Abstract
Cancer immunotherapy has led to an unprecedented, long-lasting response in populations susceptible to the therapies. Despite the therapeutic potential, identifying biomarkers and stratifying populations that are likely to respond has been a challenge. Gene expression profiling has previously been successfully used to stratify individuals based on survival and treatment characteristics, but there exist limitations with the prevalent technologies. In particular, full transcriptome gene expression estimates use limited biological material to measure the concentrations of tens of thousands uninformative genes and often lack the depth required to accurately measure expression levels of lowly-expressed genes. These genes may be critical to the identification of a signature associated with immunotherapy responders. To efficiently measure the expression of the key genes potentially informative of an immunotherapy response, we developed a high-throughput targeted gene expression solution measured by our RNA Ion Oncomine Immune Response Profiling panel* containing 395 genes. This panel provides information about the expression of genes involved in tumor checkpoint inhibition (including CTLA4, PD-1, PD-L1, OX-40, 4-1BB, TIM3, LAG3) and other targets such as CSF1R, and IDO1, as well as additional markers of T cell signaling pathway, interferon signaling, and markers of tumor infiltrating lymphocytes (TIL). We used publicly available TCGA data to demonstrate the need and develop a solution for a new normalization procedure that allows for accurate comparisons of samples within various cancer types. Furthermore, we verified a linear and unbiased estimate of fold change in our assays across mixing concentrations of a cell-line titration experiment. Finally, by achieving a high correlation (r > .99) of technical replicates, along with robust expression estimation even at low input amounts (10 ng RNA), our panel offers a valuable solution for biomarker research in cancer immunotherapy.
*For research use only. Not for use in diagnostic procedures.
Citation Format: Aleksandr Pankov, Yongming Sun, Yuan-Chieh Ku, Warren Tom, Jianping Zheng, Timothy Looney, Janice Au-Yong, Fiona Hyland, Ann Mongan. Validation of targeted gene expression profiling panel for identifying biomarker signatures of immunotherapy responders. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2016 Oct 20-23; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2017;5(3 Suppl):Abstract nr B17.
