Epigenomic evolution in diffuse large B-cell lymphomas

Heng Pan, Yanwen Jiang, Michela Boi, Fabrizio Tabbò, David Redmond, Kui Nie, Marco Ladetto, Annalisa Chiappella, Leandro Cerchietti, Rita Shaknovich, Ari M. Melnick, Giorgio G. Inghirami (), Wayne Tam () and Olivier Elemento ()
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Heng Pan: Institute for Computational Biomedicine, Weill Cornell Medical College
Yanwen Jiang: Institute for Computational Biomedicine, Weill Cornell Medical College
Michela Boi: Weill Cornell Medical College
Fabrizio Tabbò: Weill Cornell Medical College
David Redmond: Institute for Computational Biomedicine, Weill Cornell Medical College
Kui Nie: Weill Cornell Medical College
Marco Ladetto: Azienda Ospedaliera Santi Antonio e Biagio e Cesare Arrigo
Annalisa Chiappella: Azienda Ospedaliero Universitaria Città della Salute e della Scienza di Torino
Leandro Cerchietti: Weill Cornell Medical College
Rita Shaknovich: Weill Cornell Medical College
Ari M. Melnick: Institute for Computational Biomedicine, Weill Cornell Medical College
Giorgio G. Inghirami: Weill Cornell Medical College
Wayne Tam: Weill Cornell Medical College
Olivier Elemento: Institute for Computational Biomedicine, Weill Cornell Medical College

Nature Communications, 2015, vol. 6, issue 1, 1-12

Abstract: Abstract The contribution of epigenomic alterations to tumour progression and relapse is not well characterized. Here we characterize an association between disease progression and DNA methylation in diffuse large B-cell lymphoma (DLBCL). By profiling genome-wide DNA methylation at single-base pair resolution in thirteen DLBCL diagnosis–relapse sample pairs, we show that DLBCL patients exhibit heterogeneous evolution of tumour methylomes during relapse. We identify differentially methylated regulatory elements and determine a relapse-associated methylation signature converging on key pathways such as transforming growth factor-β (TGF-β) receptor activity. We also observe decreased intra-tumour methylation heterogeneity from diagnosis to relapsed tumour samples. Relapse-free patients display lower intra-tumour methylation heterogeneity at diagnosis compared with relapsed patients in an independent validation cohort. Furthermore, intra-tumour methylation heterogeneity is predictive of time to relapse. Therefore, we propose that epigenomic heterogeneity may support or drive the relapse phenotype and can be used to predict DLBCL relapse.

Date: 2015
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DOI: 10.1038/ncomms7921

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