Abstract
Abstract The class I phosphatidylinositol 3’ kinases (PI3K) play a major role in proliferation and survival in a wide variety of human cancers, and activation of the PI3K pathway is thought to be an important driver in estrogen receptor positive (ER+) breast cancer. A key factor in successful development of drugs targeting this pathway will be development in appropriate molecular subsets. Important questions relevant to PI3K inhibitor development in ER+ breast cancers are whether these inhibitors will work equally well in luminal A compared to luminal B tumors, and whether gene expression signatures of pathway activation may have additional utility in patient stratification beyond PIK3CA mutation status alone. The goal of this study was to develop a methodology for high throughput profiling of ER+ breast cancers, in order to enable molecular subtyping of patients enrolled in clinical studies. To accomplish this, we developed an analysis platform to measure the relative expression of 90 breast cancer and PI3K pathway specific genes in formalin-fixed paraffin-embedded (FFPE) tissue. The content for this panel consists of genes known to be important for epithelial-mesenchymal biology, proliferation rate, and transcriptional output of the PI3K pathway. The 96 assay panel (including 6 housekeeping genes) was developed on the Fluidigm Biomark microfluidics platform and was extensively validated using well-characterized breast cancer cell lines and FFPE breast cancer samples of known subtypes based on immunohistochemistry for HER2, ER, and PR. All assays showed high levels of inter-and intra-chip reproducibility and were sensitive on standard curves down to 3ng RNA input. Using this method we were able to separate breast cancers into distinct molecular subtypes, as well as identify more proliferative luminal B type tumors. In addition, PIK3CA mutation status, a potential biomarker, was determined using a highly specific and sensitive qRT-PCR mutation assay, in order to allow comparison with the PI3K pathway activation signature. We extended these analyses to a small cohort of patient samples consisting of matched primary and metastatic tumor tissues, and report here the correlation of primary and matched metastatic ER+ breast cancer FFPE tumor samples at both the gene expression and mutational levels. We found that the majority of matched pairs were concordant for both mutation status and gene expression, though a subset did show differences. Future studies will examine the prognostic significance and clinical relevance of this gene signature. Citation Format: Erica B. Schleifman, Rupal M. Desai, Jill Spoerke, Cheryl Victoria Wong, Ilma Abbas, Carol O'Brien, Garret Hampton, Timothy Wilson, Hartmut Koeppen, Rajesh Patel, Teiko Sumiyoshi, Ling Fu, Rachel Tam, Rajiv Raja, Mark Lackner. High-throughput qRT-PCR expression profiling of estrogen receptor positive breast tumors. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3462. doi:10.1158/1538-7445.AM2013-3462
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