Abstract 1785: Technical validation of novel 325 RNA predictive biomarkers using gene expression data generated by Nanostring n-counter and Affymetrix microarray

Abstract

Abstract Background: With new developments of oncology drug combinations and targeted treatments, the ability to stratify categories of patient populations and to develop companion diagnostics has become increasingly important. A panel of 325 RNA-biomarkers was selected based on cancer-related biological processes of healthy cells and gene expression changes over time during non-malignant epithelial cell organization. This "cancer in reverse" approach in combination with empirically derived algorithms resulted in a panel of biomarkers having little overlap with 9 other widely-used commercial gene panels analyzed to date (e.g., overlap with FoundationOne was 2% (lowest) and with OncotypeDX was 14% (highest)), providing a more in-depth and comprehensive view of gene expression profiles and key cellular signaling pathways beyond mutations in "driver-genes", and drug associations including chemotherapies, immunotherapies, and targeted-therapies. Objective: In order to technically validate an assay for the 325 RNA-biomarkers we compared gene expression profiles side-by-side using two technology platforms to address the reproducibility of the assay. Methods and Results: We have mapped the 325 RNA transcripts and 7 housekeeping genes in a custom NanoString n-Counter expression panel to be compared to all potential probe sets in the Affymetrix Human Genome U133 Plus 2.0 microarray. The experiments were conducted with 10 unique biological formalin-fixed paraffin-embedded (FFPE) breast tumor samples. Each site extracted RNA from four sections of 10-microns thick FFPE tissue over three different days by three different operators using an optimized standard operating procedure and quality control criteria. Samples were analyzed using mas5 in BioConductor and NanoStringNorm in R. Pearson correlation showed reproducibility between sites for all 60 samples with r=0.995 for Affymetrix and r=0.999 for NanoString. Correlation in multiple days and multiple users were for Affymetrix r=(0.962-0.999) and for NanoString r=(0.982-0.991). The platforms were compared using relative expression fold changes using linear regression (lm). Concordant genes were defined to have gene expression levels within +/- 2 standard deviation (sd) of each other at 95% confidence interval, or to have greater than +/- 2 sd but have changes in the same direction in both platforms. The discordant genes were defined to have opposite direction of changes. By this definition, approximately 90% of the genes fell into the concordant category. Conclusion: The 325 RNA-biomarkers showed reproducibility in two technology platforms with high concordance. With five predictive tests under development for breast (3), lung and pancreatic cancers future directions include performing clinical validation studies and generate rationale for patient selection in clinical trials using the technically validated assays. Citation Format: Marcia V. Fournier, Said Attiya, Joan Chen, John Obenauer, Anup Madan, Patricia Smith. Technical validation of novel 325 RNA predictive biomarkers using gene expression data generated by Nanostring n-counter and Affymetrix microarray [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1785. doi:10.1158/1538-7445.AM2017-1785