Development and validation of an RNA sequencing panel for gene fusions in soft tissue sarcoma.
Wanming HuLi YuanXin-Ke ZhangYang NiDongchun HongZhicai WangXiaomin LiYuan LingChao ZhangWanglong DengMinqi TianRan DingChao SongJianmin LiXing ZhangPublished in: Cancer science (2022)
Gene fusions are one of the most common genomic alterations in soft tissue sarcomas (STS), which contain more than 70 subtypes. In this study, a custom-designed RNA sequencing panel including 67 genes was developed and validated to identify gene fusions in STS. In total, 92 STS samples were analyzed using the RNA panel and 95.7% (88/92) successfully passed all the quality control parameters. Fusion transcripts were detected in 60.2% (53/88) of samples, including three novel fusions (MEG3-PLAG1, SH3BP1-NTRK1, and RPSAP52-HMGA2). The panel demonstrated excellent analytic accuracy, with 93.9% sensitivity and 100% specificity. The intra-assay, inter-assay, and personnel consistencies were all 100.0% in four samples and three replicates. In addition, different variants of ESWR1-FLI, COL1A1-PDGFB, NAB2-STAT6, and SS18-SSX were also identified in the corresponding subtypes of STS. In combination with histological and molecular diagnosis, 14.8% (13/88) patients finally changed preliminary histology-based classification. Collectively, this RNA panel developed in our study shows excellent performance on RNA from formalin-fixed, paraffin-embedded samples and can complement DNA-based assay, thereby facilitating precise diagnosis and novel fusion detection.
Keyphrases
- copy number
- genome wide
- high throughput
- quality control
- genome wide identification
- single cell
- end stage renal disease
- soft tissue
- newly diagnosed
- machine learning
- chronic kidney disease
- dna methylation
- ejection fraction
- deep learning
- prognostic factors
- single molecule
- gene expression
- patient reported outcomes
- functional connectivity
- circulating tumor
- patient reported
- sensitive detection