Purpose HTG EdgeSeq Next Generation Sequencing (NGS) technology is a targeted RNA Sequencing (RNA-Seq) platform based on quantitative nuclease protection chemistry, which requires substantially less sample input than RNA-Seq (one formalin-fixed paraffin-embedded (FFPE) slide versus 4-6 slides). The automated library processor allows fast downstream NGS analysis, making it a promising technology for clinical application and companion diagnostics, especially in samples with limited availability. Given the differences from standard RNA-Seq protocols, it is critical to investigate the performance of HTG EdgeSeq compared to whole transcriptome RNA-Seq technology. We investigated the concordance between HTG EdgeSeq and RNA-Seq on a set of FFPE samples.
Procedure The HTG EdgeSeq Oncology Biomarker Panel (OBP) is comprised of 2558 genes including genes relevant to immuno-oncology and oncology pathways. To evaluate the concordance between the two platforms, 57 FFPE samples from diverse tumor types and varying tumor content (16-100%) were analyzed. One slide was analyzed per sample with the HTG EdgeSeq OBP, while four to six slides were analyzed with whole transcriptome analysis using the Illumina TruSeq Total RNA library kit. A subset of samples and genes were selected for analysis by RT-qPCR using a customized Taqman 15 gene array. Data from the three platforms was analyzed and compared for concordance.
Data Summary Fifty-three samples passed QC on the HTG EdgeSeq platform, while only 29 samples passed a distribution-based QC of the RNA-Seq. For samples that passed QC using both technologies, the median Spearman correlation was 0.73 (25th percentile was 0.70), indicating good, but not linear correlation. In the samples that failed RNA-Seq QC, the median Spearman correlation was 0.30. Probes with low correlation (<0.25) between HTG EdgeSeq and RNA-Seq had an average interquartile range of expression less than 2 log2(CPM) indicating low dynamic range of expression. The HTG EdgeSeq platform showed a tendency towards more detection of low abundance genes indicating either higher sensitivity or higher background. Comparison of RT-qPCR to HTG EdgeSeq showed good sample to sample correlation however, in many cases, genes with low expression in HTG EdgeSeq were undetectable in RT-qPCR leaving the low-end sensitivity of HTG EdgeSeq unclear.
Conclusions HTG EdgeSeq produced fewer QC failures compared to whole transcriptome RNA-Seq while using less tissue. The resulting data showed sound correlation between RNA-Seq, HTG EdgeSeq, and RT-qPCR platforms, especially for genes with moderate to high expression, enabling relatively low risk translation between biomarker platforms. Further, these results were consistent across various cancer types. The characteristics demonstrated in this study support the potential use of HTG EdgeSeq for clinical biomarker applications.
Citation Format: Dennis O'Rourke, Jorge F. Sanchez-Garcia, P. Alexander Rolfe, Alice Huang, Danyi Wang, Juergen Scheuenpflug, Zheng Feng. Comparison of HTG-edge targeted RNA sequencing platform with whole transcriptome RNA sequencing for clinical biomarker studies [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 2016.