Proteomics and metabolomics in cancer drug development

Expert Review of Proteomics

Volumn 10, Issue 5, 2013, Pages 473-488

  D'Alessandro, Angelo ^a   Zolla, Lello ^a  

^a UNIVERSITY OF TUSCIA   (Italy)

Author keywords

cancer; drug development; mass spectrometry; metabolism; proteomics

Indexed keywords

BIGUANIDE; REDUCED NICOTINAMIDE ADENINE DINUCLEOTIDE PHOSPHATE;

APOPTOSIS; AUTOPHAGY; CANCER CELL; CANCER RESEARCH; CELL FATE; CELL METABOLISM; CELL PROLIFERATION; CELL SURVIVAL; DRUG RESEARCH; MASS SPECTROMETRY; METABOLOMICS; NEOPLASM; ONCOGENE; PROTEOMICS; REVIEW; TUMOR SUPPRESSOR GENE;

ANIMALS; ANTINEOPLASTIC AGENTS; APOPTOSIS; AUTOPHAGY; DRUG DISCOVERY; GENETIC THERAPY; GLYCOPROTEINS; HUMANS; METABOLOME; NEOPLASMS; OXIDATION-REDUCTION; PEPTIDE FRAGMENTS; PHOSPHOPROTEINS; PROTEOME; TUMOR SUPPRESSOR PROTEIN P53;

EID: 84886045643     PISSN: 14789450     EISSN: 17448387     Source Type: Journal    
DOI: 10.1586/14789450.2013.840440     Document Type: Review

References (143)

1. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell 144(5), 646-674 (2011).
2. Warburg O. On the origin of cancer cells. Science 123, 309-314(1956).
3. Vander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 324, 1029-1033 (2009).
4. Frezza C, Pollard PJ, Gottlieb E. Inborn and acquired metabolic defects in cancer. J. Mol. Med. (Berl.) 89(3), 213-220 (2011).
5. D'Alessandro A, Zolla L. Metabolomics and cancer drug discovery: let the cells do the talking. Drug Discov. Today 17(1-2), 3-9 (2012).
6. Bichsel VE, Liotta LA, Petricoin III EF. Cancer proteomics: from biomarker discovery to signal pathway profiling. Cancer J. 7, 69-78 (2001).
7. Bachi A, Bonaldi T. Quantitative proteomics as a new piece of the system biology puzzle. J. Proteomics 71(3), 357-367 (2008).
8. Legrain P, Aebersold R, Archakov A et al. The human proteome project: current state and future direction. Mol. Cell. Proteomics 10(7), M111.009993 (2011).
9. Everley PA, Krijgsveld J, Zetter BR, Gygi SP. Quantitative cancer proteomics: stable isotope labeling with amino acids in cell culture (SILAC) as a tool for prostate cancer research. Mol. Cell. Proteomics 3(7), 729-735 (2004).
10. Geiger T, Cox J, Ostasiewicz P, Wisniewski JR, Mann M. Super-SILAC mix for quantitative proteomics of human tumor tissue. Nat. Methods 7(5), 383-385 (2010).
11. Geiger T, Wisniewski JR, Cox J et al. Use of stable isotope labeling by amino acids in cell culture as a spike-in standard in quantitative proteomics. Nat. Protoc. 6, 147-157 (2011).
12. Thompson A, Schäfer J, Kuhn K et al. Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal. Chem. 75(8), 1895-1904 (2003).
13. Kuster B, Schirle M, Mallick P, Aebersold R. Scoring proteomes with proteotypic peptide probes. Nat. Rev. Mol. Cell. Biol. 6(7), 577-583 (2005).
14. D'Alessandro A, Rinalducci S, Zolla L. Redox proteomics and drug development. J. Proteomics 74(12), 2575-2595 (2011).
15. Ang CS, Rothacker J, Patsiouras H, Gibbs P, Burgess AW, Nice EC. Use of multiple reaction monitoring for multiplex analysis of colorectal cancer-associated proteins in human feces. Electrophoresis 32(15), 1926-1938 (2011).
16. Schnatbaum K, Zerweck J, Nehmer J, Wenschuh H, Schutkowski M, Reimer U. SpikeTides-proteotypic peptides for large-scale MS-based proteomics. Nature Methods 8 (Application note) (2011).
17. Bachi A, Dalle-Donne I, Scaloni A. Redox proteomics: chemical principles, methodological approaches and biological/biomedical promises. Chem. Rev. 113(1), 596-698 (2013).
18. Ashman K, Villar EL. Phosphoproteomics and cancer research. Clin. Transl. Oncol. 11(6), 356-362 (2009).
19. Engholm-Keller K, Larsen MR. Technologies and challenges in large-scale phosphoproteomics. Proteomics 13(6), 910-931 (2013).
20. Kim EH, Misek DE. Glycoproteomics-based identification of cancer biomarkers. Int. J. Proteomics 2011, 601937 (2011).
21. Gupta R, Brunak S. Prediction of glycosylation across the human proteome and the correlation to protein function. Pac. Symp. Biocomput. 7, 310-322 (2002).
22. Pan S, Chen R, Aebersold R, Brentnall TA. Mass spectrometry based glycoproteomics-from a proteomics perspective. Mol. Cell. Proteomics 10(1), R110.003251 (2011).
23. Chen R, Jiang X, Sun D et al. Glycoproteomics analysis of human liver tissue by combination of multiple enzyme digestion and hydrazide chemistry. J. Proteome Res. 8(2), 651-661 (2009).
24. Schwamborn K, Caprioli RM. MALDI imaging mass spectrometry-painting molecular pictures. Mol. Oncol. 4(6), 529-538 (2010).
25. Schöne C, Höfler H, Walch A. MALDI imaging mass spectrometry in cancer research: Combining proteomic profiling and histological evaluation. Clin. Biochem. 46(6), 539-545 (2013).
26. Franck J, Longuespée R, Wisztorski M et al. MALDI mass spectrometry imaging of proteins exceeding 30,000 daltons. Med. Sci. Monit. 16(9), BR293-299 (2010).
27. Gustafsson OJ, Eddes JS, Meding S, McColl SR, Oehler MK, Hoffmann P. Matrix-assisted laser desorption/ionization imaging protocol for in situ characterization of tryptic peptide identity and distribution in formalin-fixed tissue. Rapid Commun. Mass Spectrom. 27(6), 655-670 (2013).
28. Monteiro MS, Carvalho M, Bastos ML, de Pinho PG. Metabolomics analysis for biomarker discovery: advances and challenges. Curr. Med. Chem. 20(2), 257-271 (2013).
29. Casadonte R, Caprioli RM. Proteomic analysis of formalin-fixed paraffin-embedded tissue by MALDI imaging mass spectrometry. Nat. Protoc. 6(11), 1695-1709 (2011).
30. Picotti P, Aebersold R. Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions. Nat. Methods 9(6):555-566 (2012).
31. Putri SP, Yamamoto S, Tsugawa H, Fukusaki E. Current metabolomics: technological advances. J. Biosci. Bioeng. 116(1), 9-16 (2013).
32. D'Alessandro A, Giardina B, Gevi F, Timperio AM, Zolla L. Clinical metabolomics: the next stage of clinical biochemistry. Blood Transfus. 10(2), s19-24 (2012).
33. Milne SB, Mathews TP, Myers DS, Ivanova PT, Brown HA. Sum of the parts: mass spectrometry-based metabolomics. Biochemistry 52(22), 3829-3840 (2013).
34. D'Alessandro A, Gevi F, Zolla L. A robust high resolution reversed-phase HPLC strategy to investigate various metabolic species in different biological models. Mol. Biosyst. 7(4), 1024-1032 (2011).
35. Guo B, Chen B, Liu A, Zhu W, Yao S. Liquid chromatography-mass spectrometric multiple reaction monitoring-based strategies for expanding targeted profiling towards quantitative metabolomics. Curr. Drug Metab. 13(9), 1226-1243 (2012).
36. D'Alessandro A, Gevi F, Zolla L. Targeted mass spectrometry-based metabolomic profiling through multiple reaction monitoring of liver and other biological matrices. Methods Mol. Biol. 909, 279-294 (2012).
37. Tautenhahn R, Cho K, Uritboonthai W, Zhu Z, Patti GJ, Siuzdak G. An accelerated workflow for untargeted metabolomics using the METLIN database. Nat. Biotechnol. 30(9), 826-828 (2012).
38. Crown SB, Ahn WS, Antoniewicz MR. Rational design of 13C-labeling experiments for metabolic flux analysis in mammalian cells. BMC Syst. Biol. 6, 43-57 (2012).
39. van Kampen JJ, Burgers PC, de Groot R, Gruters RA, Luider TM. Biomedical application of MALDI mass spectrometry for small-molecule analysis. Mass Spectrom. Rev. 30(1), 101-120 (2011).
40. Klitzing HA, Weber PK, Kraft ML. Secondary ion mass spectrometry imaging of biological membranes at high spatial resolution. Methods Mol. Biol. 950, 483-501 (2013).
41. Issaq HJ, Fox SD, Chan KC, Veenstra TD. Global proteomics and metabolomics in cancer biomarker discovery. J. Sep. Sci. 34(24), 3484-3492 (2011).
42. Dang CV. Links between metabolism and cancer. Genes Dev. 26(9), 877-890 (2012).
43. López-Lázaro M. The warburg effect: why and how do cancer cells activate glycolysis in the presence of oxygen? Anticancer Agents Med. Chem. 8(3), 305-312 (2008).
44. Kilburn DG, Lilly MD, Webb FC. The energetics of mammalian cell growth. J. Cell Sci. 4(3), 645-654 (1969).
45. Frezza C, Gottlieb E. Mitochondria in cancer: not just innocent bystanders. Semin. Cancer Biol. 19, 4-11 (2009).
46. Martinez-Outschoorn UE, Lin Z, Trimmer C et al. Cancer cells metabolically 'fertilize' the tumor microenvironment with hydrogen peroxide, driving the Warburg effect: implications for PET imaging of human tumors. Cell Cycle 10(15), 2504-2520 (2011).
47. Cardaci S, Ciriolo MR. TCA Cycle Defects and cancer: when metabolism tunes redox state. Int. J. Cell Biol. 2012, 161837 (2012).
48. Guzy RD, Hoyos B, Robin E et al. Mitochondrial complex III is required for hypoxia-induced ROS production and cellular oxygen sensing. Cell Metab. 1, 401-408 (2005).
49. Frezza C, Tennant DA, Gottlieb E. IDH1 mutations in gliomas: when an enzyme loses its grip. Cancer Cell 17, 7-9 (2010).
50. Pollard PJ, Briere JJ, Alam NA et al. Accumulation of Krebs cycle intermediates and over-expression of HIF1alpha in tumours which result from germline FH and SDH mutations. Hum. Mol. Genet. 14, 2231-2239 (2005).
51. Yang M, Soga T, Pollard PJ, Adam J. The emerging role of fumarate as an oncometabolite. Front. Oncol. 2, 85 (2012).
52. Selak MA, Armour SM, MacKenzie ED et al. Succinate links TCA cycle dysfunction to oncogenesis by inhibiting HIF-alpha prolyl hydroxylase. Cancer Cell 7, 77-85 (2005).
53. Hewitson KS, Lienard BM, McDonough MA et al. Structural and mechanistic studies on the inhibition of the hypoxiainducible transcription factor hydroxylases by tricarboxylic acid cycle intermediates. J. Biol. Chem. 282, 3293-3301 (2007).
54. Navis A, Niclou S, Fack F et al. Increased mitochondrial activity in a novel IDH1-R132H mutant human oligodendroglioma xenograft model: in situ detection of 2-HG and a-KG. Acta Neuropathol. Commun. 1(1), 18 (2013).
55. Maxwell PH, Pugh CW, Ratcliffe PJ. Activation of the HIF pathway in cancer. Curr. Opin. Genet. Dev. 11, 293-299 (2001).
56. Wise DR, Ward PS, Shay JE et al. Hypoxia promotes isocitrate dehydrogenasedependent carboxylation of alpha-ketoglutarate to citrate to support cell growth and viability. Proc. Natl Acad. Sci. USA 108, 19611-19616 (2011).
57. Vance DE, Vance JE. Physiological consequences of disruption of mammalian phospholipid biosynthetic genes. J. Lipid Res. 50, S132 (2009).
58. Levine AJ, Puzio-Kuter AM. The control of the metabolic switch in cancers by oncogenes and tumor suppressor genes. Science 330, 1340-1344 (2010).
59. Schafer ZT, Grassian AR, Song L et al. Antioxidant and oncogene rescue of metabolic defects caused by loss of matrix attachment. Nature 461, 109-113 (2009).
60. Vander Heiden MG, Lunt SY, Dayton TL et al. Metabolic pathway alterations that support cell proliferation. Cold Spring Harb. Symp. Quant. Biol. 76, 325-334 (2011).
61. Muller PA, Vousden KH, Norman JC. p53 and its mutants in tumor cell migration and invasion. J. Cell Biol. 192(2), 209-218 (2011).
62. Sherr CJ, McCormick F. The RB and p53 pathways in cancer. Cancer Cell 2(2), 103-112 (2002).
63. Yeung SJ, Pan J, Lee MH. Roles of p53, MYC and HIF-1 in regulating glycolysis-the seventh hallmark of cancer. Cell. Mol. Life Sci. 65, 3981-3999 (2008).
64. Vousden KH, Ryan KM. p53 and metabolism. Nat. Rev. Cancer 9, 691-700 (2009).
65. Berkers CR, Maddocks OD, Cheung EC, Mor I, Vousden KH. Metabolic regulation by p53 family Members. Cell. Metab. doi:10.1016/j.cmet.2013.06.019 (2013) (Epub ahead of print).
66. Cheung EC, Ludwig RL, Vousden KH. Mitochondrial localization of TIGAR under hypoxia stimulates HK2 and lowers ROS and cell death. Proc. Natl Acad. Sci. USA 109(50), 20491-20496 (2012).
67. Bensaad K, Cheung EC, Vousden KH. Modulation of intracellular ROS levels by TIGAR controls autophagy. EMBO J. 28(19), 3015-3026 (2009).
68. Wanka C, Steinbach JP, Rieger J. Tp53-induced glycolysis and apoptosis regulator (TIGAR) protects glioma cells from starvation-induced cell death by up-regulating respiration and improving cellular redox homeostasis. J. Biol. Chem. 287(40), 33436-33446 (2012).
69. D'Alessandro A, Marrocco C, Rinalducci S et al. Analysis of TAp73-dependent signaling via Omics technologies. J. Proteome Res. 12(9), 4207-4220 (2013)
70. Wanka C, Brucker DP, Bähr O et al. Synthesis of cytochrome C oxidase 2: a p53-dependent metabolic regulator that promotes respiratory function and protects glioma and colon cancer cells from hypoxia-induced cell death. Oncogene 31(33), 3764-3776 (2012).
71. Hu W, Zhang C, Wu R, Sun Y, Levine A, Feng Z. Glutaminase 2, a novel p53 target gene regulating energy metabolism and antioxidant function. Proc. Natl Acad. Sci. USA 107(16), 7455-7460 (2010).
72. Giacobbe A, Bongiorno-Borbone L, Bernassola F et al. p63 regulates glutaminase 2 expression. Cell Cycle 12(9), 1395-1405 (2013).
73. Stavridi ES, Halazonetis TD. p53 and stress in the ER. Genes Dev. 18(3), 241-244 (2004).
74. Pluquet O, Qu LK, Baltzis D, Koromilas AE. Endoplasmic reticulum stress accelerates p53 degradation by the cooperative actions of Hdm2 and glycogen synthase kinase 3beta. Mol. Cell. Biol. 25(21), 9392-9405 (2005).
75. Zocchi L, Bourdon JC, Codispoti A et al. Scotin: A new p63 target gene expressed during epidermal differentiation. Biochem. Biophys. Res. Commun. 367(2), 271-276 (2008).
76. Terrinoni A, Ranalli M, Cadot B et al. p73 alpha is capable of inducing scotin and ER stress. Oncogene 23(20), 3721-3725 (2004).
77. Rufini A, Niklison-Chirou MV, Inoue S et al. TAp73 depletion accelerates aging through metabolic dysregulation. Genes Dev. 26(18), 2009-2014 (2012).
78. Zulato E, Curtarello M, Nardo G, Indraccolo S. Metabolic effects of anti-angiogenic therapy in tumors. Biochimie 94(4), 925-931 (2012).
79. Wyld L, Tomlinson M, Reed MW, Brown NJ. Aminolaevulinic acid-induced photodynamic therapy: cellular responses to glucose starvation. Br. J. Cancer 86(8), 1343-1347 (2002).
80. Sandulache VC, Ow TJ, Pickering CR et al. Glucose, not glutamine, is the dominant energy source required for proliferation and survival of head and neck squamous carcinoma cells. Cancer 117(13), 2926-2938 (2011).
81. Ogiso Y, Tomida A, Kim HD, Tsuruo T. Glucose starvation and hypoxia induce nuclear accumulation of proteasome in cancer cells. Biochem. Biophys. Res. Commun. 258(2), 448-452 (1999).
82. Berardinis RJ, Mancuso A, Daikhin E et al. Beyond aerobic glycolysis: transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis. Proc. Natl Acad. Sci. USA 104, 19345-19350 (2007).
83. Yuneva M, Zamboni N, Oefner P, Sachidanandam R, Lazebnik Y. Deficiency in glutamine but not glucose induces MYC-dependent apoptosis in human cells. J. Cell. Biol. 178(1), 93-105 (2007).
84. McCarthy N. Metabolism: Sensitivity to serine starvation. Nat. Rev. Cancer 13(2), 77 (2013).
85. Maddocks OD, Berkers CR, Mason SM et al. Serine starvation induces stress and p53-dependent metabolic remodelling in cancer cells. Nature 493(7433), 542-546 (2013).
86. Christofk HR, Vander Heiden MG, Harris MH et al. The M2 splice isoform of pyruvate kinase is important for cancer metabolism and tumour growth. Nature 452, 230-233 (2008).
87. Chaneton B, Hillmann P, Zheng L et al. Serine is a natural ligand and allosteric activator of pyruvate kinase M2. Nature 491(7424), 458-462 (2012).
88. Ye J, Mancuso A, Tong X et al. Pyruvate kinase M2 promotes de novo serine synthesis to sustain mTORC1 activity and cell proliferation. Proc. Natl Acad. Sci. USA 109(18), 6904-6909 (2012).
89. Dandapani M, Hardie DG. AMPK: opposing the metabolic changes in both tumour cells and inflammatory cells? Biochem. Soc. Trans. 41(2), 687-693 (2013).
90. Li L, Chen Y, Gibson SB. Starvation-induced autophagy is regulated by mitochondrial reactive oxygen species leading to AMPK activation. Cell. Signal. 25(1), 50-65 (2013).
91. Kupiec M, Weisman R. TOR links starvation responses to telomere length maintenance. Cell Cycle 11(12), 2268-2271 (2012).
92. Lamming DW, Ye L, Sabatini DM, Baur JA. Rapalogs and mTOR inhibitors as anti-aging therapeutics. J. Clin. Invest. 123(3), 980-989 (2013).
93. Efeyan A, Zoncu R, Sabatini DM. Amino acids and mTORC1: from lysosomes to disease. Trends Mol. Med. 18(9), 524-533 (2012).
94. Laplante M, Sabatini DM. mTOR signaling in growth control and disease. Cell 149(2), 274-293 (2012).
95. Laplante M, Sabatini DM. mTOR Signaling. Cold Spring Harb. Perspect. Biol. 4(2) a011593 (2012).
96. Sun H, Lesche R, Li DM et al. PTEN modulates cell cycle progression and cell survival by regulating phosphatidylinositol 3,4,5,-trisphosphate and Akt/protein kinase B signaling pathway. Proc. Natl Acad. Sci. USA 96(11), 6199-6204 (1999).
97. Dang CV, Le A, Gao P. MYC-induced cancer cell energy metabolism and therapeutic opportunities. Clin. Cancer Res. 15(21), 6479-6483 (2009).
98. Ying H, Kimmelman AC, Lyssiotis CA et al. Oncogenic Kras maintains pancreatic tumors through regulation of anabolic glucose metabolism. Cell 149(3), 656-670 (2012).
99. Son J, Lyssiotis CA, Ying H et al. Glutamine supports pancreatic cancer growth through a KRAS-regulated metabolic pathway. Nature 496(7443), 101-105 (2013).
100. Carracedo A, Weiss D, Leliaert AK et al. A metabolic prosurvival role for PML in breast cancer. J. Clin. Invest. 122, 3088-3100 (2012).
101. Binoux M. The IGF system in metabolism regulation. Diabete. Metab. 21(5), 330-337 (1995).
102. Sassen S, Miska EA, Caldas C. MicroRNA: implications for cancer. Virchows. Arch. 452(1), 1-10 (2008).
103. Jansson MD, Lund AH. MicroRNA and cancer. Mol. Oncol. 6(6), 590-610 (2012).
104. Rottiers V, Näär AM. MicroRNAs in metabolism and metabolic disorders. Nat. Rev. Mol. Cell Biol. 13(4):239-250 (2012).
105. Peschiaroli A, Giacobbe A, Formosa A et al. miR-143 regulates hexokinase 2 expression in cancer cells. Oncogene 32(6):797-802 (2013).
106. Soga T. Cancer metabolism: key players in metabolic reprogramming. Cancer Sci. 104(3), 275-281 (2013).
107. Birsoy K, Sabatini DM, Possemato R. Untuning the tumor metabolic machine: targeting cancer metabolism: a bedside lesson. Nat. Med. 18(7), 1022-1023 (2012).
108. Samudio I, Fiegl M, Andreeff M. Mitochondrial uncoupling and the Warburg effect: molecular basis for the reprogramming of cancer cell metabolism. Cancer Res. 69(6), 2163-2166 (2009).
109. Tennant DA, Duran RV, Gottlieb E. Targeting metabolic transformation for cancer therapy. Nat. Rev. Cancer 10, 267-277 (2010).
110. DeBerardinis RJ, Lum JJ, Hatzivassiliou G, Thompson CB. The biology of cancer: metabolic reprogramming fuels cell growth and proliferation. Cell Metab. 7, 11-20 (2008).
111. Chen Z, Lu W, Garcia-Prieto C, Huang P. The Warburg effect and its cancer therapeutic implications. J. Bioenerg. Biomembr. 39(3), 267-274 (2007).
112. Feron O. Pyruvate into lactate and back: from the Warburg effect to symbiotic energy fuel exchange in cancer cells. Radiother. Oncol. 92(3), 329-333 (2009).
113. Granchi C, Minutolo F. Anticancer agents that counteract tumor glycolysis. ChemMedChem 7(8), 1318-1350 (2012).
114. Madhok BM, Yeluri S, Perry SL, Hughes TA, Jayne DG. Targeting glucose metabolism: an emerging concept for anticancer therapy. Am. J. Clin. Oncol. 34(6), 628-635 (2011).
115. Semenza GL. Hypoxia-inducible factors: mediators of cancer progression and targets for cancer therapy. Trends Pharmacol. Sci. 33, 207-214 (2012).
116. Chiarugi A, Dölle C, Felici R, Ziegler M. The NAD metabolome-a key determinant of cancer cell biology. Nat. Rev. Cancer 12(11), 741-752 (2012).
117. Amaravadi RK, Lippincott-Schwartz J, Yin XM et al. Principles and current strategies for targeting autophagy for cancer treatment. Clin. Cancer Res. 17, 654-666 (2011).
118. Bursch W, Karwan A, Mayer M et al. Cell death and autophagy: cytokines, drugs, and nutritional factors. Toxicology 254(3), 147-157 (2008).
119. Peng T, Golub TR, Sabatini DM. The immunosuppressant rapamycin mimics a starvation-like signal distinct from amino acid and glucose deprivation. Mol. Cell Biol. 22(15), 5575-5584 (2002).
120. Dando I, Donadelli M, Costanzo C et al. Cannabinoids inhibit energetic metabolism and induce AMPK-dependent autophagy in pancreatic cancer cells. Cell Death Dis. 4, e664 (2013).
121. Lee C, Raffaghello L, Longo VD. Starvation, detoxification, and multidrug resistance in cancer therapy. Drug Resist. Updat. 15(1-2), 114-122 (2012).
122. DiPaola RS, Dvorzhinski D, Thalasila A et al. Therapeutic starvation and autophagy in prostate cancer: a new paradigm for targeting metabolism in cancer therapy. Prostate 68(16), 1743-1752 (2008).
123. Raffaghello L, Lee C, Safdie FM et al. Starvation-dependent differential stress resistance protects normal but not cancer cells against high-dose chemotherapy. Proc. Natl Acad. Sci. USA 105(24), 8215-8220 (2008).
124. Awale S, Lu J, Kalauni SK et al. Identification of arctigenin as an antitumor agent having the ability to eliminate the tolerance of cancer cells to nutrient starvation. Cancer Res. 66(3), 1751-1757 (2006).
125. Wishart DS, Knox C, Guo AC et al. DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res. 36, D901-D906 (2008).
126. Kuhajda FP, Jenner K, Wood FD et al. Fatty acid synthesis: a potential selective target for antineoplastic therapy. Proc. Natl Acad. Sci. USA 91, 6379-6383 (1994).
127. Panigrahy D, Kaipainen A, Huang S et al. PPARalpha agonist fenofibrate suppresses tumor growth through direct and indirect angiogenesis inhibition. Proc. Natl Acad. Sci. U.S.A. 105(3), 985-990 (2008).
128. Samudio I, Harmancey R, Fiegl M et al. Pharmacologic inhibition of fatty acid oxidation sensitizes human leukemia cells to apoptosis induction. J. Clin. Invest. 120, 142-156 (2010).
129. Carracedo A, Cantley LC, Pandolfi PP. Cancer metabolism: fatty acid oxidation in the limelight. Nat. Rev. Cancer 13(4), 227-232 (2013).
130. Anastasiou D, Cantley LC. Breathless cancer cells get fat on glutamine. Cell Res. 22(3), 443-446 (2012).
131. Wise DR, Thompson CB. Glutamine addiction: a new therapeutic target in cancer. Trends Biochem. Sci. 35(8), 427-433 (2010).
132. Middleton B. The mitochondrial long-chain trifunctional enzyme: 2-enoyl-CoA hydratase, 3-hydroxyacyl-CoA dehydrogenase and 3-oxoacyl-CoA thiolase. Biochem. Soc. Trans. 22(2), 427-431 (2002).
133. Zaidi N, Swinnen JV, Smans K. ATP-citrate lyase: a key player in cancer metabolism. Cancer Res. 72(15), 3709-3714 (2012).
134. Sidransky D. Emerging molecular markers of cancer. Nat. Rev. Cancer 2(3), 210-219 (2002).
135. Ciocca DR, Calderwood SK. Heat shock proteins in cancer: diagnostic, prognostic, predictive, and treatment implications. Cell Stress. Chaperones. 10(2), 86-103 (2005).
136. Shu CW, Huang CM. HSP70s: from tumor transformation to cancer therapy. Clin. Med. Oncol. 2, 335-345 (2008).
137. D'Alessandro A, Zolla L. We are what we eat: food safety and proteomics. J. Proteome Res. 11(1), 26-36 (2012).
138. Folger O, Jerby L, Frezza C, Gottlieb E, Ruppin E, Shlomi T. Predicting selective drug targets in cancer through metabolic networks. Mol. Syst. Biol. 7, 501 (2011).
139. Facchetti G, Zampieri M, Altafini C. Predicting and characterizing selective multiple drug treatments for metabolic diseases and cancer. BMC Syst. Biol. 6(1), 115 (2012).
140. Chang R, Xie L, Bourne P, Palsson B, Dunbrack R. Drug off-target effects predicted using structural analysis in the context of a metabolic network model. PLoS Comput. Biol. 6, e1000938 (2010).
141. Draoui N, Feron O. Lactate shuttles at a glance: from physiological paradigms to anti-cancer treatments. Dis. Model. Mech. 4(6), 727-732 (2011).
142. Kaelin WG Jr. The concept of synthetic lethality in the context of anticancer therapy. Nat. Rev. Cancer 5, 689-698 (2005).
143. Lehàr J, Krueger AS, Avery W et al. Synergistic drug combinations tend to improve therapeutically relevant selectivity. Nat. Biotechnol. 27, 659-666 (2009).