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Gene Fusion Discovery with INTEGRATE

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Chimeric RNA

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2079))

Abstract

Next-generation sequencing (NGS) has become the primary technology for discovering gene fusions. Decreasing NGS costs have resulted in a growing quantity of patients with whole transcriptome sequencing (RNA-seq) and whole genome sequencing (WGS) data. We developed a gene fusion discovery tool, INTEGRATE, that leverages both RNA-seq and WGS data to reconstruct gene fusion junctions and genomic breakpoints by split-read alignment. INTEGRATE has become widely adopted by the larger cancer research community to discover biologically and clinically relevant gene fusions. Here we explain the rationale driving the development of the INTEGRATE tool and describe the detailed practical procedures for applying INTEGRATE to discover gene fusions using NGS data. INTEGRATE can be applied to both combined data and RNA-seq only data.

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References

  1. Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144(5):646–674

    Article  CAS  PubMed  Google Scholar 

  2. Mertens F et al (2015) The emerging complexity of gene fusions in cancer. Nat Rev Cancer 15(6):371–381

    Article  CAS  PubMed  Google Scholar 

  3. White NM, Feng FY, Maher CA (2013) Recurrent rearrangements in prostate cancer: causes and therapeutic potential. Curr Drug Targets 14(4):450–459

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Melo JV et al (1993) The ABL-BCR fusion gene is expressed in chronic myeloid leukemia. Blood 81(1):158–165

    Article  CAS  PubMed  Google Scholar 

  5. Maher CA et al (2009) Transcriptome sequencing to detect gene fusions in cancer. Nature 458(7234):97–101

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Maher CA et al (2009) Chimeric transcript discovery by paired-end transcriptome sequencing. Proc Natl Acad Sci U S A 106(30):12353–12358

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Iyer MK, Chinnaiyan AM, Maher CA (2011) ChimeraScan: a tool for identifying chimeric transcription in sequencing data. Bioinformatics 27(20):2903–2904

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Carrara M et al (2013) State-of-the-art fusion-finder algorithms sensitivity and specificity. Biomed Res Int 2013:340620

    Article  PubMed  PubMed Central  Google Scholar 

  9. Zhang J et al (2016) INTEGRATE: gene fusion discovery using whole genome and transcriptome data. Genome Res 26(1):108–118

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Li S et al (2013) Endocrine-therapy-resistant ESR1 variants revealed by genomic characterization of breast-cancer-derived xenografts. Cell Rep 4(6):1116–1130

    Article  CAS  PubMed  Google Scholar 

  11. Lei JT et al (2018) Functional annotation of ESR1 gene fusions in estrogen receptor-positive breast cancer. Cell Rep 24(6):1434–1444 e7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Griffith OL et al (2016) A genomic case study of mixed fibrolamellar hepatocellular carcinoma. Ann Oncol 27(6):1148–1154

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Griffith M et al (2016) Comprehensive genomic analysis reveals FLT3 activation and a therapeutic strategy for a patient with relapsed adult B-lymphoblastic leukemia. Exp Hematol 44(7):603–613

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Kim J et al (2018) MYBL1 rearrangements and MYB amplification in breast adenoid cystic carcinomas lacking the MYB-NFIB fusion gene. J Pathol 244(2):143–150

    Article  PubMed  Google Scholar 

  15. Pareja F et al (2019) Assessment of HMGA2 and PLAG1 rearrangements in breast adenomyoepitheliomas. NPJ Breast Cancer 5:6

    Article  PubMed  PubMed Central  Google Scholar 

  16. Zhang J, Mardis ER, Maher CA (2017) INTEGRATE-neo: a pipeline for personalized gene fusion neoantigen discovery. Bioinformatics 33(4):555–557

    CAS  PubMed  Google Scholar 

  17. Zhang J, Gao T, Maher CA (2017) INTEGRATE-Vis: a tool for comprehensive gene fusion visualization. Sci Rep 7(1):17808

    Article  PubMed  PubMed Central  Google Scholar 

  18. Wu TD, Nacu S (2010) Fast and SNP-tolerant detection of complex variants and splicing in short reads. Bioinformatics 26(7):873–881

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Kim D et al (2013) TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol 14(4):R36

    PubMed  PubMed Central  Google Scholar 

  20. Dobin A et al (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29(1):15–21

    Article  CAS  PubMed  Google Scholar 

  21. Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25(14):1754–1760

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Heemskerk B, Kvistborg P, Schumacher TN (2013) The cancer antigenome. EMBO J 32(2):194–203

    Article  CAS  PubMed  Google Scholar 

  23. Carreno BM et al (2015) Cancer immunotherapy. A dendritic cell vaccine increases the breadth and diversity of melanoma neoantigen-specific T cells. Science 348(6236):803–808

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Hundal J et al (2016) pVAC-Seq: a genome-guided in silico approach to identifying tumor neoantigens. Genome Med 8(1):11

    Article  PubMed  PubMed Central  Google Scholar 

  25. Tarasov A et al (2015) Sambamba: fast processing of NGS alignment formats. Bioinformatics 31(12):2032–2034

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Correspondence to Christopher A. Maher .

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Zhang, J., Maher, C.A. (2020). Gene Fusion Discovery with INTEGRATE. In: Li, H., Elfman, J. (eds) Chimeric RNA. Methods in Molecular Biology, vol 2079. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9904-0_4

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  • DOI: https://doi.org/10.1007/978-1-4939-9904-0_4

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-9903-3

  • Online ISBN: 978-1-4939-9904-0

  • eBook Packages: Springer Protocols

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