Fusions4U: a resource of validated and annotated gene fusions in 328 cancer cell lines

Large-scale genomic rearrangements in cancer cells can lead to the creation of fusion genes which alter the expression or function of the partner genes. Some fusion genes act as tumour drivers and the use of kinase inhibitors in patients with specific fusions have led to breakthroughs in cancer therapy. The large clinical and scientific interest in fusions has led to the development of software that use RNA sequencing data to identify fusion transcripts. Unfortunately, fusion transcript callers output many predictions which lack underlying genomic rearrangements and large datasets with validated fusions are scarce. This paper and the accompanying Fusions4U web application present a resource of validated and annotated gene fusions for 328 cell lines from the Cancer Cell Line Encyclopedia. Predicted fusion transcripts from Arriba and STAR-Fusion were analysed with our published validation pipeline that uses matched whole-genome sequencing data to identify discordantly mapped read pairs and candidate genomic breakpoints that support genuine fusion events. This resulted in 8,753 and 2,244 validated fusion transcripts for Arriba and STAR-Fusion predictions, respectively, with 1,596 fusions common to both. Additional layers of annotation include alternative splicing of fusion transcripts, kinases, microRNA host genes, genes in the COSMIC Cancer Gene Census, as well as known fusion gene pairs from the Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer and the TumorFusions dataset. We furthermore analysed information about fusion genes together with cell line data from the PRISM drug repurposing screening as an example of how this dataset can be used. This resource can be used to design experiments for functional studies and drug development, alone or in combination with publicly available information for the Cancer Cell Line Encyclopedia cell lines. The large collection of validated fusion transcripts with candidate genomic breakpoints can also be used in development and evaluation of bioinformatic tools for fusion transcript detection.