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J Mol Diagn. 2019 Mar;21(2):352-365. doi: 10.1016/j.jmoldx.2018.10.003. Epub 2018 Dec 4.

Design, Optimization, and Multisite Evaluation of a Targeted Next-Generation Sequencing Assay System for Chimeric RNAs from Gene Fusions and Exon-Skipping Events in Non-Small Cell Lung Cancer.

Author information

1
Asuragen, Inc., Austin, Texas.
2
Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, Kansas.
3
Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, Kansas; University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, Kansas.
4
Q Squared Solutions Expression Analysis LLC, Morrisville, North Carolina.
5
The Molecular Pathology Centre, Jewish General Hospital, Montreal, Quebec, Canada.
6
Asuragen, Inc., Austin, Texas. Electronic address: glatham@asuragen.com.

Abstract

Lung cancer accounts for approximately 14% of all newly diagnosed cancers and is the leading cause of cancer-related deaths. Chimeric RNA resulting from gene fusions (RNA fusions) and other RNA splicing errors are driver events and clinically addressable targets for non-small cell lung cancer (NSCLC). The reliable assessment of these RNA markers by next-generation sequencing requires integrated reagents, protocols, and interpretive software that can harmonize procedures and ensure consistent results across laboratories. We describe the development and verification of a system for targeted RNA sequencing for the analysis of challenging, low-input solid tumor biopsies that includes reagents for nucleic acid quantification and library preparation, run controls, and companion bioinformatics software. Assay development reconciled sequence discrepancies in public databases, created predictive formalin-fixed, paraffin-embedded RNA qualification metrics, and eliminated read misidentification attributable to index hopping events on the next-generation sequencing flow cell. The optimized and standardized system was analytically verified internally and in a multiphase study conducted at five independent laboratories. The results show accurate, reproducible, and sensitive detection of RNA fusions, alternative splicing events, and other expression markers of NSCLC. This comprehensive approach, combining sample quantification, quality control, library preparation, and interpretive bioinformatics software, may accelerate the routine implementation of targeted RNA sequencing of formalin-fixed, paraffin-embedded samples relevant to NSCLC.

PMID:
30529127
DOI:
10.1016/j.jmoldx.2018.10.003
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