Identification of novel fusion genes in lung cancer using breakpoint assembly of transcriptome sequencing data

Lynnette Fernandez-Cuesta, Ruping Sun, Roopika Menon, Julie George, Susanne Lorenz, Leonardo A. Meza-Zepeda, Martin Peifer, Dennis Plenker, Johannes M. Heuckmann, Frauke Leenders, Thomas Zander, Ilona Dahmen, Mirjam Koker, Jakob Schöttle, Roland T. Ullrich, Janine Altmüller, Christian Becker, Peter Nürnberg, Henrik Seidel, Diana BöhmFriederike Göke, Sascha Ansén, Prudence A. Russell, Gavin M. Wright, Zoe Wainer, Benjamin Solomon, Iver Petersen, Joachim H. Clement, Jörg Sänger, Odd Terje Brustugun, Åslaug Helland, Steinar Solberg, Marius Lund-Iversen, Reinhard Buettner, Jürgen Wolf, Elisabeth Brambilla, Martin Vingron, Sven Perner, Stefan A. Haas, Roman K. Thomas

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

Genomic translocation events frequently underlie cancer development through generation of gene fusions with oncogenic properties. Identification of such fusion transcripts by transcriptome sequencing might help to discover new potential therapeutic targets. We developed TRUP (Tumor-specimen suited RNA-seq Unified Pipeline) (https://github.com/ruping/TRUP), a computational approach that combines split-read and read-pair analysis with de novo assembly for the identification of chimeric transcripts in cancer specimens. We apply TRUP to RNA-seq data of different tumor types, and find it to be more sensitive than alternative tools in detecting chimeric transcripts, such as secondary rearrangements in EML4-ALK-positive lung tumors, or recurrent inactivating rearrangements affecting RASSF8.

Original languageEnglish (US)
Article number7
JournalGenome biology
Volume16
Issue number1
DOIs
StatePublished - Jan 5 2015
Externally publishedYes

Bibliographical note

Funding Information:
The study as well as written informed consent documents had been approved by the Institutional Review Board of the University of Cologne. Additional biospecimens for this study were obtained from the Victorian Cancer Biobank, Melbourne, Australia. The Institutional Review Board (IRB) of each participating institution approved collection and use of all patient specimens in this study. We are indebted to the patients donating their tumor specimens as part of the Clinical Lung Cancer Genome Project initiative. We thank Marek Franitza, Graziella Bosco, and Belarmina Valdes Naves for their technical assistance. We furthermore thank the regional computing center at the University of Cologne (RRZK) for providing the CPU time on the DFG-funded supercomputer ‘CHEOPS’ as well as the support. This work was supported by the Deutsche Krebshilfe as part of the small-cell lung cancer genome-sequencing consortium (grant ID: 109679 to RKT, MP, RB, PN, MV, and SAH). Additional funds were provided by the EU-Framework program CURELUNG (HEALTH-F2-2010-258677 to RKT, JW, and EB); by the German federal state North Rhine Westphalia (NRW) and the European Union (European Regional Development Fund: Investing In Your Future) within PerMed NRW (grant 005-1111-0025 to RKT, JW, and RB); by the Deutsche Forschungsgemeinschaft through TH1386/3-1 (to RKT) and through SFB832 (TP6 to RKT, RTU, and JW; TP5 to LCH); by the German Ministry of Science and Education (BMBF) as part of the NGFNplus program (grant 01GS08101 to RKT, JW, and PN) and as part of the eMed program (grant 01ZX1303A to RKT, RB, and JW); by the Deutsche Krebshilfe as part of the Oncology Centers of Excellence funding program (RKT, RB, and JW); and by Stand Up To Cancer -American Association for Cancer Research Innovative Research Grant (SU2C-AACR-IR60109 to RKT).

Publisher Copyright:
© 2015 Fernandez-Cuesta et al.; licensee BioMed Central.

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