Predicting Molecule Pathways between LOXL1 and TGF-β
DOI: 10.12677/jcpm.2013.11001, PDF, HTML, 下载: 2,799  浏览: 10,801 
作者: 龚晓楠, 施丽冰, 邹晓晖:浙江大学生命科学学院,杭州;浙江大学医学院,杭州
关键词: LOXL1TGF-β数据挖掘网络LOXL1; TGF-β; Data Mining; Network
摘要: 盆腔器官脱垂(POP)是一种盆底支持结构功能障碍性疾病,而现有的手术手段并不能根治这种疾病,因此探究POP的发病机制是一项比较有意义的研究。已有的资料表明,类氨酰氧化酶——LOXL1的敲除能够导致小鼠在分娩之后发生POP。同时TGF-β的表达量高低与POP的严重程度相关。在已经掌握资料的基础上,我们对网络上现有的海量微阵列数据进行了查找,选取了其中两个数据集进行分析。我们通过数据挖掘的方式对于POP相关的生物芯片进行相关性分析以及聚类,最后建立生物学网络。我们发现TGF-β同时通过smad与非smad通路调控LOXL1的表达,而LOXL1在细胞外基质参与黏着斑的形成、弹性纤维与胶原的交联等等。
Abstract: POP refers to a pelvic floor structure support disorder that visceras in the female pelvic cavity move down along its normal position. However, there is no radical cure for it. So it is a significant research to inquire the pathogenesis of POP. From the information already in hand, we know that LOXL1 knock-down mouse will always produce POP after delivery. In the meantime, the expression of TGF-β has a strong relationship with the severity of POP. On the basis of the data already known, we search for the massive data on the Internet and chose two data sets to do the analysis. As for data mining, we do correlation analysis and cluster on the microarrays that we had chosen. Finally, to show it more clearly, we set up a biology network. We found that TGF-β can regulate the expression of LOXL1 through the smad and non-smad pathways, meanwhile, LOXL1 is involved in the formation of focal adhesion and the crosslinking between elastin and collagen.
文章引用:龚晓楠, 施丽冰, 邹晓晖. LOXL1与TGF-β相关分子作用路径的预测[J]. 临床个性化医学, 2013, 1(1): 1-6. http://dx.doi.org/10.12677/jcpm.2013.11001


[1] Liu, X., Zhao, Y., Gao, J., et al. (2004) Elastic fiber homeostasis requires lysyl oxidase-like 1 protein. Nature Genetics, 36, 178- 182.
[2] Brizzolara, S.S., Killeen, J. and Urschitz, J. (2009) Gene expres- sion profile in pelvic organ prolapse. Molecular Human Repro- duction, 15, 59-67.
[3] Hawkins, S.M., Creighton, C.J., Han, D.Y., et al. (2011) Func- tional microRNA involved in endometriosis. Molecular Endocrinology (Baltimore, Md.), 25, 821-832.
[4] R. Core Team (2013) R: A language and environment for statis- ticalcomputing. http://www.R-project.org/
[5] Huang, D.W., Sherman, B.T. and Lempicki, R.A. (2009) Syste- matic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nature Protocols, 4, 44-57.
[6] Eisen, M.B., Spellman, P.T., Brown, P.O., et al. (1998) Cluster analysis and display of genome-wide expression patterns. Pro- ceedings of the National Academy of Sciences of USA, 95, 14863- 14868.
[7] Sethi, A., Mao, W., Wordinger, R.J., et al. (2011) Transforming growth factor-beta induces extracellular matrix protein cross- linking lysyl oxidase (LOX) genes in human trabecular mesh- work cells. Investigative Ophthalmology & Visual Science, 52, 5240-5250.
[8] Zhang, Q.C., Petrey, D., Garzon, J.I., et al. (2013) PrePPI: A structure-informed database of protein-protein interactions. Nu- cleic Acids Research, 41, D828-D833.
[9] Cline, M.S., Smoot, M., Cerami, E., et al. (2007) Integration of biological networks and gene expression data using Cytoscape. Nature Protocols, 2, 2366-2382.