title: Comparison of the predictive accuracy of DNA array-based multigene classifiers across cDNA arrays and Affymetrix GeneChips.
abstract: We examined how well differentially expressed genes and multigene outcome classifiers retain their class-discriminating values when tested on data generated by different transcriptional profiling platforms. RNA from 33 stage I-III breast cancers was hybridized to both Affymetrix GeneChip and Millennium Pharmaceuticals cDNA arrays. Only 30% of all corresponding gene expression measurements on the two platforms had Pearson correlation coefficient r >or= 0.7 when UniGene was used to match probes. There was substantial variation in correlation between different Affymetrix probe sets matched to the same cDNA probe. When cDNA and Affymetrix probes were matched by basic local alignment tool (BLAST) sequence identity, the correlation increased substantially. We identified 182 genes in the Affymetrix and 45 in the cDNA data (including 17 common genes) that accurately separated 91% of cases in supervised hierarchical clustering in each data set. Cross-platform testing of these informative genes resulted in lower clustering accuracy of 45 and 79%, respectively. Several sets of accurate five-gene classifiers were developed on each platform using linear discriminant analysis. The best 100 classifiers showed average misclassification error rate of 2% on the original data that rose to 19.5% when tested on data from the other platform. Random five-gene classifiers showed misclassification error rate of 33%. We conclude that multigene predictors optimized for one platform lose accuracy when applied to data from another platform due to missing genes and sequence differences in probes that result in differing measurements for the same gene.
authors.affiliation: Millennium Pharmaceuticals, Inc., Cambridge, Massachusetts, USA.
authors.forename: James
authors.initials: J
authors.lastname: Stec
authors.forename: Jing
authors.initials: J
authors.lastname: Wang
authors.forename: Kevin
authors.initials: K
authors.lastname: Coombes
authors.forename: Mark
authors.initials: M
authors.lastname: Ayers
authors.forename: Sebastian
authors.initials: S
authors.lastname: Hoersch
authors.forename: David L
authors.initials: DL
authors.lastname: Gold
authors.forename: Jeffrey S
authors.initials: JS
authors.lastname: Ross
authors.forename: Kenneth R
authors.initials: KR
authors.lastname: Hess
authors.forename: Stephen
authors.initials: S
authors.lastname: Tirrell
authors.forename: Gerald
authors.initials: G
authors.lastname: Linette
authors.forename: Gabriel N
authors.initials: GN
authors.lastname: Hortobagyi
authors.forename: W
authors.initials: W
authors.lastname: Fraser Symmans
authors.forename: Lajos
authors.initials: L
authors.lastname: Pusztai
mesh_terms: D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000235:genetics*; D015342:DNA Probes / Q000145:classification / Q000235:genetics; D005260:Female; D020869:Gene Expression Profiling / Q000592:standards; D005807:Genes, Overlapping / Q000235:genetics*; D006801:Humans; D008875:Middle Aged; D018299:Neoplasms, Ductal, Lobular, and Medullary / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000592:standards*; D016133:Polymerase Chain Reaction; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D012334:RNA, Neoplasm / Q000235:genetics / Q000378:metabolism; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D015342:DNA Probes; D012333:RNA, Messenger; D012334:RNA, Neoplasm