Back to Search Start Over

Detection of gene fusions using targeted next-generation sequencing: a comparative evaluation.

Authors :
Heydt C
Wölwer CB
Velazquez Camacho O
Wagener-Ryczek S
Pappesch R
Siemanowski J
Rehker J
Haller F
Agaimy A
Worm K
Herold T
Pfarr N
Weichert W
Kirchner T
Jung A
Kumbrink J
Goering W
Esposito I
Buettner R
Hillmer AM
Merkelbach-Bruse S
Source :
BMC medical genomics [BMC Med Genomics] 2021 Feb 27; Vol. 14 (1), pp. 62. Date of Electronic Publication: 2021 Feb 27.
Publication Year :
2021

Abstract

Background: Gene fusions represent promising targets for cancer therapy in lung cancer. Reliable detection of multiple gene fusions is therefore essential.<br />Methods: Five commercially available parallel sequencing assays were evaluated for their ability to detect gene fusions in eight cell lines and 18 FFPE tissue samples carrying a variety of known gene fusions. Four RNA-based assays and one DNA-based assay were compared; two were hybrid capture-based, TruSight Tumor 170 Assay (Illumina) and SureSelect XT HS Custom Panel (Agilent), and three were amplicon-based, Archer FusionPlex Lung Panel (ArcherDX), QIAseq RNAscan Custom Panel (Qiagen) and Oncomine Focus Assay (Thermo Fisher Scientific).<br />Results: The Illumina assay detected all tested fusions and showed the smallest number of false positive results. Both, the ArcherDX and Qiagen panels missed only one fusion event. Among the RNA-based assays, the Qiagen panel had the highest number of false positive events. The Oncomine Focus Assay (Thermo Fisher Scientific) was the least adequate assay for our purposes, seven fusions were not covered by the assay and two fusions were classified as uncertain. The DNA-based SureSelect XT HS Custom Panel (Agilent) missed three fusions and nine fusions were only called by one software version. Additionally, many false positive fusions were observed.<br />Conclusions: In summary, especially RNA-based parallel sequencing approaches are potent tools for reliable detection of targetable gene fusions in clinical diagnostics.

Details

Language :
English
ISSN :
1755-8794
Volume :
14
Issue :
1
Database :
MEDLINE
Journal :
BMC medical genomics
Publication Type :
Academic Journal
Accession number :
33639937
Full Text :
https://doi.org/10.1186/s12920-021-00909-y