Xiang Yang, Kogel Ulrike, Gebel Stephan, Peck Michael J, Peitsch Manuel C, Akmaev Viatcheslav R, Hoeng Julia
Philip Morris Research and Development, Neuchâtel, Switzerland.
Philip Morris Research Laboratories GmbH, Köln, Germany.
Gene Regul Syst Bio. 2014 Feb 19;8:45-61. doi: 10.4137/GRSB.S13140. eCollection 2014.
Chronic obstructive pulmonary disease (COPD) is a respiratory disorder caused by extended exposure of the airways to noxious stimuli, principally cigarette smoke (CS). The mechanisms through which COPD develops are not fully understood, though it is believed that the disease process includes a genetic component, as not all smokers develop COPD. To investigate the mechanisms that lead to the development of COPD/emphysema, we measured whole genome gene expression and several COPD-relevant biological endpoints in mouse lung tissue after exposure to two CS doses for various lengths of time. A novel and powerful method, Reverse Engineering and Forward Simulation (REFS™), was employed to identify key molecular drivers by integrating the gene expression data and four measured COPD-relevant endpoints (matrix metalloproteinase (MMP) activity, MMP-9 levels, tissue inhibitor of metalloproteinase-1 levels and lung weight). An ensemble of molecular networks was generated using REFS™, and simulations showed that it could successfully recover the measured experimental data for gene expression and COPD-relevant endpoints. The ensemble of networks was then employed to simulate thousands of in silico gene knockdown experiments. Thirty-three molecular key drivers for the above four COPD-relevant endpoints were therefore identified, with the majority shown to be enriched in inflammation and COPD.
慢性阻塞性肺疾病(COPD)是一种由于气道长期暴露于有害刺激物(主要是香烟烟雾(CS))而引起的呼吸系统疾病。虽然并非所有吸烟者都会患上COPD,但人们认为该疾病的发病过程包括遗传因素,不过COPD的发病机制尚未完全明确。为了研究导致COPD/肺气肿发生的机制,我们在小鼠肺组织暴露于两种不同剂量的香烟烟雾不同时长后,测量了全基因组基因表达以及几个与COPD相关的生物学终点。我们采用了一种新颖且强大的方法——逆向工程与正向模拟(REFS™),通过整合基因表达数据和四个测量得到的与COPD相关的终点指标(基质金属蛋白酶(MMP)活性、MMP-9水平、金属蛋白酶组织抑制剂-1水平和肺重量)来识别关键分子驱动因素。使用REFS™生成了一组分子网络,模拟结果表明它能够成功恢复基因表达和与COPD相关终点指标的实测实验数据。然后利用这组网络模拟了数千次计算机基因敲除实验。由此确定了上述四个与COPD相关终点指标的33个分子关键驱动因素,其中大多数在炎症和COPD中表现出富集。