Transcriptional profiling of patient-matched ER-positive breast cancer tissue from post-menopausal women treated with neoadjuvant RAD001.

Abstract

Abstract Abstract #2035 Background: RAD001 (everolimus) is a rapamycin derivative that inhibits mTOR and its downstream substrates and has shown promising results in Phase I clinical trials. This is the first clinical study of RAD001 administered alone in breast cancer. The aim of this study was to characterise the effects of RAD001 treatment on tumour gene expression and to assess whether we can predict which patients will respond to RAD001.
 Materials & Methods: 32 post-menopausal women with operable estrogen receptor positive early breast cancer received 5mg RAD001 pre-operative treatment daily for 14 days prior to primary surgery. 25 patients completed treatment, 6 withdrew and 1 did not start medication. Paired biopsies were taken at diagnosis and at surgery from each of the 31 patients who received RAD001. Half of the biopsy was immediately flash frozen in liquid nitrogen and RNA extracted, amplified in duplicate and analysed using Illumina Human Ref.8 chip v2, the other half of the biopsy was embedded in paraffin for the analysis of biological response markers, including changes in proliferation (Ki67) by immunohistochemistry (Macaskill et al., 2006: Breast Cancer Research & Treatment: 100: S1: S286). 15 patients were classified as responders to RAD001 and 10 patients non-responders (responders were defined by a fall in % Ki-67 positive cells). Gene expression changes were compared before and after treatment with RAD001 and between the responders and non-responders using Bioconductor programs implemented in the R statistical programming language.
 Results & Discussion: All pre- and post-treatment biopsies were available for microarray processing and assessment of biological response markers for patients completing RAD001 treatment. Analysing data from duplicate samples enabled us to vigorously evaluate the reproducibility of the Illumina beadarray platform and revealed some slight batch-to-batch variation which can be accounted for in the analysis. This dataset has enabled us to begin to identify genes and pathways associated with RAD001 treatment and to generate a gene expression classifier for predicting which patients will benefit from RAD001 treatment. Genes of interest will be validated by quantitative real time PCR and key pathways reported.
 Acknowledgements: This work was supported by a grant from Breast Cancer Research & Treatment, UK. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 2035.