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Analysis of the coding genome of diffuse large B-cell lymphoma

Nature Genetics volume 43, pages 830–837 (2011)Cite this article

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Abstract

Diffuse large B-cell lymphoma (DLBCL) is the most common form of human lymphoma. Although a number of structural alterations have been associated with the pathogenesis of this malignancy, the full spectrum of genetic lesions that are present in the DLBCL genome, and therefore the identity of dysregulated cellular pathways, remains unknown. By combining next-generation sequencing and copy number analysis, we show that the DLBCL coding genome contains, on average, more than 30 clonally represented gene alterations per case. This analysis also revealed mutations in genes not previously implicated in DLBCL pathogenesis, including those regulating chromatin methylation (MLL2; 24% of samples) and immune recognition by T cells. These results provide initial data on the complexity of the DLBCL coding genome and identify novel dysregulated pathways underlying its pathogenesis.

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Figure 1: DLBCL non-silent mutation load.
Figure 2: Copy number analysis of the six DLBCL discovery cases.
Figure 3: DLBCL harbors a heterogeneous load of numerical and structural genomic aberrations.
Figure 4: Recurrent mutations in DLBCL.
Figure 5: MLL2 is mutated in a large fraction of DLBCLs.
Figure 6: Disruption of histone and/or chromatin modification genes is a major feature of DLBCL.

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  • 19 August 2011

    In the version of this supplementary file originally posted online, Supplementary Figures 2, 4 and 6 and Supplementary Tables 12, 14, 18 and 19 contained errors. The errors have been corrected in this file as of 19 August 2011.

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Acknowledgements

We would like to thank T. Palomero, E. Tzilianos, V. Miljkovic and the Genomics Technologies Shared Resource of the Herbert Irving Comprehensive Cancer Center at Columbia University; D. Burgess at Roche NimbleGen (Madison, Wisconsin, USA) and B. Boese at 454 Life Sciences (Branford, Connecticut, USA) for assistance with the whole-exome capture and sequencing procedure; K. Basso and A. Holmes for help with the manual curation and analysis of the copy number data; M. Malladi and Y.K. Lieu for help with the analysis of B2M and CD58; and J. Zhang for filtering the list of candidate mutations against the database of germline variants discovered from the St. Jude Children's Research Hospital-Washington University Pediatric Cancer Genome Project. The Affymetrix SNP6.0 array experiments were processed in part at the Affymetrix Research Services Laboratory. Automated DNA sequencing was performed at Genewiz, Inc. This work was supported by US National Institutes of Health (NIH) Grants PO1-CA092625 and RO1-CA37295 (to R.D.-F.), a Specialized Center of Research grant from the Leukemia & Lymphoma Society (to R.D.-F.), NIH Grant CA121852-05, the Northeast Biodefense Center (U54-AI057158) and the National Library of Medicine (1R01LM010140-01) (to R.R.), and the Associazione Italiana per la Ricerca sul Cancro (AIRC) Special Program Molecular Clinical Oncology-5 per mille (Contract No. 10007, Milan, Italy). A. Chiarenza was on leave from the Division of Hematology, Ospedale Ferrarotto, University of Catania, Catania, Italy.

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Authors and Affiliations

  1. Institute for Cancer Genetics, Columbia University, New York, New York, USA

    Laura Pasqualucci, Giulia Fabbri, Annalisa Chiarenza, Victoria A Wells, Adina Grunn, Monica Messina & Riccardo Dalla-Favera

  2. Herbert Irving Comprehensive Cancer Center, Columbia University, New York, New York, USA

    Laura Pasqualucci, Govind Bhagat & Riccardo Dalla-Favera

  3. Department of Pathology & Cell Biology, Columbia University, New York, New York, USA

    Laura Pasqualucci, Govind Bhagat & Riccardo Dalla-Favera

  4. Department of Biomedical Informatics and Center for Computational Biology and Bioinformatics, Columbia University, New York, New York, USA

    Vladimir Trifonov, Oliver Elliot, Joseph Chan & Raul Rabadan

  5. Department of Pathology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA

    Jing Ma & Charles G Mullighan

  6. Division of Hematology, Department of Clinical and Experimental Medicine and Interdisciplinary Research Center of Autoimmune Diseases, Amedeo Avogadro University of Eastern Piedmont, Novara, Italy

    Davide Rossi & Gianluca Gaidano

  7. Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA

    Amy Chadburn

  8. Department of Genetics & Development, Columbia University, New York, New York, USA

    Riccardo Dalla-Favera

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  1. Laura Pasqualucci
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Contributions

L.P. and R.D.-F. designed the study and wrote the manuscript. L.P. conducted experiments, analyzed data and supervised the study. G.F., A. Chiarenza, A.G., V.A.W. and M.M. performed PCR amplification and sequencing analysis. C.G.M. and J.M. developed methods for analysis of high-density SNP array data, which was conducted by C.G.M., J.M., L.P. and G.F. Pathologically characterized subject samples were provided by D.R., G.G., G.B. and A. Chadburn. V.T. and R.R. analyzed high-throughput sequencing data and developed the ComFocal algorithm for analysis of copy number data with the help of O.E. and J.C. All authors read and approved the manuscript.

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Correspondence to Laura Pasqualucci or Riccardo Dalla-Favera.

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Supplementary Note, Supplementary Figures 1–6 and Supplementary Tables 1–19. (PDF 1768 kb)

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Pasqualucci, L., Trifonov, V., Fabbri, G. et al. Analysis of the coding genome of diffuse large B-cell lymphoma. Nat Genet 43, 830–837 (2011). https://doi.org/10.1038/ng.892

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