Integrative analysis of the transcriptome and targetome identifies the regulatory network of miR-16: An inhibitory role against the activation of hepatic stellate cells

Bio-Medical Materials and Engineering

Volumn 24, Issue 6, 2014, Pages 3863-3871

  Qin, Pan ^a   Canjie, Guo ^b   Chao, Sun ^a   Jiangao, Fan ^a,c   Chunhua, Fang ^d  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b SHANGHAI JIAO TONG UNIVERSITY SCHOOL OF MEDICINE   (China)

^c Shanghai Key Laboratory of Children's Digestion and Nutrition   (China)

^d TONGJI UNIVERSITY   (China)

Author keywords

Hepatic stellate cell; MiR 16; Network; Targetome; Transcriptome

Indexed keywords

ALGORITHMS; CELL DEATH; CHEMICAL ACTIVATION; ITERATIVE METHODS; NETWORK LAYERS; NETWORKS (CIRCUITS); SEARCH ENGINES;

DIJKSTRA'S ALGORITHMS; HEPATIC STELLATE CELLS; INTEGRATIVE ANALYSIS; ITERATIVE ALGORITHM; MIR-16; REGULATORY NETWORK; TARGETOME; TRANSCRIPTOMES;

ACTIVATION ANALYSIS;

LENTIVIRUS VECTOR; MICRORNA 16; RNA; TARGETOME; TRANSCRIPTOME; UNCLASSIFIED DRUG; MICRORNA; MIRN16 MICRORNA, HUMAN; TRANSCRIPTION FACTOR;

ALGORITHM; ANIMAL EXPERIMENT; APOPTOSIS; BIOINFORMATICS; CELL ACTIVATION; CELL PROLIFERATION; CONFERENCE PAPER; DATA BASE; GENE EXPRESSION; MALE; NONHUMAN; PHENOTYPE; RAT; RNA HYBRIDIZATION; STELLATE CELL; CYTOLOGY; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORK; GENE TARGETING; GENETICS; HUMAN; PHYSIOLOGY; TRANSCRIPTION INITIATION;

CELL PROLIFERATION; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORKS; GENE TARGETING; HEPATIC STELLATE CELLS; HUMANS; MICRORNAS; TRANSCRIPTION FACTORS; TRANSCRIPTIONAL ACTIVATION; TRANSCRIPTOME;

EID: 84907270502     PISSN: 09592989     EISSN: 18783619     Source Type: Journal    
DOI: 10.3233/BME-141217     Document Type: Conference Paper

References (20)

1. C.J. Guo, Q. Pan, B. Jiang, G.Y. Chen and D.G. Li, Effects of upregulated expression of microRNA-16 on biological properties of culture-activated hepatic stellate cells, Apoptosis 14 (2009), 1331-1340.
2. L.P. Lim, N.C. Lau, P. Garrett-Engele, A. Grimson, J.M. Schelter, J. Castle, D.P. Bartel, P.S. Linsley and J.M. Johnson, Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs, Nature 433 (2005), 769-773.
3. G.W. Wright and R.M. Simon, A random variance model for detection of differential gene expression in small microarray experiments, Bioinformatics 19 (2003), 2448-2455.
4. S. Griffiths-Jones, R.J. Grocock, S. van Dongen, A. Bateman and A.J. Enright, miRBase: microRNA sequences, targets and gene nomenclature, Nucleic Acids Res. 34 (2006), D140-D144.
5. B.P. Lewis, C.B. Burge and D.P. Bartel, Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets, Cell 120 (2005), 15-20.
6. G.D. Bader, I. Donaldson, C. Wolting, B.F. Ouellette, T. Pawson and C.W. Hogue, BIND-the biomolecular interaction network database, Nucleic Acids Research 29 (2001), 242-245.
7. A. Chatr-Aryamontri, B.J. Breitkreutz, S. Heinicke, L. Boucher, A. Winter, C. Stark, J. Nixon, L. Ramage, N. Kolas, L. O'Donnell, T. Reguly, A. Breitkreutz, A. Sellam, D. Chen, C. Chang, J. Rust, M. Livstone, R. Oughtred, K. Dolinski and M. Tyers, The BioGRID interaction database: 2013 update, Nucleic Acids Research 41 (2013), D816-D823.
8. M. Kanehisa, Molecular network analysis of diseases and drugs in KEGG, Methods in Molecular Biology 939 (2013), 263-275.
9. T.M. Chan, K.C. Wong, K.H. Lee, M.H. Wong, C.K. Lau, S.K. Tsui and K.S. Leung, Discovering approximateassociated sequence patterns for protein-DNA interactions, Bioinformatics 27 (2011), 471-478.
10. M. He, Q.Y. Wang, Q.Q. Yin, J. Tang, Y. Lu, C.X. Zhou, C.W. Duan, D.L. Hong, T. Tanaka, G.Q. Chen and Q. Zhao, HIF-1- downregulates miR-17/20a directly targeting p21 and STAT3: a role in myeloid leukemic cell differentiation, Cell Death Differ. 20 (2013), 408-418.
11. M. Yi, J.D. Horton, J.C. Cohen, H.H. Hobbs and R.M. Stephens, Whole Pathway Scope: a comprehensive pathwaybased analysis tool for high-throughput data, BMC Bioinformatics 7 (2006), 30-53.
12. J. Jiang, X. Yuan, H. Zhao, X. Yan, X. Sun and Q. Zheng, Licochalcone A inhibiting proliferation of bladder cancer T24 cells by inducing reactive oxygen species production, Bio-Medical Materials and Engineering 24 (2014), 1019-1025.
13. L.D. Hernández-Ortega, B.E. Alcántar-Díaz, L.A. Ruiz-Corro, A. Sandoval-Rodriguez, M. Bueno-Topete, J. Armendariz-Borunda and A.M. Salazar-Montes, Quercetin improves hepatic fibrosis reducing hepatic stellate cells and regulating pro-fibrogenic/anti-fibrogenic molecules balance, Journal of Gastroenterology and Hepatology 27 (2012), 1865-1872.
14. Y.B. Ji, C.F. Ji and L. Yue, Human gastric cancer cell line SGC-7901 apoptosis induced by SFPS-B2 via a mitochondrial-mediated pathway, Bio-Medical Materials and Engineering 24 (2014), 1141-1147.
15. R.L. Kortum, A.K. Rouquette-Jazdanian and L.E. Samelson, Ras and extracellular signal-regulated kinase signaling in thymocytes and T cells, Trends in Immunology 34 (2013), 259-268.
16. N. Maeda, N. Kawada, S. Seki, T. Arakawa, K. Ikeda, H. Iwao, H. Okuyama, J. Hirabayashi, K. Kasai and K. Yoshizato, Stimulation of proliferation of rat hepatic stellate cells by galectin-1 and galectin-3 through different intracellular signaling pathways, Journal of Biological Chemistry 278 (2003), 18938-18944.
17. A. Hauburger, S. von. Einem, G.K. Schwaerzer, A. Buttstedt, M. Zebisch, M. Schräml, P. Hortschansky, P. Knaus and E. Schwarz, The pro-form of BMP-2 interferes with BMP-2 signalling by competing with BMP-2 for IA receptor binding, FEBS Journal 276 (2009), 6386-6398.
18. Q. Liu, X. Wang, Y. Zhang, C.J. Li, L.H. Hu and X. Shen, Leukamenin F suppresses liver fibrogenesis by inhibiting both hepatic stellate cell proliferation and extracellular matrix production, Acta. Pharmacologica. Sinica. 31 (2010), 839-848.
19. G. Wang, C. Chen, R. Yang, X. Cao, S. Lai, X. Luo, Y. Feng, X. Xia, J. Gong and J. Hu, p55PIK-PI3K stimulates angiogenesis in colorectal cancer cell by activating NF-B pathway, Angiogenesis 16 (2013), 561-573.
20. P. Ramanathan, I.C. Martin, M. Gardiner-Garden, P.C. Thomson, R.M. Taylor, C.J. Ormandy, C. Moran and P. Williamson, Transcriptome analysis identifies pathways associated with enhanced maternal performance in QSi5 mice, BMC Genomics 9 (2008), 197-209.