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Article type: Research Article
Authors: Creighton, Chad | Hanash, Samir
Affiliations: Bioinformatics Program, University of Michigan, Ann Arbor, MI 48109, USA | Departments of Pediatrics and Communicable Diseases, University of Michigan, Ann Arbor, MI 48109, USA
Note: [] Corresponding author: Chad Creighton, Bioinformatics Program, University of Michigan, Ann Arbor, MI 48109, USA. Tel.: +1 734 763 0917; Fax: +1 734 615 4637; E-mail: [email protected]
Abstract: Matrix metalloproteinases (MMPs) are endopeptidases considered to be important regulators of the microenvironment of cancer. While MMPs are traditionally associated with the extracellular matrix (ECM), here we provide new evidence from an analysis of gene expression profiles from human tumor tissue that MMP-9 (gelatinase B) is associated with elements of the immune system in a way analogous to the association of other MMPs, such as MMP-2 (gelatinase A), with components of the ECM. An analysis of three independent microarray datasets of lung adenocarcinomas from previous studies [Nat. Med. 8, 816–824 (2002); Proc. Natl. Acad. Sci. USA 98, 13790–13795 (2001); Proc. Natl. Acad. Sci. USA, 98, 13784–13789 (2001)] showed that, in each dataset, out of the set of genes with significant correlations in mRNA expression to the expression of MMP9 (P < 0.005), a highly disproportionate number were found to be annotated in the Locuslink database as having a role in the anti-pathogen response. By comparison, out of the set of genes significantly correlated with the expression of MMP2, a highly disproportionate number were known components of the ECM. The same patterns observed in the lung data for both MMP2 and MMP9 were found as well in an additional published dataset of colon and ovarian adenocarcinomas [Am. J. Pathol. 159, 1231–1238 (2001)]. The results of this study suggest a greater functional role for MMP-9 in the immune response to cancer than what may previously have been thought.
Keywords: matrix metalloproteinases, microarrays, MMP9, data mining, immune response
Journal: In Silico Biology, vol. 3, no. 3, pp. 301-311, 2003
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