phased CSCs into the proliferative state [9]. Given that PGE2-mediated metabolic activation in mitochondria has been demonstrated in non-malignant cells [38], it is possible that activated CSCs undergo altered metabolic reprogramming (Fig. 3). Similarly, the survivors after transient depletion of a driver oncogene (i.e., activated mutant KRAS G12D in pancreatic cancer) tend to depend heavily on OXPHOS in mitochondria rather than aerobic glycolysis. Comprehensive analysis of metabolic pathways of survivors after chemotherapy revealed the prominent expression of genes that regulate mitochondrial function, autophagy and lysosome degradation activity, as well as a strong reliance on mitochondrial respiration and diminished dependence on the Warburg effect [10]. Autophagy is a metabolic-recycling pathway involving proteasome-independent degradation of cellular components (e.g., old and dysfunctional mitochondria), which is partially responsible for cancer chemoresistance [39].

figure2
Tumor heterogeneity in metabolism. The degree of addiction to glucose or glutamate differs among various types of cancer cells. Tumor cells robustly importing glucose via the GLUT1 transporter are responsible for the high intensity of FDG-PET in the clinical settings. Cancer cells that express high levels of GLUT1 also induce a low-pH acidic tumor microenvironment, thereby increasing the invasive potential of tumors



figure3
Iatrogenic activation of CSCs with altered metabolic reprogramming. Non-CSCs are susceptible to chemotherapy and undergo apoptosis. Released PGE2 awakens the dormant CSCs localized in the niche. Proliferating CSCs are likely to exhibit additional metabolic reprogramming, concomitant with up-regulation of OXPHOS-related molecules

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Furthermore, malignant melanoma cells that survive and proliferate after treatment with mutant BRAF (V600E) inhibitor tend to exhibit relative dependence on mitochondrial metabolism [11]. Because BRAF suppresses oxidative phosphorylation (OXPHOS), MRD cells up-regulate proliferator-activated receptor-gamma coactivator-1 (PGC1-alpha). The BRAF (V600E)-MITF-PGC1-alpha axis promotes the biogenesis of mitochondria and causes BRAF-mutant melanoma cells to become addicted to mitochondrial metabolism [11]. Because histone H3 lysine 4 (H3K4)-demethylase JARID1B-highly expressing melanoma cells proliferate slowly and are highly dependent on mitochondrial metabolism [11, 40], chemotherapy-induced metabolic reprogramming in tumor tissue is likely to be responsible for the enrichment of CSCs in MRD.

Metabolic interaction driven by tumor heterogeneity
Initially, the concept of Warburg effect was believed to be confined to cancer cells. More recently, the emerging concept of the “reverse Warburg effect”, however, has attracted considerable attention. Tumor cell-derived reactive oxygen species (ROS) decrease the expression of caveolin-1 in cancer-associated fibroblasts (CAFs). CAFs are the major component of tumor stroma, and as such they express alpha-smooth muscle actin (alpha-SMA) and are widely recognized to drive tumor progression and metastasis [41]. Loss of caveolin-1 in CAFs results in elevated ROS levels, which in turn stabilize HIF-1 alpha [17, 42]. In brief, cancer cells create “pseudo-hypoxic” conditions for fibroblasts. Because the transcription factor HIF-1 alpha promotes glycolysis and provides tumor cells with lactate and glutamate, elevated production of ROS in cancer cells indirectly induces uptake of intermediate metabolites of the tricarboxylic acid (TCA) cycle in mitochondria. CAFs consume more glucose and secrete more lactate than normal fibroblasts. Furthermore, CAFs depend significantly on autophagy, and the activation of autophagy in tumor stroma leads to chemoresistance [18, 42] (Fig. 4).

figure4
Interaction of caveolin 1-deficient CAFs with tumor cells. Cancer cells induce a pseudo-hypoxic microenvironment rich in ROS derived from metabolic reprogramming. By contrast, CAFs negative for caveolin 1 provide tumor cells with lactate, pyruvate, and ketone bodies. Notably, although cancer cells depend heavily on mitochondrial metabolism, CAFs exhibit the Warburg effect and activation of the autophagic pathway

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As mentioned above, fibroblasts surrounding epithelial cancer cells undergo metabolic reprogramming resembling the phenotype associated with the Warburg effect. Metabolic symbiosis between epithelial cancer cells and CAFs requires that each cell express a different subtype of monocarboxylate transporter (MCT). Epithelial cancer cells express MCT1, which contributes to uptake of lactate provided by caveolin1-null CAFs expressing MCT4 [17, 43]. Tumor cells synthesize pyruvate from lactate, providing the TCA cycle with an intermediate metabolite. Notably, an extracellular space rich in lactate reflects acidic conditions, which in turn lead to the formation of pseudo-hypoxic conditions.

It should be emphasized, however, that this reverse Warburg effect is not necessarily present in all tumor types. Tumors expressing high levels of MCT4 or mesenchymal phenotype do not tend to exhibit the reverse Warburg phenomenon. Instead, cancer cells exhibit hierarchical metabolic heterogeneity: MCT4-expressing tumor cells perform glycolysis and secrete lactate via MCT4, whereas MCT1-expressing cells import lactate via MCT1 and perform OXPHOS. In addition, the amount of glucose uptake is lower in MCT1-positive cancer cells than in MCT4-positive cells [19, 20] (Fig. 5). This metabolic heterogeneity is referred to as metabolic symbiosis, and this kind of lactate shuttle is also observed between neurons and astrocytes in the normal brain tissue [44]. It is notable that normal and cancerous tissues share finely regulated mechanisms of metabolic symbiosis.


figure5
Metabolic symbiosis between oxidative/aerobic tumor cells and hypoxic/glycolytic cells. Tumor heterogeneity induces a lactate shuttle between hypoxic and oxidative cancer cells. While MCT4-positive hypoxic cells contribute to formation of an acidic microenvironment by aerobic glycolysis and secretion of lactate, MCT1-expressing oxidative cells utilize lactate as a substrate of the TCA cycle, and consequently exhibit stem-like characteristics. Notably, in contrast with MCT1-positive cancer cells, glucose uptake is robust in MCT4-expressing cells


Cancer stem-like cells in metabolic symbiosis
Importantly, well-oxygenated/aerobic cancer cells expressing high levels of MCT1 efficiently produce metabolic intermediates, as well as ATP, by utilizing lactate derived from hypoxic/glycolytic cells expressing high levels of MCT4. Redox stress is a major hallmark of cancer tissues that drives robust metabolism in adjacent proliferating MCT1-positive cancer cells, which are rich in mitochondria, mediated by the paracrine transfer of mitochondrial fuels such as lactate, pyruvate, and ketone bodies [19, 20] (Figs. 4 and 5).

Most importantly, genotoxic stress due to chemotherapy or irradiation, which increase ROS levels, promotes a CSC-like phenotype [45–47]. Because CSCs exhibit a rapidly proliferating and poorly differentiated phenotype, MCT1-positive cancer cells are likely to harbor stem-like phenotypes in heterogeneous populations of tumor cells. After all, activated mitochondrial metabolism produces enough energy not only for self-renewal by proliferation but also for invasion/distant metastasis, both of which are activated in CSCs.

Thus, the pharmacological blockage of MCT1 is useful for the treatment of cancer. MCT1 inhibition disrupts metabolic symbiosis, and MCT1-positive aerobic cancer cells can no longer uptake lactate [20], which suggests that MCT1-positive CSCs play a fundamental role in maintaining the hierarchy in tumor cellular society, in contrast to MCT4-positive cells (Fig. 5).

Acquisition of stem-like and malignant phenotypes with metabolic reprogramming
The cooperation of amino acid transporters is necessary for cancer cells to undergo metabolic reprogramming and maintain stem-like phenotypes. For example, triple-negative breast cancer (TNBC) cells, which lack estrogen receptor, progesterone receptor, and the tyrosine kinase receptor HER2, exhibit addiction to glutamine metabolism due to coordination between the xCT and ASCT2 amino acid transporters [48, 49]: xCT uptakes cystine in exchange for glutamine, for use in GSH synthesis [7], whereas ASCT2 uptakes glutamine in a collaborative manner [50]. Glutamine is simultaneously imported via ASCT2 transporter and exported in exchange for leucine via the LAT1/4F2 (CD98 heavy chain) antiporter [48]. The glutamine uptake pathway contributes to the synthesis of alpha-KG, promoting the TCA cycle in mitochondria, as well as glutamate, thereby promoting synthesis of nucleotides required for cellular proliferation [48] (Fig. 6). Thus, metabolic reprogramming, which is orchestrated by the elevated expression and interaction of amino acid transporters, contributes to the activation of glutamine metabolic reprogramming and protects tumor cells against accumulation of oxidative stress mediated by cystine metabolic reprogramming.

figure6
Metabolic reprogramming of amino acids due to coordinated transporters. ASCT2/LAT1 and xCT/CD98hc transporter complexes in tumor cells activate the mTORC1-SIRT4-GDH axis and glutathione synthesis, respectively. The former pathway promotes conversion of glutamate into alpha-KG, a substrate of the TCA cycle, whereas the latter pathway maintains redox status


Remarkably, circulating tumor cells (CTCs) that have undergone metabolic reprogramming provide themselves with a microenvironment that is favorable for colonization and distant metastasis. Recent work showed that CTCs derived from colon adenocarcinoma and positive for CD110, the thrombopoietin receptor, can home to the pre-metastatic niche and colonize metastatic hepatic tissue due to elevated lysine catabolism [51, 52]. Lysine degradation provides CD110-positive CTCs with glutamate and acetyl-CoA, which contributes to the synthesis of anti-oxidant GSH and p300-dependent LRP6 acetylation, respectively [52, 53]. This metabolic reprogramming promotes the metastatic potential of CTCs via a reduction in ROS levels, elevation of self-renewal potential, and activation of the Wnt/beta-catenin signal pathway [52]. Thus, CTCs resemble CSCs during the process of metastasis, at least in terms of the ‘education’ of the pre-metastatic niche. Most importantly, this metastatic phenotype is supported by lysine metabolic reprogramming.

A subpopulation of cancer cells that depend heavily on aerobic glycolysis robustly uptakes and consumes glucose, whereas another subpopulation engages in OXPHOS and glutaminolysis with activated mitochondrial metabolism. The efficiency of lactate production in the former (MCT4-positive) subpopulation is much higher than in the latter (MCT1-positive) subpopulation, which relies on OXPHOS and glutamine-derived TCA cycle in the mitochondria [54] (Fig. 5). Thus, tumor cells tend to decrease microenvironmental pH via elevated lactate secretion. The acidic tumor microenvironment induces expression of matrix metalloproteinases (MMPs), especially MMP-2 and MMP-9 [55]. Thus, metabolic reprogramming remarkably enhances the invasion and metastatic potentials of cancer cells.

Activation of glutamine metabolism driven by oncogene addiction
Mitochondria plays a much more important role in cancer metabolism than previously expected, and glutaminolysis is the most common metabolic pathway regulated in this organelle [56]. Glutaminolysis is the series of biochemical reactions by which glutamine is catabolized into downstream metabolites, e.g., alpha-ketoglutarate (alpha-KG) and glutamate. Via the TCA cycle, alpha-KG undergoes catabolism to malate, which is transported into the cytoplasm and converted to pyruvate, and then ultimately to lactate [22]. Mechanistically, mTORC1 signaling promotes glutamine anaplerosis via upregulation of glutamate dehydrogenase (GDH) [57]. SIRT4 is a mitochondrial-localized member of the sirtuin family of NAD-dependent enzymes that play fundamental roles in metabolism, stress response and longevity [58]. In regard to glutaminolysis, SIRT4 is a critical negative regulator for glutamine metabolism in mitochondria [58], which is down-regulated at the transcriptional level when the mTOR signaling pathway is activated [57]. Thus, mTOR inhibitors such as rapamycin are expected to block mTORC1-SIRT4-GDH axis, which is essential for glutaminolysis [57] (Fig. 6).

As mentioned above, tumor tissue consists of a cellular population that is heterogeneous in terms of dependency on the Warburg effect and mitochondrial metabolism. Relative to slow-cycling CSCs, proliferative cancer cells tend to take up a great deal of glutamine, as well as glucose, for the generation of metabolites [54]. Both aerobic glycolysis and glutaminolysis are frequently simultaneously activated in malignant cancer cells [36, 59]. Seemingly paradoxically, however, some cancer cell lines cannot survive and proliferate in the absence of glutamine, despite the fact that glutamine is a non-essential amino acids that can be synthesized from glucose [60]. Glutamine is a primary substrate for the TCA cycle and is required to maintain the redox state via the production of nicotinamide adenine dinucleotide phosphate (NADPH). Glutaminolysis enables cancer cells to reduce NADP+ to NADPH, a reaction that is catalyzed by malic enzymes. NADPH is a required electron donor for reductive steps in lipid synthesis, nucleotide metabolism, and maintenance of reduced GSH [21]. In this way, metabolic reprogramming of glutaminolysis enables cancer cells to regulate redox state.

Oncogenic c-Myc mediates elevation of glutaminolysis in cancer cells. c-Myc promotes both glutamine uptake and glutamine catabolism [61]. Because of c-Myc-mediated metabolic reprogramming, cancer cells tend to exhibit “glutamine addiction” [48, 61]. This is a typical example of metabolic reprogramming in cancer cells with oncogene-addiction [62, 63], suggesting a potential “Achilles’ heel” of tumor cells that are addicted to glutamine metabolism in manner that is mediated by c-Myc.

Therapeutic strategies targeting metabolic reprogramming
Drug repositioning (DR), screening for anti-cancer therapeutic effects of conventionally administered medications for non-malignant disorders, has attracted a great deal of attention because the safety and frequency of side effects of these medicines have been already proven [64]. Proton pump inhibitor (PPIs), for instance, are acid-activated pro-drugs that inhibit H/K-ATPase expressed in gastric parietal cells and are conventionally used for the treatment of gastric ulcer [65]. PPIs have exert synergistic effects on chemotherapy [66] by modulating the acidic microenvironment [67] or down-regulating microRNAs involved in chemotherapy resistance [68]. Other typical examples of DR include sulfasalazine [7, 8, 69], itraconazole [70, 71], terfenadine [72, 73], and simvastatin [74, 75] are described in Table 1. To address their anti-tumor therapeutic effects in clinical settings, all of those drugs are being tested in clinical trials or xenograft experiments.

Table 1 Typical examples of conventional drugs as anti-tumor agents
Full size table
Here, we will describe in detail the potential effects of metformin as an anti-cancer drug. DR has revealed, for example, that metformin, an oral drug widely used to treat type 2 diabetes mellitus (DM) [76], prevents tumor growth and development. A large number of retrospective clinical studies also show that metformin prevents carcinogenesis and improves clinical prognosis [77–79]. Metformin activates AMPK signal transduction, which not only decreases insulin resistance in type 2 DM [76] but also blocks AMPK-mediated mTOR activation even in CSCs [77]. mTOR signals are regulated by amino-acid transporters, characterized by the L-type amino acid transporter 1 (LAT1; SLC7A5) and the glutamine/amino acid transporter (ASCT2; SLC1A5) [80, 81], which is why the AMPK-mTOR axis functions as a sensor of dynamic change in the nutrient/growth factor microenvironment. In particular, leucine uptake via LAT1 activates the mTOR signal pathway [81, 82] leading to poor prognosis [83, 84]. Because EpCAM is a functional CSC marker that forms a complex with amino-acid transporters such as LAT1 [82, 85], it is reasonable that the LAT1 expression level would be positively correlated with poor prognosis [83, 84]. Therefore, the LKB1-AMPK-mTOR axis is orchestrated by amino-acid concentration in the tumor microenvironment, and this axis promotes metabolic reprogramming of cancer cells in response to the microenvironment.

Remarkably, recent investigations have revealed that this anti-type 2 DM drug suppresses ectonucleotide pyrophosphatase/phosphodiesterase family member 1 (ENPP1). Consequently, metformin can inhibit the generation of the subpopulation of cancer cells that express high levels of ABCG2, an ATP-binding cassette (ABC) transporter responsible for active drug efflux. Mechanistically, the cytosolic domain of ENPP1 is crucial for interaction with ABCG2 at the cellular membrane; thus ENPP1 contributes to drug resistance by promoting the stabilization of ABCG2 [86, 87]. In addition, metformin induces microRNA-27b-mediated suppression of ENPP1, which reduces chemoresistance and tumor seeding potential [86]. ENPP1 is widely accepted as a cause of insulin resistance in type 2 DM [88], emphasizing the significance of drug repositioning. Collectively, these observations indicate that this anti-DM agent is a promising means to attenuate the malignant behavior of cancer cells, much like other drugs conventionally administered for non-cancerous diseases.

Conclusions
The complex and dynamic metabolic reprogramming should be regarded as a reflection of the “robustness” of tumor cells against unfavorable conditions. Hyper-adaptation due to metabolic reprogramming of cancer cells is likely to give us a great opportunity to attack the “shatter point” in heterogeneous tumor tissue. DR enables us to identify “silver bullets” for the treatment of tumor tissues in metabolically heterogeneous cell populations. To facilitate development of novel therapeutic strategies, the synergistic effects of repositioned drugs with conventional anti-cancer agents should be evaluated in clinical trials in the near future.

Abbreviations
alpha-KG:
Alpha-ketoglutarate

AMPK:
Adenosine monophosphate-activated protein kinase

CAFs:
Cancer-associated fibroblasts

CSC:
Cancer stem-like cell

CTC:
Circulating tumor cells

DM:
Diabetes mellitus

DR:
Drug-repositioning

ECM:
Extracellular matrix

ENPP1:
Ectonucleotide pyrophosphatase/phosphodiesterase family member 1

GDH:
Glutamate dehydrogenase

HIF-1 alpha:
Hypoxic inducible factor-1 alpha

LAT1:
L-type amino acid transporter 1

MCT:
Monocarboxylate transporter

MMP:
Matrix metalloproteinases

MRD:
Minimal residual disease

mTOR:
Mammalian target of rapamycin

NADPH:
Nicotinamide adenine dinucleotide phosphate

OXPHOS:
Oxidative phosphorylation

ROS:
Reactive oxygen species

TCA:
Tricarboxylic acid

Metabolic reprogramming: the emerging concept and associated therapeutic strategies | Journal of Experimental & Clinical Cancer Research | Full Text
https://jeccr.biomedcentral.com/articles/10.1186/s13046-015-0221-y