title: Identifying pre-post chemotherapy differences in gene expression in breast tumours: a statistical method appropriate for this aim.
abstract: Although widely used for the analysis of gene expression microarray data, cluster analysis may not be the most appropriate statistical technique for some study aims. We demonstrate this by considering a previous analysis of microarray data obtained on breast tumour specimens, many of which were paired specimens from the same patient before and after chemotherapy. Reanalysing the data using statistical methods that appropriately utilise the paired differences for identification of differentially expressed genes, we find 17 genes that we can confidently identify as more expressed after chemotherapy than before. These findings were not reported by the original investigators who analysed the data using cluster analysis techniques.
authors.affiliation: Biometric Research Branch, EPN-8128, National Cancer Institute, National Institutes of Health, Bethesda MD 20892, USA. korne@ctep.nci.nih.gov
authors.forename: E L
authors.initials: EL
authors.lastname: Korn
authors.forename: L M
authors.initials: LM
authors.lastname: McShane
authors.forename: J F
authors.initials: JF
authors.lastname: Troendle
authors.forename: A
authors.initials: A
authors.lastname: Rosenwald
authors.forename: R
authors.initials: R
authors.lastname: Simon
mesh_terms: D000970:Antineoplastic Agents / Q000627:therapeutic use; D001943:Breast Neoplasms / Q000188:drug therapy* / Q000235:genetics*; D016000:Cluster Analysis; D005260:Female; D005500:Follow-Up Studies; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D015203:Reproducibility of Results
chemical_list: D000970:Antineoplastic Agents