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

Nohr, E.; Kunder, C. A.; Jones, C.; Sutton, S.; Fung, E.; Zhu, H.; Feng, S. J.; Gojenola, L.; Bustamante, C.; Zehnder, J. L.; Costa, H. A.

doi:10.1101/870634

bioRxiv · 10.1101/870634

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

Nohr, E.·Kunder, C. A.·Jones, C.·Sutton, S.·Fung, E.·Zhu, H.·Feng, S. J.·Gojenola, L.·Bustamante, C.·Zehnder, J. L.·Costa, H. A.

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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.

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Nohr, E., Kunder, C. A., Jones, C., Sutton, S., Fung, E., Zhu, H., Feng, S. J., Gojenola, L., Bustamante, C., Zehnder, J. L., Costa, H. A.. 2019-12-10. Development and clinical validation of a targeted RNAseq panel (Fusion-STAMP) for diagnostic and predictive gene fusion detection in solid tumors. https://doi.org/10.1101/870634

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