Combining multigene profiling of molecular subtypes with the 70-gene profile for classification of breast cancer

Publication Name: Abstract, ASCO 2009

Author(s): Stork-Sloots L, Krijgsman O, Roepman P, et al. Combining multigene profiling of molecular subtypes with the 70-gene profile for classification of breast cancer. J Clin Oncol 2009; 27: 15s

Background: Classification of breast cancers into molecular subtypes may be important for accurate selection of therapy for patients. Herein we report a multigene profile for classification of breast cancer into molecular subtypes. The profile separates tumors into hormone receptor (HR)+/luminal-like, HER2+/ERBB2-like, and triple negative/basal-like subclasses. Methods: A multi-gene profile was developed based on a series of 200 tumor samples of known ER, PR and HER2 receptor status (concordant IHC and gene expression result) hybridized on 44k microarrays. The profile classifies 96% concordant to the molecular subtypes named luminal-, ERBB2- or basal-type as published by Perou et al (Perou et al, Nature, 2000; Fan et al, NEJM, 2005). The profile was validated using 469 independent samples as well as on two publically available gene expression datasets (n=251 and n=159). Results: The profile classified 66% (712) as luminal-like, 18% (194) ERBB2-like, and 16% (173) as basal-like. As compared to single-marker readout for the presence of ER, PR and HER2, 13% of the samples that were scored positive for presence of ER/PR did not express a luminal-like gene profile. Samples with a ERBB2-like or basal-like gene profile showed equally poor 5-year survival rates of ~65%. However, the ERBB2-like subset of MammaPrint low risk patients (15%) showed an 89% (95%CI, 71-100) survival rate without trastuzumab treatment. When the luminal-like subtype was separated into “high-” and “low-risk” by MammaPrint the survival rate was 56% (95%CI, 46-68) for high-risk luminal-like samples and 94% (95%CI, 90-99) for low-risk samples. Conclusions: The developed multigene profile can classify breast tumors into luminal-, ERBB2- and basal-like subgroups. By combining this molecular subtyping with MammaPrint risk-classification specific groups of patients can be recognized that that are at high risk of recurrence. The low risk patients within the luminal- and ERBB2-like subclasses have a very low risk of recurrence. Implementation of this knowledge can improve the clinical management of breast cancer patients

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