Prediction of novel drug indications using network driven biological data prioritization and integration

Journal of Cheminformatics

Volumn 6, Issue 1, 2014, Pages

  Qabaja, Ala ^a,d   Alshalalfa, Mohammed ^a,c   Alanazi, Eisa ^b,f   Alhajj, Reda ^a,e  

^a UNIVERSITY OF CALGARY   (Canada)

^b UNIVERSITY OF REGINA   (Canada)

^c PALESTINE POLYTECHNIC UNIVERSITY   (Palestine)

^d AN NAJAH NATIONAL UNIVERSITY   (Palestine)

^e GLOBAL UNIVERSITY   (Lebanon)

^f UMM AL QURA UNIVERSITY   (Saudi Arabia)

Author keywords

Disease; Drug; Gene; Protein networks

Indexed keywords

EID: 84929627416     PISSN: None     EISSN: 17582946     Source Type: Journal    
DOI: 10.1186/1758-2946-6-1     Document Type: Article

References (37)

1. DiMasi J, Hansen R, Grabowski H: The price of innovation: new estimates of drug development costs. J Health Econ 2003,22(2):151-185.
2. Chong C, Sullivan D: New uses for old drugs. Nature 2007,448(7154):645-646.
3. Pujol A, Mosca R, Farrés J, Aloy P: Unveiling the role of network and systems biology in drug discovery. Trends Pharmacol Sci 2010,31(3):115-123.
4. Jones D: Pathways to cancer therapy. Nat Rev Drug Discov 2008,7(11):875-876.
5. Yap Y, Zhang X, Smith D, Soong R, Hill J: Molecular gene expression signature patterns for gastric cancer diagnosis. Comput Biol Chem 2007,31(4):275-287.
6. Walsh C, Ogawa S, Karahashi H, Scoles D, Pavelka J: ERCC5 is a novel biomarker of ovarian cancer prognosis. J Clin Oncol 2008,26(18):2952-2958.
7. Wang W, Guo X, Duan C, Ma W, Zhang Y: Comparative analysis of gene expression profiles between the normal human cartilage and the one with endemic osteoarthritis. Osteoarthritis Cartilage 2009,17(1):83-90.
8. Hu G, Agarwal P: Human disease-drug network based on genomic expression profiles. PloS One 2009,4(8):e6536.
9. Gardner T, di Bernardo D, Lorenz D, JJ C: Inferring genetic networks and identifying compound mode of action via expression profiling. Science 2003,301(5629):102-107.
10. Lamb J, Crawford E, Peck D, Modell J, Blat I, Wrobel M, Lerner J, Brunet J, Subramanian A, Ross K, Reich M, Lander E, Golub T: The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease. Science 2006,313(5795):1929-1935.
11. Sirota M, Dudley J, Kim J, Sage J, Butte A: Discovery and preclinical validation of drug indications using compendia of public gene expression data. Sci Transl Med 2011,3(96):96ra77.
12. Iorio F, Bosotti R, Scacheri E, Isacchi A, di Bernardo D: Discovery of drug mode of action and drug repositioning from transcriptional responses. Proc Natl Acad Sci USA 2010,107(33):14621-14627.
13. Subramanian A, Tamayo P, Mootha V, Golub T, Lander E, Mesirov J: Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 2005,102(43):15545-15550.
14. Nitsch D, Tranchevent L, Gonçalves J, Vogt J, Madeira S, Moreau Y: PINTA: a web server for network-based gene prioritization from expression data. Nucleic Acids Res 2011, 39:W334-W338.
15. Taylor I, Linding R, Warde-Farley D, Pawson T, Morris Q, Wrana J: Dynamic modularity in protein interaction networks predicts breast cancer outcome. Nature Biotechnol 2009,27(2):199-204.
16. Reverter A, Hudson N, Nagaraj S, Pérez-Enciso M, Dalrymple B: Regulatory impact factors: unraveling the transcriptional regulation of complex traits from expression data. Bioinformatics 2010,26(7):896-904.
17. Wu C, Zhu J, Zhang X: Integrating gene expression and protein-protein interaction network to prioritize cancer-associated genes. BMC Bioinformatics 2012, 13:182-195.
18. Cheng D, Knox C, Young N, Stothard P, Damaraju S, Wishart D: PolySearch: a web-based text mining system for extracting relationships between human diseases, genes, mutations, drugs and metabolites. Nucleic Acids Res 2008, 36:W399-W405.
19. Li J, Zhu X, Chen J: Building disease-specific drug-protein connectivity maps from molecular interaction networks and PubMed abstracts. PLoS Comput Biol 2009,5(7):e1000450.
20. Chen J, Aronow B, Jegga A: Disease candidate gene identification and prioritization using protein interaction networks. BMC Bioinformatics 2009, 10:73-83.
21. Ozgür A, Vu T, Erkan G, Radev D: Identifying gene-disease associations using centrality on a literature mined gene-interaction network. Bioinformatics 2008,24(13):277-285.
22. Gottlieb A, Stein G, Ruppin E, Sharan R: PREDICT: a method for inferring novel drug indications with application to personalized medicine. Mol Syst Biol 2011, 7:496.
23. Cheng A, Coleman R, Smith K, Cao Q, Soulard P, Caffrey D, Salzberg A, Huang E: Structure-based maximal affinity model predicts small-molecule druggability. Nat Biotechnol 2007,25(1):71-76.
24. Knox C, Law V, Jewison T, Guo A, Wishart D: DrugBank 3.0: a comprehensive resource for 'omics' research on drugs. Nucleic Acids Res 2011, 39:D1035-D1041.
25. Wu G, Feng X, Stein L: A human functional protein interaction network and its application to cancer data analysis. Genome Biol 2010,11(5):R53.
26. Lamb J, Crawford E, Peck D, Modell J, Blat I, Wrobel M, Lerner J, Brunet J, Subramanian A, Ross K, Reich M, Lander E, Golub T: The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease. Science 2006,313(5795):1929-1935.
27. Irizarry R, Bolstad B, Collin F, Cope L, Hobbs B, Speed T: Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res 2003, 31:4.
28. Tusher V, Tibshirani R, Chu G: Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA 2001,98(9):5116-51121.
29. Szklarczyk D, Franceschini A, Jensen L, Mering C: The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Res 2011, 39:D561-D568.
30. Cui Q, Ma Y, Jaramillo M, Purisima E, Wang E: A map of human cancer signaling. Mol Syst Biol 2007, 3:152.
31. Bastian M, Heymann S, Jacomy M: Gephi: an open source software for exploring and manipulating networks. AAAI Conference on Weblogs and Social Media 2009.
32. Festuccia C, Gravina G, D'Alessandro A, Vicentini C, Bologna M: Azacitidine improves antitumor effects of docetaxel and cisplatin in aggressive prostate cancer models. Endocr Relat Cancer 2009,16(2):401-413.
33. Gravina G, Festuccia C, Millimaggi D, Dolo V, Vicentini B: Chronic Azacitidine treatment results in differentiating effects, sensitizes against bicalutamide in androgen-independent prostate cancer cells. Rostate 2008,68(7):793-801.
34. Wang Y, Liu Q, Gong Y, Shao C: Berberine, a genotoxic alkaloid, induces ATM-Chk1 mediated G2 arrest in prostate cancer cells. Mutat Res 2012,734(1):20-29.
35. Li J, Cao B, Dong Y: Berberine suppresses androgen receptor signaling in prostate cancer. Mol Cancer Ther 2011,10(8):1346-1356.
36. He Q, Li J, Yin W, Gao J: Low-dose paclitaxel enhances the anti-tumor efficacy of GM-CSF surface-modified whole-tumor-cell vaccine in mouse model of prostate cancer. Cancer Immuno Immunother 2011,60(5):715-730.
37. Lu P, Yu C, Chiang P, Chen Y, Ho Y, Kung F, Guh F: Paclitaxes induces apoptosis through activation of nuclear protein kinas and subsequent activation of Golgi associated Cdk1 in human hormone refractory prostate cancer. J Urol 2011,186(6):2434-2441.