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Delineation of a Gene Network Underlying the Pulmonary Response to Oxidative Stress in Asthma
  1. Robert J. Freishtat, MD, MPH*†‡,
  2. Angela S. Benton, BAS,
  3. Alan M. Watson, PhD†§,
  4. Zuyi Wang, PhD†∥,
  5. Mary C. Rose, PhD†‡,
  6. Eric P. Hoffman, PhD†‡
  1. From the *Division of Emergency Medicine, †Research Center for Genetic Medicine, Children's National Medical Center; ‡School of Medicine and Health Sciences, §Institute of Biomedical Sciences, The George Washington University, NW, Washington, DC; and ∥The Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA.
  1. Received March 25, 2009, and in revised form July 15, 2009.
  2. Accepted for publication July 15, 2009.
  3. Reprints: Robert J. Freishtat, MD, MPH, Division of Emergency Medicine, Children's National Medical Center, 111 Michigan Ave, NW, Washington, DC 20010. E-mail: rfreishtat{at}cnmcresearch.org.
  4. Supported by the National Institutes of Health, Bethesda, MD, via grant K23-RR-020069 to RJF and institutional funding from Children's National Medical Center.

Abstract

Cigarette smoke exposure induces a respiratory epithelial response that is mediated in part by oxidative stress. The contribution of oxidative stress to cigarette smoke-induced responses in asthmatic respiratory epithelium is not well understood. We sought to increase this understanding by employing data integration and systems biology approaches to publicly available microarray data deposited over the last several years. In this study, we analyzed 14 publicly available asthma- or tobacco-relevant data series and found 4 (2 mice and 2 human) that fulfilled adequate signal/noise thresholds using unsupervised clustering and F test statistics. Using significance filters and a 4-way Venn diagram approach, we identified 26 overlapping genes in the epithelial transcriptional stress response to cigarette smoke and asthma. This test set corresponded to a 26-member gene/protein network containing 18 members that were highly regulated in a fifth data series of direct lung oxidative stress. Of those network members, 2 stood out (ie, tissue inhibitor of metalloproteinase 1 and thrombospondin 1) owing to central location within the network and marked up-regulation sustained at later times in response to oxidative stress. These analyses identified key relationships and primary hypothetical targets for future studies of cigarette smoke-induced oxidative stress in asthma.

Key Words
  • asthma
  • microarray analysis
  • tobacco smoke pollution
  • reactive oxygen species

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