Development and clinical validation of a targeted RNAseq panel (Fusion-STAMP) for diagnostic and predictive gene fusion detection in solid tumors

Abstract

RNA sequencing is emerging as a powerful technique to detect a diverse array of fusions in human neoplasia, but few clinically validated assays have been described to date. We designed and validated a hybrid-capture RNAseq assay for FFPE tissue (Fusion-STAMP). It fully targets the transcript isoforms of 43 genes selected for their known impact as actionable targets of existing and emerging anti-cancer therapies (especially in lung adenocarcinomas), prognostic features, and/or utility as diagnostic cancer biomarkers (especially in sarcomas). 57 fusion results across 34 samples were evaluated. Fusion-STAMP demonstrated high overall accuracy with 98% sensitivity and 94% specificity for fusion detection. There was high intra- and inter-run reproducibility. Detection was sensitive to approximately 10% tumor, though this is expected to be impacted by fusion transcript expression levels, hybrid capture efficiency, and RNA quality. Challenges of clinically validating RNA sequencing for fusion detection include a low average RNA quality in FFPE specimens, and variable RNA total content and expression profile per cell. These challenges contribute to highly variable on-target rates, total read pairs, and total mapped read pairs. False positive results may be caused by intergenic splicing, barcode hopping / index hopping, or misalignment. Despite this, Fusion-STAMP demonstrates high overall performance metrics for qualitative fusion detection and is expected to provide clinical utility in identifying actionable fusions.