DNA methylation at enhancers identifies distinct breast cancer lineages

Thomas Fleischer(Oslo University Hospital), Xavier Tekpli(Oslo University Hospital), Anthony Mathelier(Oslo University Hospital), Shixiong Wang(University of Oslo), Daniel Nebdal(Oslo University Hospital), Hari Prasad Dhakal(Oslo University Hospital), Kristine Kleivi Sahlberg(Oslo University Hospital), Ellen Schlichting(Oslo University Hospital), Torill Sauer(Akershus University Hospital), Jürgen Geisler(Akershus University Hospital), Solveig Hofvind(OsloMet – Oslo Metropolitan University), Tone F. Bathen(Norwegian University of Science and Technology), Olav Engebraaten(Oslo University Hospital), Øystein Garred(Oslo University Hospital), Gry Aarum Geitvik(Oslo University Hospital), Anita Langerød(Oslo University Hospital), Rolf Kåresen(Oslo University Hospital), Gunhild M. Mælandsmo(Oslo University Hospital), Hege G. Russnes(Oslo University Hospital), Thérese Sørlie(Oslo University Hospital), Ole Christian Lingjærde(University of Oslo), Helle Kristine Skjerven(Vestre Viken Hospital Trust), Daehoon Park(Vestre Viken Hospital Trust), Britt Fritzman(Østfold Hospital Trust), Anne‐Lise Børresen‐Dale(Oslo University Hospital), Elin Borgen(Oslo University Hospital), Bjørn Naume(Oslo University Hospital), Ragnhild Eskeland(Oslo University Hospital), Arnoldo Frigessi(Oslo University Hospital), Jörg Tost(Commissariat à l'Énergie Atomique et aux Énergies Alternatives), Antoni Hurtado(Oslo University Hospital), Vessela N. Kristensen(University of Oslo)
Nature Communications
November 3, 2017
Cited by 160Open Access
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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.


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