Abstract 144: Genome-wide DNA methylation changes in AI-resistant breast cancer models during E2-treatment
2020-08-15

Abstract Disruption of estrogen signaling with tamoxifen or aromatase inhibitors (AI) is the clinical standard for the treatment of estrogen receptor-positive breast cancer, yet resistance to antiestrogen therapies is inevitable. The long-term E2-deprived breast cancer models MCF-7:5C and MCF-7:2A mimic AI resistance and moreover are vulnerable to E2-induced apoptosis due to the reconfiguration of their survival signaling. E2-induced apoptosis which results from the accumulation of endoplasmic reticulum (ER), oxidative, and inflammatory stresses, is a new paradigm to subvert endocrine resistance, with sensors of the unfolded protein response (UPR) being important mediators of ER stress (Ariazi et al. 2011; Fan et al. 2013, 2015). Here we asked whether epigenetic modifications may play a role in this and investigated genome-wide changes of 5C and 2A DNA methylation patterns that occurred during E2 stimulation during a 72h time course with WS8 cells as a reference. Methylation patterns were established using the Illumina Infinium HumanMethylation450 BeadChip (Service XS, Leiden, NL), and raw intensities were normalized and filtered using the bioconductor minfi package. A linear model (bioconductor limma package) has been built to detect differentially methylated CpGs. F-statistics were calculated by empirical Bayes moderation of standard errors with "trend" and "robust" set “on”. We also performed whole-genome bisulfite sequencing (WGBS) in untreated cells using the Illumina HiSeq platform (GATC Biotech, Konstanz, DE) to obtain maximum baseline CpG coverage. Trimmed WGBS reads were aligned to the hg38 genome (Bismarck, PMC3102221), duplicates removed, and methylation levels extracted with MethylDackel (https://github.com/dpryan79/MethylDackel) with a 3x coverage threshold (Wreczycka et al. 2017). Raw methylation levels were smoothed and differential methylation called using the bsseq package (Hansen et al. 2012). At baseline, WGBS-derived profiles showed a 2-fold higher degree of hypomethylation (beta &amp;lt;0.2) in 5C compared to 2A and WS8. In time course E2-treatments we identified 134 dynamic CpGs across all three models (Padj &amp;lt; 0.05). Methylation status mainly decreased, with few specific changes in 5C and 2A. Among 120 affected CpG sites matching to GeneHancer regulatory elements 23 locate to ERE sites suggesting a direct control of inferred target genes (UCSC genome browser). Their matching to ER stress-, UPR- and apoptosis-related gene sets identified among others ATF6B, EIF2AK4, HSPB1, TNF, GANAB and PPIA. Currently, we are performing functional enrichment analyses and E2-responsive CpGs are being correlated with respective transcriptome signatures. Our preliminary data suggest that E2-triggered methylation changes in cell models vulnerable to E2-induced apoptosis may aid the identification of potential therapeutic targets towards overcoming endocrine resistance. Citation Format: Reiner Hoppe, Siarhei Kandabarau, Ping Fan, Stefan Winter, Balkees Abderrahman, Heather Cunliffe, Werner Schroth, V. Craig Jordan, Hiltrud B. Brauch. Genome-wide DNA methylation changes in AI-resistant breast cancer models during E2-treatment [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 144.