Abstract 5411: Demonstrated improvements in tumor profiling with enzymatic ribosomal RNA depletion and streamlined RNA-sequencing library preparation

Abstract

Abstract High resolution RNA analysis using next-generation sequencing (RNA-seq) is a rapidly growing application in cancer research. Formalin-fixed paraffin-embedded (FFPE) tissue is a ubiquitous resource for clinical studies. However, the ability to generate high quality libraries is confounded by the low quality and yield of RNA extracted from FFPE specimen. To enable optimal interrogation of such a clinically-relevant tissue resource, it is critical to identify RNA-seq library construction workflows that improve performance using challenging and degraded sample types. In this study, the effects of RNA type, quality, and quantity on RNA-seq library construction are assessed, and expectations regarding sequencing data quality are addressed. Included are recommendations for quality control measures and input-specific modifications that may improve performance Three workflows employing either bead-based or enzymatic strategies for the removal of ribosomal RNA content were used to prepare RNA-seq libraries from degraded paired breast normal and tumor samples. Enzymatic depletion followed by library preparation using the KAPA RNA HyperPrep1 workflow identified the highest number of transcripts for each sample, translating to a 4.9-fold increase in number of differentially expressed transcripts detected between normal and tumor samples. Of the transcripts identified as differentially expressed exclusively by Kapa, 174 are protein-coding RNAs, many of which are frequently dysregulated in breast cancer. In contrast, only two protein-coding RNAs were identified exclusively by the alternative workflows. RealTime Ready Custom panels were used for independent quantitative rt-PCR assessment. Of a subset of 71 transcripts identified exclusively by Kapa, up to 69 (97%) were validated as differentially expressed. Additional performance improvements of the KAPA RNA HyperPrep workflow include coverage balance across transcripts, lower duplication rate, technical replicate reproducibility, agreement across input quantities, and gene expression concordance between paired fresh frozen and FFPE samples. 1For Research Use Only. Not for use in diagnostic procedures. Citation Format: Nancy H. Nabilsi, Drew Cheney, Leendert Cloete, Ida van Jaarsveld, Rachel Kasinskas, Jennifer Pavlica. Demonstrated improvements in tumor profiling with enzymatic ribosomal RNA depletion and streamlined RNA-sequencing library preparation [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 5411. doi:10.1158/1538-7445.AM2017-5411