TY - GEN
T1 - Meta-analysis of cancer microarray data reveals signaling pathway hotspots
AU - Chopra, Pankaj
AU - Kang, Jaewoo
AU - Hong, Seung Mo
PY - 2009
Y1 - 2009
N2 - Recent studies have shown that the identification of deregulated bio-molecular pathways in cancer may be more important than identification of individual genes through differential expression. Since the same pathway can be deregulated by a different subset of genes, it is critical to study pathways as a whole, rather than focus on individual genes. Most papers on meta-analysis of cancer datasets focus on the identification of a set of individual genes, and not on pathways, protein families and gene ontology terms. We have analyzed data from 87 microarray datasets consisting of 5,126 samples and spanning 25 different types of cancer. We have identified 212 KEGG pathways, 578 protein families and 1,717 gene ontology terms that are statistically significant (p < 0.01), and deregulated in cancer. Many of the top pathways and proteins from our meta-analysis, e.g., Jak-Stat pathway, Annexin proteins etc. are already known to play a pivotal role in carcinogenesis. To the best of our knowledge this is the largest meta analysis of cancer pathways, protein families and gene ontology terms to date.
AB - Recent studies have shown that the identification of deregulated bio-molecular pathways in cancer may be more important than identification of individual genes through differential expression. Since the same pathway can be deregulated by a different subset of genes, it is critical to study pathways as a whole, rather than focus on individual genes. Most papers on meta-analysis of cancer datasets focus on the identification of a set of individual genes, and not on pathways, protein families and gene ontology terms. We have analyzed data from 87 microarray datasets consisting of 5,126 samples and spanning 25 different types of cancer. We have identified 212 KEGG pathways, 578 protein families and 1,717 gene ontology terms that are statistically significant (p < 0.01), and deregulated in cancer. Many of the top pathways and proteins from our meta-analysis, e.g., Jak-Stat pathway, Annexin proteins etc. are already known to play a pivotal role in carcinogenesis. To the best of our knowledge this is the largest meta analysis of cancer pathways, protein families and gene ontology terms to date.
KW - Cancer
KW - GO
KW - Gene expression
KW - KEGG
KW - Meta-analysis
KW - Microarray
KW - PFAM
KW - Pathway
KW - Signaling
UR - http://www.scopus.com/inward/record.url?scp=72849133004&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=72849133004&partnerID=8YFLogxK
U2 - 10.1109/BIBMW.2009.5332097
DO - 10.1109/BIBMW.2009.5332097
M3 - Conference contribution
AN - SCOPUS:72849133004
SN - 9781424451210
T3 - Proceedings - 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009
SP - 214
EP - 219
BT - Proceedings - 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009
T2 - 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009
Y2 - 1 November 2009 through 4 November 2009
ER -