Meta-analysis of breast cancer microarray studies in conjunction with conserved cis-elements suggest patterns for coordinate reg

Background: Gene expression measurements from breast cancer (BrCa) tumors are established clinical predictive tools to identify tumor subtypes, identify patients showing poor/good prognosis, and identify patients likely to have disease recurrence. However, diverse breast cancer datasets in conjunction with diagnostic clinical arrays show little overlap in the sets of genes identified. One approach to identify a set of consistently dysregulated candidate genes in these tumors is to employ meta-analysis of multiple independent microarray datasets. This allows one to compare expression data from a diverse collection of breast tumor array datasets generated on either cDNA or oligonucleotide arrays. Results: We gathered expression data from 9 published microarray studies examining estrogen receptor positive (ER+) and estrogen receptor negative (ER-) BrCa tumor cases from the Oncomine database. We performed a meta-analysis and identified genes that were universally up or down regulated with...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: David D. Smith, Pål Sætrom, Ola R. Snøve Jr., Cathryn Lundberg, Guillermo E. Rivas, Carlotta Glackin, Garrett P. Larson
• Keywords: BMCBI 2008, Expression Data, Gene Expression, Tumors