Signalling entropy: A novel network-theoretical framework for systems analysis and interpretation of functional omic data

Methods

Volumn 67, Issue 3, 2014, Pages 282-293

  Teschendorff, Andrew E ^a,b   Sollich, Peter ^c   Kuehn, Reimer ^c  

^a MAX PLANCK INSTITUTE   (Germany)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

^c KING'S COLLEGE LONDON   (United Kingdom)

Author keywords

Cancer; Differentiation; Drug resistance; Entropy; Genomics; Network; Signalling; Stem cell

Indexed keywords

HISTONE DEACETYLASE 1; HISTONE DEACETYLASE 2; MYC PROTEIN; PROTEIN P53; STAT3 PROTEIN; TRANSCRIPTION FACTOR NANOG;

ARTICLE; CANCER CELL; CELL DIFFERENTIATION; CONTROLLED STUDY; DRUG SENSITIVITY; EMBRYONIC STEM CELL; ENTROPY; ENVIRONMENTAL STRESS; GENE DUPLICATION; GENE EXPRESSION; HUMAN; HUMAN CELL; INTRACELLULAR SIGNALING; MULTIPOTENT STEM CELL; PLURIPOTENT STEM CELL; PRIORITY JOURNAL; PROTEIN EXPRESSION; SIGNAL TRANSDUCTION; SIGNALLING ENTROPY; SYSTEM ANALYSIS; TUMOR SUPPRESSOR GENE; BIOLOGICAL MODEL; DRUG RESISTANCE; PROCEDURES; SYSTEMS BIOLOGY;

DRUG RESISTANCE; ENTROPY; MODELS, BIOLOGICAL; SIGNAL TRANSDUCTION; SYSTEMS BIOLOGY;

EID: 84901439430     PISSN: 10462023     EISSN: 10959130     Source Type: Journal    
DOI: 10.1016/j.ymeth.2014.03.013     Document Type: Article

References (61)

1. Hood L., Rowen L. The human genome project: big science transforms biology and medicine. Genome Med. 2013, 5(9):79.
2. Tcga N. Integrated genomic analyses of ovarian carcinoma. Nature 2011, 474(7353):609-615.
3. Hanahan D., Weinberg R.A. Hallmarks of cancer: the next generation. Cell 2011, 144(5):646-674.
4. Barabasi A.L., Gulbahce N., Loscalzo J. Network medicine: a network-based approach to human disease. Nat. Rev. Genet. 2011, 12(1):56-68.
5. Creixell P., Schoof E.M., Erler J.T., Linding R. Navigating cancer network attractors for tumor-specific therapy. Nat. Biotechnol. 2012, 30(9):842-848.
6. Weng G., Bhalla U.S., Iyengar R. Complexity in biological signaling systems. Science 1999, 284(5411):92-96.
7. Barabasi A.L. Network science. Philos. Trans. A: Math. Phys. Eng. Sci. 2013, 371(1987):20120375.
8. Teschendorff A.E., Severini S. Increased entropy of signal transduction in the cancer metastasis phenotype. BMC Syst. Biol. 2010, 4:104.
9. West J., Bianconi G., Severini S., Teschendorff A.E. Differential network entropy reveals cancer system hallmarks. Sci. Rep. 2012, 2:802.
10. Barabasi A.L., Oltvai Z.N. Network biology: understanding the cell's functional organization. Nat. Rev. Genet. 2004, 5(2):101-113.
11. Robin X., Creixell P., Radetskaya O., Costa Santini C., Longden J., Linding R. Personalized network-based treatments in oncology. Clin. Pharmacol. Ther. 2013, 94(6):646-650.
12. Erler J.T., Linding R. Network medicine strikes a blow against breast cancer. Cell 2012, 149(4):731-733.
13. Lee M.J., Ye A.S., Gardino A.K., Heijink A.M., Sorger P.K., MacBeath G., Yaffe M.B. Sequential application of anticancer drugs enhances cell death by rewiring apoptotic signaling networks. Cell 2012, 149(4):780-794.
14. Carro M.S., Lim W.K., Alvarez M.J., Bollo R.J., Zhao X., Snyder E.Y., Sulman E.P., Anne S.L., Doetsch F., Colman H., Lasorella A., Aldape K., Califano A., Iavarone A. The transcriptional network for mesenchymal transformation of brain tumours. Nature 2010, 463(7279):318-325.
15. Lefebvre C., Rieckhof G., Califano A. Reverse engineering human regulatory networks. Wiley Interdiscip. Rev. Syst. Biol. Med. 2012, 4(4):311-325.
16. Segal E., Friedman N., Koller D., Regev A. A module map showing conditional activity of expression modules in cancer. Nat. Genet. 2004, 36(10):1090-1098.
17. Opgen-Rhein R., Strimmer K. From correlation to causation networks: a simple approximate learning algorithm. BMC Syst. Biol. 2007, 1:37.
18. Barzel B., Barabasi A.L. Network link prediction by global silencing of indirect correlations. Nat. Biotechnol. 2013, 31(8):720-725.
19. Feizi S., Marbach D., Medard M., Kellis M. Network deconvolution as a general method to distinguish direct dependencies in. Nat. Biotechnol. 2013, 31(8):726-733.
20. Chuang H.Y., Lee E., Liu Y.T., Lee D., Ideker T. Network-based classification of breast cancer metastasis. Mol. Syst. Biol. 2007, 3:140.
21. J. Dutkowski, T. Ideker, Protein networks as logic functions in development and cancer, PLoS. Comput. Biol. 7(9) (2011) e1002180.
22. Mitra K., Carvunis A.R., Ramesh S.K., Ideker T. Integrative approaches for finding modular structure in biological networks. Nat. Rev. Genet. 2013, 14(10):719-732.
23. Prasad T.S., Kandasamy K., Pandey A. Human protein reference database and human proteinpedia as discovery tools for systems biology. Methods Mol. Biol. 2009, 577:67-79.
24. E.G. Cerami, B.E. Gross, E. Demir, I. Rodchenkov, O. Babur, N. Anwar, N. Schultz, G.D. Bader, C. Sander, Pathway commons, a web resource for biological pathway data, Nucleic Acids Res 39 (Database) (2011) D685-D690.
25. Vidal M., Cusick M.E., Barabasi A.L. Interactome networks and human disease. Cell 2011, 144(6):986-998.
26. Ulitsky I., Shamir R. Identification of functional modules using network topology and high-throughput data. BMC Syst. Biol. 2007, 1:8.
27. Taylor I.W., Linding R., Warde-Farley D., Liu Y., Pesquita C., Faria D., Bull S., Pawson T., Morris Q., Wrana J.L. Dynamic modularity in protein interaction networks predicts breast cancer outcome. Nat. Biotechnol. 2009, 27(2):199-204.
28. West J., Beck S., Wang X., Teschendorff A.E. An integrative network algorithm identifies age-associated differential methylation interactome hotspots targeting stem-cell differentiation pathways. Sci. Rep. 2013, 3:1630.
29. Roy J., Winter C., Isik Z., Schroeder M. Network information improves cancer outcome prediction. Brief Bioinform. 2012, Epub.
30. Winter C., Kristiansen G., Kersting S., Roy J., Aust D., Knosel T., Rummele P., Jahnke B., Hentrich V., Ruckert F., Niedergethmann M., Weichert W., Bahra M., Schlitt H.J., Settmacher U., Friess H., Buchler M., Saeger H.D., Schroeder M., Pilarsky C., Grutzmann R. Google goes cancer: improving outcome prediction for cancer patients by. PLoS Comput. Biol. 2012, 8(5):e1002511.
31. Suthram S., Beyer A., Karp R.M., Eldar Y., Ideker T. eqed: an efficient method for interpreting eqtl associations using protein. Mol. Syst. Biol. 2008, 4:162.
32. Kim Y.A., Wuchty S., Przytycka T.M. Identifying causal genes and dysregulated pathways in complex diseases. PLoS Comput. Biol. 2011, 7(3):e1001095.
33. Komurov K., White M.A., Ram P.T. Use of data-biased random walks on graphs for the retrieval of context-specific networks from genomic data. PLoS Comput. Biol. 2010, 6(8):e1000889.
34. Komurov K., Tseng J.T., Muller M., Seviour E.G., Moss T.J., Yang L., Nagrath D., Ram P.T. The glucose-deprivation network counteracts lapatinib-induced toxicity in. Mol. Syst. Biol. 2012, 8:596.
35. Bandyopadhyay S., Mehta M., Kuo D., Sung M.K., Chuang R., Jaehnig E.J., Bodenmiller B., Licon K., Copeland W., Shales M., Fiedler D., Dutkowski J., Gunol A., van Attikum H., Shokat K.M., Kolodner R.D., Huh W.K., Aebersold R., Keogh M.C., Krogan N.J., Ideker T. Rewiring of genetic networks in response to dna damage. Science 2010, 330(6009):1385-1389.
36. Califano A. Rewiring makes the difference. Mol. Syst. Biol. 2011, 7:463.
37. Ideker T., Krogan N.J. Differential network biology. Mol. Syst. Biol. 2012, 8:565.
38. Banerji C.R., Miranda-Saavedra D., Severini S., Widschwendter M., Enver T., Zhou J.X., Teschendorff A.E. Cellular network entropy as the energy potential in waddington's differentiation landscape. Sci. Rep. 2013, 3:3039.
39. Chang H.H., Hemberg M., Barahona M., Ingber D.E., Huang S. Transcriptome-wide noise controls lineage choice in mammalian progenitor cells. Nature 2008, 453(7194):544-547.
40. Macarthur B.D., Lemischka I.R. Statistical mechanics of pluripotency. Cell 2013, 154(3):484-489.
41. Furusawa C., Kaneko K. Chaotic expression dynamics implies pluripotency: when theory and experiment meet. Biol. Direct. 2009, 15(4):17.
42. Furusawa C., Kaneko K. A dynamical systems view of stem cell biology. Science 2012, 338(6104):215-217.
43. Lee T.I., Jenner R.G., Boyer L.A., Guenther M.G., Levine S.S., Kumar R.M., Chevalier B., Johnstone S.E., Cole M.F., Isono K., Koseki H., Fuchikami T., Abe K., Murray H.L., Zucker J.P., Yuan B., Bell G.W., Herbolsheimer E., Hannett N.M., Sun K., Odom D.T., Otte A.P., Volkert T.L., Bartel D.P., Melton D.A., Gifford D.K., Jaenisch R., Young R.A. Control of developmental regulators by polycomb in human embryonic stem cells. Cell 2006, 125(2):301-313.
44. Demetrius L., Grundlach V.M., Ochs G. Complexity and demographic stability in population models. Theor. Pop. Biol. 2004, 65:211-225.
45. Demetrius L., Manke T. Robustness and network evolution-an entropic principle. Phys. A 2005, 346:682-696.
46. Manke T., Demetrius L., Vingron M. An entropic characterization of protein interaction networks and cellular robustness. J. R. Soc. Interface 2006, 3(11):843-850.
47. Stelling J., Sauer U., Szallasi Z., Doyle F.J., Doyle J. Robustness of cellular functions. Cell 2004, 118(6):675-685.
48. Han J.D., Bertin N., Hao T., Goldberg D.S., Berriz G.F., Zhang L.V., Dupuy D., Walhout A.J., Cusick M.E., Roth F.P., Vidal M. Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Nature 2004, 430(6995):88-93.
49. Li J., Yuan Z., Zhang Z. The cellular robustness by gene redundancy in budding yeast. PLoS Genet. 2010, 6(11):e1001187.
50. Engelman J.A., Chen L., Tan X., Crosby K., Guimaraes A.R., Upadhyay R., Maira M., McNamara K., Perera S.A., Song Y., Chirieac L.R., Kaur R., Lightbown A., Simendinger J., Li T., Padera R.F., Garcia-Echeverria C., Weissleder R., Mahmood U., Cantley L.C., Wong K.K. Effective use of PI3K and MEK inhibitors to treat mutant Kras G12D and PIK3CA H1047R murine lung cancers. Nat. Med. 2008, 14(12):1351-1356.
51. Sjoblom T., Jones S., Wood L.D., Parsons D.W., Lin J., Barber T.D., Mandelker D., Leary R.J., Ptak J., Silliman N., Szabo S., Buckhaults P., Farrell C., Meeh P., Markowitz S.D., Willis J., Dawson D., Willson J.K., Gazdar A.F., Hartigan J., Wu L., Liu C., Parmigiani G., Park B.H., Bachman K.E., Papadopoulos N., Vogelstein B., Kinzler K.W., Velculescu V.E. The consensus coding sequences of human breast and colorectal cancers. Science 2006, 314(5797):268-274.
52. Wood L.D., Parsons D.W., Jones S., Lin J., Sjblom T., Leary R.J., Shen D., Boca S.M., Barber T., Ptak J., Silliman N., Szabo S., Dezso Z., Ustyanksky V., Nikolskaya T., Nikolsky Y., Karchin R., Wilson P.A., Kaminker J.S., Zhang Z., Croshaw R., Willis J., Dawson D., Shipitsin M., Willson J.K., Sukumar S., Polyak K., Park B.H., Pethiyagoda C.L., Pant P.V., Ballinger D.G., Sparks A.B., Hartigan J., Smith D.R., Suh E., Papadopoulos N., Buckhaults P., Markowitz S.D., Parmigiani G., Kinzler K.W., Velculescu V.E., Vogelstein B. The genomic landscapes of human breast and colorectal cancers. Science 2007, 318(5853):1108-1113.
53. Vogelstein B., Papadopoulos N., Velculescu V.E., Zhou S., Diaz L.A., Kinzler K.W. Cancer genome landscapes. Science 2013, 339(6127):1546-1558.
54. Latora V., Baranger M. Kolmogorov-sinai entropy rate versus physical entropy. Phys. Rev. Lett. 1999, 82(3):520-524.
55. Gomez-Gardenes J., Latora V. Entropy rate of diffusion processes on complex networks. Phys. Rev. E: Stat. Nonlin. Soft Matter Phys. 2008, 78(6):065102.
56. Friedman J. On the second eigenvalue and random walks in random d-regular graphs. Combinatorica 1991, 11. 331-262.
57. Barretina J., Caponigro G., Stransky N., Venkatesan K., Margolin A.A., Kim S., Wilson C.J., Lehr J., Kryukov G.V., Sonkin D., Reddy A., Liu M., Murray L., Berger M.F., Monahan J.E., Morais P., Meltzer J., Korejwa A., Jan-Valbuena J., Mapa F.A., Thibault J., Bric-Furlong E., Raman P., Shipway A., Engels I.H., Cheng J., Yu G.K., Yu J., Aspesi P., de Silva M., Jagtap K., Jones M.D., Wang L., Hatton C., Palescandolo E., Gupta S., Mahan S., Sougnez C., Onofrio R.C., Liefeld T., MacConaill L., Winckler W., Reich M., Li N., Mesirov J.P., Gabriel S.B., Getz G., Ardlie K., Chan V., Myer V.E., Weber B.L., Porter J., Warmuth M., Finan P., Harris J.L., Meyerson M., Golub T.R., Morrissey M.P., Sellers W.R., Schlegel R., Garraway L.A. The cancer cell line encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 2012, 483(7391):603-607.
58. J. Ahmed, T. Meinel, M. Dunkel, M.S. Murgueitio, R. Adams, C. Blasse, A. Eckert, S. Preissner, R. Preissner, Cancerresource: a comprehensive database of cancer-relevant proteins and compound interactions supported by experimental knowledge, Nucl. Acids Res. 39 (Database) (2011) D960-D967.
59. Speicher M.R. Single-cell analysis: toward the clinic. Genome Med. 2013, 5(8):74.
60. Kandasamy K., Mohan S.S., Raju R., Keerthikumar S., Kumar G.S., Venugopal A.K., Telikicherla D., Navarro J.D., Mathivanan S., Pecquet C., Gollapudi S.K., Tattikota S.G., Mohan S., Padhukasahasram H., Subbannayya Y., Goel R., Jacob H.K., Zhong J., Sekhar R., Nanjappa V., Balakrishnan L., Subbaiah R., Ramachandra Y.L., Rahiman B.A., Prasad T.S., Lin J.X., Houtman J.C., Desiderio S., Renauld J.C., Constantinescu S.N., Ohara O., Hirano T., Kubo M., Singh S., Khatri P., Draghici S., Bader G.D., Sander C., Leonard W.J., Pandey A. Netpath: a public resource of curated signal transduction pathways. Genome Biol. 2010, 11(1):R3.
61. L. Lovasz, Random walks on graphs: A survey, in: Combinatorics, Paul Erdos is Eighty, Vol. 2 of Mathematical Studies, Bolyai Society, Keszthely, Hungary, 1993, pp. 1-46.