Abstract 738: Utility of Assessing HER2 RNA expression for precision medicine

Abstract

Abstract Genomic analysis of tumors is rapidly becoming routine clinical practice. Most of the next generation sequencing (NGS)-based oncology assay focused on DNA alteration data for single nucleotide variants (SNVs), insertions and deletions (indels) and copy number variants (CNVs) of genes which have targeted drug. Although RNA sequencing technology is increasingly being explored, its clinical utility still needs to be clarified. As there is a growing number of HER2-targeted therapies, in this study, we dissected the association between HER2 amplification, RNA overexpression, HER2 protein expression by immunohistochemistry (IHC) and reverse phase proteomic arrays (RPPA) in 618 breast tumors in the TCGA. We conducted unsupervised clustering analysis based on HER2 RNA-seq gene expression and RPPA protein data to identify HER2 overexpression samples. As expected there was a strong correlation with ERBB2 copy number with HER2 RNA expression (R2 = 0.56, P <0.001), and HER2 protein expression by IHC (R2 = 0.25, P < 0.001). RNA expression also correlated with HER2 IHC (R2 = 0.40, P < 0.001) and HER2 protein expression by RPPA (R2 = 0.68, P < 0.001). We performed unsupervised clustering analysis based on RPPA protein data and gene expression data of the HER2 gene, all the breast cancer samples were classified as two distinct clusters. Among the two subgroups, one subgroup had significantly higher expression and protein level of HER2 gene. The clustering results of most breast tumors were consistent with the IHC score and copy number data. The gene expression cutoff value to distinguish the HER2 overexpression subgroup from the other was about 204 FPKM. In addition, we identified two HER2 overexpression tumors which were classified as HER2 negative based on IHC. Studies are planned to test transcriptomic based actionability in patient derived models. Our results suggest that RNA-seq gene expression data may identify patients with HER2 overexpression that may be classified as HER2 negative based on IHC. Further studies are needed to determine the role of HER2 RNA overexpression as a predictive marker and to determine HER2 RNA expression across tumor types. Citation Format: Yifei Shen, Christian Cruz Pico, Vakul Mohanty, Amber Johnson, Jia Zeng, Kenna Mills Shaw, Ken Chen, Funda Meric-Bernstam. Utility of Assessing HER2 RNA expression for precision medicine [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 738.