Epigenetic alterations at distal enhancers are linked to proliferation in human breast cancer

Abstract

Aberrant DNA methylation is an early event in breast carcinogenesis and plays a critical role in regulating gene expression. Here, we perform genome-wide expression-methylation Quantitative Trait Loci (emQTL) analysis through the integration of DNA methylation and gene expression to identify disease-driving pathways under epigenetic control. By grouping the emQTLs using biclustering we identify associations representing important biological processes associated with breast cancer pathogenesis including regulation of proliferation and tumor-infiltrating fibroblasts. We report genome-wide loss of enhancer methylation at binding sites of proliferation-driving transcription factors including CEBP-β, FOSL1, and FOSL2 with concomitant high expression of proliferation-related genes in aggressive breast tumors as we confirm with scRNA-seq. The identified emQTL-CpGs and genes were found connected through chromatin loops, indicating that proliferation in breast tumors is under epigenetic regulation by DNA methylation. Interestingly, the associations between enhancer methylation and proliferation-related gene expression were also observed within known subtypes of breast cancer, suggesting a common role of epigenetic regulation of proliferation. Taken together, we show that proliferation in breast cancer is linked to loss of methylation at specific enhancers and transcription factor binding and gene activation through chromatin looping.

An integrated ‘omics approach highlights the role of epigenetic events to explain and predict response to neoadjuvant chemotherapy and bevacizumab

“…The fact that the pre-selected CpGs were also strongly associated to expression levels of genes [17] enabled us to calculate a “translated” signature by multiplying the methylation beta coefficients with the correlation coefficients of the gene with highest absolute correlation, thus constructing a predictive signature that could be applied also on gene expression data ( Table 1 ). When applying this signature to the gene expression data ( Supplementary Figure1B ) we obtained an area under the ROC curves of 0.870.…”

“…We have previously shown that genome-wide associations ( in cis and in trans ) between DNA methylation and gene expression (emQTLs) are a powerful approach to identify transcriptional programs based on epigenetic modifications and TF activity, differentially regulated between patients [16, 37]. To identify such epigenetically regulated transcriptional programs involved in response to therapy as well as patient group-specific alterations in DNA methylation, we applied the emQTL approach to delta methylation and delta expression values before and after treatment with FEC +/- Bevacizumab (delta emQTL).…”

“…To assess the potential of DNA methylation in pre-treatment tumor samples to predict treatment response, we performed a machine learning approach (LASSO) to identify the CpGs most predictive of pathologic complete response (pCR). 44,263 CpGs identified in our previous studies [17] to be involved in epigenetic de-regulation (and associated to gene expression) in one of four important functions in breast cancer were used in the LASSO analysis: 1) estrogen signaling, 2) non-estrogen regulated proliferation in tumor cells, 3) varying immune infiltration, or 4) varying fibroblast infiltration were further studied for their potential to predict treatment response.…”

“…Preselection of CpGs for identification of the predictive signature was performed based on the results in Ankill et al [17], where we show that 44,263 CpGs capture important biological variation in breast cancer involving estrogen signaling, non-estrogen-controlled regulation of proliferation, immune infiltration and fibroblast infiltration. The majority of CpGs in the identified predictive signature were associated to regulation of the cell cycle, showing that epigenetic marks related to proliferation can be predictive of response, which is in concordance with previous studies [15, 21].…”

“…The emQTL approach enabled us to identify variation in DNA methylation with concomitant variation in gene expression in breast tumors. This led to the discovery of a mechanism to maintain continuously active estrogen receptor signaling in ER positive breast tumors through loss of DNA methylation at enhancers carrying binding sites for the transcription factors (TFs) ER, FOXA1 and GATA3 [16], and loss of methylation at enhancers carrying binding sites of TFs related to proliferation in ER negative tumors [17]. Treatment-induced epigenetic changes at enhancers through DNA methylation have to our knowledge not yet been investigated.…”