Comparative network analysis via differential graphlet communities

Proteomics

Volumn 15, Issue 2-3, 2015, Pages 608-617

  Wong, Serene W H ^a,b   Cercone, Nick ^a   Jurisica, Igor ^b,c  

^a YORK UNIVERSITY   (Canada)

^b UNIVERSITY HEALTH NETWORK   (Canada)

^c UNIVERSITY OF TORONTO   (Canada)

Author keywords

Comparative network analysis; Differential graphlet communities; Non small cell lung cancer; Systems Biology

Indexed keywords

BRUTON TYROSINE KINASE; CASPASE 10; CHEMOKINE RECEPTOR CCR2; CHEMOKINE RECEPTOR CCR7; INTERFERON REGULATORY FACTOR 4; INTERLEUKIN 16; INTERLEUKIN 7 RECEPTOR; MITOGEN ACTIVATED PROTEIN KINASE 1; PROTEIN KINASE LCK; PROTEIN TYROSINE PHOSPHATASE; STAT3 PROTEIN; PROTEIN;

ARTICLE; CD8+ T LYMPHOCYTE; GENE EXPRESSION; HUMAN; MOLECULAR BIOLOGY; NON SMALL CELL LUNG CANCER; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN INTERACTION; COMPARATIVE STUDY; GENE EXPRESSION REGULATION; GENETICS; LUNG; LUNG TUMOR; METABOLISM; PROCEDURES; PROTEIN PROTEIN INTERACTION; SIGNAL TRANSDUCTION; SYSTEMS BIOLOGY;

CARCINOMA, NON-SMALL-CELL LUNG; GENE EXPRESSION REGULATION, NEOPLASTIC; HUMANS; LUNG; LUNG NEOPLASMS; PROTEIN INTERACTION MAPPING; PROTEIN INTERACTION MAPS; PROTEINS; SIGNAL TRANSDUCTION; SYSTEMS BIOLOGY;

EID: 84921321474     PISSN: 16159853     EISSN: 16159861     Source Type: Journal    
DOI: 10.1002/pmic.201400233     Document Type: Article

References (47)

1. de la Fuente, A., From 'differential expression' to 'differential networking'-identification of dysfunctional regulatory networks in diseases. Trends Genet. 2010, 26, 326-333.
2. Cui, X., Churchill, G. A., Statistical tests for differential expression in cDNA microarray experiments. Genome Biol. 2003, 4, 210.
3. Boutros, P. C., Lau, S. K., Pintilie, M., Liu, N. et al., Prognostic gene signatures for non-small-cell lung cancer. Proc. Natl. Acad. Sci. USA 2009, 106, 2824-2828.
4. Jeong, H., Mason, S. P., Barabási, A. L., Oltvai, Z. N., Lethality and centrality in protein networks. Nat. Brief Comm. 2001, 411, 41-42.
5. Pržulj, N., Wigle, D., Jurisica, I., Functional topology in a network of protein interactions. Bioinformatics 2004, 20, 340-348.
6. Jonsson, P. F., Bates, P. A., Global topological features of cancer proteins in the human interactome. Bioinformatics 2006, 22, 2291-2297.
7. Ideker, T., Ozier, O., Schwikowski, B., Siegel, A. F., Discovering regulatory and signalling circuits in molecular interaction networks. Bioinformatics 2002, 18 (Suppl. 1), S233-S240.
8. 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.
9. Fortney, K., Kotlyar, M., Jurisica, I., Inferring the functions of longevity genes with modular subnetwork biomarkers of Caenorhabditis elegans aging. Genome Biol. 2010, 11, R13.
10. Choi, J. K., Yu, U., Yoo, O. J., Kim, S., Differential coexpression analysis using microarray data and its application to human cancer. Bioinformatics 2005, 21, 4348-4355.
11. Fuller, T. F., Ghazalpour, A., Aten, J. E., Drake, T. A. et al., Weighted gene coexpression network analysis strategies applied to mouse weight. Mamm. Genome 2007, 18, 463-472.
12. Watson, M., CoXpress: differential co-expression in gene expression data. BMC Bioinformatics 2006, 7, 509.
13. Qiu, P., Wang, Z. J., Liu, K. J. R., Hu, Z. Z., Wu, C. H., Dependence network modeling for biomarker identification. Bioinformatics 2007, 23, 198-206.
14. Zhang, B., Li, H., Riggins, R. B., Zhan, M. et al., Differential dependency network analysis to identify condition-specific topological changes in biological networks. Bioinformatics 2009, 25, 526-532.
15. Pržulj, N., Biological network comparison using graphlet degree distribution. Bioinformatics 2007, 23, e177-e183.
16. Pržulj, N., Milenkovi, T., Computational methods for analyzing and modeling biological networks, in: Chen, J., Lonardi, S. (Eds.), Biological Data Mining, Chapman & Hall/CRC, Boca Raton, FL 2009, pp. 397-428.
17. Pržulj, N., Graph theory analysis of protein-protein interactions, in: Jurisica, I., Wigle, D. (Eds.), Knowledge Discovery in Proteomics, volume 8 of Chapman and Hall/CRC Mathematical Biology and Medicine Series, CRC Press Taylor and Francis Group, Boca Raton, FL 2006, pp. 73-128.
18. Pržulj, N., Corneil, D. G., Jurisica, I., Modeling interactome: scale-free or geometric? Bioinformatics 2004, 20, 3508-3515.
19. Wong, S., Kotlyar, M., Strumpf, D., Cercone, N. et al., Systematic, comparative network analysis on non-small cell lung cancer [abstract]. Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research, volume 72 of Cancer Research, Abstract nr 4912, Chicago 2012.
20. Garey, M. R., Johnson, D. S., Computers and Intractability-A Guide to the Theory of NP-Completeness. W. H. Freeman and Company, San Francisco, CA 1979.
21. Omidi, S., Schreiber, F., Masoudi-Nejad, A., MODA: an efficient algorithm for network motif discovery in biological networks. Genes Genet. Syst. 2009, 84, 385-395.
22. Palla, G., Derényi, I., Farkas, I., Vicsek, T., Uncovering the overlapping community structure of complex networks in nature and society. Nature 2005, 435, 814-818.
23. Hou, J., Aerts, J., den Hamer, B., van Ijcken, W. et al., Gene expression-based classification of non-small cell lung carcinomas and survival prediction. PLoS One 2010, 5, e10312.
24. Su, L., Chang, C., Wu, Y., Chen, K. et al., Selection of DDX5 as a novel internal control for Q-RT-PCR from microarray data using a block bootstrap re-sampling scheme. BMC Genomics 2007, 8, 140.
25. Landi, M. T., Dracheva, T., Rotunno, M., Figueroa, J. D. et al., Gene expression signature of cigarette smoking and its role in lung adenocarcinoma development and survival. PLoS One 2008, 3, e1651.
26. Edgar, R., Domrachev, M., Lash, A. E., Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002, 30, 207-210.
27. Lu, T. P., Tsai, M. H., Lee, J. M., Hsu, C. et al., Identification of a novel biomarker, SEMA5A, for non- small cell lung carcinoma in nonsmoking women. Cancer Epidemiol. Biomarkers Prev. 2010, 19, 2590-2597.
28. Sanchez-Palencia, A., Gomez-Morales, M., Gomez-Capilla, J. A., Pedraza, V. et al., Gene expression profiling reveals novel biomarkers in nonsmall cell lung cancer. Int. J. Cancer 2011, 129, 355-364.
29. Okayama, H., Kohno, T., Ishii, Y., Shimada, Y. et al., Identification of genes upregulated in ALK-positive and EGFR/KRAS/ALK-negative lung adenocarcinomas. Cancer Res. 2012, 72, 100-111.
30. Girard, L., Minna, J. D., Gerald, W. L., Saintigny, P., Zhang, L., MSKCC-a primary lung cancer specimens. Gene Express. Omnibus GSE31547, 2011.
31. Brown, K. R., Otasek, D., Ali, M., McGuffin, M. J. et al., NAViGaTOR: network analysis, visualization and graphing Toronto. Bioinformatics 2009, 25, 3327-3329.
32. Romero, P., Wagg, J., Green, M. L., Kaiser, D. et al., Computational prediction of human metabolic pathways from the complete human genome. Genome Biol. 2004, 6, R2.
33. Kanehisa, M., Goto, S., KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000, 28, 27-30.
34. Schaefer, C. F., Anthony, K., Krupa, S., Buchoff, J. et al., PID: the pathway interaction database. Nucleic Acids Res. 2009, 37, D674-D679.
35. Matthews, L., Gopinath, G., Gillespie, M., Caudy, M. et al., Reactome knowledgebase of human biological pathways and processes. Nucleic Acids Res. 2009, 37, D619-D622.
36. Bader, G., Cerami, E., Gross, B., Sander, C., The Cancer Cell Map, The Computational Biology Center at Memorial Sloan-Kettering Cancer Center and the Institute of Bioinformatics. http://cancer.cellmap.org/cellmap/home.do.
37. Cerami, E. G., Gross, B. E., Demir, E., Rodchenkov, I. et al., Pathway commons, a web resource for biological pathway data. Nucleic Acids Res. 2011, 39, D685-D690.
38. Binns, D., Dimmer, E., Huntley, R., Barrell, D. et al., QuickGO: a web-based tool for Gene Ontology searching. Bioinformatics 2009, 25, 3045-3046.
39. Grivennikov, S., Karin, M., Dangerous liaisons: STAT3 and NF-kappaB collaboration and crosstalk in cancer. Cytokine Growth Factor Rev. 2010, 21, 11-19.
40. Dauer, D. J., Ferraro, B., Song, L., Yu, B. et al., Stat3 regulates genes common to both wound healing and cancer. Oncogene 2005, 24, 3397-3408.
41. Bremnes, R. M., Al-Shibli, K., Donnem, T., Sirera, R. et al., The role of tumor-infiltrating immune cells and chronic inflammation at the tumor site on cancer development, progression, and prognosis: emphasis on non-small cell lung cancer. J. Thorac. Oncol. 2011, 6, 824-833.
42. Bonecchi, R., Galliera, E., Borroni, E. M., Corsi, M. M. et al., Chemokines and chemokine receptors: an overview. Front Biosci. 2009, 14, 540-551.
43. Yu, H., Kortylewski, M., Pardoll, D., Crosstalk between cancer and immune cells: role of STAT3 in the tumour microenvironment. Nat. Rev. Immunol. 2007, 7, 41-51.
44. Shinners, N. P., Carlesso, G., Castro, I., Hoek, K. L. et al., Bruton's tyrosine kinase mediates NF- kappaB activation and B cell survival by B cell-activating factor receptor of the TNF-R family. J. Immunol. 2007, 179, 3872-3880.
45. Shuai, K., Liu, B., Regulation of JAK-STAT signalling in the immune system. Nat. Rev. Immunol. 2003, 3, 900-911.
46. Doody, K. M., Bourdeau, A., Tremblay, M. L., T-cell protein tyrosine phosphatase is a key regulator in immune cell signaling: lessons from the knockout mouse model and implications in human disease. Immunol. Rev. 2009, 228, 325-341.
47. Geer, L. Y., Marchler-Bauer, A., Geer, R. C., Han, L. et al., The NCBI BioSystems database. Nucleic Acids Res. 2010, 38, D492-D496.