Study

Arriba: accurate and efficient detection of gene fusions from RNA-Seq (H021)

Study ID Alternative Stable ID Type
EGAS00001003554 Other

Study Description

The identification of gene fusions from RNA sequencing data is a routine task in cancer research and precision oncology. However, despite the availability of many computational tools, fusion detection remains challenging. Existing methods suffer from poor prediction accuracy and are computationally demanding. We developed Arriba, a novel fusion detection algorithm with high sensitivity and short runtime. When applied to a large collection of published pancreatic cancer samples (n=803), Arriba identified a variety of driver fusions, many of which affected druggable proteins, including ALK, BRAF, FGFR2, NRG1, NTRK1, NTRK3, RET, and ROS1. The fusions were significantly associated with KRAS wild-type tumors and involved proteins stimulating the MAPK signaling pathway, suggesting that they substitute for activating mutations in KRAS. In addition, we confirmed the transforming potential of two novel fusions, RRBP1-RAF1 and RASGRP1-ATP1A1, in cellular assays. These results demonstrate Arriba’s utility in both basic cancer research and clinical translation.

Study Datasets 1 dataset.

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Dataset ID Description Technology Samples
EGAD00001005069
Whole genome and transcriptome sequencing of a pancreatic tumor harboring a RASGRP1 gene fusion
HiSeq X Ten,Illumina HiSeq 4000 2

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