FindDNAFusion: An Analytical Pipeline with Multiple Software Tools Improves Detection of Cancer-Associated Gene Fusions from Genomic DNA

Abstract

Detection of cancer-associated gene fusions is crucial for diagnosis, prognosis, and treatment selection. Many bioinformatics tools are available for the detection of fusion transcripts by RNA sequencing, but there are fewer well-validated software tools for DNA next-generation sequencing (NGS). A 542-gene solid tumor NGS panel was designed, with exonic probes supplemented with intronic bait probes against genes commonly involved in oncogenic fusions, with a focus on lung cancer. Three software tools for the detecting gene fusions in this DNA-NGS panel were selected and evaluated. The performance of these tools was compared after a pilot study, and each was configured for optimal batch analysis and detection rate. A blacklist for filtering common tool-specific artifacts, and criteria for selecting clinically reportable fusions, were established. Visualization tools for annotating and confirming somatic fusions were applied. Subsequently, a full clinical validation was used for comparing the results to those from in situ hybridization and/or RNA sequencing. With JuLI, Factera, and GeneFuse, 94.1%, 88.2%, and 66.7% of expected fusions were detected, respectively. With a combinatorial pipeline (termed FindDNAFusion), developed by integrating fusion-calling tools with methods for fusion filtering, annotating, and flagging reportable calls, the accuracy of detection of intron-tiled genes was improved to 98.0%. FindDNAFusion is an accurate and efficient tool in detecting somatic fusions in DNA-NGS panels with intron-tiled bait probes when RNA is unavailable.