Title

RNA-Seq for the detection of gene fusions in solid tumors: development and validation of the JAX FusionSeq™ 2.0 assay.

Document Type

Article

Publication Date

2-1-2022

Publication Title

J Mol Med (Berl)

Keywords

JGM

JAX Source

J Mol Med (Berl) 2022 Feb; 100(2):323-335

Volume

100

Issue

2

First Page

323

Last Page

335

ISSN

1432-1440

PMID

35013752

DOI

https://doi.org/10.1007/s00109-021-02149-0

Abstract

Whole transcriptome sequencing (RNA-Seq) has gained prominence for the detection of fusions in solid tumors. Here, we describe the development and validation of an in-house RNA-Seq-based test system (FusionSeq™ 2.0) for the detection of clinically actionable gene fusions, in formalin-fixed paraffin-embedded (FFPE) specimens, using seventy tumor samples with varying fusion status. Conditions were optimized for RNA input of 50 ng, shown to be adequate to call known fusions at as low as 20% neoplastic content. Evaluation of assay performance between FFPE and fresh-frozen (FF) tissues exhibited little to no difference in fusion calling capability. Performance analysis of the assay validation data determined 100% accuracy, sensitivity, specificity, and reproducibility. This clinically developed and validated RNA-Seq-based approach for fusion detection in FPPE samples was shown to be on par if not superior to off-the-shelf commercially offered assays. With gene fusions implicated in a variety of cancer types, offering high-quality, low-cost molecular testing services for FFPE specimens will serve to best benefit the patient and the advancement of precision medicine in molecular oncology. KEY MESSAGES: A custom RNA-Seq-based test system (FusionSeq™ 2.0) for the detection of clinically actionable gene fusions, Evaluation of assay performance between FFPE and fresh-frozen (FF) tissues exhibited little to no difference in fusion calling capability. The assay can be performed with low RNA input and neoplastic content. Performance characteristics of the assay validation data determined 100% accuracy, sensitivity, specificity, and reproducibility.

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