Accurate RNA sequencing from formalin-fixed cancer tissue to represent high-quality transcriptome from frozen tissue
- Author(s)
- Li, J; Fu, C; Speed, TP; Wang, W; Symmans, WF;
- Journal Title
- JCO Precision Oncology
- Publication Type
- Journal Article in press
- Abstract
- Purpose: Accurate transcriptional sequencing (RNA-seq) from formalin-fixation and paraffin-embedding (FFPE) tumor samples presents an important challenge for translational research and diagnostic development. In addition, there are now several different protocols to prepare a sequencing library from total RNA. We evaluated the accuracy of RNA-seq data generated from FFPE samples in terms of expression profiling. Methods: We designed a biospecimen study to directly compare gene expression results from different protocols to prepare libraries for RNA-seq from human breast cancer tissues, with randomization to fresh-frozen (FF) or FFPE conditions. The protocols were compared using multiple computational methods to assess alignment of reads to reference genome, and the uniformity and continuity of coverage; as well as the variance and correlation, of overall gene expression and patterns of measuring coding sequence, phenotypic patterns of gene expression, and measurements from representative multigene signatures. Results: The principal determinant of variance in gene expression was use of exon capture probes, followed by the conditions of preservation (FF versus FFPE), and phenotypic differences between breast cancers. One protocol, with RNase H-based rRNA depletion, exhibited least variability of gene expression measurements, strongest correlation between FF and FFPE samples, and was generally representative of the transcriptome from standard FF RNA-seq protocols. Conclusion: Method of RNA-seq library preparation from FFPE samples had marked effect on the accuracy of gene expression measurement compared to matched FF samples. Nevertheless, some protocols produced highly concordant expression data from FFPE RNA-seq data, compared to RNA-seq results from matched frozen samples.
- Publisher
- ASCO
- Research Division(s)
- Bioinformatics
- PubMed ID
- 29862382
- Publisher's Version
- https://doi.org/10.1200/PO.17.00091
- NHMRC Grants
- NHMRC/1054618,
- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2018-06-26 12:34:42
Last Modified: 2018-06-26 01:02:36