Preclinical study

Breast Cancer Research and Treatment

, Volume 121, Issue 2, pp 301-309

First online:

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

  • Cornelia LiedtkeAffiliated withDepartment of Breast Medical Oncology, The University of Texas M. D. Anderson Cancer CenterDepartment of Gynecology and Obstetrics, University Hospital Muenster
  • , Jing WangAffiliated withDepartment of Bioinformatics and Computational Biology, The University of Texas M. D. Anderson Cancer Center
  • , Attila TordaiAffiliated withDepartment of Molecular Diagnostics, National Medical Center
  • , William F. SymmansAffiliated withDepartment of Pathology, The University of Texas M. D. Anderson Cancer Center
  • , Gabriel N. HortobagyiAffiliated withDepartment of Breast Medical Oncology, The University of Texas M. D. Anderson Cancer Center
  • , Ludwig KieselAffiliated withDepartment of Gynecology and Obstetrics, University Hospital Muenster
  • , Kenneth HessAffiliated withDepartment of Biostatistics, The University of Texas M. D. Anderson Cancer Center
  • , Keith A. BaggerlyAffiliated withDepartment of Bioinformatics and Computational Biology, The University of Texas M. D. Anderson Cancer Center
  • , Kevin R. CoombesAffiliated withDepartment of Bioinformatics and Computational Biology, The University of Texas M. D. Anderson Cancer Center
    • , Lajos PusztaiAffiliated withDepartment of Breast Medical Oncology, The University of Texas M. D. Anderson Cancer Center Email author 

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Abstract

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.

Keywords

Cell lines Chemosensitivity Multigene predictor Breast cancer Gene expression profiling