Title

Insight into redox-regulated gene networks in vascular cells

Authors

Charles D Johnson¹, Yoganand Balagurunathan², Edward R. Dougherty², Cynthia A Afshari³, Qiang He¹ and Kenneth S. Ramos^1*

Affiliation

¹Department of Biochemistry and Molecular Biology, University of Louisville, Louisville, Kentucky - 40292; ²Department of Electrical Engineering, Texas A&M University, College Station, Texas - 77843; ³Amgen Corporation, Thousand Oaks, CA - 91320

Email

kenneth.ramos@louisville.edu

Phone

+502 852 5217

Fax

+502 852 6221; * Corresponding author

Article Type

Prediction Model

Date

received November 06, 2006; accepted January 21, 2007; published online April 10, 2007

Abstract

To understand the complex nature of the atherogenic response initiated by oxidative stress in vascular smooth muscle cells (vSMCs), computational prediction methodology was employed to define putative gene-gene and gene-environment interactions in vSMCs subjected to oxidative chemical stress. Computational relationships were derived from the global gene expression profiles of murine cells challenged with a chemical pro-oxidant to cause oxidative stress or cells treated with anti-oxidant prior to oxidative injury. Target clones were chosen based on their biological relevance within the context of the atherogenic response and included lysyl oxidase, matrix metalloproteinase 2, insulin like growth factor binding protein 5, and lymphocyte antigen 6c. Established biological relationships were derived computationally confirming the usefulness of the algorithm in uncovering novel biological relationships worthy of future investigation. Thus, the predictive algorithm can be a useful tool to advance the frontiers of biological discovery. 

Keywords

gene networks; vascular cells; oxidative stress; redox

Citation

Edited by

Susmita Datta

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.