Abstract 2160: New prognostic breast cancer biomarkers selected from formalin fixed tissue RNA samples after whole transcriptome amplification
Authors: Cronin Maureen , Liu Mei-Lan , Jeong Jennie , Scott Aaron , Ambannavar Ranjana , Pho Mylan , Son Hyun S. , Kiefer Mike , Collin Francois , Baker Joffre 
Published: February 2011

Abstract
RT-PCR-based gene expression profiling in archival FFPE tissues with associated clinical records is clinically important in oncology, as evidenced by the wide use of the breast cancer prognostic and predictive Oncotype DX® 21-gene test1. The strength of evidence underlying this test relies on the use of landmark clinical trial patient cohorts and other valuable clinical specimens used for its development and validation. However, the limited amount of RNA available from these FFPE specimens restricts the number of candidate biomarkers that can be tested in discovery studies. To compensate for this limitation, we have developed a method to amplify FFPE RNA which preserves the pre-amplified RNA expression profiles. We have now applied this method to evaluate more than 300 previously untested candidate genes in two of the key clinical cohorts used to develop the Oncotype DX assay. In total, 214 patient RNA samples were amplified and their expression levels for new prognostic markers were analyzed.
Genes discovered to be associated with prognosis in the original studies were included in the amplified RNA study as positive controls to confirm that gene expression profiles in the amplified RNA remained consistent with those in the original RNA extracts.2,3 New genes were found that correlate with the risk of breast cancer recurrence across both clinical populations. A number of these genes co-express in a “metabolism-related” gene signature which includes ENO1, the gene encoding enolase 1. After stratifying the patients into ER+ and ER- cohorts, additional prognostic gene expression biomarkers were identified in the ER- patients that are consistent with a TGFbeta-related “stromal response” signature.
Newly identified genes were confirmed for association with clinical outcome using publicly available microarray-based data sets.4 Most of the newly identified genes and the previously validated biomarker genes were confirmed as being significantly associated with patient outcome using these data. It will be important to confirm these findings in additional separate patient cohorts.1. Paik S, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004;351:28172. Cobleigh, Ml, etl. al.. (2005) Tumor gene expression predicts distant recurrence-free survival in breast cancer patients with 10 or more positive nodes: High throughput RT-PCR assay of paraffin-embedded tumor tissues. Clin Cancer Res 11: 86233. Cronin, M, et. al., (2004) Measurement of Gene Expression in Archival Paraffin-embedded Tissues: Development and Performance of a 92 Gene RT-PCR Assay. American Journal of Pathology, 164: 354. Wirapati, P., et. al., (2008) Meta-Anlayis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Research, 10: R65 (doi:10.1186/bcr2124)
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2160.