Abstract Growing interest in cancer classification and progression has accelerated the rate of novel gene fusions discovery with increasing recognition of their roles as biomarkers. RNA-Seq is an attractive method for expressed fusion discovery and detection because of its ability to provide unbiased fusion sequencing information. The ability to detect low expressing fusion transcripts, however, require high sequencing depth and represents a significant financial barrier and identification of clinically relevant fusion sequences from a large data set can be a bioinformatics challenge. To address these challenges we have tested the Ovation® Fusion Panel Target Enrichment System V2, a targeted RNA sequencing method using the Single Primer Enrichment Technology (SPET), with a number of control and clinical samples. Initial studies were performed using a comprehensive target enrichment panel targeting 502 genes with three samples from Horizon DX containing known fusions. Target enriched libraries were constructed with 10 ng and 100 ng inputs and the data was analyzed using the NuFuseD pipeline (available as a point and click BaseSpace application or downloadable linux package) which has been optimized for fusion analysis from this data. Expected fusions were identified at both input levels, even when down sampled to 500K reads, with fewer fusion calls compared to other publically available fusion detection software (Chimerascan and SOAPFuse), suggesting a lower false positive rate. NuFuseD fusion calls are provided with a P-value to help prioritize the identified fusions for subsequent validation. Additionally, NuFuseD detected novel fusions in the control samples demonstrating the advantage of a comprehensive panel compared to more restricted panels. We further validated the target panel using control RNA (UHR and Human Brain) and fresh or FFPE cell lines (NCI-H2228, HCC1937) to further demonstrate our ability to identify known fusions. Finally, the system was evaluated at an external site using patient FFPE samples. These samples (N=8) were from a set of breast, liver and ovarian cancers, containing a unique fusion in 4 of the samples based on DNA based sequencing. Only 1 of the 4 expected fusions were identified using whole transcriptome data (100 million reads) while 3 of the 4 fusions were detected with this assay (10 million reads) demonstrating its ability to generate targeted RNA sequencing libraries with increased sensitivity of gene fusion detection and reduced sequencing costs compared to standard RNA-Seq methods. Citation Format: Ashesh Saraiya, Brandon Young, Tobias Meißner, Brian L. Jones, Stephanie C. Huelga, Doug A. Amorese. A comprehensive target enrichment panel for fusion detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 487. doi:10.1158/1538-7445.AM2017-487