Identification of gene fusions from human lung cancer mass spectrometry data

BMC Genomics

Research

Xiao Chang¹  Fengli Zhou²  Xiaobin Xing³  Guangwu Wei⁴  Lu Xie⁵  Yixue Li⁵  Han Sun⁵  Ying He⁵  Wei Li⁶  Jia Jia⁶  Jing Li⁶  Yunqin Chen⁶ 

[1] Department of Pediatrics, Division of Human Genetics, The Center for Applied Genomics, Children's Hospital of Philadelphia, 19104, Philadelphia, PA, USA;Department of Respiration, The Third Affiliated Hospital of Sun Yat-sen University, 510630, Guangzhou, China;Genome Biology Unit, European Molecular Biology Laboratory, 69117, Heidelberg, Germany;Key Laboratory of Systems Biology, Shanghai Institutes for Biological Science, Chinese Academy of Sciences, 200031, Shanghai, China;Key Laboratory of Systems Biology, Shanghai Institutes for Biological Science, Chinese Academy of Sciences, 200031, Shanghai, China;Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, 201203, Shanghai, China;Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, 201203, Shanghai, China;

关键词: Gene Fusion;    Splice Event;    Mass Spectrometry Data;    Anaplastic Large Cell Lymphoma;    Small Cell Lung Carcinoma;   

DOI  :  10.1186/1471-2164-14-S8-S5

来源: Springer

【 摘 要 】

BackgroundTandem mass spectrometry (MS/MS) technology has been applied to identify proteins, as an ultimate approach to confirm the original genome annotation. To be able to identify gene fusion proteins, a special database containing peptides that cross over gene fusion breakpoints is needed.MethodsIt is impractical to construct a database that includes all possible fusion peptides originated from potential breakpoints. Focusing on 6259 reported and predicted gene fusion pairs from ChimerDB 2.0 and Cancer Gene Census, we for the first time created a database CanProFu that comprehensively annotates fusion peptides formed by exon-exon linkage between these pairing genes.ResultsApplying this database to mass spectrometry datasets of 40 human non-small cell lung cancer (NSCLC) samples and 39 normal lung samples with stringent searching criteria, we were able to identify 19 unique fusion peptides characterizing gene fusion events. Among them 11 gene fusion events were only found in NSCLC samples. And also, 4 alternative splicing events were characterized in cancerous or normal lung samples.ConclusionsThe database and workflow in this work can be flexibly applied to other MS/MS based human cancer experiments to detect gene fusions as potential disease biomarkers or drug targets.

【 授权许可】

Unknown   
© Sun et al.; licensee BioMed Central Ltd. 2013. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.