DNA methylation at enhancers identifies distinct breast cancer lineages

Thomas Fleischer, Xavier Tekpli, Anthony Mathelier, Shixiong Wang, Daniel Nebdal, Hari P. Dhakal, Kristine Kleivi Sahlberg, Ellen Schlichting, Anne-Lise Børresen-Dale, Elin Borgen, Bjørn Naume, Ragnhild Eskeland, Arnoldo Frigessi, Jörg Tost, Antoni Hurtado and Vessela N. Kristensen ()
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Thomas Fleischer: Oslo University Hospital, The Norwegian Radium Hospital
Xavier Tekpli: Oslo University Hospital, The Norwegian Radium Hospital
Anthony Mathelier: Oslo University Hospital, The Norwegian Radium Hospital
Shixiong Wang: University of Oslo
Daniel Nebdal: Oslo University Hospital, The Norwegian Radium Hospital
Hari P. Dhakal: Oslo University Hospital
Kristine Kleivi Sahlberg: Oslo University Hospital, The Norwegian Radium Hospital
Ellen Schlichting: Oslo University Hospital
Anne-Lise Børresen-Dale: Oslo University Hospital, The Norwegian Radium Hospital
Elin Borgen: Oslo University Hospital
Bjørn Naume: Oslo University Hospital
Ragnhild Eskeland: University of Oslo
Arnoldo Frigessi: University of Oslo and Research Support Services, Oslo University Hospital
Jörg Tost: CEA–Institut de Génomique
Antoni Hurtado: Oslo University Hospital, The Norwegian Radium Hospital
Vessela N. Kristensen: Oslo University Hospital, The Norwegian Radium Hospital

Nature Communications, 2017, vol. 8, issue 1, 1-14

Abstract: Abstract Breast cancers exhibit genome-wide aberrant DNA methylation patterns. To investigate how these affect the transcriptome and which changes are linked to transformation or progression, we apply genome-wide expression–methylation quantitative trait loci (emQTL) analysis between DNA methylation and gene expression. On a whole genome scale, in cis and in trans, DNA methylation and gene expression have remarkably and reproducibly conserved patterns of association in three breast cancer cohorts (n = 104, n = 253 and n = 277). The expression–methylation quantitative trait loci associations form two main clusters; one relates to tumor infiltrating immune cell signatures and the other to estrogen receptor signaling. In the estrogen related cluster, using ChromHMM segmentation and transcription factor chromatin immunoprecipitation sequencing data, we identify transcriptional networks regulated in a cell lineage-specific manner by DNA methylation at enhancers. These networks are strongly dominated by ERα, FOXA1 or GATA3 and their targets were functionally validated using knockdown by small interfering RNA or GRO-seq analysis after transcriptional stimulation with estrogen.

Date: 2017
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DOI: 10.1038/s41467-017-00510-x

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