title: deFuse: an algorithm for gene fusion discovery in tumor RNA-Seq data.
abstract: Gene fusions created by somatic genomic rearrangements are known to play an important role in the onset and development of some cancers, such as lymphomas and sarcomas. RNA-Seq (whole transcriptome shotgun sequencing) is proving to be a useful tool for the discovery of novel gene fusions in cancer transcriptomes. However, algorithmic methods for the discovery of gene fusions using RNA-Seq data remain underdeveloped. We have developed deFuse, a novel computational method for fusion discovery in tumor RNA-Seq data. Unlike existing methods that use only unique best-hit alignments and consider only fusion boundaries at the ends of known exons, deFuse considers all alignments and all possible locations for fusion boundaries. As a result, deFuse is able to identify fusion sequences with demonstrably better sensitivity than previous approaches. To increase the specificity of our approach, we curated a list of 60 true positive and 61 true negative fusion sequences (as confirmed by RT-PCR), and have trained an adaboost classifier on 11 novel features of the sequence data. The resulting classifier has an estimated value of 0.91 for the area under the ROC curve. We have used deFuse to discover gene fusions in 40 ovarian tumor samples, one ovarian cancer cell line, and three sarcoma samples. We report herein the first gene fusions discovered in ovarian cancer. We conclude that gene fusions are not infrequent events in ovarian cancer and that these events have the potential to substantially alter the expression patterns of the genes involved; gene fusions should therefore be considered in efforts to comprehensively characterize the mutational profiles of ovarian cancer transcriptomes.
authors.affiliation: Centre for Translational and Applied Genomics, BC Cancer Agency, Vancouver, British Columbia, Canada.
authors.forename: Andrew
authors.initials: A
authors.lastname: McPherson
authors.forename: Fereydoun
authors.initials: F
authors.lastname: Hormozdiari
authors.forename: Abdalnasser
authors.initials: A
authors.lastname: Zayed
authors.forename: Ryan
authors.initials: R
authors.lastname: Giuliany
authors.forename: Gavin
authors.initials: G
authors.lastname: Ha
authors.forename: Mark G F
authors.initials: MG
authors.lastname: Sun
authors.forename: Malachi
authors.initials: M
authors.lastname: Griffith
authors.forename: Alireza
authors.initials: A
authors.lastname: Heravi Moussavi
authors.forename: Janine
authors.initials: J
authors.lastname: Senz
authors.forename: Nataliya
authors.initials: N
authors.lastname: Melnyk
authors.forename: Marina
authors.initials: M
authors.lastname: Pacheco
authors.forename: Marco A
authors.initials: MA
authors.lastname: Marra
authors.forename: Martin
authors.initials: M
authors.lastname: Hirst
authors.forename: Torsten O
authors.initials: TO
authors.lastname: Nielsen
authors.forename: S Cenk
authors.initials: SC
authors.lastname: Sahinalp
authors.forename: David
authors.initials: D
authors.lastname: Huntsman
authors.forename: Sohrab P
authors.initials: SP
authors.lastname: Shah
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D002277:Carcinoma / Q000235:genetics; D045744:Cell Line, Tumor; D005260:Female; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics; D006801:Humans; D008297:Male; D008545:Melanoma / Q000235:genetics; D008969:Molecular Sequence Data; D009154:Mutation; D050596:Oncogene Fusion; D010051:Ovarian Neoplasms / Q000235:genetics*; D011471:Prostatic Neoplasms / Q000235:genetics; D012509:Sarcoma / Q000235:genetics; D017423:Sequence Analysis, RNA / Q000379:methods*; D012878:Skin Neoplasms / Q000235:genetics