GeniOmics

Public knowledge document

Accurate and efficient detection of gene fusions from RNA sequencing data.

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 show Arriba'

Open platform knowledge

Accurate and efficient detection of gene fusions from RNA sequencing data.

> 商业许可源文 · EUROPE_PMC · [CC-BY](https://creativecommons.org/licenses/by/)

书目信息

  • 引用：Uhrig S, Ellermann J, Walther T, Burkhardt P, Fröhlich M, Hutter B, Toprak UH, Neumann O, Stenzinger A, Scholl C, Fröhling S, Brors B. (2021). Accurate and efficient detection of gene fusions from RNA sequencing data. Genome research. PMID 33441414 · PMC7919457 · DOI 10.1101/gr.257246.119
  • 证据类型：PRIMARY_RESEARCH
  • 主题：rna-seq
  • 被引次数（采集时）：433
  • 原始记录：[Europe PMC](https://europepmc.org/article/MED/33441414)
  • 来源许可：[CC-BY](https://creativecommons.org/licenses/by/)

    • 作者摘要（按来源许可复用）

    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 show Arriba's utility in both basic cancer research and clinical translation.

    合规说明

    本页保存的是来源文献书目信息及其在 CC-BY 许可下公开的作者摘要。除去除来源 HTML 标签和规范化空白外，摘要未作内容改写。本页不代表 GeniOmics 的医学建议；原文版权、署名和许可仍归原权利人，请通过原始记录核对最新版本、更正或撤稿状态。

    Accurate and efficient detection of gene fusions from RNA sequencing data. · GeniOmics