Breast Cancer Research and Treatment

, Volume 132, Issue 3, pp 1035–1047

Gene expression profiling of breast tumor cell lines to predict for therapeutic response to microtubule-stabilizing agents

  • Gais Kadra
  • Pascal Finetti
  • Yves Toiron
  • Patrice Viens
  • Daniel Birnbaum
  • Jean-Paul Borg
  • François Bertucci
  • Anthony Gonçalves
Preclinical study

DOI: 10.1007/s10549-011-1687-8

Cite this article as:
Kadra, G., Finetti, P., Toiron, Y. et al. Breast Cancer Res Treat (2012) 132: 1035. doi:10.1007/s10549-011-1687-8

Abstract

Microtubule-targeting agents, including taxanes (Tax) and ixabepilone (Ixa), are important components of modern breast cancer chemotherapy regimens, but no molecular parameter is currently available that can predict for their efficiency. We sought to develop pharmacogenomic predictors of Tax- and Ixa-response from a large panel of human breast tumor cell lines (BTCL), then to evaluate their performance in clinical samples. Thirty-two BTCL, representative of the molecular diversity of breast cancers (BC), were treated in vitro with Tax (paclitaxel (Pac), docetaxel (Doc)), and ixabepilone (Ixa), then classified as drug-sensitive or resistant according to their 50% inhibitory concentrations (IC50s). Baseline gene expression data were obtained using Affymetrix U133 Plus 2.0 human oligonucleotide microarrays. Gene expression set (GES) predictors of response to taxanes were derived, then tested for validation internally and in publicly available gene expression datasets. In vitro IC50s of Pac and Doc were almost identical, whereas some Tax-resistant BTCL retained sensitivity to Ixa. GES predictors for Tax-sensitivity (333 genes) and Ixa-sensitivity (79 genes) were defined. They displayed a limited number of overlapping genes. Both were validated by leave-n-out cross-validation (n = 4; for overall accuracy (OA), P = 0.028 for Tax, and P = 0.0005 for Ixa). The GES predictor of Tax-sensitivity was tested on publicly available external datasets and significantly predicted Pac-sensitivity in 16 BTCL (P = 0.04 for OA), and pathological complete response to Pac-based neoadjuvant chemotherapy in BC patients (P = 0.0045 for OA). Applying Tax and Ixa-GES to a dataset of clinically annotated early BC patients identified subsets of tumors with potentially distinct phenotypes of drug sensitivity: predicted Ixa-sensitive/Tax-resistant BC were significantly (P < 0.05, Fischer’s exact test) more frequently ER/PR-positive, Ki67-negative, and luminal subtype than predicted Ixa-resistant/Tax-sensitive BC. Genomic predictors for Tax- and Ixa-sensitivity can be derived from BTCL and may be helpful for better selecting cytotoxic treatment in BC patients.

Keywords

Taxanes Ixabepilone Paclitaxel Docetaxel Breast cancer Microarrays Gene expression profiling Molecular signatures 

Abbreviations

Tax

Taxanes

Pac

Paclitaxel

Doc

Docetaxel

Ixa

Ixabepilone

BTCL

Breast tumor cell lines

IC50

50% inhibitory concentrations

GES

Gene expression set

ER

Oestrogen receptor

PR

Progesterone receptor

HER2

Human epidermal growth factor receptor 2

FDR

False discovery rate

RT-PCR

Reverse transcriptase-polymerase chain reaction

cDNA

Complementary DNA

FFPE

Formalin-fixed paraffin-embedded

PPV

Positive predictive value

NPV

Negative predictive value

OA

Overall accuracy

pCR

Pathological complete response

Supplementary material

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Supplementary material 1 (DOC 41 kb)
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Supplementary material 2 (XLS 138 kb)
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Supplementary material 3 (XLS 43 kb)
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Supplementary material 4 (XLS 38 kb)
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Supplementary material 5 (XLS 32 kb)
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Supplementary material 6 (XLS 29 kb)
10549_2011_1687_MOESM7_ESM.doc (31 kb)
Supplementary material 7 (DOC 32 kb)

Copyright information

© Springer Science+Business Media, LLC. 2011

Authors and Affiliations

  • Gais Kadra
    • 1
  • Pascal Finetti
    • 2
  • Yves Toiron
    • 1
  • Patrice Viens
    • 3
    • 4
  • Daniel Birnbaum
    • 2
  • Jean-Paul Borg
    • 1
    • 4
  • François Bertucci
    • 2
    • 3
    • 4
  • Anthony Gonçalves
    • 1
    • 3
    • 4
  1. 1.Département de Pharmacologie Moléculaire and U891 INSERM, Centre de Recherche En Cancérologie de MarseilleInstitut Paoli-CalmettesMarseilleFrance
  2. 2.Département d’Oncologie Moléculaire and U891 INSERM, Centre de Recherche en Cancérologie de MarseilleInstitut Paoli-CalmettesMarseilleFrance
  3. 3.Département d’Oncologie Médicale and U891 INSERM, Centre de Recherche en Cancérologie de MarseilleInstitut Paoli-CalmettesMarseilleFrance
  4. 4.Université de la MéditerranéeMarseilleFrance

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