Abstract 1115: Targeted RNA sequencing improves transcript analysis in cancer samples

Abstract

Abstract RNA sequencing (RNA-seq) is a transcriptome profiling technology that provides multiple levels of insight into the genome. In addition to expression levels (transcript abundance), it generates endpoints such as alternative splicing, somatic mutations and rearrangements, which may have functional consequences in cancer. Although somatic mutations are generally identified by DNA sequencing, RNA-seq has the advantage of detecting allele-specific expression affecting a variant allele, as well as functional chimeric transcripts that result from structural rearrangements. Compared to microarray technologies, RNA-seq can provide additional information about novel transcripts. Due to the complexity of the human transcriptome and the variability of gene abundance, the cost of whole transcriptome sequencing to achieve sufficient coverage to detect these types of alterations remains high. To explore the feasibility of a more cost-effective method, we compared the performance of three different RNA-seq methods: whole-transcriptome-, exome-, and targeted RNA-seq, using RNA derived from cancer cell lines and Formaldehyde Fixed-Paraffin Embedded (FFPE) samples. For whole-transcriptome preparation, we used the Illumina TruSeq Stranded mRNA and total RNA kits for cell line and FFPE samples, respectively. Exome-RNAseq was performed using the Illumina Access kit. The libraries from whole-transcriptome RNAseq were subjected to hybridization capture using OncoPanel-an Agilent SureSelect baitset of 500 cancer-related genes. Compared to whole-transcriptome, exome- and targeted-RNA-seq demonstrated (1) higher coding exon coverage and multiplexing capability; (2) reduced rRNA composition to 1%; (3) comparable gene abundance information and (4) over 90% of reads aligned to coding exon regions in FFPE samples, compare to ∼30% when using whole transcriptome method. In conclusion, we demonstrated that exome- and targeted RNA-seq provide a cost-effective way to analyze a subset of the transcriptome. Furthermore, targeted RNA-seq can be highly multiplexed and is therefore amenable for large-scale tumor profiling in clinical or research settings. Citation Format: Ling Lin, Ryan Abo, Deniz Dolcen, Rachel Paquette, Angelica Laing, Luc de Waal, Aaron Thorner, Matthew Ducar, Liuda Ziaugra, Bruce Wollison, Marc Breneiser, William Hahn, Matthew Meyerson, Paul Van Hummelen, Laura MacConaill. Targeted RNA sequencing improves transcript analysis in cancer samples. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1115. doi:10.1158/1538-7445.AM2015-1115