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Comprehensive characterization of complex structural variations in cancer by directly comparing genome sequence reads

Nature Biotechnology volume 32, pages 1106–1112 (2014)Cite this article

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Abstract

The development of high-throughput sequencing technologies has advanced our understanding of cancer. However, characterizing somatic structural variants in tumor genomes is still challenging because current strategies depend on the initial alignment of reads to a reference genome. Here, we describe SMUFIN (somatic mutation finder), a single program that directly compares sequence reads from normal and tumor genomes to accurately identify and characterize a range of somatic sequence variation, from single-nucleotide variants (SNV) to large structural variants at base pair resolution. Performance tests on modeled tumor genomes showed average sensitivity of 92% and 74% for SNVs and structural variants, with specificities of 95% and 91%, respectively. Analyses of aggressive forms of solid and hematological tumors revealed that SMUFIN identifies breakpoints associated with chromothripsis and chromoplexy with high specificity. SMUFIN provides an integrated solution for the accurate, fast and comprehensive characterization of somatic sequence variation in cancer.

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Figure 1: SMUFIN.
Figure 2: Large structural variation in pediatric medulloblastoma tumor MB1.
Figure 3: Identification and validation of chromoplexy in mantle cell lymphoma tumor M003.

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Acknowledgements

The ICGC-CLL Genome Consortium is funded by the Spanish Ministry of Economy and Competitiveness (MINECO) through the Instituto de Salud Carlos III (ISCIII), Red Temática de Investigación del Cáncer (RTICC) of the ISCIII (RD12/0036/0036) and National Institute of Bioinformatics (INB). This study was also supported by Ministerio de Economía y Competitividad, Secretaría De Estado De Investigación, Desarrollo e Innovación PLAN NACIONAL de I+D+i 2008-2011, Subprograma de Apoyo a Centros y Unidades de excelencia Severo Ochoa; and Plan Nacional SAF12/38432; Generalitat de Catalunya AGAUR 2009-SGR-992; Fondo de Investigaciones Sanitarias (PI11/01177); Association for International Cancer Research (12-0142). J.O.K. and M.S.W. were supported by the European Commission (Health-F2-2010-260791). C.L.-O. is an investigator of the Botin Foundation. E.C. and M.O. are ICREA Academia Researchers. We also thank S. Guijarro and C. Gómez for their excellent technical assistance.

Author information

Author notes

  1. Valentí Moncunill and Santi Gonzalez: These authors contributed equally to this work.

Authors and Affiliations

  1. Joint IRB-BSC Program in Computational Biology, Barcelona Supercomputing Center, Barcelona, Spain

    Valentí Moncunill, Santi Gonzalez, Lise O Andrieux, Laura Martinez, Montserrat Puiggròs, Romina Royo, Josep L Gelpí, Modesto Orozco & David Torrents

  2. Department of Pathology, Hematopathology Unit, Hospital Clinic, Institut d'Investigació Biomèdica August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain

    Sílvia Beà, Itziar Salaverria, Cristina Royo, Alba Navarro & Elias Campo

  3. Computational Bioinformatics, National Institute of Bioinformatics, Barcelona, Spain

    Montserrat Puiggròs, Romina Royo & Josep L Gelpí

  4. European Molecular Biology Laboratory, Genome Biology Research Unit, Heidelberg, Germany

    Maia Segura-Wang, Adrian M Stütz & Jan O Korbel

  5. Department of Biochemistry and Molecular Biology, University of Barcelona, Barcelona, Spain

    Josep L Gelpí & Modesto Orozco

  6. Centro Nacional de Analisis Genomico (CNAG), Barcelona, Spain

    Ivo G Gut

  7. Departamento de Bioquímica y Biología Molecular, Universidad de Oviedo–IUOPA, Oviedo, Spain

    Carlos López-Otín & Xose S Puente

  8. Institute for Research in Biomedicine (IRB Barcelona), Barcelona, Spain

    Modesto Orozco

  9. Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain

    Elias Campo & David Torrents

Authors
  1. Valentí Moncunill
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  2. Santi Gonzalez
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  3. Sílvia Beà
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  8. Montserrat Puiggròs
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  10. Adrian M Stütz
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  11. Alba Navarro
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  12. Romina Royo
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  13. Josep L Gelpí
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  14. Ivo G Gut
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  15. Carlos López-Otín
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Contributions

V.M., S.G. and D.T. conceived and designed the study. L.O.A., L.M., M.P., J.L.G., R.R. and M.O. performed data analysis. S.B., I.S., C.R., A.N., E.C. and I.G.G. generated and experimentally validated the MCL samples. M.S.-W., A.M.S. and J.O.K. generated and experimentally validated the MB1 sample. C.L.-O., X.S.P., E.C. and D.T. wrote the manuscript; and D.T. supervised the whole study.

Corresponding author

Correspondence to David Torrents.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–5 and Supplementary Tables 2 and 4 (PDF 4689 kb)

Supplementary Table 1 (XLSX)

List of somatic modifications affecting the in silico genome (XLSX 951 kb)

Supplementary Table 3 (XLSX)

Results of SMUFIN and others methods for the in silico validation analysis (XLSX 5687 kb)

Supplementary Table 5 (XLSX)

Results of SMUFIN on the Mantle Lymphoma M004 (XLSX 773 kb)

Supplementary Table 6 (XLSX)

Validation sequences of M003 lage structural variants. The identifyiers shown here correspond to the ones of Supplementary Table 8. (XLSX 23 kb)

Supplementary Table 7 (XLSX)

Results of SMUFIN on the Medulloblastoma MB1 (XLSX 208 kb)

Supplementary Table 8

Results of SMUFIN on the Mantle Lymphoma M003 (XLSX 194 kb)

Supplementary Source Code

Compressed ZIP file with SMUFIN's source code (ZIP 1659 kb)

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Moncunill, V., Gonzalez, S., Beà, S. et al. Comprehensive characterization of complex structural variations in cancer by directly comparing genome sequence reads. Nat Biotechnol 32, 1106–1112 (2014). https://doi.org/10.1038/nbt.3027

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