Zooming-in on cancer metabolic rewiring with tissue specific constraint-based models

Computational Biology and Chemistry

Volumn 62, Issue , 2016, Pages 60-69

  Di Filippo, Marzia ^a,b   Colombo, Riccardo ^a,b   Damiani, Chiara ^a,b   Pescini, Dario ^a,b   Gaglio, Daniela ^a,c   Vanoni, Marco ^a,b   Alberghina, Lilia ^a,b   Mauri, Giancarlo ^a,b  

^a Milano and Rome   (Italy)

^b UNIVERSITY OF MILANO BICOCCA   (Italy)

^c INSTITUTE OF MOLECULAR BIOIMAGING AND PHYSIOLOGY   (Italy)

Author keywords

Cancer metabolic rewiring; Core metabolic model; Flux Balance Analysis; Network reconstruction

Indexed keywords

DISEASES; TISSUE;

CANCER METABOLIC REWIRING; CONSTRAINT-BASED MODELS; FLUX BALANCE ANALYSIS; GENOME SCALE METABOLIC MODEL; METABOLIC FLUX DISTRIBUTION; METABOLIC MODELING; METABOLIC NETWORK MODELS; NETWORK RECONSTRUCTION;

METABOLISM;

BIOLOGICAL MODEL; BIOLOGY; HUMAN; METABOLISM; NEOPLASM; PATHOPHYSIOLOGY;

COMPUTATIONAL BIOLOGY; HUMANS; METABOLIC NETWORKS AND PATHWAYS; MODELS, BIOLOGICAL; NEOPLASMS;

EID: 84963526277     PISSN: 14769271     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiolchem.2016.03.002     Document Type: Article

References (54)

1. R. Agren, S. Bordel, A. Mardinoglu, N. Pornputtapong, I. Nookaew, and J. Nielsen Reconstruction of genome-scale active metabolic networks for 69 human cell types and 16 cancer types using INIT PLoS Comput. Biol. 8 5 2012 e1002518 10.1371/journal.pcbi.1002518
2. R. Agren, A. Mardinoglu, A. Asplund, C. Kampf, M. Uhlen, and J. Nielsen Identification of anticancer drugs for hepatocellular carcinoma through personalized genome-scale metabolic modeling Mol. Syst. Biol. 10 2014 721 10.1002/msb.145122
3. L. Alberghina, and D. Gaglio Redox control of glutamine utilization in cancer Cell Death Dis. 5 12 2014 e1561 10.1038/cddis.2014.513
4. L. Alberghina, and H.V. Westerhoff Systems Biology: Definitions and Perspectives 2005 Springer
5. A.-L. Barabási, and Z.N. Oltvai Network biology: understanding the cell's functional organization Nat. Rev. Genet. 5 2 2004 101 113 10.1038/nrg1272
6. S.A. Becker, A.M. Feist, M.L. Mo, G. Hannum, B.Ø. Palsson, and M.J. Herrgard Quantitative prediction of cellular metabolism with constraint-based models: the COBRA toolbox Nat. Protoc. 2 3 2007 727 738 10.1038/nprot.2007.99
7. +channel axis is suppressed in cancer and its normalization promotes apoptosis and inhibits cancer growth Cancer Cell 11 1 2007 37 51 10.1016/j.ccr.2006.10.020
8. F. Bray, J.-S. Ren, E. Masuyer, and J. Ferlay Estimates of global cancer prevalence for 27 sites in the adult population in 2008 Int. J. Cancer 132 5 2013 1133 1145 10.1002/ijc.27711
9. P. Cazzaniga, C. Damiani, D. Besozzi, R. Colombo, M.S. Nobile, D. Gaglio, D. Pescini, S. Molinari, G. Mauri, L. Alberghina, and M. Vanoni Computational strategies for a system-level understanding of metabolism Metabolites 4 4 2014 1034 1087 10.3390/metabo4041034
10. M.S. Cline, M. Smoot, E. Cerami, A. Kuchinsky, N. Landys, C. Workman, R. Christmas, I. Avila-Campilo, M. Creech, B. Gross, and et al. Integration of biological networks and gene expression data using Cytoscape Nat. Protoc. 2 10 2007 2366 2382 10.1038/nprot.2007.324
11. C. Damiani, D. Pescini, R. Colombo, S. Molinari, L. Alberghina, M. Vanoni, and G. Mauri An ensemble evolutionary constraint-based approach to understand the emergence of metabolic phenotypes Natural Comput. 13 3 2014 321 331 10.1007/s11047-014-9439-4
12. D. De Martino, F. Capuani, M. Mori, A. De Martino, and E. Marinari Counting and correcting thermodynamically infeasible flux cycles in genome-scale metabolic networks Metabolites 3 4 2013 946 966 10.3390/metabo3040946
13. R.J. DeBerardinis, and T. Cheng Q's next: the diverse functions of glutamine in metabolism, cell biology and cancer Oncogene 29 3 2010 313 324 10.1038/onc.2009.358
14. R.J. DeBerardinis, A. Mancuso, E. Daikhin, I. Nissim, M. Yudkoff, S. Wehrli, and C.B. Thompson Beyond aerobic glycolysis: transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis Proc. Natl. Acad. Sci. U. S. A. 104 49 2007 19345 19350 10.1073/pnas.0709747104
15. R.J. DeBerardinis, J.J. Lum, G. Hatzivassiliou, and C.B. Thompson The biology of cancer: metabolic reprogramming fuels cell growth and proliferation Cell Metab. 7 1 2008 11 20 10.1016/j.cmet.2007.10.002
16. N.C. Duarte, S.A. Becker, N. Jamshidi, I. Thiele, M.L. Mo, T.D. Vo, R. Srivas, and B.Ø. Palsson Global reconstruction of the human metabolic network based on genomic and bibliomic data PNAS 104 6 2007 1777 1782 10.1073/pnas.0610772104
17. D.A. Fell, and J.R. Small Fat synthesis in adipose tissue. an examination of stoichiometric constraints Biochem. J. 238 1986 781 786
18. J. Ferlay, I. Soerjomataram, M. Ervik, R. Dikshit, S. Eser, C. Mathers, M. Rebelo, D. Forman, and F. Bray GLOBOCAN 2012 v1. 0, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 11 [Internet] 2013 Fr Int Agency Res Cancer Lyon
19. O. Folger, L. Jerby, C. Frezza, E. Gottlieb, E. Ruppin, and T. Shlomi Predicting selective drug targets in cancer through metabolic networks Mol. Syst. Biol. 7 2011 501 10.1038/msb.2011.35
20. S. Ganapathy-Kanniappan, and J.-F.H. Geschwind Tumor glycolysis as a target for cancer therapy: progress and prospects Mol Cancer 12 2013 152 10.1186/1476-4598-12-152
21. F. Gatto, I. Nookaew, and J. Nielsen Chromosome 3p loss of heterozygosity is associated with a unique metabolic network in clear cell renal carcinoma Natl. Acad. Sci. 111 9 2014 E866 75 10.1073/pnas.1319196111
22. D. Hanahan, and R.A. Weinberg Hallmarks of cancer: the next generation Cell 144 5 2011 646 674 10.1016/j.cell.2011.02.013
23. T. Hao, H.-W. Ma, X.-M. Zhao, and I. Goryanin Compartmentalization of the Edinburgh human metabolic network BMC Bioinform. 11 2010 393 10.1186/1471-2105-11-393
24. K. Hiller, and C.M. Metallo Profiling metabolic networks to study cancer metabolism Curr. Opin. Biotechnol. 24 1 2013 60 68 10.1016/j.copbio.2012.11.001
25. J. Hooda, D. Cadinu, M.M. Alam, A. Shah, T.M. Cao, L.A. Sullivan, R. Brekken, and L. Zhang Enhanced heme function and mitochondrial respiration promote the progression of lung cancer cells PLoS ONE 8 5 2013 e63402 10.1371/journal.pone.0063402
26. J.J. Hornberg, F.J. Bruggeman, H.V. Westerhoff, and J. Lankelma Cancer: a systems biology disease Biosystems 83 2-3 2006 81 90 10.1016/j.biosystems.2005.05.014
27. J. Hu, J.W. Locasale, J.H. Bielas, J. O'Sullivan, K. Sheahan, L.C. Cantley, M.G. Vander Heiden, and D. Vitkup Heterogeneity of tumor-induced gene expression changes in the human metabolic network Nat. Biotechnol. 31 6 2013 522 529 10.1038/nbt.2530
28. M. Kanehisa, and S. Goto KEGG: Kyoto encyclopedia of genes and genomes Nucleic Acids Res. 28 1 2000 27 30 10.1093/nar/28.1.27
29. M. Kanehisa, S. Goto, Y. Sato, M. Kawashima, M. Furumichi, and M. Tanabe Data, information, knowledge and principle: back to metabolism in KEGG Nucleic Acids Res. 42 D1 2014 D199 D205 10.1093/nar/gkt1076
30. H. Kitano Perspectives on systems biology New Gener. Comput. 18 3 2000 199 216 10.1007/BF03037529
31. H. Kitano Systems biology: toward system-level understanding of biological systems K.H. Foundations of Systems Biology 2001 MIT Press 1 36 10.1007/978-1-84882-023-4
32. H. Kitano Systems biology: a brief overview Science 295 5560 2002 1662 1664 10.1126/science.1069492
33. C. Li, M. Donizelli, N. Rodriguez, H. Dharuri, L. Endler, V. Chelliah, L. Li, E. He, A. Henry, M.I. Stefan, and et al. BioModels Database: an enhanced, curated and annotated resource for published quantitative kinetic models BMC Syst. Biol. 4 1 2010 92 10.1186/1752-0509-4-92
34. J.W. Locasale, and L.C. Cantley Altered metabolism in cancer BMC Biol. 8 2010 88 10.1186/1741-7007-8-88
35. H. Ma, A. Sorokin, A. Mazein, A. Selkov, E. Selkov, O. Demin, and I. Goryanin The Edinburgh human metabolic network reconstruction and its functional analysis Mol. Syst. Biol. 3 2007 135 10.1038/msb4100177
36. C.M. Metallo, P.A. Gameiro, E.L. Bell, K.R. Mattaini, J. Yang, K. Hiller, C.M. Jewell, Z.R. Johnson, D.J. Irvine, L. Guarente, and et al. Reductive glutamine metabolism by IDH1 mediates lipogenesis under hypoxia Nature 481 7381 2012 380 384 10.1038/nature10602
37. H.Z. Mullen, and A.R. Oxidation of alpha-ketoglutarate is required for reductive carboxylation in cancer cells with mitochondrial defects Cell Rep. 7 5 2014 1679 1690 10.1016/j.celrep.2014.04.037
38. J.D. Orth, I. Thiele, and B.Ø. Palsson What is flux balance analysis? Nat. Biotechnol. 28 3 2010 245 248 10.1038/nbt.1614
39. K. Raman, and N. Chandra Flux balance analysis of biological systems: applications and challenges Brief. Bioinform. 10 4 2009 435 449 10.1093/bib/bbp011
40. O. Resendis-Antonio, A. Checa, and S. Encarnacin Modeling core metabolism in cancer cells: surveying the topology underlying the Warburg effect PLoS ONE 5 8 2010 e12383 10.1371/journal.pone.0012383
41. P. Romero, J. Wagg, M.L. Green, D. Kaiser, M. Krummenacker, and P.D. Karp Computational prediction of human metabolic pathways from the complete human genome Genome Biol. 6 1 2004 R2 10.1186/gb-2004-6-1-r2
42. J. Schellenberger, R. Que, R.M.T. Fleming, I. Thiele, J.D. Orth, A.M. Feist, D.C. Zielinski, A. Bordbar, N.E. Lewis, S. Rahmanian, and et al. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA toolbox v2.0 Nat. Protoc. 6 9 2011 1290 1307 10.1038/nprot.2011.308
43. P. Shannon, A. Markiel, O. Ozier, N.S. Baliga, J.T. Wang, D. Ramage, N. Amin, B. Schwikowski, and T. Ideker Cytoscape: a software environment for integrated models of biomolecular interaction networks Genome Res. 13 11 2003 2498 2504 10.1101/gr.1239303
44. J. Stelling Mathematical models in microbial systems biology Curr. Opin. Microbiol. 7 5 2004 513 518 10.1016/j.mib.2004.08.004
45. I. Thiele, N. Swainston, R.M. Fleming, A. Hoppe, S. Sahoo, M.K. Aurich, H. Haraldsdottir, M.L. Mo, O. Rolfsson, M.D. Stobbe, and et al. A community-driven global reconstruction of human metabolism Nat. Biotechnol. 31 5 2013 419 425 10.1038/nbt.2488
46. M. Uhlén, E. Björling, C. Agaton, C.A.-K. Szigyarto, B. Amini, E. Andersen, A.-C. Andersson, P. Angelidou, A. Asplund, C. Asplund, and et al. A human protein atlas for normal and cancer tissues based on antibody proteomics Mol. Cell. Proteomics 4 12 2005 1920 1932 10.1074/mcp.M500279-MCP200
47. M. Uhlén, L. Fagerberg, B.M. Hallström, C. Lindskog, P. Oksvold, A. Mardinoglu, Å. Sivertsson, C. Kampf, E. Sjöstedt, A. Asplund, and et al. Tissue-based map of the human proteome Science 347 6220 2015 1260419 10.1126/science.1260419
48. M.G. Vander Heiden, L.C. Cantley, and C.B. Thompson Understanding the Warburg effect: the metabolic requirements of cell proliferation Science 324 5930 2009 1029 1033 10.1126/science.1160809
49. A. Varma, and B.Ø. Palsson Metabolic capabilities of Escherichia coli: I. Synthesis of biosynthetic precursors and cofactors J. Theor. Biol. 165 4 1993 477 502
50. A. Varma, and B.Ø. Palsson Metabolic capabilities of Escherichia coli: II. Optimal growth patterns J. Theor. Biol. 165 4 1993 503 522
51. D.S. Wishart, D. Tzur, C. Knox, R. Eisner, A.C. Guo, N. Young, D. Cheng, K. Jewell, D. Arndt, S. Sawhney, and et al. HMDB: the human metabolome database Nucleic Acids Res. 35 Suppl. 1 2007 D521 D526 10.1093/nar/gkl923
52. D.S. Wishart, C. Knox, A.C. Guo, R. Eisner, N. Young, B. Gautam, D.D. Hau, N. Psychogios, E. Dong, S. Bouatra, and et al. HMDB: a knowledgebase for the human metabolome Nucleic Acids Res. 37 Suppl. 1 2009 D603 D610 10.1093/nar/gkn810
53. D.S. Wishart, T. Jewison, A.C. Guo, M. Wilson, C. Knox, Y. Liu, Y. Djoumbou, R. Mandal, F. Aziat, E. Dong, and et al. HMDB 3.0 - the human metabolome database in 2013 Nucleic Acids Res. 2012 gks1065 10.1093/nar/gks1065
54. K. Yizhak, S.E. Le Dvdec, V.M. Rogkoti, F. Baenke, V.C. de Boer, C. Frezza, A. Schulze, B. van de Water, and E. Ruppin A computational study of the Warburg effect identifies metabolic targets inhibiting cancer migration Mol. Syst. Biol. 10 2014 744 10.15252/msb.20134993