The Hallmarks of Cancer Revisited Through Systems Biology and Network Modelling

  • Charles Auffray
  • Trey Ideker
  • David J. Galas
  • Leroy Hood
Chapter

Abstract

Since 10 years ago, when the seven hallmarks of cancer were first defined by Hanahan and Weinberg, after decades of molecular, cellular and clinical investigations, new systems-based approaches have provided a wide range of improved investigative methods. These approaches integrate various global data types into mathematical and computational models of molecular and cellular pathways and networks that become dysregulated in cancer, since the models are now able to take into account the large-scale properties of complex biological networks. Genome variation and instability have been revisited through study of genetic and genomic networks; while transcription and protein interaction networks are revealing cancer biomarkers of modular change. Growth, proliferation and apoptosis are being more fully described by signalling network modelling. Sustained angiogenesis and metastasis are being addressed via multiscale modelling. Enhanced understanding of the initial hallmarks of cancer, extended to the control of metabolism and stress, is opening novel avenues for cancer diagnosis and treatment. It is fully expected that further progress will take place through iterative cycles of experimentation and modelling, typical of systems biology. All of this will require advances in molecular data acquisition, multiscale integration of data scales and types, new approaches to data analysis and improved modelling. Success in all these endeavours cannot be achieved without better cross-disciplinary interactions among researchers and technologists.

Keywords

Data Data Markov Logic Network Growth Growth Disease Disease Network Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

We thank Odile Brasier for secretarial assistance. Eruption of the Eyjafjöll provided the opportunity to complete this chapter on time.

References

  1. Aebersold R, Auffray C et al (2009) Report on EU-USA workshop: how systems biology can advance cancer research (27 October 2008). Mol Oncol 3(1):9–17PubMedCrossRefGoogle Scholar
  2. Ahn AC, Tewari M et al (2006a) The clinical applications of a systems approach. PLoS Med 3(7):e209CrossRefGoogle Scholar
  3. Ahn AC, Tewari M et al (2006b) The limits of reductionism in medicine: could systems biology offer an alternative? PLoS Med 3(6):e208CrossRefGoogle Scholar
  4. Aldridge BB, Burke JM et al (2006) Physicochemical modeling of cell signaling pathways. Nat Cell Biol 8(11):1195–1203PubMedCrossRefGoogle Scholar
  5. Aldridge BB, Saez-Rodriguez J et al (2009) Fuzzy logic analysis of kinase pathway crosstalk in TNF/EGF/insulin-induced signaling. PLoS Comput Biol 5(4):e1000340PubMedCrossRefGoogle Scholar
  6. Alon U (2007) Network motifs: theory and experimental approaches. Nat Rev Genet 8(6):450–461PubMedCrossRefGoogle Scholar
  7. Anderson AR, Quaranta V (2008) Integrative mathematical oncology. Nat Rev Cancer 8(3):227–234PubMedCrossRefGoogle Scholar
  8. Anderson AR, Weaver AM et al (2006) Tumor morphology and phenotypic evolution driven by selective pressure from the microenvironment. Cell 127(5):905–915PubMedCrossRefGoogle Scholar
  9. Ao P, Galas D et al (2008) Cancer as robust intrinsic state of endogenous molecular-cellular network shaped by evolution. Med Hypotheses 70(3):678–684PubMedCrossRefGoogle Scholar
  10. Auffray C (2007) Protein subnetwork markers improve prediction of cancer outcome. Mol Syst Biol 3:141PubMedCrossRefGoogle Scholar
  11. Auffray C, Chen Z et al (2009) Systems medicine: the future of medical genomics and healthcare. Genome Med 1(1):2PubMedCrossRefGoogle Scholar
  12. Auffray C, Imbeaud S et al (2003) From functional genomics to systems biology: concepts and practices. C R Biol 326(10–11):879–892PubMedCrossRefGoogle Scholar
  13. Auffray C, Noble D (2009) Origins of systems biology in William Harvey's masterpiece on the movement of the heart and the blood in animals. Int J Mol Sci 10(4):1658–1669PubMedCrossRefGoogle Scholar
  14. Auffray C, Nottale L (2008) Scale relativity theory and integrative systems biology: 1. Founding principles and scale laws. Prog Biophys Mol Biol 97(1):79–114PubMedCrossRefGoogle Scholar
  15. Barabasi AL (2007) Network medicine—from obesity to the “diseasome”. N Engl J Med 357(4):404–407PubMedCrossRefGoogle Scholar
  16. Barabasi AL, Albert R (1999) Emergence of scaling in random networks. Science 286(5439):509–512PubMedCrossRefGoogle Scholar
  17. Barabasi AL, Oltvai ZN (2004) Network biology: understanding the cell’s functional organization. Nat Rev Genet 5(2):101–113PubMedCrossRefGoogle Scholar
  18. Barrett CL, Palsson BO (2006) Iterative reconstruction of transcriptional regulatory networks: an algorithmic approach. PLoS Comput Biol 2(5):e52PubMedCrossRefGoogle Scholar
  19. Bartkova J, Rezaei N et al (2006) Oncogene-induced senescence is part of the tumorigenesis barrier imposed by DNA damage checkpoints. Nature 444(7119):633–637PubMedCrossRefGoogle Scholar
  20. Bassingthwaighte J, Hunter P et al (2009) The Cardiac Physiome:perspectives for the future. Exp Physiol 94(5): 597–605PubMedCrossRefGoogle Scholar
  21. Beckman RA, Loeb LA (2005) Genetic instability in cancer: theory and experiment. Semin Cancer Biol 15(6):423–435PubMedCrossRefGoogle Scholar
  22. Benz CC, Yau C (2008) Ageing, oxidative stress and cancer: paradigms in parallax. Nat Rev Cancer 8(11):875–879PubMedCrossRefGoogle Scholar
  23. Bild AH, Potti A et al (2006a) Linking oncogenic pathways with therapeutic opportunities. Nat Rev Cancer 6(9):735–741CrossRefGoogle Scholar
  24. Bild AH, Yao G et al (2006b) Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature 439(7074):353–357CrossRefGoogle Scholar
  25. Billy F, Ribba B et al (2009) A pharmacologically based multiscale mathematical model of angiogenesis and its use in investigating the efficacy of a new cancer treatment strategy. J Theor Biol 260(4):545–562PubMedCrossRefGoogle Scholar
  26. Bizzarri M, Cucina A et al (2008) Beyond the oncogene paradigm: understanding complexity in cancerogenesis. Acta Biotheor 56(3):173–196PubMedCrossRefGoogle Scholar
  27. Bluthgen N, Legewie S et al (2009) A systems biological approach suggests that transcriptional feedback regulation by dual-specificity phosphatase 6 shapes extracellular signal-related kinase activity in RAS-transformed fibroblasts. FEBS J 276(4):1024–1035PubMedCrossRefGoogle Scholar
  28. Bonneau R (2008) Learning biological networks: from modules to dynamics. Nat Chem Biol 4(11):658–664PubMedCrossRefGoogle Scholar
  29. Bonneau R, Reiss DJ et al (2006) The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo. Genome Biol 7(5):R36PubMedCrossRefGoogle Scholar
  30. Bonneau R, Facciotti MT et al (2007) A predictive model for transcriptional control of physiology in a free living cell. Cell 131(7):1354–1365PubMedCrossRefGoogle Scholar
  31. Borisov N, Aksamitiene E et al (2009) Systems-level interactions between insulin-EGF networks amplify mitogenic signaling. Mol Syst Biol 5:256PubMedCrossRefGoogle Scholar
  32. Boros LG, Cascante M et al (2002) Metabolic profiling of cell growth and death in cancer: applications in drug discovery. Drug Discov Today 7(6):364–372PubMedCrossRefGoogle Scholar
  33. Bosl WJ (2007) Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery. BMC Syst Biol 1:13PubMedCrossRefGoogle Scholar
  34. Braun A, Samann A et al (2008) Effects of metabolic control, patient education and initiation of insulin therapy on the quality of life of patients with type 2 diabetes mellitus. Patient Educ Couns 73(1):50–59PubMedCrossRefGoogle Scholar
  35. Butte AJ (2008) Medicine. The ultimate model organism. Science 320(5874):325–327Google Scholar
  36. Brynildsen MP, Collins JJ (2009) Systems biology makes it personal. Mol Cell 34(2):137–138PubMedCrossRefGoogle Scholar
  37. Byrne HM (2010) Dissecting cancer through mathematics: from the cell to the animal model. Nat Rev Cancer 10(3):221–230Google Scholar
  38. Cancer Genome Atlas Research Network (2008) Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 455(7216):1061–1068CrossRefGoogle Scholar
  39. Carrivick L, Rogers S et al (2006) Identification of prognostic signatures in breast cancer microarray data using Bayesian techniques. J R Soc Interface 3(8):367–381PubMedCrossRefGoogle Scholar
  40. Carro MS, Lim WK et al (2010) The transcriptional network for mesenchymal transformation of brain tumours. Nature 463(7279):318–325Google Scholar
  41. Carter GW, Galas DJ et al (2009) Maximal extraction of biological information from genetic interaction data. PLoS Comput Biol 5(4):e1000347PubMedCrossRefGoogle Scholar
  42. Cascante M, Boros LG et al (2002) Metabolic control analysis in drug discovery and disease. Nat Biotechnol 20(3):243–249PubMedCrossRefGoogle Scholar
  43. Cascante M, Marin S (2008) Metabolomics and fluxomics approaches. Essays Biochem 45:67–81PubMedCrossRefGoogle Scholar
  44. Chang JT, Carvalho C et al (2009) A genomic strategy to elucidate modules of oncogenic pathway signaling networks. Mol Cell 34(1):104–114PubMedCrossRefGoogle Scholar
  45. Chang LW, Payton JE et al (2008) Computational identification of the normal and perturbed genetic networks involved in myeloid differentiation and acute promyelocytic leukemia. Genome Biol 9(2):R38PubMedCrossRefGoogle Scholar
  46. Chaplain MA, McDougall SR et al (2006) Mathematical modeling of tumor-induced angiogenesis. Annu Rev Biomed Eng 8:233–257PubMedCrossRefGoogle Scholar
  47. Chen LL, Blumm N et al (2009) Cancer metastasis networks and the prediction of progression patterns. Br J Cancer 101(5):749–758PubMedCrossRefGoogle Scholar
  48. Cho KH, Kim JR et al (2006) Inferring biomolecular regulatory networks from phase portraits of time-series expression profiles. FEBS Lett 580(14):3511–3518PubMedCrossRefGoogle Scholar
  49. Chuang HY, Lee E et al (2007) Network-based classification of breast cancer metastasis. Mol Syst Biol 3:140PubMedCrossRefGoogle Scholar
  50. Citri A, Yarden Y (2006) EGF-ERBB signaling: towards the systems level. Nat Rev Mol Cell Biol 7(7):505–516PubMedCrossRefGoogle Scholar
  51. Clermont G, Auffray C et al (2009) Bridging the gap between systems biology and medicine. Genome Med 1(9):88PubMedCrossRefGoogle Scholar
  52. Cline MS, Smoot M et al (2007) Integration of biological networks and gene expression data using Cytoscape. Nat Protoc 2(10):2366–2382PubMedCrossRefGoogle Scholar
  53. Colotta F, Allavena P et al (2009) Cancer-related inflammation, the seventh hallmark of cancer: links to genetic instability. Carcinogenesis 30(7):1073–1081PubMedCrossRefGoogle Scholar
  54. Cui Q, Ma Y et al (2007) A map of human cancer signaling. Mol Syst Biol 3:152PubMedCrossRefGoogle Scholar
  55. Cusick ME, Klitgord N et al (2005) Interactome: gateway into systems biology. Hum Mol Genet 14(Spec No. 2):R171–R181PubMedCrossRefGoogle Scholar
  56. Davidson EH, Rast JP et al (2002) A genomic regulatory network for development. Science 295(5560):1669–1678PubMedCrossRefGoogle Scholar
  57. Deberardinis RJ, Sayed N et al (2008) Brick by brick: metabolism and tumor cell growth. Curr Opin Genet Dev 18(1):54–61PubMedCrossRefGoogle Scholar
  58. Debily MA, Marhomy SE et al (2009) A functional and regulatory network associated with PIP expression in human breast cancer. PLoS One 4(3):e4696PubMedCrossRefGoogle Scholar
  59. Dewhirst MW, Cao Y et al (2008) Cycling hypoxia and free radicals regulate angiogenesis and radiotherapy response. Nat Rev Cancer 8(6):425–437PubMedCrossRefGoogle Scholar
  60. Diehn M, Cho RW et al (2009) Association of reactive oxygen species levels and radioresistance in cancer stem cells. Nature 458(7239):780–783PubMedCrossRefGoogle Scholar
  61. Ding L, Ellis MJ et al (2010) Genome remodeling in a basal-like breast cancer metastasis and xenograft. Nature 464(7291):999–1005Google Scholar
  62. Ding L, Getz G et al (2008) Somatic mutations affect key pathways in lung adenocarcinoma. Nature 455(7216):1069–1075PubMedCrossRefGoogle Scholar
  63. DiPaola RS, Dvorzhinski D et al (2008) Therapeutic starvation and autophagy in prostate cancer: a new paradigm for targeting metabolism in cancer therapy. Prostate 68(16):1743–1752PubMedCrossRefGoogle Scholar
  64. Du Y, Wang K et al (2006) Coordination of intrinsic, extrinsic, and endoplasmic reticulum-mediated apoptosis by imatinib mesylate combined with arsenic trioxide in chronic myeloid leukemia. Blood 107(4):1582–1590PubMedCrossRefGoogle Scholar
  65. Duarte NC, Becker SA et al (2007) Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci U S A 104(6):1777–1782PubMedCrossRefGoogle Scholar
  66. Farmer H, McCabe N et al (2005) Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy. Nature 434(7035):917–921PubMedCrossRefGoogle Scholar
  67. Fell DA (2005) Enzymes, metabolites and fluxes. J Exp Bot 56(410):267–272PubMedCrossRefGoogle Scholar
  68. Ferreira SC Jr, Martins ML et al (2002) Reaction-diffusion model for the growth of avascular tumor. Phys Rev E Stat Nonlin Soft Matter Phys 65(2 Pt 1):021907PubMedCrossRefGoogle Scholar
  69. Folkman J (2007) Angiogenesis: an organizing principle for drug discovery? Nat Rev Drug Discov 6(4):273–286PubMedCrossRefGoogle Scholar
  70. Ganem NJ, Storchova Z et al (2007) Tetraploidy, aneuploidy and cancer.Curr Opin Genet Dev 17(2):157–162PubMedCrossRefGoogle Scholar
  71. Garinis GA, van der Horst GT et al (2008) DNA damage and ageing: newage ideas for an age-old problem. Nat cell Biol 10(11):1241–1247PubMedCrossRefGoogle Scholar
  72. Gianchandani EP, Brautigan DL et al (2006) Systems analyses characterize integrated functions of biochemical networks. Trends Biochem Sci 31(5):284–291PubMedCrossRefGoogle Scholar
  73. Gogvadze V, Orrenius S et al (2008) Mitochondria in cancer cells: what is so special about them? Trends Cell Biol 18(4):165–173PubMedCrossRefGoogle Scholar
  74. Goh KI, Cusick ME et al (2007) The human disease network. Proc Natl Acad Sci U S A 104(21):8685–8690PubMedCrossRefGoogle Scholar
  75. Gorgoulis VG, Vassiliou LV et al (2005) Activation of the DNA damage checkpoint and genomic instability in human precancerous lesions. Nature 434(7035):907–913PubMedCrossRefGoogle Scholar
  76. Graudens E, Boulanger V et al (2006) Deciphering cellular states of innate tumor drug responses. Genome Biol 7(3):R19PubMedCrossRefGoogle Scholar
  77. Greenman C, Stephens P et al (2007) Patterns of somatic mutation in human cancer genomes. Nature 446(7132):153–158PubMedCrossRefGoogle Scholar
  78. Halazonetis TD, Gorgoulis VG et al (2008) An oncogene-induced DNA damage model for cancer development. Science 319(5868):1352–1355PubMedCrossRefGoogle Scholar
  79. Harper JW, Elledge SJ (2007) The DNA damage response: ten years after. Mol Cell 28(5):739–745PubMedCrossRefGoogle Scholar
  80. Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100(1):57–70PubMedCrossRefGoogle Scholar
  81. Heiser LM, Wang NJ et al (2009) Integrated analysis of breast cancer cell lines reveals unique signaling pathways. Genome Biol 10(3):R31PubMedCrossRefGoogle Scholar
  82. Holland AJ, Cleveland DW (2009) Boveri revisited: chromosomal instability, aneuploidy and tumorigenesis. Nat Rev Mol Cell Biol 10(7):478–487PubMedCrossRefGoogle Scholar
  83. Hood L, Heath JR et al (2004) Systems biology and new technologies enable predictive and preventative medicine. Science 306(5696):640–643PubMedCrossRefGoogle Scholar
  84. Hornberg JJ, Bruggeman FJ et al (2007) Metabolic control analysis to identify optimal drug targets. Prog Drug Res 64:171, 173–189PubMedCrossRefGoogle Scholar
  85. Hu M, Polyak K (2008) Microenvironmental regulation of cancer development. Curr Opin Genet Dev 18(1):27–34PubMedCrossRefGoogle Scholar
  86. Huang S, Ernberg I et al (2009) Cancer attractors: a systems view of tumors from a gene network dynamics and developmental perspective. Semin Cell Dev Biol 20(7):869–876PubMedCrossRefGoogle Scholar
  87. Huang SS, Fraenkel E (2009) Integrating proteomic, transcriptional, and interactome data reveals hidden components of signaling and regulatory networks. Sci Signal 2(81):ra40PubMedCrossRefGoogle Scholar
  88. Huang YJ, Hang D et al (2008) Targeting the human cancer pathway protein interaction network by structural genomics. Mol Cell Proteomics 7(10):2048–2060PubMedCrossRefGoogle Scholar
  89. Hwang D, Lee IY et al (2009) A systems approach to prion disease. Mol Syst Biol 5:252PubMedCrossRefGoogle Scholar
  90. Hwang D, Rust AG et al (2005a) A data integration methodology for systems biology. Proc Natl Acad Sci U S A 102(48):17296–17301CrossRefGoogle Scholar
  91. Hwang D, Smith JJ et al (2005b) A data integration methodology for systems biology: experimental verification. Proc Natl Acad Sci U S A 102(48):17302–17307CrossRefGoogle Scholar
  92. Ideker T, Galitski T et al (2001) A new approach to decoding life: systems biology. Annu Rev Genomics Hum Genet 2:343–372PubMedCrossRefGoogle Scholar
  93. Ideker T, Sharan R (2008) Protein networks in disease. Genome Res 18(4):644–652PubMedCrossRefGoogle Scholar
  94. Itadani H, Mizuarai S et al (2008) Can systems biology understand pathway activation? Gene expression signatures as surrogate markers for understanding the complexity of pathway activation. Curr Genomics 9(5):349–360PubMedCrossRefGoogle Scholar
  95. Janes KA, Yaffe MB (2006) Data-driven modeling of signal-transduction networks. Nat Rev Mol Cell Biol 7(11):820–828PubMedCrossRefGoogle Scholar
  96. Jiang Y, Pjesivac-Grbovic J et al (2005) A multiscale model for avascular tumor growth. Biophys J 89(6):3884–3894PubMedCrossRefGoogle Scholar
  97. Johnston MD, Edwards CM et al (2007) Mathematical modeling of cell population dynamics in the colonic crypt and in colorectal cancer. Proc Natl Acad Sci U S A 104(10):4008–4013PubMedCrossRefGoogle Scholar
  98. Jones S, Zhang X et al (2008) Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science 321(5897):1801–1806PubMedCrossRefGoogle Scholar
  99. Kaelin WG, Jr. (2005) The concept of synthetic lethality in the context of anticancer therapy. Nat Rev Cancer 5(9):689–698PubMedCrossRefGoogle Scholar
  100. Karnoub AE, Dash AB et al (2007) Mesenchymal stem cells within tumour stroma promote breast cancer metastasis. Nature 449(7162):557–563PubMedCrossRefGoogle Scholar
  101. Kirschner MW (2005) The meaning of systems biology. Cell 121(4):503–504PubMedCrossRefGoogle Scholar
  102. Kitano H (2002) Systems biology: a brief overview. Science 295(5560):1662–1664PubMedCrossRefGoogle Scholar
  103. Klemm K, Bornholdt S (2005) Topology of biological networks and reliability of information processing. Proc Natl Acad Sci U S A 102(51):18414–18419PubMedCrossRefGoogle Scholar
  104. Kohl P, Noble D (2009) Systems biology and the virtual physiological human. Mol Syst Biol 5:292PubMedCrossRefGoogle Scholar
  105. Kreeger PK, Lauffenburger DA (2010) Cancer systems biology: a network modeling perspective. Carcinogenesis 31(1):2–8Google Scholar
  106. Kreeger PK, Mandhana R et al (2009) RAS mutations affect tumor necrosis factor-induced apoptosis in colon carcinoma cells via ERK-modulatory negative and positive feedback circuits along with non-ERK pathway effects. Cancer Res 69(20):8191–8199PubMedCrossRefGoogle Scholar
  107. Kroemer G, Pouyssegur J (2008) Tumor cell metabolism: cancer’s Achilles’ heel. Cancer Cell 13(6):472–482PubMedCrossRefGoogle Scholar
  108. Kumar N, Afeyan R et al (2008) Multipathway model enables prediction of kinase inhibitor cross-talk effects on migration of Her2-overexpressing mammary epithelial cells. Mol Pharmacol 73(6):1668–1678PubMedCrossRefGoogle Scholar
  109. Lazzara MJ, Lauffenburger DA (2009) Quantitative modeling perspectives on the ErbB system of cell regulatory processes. Exp Cell Res 315(4):717–725PubMedCrossRefGoogle Scholar
  110. Lee JM, Gianchandani EP et al (2006) Flux balance analysis in the era of metabolomics. Brief Bioinform 7(2):140–150PubMedCrossRefGoogle Scholar
  111. Lee DS, Park J et al (2008) The implications of human metabolic network topology for disease comorbidity. Proc Natl Acad Sci U S A 105(29):9880–9885PubMedCrossRefGoogle Scholar
  112. Lee Y, Yang X et al (2010) Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis. PLoS Comput Biol 6(4):e1000730Google Scholar
  113. Legewie S, Herzel H et al (2008) Recurrent design patterns in the feedback regulation of the mammalian signaling network. Mol Syst Biol 4:190PubMedCrossRefGoogle Scholar
  114. Ley TJ, Mardis ER et al (2008) DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome. Nature 456(7218):66–72PubMedCrossRefGoogle Scholar
  115. Lin B, White JT et al (2005) Evidence for the presence of disease-perturbed networks in prostate cancer cells by genomic and proteomic analyses: a systems approach to disease. Cancer Res 65(8):3081–3091PubMedGoogle Scholar
  116. Linding RL, Jensen J et al (2007) Systematic discovery of in vivo phosphorylation networks. Cell 129(7):1415–1426PubMedCrossRefGoogle Scholar
  117. Lord CJ, Ashworth A (2009) Bringing DNA repair in tumors into focus. Clin Cancer Res 15(10):3241–3243PubMedCrossRefGoogle Scholar
  118. Ludwig JA, Weinstein JN (2005) Biomarkers in cancer staging, prognosis and treatment selection. Nat Rev Cancer 5(11):845–856PubMedCrossRefGoogle Scholar
  119. Luo J, Solimini NL et al (2009) Principles of cancer therapy: oncogene and non-oncogene addiction. Cell 136(5):823–837PubMedCrossRefGoogle Scholar
  120. Ma H, Sorokin A et al (2007) The Edinburgh human metabolic network reconstruction and its functional analysis. Mol Syst Biol 3:135PubMedCrossRefGoogle Scholar
  121. Macklin P, McDougall S et al (2009) Multiscale modeling and nonlinear simulation of vascular tumour growth. J Math Biol 58(4–5):765–798PubMedCrossRefGoogle Scholar
  122. Madar A, Bonneau R (2009) Learning global models of transcriptional regulatory networks from data. Methods Mol Biol 541:181PubMedCrossRefGoogle Scholar
  123. Mani KM, Lefebvre C et al (2008) A systems biology approach to prediction of oncogenes and molecular perturbation targets in B-cell lymphomas. Mol Syst Biol 4:169PubMedCrossRefGoogle Scholar
  124. Mathew R, Karantza-Wadsworth V et al (2007) Role of autophagy in cancer. Nat Rev Cancer 7(12):961–967PubMedCrossRefGoogle Scholar
  125. Mathew R, Karp CM et al (2009) Autophagy suppresses tumorigenesis through elimination of p62. Cell 137(6):1062–1075PubMedCrossRefGoogle Scholar
  126. Mazzone M, Comoglio PM (2006) The Met pathway: master switch and drug target in cancer progression. FASEB J 20(10):1611–1621PubMedCrossRefGoogle Scholar
  127. Mo ML, Jamshidi N et al (2007) A genome-scale, constraint-based approach to systems biology of human metabolism. Mol Biosyst 3(9):598–603PubMedCrossRefGoogle Scholar
  128. Mo ML, Palsson BO (2009) Understanding human metabolic physiology: a genome-to-systems approach. Trends Biotechnol 27(1):37–44PubMedCrossRefGoogle Scholar
  129. Mortazavi A, Williams BA et al (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5(7):621–628PubMedCrossRefGoogle Scholar
  130. Ngo VN, Davis RE et al (2006) A loss-of-function RNA interference screen for molecular targets in cancer. Nature 441(7089):106–110PubMedCrossRefGoogle Scholar
  131. Nguyen DX, Bos PD et al (2009) Metastasis: from dissemination to organ-specific colonization. Nat Rev Cancer 9(4):274–284PubMedCrossRefGoogle Scholar
  132. Nicholson JK, Holmes E et al (2004) The challenges of modeling mammalian biocomplexity. Nat Biotechnol 22(10):1268–1274PubMedCrossRefGoogle Scholar
  133. Noble D (2002) Modeling the heart—from genes to cells to the whole organ. Science 295(5560):1678–1682PubMedCrossRefGoogle Scholar
  134. Noble D (2008) Claude Bernard, the first systems biologist, and the future of physiology. Exp Physiol 93(1):16–26PubMedCrossRefGoogle Scholar
  135. Novak B, Tyson JJ (2008) Design principles of biochemical oscillators. Nat Rev Mol Cell Biol 9(12):981–991PubMedCrossRefGoogle Scholar
  136. Nottale L, Auffray C (2008) Scale relativity theory and integrative systems biology: 2. Macroscopic quantum-type mechanics. Prog Biophys Mol Biol 97(1):115–157PubMedCrossRefGoogle Scholar
  137. Oberhardt MA, Palsson BO et al (2009) Applications of genome-scale metabolic reconstructions. Mol Syst Biol 5:320PubMedCrossRefGoogle Scholar
  138. Oliveri P, Tu Q et al (2008) Global regulatory logic for specification of an embryonic cell lineage. Proc Natl Acad Sci U S A 105(16):5955–5962PubMedCrossRefGoogle Scholar
  139. Ornish D, Magbanua MJ et al (2008) Changes in prostate gene expression in men undergoing an intensive nutrition and lifestyle intervention. Proc Natl Acad Sci U S A 105(24):8369–8374PubMedCrossRefGoogle Scholar
  140. Ornish D, Magbanua MJ et al (2008) Changes in prostate gene expression in men undergoing an intensive nutrition and lifestyle intervention. Proc Natl Acad Sci U S A 105(24):8369–8374PubMedCrossRefGoogle Scholar
  141. Ovadi J, Saks V (2004) On the origin of intracellular compartmentation and organized metabolic systems. Mol Cell Biochem 256–257(1–2):5–12PubMedCrossRefGoogle Scholar
  142. Papin JA, Price ND et al (2003) Metabolic pathways in the post-genome era. Trends Biochem Sci 28(5):250–258PubMedCrossRefGoogle Scholar
  143. Parsons DW, Jones S et al (2008) An integrated genomic analysis of human glioblastoma multiforme. Science 321(5897):1807–1812PubMedCrossRefGoogle Scholar
  144. Pawson T, Warner N (2007) Oncogenic re-wiring of cellular signaling pathways. Oncogene 26(9):1268–1275PubMedCrossRefGoogle Scholar
  145. Pawson T, Linding R (2008) Network medicine. FEBS Lett 582(8):1266–1270PubMedCrossRefGoogle Scholar
  146. Polyak K, Haviv I et al (2009) Co-evolution of tumor cells and their microenvironment. Trends Genet 25(1):30–38PubMedCrossRefGoogle Scholar
  147. Pouyssegur J, Dayan F et al (2006) Hypoxia signaling in cancer and approaches to enforce tumour regression. Nature 441(7092):437–443PubMedCrossRefGoogle Scholar
  148. Pujana MA, Han JD et al (2007) Network modeling links breast cancer susceptibility and centrosome dysfunction. Nat Genet 39(11):1338–1349PubMedCrossRefGoogle Scholar
  149. Rachlin J, Cohen DD et al (2006) Biological context networks: a mosaic view of the interactome. Mol Syst Biol 2:66PubMedCrossRefGoogle Scholar
  150. Ramis-Conde I, Chaplain MA et al (2009) Multi-scale modeling of cancer cell intravasation: the role of cadherins in metastasis. Phys Biol 6(1):016008PubMedCrossRefGoogle Scholar
  151. Ransohoff DF (2009) Promises and limitations of biomarkers. Recent Results Cancer Res 181:55–59PubMedCrossRefGoogle Scholar
  152. Ransohoff DF, Gourlay ML (2010) Sources of bias in specimens for research about molecular markers for cancer. J Clin Oncol 28(4):698–704Google Scholar
  153. Rhodes DR, Chinnaiyan AM (2005) Integrative analysis of the cancer transcriptome. Nat Genet (37 Suppl):S31–S37Google Scholar
  154. Rhodes DR, Tomlins SA et al (2005) Probabilistic model of the human protein-protein interaction network. Nat Biotechnol 23(8):951–959PubMedCrossRefGoogle Scholar
  155. Roach JC, Glusman G et al (2010) Analysis of genetic inheritance in a family quartet by whole-genome sequencing. Science 328(5978):636–639PubMedCrossRefGoogle Scholar
  156. Ruan K, Song G et al (2009) Role of hypoxia in the hallmarks of human cancer. J Cell Biochem 107(6):1053–1062PubMedCrossRefGoogle Scholar
  157. Sakhanenko N, Galas DJ (2010) Markov logic networks in the analysis of genetic data. J Comp Biol 17(11):1491–1508Google Scholar
  158. Samaga R, Saez-Rodriguez J et al (2009) The logic of EGFR/ErbB signaling: theoretical properties and analysis of high-throughput data. PLoS Comput Biol 5(8):e1000438PubMedCrossRefGoogle Scholar
  159. Sawyers CL (2008) The cancer biomarker problem. Nature 452(7187):548–552PubMedCrossRefGoogle Scholar
  160. Schlabach MR, Luo J et al (2008) Cancer proliferation gene discovery through functional genomics. Science 319(5863):620–624PubMedCrossRefGoogle Scholar
  161. Schlitt T, Brazma A (2005) Modeling gene networks at different organisational levels. FEBS Lett 579(8):1859–1866PubMedCrossRefGoogle Scholar
  162. Schoeberl B, Pace EA et al (2009) Therapeutically targeting ErbB3: a key node in ligand-induced activation of the ErbB receptor-PI3K axis. Sci Signal 2(77):ra31PubMedCrossRefGoogle Scholar
  163. Seyfried TN, Shelton LM (2010) Cancer as a metabolic disease. Nutr Metab (Lond) 7:7Google Scholar
  164. Sheng H, Niu B et al (2009) Metabolic targeting of cancers: from molecular mechanisms to therapeutic strategies. Curr Med Chem 16(13):1561–1587PubMedCrossRefGoogle Scholar
  165. Shimoni Y, Friedlander G et al (2007) Regulation of gene expression by small non-coding RNAs: a quantitative view. Mol Syst Biol 3:138PubMedCrossRefGoogle Scholar
  166. Silva JM, Marran K et al (2008) Profiling essential genes in human mammary cells by multiplex RNAi screening. Science 319(5863):617–620PubMedCrossRefGoogle Scholar
  167. Sjoblom T, Jones S et al (2006) The consensus coding sequences of human breast and colorectal cancers. Science 314(5797):268–274PubMedCrossRefGoogle Scholar
  168. Solimini NL, Luo J et al (2007) Non-oncogene addiction and the stress phenotype of cancer cells. Cell 130(6):986–988PubMedCrossRefGoogle Scholar
  169. Spencer SL, Gaudet S et al (2009) Non-genetic origins of cell-to-cell variability in TRAIL-induced apoptosis. Nature 459(7245):428–432PubMedCrossRefGoogle Scholar
  170. Stites EC, Trampont PC et al (2007) Network analysis of oncogenic Ras activation in cancer. Science 318(5849):463–467PubMedCrossRefGoogle Scholar
  171. Strebhardt K, Ullrich A (2008) Paul Ehrlich’s magic bullet concept: 100 years of progress. Nat Rev Cancer 8(6):473–480PubMedCrossRefGoogle Scholar
  172. Tan CS, Bodenmiller B et al (2009) Comparative analysis reveals conserved protein phosphorylation networks implicated in multiple diseases. Sci Signal 2(81):ra39PubMedCrossRefGoogle Scholar
  173. Taylor IW, Linding R et al (2009) Dynamic modularity in protein interaction networks predicts breast cancer outcome. Nat Biotechnol 27(2):199–204PubMedCrossRefGoogle Scholar
  174. Tegner JN, Compte A et al (2009) Computational disease modeling—fact or fiction? BMC Syst Biol 3:56PubMedCrossRefGoogle Scholar
  175. Tennant DA, Duran RV et al (2009) Metabolic transformation in cancer. Carcinogenesis 30(8):1269–1280PubMedCrossRefGoogle Scholar
  176. Thorisson GA, Muilu J et al (2009) Genotype-phenotype databases: challenges and solutions for the post-genomic era. Nat Rev Genet 10(1):9–18PubMedCrossRefGoogle Scholar
  177. Tomlins SA, Mehra R et al (2007) Integrative molecular concept modeling of prostate cancer progression. Nat Genet 39(1):41–51PubMedCrossRefGoogle Scholar
  178. Tonon G (2008) From oncogene to network addiction: the new frontier of cancer genomics and therapeutics. Future Oncol 4(4):569–577PubMedCrossRefGoogle Scholar
  179. Torres EM, Williams BR et al (2008) Aneuploidy: cells losing their balance. Genetics 179(2):737–746PubMedCrossRefGoogle Scholar
  180. Tyson JJ, Chen K et al (2001) Network dynamics and cell physiology. NatRev Mol Cell Biol 2(12):908–916CrossRefGoogle Scholar
  181. Tyson JJ, Novak B (2008). Temporal organization of the cell cycle. Curr Biol 18(17):R759–R768CrossRefGoogle Scholar
  182. van’t Veer’ LJ, Bernards R (2008) Enabling personalized cancer medicine through analysis of gene-expression patterns. Nature 452(7187):564–570CrossRefGoogle Scholar
  183. Varambally S, Yu J et al (2005) Integrative genomic and proteomic analysis of prostate cancer reveals signatures of metastatic progression. Cancer Cell 8(5):393–406PubMedCrossRefGoogle Scholar
  184. Velculescu VE, Kinzler KW (2007) Gene expression analysis goes digital. Nat Biotechnol 25(8):878–880PubMedCrossRefGoogle Scholar
  185. Vogelstein B, Kinzler KW (2004) Cancer genes and the pathways they control. Nat Med 10(8):789–799PubMedCrossRefGoogle Scholar
  186. Wang Z, Zhang L et al (2007) Simulating non-small cell lung cancer with a multiscale agent-based model. Theor Biol Med Model 4:50PubMedCrossRefGoogle Scholar
  187. Wang Z, Birch CM et al (2009) Cross-scale, cross-pathway evaluation using an agent-based non-small cell lung cancer model. Bioinformatics 25(18):2389–2396PubMedCrossRefGoogle Scholar
  188. Weinberg RA (2006) The biology of cancer. New York, Taylor and FrancisGoogle Scholar
  189. Weinstein IB (2002) Cancer. Addiction to oncogenes—the Achilles heal of cancer. Science 297(5578):63–64PubMedCrossRefGoogle Scholar
  190. Weinstein IB, Joe A (2008) Oncogene addiction. Cancer Res 68(9):3077–3080; discussion 3080PubMedCrossRefGoogle Scholar
  191. Wells JA, McClendon CL (2007) Reaching for high-hanging fruit in drug discovery at protein-protein interfaces. Nature 450(7172):1001–1009PubMedCrossRefGoogle Scholar
  192. Westerhoff HV, Palsson BO (2004) The evolution of molecular biology into systems biology. Nat Biotechnol 22(10):1249–1252PubMedCrossRefGoogle Scholar
  193. Whitesell L, Lindquist SL (2005) HSP90 and the chaperoning of cancer. Nat Rev Cancer 5(10):761–772PubMedCrossRefGoogle Scholar
  194. Williams BR, Prabhu VR et al (2008) Aneuploidy affects proliferation and spontaneous immortalization in mammalian cells. Science 322(5902):703–709PubMedCrossRefGoogle Scholar
  195. Wolkenhauer O (2001) Systems biology: the reincarnation of systems theory applied in biology? Brief Bioinform 2(3):258–270PubMedCrossRefGoogle Scholar
  196. Wolkenhauer O, Auffray C et al (2010) Systems biologists seek fuller integration of systems biology approaches in new cancer research programs. Cancer Res 70(1):12–13PubMedCrossRefGoogle Scholar
  197. Wong PK, Yu F et al (2008) Closed-loop control of cellular functions using combinatory drugs guided by a stochastic search algorithm. Proc Natl Acad Sci U S A 105(13):5105–5110PubMedCrossRefGoogle Scholar
  198. Wood LD, Parsons DW et al (2007) The genomic landscapes of human breast and colorectal cancers. Science 318(5853):1108–1113PubMedCrossRefGoogle Scholar
  199. Wu JQ, Du J et al (2008) Systematic analysis of transcribed loci in ENCODE regions using RACE sequencing reveals extensive transcription in the human genome. Genome Biol 9(1):R3PubMedCrossRefGoogle Scholar
  200. Yeger-Lotem E, Sattath S et al (2004) Network motifs in integrated cellular networks of transcription-regulation and protein-protein interaction. Proc Natl Acad Sci U S A 101(16):5934–5939PubMedCrossRefGoogle Scholar
  201. Yildirim MA, Goh KI et al (2007) Drug-target network. Nat Biotechnol 25(10):1119–1126PubMedCrossRefGoogle Scholar
  202. Yuan JM, Hu DW (2006) Time-dependent sensitivity analysis of biological networks: coupled MAPK andPI3K signal transduction pathways. J Phys Chem A110:5361–5370Google Scholar
  203. Zerhouni EA (2005) Translational and clinical science – time for a new vision. N Engl J Med 353(15):1621–1623PubMedCrossRefGoogle Scholar
  204. Zheng PZ, Wang KK et al (2005) Systems analysis of transcriptome and proteome in retinoic acid/arsenic trioxide-induced cell differentiation/apoptosis of promyelocytic leukemia. Proc Natl Acad Sci U S A 102(21):7653–7658PubMedCrossRefGoogle Scholar
  205. Zou W (2005) Immunosuppressive networks in the tumour environment and their therapeutic relevance. Nat Rev Cancer 5(4):263–274PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Charles Auffray
    • 1
  • Trey Ideker
    • 2
  • David J. Galas
    • 3
  • Leroy Hood
    • 3
  1. 1.Functional Genomics and Systems Biology for HealthCNRS Institute of Biological Sciences – 7VillejuifFrance
  2. 2.Departments of Medicine and BioengineeringUniversity of California San DiegoCAUSA
  3. 3.Institute for Systems BiologySeattle, WAUSA

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