Comparative meta-analysis between human and mouse cancer microarray data reveals critical pathways

Authors:
Pankaj Chopra;Jaewoo Kang;Seung-Mo Hong
Affiliations:
Department of Computer Science, North Carolina State University, Raleigh, NC 27695, USA;Department of Computer Science and Engineering, College of Information and Communication, Korea University, Seoul, Korea 136-713;Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea 138-736
Venue:
International Journal of Data Mining and Bioinformatics
Year:
2013

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Abstract

Identification of deregulated biomolecular pathways in cancer may be more important than identification of individual genes through differential expression. We have analysed data from 87 microarray datasets, spanning 25 different types of cancer, and have identified several hundred pathways that are statistically significant p < 0.01 and deregulated in cancer. We also conducted a meta-analysis of 18 mouse cancer datasets and found that a statistically significant number of ontology terms are common between human and mouse cancers and known for their role in carcinogenesis. These point to critical pathways that are disrupted in both human and mouse cancers.