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  • 标题:Prediction of Toxicant-Specific Gene Expression Signatures after Chemotherapeutic Treatment of Breast Cell Lines
  • 作者:Melissa A. Troester ; Katherine A. Hoadley ; Joel S. Parker
  • 期刊名称:Environmental Health Perspectives
  • 印刷版ISSN:0091-6765
  • 电子版ISSN:1552-9924
  • 出版年度:2004
  • 卷号:112
  • 期号:16
  • 页码:1607-1613
  • DOI:10.1289/txg.7204
  • 语种:English
  • 出版社:OCR Subscription Services Inc
  • 摘要:Global gene expression profiling has demonstrated that the predominant cellular response to a range of toxicants is a general stress response. This stereotyped environmental stress response commonly includes repression of protein synthesis and cell-cycle–regulated genes and induction of DNA damage and oxidative stress–responsive genes. Our laboratory recently characterized the general stress response of breast cell lines derived from basal-like and luminal epithelium after treatment with doxorubicin (DOX) or 5-fluorouracil (5FU) and showed that each cell type has a distinct response. However, we expected that some of the expression changes induced by DOX and 5FU would be unique to each compound and might reflect the underlying mechanisms of action of these agents. Therefore, we employed supervised analyses (significance analysis of microarrays) to identify genes that showed differential expression between DOX-treated and 5FU-treated cell lines. We then used cross-validation analyses and identified genes that afforded high predictive accuracy in classifying samples into the two treatment classes. To test whether these gene lists had good predictive accuracy in an independent data set, we treated our panel of cell lines with etoposide, a compound mechanistically similar to DOX. We demonstrated that using expression patterns of 100 genes we were able to obtain 100% predictive accuracy in classifying the etoposide samples as being more similar in expression to DOX-treated than to 5FU-treated samples. These analyses also showed that toxicant-specific gene expression patterns, similar to general stress responses, vary according to cell type.
  • 关键词:breast cancer; class prediction; doxorubicin; etoposide; 5-fluorouracil; gene expression; microarrays
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