Strategies for comparing gene expression profiles from different microarray platforms: Application to a case-control experiment

Meta-analysis of microarray data is increasingly important, considering both the availability of multiple platforms using disparatetechnologies and the accumulation in public repositories of data sets from diVerent laboratories. We addressed the issue of comparinggene expression proWles from two microarray platforms by devising a standardized investigative strategy. We tested this procedure bystudying MDA-MB-231 cells, which undergo apoptosis on treatment with resveratrol. Gene expression proWles were obtained using highdensity,short-oligonucleotide, single-color microarray platforms: GeneChip (AVymetrix) and CodeLink (Amersham). Interplatformanalyses were carried out on 8414 common transcripts represented on both platforms, as identiWed by LocusLink ID, representing 70.8%and 88.6% of annotated GeneChip and CodeLink features, respectively. We identiWed 105 diVerentially expressed genes (DEGs) on Code-Link and 42 DEGs on GeneChip. Among them, only 9 DEGs were commonly identiWed by both platforms. Multiple analyses (BLASTalignment of probes with target sequences, gene ontology, literature mining, and quantitative real-time PCR) permitted us to investigatethe factors contributing to the generation of platform-dependent results in single-color microarray experiments. An eVective approach tocross-platform comparison involves microarrays of similar technologies, samples prepared by identical methods, and a standardized batteryof bioinformatic and statistical analyses.