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Treatment with the anti‐angiogenic drug bevacizumab in addition to chemotherapy has shown efficacy for breast cancer in some clinical trials, but better biomarkers are needed to optimally select patients for treatment. Here, we present an omics approach where DNA methylation profiles are integrated with gene expression and results from proteomic data in breast cancer patients to predict response to therapy and pinpoint response‐related epigenetic events. Fresh‐frozen tumor biopsies taken before, during, and after treatment from human epidermal growth factor receptor 2 negative non‐metastatic patients receiving neoadjuvant chemotherapy with or without bevacizumab were subjected to molecular profiling. Here, we report that DNA methylation at enhancer CpGs related to cell cycle regulation can predict response to chemotherapy and bevacizumab for the estrogen receptor positive subset of patients (AUC = 0.874), and we validated this observation in an independent patient cohort with a similar treatment regimen (AUC = 0.762). Combining the DNA methylation scores with the scores from a previously published protein signature resulted in a slight increase in the prediction performance (AUC = 0.784). We also show that tumors receiving the combination treatment underwent more extensive epigenetic alterations. Finally, we performed an integrative expression–methylation quantitative trait loci analysis on alterations in DNA methylation and gene expression levels, showing that the epigenetic alterations that occur during treatment are different between responders and non‐responders and that these differences may be explained by the proliferation–epithelial‐to‐mesenchymal transition axis through the activity of grainyhead like transcription factor 2. Using tumor purity computed from copy number data, we developed a method for estimating cancer cell‐specific methylation to confirm that the association to response reflects DNA methylation in cancer cells. Taken together, these results support the potential for clinical benefit of the addition of bevacizumab to chemotherapy when administered to the correct patients. [ABSTRACT FROM AUTHOR]

Long non-coding RNAs (lncRNAs) are involved in breast cancer pathogenesis through chromatin remodeling, transcriptional and post-transcriptional gene regulation. We report robust associations between lncRNA expression and breast cancer clinicopathological features in two population-based cohorts: SCAN-B and TCGA. Using co-expression analysis of lncRNAs with protein coding genes, we discovered three distinct clusters of lncRNAs. In silico cell type deconvolution coupled with single-cell RNA-seq analyses revealed that these three clusters were driven by cell type specific expression of lncRNAs. In one cluster lncRNAs were expressed by cancer cells and were mostly associated with the estrogen signaling pathways. In the two other clusters, lncRNAs were expressed either by immune cells or fibroblasts of the tumor microenvironment. To further investigate the cis-regulatory regions driving lncRNA expression in breast cancer, we identified subtype-specific transcription factor (TF) occupancy at lncRNA promoters. We also integrated lncRNA expression with DNA methylation data to identify long-range regulatory regions for lncRNA which were validated using ChiA-Pet-Pol2 loops. lncRNAs play an important role in shaping the gene regulatory landscape in breast cancer. We provide a detailed subtype and cell type-specific expression of lncRNA, which improves the understanding of underlying transcriptional regulation in breast cancer. Long non-coding RNAs (lncRNAs) have been shown to be involved in breast cancer pathogenesis through regulation of multiple steps of gene expression. lncRNA expression patterns are also associated with breast cancer clinicopathological features in large population-based cohorts. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Altered DNA methylation patterns are found in many diseases, particularly in cancer, where the analysis of DNA methylation holds the promise to provide diagnostic, prognostic and predictive information of great clinical value. Methylation of the promoter-associated CpG island of GSTP1 occurs in many hormone-sensitive cancers, has been shown to be a biomarker for the early detection of cancerous lesions and has been associated with important clinical parameters, such as survival and response to treatment. In the current manuscript, we assessed the performance of several widely-used sodium bisulfite conversion-dependent methods (methylation-specific PCR, MethyLight, pyrosequencing and MALDI mass-spectrometry) for the analysis of DNA methylation patterns in the GSTP1 promoter. We observed large discordances between the results obtained by the different technologies. Cloning and sequencing of the investigated region resolved single-molecule DNA methylation patterns and identified heterogeneous DNA methylation patterns as the underlying cause of the differences. Heterogeneous DNA methylation patterns in the GSTP1 promoter constitute a major obstacle to the implementation of DNA methylation-based analysis of GSTP1 and might explain some of the contradictory findings in the analysis of the significance of GSTP1 promoter methylation in breast cancer. [ABSTRACT FROM AUTHOR]

Radiotherapy (RT) is a central treatment modality for breast cancer patients. The purpose of our study was to investigate the DNA methylation changes in tumors following RT, and to identify epigenetic markers predicting treatment outcome. Paired biopsies from patients with inoperable breast cancer were collected both before irradiation ( n = 20) and after receiving 10-24 Gray (Gy) ( n = 19). DNA methylation analysis was performed by using Illumina Infinium 27K arrays. Fourteen genes were selected for technical validation by pyrosequencing. Eighty-two differentially methylated genes were identified in irradiated ( n = 11) versus nonirradiated ( n = 19) samples (false discovery rate, FDR = 1.1%). Methylation levels in pathways belonging to the immune system were most altered after RT. Based on methylation levels before irradiation, a panel of five genes ( H2AFY, CTSA, LTC4S, IL5RA and RB1) were significantly associated with clinical response ( p = 0.041). Furthermore, the degree of methylation changes for 2,516 probes correlated with the given radiation dose. Within the 2,516 probes, an enrichment for pathways involved in cellular immune response, proliferation and apoptosis was identified (FDR < 5%). Here, we observed clear differences in methylation levels induced by radiation, some associated with response to treatment. Our study adds knowledge on the molecular mechanisms behind radiation response. [ABSTRACT FROM AUTHOR]

Breast cancer is a heterogeneous disease for which alterations in DNA methylation patterns have been shown to be of biological and clinical importance. Here we report on the integrated analysis of molecular alterations including the methylation status of 27 gene promoters analyzed by highly quantitative pyrosequencing, and the association to gene expression, germline genotype and clinical parameters including survival. Breast cancer specific deregulation of DNA methylation (both hyper- and hypomethylation) was found in twenty genes including ACVR1, OGG1, IL8 and TFF1. The methylation level in the promoter regions was significantly negatively correlated to gene expression for twelve genes (such as MST1R, ST6GAL1 and TFF1) indicating that a gain of aberrant methylation (hypermethylation) inhibits gene expression. Multiple associations between molecular and clinical parameters were identified, and multivariate statistical analysis demonstrated that methylation was more strongly associated to clinical parameters than gene expression for the investigated genes. The methylation level of BCAP31 and OGG1 showed significant association to survival, and these associations were validated in a larger patient cohort (The Cancer Genome Atlas). Our study provides evidence for the promise of DNA methylation alterations for clinical applications. [ABSTRACT FROM AUTHOR]

Background: Aberrant DNA methylation of regulatory genes has frequently been found in human breast cancers and correlated to clinical outcome. In the present study we investigate stage specific changes in the DNA methylation patterns in order to identify valuable markers to understand how these changes affect breast cancer progression.Methods: Quantitative DNA methylation analyses of 12 candidate genes ABCB1, BRCCA1, CDKN2A, ESR1, GSTP1, IGF2, MGMT, HMLH1, PPP2R2B, PTEN, RASSF1A and FOXC1 was performed by pyrosequencing a series of 238 breast cancer tissue samples from DCIS to invasive tumors stage I to IV.Results: Significant differences in methylation levels between the DCIS and invasive stage II tumors were observed for six genes RASSF1A, CDKN2A, MGMT, ABCB1, GSTP1 and FOXC1. RASSF1A, ABCB1 and GSTP1 showed significantly higher methylation levels in late stage compared to the early stage breast carcinoma. Z-score analysis revealed significantly lower methylation levels in DCIS and stage I tumors compared with stage II, III and IV tumors. Methylation levels of PTEN, PPP2R2B, FOXC1, ABCB1 and BRCA1 were lower in tumors harboring TP53 mutations then in tumors with wild type TP53. Z-score analysis showed that TP53 mutated tumors had significantly lower overall methylation levels compared to tumors with wild type TP53. Methylation levels of RASSF1A, PPP2R2B, GSTP1 and FOXC1 were higher in ER positive vs. ER negative tumors and methylation levels of PTEN and CDKN2A were higher in HER2 positive vs. HER2 negative tumors. Z-score analysis also showed that HER2 positive tumors had significantly higher z-scores of methylation compared to the HER2 negative tumors. Univariate survival analysis identifies methylation status of PPP2R2B as significant predictor of overall survival and breast cancer specific survival.Conclusions: In the present study we report that the level of aberrant DNA methylation is higher in late stage compared with early stage of invasive breast cancers and DCIS for genes mentioned above. [ABSTRACT FROM AUTHOR]

Abstract: Breast cancer is a heterogeneous disease that can be divided in subtypes based on histology, gene expression profiles as well as differences in genomic aberrations. Distinct global DNA methylation profiles have been reported in normal breast epithelial cells as well as in breast tumors. However, the influence of the tumor methylome on the previously described subgroups of breast cancer is not fully understood. Here we report the DNA methylation profiles of 80 breast tumors using a panel of 807 cancer related genes interrogating 1505 CpG sites. We identified three major clusters based on the methylation profiles; one consisting of mainly tumors of myoepithelial origin and two other clusters with tumors of predominantly luminal epithelial origin. The clusters were different with respect to estrogen receptor status, TP53 status, ErbB2 status and grade. The most significantly differentially methylated genes including HDAC1, TFF1, OGG1, BMP3, FZD9 and HOXA11 were confirmed by pyrosequencing. Gene Ontology analysis revealed enrichment for genes involved in developmental processes including homeobox domain genes (HOXA9, HOXA11, PAX6, MYBL2, ISL1 and IPF1) and (ETS1, HDAC1, CREBBP, GAS7, SPI1 and TBX1). Extensive correlation to mRNA expression was observed. Pathway analyses identified a significant association with canonical (curated) pathways such as hepatic fibrosis including genes like EGF, NGFR and TNF, dendritic cell maturation and the NF-κB signaling pathway. Our results show that breast tumor expression subtypes harbor major epigenetic differences and tumors with similar gene expression profiles might belong to epigenetically different subtypes. Some of the transcription factors identified, with key roles in differentiation and development might play a role in inducing and maintaining the different phenotypes. [ABSTRACT FROM AUTHOR]

Abstract: Epigenetic changes can be defined as stable molecular alterations of a cellular phenotype such as the gene expression profile of a cell that are heritable during somatic cell divisions (and sometimes germ line transmissions) but do not involve changes of the DNA sequence itself. Epigenetic phenomena are mediated by several molecular mechanisms comprising histone modifications, polycomb/trithorax protein complexes, small non-coding or antisense RNAs and DNA methylation. These different modifications are closely interconnected. Epigenetic regulation is critical in normal growth and development and closely conditions the transcriptional potential of genes. Epigenetic mechanisms convey genomic adaption to an environment thereby ultimately contributing towards given phenotype. In this review we will describe the various aspects of epigenetics and in particular DNA methylation in breast carcinogenesis and their potential application for diagnosis, prognosis and treatment decision. [Copyright &y& Elsevier]

Background: Using array comparative genomic hybridization (aCGH), a large number of deleted genomic regions have been identified in human cancers. However, subsequent efforts to identify target genes selected for inactivation in these regions have often been challenging. Methods: We integrated here genome-wide copy number data with gene expression data and non-sense mediated mRNA decay rates in breast cancer cell lines to prioritize gene candidates that are likely to be tumour suppressor genes inactivated by bi-allelic genetic events. The candidates were sequenced to identify potential mutations. Results: This integrated genomic approach led to the identification of RIC8A at 11p15 as a putative candidate target gene for the genomic deletion in the ZR-75-1 breast cancer cell line. We identified a truncating mutation in this cell line, leading to loss of expression and rapid decay of the transcript. We screened 127 breast cancers for RIC8A mutations, but did not find any pathogenic mutations. No promoter hypermethylation in these tumours was detected either. However, analysis of gene expression data from breast tumours identified a small group of aggressive tumours that displayed low levels of RIC8A transcripts. qRT-PCR analysis of 38 breast tumours showed a strong association between low RIC8A expression and the presence of TP53 mutations (P = 0.006). Conclusion: We demonstrate a data integration strategy leading to the identification of RIC8A as a gene undergoing a classical double-hit genetic inactivation in a breast cancer cell line, as well as in vivo evidence of loss of RIC8A expression in a subgroup of aggressive TP53 mutant breast cancers. [ABSTRACT FROM AUTHOR]

A conference paper about DNA methylation and gene expression patterns in breast cancer progressions presented. It discusses that the genes get differentially methylated when the cancer progresses. It mentions several methods involved in the study including methylation array, gene expression and miRNA expression array. The study found significant changes in DNA methylation patterns between tissues with different stages of progression in breast cancer.

Abstract: Introduction: We investigated the effect of genetic variation on gene expression in blood from a cohort of BC survivors. Further, we investigated the associations that were specific for BC survivors by performing identical analyses for a group of healthy women and comparing the results. Methods: eQTL analysis was performed for 288 BC survivors (full data set). Further, using a subset of the data, eQTL analyses were performed on 288 BC survivors and on 81 healthy women separately and results were compared. Results: A large number of associations were observed for the BC survivors, and the expression of human leukocyte antigen genes was found associated with SNPs in 100 genes. The comparison analyses with healthy women revealed associations occurring specifically in BC survivors, and the genes showed enrichment for immune system processes. Conclusions: The results suggest that the immune system has a different constitution in BC survivors compared to healthy women. [Copyright &y& Elsevier]