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Meta-Analysis of Gene Expression Microarray Data: Degradome Genes in Healthy and Cancer Tissues

  • Kristiina Iljin
  • Sami Kilpinen
  • Johanna Ivaska
  • Olli Kallioniemi

Abstract

The “degradome” set of genes comprises proteases and their inhibitors. These genes may have distinct roles in normal tissues as well as in tumor development and progression. In order to systematically investigate which proteases are overexpressed in cancers, we studied the mRNA expression patterns of degradome genes across healthy and malignant human tissues using our In Silico Transcriptomics (IST) database which covers gene expression data from over 70 different normal tissue types and 50 tumor types. The analysis of nearly 500 degradome gene expression profiles across all major human tissues and malignancies gave a comprehensive view of the expression of proteases in healthy and diseased tissues. Interestingly, the most distinct clusters enriched in protease inhibitors were detected from normal tissues, such as liver, highlighting the tight control of extracellular matrix remodeling. Furthermore, normal tissues and their corresponding cancer tissues clustered separately in most cases, indicating significant alteration in protease expression during carcinogenesis. More detailed analysis of matrix metalloproteinase (MMP) gene expression patterns validated many previously published findings such as overexpression of MMP13 gene in several cancer types as well as downregulation of MMP28 in colorectal cancers. In addition, meta-analysis revealed novel aspects on MMPs, such as elevated MMP12 gene expression in several cancer types where it had not been previously studied. Furthermore, we performed in silico coexpression analyses to obtain insights on biological processes which may be associated with MMP12 expression. The most significant associations were found with mitosis and inflammatory response. Taken together, we demonstrate novel, unprecedented possibilities for rapid discovery of biological insights, putative biomarkers, and therapeutic targets using in silico analysis of existing gene expression datasets.

Keywords

Coexpression Network Vasculogenic Mimicry Gene Expression Microarray Data Human Airway Smooth Muscle Cell MMP12 mRNA Expression 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science + Business Media, LLC 2008

Authors and Affiliations

  • Kristiina Iljin
    • 1
  • Sami Kilpinen
    • 1
  • Johanna Ivaska
    • 1
  • Olli Kallioniemi
    • 1
  1. 1.Medical BiotechnologyVTT Technical Research Centre of Finland and University of TurkuTurkuFinland

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