Breast Cancer Research and Treatment

, Volume 121, Issue 2, pp 301–309

Clinical evaluation of chemotherapy response predictors developed from breast cancer cell lines

  • Cornelia Liedtke
  • Jing Wang
  • Attila Tordai
  • William F. Symmans
  • Gabriel N. Hortobagyi
  • Ludwig Kiesel
  • Kenneth Hess
  • Keith A. Baggerly
  • Kevin R. Coombes
  • Lajos Pusztai
Preclinical study


The goal of this study was to develop pharmacogenomic predictors in response to standard chemotherapy drugs in breast cancer cell lines and test their predictive value in patients who received treatment with the same drugs. Nineteen human breast cancer cell lines were tested for sensitivity to paclitaxel (T), 5-fluorouracil (F), doxorubicin (A) and cyclophosphamide (C) in vitro. Baseline gene expression data were obtained for each cell line with Affymetrix U133A gene chips, and multigene predictors of sensitivity were derived for each drug separately. These predictors were applied individually and in combination to human gene expression data generated with the same Affymetrix platform from fine needle aspiration specimens of 133 stage I-III breast cancers. Tumor samples were obtained at baseline, and each patient received 6 months of preoperative TFAC chemotherapy followed by surgery. Cell line-derived prediction results were correlated with the observed pathologic response to chemotherapy. Statistically robust differentially expressed genes between sensitive and resistant cells could only be found for paclitaxel. False discovery rates associated with the informative genes were high for all other drugs. For each drug, the top 100 differentially expressed genes were combined into a drug-specific response predictor. When these cell line-based predictors were applied to patient data, there was no significant correlation between observed response and predicted response either for individual drug predictors or combined predictions. Cell line-derived predictors of response to four commonly used chemotherapy drugs did not predict response accurately in patients.


Cell lines Chemosensitivity Multigene predictor Breast cancer Gene expression profiling 

Supplementary material

10549_2009_445_MOESM1_ESM.pdf (888 kb)
Supplementary material 1 (PDF 888 kb)


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Copyright information

© Springer Science+Business Media, LLC. 2009

Authors and Affiliations

  • Cornelia Liedtke
    • 1
    • 2
  • Jing Wang
    • 3
  • Attila Tordai
    • 4
  • William F. Symmans
    • 5
  • Gabriel N. Hortobagyi
    • 1
  • Ludwig Kiesel
    • 2
  • Kenneth Hess
    • 6
  • Keith A. Baggerly
    • 3
  • Kevin R. Coombes
    • 3
  • Lajos Pusztai
    • 1
  1. 1.Department of Breast Medical OncologyThe University of Texas M. D. Anderson Cancer CenterHoustonUSA
  2. 2.Department of Gynecology and ObstetricsUniversity Hospital MuensterMuensterGermany
  3. 3.Department of Bioinformatics and Computational BiologyThe University of Texas M. D. Anderson Cancer CenterHoustonUSA
  4. 4.Department of Molecular DiagnosticsNational Medical CenterBudapestHungary
  5. 5.Department of PathologyThe University of Texas M. D. Anderson Cancer CenterHoustonUSA
  6. 6.Department of BiostatisticsThe University of Texas M. D. Anderson Cancer CenterHoustonUSA

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