Abstract
Purpose of Review:
In an attempt to identify potential new therapeutic targets, efforts to describe the metabolic features unique to cancer cells are increasingly being reported. While current standard of care regimens for several pediatric malignancies incorporate agents that target tumor metabolism, these drugs have been part of the therapeutic landscape for decades. More recent research has focused on the identification and targeting of new metabolic vulnerabilities in pediatric cancers. The purpose of this review is to describe the most recent translational findings in the metabolic targeting of pediatric malignancies.
Recent Findings:
Across multiple pediatric cancer types, dependencies on a number of key metabolic pathways have emerged through study of patient tissue samples and preclinical modeling. Among the potentially targetable vulnerabilities are glucose metabolism via glycolysis, oxidative phosphorylation, amino acid and polyamine metabolism, and NAD+ metabolism. While few agents have yet to move forward into clinical trials for pediatric cancer patients, the robust and promising preclinical data that has been generated suggests that future clinical trials should rationally test metabolically-targeted agents for relevant disease populations.
Summary:
Recent advances in our understanding of the metabolic dependencies of pediatric cancers represent a source of potential new therapeutic opportunities for these diseases.
Keywords: cancer metabolism, pediatric cancer, glycolysis, oxidative phosphorylation, amino acid metabolism
INTRODUCTION
Proliferating cancer cells exhibit significantly different metabolic needs compared to normal differentiated cells, including rapid ATP production to maintain energy status, increased macromolecular biosynthesis, and tightened maintenance of appropriate cellular redox status (1, 2). To meet the increased demands necessary to support cancer cell survival and proliferation, cellular metabolism is altered through changes in signaling pathways that are affected by genetic and microenvironmental factors (1–3). Given their importance across many different cancer types, altered cellular metabolism has been recognized as a hallmark of cancer (4, 5).
Research into how cancer cell metabolism differs from that of normal cells may uncover therapeutic opportunities to exploit the differential metabolic dependencies of cancer cells while potentially sparing normal cells from toxicity (6). In the field of pediatric oncology, therapies targeting cancer metabolism have been in use for decades. The first report of a metabolic inhibitor demonstrating clinical activity was published in 1948 by the pediatric pathologist Sidney Farber, who reported that use of aminopterin, a folate analog that competitively inhibits dihydrofolate reductase (DHFR), resulted in temporary remissions in children with leukemia (7, 8). Mechanistically, folate analogs deplete tetrahydrofolate, impairing thymidylate production and impeding DNA synthesis, which is required for rapidly dividing cancer cells (9). Even today, DHFR inhibitors like methotrexate are currently incorporated into standard first-line treatments for pediatric acute lymphoblastic leukemia (ALL) (10) and osteosarcoma (11), and ongoing research has revealed that the metabolic consequences of methotrexate may also include effects on glucose metabolism and altered response to oxidative stress (12).
Following the identification of folate analogs as anticancer agents, analogs of purine, pyrimidine, thymidine, and other nucleosides were developed, forming the class of agents known as antimetabolites (13). Several antimetabolites, such as 6-mercaptopurine and cytarabine, have endured in standard regimens to treat ALL (14) and acute myeloid leukemia (AML) in children (15). In addition to antimetabolites, asparaginase is another standard of care agent targeting cancer metabolism for pediatric patients. Asparaginase exploits the lack of asparagine synthetase activity in ALL cells by depleting necessary serum asparagine (16, 17). While asparaginase remains an integral part of the therapeutic backbone for pediatric ALL (14), research efforts to enhance its efficacy in ALL (18–20) reduce its associated toxicity (21), and identify other pediatric malignancies that share asparagine dependency (22–24) are ongoing.
Several recent studies have focused on characterizing the metabolic profiles of tumor cells, determining the effects of genetic drivers on tumor metabolism, and gaining new insights into the unique metabolic dependencies of pediatric cancer cells with the goal of improving upon current therapies. The purpose of this review is to describe the most recent translational findings in metabolic targeting of pediatric cancers.
GLYCOLYSIS
Among the earliest insights into the metabolic differences between normal and cancer cells was the observation by Otto Warburg that many cancer cells exhibit an increased dependence on aerobic glycolysis, preferentially catalyzing the conversion of glucose to lactate, as opposed to carbon dioxide, in the presence of oxygen (25). Dependence on glycolysis is frequently a consequence of genetic alterations which result in overexpression or silencing of key enzymes along the glycolytic pathway (26).
Recent work has shown that despite a relatively low mutational burden, numerous pediatric cancers have altered expression of key glycolytic enzymes, suggestive of an increased dependence on glycolysis. Specifically, expression of hexokinase 2 (HK2), an isoform of the first enzyme of glycolysis that converts glucose to glucose-6-phosphate, was found to be increased in clinical samples and preclinical models of pediatric malignancies. These included the SHH subtype of medulloblastoma (27, 28) and diffuse large B-cell lymphoma (DLBCL), where high HK2 expression correlated with poor prognosis (29). Similarly, in osteosarcoma tissue samples, elevated HK2 expression was correlated with Ki-67 expression (30), and was directly regulated by NF-KB (31).
In addition, high expression of several isoforms of lactate dehydrogenase (LDH), the terminal enzyme in glycolysis that converts pyruvate to lactate, has been described. High LDHA expression has been linked to poor prognoses in neuroblastoma, where it correlated with MYCN-amplification (32), and in medulloblastoma, where it was associated with two of the genetically-defined subtypes, including the aggressive group 3 subtype which portends a very poor prognosis (33). Increased expression of LDHB was also observed in embryonal hepatoblastoma cell lines, as compared to normal liver and fetal hepatoblastoma cell lines (34). In preclinical models of Ewing sarcoma, the driver oncogenic fusion protein EWS-FLI1 was found to regulate a pro-glycolytic phenotype (35), specifically through direct upregulation of LDHA (36).
Altered expression of transporters of the substrates and products of glycolysis has also been identified in several pediatric cancers. Glucose transporters, such as GLUT1, GLUT3, and GLUT4 have been found to be more highly expressed in tumor samples of medulloblastoma (Bhatia 2012) aggressive neuroblastoma (37), Wilms’ tumor (38), and embryonal hepatoblastoma (34). Loss of expression of the monocarboxylate transporter 4 (MCT4), which functions to efflux lactate in highly glycolytic tissues was noted in a majority of Burkitt lymphoma and DLBCL patient samples, suggesting that these cancers may be more dependent on compensatory mechanisms of lactate transport (39).
From a translational perspective, recent preclinical studies investigating the utility of inhibiting aspects of glycolysis as a strategy for treating pediatric cancers suggest that there may be a role for this approach. Inhibition of HK with 2-Deoxy-D-glucose (2-DG) resulted in apoptotic death in Ewing sarcoma (40), alveolar rhabdomyosarcoma (41), and embryonal hepatoblastoma (34) cell lines. In medulloblastoma, genetic depletion of HK2 abrogated the aggressive phenotype of these cells in vivo (42); in osteosarcoma, genetic depletion of HK2 induced apoptosis in some, but not all preclinical models (30, 31). Genetic depletion of LDHA was effective in inhibiting the growth of preclinical models of neuroblastoma (32) and Ewing sarcoma, which was also sensitive to pharmacological targeting of LDH (36). Pharmacological targeting of glycolysis in medulloblastoma and neuroblastoma using other glycolytic inhibitors reduced cellular viability (33, 43) through potentially distinct mechanisms of growth inhibition. In Burkitt lymphoma and DLBCL models with low MCT4 expression, targeting the compensatory monocarboxylate transporter 1 (MCT1) with a small molecule inhibitor profoundly reduced proliferation in vitro and in vivo (39). Additionally, a compensatory increase in oxidative phosphorylation (OXPHOS) has been reported with glycolytic inhibition in numerous preclinical studies, suggesting that resistance may be mediated through this mechanism (33, 36, 39).
Finally, several studies have investigated the role of glycolysis in relation to resistance to standard therapies. In models of pediatric AML, resistance to adriamycin was associated with increased glycolysis and HK2 expression in patient samples. Notably, use of 2-DG in resistant models of this disease restored sensitivity to chemotherapy (44). Similarly, acquired resistance to chemotherapy plus rituximab in DLBCL models was associated with increased HK2 expression and could be overcome by the HK inhibitors 2-DG or lonidamine (29). In pediatric ALL models, resistance to glucocorticoid agents could be mitigated by the addition of 2-DG (45), and in Ewing sarcoma cell lines, the addition of 2-DG to standard chemotherapy drugs enhanced their antiproliferative effect (40). Taken together, these studies suggest there may be a role for targeting glycolysis through inhibition of key enzymes or substrate transporters in a subset of pediatric cancers. While clinical investigation of 2-DG has been conducted for adult patients with cancer (46) and a trial using an MCT1 inhibitor is currently open for adults (NCT01791595), clinical testing of these agents in children has not yet been performed.
OXIDATIVE PHOSPHORYLATION
More recent insights into tumor metabolism have revealed that in addition to increased glycolysis, mitochondrial metabolism also plays a major role in tumor growth and survival (47). As a result, there have been increased efforts to understand tumor-specific dependencies on the tricarboxylic acid (TCA) cycle and to identify targetable vulnerabilities in this pathway in pediatric cancers. Recent studies indicate that mitochondrial number and function differed from the surrounding normal tissue in Wilms’ tumor (48), neuroblastoma (49), and pediatric brain tumors like high grade glioma (HGG), in which an aggressive phenotype may be partly related to a relatively low mitochondrial DNA (mtDNA) copy number (50–52).
Most preclinical studies in pediatric malignancies have targeted OXPHOS with metformin, a widely prescribed type 2 diabetes medication that can inhibit Complex I of the mitochondrial respiratory chain (53). Metformin treatment was associated with cancer cell growth inhibition in preclinical models of several pediatric solid tumors, including Ewing sarcoma (40), rhabdomyosarcoma (54), neuroblastoma (55–57), HGG (50) and osteosarcoma, in which antitumor effects against primary tumor cells (58) and microenvironmental factors (59) were reported. In preclinical models of pediatric hematological malignancies, including FLT3-ITD AML (60) and ALL (61), metformin negatively impacted cellular viability. In addition to metformin, other hypoglycemic agents such as the thiazolidinediones had activity against pediatric cancers, including neuroblastoma (56). CCI-006, a non-hypoglycemic agent that induces mitochondrial depolarization, had potent activity against MLL-rearranged leukemias (62), as did genetic depletion of mtDNA in HGG (50).
Another potential target relevant to OXPHOS regulation is pyruvate dehydrogenase kinase 1 (PDK1), which catalyzes the phosphorylation and inactivation of pyruvate dehydrogenase (PDH), thus inhibiting the conversion of pyruvate into acetyl-CoA through the TCA cycle. PDK1 was found to be overexpressed in retinoblastoma (63). Functionally, inhibition of PDK1, which permits more entry of pyruvate into the TCA cycle, resulted in decreased cell growth in models of AML (64) and retinoblastoma, where it also sensitized cells to the effects of chemotherapy (63). Inhibition of OXPHOS also improved responses to chemotherapy in osteosarcoma (58). Another combination approach that has been studied in Ewing sarcoma (40), HGG (50), and AML (60) involved dual targeting of OXPHOS and glycolysis, which addresses the reported compensatory induction of one pathway upon inhibition of the other (33, 36, 40, 60). Combining metformin with other DNA damaging agents such as radiation in HGG (50) or molecularly targeted therapies in neuroblastoma or AML (55, 60) was also efficacious preclinically.
Unlike glycolytic inhibitors, OXPHOS inhibitors such as metformin (65), DCA (66, 67), and the PDH inhibitor CPI-613 (68–71), remain in the clinic for testing in adult cancer patients. Notably, a recently completed phase 1 study for pediatric patients with relapsed ALL investigated the addition of metformin to a 28-day pre-transplant induction regimen, concluding that the combination was safe and reporting pharmacodynamic evidence of on-target metformin activity in blood cells (72). An additional phase 1 study (NCT01528046) combining metformin with chemotherapy for pediatric patients with relapsed solid tumors is ongoing.
AMINO ACID METABOLISM
Major differences exist in the uptake and metabolism of amino acids in tumors relative to normal tissues. Amino acids play key roles in cancer cell proliferation, as they provide precursors for macromolecular biosynthesis, control redox status and antioxidant systems, and serve as substrates for post-translational and epigenetic modifications. Consequently, there is significant interest in understanding and targeting amino acid metabolism for cancer therapy (73, 74).
Glutamine Metabolism
Glutamine, the most abundant amino acid in serum, is metabolized in multiple pathways supporting cellular proliferation (2, 75–77). Several pediatric cancers display altered glutamine metabolism and increased dependence on glutamine. Specifically, an enriched glutaminolysis gene signature associated with MYCN-amplification was identified in neuroblastoma patient tumor samples (78), and unbiased metabolic profiling of atypical teratoid/rhabdoid tumors (AT/RT) revealed increased glutamine metabolism in high versus low MYC-expressing patient-derived cell lines (79). In medulloblastoma, glutamine addiction was identified in a subset of tumors of the non-Wnt subtypes where it was essential for sustained cell growth and proliferation (80). Rhabdomyosarcoma and Ewing sarcoma cell lines were also shown to be dependent on glutamine for maximal proliferation and were able to increase the expression of glutamine synthetase, which drives de novo glutamine synthesis, to overcome glutamine withdrawal. In Ewing sarcoma tumors, high glutamine synthetase expression correlated with worse survival (81).
Several recent preclinical studies have reported the effects of targeting glutamine metabolism in pediatric cancer models. In AT/RT, both glutamine restriction and treatment with the glutamine analog 6-diazo-5-oxo-L-norleucine (DON) selectively affected high-MYC expressing cell lines, slowing proliferation in vitro and in vivo, and extending survival when combined with carboplatin in orthotopic mouse models (79). In medulloblastoma, dietary glutamine restriction increased survival in a mouse xenograft model and synergized with cisplatin treatment (80). Mechanistically, both DON treatment and glutamine restriction resulted in reduced levels of the antioxidant glutathione (GSH), and increased levels of reactive oxygen species (ROS). This relationship between glutamine depletion and increased oxidative stress in glutamine-dependent cells has also been described in osteosarcoma models (82). Similarly, the glutaminase inhibitor CB-839, which impairs conversion of glutamine to glutamate, decreased GSH production in AML, resulting in accumulation of ROS and apoptosis. Glutaminase inhibition also sensitized AML and ALL cells to redox-targeted agents in vitro and in vivo (83). In rhabdomyosarcoma and Ewing sarcoma, inhibition of glutamine synthetase with methionine sulfoximine selectively abolished the ability of glutamine-deprived cells to proliferate. Mechanistically, glutamine metabolism supported sarcoma nucleotide biosynthesis and mitochondrial bioenergetics. Pharmacological and genetic inhibition of glutamine synthetase significantly reduced Ewing sarcoma orthotopic xenograft tumor growth (81). In the clinic, multiple studies of CB-839 are ongoing, including one phase 1 trial (NCT03528642) that includes adolescent patients with IDH-mutant brain tumors.
Serine, Glycine and One-carbon Metabolism
Serine, glycine, and downstream one-carbon metabolism (involving the folate and methionine cycles) support several biological processes that are crucial for the growth and survival of proliferating cells. Overexpression of enzymes in these pathways has been linked to more aggressive cancer phenotypes (84–86). Several recent studies have indicated that altered serine-glycine-one-carbon metabolism may play an essential role in certain pediatric cancers. In neuroblastoma, high expression of a serine-glycine-one-carbon metabolism gene signature (87) or of glycine decarboxylase (GLDC), the enzyme which catalyzes glycine breakdown producing the one-carbon unit 5,10-methylene-tetrahydrofolate (88), was identified in MYCN-amplified patient tumor samples and was associated with advanced disease stage and poor prognosis. Both studies demonstrated that MYC transcriptionally activated targets in the serine-glycine-one-carbon metabolism pathway. In Ewing sarcoma call lines, several components of the serine-glycine synthesis pathway were also found to be direct transcriptional targets of EWS-FLI1. These genes were also found to be highly expressed in Ewing sarcoma patient tumors, and their expression was correlated with high-risk disease and poor survival (35, 89, 90).
Preclinical studies targeting serine-glycine-one-carbon metabolism have shown promise as a potential therapeutic strategy for pediatric malignancies and indicate that perturbation of these pathways impacts multiple other metabolic processes in pediatric cancer models. In AML models, knockdown of methylenetetrahydrofolate dehydrogenase (MTHFD2), which is essential for mitochondrial one-carbon folate metabolism, decreased cell growth in culture and prolonged survival in murine models. Mechanistically, loss of MTHFD2 increased glycine dependence and depleted TCA cycle intermediates in these models (91). In MYCN-amplified neuroblastoma cell lines, GLDC knockdown inhibited cellular proliferation and tumorigenicity by disrupting glycolysis, the TCA cycle, lipid synthesis, and purine metabolism (88). MYCN-amplified neuroblastoma cell lines were also susceptible to pharmacological inhibition of 3-phosphoglycerate dehydrogenase (PHGDH), the enzyme that catalyzes the first committed step in de novo serine synthesis, using the small-molecule NCT-503, which selectively decreased proliferation and xenograft tumor growth (87). Similarly, in several studies using Ewing sarcoma models, both pharmacological and genetic inhibition of PHGDH decreased proliferation and induced apoptosis in cell lines and xenografts through induction of ROS and DNA damage (35, 89, 90). While there are no inhibitors of serine or glycine metabolism currently being tested the clinic, these data suggest that if and when they enter clinical development, there may be a role for targeting these pathways in certain pediatric malignancies.
Arginine Metabolism
Arginine represents another critical amino acid for cancer cell survival. Arginine is produced via argininosuccinate synthetase 1 (ASS1), the rate-limiting enzyme in arginine synthesis. Immunohistochemical analysis of primary sarcomas including pediatric histologies such as malignant peripheral nerve sheath tumor, synovial sarcoma, rhabdomyosarcoma, desmoplastic small round cell tumor, osteosarcoma, and Ewing sarcoma, revealed that >85% of samples had undetectable or very low expression of ASS1, rendering cells dependent on extracellular arginine. Consequently, arginine deprivation therapy with pegylated arginine deiminase (ADI-PEG20) resulted in growth arrest in ASS1-deficient models of osteosarcoma, Ewing sarcoma, synovial sarcoma, and alveolar soft part sarcoma (92). Arginine has also been found to be an important metabolic target specifically in EVI1-positive AML, where suppression of arginine-creatine metabolism by genetic or pharmacological means selectively decreased cellular viability and prolonged survival in mouse models (93). In preclinical models of osteosarcoma, Ewing sarcoma, synovial sarcoma, and rhabdomyosarcoma, efficacy was noted using ADI-PEG20 plus gemcitabine and docetaxel, and this combination is currently being evaluated in a phase II trial (NCT03449901) for patients with soft tissue sarcoma, including adolescents (94). Similarly, arginine depletion with BCT-100 (pegylated recombinant human arginase) treatment was effective against in vitro and in vivo models of ALL, and is currently being evaluated in a phase I/II study (NCT03455140) in children and young adults with relapsed/refractory leukemia, neuroblastoma, sarcoma, and HGG (95).
Polyamine Metabolism
The amino acid-derived polyamines are involved in many fundamental processes related to cell growth and survival. Polyamine metabolism is frequently dysregulated in cancer, where elevated polyamine levels can affect transformation and tumor progression. Intracellular polyamine levels are maintained through a highly-regulated metabolic pathway and import/export systems. Arginase produces the non-proteinogenic amino acid ornithine from arginine. In turn, ornithine decarboxylase (ODC), the first, rate-limiting enzyme in polyamine synthesis, produces the diamine putrescine, which is the precursor of the polyamines spermidine and spermine (96, 97).
Several studies have suggested a critical role for polyamine metabolism in pediatric cancers. In neuroblastoma patient tumors, elevated mRNA levels of ODC correlated with poor prognosis (98). Further, high expression of each polyamine biosynthetic gene and low expression of genes driving polyamine catabolism correlated with poor event-free and overall survival and were associated with MYCN-amplification and unfavorable tumor stage in neuroblastoma. MYCN directly increased polyamine synthesis and promoted neuroblastoma cell proliferation by regulating the key polyamine transporter SLC3A2 in neuroblastoma, along with other regulatory components of polyamine metabolism (99).
From a translational perspective, several preclinical and clinical studies have investigated the utility of targeting polyamine metabolism in pediatric cancer. In osteosarcoma, the ODC inhibitor difluoromethylornithine (DFMO) reduced intracellular polyamine levels, induced differentiation, and caused growth suppression in vitro (100). In a number of studies in preclinical models of neuroblastoma, single-agent and combination treatment approaches using DFMO plus chemotherapy or other agents targeting polyamine homeostasis have been shown to effectively inhibit cellular proliferation and tumor growth (98, 99, 101, 102). Additionally, there are ongoing research efforts focused on defining the interactions between polyamine homeostasis and other metabolic pathways in neuroblastoma (103).
Targeting polyamine synthesis with DFMO has been evaluated in several early phase clinical trials in children with neuroblastoma where it was shown to be safe (104, 105). Clinical studies to further determine the efficacy of DFMO in this population and preclinical studies to optimize its use are ongoing (106, 107).
NICOTINAMIDE ADENINE DINUCLEOTIDE (NAD+) METABOLISM
For some cancer cells, increased requirements for NAD+ result in altered dependency on NAD+ production pathways to maintain efficient growth and survival (108). Mounting evidence that depletion of NAD+ may inhibit cellular proliferation in some malignancies has led to the development of therapeutics targeting the NAD+ production enzyme nicotinamide phosphoribosyltransferase (NAMPT) (109). Ewing sarcoma has emerged as a particularly sensitive tumor type to NAMPT inhibitors which, when applied to cells, resulted in NAD+ depletion, metabolic collapse, impaired DNA synthesis, increased DNA damage, and cell death in vitro and in vivo. NAMPT inhibitor-sensitivity in Ewing sarcoma has been linked to several factors, including increased reliance on the NAD+-dependent enzyme poly (ADP-ribose) polymerase (PARP) as well as EWS-FLI1-mediated dependency on NAD+ (110, 111).
In addition to Ewing sarcoma, recent insights have revealed that other pediatric cancers may also be susceptible to NAMPT inhibition. Preclinical models of pediatric hematologic malignancies, including B- and T-cell leukemias (112, 113), and AML (114, 115) underwent growth inhibition upon treatment with single agent NAMPT inhibitors. Models of pediatric HGG, including diffuse pontine gliomas (DIPG) were also sensitive to inhibition of NAMPT, which may be mediated by genetic silencing of compensatory enzymes (116).
Several combination therapies using NAMPT inhibitors have been identified as active in preclinical models of pediatric cancers and represent potential future regimens for clinical testing. These include combinations with PARP inhibitors in Ewing sarcoma (111), and etoposide in T-cell leukemia (112). In addition, Vacor, a rodenticide that has recently been found to have dual inhibitory activity against NAMPT and nicotinamide mononucleotide adenylyltransferase 2 (NMNAT2), a compensatory enzyme in the biosynthetic NAD+ pathway, was noted to be active against NMNAT2-expressing neuroblastoma cells (117). While there are a number of completed (118, 119) and ongoing studies testing various NAMPT inhibitors in adult cancer patients, a pediatric trial has yet to be initiated.
ADDITIONAL METABOLIC PATHWAYS
In addition to the pathways already described, several other potential metabolic vulnerabilities have been defined in various pediatric cancers. These include reports of metabolic phenotypes that differ from untransformed cells due to the influence of a particular oncogenic driver such as EWS-FLI1 (35), RAS (22), or MYC (120–124), mutations of metabolic enzymes (122, 125–129), or factors based on tissue of origin (130), or microenvironmental conditions (131, 132), as well as alterations in specific pathways such as lipid synthesis (133) and maintenance of antioxidant homeostasis(134–137).
CONCLUSIONS
It is evident that much like the metabolic landscape that has been described in adult cancers, pediatric cancers share some common metabolic vulnerabilities across subtypes. As preclinical evidence and the translational potential of targeting these pathways grows, efforts should be made to formally test these interventions in the setting of clinical trials for children with these cancers.
KEY POINTS.
The understanding that the metabolic needs of cancer cells are significantly different from those of normal cells has spurred an increase in research efforts to identify metabolic vulnerabilities specific to pediatric malignancies.
Across multiple pediatric cancer types, a number of dependencies in key metabolic pathways, including glycolysis, oxidative phosphorylation, and amino acid, polyamine, and NAD+ metabolism have recently been identified.
These promising preclinical findings represent opportunities for potential new therapeutic interventions for children with cancer and suggest that future clinical trials should rationally test metabolically-targeted agents for relevant pediatric cancer populations.
ACKNOWLEDGEMENTS
None.
FINANCIAL SUPPORT AND SPONSORSHIP
The authors are supported by grants from the Intramural Research Program of the National Institutes of Health, the National Cancer Institute, and the Center for Cancer Research.
Footnotes
CONFLICTS OF INTEREST
None.
REFERENCES AND RECOMMENDED READING
- 1.Cairns RA, Harris IS, Mak TW. Regulation of cancer cell metabolism. Nat Rev Cancer 2011; 11:85–95. [DOI] [PubMed] [Google Scholar]
- 2.Vander Heiden MG. Targeting cancer metabolism: a therapeutic window opens. Nat Rev Drug Discov 2011; 10:671–84. [DOI] [PubMed] [Google Scholar]
- 3.Boroughs LK, DeBerardinis RJ. Metabolic pathways promoting cancer cell survival and growth. Nat Cell Biol 2015; 17:351–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell 2011; 144:646–74. [DOI] [PubMed] [Google Scholar]
- 5.DeBerardinis RJ, Chandel NS. Fundamentals of cancer metabolism. Sci Adv 2016; 2:e1600200. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Zhao Y, Liu H, Riker AI, et al. Emerging metabolic targets in cancer therapy. Front Biosci (Landmark Ed) 2011; 16:1844–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Farber S, Diamond LK. Temporary remissions in acute leukemia in children produced by folic acid antagonist, 4-aminopteroyl-glutamic acid. N Engl J Med 1948; 238:787–93. [DOI] [PubMed] [Google Scholar]
- 8.Farber S Some observations on the effect of folic acid antagonists on acute leukemia and other forms of incurable cancer. Blood 1949; 4:160–7. [PubMed] [Google Scholar]
- 9.Raimondi MV, Randazzo O, La Franca M, et al. DHFR Inhibitors: Reading the Past for Discovering Novel Anticancer Agents. Molecules 2019; 24: [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Kato M, Manabe A. Treatment and biology of pediatric acute lymphoblastic leukemia. Pediatr Int 2018; 60:4–12. [DOI] [PubMed] [Google Scholar]
- 11.Harrison DJ, Geller DS, Gill JD, et al. Current and future therapeutic approaches for osteosarcoma. Expert Rev Anticancer Ther 2018; 18:39–50. [DOI] [PubMed] [Google Scholar]
- 12.Hess JA, Khasawneh MK. Cancer metabolism and oxidative stress: Insights into carcinogenesis and chemotherapy via the non-dihydrofolate reductase effects of methotrexate. BBA Clin 2015; 3:152–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Luengo A, Gui DY, Vander Heiden MG. Targeting Metabolism for Cancer Therapy. Cell Chem Biol 2017; 24:1161–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Pui CH, Yang JJ, Hunger SP, et al. Childhood Acute Lymphoblastic Leukemia: Progress Through Collaboration. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2015; 33:2938–48. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Zwaan CM, Kolb EA, Reinhardt D, et al. Collaborative Efforts Driving Progress in Pediatric Acute Myeloid Leukemia. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2015; 33:2949–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Egler RA, Ahuja SP, Matloub Y. L-asparaginase in the treatment of patients with acute lymphoblastic leukemia. J Pharmacol Pharmacother 2016; 7:62–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Marini BL, Perissinotti AJ, Bixby DL, et al. Catalyzing improvements in ALL therapy with asparaginase. Blood Rev 2017; 31:328–38. [DOI] [PubMed] [Google Scholar]
- 18.Hinze L, Pfirrmann M, Karim S, et al. Synthetic Lethality of Wnt Pathway Activation and Asparaginase in Drug-Resistant Acute Leukemias. Cancer Cell 2019; 35:664–76 e7. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■■ This study identifies a synthetic letal interaction between Wnt activation and asparaginase and provides a rationale to combine asparaginase with pharmacologic GSK3α inhibition in leukemia.
- 19.Serravalle S, Bertuccio SN, Astolfi A, et al. Synergistic Cytotoxic Effect of L-Asparaginase Combined with Decitabine as a Demethylating Agent in Pediatric T-ALL, with Specific Epigenetic Signature. Biomed Res Int 2016; 2016:1985750. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Hermanova I, Arruabarrena-Aristorena A, Valis K, et al. Pharmacological inhibition of fatty-acid oxidation synergistically enhances the effect of l-asparaginase in childhood ALL cells. Leukemia 2016; 30:209–18. [DOI] [PubMed] [Google Scholar]
- 21.Nguyen HA, Su Y, Zhang JY, et al. A Novel l-Asparaginase with low l-Glutaminase Coactivity Is Highly Efficacious against Both T- and B-cell Acute Lymphoblastic Leukemias In Vivo. Cancer Res 2018; 78:1549–60. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■ This study describes novel variants of L-asparaginase with reduced glutaminase activity, a common coactivity of FDA-approved L-asparaginases which may cause many of the side effects of conventional L-asparaginase. The new variants were efficacious against T- and B-cell ALL, while displaying reduced acute toxicity.
- 22.Hettmer S, Schinzel AC, Tchessalova D, et al. Functional genomic screening reveals asparagine dependence as a metabolic vulnerability in sarcoma. Elife 2015; 4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Bertuccio SN, Serravalle S, Astolfi A, et al. Identification of a cytogenetic and molecular subgroup of acute myeloid leukemias showing sensitivity to L-Asparaginase. Oncotarget 2017; 8:109915–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Panosyan EH, Wang Y, Xia P, et al. Asparagine depletion potentiates the cytotoxic effect of chemotherapy against brain tumors. Mol Cancer Res 2014; 12:694–702. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Warburg O, Wind F, Negelein E. The Metabolism of Tumors in the Body. J Gen Physiol 1927; 8:519–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Bi J, Wu S, Zhang W, Mischel PS. Targeting cancer’s metabolic co-dependencies: A landscape shaped by genotype and tissue context. Biochim Biophys Acta Rev Cancer 2018; 1870:76–87. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Bhatia B, Potts CR, Guldal C, et al. Hedgehog-mediated regulation of PPARgamma controls metabolic patterns in neural precursors and shh-driven medulloblastoma. Acta Neuropathol 2012; 123:587–600. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Tech K, Gershon TR. Energy metabolism in neurodevelopment and medulloblastoma. Transl Pediatr 2015; 4:12–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Gu JJ, Singh A, Xue K, et al. Up-regulation of hexokinase II contributes to rituximab-chemotherapy resistance and is a clinically relevant target for therapeutic development. Oncotarget 2018; 9:4020–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Zhuo B, Li Y, Li Z, et al. PI3K/Akt signaling mediated Hexokinase-2 expression inhibits cell apoptosis and promotes tumor growth in pediatric osteosarcoma. Biochem Biophys Res Commun 2015; 464:401–6. [DOI] [PubMed] [Google Scholar]
- 31.Londhe P, Yu PY, Ijiri Y, et al. Classical NF-kappaB Metabolically Reprograms Sarcoma Cells Through Regulation of Hexokinase 2. Front Oncol 2018; 8:104. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■ This study reports on the role of HK2 in osteosarcoma and rhabdomyosarcoma cell lines.
- 32.Dorneburg C, Fischer M, Barth TFE, et al. LDHA in Neuroblastoma Is Associated with Poor Outcome and Its Depletion Decreases Neuroblastoma Growth Independent of Aerobic Glycolysis. Clin Cancer Res 2018; 24:5772–83. [DOI] [PubMed] [Google Scholar]; ■ This study describes the prognostic significance of LDHA and LDHB expression in neuroblastoma.
- 33.Valvona CJ, Fillmore HL. Oxamate, but Not Selective Targeting of LDH-A, Inhibits Medulloblastoma Cell Glycolysis, Growth and Motility. Brain Sci 2018; 8, 56. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■ This study identifies the medullobastoma subgroups Wnt and group 3 as associated with LDHA overexpression and susceptible to glycolytic inhibition.
- 34.Crippa S, Ancey PB, Vazquez J, et al. Mutant CTNNB1 and histological heterogeneity define metabolic subtypes of hepatoblastoma. EMBO Mol Med 2017; 9:1589–604. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Tanner JM, Bensard C, Wei P, et al. EWS/FLI is a Master Regulator of Metabolic Reprogramming in Ewing Sarcoma. Mol Cancer Res 2017; 15:1517–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Yeung C, Gibson AE, Issaq SH, et al. Targeting Glycolysis through Inhibition of Lactate Dehydrogenase Impairs Tumor Growth in Preclinical Models of Ewing Sarcoma. Cancer Res 2019; 79:5060–73. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■■ This study highlights the importance of EWS-FLI1 regulation of LDHA in the glycolytic phenotype of Ewing sarcoma and describes pharmacological targeting of LDH in in vivo models of this cancer.
- 37.Matsushita K, Uchida K, Saigusa S, et al. Glycolysis inhibitors as a potential therapeutic option to treat aggressive neuroblastoma expressing GLUT1. J Pediatr Surg 2012; 47:1323–30. [DOI] [PubMed] [Google Scholar]
- 38.Rakheja D, Khokhar S, Mitui M, Cost NG. Immunohistochemical expression of GLUT1 and its correlation with unfavorable histology and TP53 codon 72 polymorphism in Wilms tumors. Pediatr Dev Pathol 2012; 15:286–92. [DOI] [PubMed] [Google Scholar]
- 39.Noble RA, Bell N, Blair H, et al. Inhibition of monocarboxyate transporter 1 by AZD3965 as a novel therapeutic approach for diffuse large B-cell lymphoma and Burkitt lymphoma. Haematologica 2017; 102:1247–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Dasgupta A, Trucco M, Rainusso N, et al. Metabolic modulation of Ewing sarcoma cells inhibits tumor growth and stem cell properties. Oncotarget 2017; 8:77292–308. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Ramirez-Peinado S, Alcazar-Limones F, Lagares-Tena L, et al. 2-deoxyglucose induces Noxa-dependent apoptosis in alveolar rhabdomyosarcoma. Cancer Res 2011; 71:6796–806. [DOI] [PubMed] [Google Scholar]
- 42.Gershon TR, Crowther AJ, Tikunov A, et al. Hexokinase-2-mediated aerobic glycolysis is integral to cerebellar neurogenesis and pathogenesis of medulloblastoma. Cancer Metab 2013; 1:2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Levy AG, Zage PE, Akers LJ, et al. The combination of the novel glycolysis inhibitor 3-BrOP and rapamycin is effective against neuroblastoma. Investigational new drugs 2012; 30:191–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Zhang Y, Liu Y, Xu X. Knockdown of LncRNA-UCA1 suppresses chemoresistance of pediatric AML by inhibiting glycolysis through the microRNA-125a/hexokinase 2 pathway. J Cell Biochem 2018; 119:6296–308. [DOI] [PubMed] [Google Scholar]; ■ This study describes the metabolic contribution of glycolytic upregulation to chemoresistance in patient samples of pediatric AML and shows that use of glycolytic inhibitors restores chemosensitivity to those cells.
- 45.Leni Z, Cwiek P, Dimitrova V, et al. 2-Deoxy-D-glucose Restore Glucocorticoid Sensitivity in Acute Lymphoblastic Leukemia via Modification of N-Linked Glycosylation in an Oxygen Tension-Independent Manner. Oxid Med Cell Longev 2017; 2017:2487297. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Dwarakanath BS, Singh D, Banerji AK, et al. Clinical studies for improving radiotherapy with 2-deoxy- D-glucose: present status and future prospects. J Cancer Res Ther 2009; 5 Suppl 1:S21–6. [DOI] [PubMed] [Google Scholar]
- 47.Ahn CS, Metallo CM. Mitochondria as biosynthetic factories for cancer proliferation. Cancer Metab 2015; 3:1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Feichtinger RG, Neureiter D, Royer-Pokora B, et al. Heterogeneity of mitochondrial energy metabolism in classical triphasic Wilms’ tumor. Front Biosci (Elite Ed) 2011; 3:187–93. [DOI] [PubMed] [Google Scholar]
- 49.Feichtinger RG, Zimmermann F, Mayr JA, et al. Low aerobic mitochondrial energy metabolism in poorly- or undifferentiated neuroblastoma. BMC Cancer 2010; 10:149. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Shen H, Yu M, Tsoli M, et al. Targeting reduced mitochondrial DNA quantity as a therapeutic approach in pediatric high-grade gliomas. Neuro-oncology 2019; noz140. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■ This study characterizes mitochondrial DNA copy number in samples of pediatric high grade glioma and normal brain and reports on the functional implications of these differences for therapeutic targeting.
- 51.Luna B, Bhatia S, Yoo C, et al. Proteomic and Mitochondrial Genomic Analyses of Pediatric Brain Tumors. Mol Neurobiol 2015; 52:1341–63. [DOI] [PubMed] [Google Scholar]
- 52.Triska P, Kaneva K, Merkurjev D, et al. Landscape of Germline and Somatic Mitochondrial DNA Mutations in Pediatric Malignancies. Cancer Res 2019; 79:1318–30. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■■ This study describes the landscape of germline and somatic mitochondrial DNA (mtDNA) mutations across a number of pediatric cancers and highlights the contribution of mtDNA mutations to the development and progression of pediatric cancers.
- 53.Fontaine E Metformin-Induced Mitochondrial Complex I Inhibition: Facts, Uncertainties, and Consequences. Front Endocrinol (Lausanne) 2018; 9:753. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Garofalo C, Capristo M, Manara MC, et al. Metformin as an adjuvant drug against pediatric sarcomas: hypoxia limits therapeutic effects of the drug. PLoS One 2013; 8:e83832. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Vujic I, Sanlorenzo M, Posch C, et al. Metformin and trametinib have synergistic effects on cell viability and tumor growth in NRAS mutant cancer. Oncotarget 2015; 6:969–78. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Vella S, Conaldi PG, Florio T, Pagano A. PPAR Gamma in Neuroblastoma: The Translational Perspectives of Hypoglycemic Drugs. PPAR Res 2016; 2016:3038164. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Wang SS, Hsiao R, Limpar MM, et al. Destabilization of MYC/MYCN by the mitochondrial inhibitors, metaiodobenzylguanidine, metformin and phenformin. Int J Mol Med 2014; 33:35–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Ko Y, Choi A, Lee M, Lee JA. Metformin displays in vitro and in vivo antitumor effect against osteosarcoma. Korean J Pediatr 2016; 59:374–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59.Uehara T, Eikawa S, Nishida M, et al. Metformin induces CD11b+-cell-mediated growth inhibition of an osteosarcoma: implications for metabolic reprogramming of myeloid cells and anti-tumor effects. Int Immunol 2019; 31:187–98. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■ This study highlights the anti-tumor effect of metformin on tumor-associated myeloid cells in preclinical models of osteosarcoma.
- 60.Sabnis HS, Bradley HL, Tripathi S, et al. Synergistic cell death in FLT3-ITD positive acute myeloid leukemia by combined treatment with metformin and 6-benzylthioinosine. Leuk Res 2016; 50:132–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Leclerc GM, Leclerc GJ, Kuznetsov JN, et al. Metformin induces apoptosis through AMPK-dependent inhibition of UPR signaling in ALL lymphoblasts. PLoS One 2013; 8:e74420. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Somers K, Wen VW, Middlemiss SMC, et al. A novel small molecule that kills a subset of MLL-rearranged leukemia cells by inducing mitochondrial dysfunction. Oncogene 2019; 38:3824–42. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■ This study reports on the effects of a cytotoxic agent, CCI-006, on the mitochondrial function of MLL-rearranged leukemias and defines determinants of sensitivity to mitochondrial perturbation in models of this disease.
- 63.Sradhanjali S, Tripathy D, Rath S, et al. Overexpression of pyruvate dehydrogenase kinase 1 in retinoblastoma: A potential therapeutic opportunity for targeting vitreous seeds and hypoxic regions. PLoS One 2017; 12:e0177744. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64.Qin L, Tian Y, Yu Z, et al. Targeting PDK1 with dichloroacetophenone to inhibit acute myeloid leukemia (AML) cell growth. Oncotarget 2016; 7:1395–407. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65.Morales DR, Morris AD. Metformin in cancer treatment and prevention. Annu Rev Med 2015; 66:17–29. [DOI] [PubMed] [Google Scholar]
- 66.Michelakis ED, Sutendra G, Dromparis P, et al. Metabolic modulation of glioblastoma with dichloroacetate. Sci Transl Med 2010; 2:31ra4. [DOI] [PubMed] [Google Scholar]
- 67.Dunbar EM, Coats BS, Shroads AL, et al. Phase 1 trial of dichloroacetate (DCA) in adults with recurrent malignant brain tumors. Investigational new drugs 2014; 32:452–64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Alistar A, Morris BB, Desnoyer R, et al. Safety and tolerability of the first-in-class agent CPI-613 in combination with modified FOLFIRINOX in patients with metastatic pancreatic cancer: a single-centre, open-label, dose-escalation, phase 1 trial. Lancet Oncol 2017; 18:770–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69.Lycan TW, Pardee TS, Petty WJ, et al. A Phase II Clinical Trial of CPI-613 in Patients with Relapsed or Refractory Small Cell Lung Carcinoma. PLoS One 2016; 11:e0164244. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70.Philip PA, Buyse ME, Alistar AT, et al. A Phase III open-label trial to evaluate efficacy and safety of CPI-613 plus modified FOLFIRINOX (mFFX) versus FOLFIRINOX (FFX) in patients with metastatic adenocarcinoma of the pancreas. Future Oncol 2019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 71.Pardee TS, Lee K, Luddy J, et al. A phase I study of the first-in-class antimitochondrial metabolism agent, CPI-613, in patients with advanced hematologic malignancies. Clin Cancer Res 2014; 20:5255–64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72.Trucco M, Barredo JC, Goldberg J, et al. A phase I window, dose escalating and safety trial of metformin in combination with induction chemotherapy in relapsed refractory acute lymphoblastic leukemia: Metformin with induction chemotherapy of vincristine, dexamethasone, PEG-asparaginase, and doxorubicin. Pediatric blood & cancer 2018; 65:e27224. [DOI] [PubMed] [Google Scholar]; ■ This study reports on the first phase 1 clinical trial using metformin in combination with a chemotherapy backbone in pediatric paitents with relapsed leukemia.
- 73.Choi BH, Coloff JL. The Diverse Functions of Non-Essential Amino Acids in Cancer. Cancers (Basel) 2019; 11 675. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 74.Synakiewicz A, Sawicka-Zukowska M, Adrianowska N, et al. Amino acid profiles as potential biomarkers for pediatric cancers: a preliminary communication. Biomark Med 2017; 11:619–27. [DOI] [PubMed] [Google Scholar]
- 75.DeBerardinis RJ, Lum JJ, Hatzivassiliou G, Thompson CB. The biology of cancer: metabolic reprogramming fuels cell growth and proliferation. Cell Metab 2008; 7:11–20. [DOI] [PubMed] [Google Scholar]
- 76.Altman BJ, Stine ZE, Dang CV. From Krebs to clinic: glutamine metabolism to cancer therapy. Nat Rev Cancer 2016; 16:619–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 77.Lukey MJ, Wilson KF, Cerione RA. Therapeutic strategies impacting cancer cell glutamine metabolism. Future Med Chem 2013; 5:1685–700. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 78.Wang T, Liu L, Chen X, et al. MYCN drives glutaminolysis in neuroblastoma and confers sensitivity to an ROS augmenting agent. Cell Death Dis 2018; 9:220. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■ This study reports an enriched glutaminolysis gene signature associated with MYCN amplification in neuroblastoma patient tumor samples.
- 79.Wang SZ, Poore B, Alt J, et al. Unbiased Metabolic Profiling Predicts Sensitivity of High MYC-Expressing Atypical Teratoid/Rhabdoid Tumors to Glutamine Inhibition with 6-Diazo-5-Oxo-L-Norleucine. Clin Cancer Res 2019; 25:5925–36. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■■ This study describes the results of unbiased metabolic profiling of atypical teratoid/rhabdoid tumors (AT/RT). It identifes a unique metabolic profile characterized by increased glutamine metabolism in high versus low MYC-expressing patient-derived cell lines that can be exploited pharmacologically.
- 80.Niklison-Chirou MV, Erngren I, Engskog M, et al. TAp73 is a marker of glutamine addiction in medulloblastoma. Genes Dev 2017; 31:1738–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81.Issaq SH, Mendoza A, Fox SD, Helman LJ. Glutamine synthetase is necessary for sarcoma adaptation to glutamine deprivation and tumor growth. Oncogenesis 2019; 8:20. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■ This study reports that pediatric sarcoma cells adapt to glutamine deprivation through increased expression of glutamine synthetase, which is required for de novo glutamine synthesis, and may be a potential therapeutic target.
- 82.Cetinbas NM, Sudderth J, Harris RC, et al. Glucose-dependent anaplerosis in cancer cells is required for cellular redox balance in the absence of glutamine. Sci Rep 2016; 6:32606. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83.Gregory MA, Nemkov T, Park HJ, et al. Targeting Glutamine Metabolism and Redox State for Leukemia Therapy. Clin Cancer Res 2019; 25:4079–90. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■■ This study demonstrates that glutaminase inhibition sensitizes leukemia cells to redox-targeted agents in vitro and in vivo, suggesting that targeting glutamine metabolism in combination with drugs that perturb mitochondrial redox state may be a widely-applicable strategy for leukemia therapy.
- 84.Locasale JW. Serine, glycine and one-carbon units: cancer metabolism in full circle. Nat Rev Cancer 2013; 13:572–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 85.Mattaini KR, Sullivan MR, Vander Heiden MG. The importance of serine metabolism in cancer. J Cell Biol 2016; 214:249–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 86.Yang M, Vousden KH. Serine and one-carbon metabolism in cancer. Nat Rev Cancer 2016; 16:650–62. [DOI] [PubMed] [Google Scholar]
- 87.Xia Y, Ye B, Ding J, et al. Metabolic Reprogramming by MYCN Confers Dependence on the Serine-Glycine-One-Carbon Biosynthetic Pathway. Cancer Res 2019; 79:3837–50. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■■ This study provides genetic evidence for transcriptional activation of a serine-glycine-one-carbon metabolism gene signature in high-risk neuroblastoma patient tumor samples with MYCN amplification and demonstrates that pharmacological inhibition of this pathway inhibits cell proliferation and tumor growth in preclinical models of high-risk neuroblastoma.
- 88.Alptekin A, Ye B, Yu Y, et al. Glycine decarboxylase is a transcriptional target of MYCN required for neuroblastoma cell proliferation and tumorigenicity. Oncogene 2019. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■ This study reports that glycine decarboxylase (GLDC), which catalyzes glycine breakdown and production of the one-carbon unit 5,10-methylene-tetrahydrofolate, is a potential therapeutic target and direct transcriptional target of MYCN in high-risk neuroblastoma, where high GLDC expression is associated with poor survival.
- 89.Sen N, Cross AM, Lorenzi PL, et al. EWS-FLI1 reprograms the metabolism of Ewing sarcoma cells via positive regulation of glutamine import and serine-glycine biosynthesis. Mol Carcinog 2018; 57:1342–57. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■ This study demonstrates that several components of the serine-glycine synthesis pathway are direct transcriptional targets of the oncogenic transcription factor EWS-FLI1 in Ewing sarcoma cell lines and that inhibition of serine synthesis impacts cellular survival in this models of this cancer.
- 90.Svoboda LK, Teh SSK, Sud S, et al. Menin regulates the serine biosynthetic pathway in Ewing sarcoma. J Pathol 2018; 245:324–36. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■■ This study describes the effect of inhibiting the interaction between the TrxG histone methyltransferase MLL1 and the scaffolding protein menin, which reduces expression of serine synthesis pathway components, inhibits serine and glycine synthesis, and decreases cell growth in Ewing sarcoma.
- 91.Pikman Y, Puissant A, Alexe G, et al. Targeting MTHFD2 in acute myeloid leukemia. J Exp Med 2016; 213:1285–306. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 92.Bean GR, Kremer JC, Prudner BC, et al. A metabolic synthetic lethal strategy with arginine deprivation and chloroquine leads to cell death in ASS1-deficient sarcomas. Cell Death Dis 2016; 7:e2406. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 93.Fenouille N, Bassil CF, Ben-Sahra I, et al. The creatine kinase pathway is a metabolic vulnerability in EVI1-positive acute myeloid leukemia. Nat Med 2017; 23:301–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 94.Prudner BC, Rathore R, Robinson AM, et al. Arginine Starvation and Docetaxel Induce c-Myc-Driven hENT1 Surface Expression to Overcome Gemcitabine Resistance in ASS1-Negative Tumors. Clin Cancer Res 2019; 25:5122–34. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■■ This study reports that arginine deprivation therapy with ADI-PEG 20 in combination with gemcitabine and docetaxel is effective in preclinical sarcoma models. This study is the foundation of a Phase II trial (NCT03449901) in soft-tissue sarcoma.
- 95.De Santo C, Booth S, Vardon A, et al. The arginine metabolome in acute lymphoblastic leukemia can be targeted by the pegylated-recombinant arginase I BCT-100. Int J Cancer 2018; 142:1490–502. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 96.Casero RA Jr., Murray Stewart T, Pegg AE. Polyamine metabolism and cancer: treatments, challenges and opportunities. Nat Rev Cancer 2018; 18:681–95. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 97.Gerner EW, Meyskens FL Jr. Polyamines and cancer: old molecules, new understanding. Nat Rev Cancer 2004; 4:781–92. [DOI] [PubMed] [Google Scholar]
- 98.Schultz CR, Geerts D, Mooney M, et al. Synergistic drug combination GC7/DFMO suppresses hypusine/spermidine-dependent eIF5A activation and induces apoptotic cell death in neuroblastoma. Biochem J 2018; 475:531–45. [DOI] [PubMed] [Google Scholar]
- 99.Gamble LD, Purgato S, Murray J, et al. Inhibition of polyamine synthesis and uptake reduces tumor progression and prolongs survival in mouse models of neuroblastoma. Sci Transl Med 2019; 11: eaau1099. [DOI] [PubMed] [Google Scholar]; ■■ This study highlights strategies to improve the efficacy of targeting polyamine metabolism with difluoromethylornithine (DFMO) in neuroblastoma through the use of combinations with novel agents and standard chemotherapy.
- 100.Weicht RR, Schultz CR, Geerts D, et al. Polyamine Biosynthetic Pathway as a Drug Target for Osteosarcoma Therapy. Med Sci (Basel) 2018; 6, 65. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 101.Evageliou NF, Haber M, Vu A, et al. Polyamine Antagonist Therapies Inhibit Neuroblastoma Initiation and Progression. Clin Cancer Res 2016; 22:4391–404. [DOI] [PubMed] [Google Scholar]
- 102.Samal K, Zhao P, Kendzicky A, et al. AMXT-1501, a novel polyamine transport inhibitor, synergizes with DFMO in inhibiting neuroblastoma cell proliferation by targeting both ornithine decarboxylase and polyamine transport. International journal of cancer Journal international du cancer 2013; 133:1323–33. [DOI] [PubMed] [Google Scholar]
- 103.Ruiz-Perez MV, Medina MA, Urdiales JL, et al. Polyamine metabolism is sensitive to glycolysis inhibition in human neuroblastoma cells. J Biol Chem 2015; 290:6106–19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 104.Saulnier Sholler GL, Gerner EW, Bergendahl G, et al. A Phase I Trial of DFMO Targeting Polyamine Addiction in Patients with Relapsed/Refractory Neuroblastoma. PLoS One 2015; 10:e0127246. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 105.Sholler GLS, Ferguson W, Bergendahl G, et al. Maintenance DFMO Increases Survival in High Risk Neuroblastoma. Sci Rep 2018; 8:14445. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■ This study describes the results of a phase II single agent trial evaluating DFMO in neuroblastoma patients. The results indicate that DFMO maintenance therapy for patients in remission is safe and may provide a new strategy for preventing relapse in children with high-risk neuroblastoma.
- 106.Bassiri H, Benavides A, Haber M, et al. Translational development of difluoromethylornithine (DFMO) for the treatment of neuroblastoma. Transl Pediatr 2015; 4:226–38. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 107.Lozier AM, Rich ME, Grawe AP, et al. Targeting ornithine decarboxylase reverses the LIN28/Let-7 axis and inhibits glycolytic metabolism in neuroblastoma. Oncotarget 2015; 6:196–206. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 108.Chowdhry S, Zanca C, Rajkumar U, et al. NAD metabolic dependency in cancer is shaped by gene amplification and enhancer remodelling. Nature 2019; 569:570–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 109.Roulston A, Shore GC. New strategies to maximize therapeutic opportunities for NAMPT inhibitors in oncology. Mol Cell Oncol 2016; 3:e1052180. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 110.Mutz CN, Schwentner R, Aryee DN, et al. EWS-FLI1 confers exquisite sensitivity to NAMPT inhibition in Ewing sarcoma cells. Oncotarget 2017; 8:24679–93. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 111.Heske CM, Davis MI, Baumgart JT, et al. Matrix screen identifies synergistic combination of PARP inhibitors and nicotinamide phosphoribosyltransferase (NAMPT) inhibitors in Ewing sarcoma. Clin Cancer Res 2017; 23:7301–7311. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 112.Grohmann T, Penke M, Petzold-Quinque S, et al. Inhibition of NAMPT sensitizes MOLT4 leukemia cells for etoposide treatment through the SIRT2-p53 pathway. Leuk Res 2018; 69:39–46. [DOI] [PubMed] [Google Scholar]; ■ This study descibes the mechanism responsible for the role of NAMPT inhibition in chemosensitization of T-cell acute leukemia models.
- 113.Takao S, Chien W, Madan V, et al. Targeting the vulnerability to NAD(+) depletion in B-cell acute lymphoblastic leukemia. Leukemia 2018; 32:616–25. [DOI] [PubMed] [Google Scholar]; ■ This study reports on the activity of KPT-9274, a dual NAMPT/PAK4 inhibitor currently under clinical investiagtion, in B-cell leukemia and identifies low nicotanimide levels as a predictor of sensitivity to NAMPT inhibition in this cancer.
- 114.Thakur BK, Dittrich T, Chandra P, et al. Involvement of p53 in the cytotoxic activity of the NAMPT inhibitor FK866 in myeloid leukemic cells. International journal of cancer 2013; 132:766–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 115.Mitchell SR, Larkin K, Grieselhuber NR, et al. Selective targeting of NAMPT by KPT-9274 in acute myeloid leukemia. Blood Adv 2019; 3:242–55. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■ This study describes the effect of KPT-9274, a dual NAMPT/PAK4 inhibitor that is currently being investigated in clinical trials, on preclinical models of AML.
- 116.Fons NR, Sundaram RK, Breuer GA, et al. PPM1D mutations silence NAPRT gene expression and confer NAMPT inhibitor sensitivity in glioma. Nat Commun 2019; 10:3790. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■■ This study identifies the effect of PPM1D mutations on the expression of NAPRT, and resulting sensitivity to NAMPT inhibition in pediatric high grade gliomas, such as DIPG. These results could have implications for patient selection in future clinical trials using NAMPT inhibitors.
- 117.Buonvicino D, Mazzola F, Zamporlini F, et al. Identification of the Nicotinamide Salvage Pathway as a New Toxification Route for Antimetabolites. Cell Chem Biol 2018; 25:471–82. [DOI] [PubMed] [Google Scholar]; ■ This study reports on the preclinical activity of a rodenticide agent to co-target multiple redundant enymes in the NAD salvage pathways and suggests that such a strategy might overcome resistance to single enzyme targeting.
- 118.von Heideman A, Berglund A, Larsson R, Nygren P. Safety and efficacy of NAD depleting cancer drugs: results of a phase I clinical trial of CHS 828 and overview of published data. Cancer chemotherapy and pharmacology 2010; 65:1165–72. [DOI] [PubMed] [Google Scholar]
- 119.Goldinger SM, Gobbi Bischof S, Fink-Puches R, et al. Efficacy and Safety of APO866 in Patients With Refractory or Relapsed Cutaneous T-Cell Lymphoma: A Phase 2 Clinical Trial. JAMA Dermatol 2016; 152:837–9. [DOI] [PubMed] [Google Scholar]
- 120.Altman BJ, Hsieh AL, Sengupta A, et al. MYC Disrupts the Circadian Clock and Metabolism in Cancer Cells. Cell Metab 2015; 22:1009–19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 121.Sabnis HS, Somasagara RR, Bunting KD. Targeting MYC Dependence by Metabolic Inhibitors in Cancer. Genes (Basel) 2017; 8, 114. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 122.Teicher BA, Linehan WM, Helman LJ. Targeting cancer metabolism. Clin Cancer Res 2012; 18:5537–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 123.Ren P, Yue M, Xiao D, et al. ATF4 and N-Myc coordinate glutamine metabolism in MYCN-amplified neuroblastoma cells through ASCT2 activation. J Pathol 2015; 235:90–100. [DOI] [PubMed] [Google Scholar]
- 124.Aminzadeh S, Vidali S, Sperl W, et al. Energy metabolism in neuroblastoma and Wilms tumor. Transl Pediatr 2015; 4:20–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 125.Boikos SA, Pappo AS, Killian JK, et al. Molecular Subtypes of KIT/PDGFRA Wild-Type Gastrointestinal Stromal Tumors: A Report From the National Institutes of Health Gastrointestinal Stromal Tumor Clinic. JAMA Oncol 2016; 2:922–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 126.Killian JK, Miettinen M, Walker RL, et al. Recurrent epimutation of SDHC in gastrointestinal stromal tumors. Sci Transl Med 2014; 6:268ra177. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 127.Waterfall JJ, Killian JK, Meltzer PS. The role of mutation of metabolism-related genes in genomic hypermethylation. Biochem Biophys Res Commun 2014; 455:16–23. [DOI] [PubMed] [Google Scholar]
- 128.Lee J, Putnam AR, Chesier SH, et al. Oligodendrogliomas, IDH-mutant and 1p/19q-codeleted, arising during teenage years often lack TERT promoter mutation that is typical of their adult counterparts. Acta Neuropathol Commun 2018; 6:95. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■ This study describes genomic analysis of a series of adolescent patients with IDH-mutant oligodendrogliomas, demonstrating that these tumors are molecularly distinct from their adult counterparts.
- 129.Korshunov A, Ryzhova M, Hovestadt V, et al. Integrated analysis of pediatric glioblastoma reveals a subset of biologically favorable tumors with associated molecular prognostic markers. Acta Neuropathol 2015; 129:669–78. [DOI] [PubMed] [Google Scholar]
- 130.Kohe SE, Bennett CD, Gill SK, et al. Metabolic profiling of the three neural derived embryonal pediatric tumors retinoblastoma, neuroblastoma and medulloblastoma, identifies distinct metabolic profiles. Oncotarget 2018; 9:11336–51. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 131.Ren L, Hong ES, Mendoza A, et al. Metabolomics uncovers a link between inositol metabolism and osteosarcoma metastasis. Oncotarget 2017; 8:38541–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 132.Delaidelli A, Negri GL, Jan A, et al. MYCN amplified neuroblastoma requires the mRNA translation regulator eEF2 kinase to adapt to nutrient deprivation. Cell Death Differ 2017; 24:1564–76. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 133.Bhatia B, Hsieh M, Kenney AM, Nahle Z. Mitogenic Sonic hedgehog signaling drives E2F1-dependent lipogenesis in progenitor cells and medulloblastoma. Oncogene 2011; 30:410–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 134.Zhang C, D’Alessandro A, Wellendorf AM, et al. KLF5 controls glutathione metabolism to suppress p190-BCR-ABL+ B-cell lymphoblastic leukemia. Oncotarget 2018; 9:29665–79. [DOI] [PMC free article] [PubMed] [Google Scholar]; ■ This study identifies the role of low KLF5 expression on impairment of glutathione metabolism and promotion of cell proliferation in B-cell leukemias, including BCR-ABL1- positive leukemias.
- 135.Hedrick E, Crose L, Linardic CM, Safe S. Histone Deacetylase Inhibitors Inhibit Rhabdomyosarcoma by Reactive Oxygen Species-Dependent Targeting of Specificity Protein Transcription Factors. Mol Cancer Ther 2015; 14:2143–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 136.Chen X, Stewart E, Shelat AA, et al. Targeting oxidative stress in embryonal rhabdomyosarcoma. Cancer Cell 2013; 24:710–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 137.Jha P, Pia Patric IR, Shukla S, et al. Genome-wide methylation profiling identifies an essential role of reactive oxygen species in pediatric glioblastoma multiforme and validates a methylome specific for H3 histone family 3A with absence of G-CIMP/isocitrate dehydrogenase 1 mutation. Neuro-oncology 2014; 16:1607–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
