Differences in gene expression between B-cell chronic lymphocytic leukemia and normal B cells: a meta-analysis of three microarray studies

Motivation: A major focus of current cancer research is to identify genes that can be used as markers for prognosis and diagnosis, and as targets for therapy. Microarray technology has been applied extensively for this purpose, even though it has been reported that the agreement between microarray platforms is poor. A critical question is: how can we best combine the measurements of matched genes across microarray platforms to develop diagnostic and prognostic tools related to the underlying biology? Results: We introduce a statistical approach within a Bayesian framework to combine the microarray data on matched genes from three investigations of gene expression profiling of B-cell chronic lymphocytic leukemia (CLL) and normal B cells (NBC) using three different microarray platforms, oligonucleotide arrays, cDNA arrays printed on glass slides and cDNA arrays printed on nylon membranes. Using this approach, we identified a number of genes that were consistently differentially expressed between CLL and NBC samples. Availability: Glass slide cDNA array data are available through the public archives of Stanford University at http://cmgm.stanford.edu/pbrown/. Oligonucleotide array data are available in the supplemental material from Klein ηl. Nylon membrane cDNA microarray data are freely available at our website, http://bioinformatics.mdanderson.org/pubdata.html. Software to batch-process gene annotations (GeneLink) is available at http://bioinformatics.mdanderson.org/GeneLink.html. Image quantification software (ScanAlyze) is available at http://rana.lbl.gov/downloads/ScanAlyze.zip. Statistical software (S-Plus 2000) is available commercially from Insightful Corp., Seattle, WA. Software to determine the co-occurrence of terms in PubMed abstracts (PDQ_MED) is commercially available from Inpharmix Inc., Greenwood, IN.