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

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.

[1]  J. Cáceres-Cortés.  A potent anti-carcinoma and anti-acute myeloblastic leukemia agent, AG490. , 2008, Anti-cancer agents in medicinal chemistry.

[2]  S. Mussunoor,et al.  The role of annexins in tumour development and progression , 2008, The Journal of pathology.

[3]  Purvesh Khatri,et al.  Ontological analysis of gene expression data: current tools, limitations, and open problems , 2005, Bioinform..

[4]  D. Busam,et al.  An Integrated Genomic Analysis of Human Glioblastoma Multiforme , 2008, Science.

[5]  Dennis B. Troup,et al.  NCBI GEO: mining tens of millions of expression profiles—database and tools update , 2006, Nucleic Acids Res..

[6]  C. Sotiriou,et al.  Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures , 2007, Breast Cancer Research.

[7]  G. Milano,et al.  JAK/STAT signalling pathway in colorectal cancer: a new biological target with therapeutic implications. , 2006, European journal of cancer.

[8]  S. Moss,et al.  Annexins and disease. , 2004, Biochemical and biophysical research communications.

[9]  B. Hulsegge,et al.  A Pathway Analysis Tool for Analyzing Microarray Data of Species with Low Physiological Information , 2008, Adv. Bioinformatics.

[10]  Jiong Yang,et al.  A framework for ontology-driven subspace clustering , 2004, KDD.

[11]  Vasyl Pihur,et al.  RankAggreg, an R package for weighted rank aggregation , 2009, BMC Bioinformatics.

[12]  L. Holm,et al.  The Pfam protein families database , 2005, Nucleic Acids Res..

[13]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[14]  S. Drăghici.  Statistical intelligence: effective analysis of high-density microarray data. , 2002, Drug discovery today.

[15]  R. Gillies,et al.  Why do cancers have high aerobic glycolysis? , 2004, Nature Reviews Cancer.

[16]  Kent A. Spackman,et al.  Using co-occurrence network structure to extract synonymous gene and protein names from MEDLINE abstracts , 2005, BMC Bioinformatics.

[17]  A. Valencia,et al.  Linking genes to literature: text mining, information extraction, and retrieval applications for biology , 2008, Genome Biology.

[18]  Mahesh C Sharma,et al.  The role of annexin II in angiogenesis and tumor progression: a potential therapeutic target. , 2007, Current pharmaceutical design.

[19]  D. Koller,et al.  A module map showing conditional activity of expression modules in cancer , 2004, Nature Genetics.

[20]  Carol Friedman,et al.  Automatic extraction of gene and protein synonyms from MEDLINE and journal articles , 2002, AMIA.

[21]  T. Werner.  Bioinformatics applications for pathway analysis of microarray data. , 2008, Current opinion in biotechnology.

[22]  João Pedro de Magalhães,et al.  Meta-analysis of age-related gene expression profiles identifies common signatures of aging , 2009, Bioinform..

[23]  C. Pecquet,et al.  Mining for JAK-STAT mutations in cancer. , 2008, Trends in biochemical sciences.

[24]  K. Bretonnel Cohen,et al.  Manual curation is not sufficient for annotation of genomic databases , 2007, ISMB/ECCB.

[25]  Yoshihiro Yamanishi,et al.  KEGG for linking genomes to life and the environment , 2007, Nucleic Acids Res..

[26]  J. Kovarik,et al.  JAK/STAT signaling pathways and cancer. Janus kinases/signal transducers and activators of transcription. , 2002, Neoplasma.