Gene expression profiling of ATP-binding cassette (ABC) transporters as a predictor of the pathologic response to neoadjuvant chemotherapy in breast cancer patients

Breast Cancer Res Treat. 2006 Sep;99(1):9-17. doi: 10.1007/s10549-006-9175-2. Epub 2006 Jun 5.

Abstract

Drug resistance is a major obstacle to the successful chemotherapy. Several ATP-binding cassette (ABC) transporters including ABCB1, ABCC1 and ABCG2 have been known to be important mediators of chemoresistance. Using oligonucleotide microarrays (HG-U133 Plus 2.0; Affymetrix), we analyzed the ABC transporter gene expression profiles in breast cancer patients who underwent sequential weekly paclitaxel/FEC (5-fluorouracil, epirubicin and cyclophosphamide) neoadjuvant chemotherapy. We compared the ABC transporter expression profile between two classes of pretreatment tumor samples divided by the patients' pathological response to neoadjuvant chemotherapy (residual disease [RD] versus pathologic complete response [pCR]) ABCB3, ABCC7 and ABCF2 showed significantly high expression in the pCR. Several ABC transporters including ABCC5, ABCA12, ABCA1 ABCC13, ABCB6 and ABCC11 showed significantly increased expression in the RD (p<0.05). We evaluated the feasibility of developing a multigene predictor model of pathologic response to neoadjuvant chemotherapy using gene expression profiles of ABC transporters. The prediction error was evaluated by leave-one-out cross-validation (LOOCV). A multigene predictor model with the ABC transporters differentially expressed between the two classes (p<or=0.003) showed an average 92.8% of predictive accuracy (95% CI, 88.0-97.4%) with a 93.2% (95% CI, 85.2-100%) positive predictive value for pCR, a 93.6% (95% CI, 87.8-99.4%) negative predictive value, a sensitivity of 88.1%(95% CI, 76.8-99.4%), and a specificity of 95.9% (91.1% CI, 87.8-100%). Our results suggest that several ABC transporters in human breast cancer cells may affect the clinical response to neoadjuvant chemotherapy, and transcriptional profiling of these genes may be useful to predict the pathologic response to sequential weekly paclitaxel/FEC in breast cancer patients.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • ATP-Binding Cassette Transporters / chemistry*
  • Adult
  • Base Sequence
  • Breast Neoplasms / drug therapy*
  • Breast Neoplasms / genetics*
  • Breast Neoplasms / metabolism*
  • Female
  • Gene Expression Profiling / methods*
  • Gene Expression Regulation, Neoplastic*
  • Humans
  • Membrane Transport Proteins / metabolism
  • Middle Aged
  • Molecular Sequence Data
  • Multivariate Analysis
  • Neoadjuvant Therapy / methods*
  • Oligonucleotide Array Sequence Analysis
  • Treatment Outcome

Substances

  • ATP-Binding Cassette Transporters
  • Membrane Transport Proteins