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Breast Cancer Research and Treatment

, Volume 133, Issue 1, pp 37–47 | Cite as

A diagnostic gene profile for molecular subtyping of breast cancer associated with treatment response

  • Oscar Krijgsman
  • Paul Roepman
  • Wilbert Zwart
  • Jason S. Carroll
  • Sun Tian
  • Femke A. de Snoo
  • Richard A. Bender
  • Rene Bernards
  • Annuska M. Glas
Preclinical Study

Abstract

Classification of breast cancer into molecular subtypes maybe important for the proper selection of therapy, as tumors with seemingly similar histopathological features can have strikingly different clinical outcomes. Herein, we report the development of a molecular subtyping profile (BluePrint), that enables rationalization in patient selection for either chemotherapy or endocrine therapy prescription. An 80-Gene Molecular Subtyping Profile (BluePrint) was developed using 200 breast cancer patient specimens and confirmed on four independent validation cohorts (n = 784). Additionally, the profile was tested as a predictor of chemotherapy response in 133 breast cancer patients, treated with T/FAC neoadjuvant chemotherapy. BluePrint classification of a patient cohort that was treated with neoadjuvant chemotherapy (n = 133) shows improved distribution of pathological Complete Response (pCR), among molecular subgroups compared with local pathology: 56% of the patients had a pCR in the Basal-type subgroup, 3% in the MammaPrint Low-risk, Luminal-type subgroup, 11% in the MammaPrint High-risk, Luminal-type subgroup, and 50% in the HER2-type subgroup. The group of genes identifying Luminal-type breast cancer is highly enriched for genes having an Estrogen Receptor binding site proximal to the promoter-region, suggesting that these genes are direct targets of the Estrogen Receptor. Implementation of this profile may improve the clinical management of breast cancer patients, by enabling the selection of patients who are most likely to benefit from either chemotherapy or from endocrine therapy.

Keywords

Breast cancer Estrogen receptor Molecular subtyping Luminal Basal HER2 

Notes

Acknowledgments

The authors thank Rob Pover, Maurice Pater, and Arenda Schuurman for sample and microarray processing; Cor Lieftink and Bram Gerritsen for statistical advice, and Lisette Stork-Sloots and Laura van ‘t Veer for fruitful discussions and helpful suggestions.

Conflicts of interest

RAB is employed by Agendia Inc, all other authors, except WZ and JC, are employed by Agendia BV.

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Copyright information

© Springer Science+Business Media, LLC. 2011

Authors and Affiliations

  • Oscar Krijgsman
    • 1
    • 6
  • Paul Roepman
    • 1
  • Wilbert Zwart
    • 2
  • Jason S. Carroll
    • 2
  • Sun Tian
    • 1
  • Femke A. de Snoo
    • 3
  • Richard A. Bender
    • 4
  • Rene Bernards
    • 1
    • 5
  • Annuska M. Glas
    • 1
  1. 1.Research and Development, Agendia BVAmsterdamThe Netherlands
  2. 2.Cancer Research UK, Cambridge Research Institute, Li Ka Shing CentreCambridgeUK
  3. 3.Department of Medical Affairs Agendia BVAmsterdamThe Netherlands
  4. 4.Department of Medical AffairsAgendia IncIrvineUSA
  5. 5.Division of Molecular Carcinogenesis, Center for Biomedical Genetics and Cancer, Genomics CenterThe Netherlands Cancer InstituteAmsterdamThe Netherlands
  6. 6.Department of PathologyVU University Medical CenterAmsterdamThe Netherlands

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