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01-05-2012 | Preclinical Study

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

Authors: Oscar Krijgsman, Paul Roepman, Wilbert Zwart, Jason S. Carroll, Sun Tian, Femke A. de Snoo, Richard A. Bender, Rene Bernards, Annuska M. Glas

Published in: Breast Cancer Research and Treatment | Issue 1/2012

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.

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Title: A diagnostic gene profile for molecular subtyping of breast cancer associated with treatment response
Authors: Oscar Krijgsman
Paul Roepman
Wilbert Zwart
Jason S. Carroll
Sun Tian
Femke A. de Snoo
Richard A. Bender
Rene Bernards
Annuska M. Glas
Publication date: 01-05-2012
Publisher: Springer US
Published in: Breast Cancer Research and Treatment / Issue 1/2012
Print ISSN: 0167-6806
Electronic ISSN: 1573-7217
DOI: https://doi.org/10.1007/s10549-011-1683-z

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