DNA methylation at enhancers identifies distinct breast cancer lineages

Activation of Bivalent Gene POU4F1 Promotes and Maintains Basal-like Breast Cancer

Basal-like breast cancer (BLBC) is the most aggressive molecular subtype of breast cancer with worse prognosis and fewer treatment options. The underlying mechanisms upon BLBC transcriptional dysregulation and its upstream transcription factors (TFs) remain unclear. Here, among the hyperactive candidate TFs of BLBC identified by bioinformatic analysis, POU4F1 is uniquely upregulated in BLBC and is associated with poor prognosis. POU4F1 is necessary for the tumor growth and malignant phenotypes of BLBC through regulating G1/S transition by direct binding at the promoter of CDK2 and CCND1. More importantly, POU4F1 maintains BLBC identity by repressing ERα expression through CDK2-mediated EZH2 phosphorylation and subsequent H3K27me3 modification in ESR1 promoter. Knocking out POU4F1 in BLBC cells reactivates functional ERα expression, rendering BLBC sensitive to tamoxifen treatment. In-depth epigenetic analysis reveals that the subtype-specific re-configuration and activation of the bivalent chromatin in the POU4F1 promoter contributes to its unique expression in BLBC, which is maintained by DNA demethylase TET1. Together, these results reveal a subtype-specific epigenetically activated TF with critical role in promoting and maintaining BLBC, suggesting that POU4F1 is a potential therapeutic target for BLBC.

An integrated omics approach highlights how epigenetic events can explain and predict response to neoadjuvant chemotherapy and bevacizumab in breast cancer

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.

Epigenetic disruption of the RARγ complex impairs its function to bookmark AR enhancer interactions required for enzalutamide sensitivity in prostate cancer

The current study in prostate cancer (PCa) focused on the genomic mechanisms at the cross-roads of pro-differentiation signals and the emergence of lineage plasticity. We explored an understudied cistromic mechanism involving RARγ's ability to govern AR cistrome-transcriptome relationships, including those associated with more aggressive PCa features. The RARγ complex in PCa cell models was enriched for canonical cofactors, as well as proteins involved in RNA processing and bookmarking. Identifying the repertoire of miR-96 bound and regulated gene targets, including those recognition elements marked by m6A, revealed their significant enrichment in the RARγ complex. RARγ significantly enhanced the AR cistrome, particularly in active enhancers and super-enhancers, and overlapped with the binding of bookmarking factors. Furthermore, RARγ expression led to nucleosome-free chromatin enriched with H3K27ac, and significantly enhanced the AR cistrome in G2/M cells. RARγ functions also antagonized the transcriptional actions of the lineage master regulator ONECUT2. Similarly, gene programs regulated by either miR-96 or antagonized by RARγ were enriched in alternative lineages and more aggressive PCa phenotypes. Together these findings reveal an under-investigated role for RARγ, modulated by miR-96, to bookmark enhancer sites during mitosis. These sites are required by the AR to promote transcriptional competence, and emphasize luminal differentiation, while antagonizing ONECUT2.

Neighborhood Deprivation and DNA Methylation and Expression of Cancer Genes in Breast Tumors

Importance

The biological processes that underlie the association of neighborhood environment with chronic diseases, such as cancer, remain poorly understood.

Objective

To determine whether differences in breast tissue DNA methylation are associated with neighborhood deprivation among Black and White women with breast cancer.

Design, Setting, and Participants

This cross-sectional study collected breast tissue from women undergoing surgery for breast cancer between January 1, 1993, and December 31, 2003. Participants were recruited through the University of Maryland Medical Center, with additional collection sites at Baltimore-area hospitals. Data analysis was performed from March 1 through December 1, 2022.

Exposure

Year 2000 census tract-level socioeconomic deprivation measured via neighborhood deprivation index (NDI) as a standardized score, with Black and White race being ascertained through self-report.

Main Outcome and Measures

The primary outcome was tissue DNA methylation using genome-wide measurements. The secondary outcome was tissue gene expression.

Results

Participants included 185 women with breast cancer (110 Black [59.5%], 75 White [40.5%]). Mean (SD) age at surgery was 56.0 (14.1) years. Neighborhood deprivation was higher for Black women than for White women (Mean [SD] NDI, 2.96 [3.03] for Black women and -0.54 [1.91] for White women; difference, -3.50; 95% CI, -4.22 to -2.79; P < .001). In unstratified analysis, 8 hypomethylated CpG sites were identified as associated with the NDI, including sites in 2 tumor suppressor genes, LRIG1 and WWOX. Moreover, expression of the 2 genes inversely correlated with neighborhood deprivation. In the race-stratified analysis, the negative correlation between the LRIG1 gene body CpG site cg26131019 and the NDI remained significant in Black women. A neighborhood deprivation-associated decrease in gene expression was also observed for LRIG1 and WWOX in tumors from Black women.

Conclusions and Relevance

In this study, high neighborhood deprivation was associated with differences in tissue DNA methylation and gene expression among Black women. These findings suggest that continued investment in public health interventions and policy changes at the neighborhood level may help to remedy biological alterations that could make minoritized populations more susceptible to chronic diseases.

Srd5a1 is Differentially Regulated and Methylated During Prepubertal Development in the Ovary and Hypothalamus

5α-reductase-1 catalyzes production of various steroids, including neurosteroids. We reported previously that expression of its encoding gene, Srd5a1, drops in murine ovaries and hypothalamic preoptic area (POA) after early-life immune stress, seemingly contributing to delayed puberty and ovarian follicle depletion, and in the ovaries the first intron was more methylated at two CpGs. Here, we hypothesized that this CpG-containing locus comprises a methylation-sensitive transcriptional enhancer for Srd5a1. We found that ovarian Srd5a1 mRNA increased 8-fold and methylation of the same two CpGs decreased up to 75% between postnatal days 10 and 30. Estradiol (E2) levels rise during this prepubertal stage, and exposure of ovarian cells to E2 increased Srd5a1 expression. Chromatin immunoprecipitation in an ovarian cell line confirmed ESR1 binding to this differentially methylated genomic region and enrichment of the enhancer modification, H3K4me1. Targeting dCas9-DNMT3 to this locus increased CpG2 methylation 2.5-fold and abolished the Srd5a1 response to E2. In the POA, Srd5a1 mRNA levels decreased 70% between postnatal days 7 and 10 and then remained constant without correlation to CpG methylation levels. Srd5a1 mRNA levels did not respond to E2 in hypothalamic GT1-7 cells, even after dCas9-TET1 reduced CpG1 methylation by 50%. The neonatal drop in POA Srd5a1 expression occurs at a time of increasing glucocorticoids, and treatment of GT1-7 cells with dexamethasone reduced Srd5a1 mRNA levels; chromatin immunoprecipitation confirmed glucocorticoid receptor binding at the enhancer. Our findings on the tissue-specific regulation of Srd5a1 and its methylation-sensitive control by E2 in the ovaries illuminate epigenetic mechanisms underlying reproductive phenotypic variation that impact life-long health.

Extensive review on breast cancer its etiology, progression, prognostic markers, and treatment

As the most frequent and vulnerable malignancy among women, breast cancer universally manifests a formidable healthcare challenge. From a biological and molecular perspective, it is a heterogenous disease and is stratified based on the etiological factors driving breast carcinogenesis. Notably, genetic predispositions and epigenetic impacts often constitute the heterogeneity of this disease. Typically, breast cancer is classified intrinsically into histological subtypes in clinical landscapes. These stratifications empower physicians to tailor precise treatments among the spectrum of breast cancer therapeutics. In this pursuit, numerous prognostic algorithms are extensively characterized, drastically changing how breast cancer is portrayed. Therefore, it is a basic requisite to comprehend the multidisciplinary rationales of breast cancer to assist the evolution of novel therapeutic strategies. This review aims at highlighting the molecular and genetic grounds of cancer additionally with therapeutic and phytotherapeutic context. Substantially, it also renders researchers with an insight into the breast cancer cell lines as a model paradigm for breast cancer research interventions.

Dynamic changes of DNA methylation induced by benzo(a)pyrene in cancer

Benzo(a)pyrene (BaP), the earliest and most significant carcinogen among polycyclic aromatic hydrocarbons (PAHs), has been found in foods, tobacco smoke, and automobiles exhaust, etc. Exposure to BaP induced DNA damage directly, or oxidative stress-related damage, resulting in cell apoptosis and carcinogenesis in human respiratory system, digestive system, reproductive system, etc. Moreover, BaP triggered genome-wide epigenetic alterations by methylation, which might cause disturbances in regulation of gene expression, and thereby induced cancer. It has been proved that BaP reduced genome-wide DNA methylation, and activated proto-oncogene by hypomethylation in the promoter region, but silenced tumor suppressor genes by promoter hypermethylation, resulting in cancer initiation and progression. Here we summarized the changes in DNA methylation in BaP exposure, and revealed the methylation of DNA plays a role in cancer development.

DNA methylation differences in noncoding regions in ER negative breast tumors between Black and White women

Introduction

Incidence of estrogen receptor (ER)-negative breast cancer, an aggressive tumor subtype associated with worse prognosis, is higher among African American/Black women than other US racial and ethnic groups. The reasons for this disparity remain poorly understood but may be partially explained by differences in the epigenetic landscape.

Methods

We previously conducted genome-wide DNA methylation profiling of ER- breast tumors from Black and White women and identified a large number of differentially methylated loci (DML) by race. Our initial analysis focused on DML mapping to protein-coding genes. In this study, motivated by increasing appreciation for the biological importance of the non-protein coding genome, we focused on 96 DMLs mapping to intergenic and noncoding RNA regions, using paired Illumina Infinium Human Methylation 450K array and RNA-seq data to assess the relationship between CpG methylation and RNA expression of genes located up to 1Mb away from the CpG site.

Results

Twenty-three (23) DMLs were significantly correlated with the expression of 36 genes (FDR<0.05), with some DMLs associated with the expression of single gene and others associated with more than one gene. One DML (cg20401567), hypermethylated in ER- tumors from Black versus White women, mapped to a putative enhancer/super-enhancer element located 1.3 Kb downstream of HOXB2. Increased methylation at this CpG correlated with decreased expression of HOXB2 (Rho=-0.74, FDR<0.001) and other HOXB/HOXB-AS genes. Analysis of an independent set of 207 ER- breast cancers from TCGA similarly confirmed hypermethylation at cg20401567 and reduced HOXB2 expression in tumors from Black versus White women (Rho=-0.75, FDR<0.001).

Discussion

Our findings indicate that epigenetic differences in ER- tumors between Black and White women are linked to altered gene expression and may hold functional significance in breast cancer pathogenesis.

Methylglyoxal: a novel upstream regulator of DNA methylation

BACKGROUND

Aerobic glycolysis, also known as the Warburg effect, is predominantly upregulated in a variety of solid tumors, including breast cancer. We have previously reported that methylglyoxal (MG), a very reactive by-product of glycolysis, unexpectedly enhanced the metastatic potential in triple negative breast cancer (TNBC) cells. MG and MG-derived glycation products have been associated with various diseases, such as diabetes, neurodegenerative disorders, and cancer. Glyoxalase 1 (GLO1) exerts an anti-glycation defense by detoxifying MG to D-lactate.

METHODS

Here, we used our validated model consisting of stable GLO1 depletion to induce MG stress in TNBC cells. Using genome-scale DNA methylation analysis, we report that this condition resulted in DNA hypermethylation in TNBC cells and xenografts.

RESULTS

GLO1-depleted breast cancer cells showed elevated expression of DNMT3B methyltransferase and significant loss of metastasis-related tumor suppressor genes, as assessed using integrated analysis of methylome and transcriptome data. Interestingly, MG scavengers revealed to be as potent as typical DNA demethylating agents at triggering the re-expression of representative silenced genes. Importantly, we delineated an epigenomic MG signature that effectively stratified TNBC patients based on survival.

CONCLUSION

This study emphasizes the importance of MG oncometabolite, occurring downstream of the Warburg effect, as a novel epigenetic regulator and proposes MG scavengers to reverse altered patterns of gene expression in TNBC.

Chromatin profile-based identification of a novel ER-positive breast cancer subgroup with reduced ER-responsive element accessibility

BACKGROUND

Oestrogen receptor (ER) signalling-dependent cancer cell growth is one of the major features of ER-positive breast cancer (BC). Inhibition of ER function is a standard and effective treatment for ER-positive tumours; however, ~20% of patients with ER-positive BC experience early or late recurrence. In this study, we examined intertumour heterogeneity from an epigenetic perspective based on the hypothesis that the intrinsic difference in epigenetic states around ER signalling pathway underlies endocrine therapy resistance.

METHODS

We performed transposase-accessible chromatin sequencing (ATAC-seq) analysis of 42 BC samples, including 35 ER-positive(+) human epidermal growth factor receptor 2 (HER2)-negative(-) and 7 triple-negative tumours. We also reanalysed ATAC-seq data of 45 ER + /HER2 - tumours in the Cancer Genome Atlas (TCGA) BC cohort to validate our observations.

RESULTS

We conducted a comprehensive analysis of cis-regulatory elements (CREs) using ATAC-seq, identifying three subgroups based on chromatin accessibility profiles. We identified a subgroup of ER-positive BCs with a distinctive chromatin accessibility pattern including reduced accessibility to ER-responsive elements (EREs). The same subgroup was also observed in TCGA BC cohort. Despite the reduced accessibility to EREs, the expression of ER and potential ER target genes were not decreased in these tumours.

CONCLUSION

Our findings highlight the existence of a subset of ER-positive BCs with unchanged ER expression but reduced EREs accessibility that cannot be distinguished by conventional immunostaining for ER. Future studies should determine whether these tumours are associated with resistance to endocrine therapy.

Multiomics in primary and metastatic breast tumors from the AURORA US network finds microenvironment and epigenetic drivers of metastasis

The AURORA US Metastasis Project was established with the goal to identify molecular features associated with metastasis. We assayed 55 females with metastatic breast cancer (51 primary cancers and 102 metastases) by RNA sequencing, tumor/germline DNA exome and low-pass whole-genome sequencing and global DNA methylation microarrays. Expression subtype changes were observed in ~30% of samples and were coincident with DNA clonality shifts, especially involving HER2. Downregulation of estrogen receptor (ER)-mediated cell-cell adhesion genes through DNA methylation mechanisms was observed in metastases. Microenvironment differences varied according to tumor subtype; the ER+/luminal subtype had lower fibroblast and endothelial content, while triple-negative breast cancer/basal metastases showed a decrease in B and T cells. In 17% of metastases, DNA hypermethylation and/or focal deletions were identified near HLA-A and were associated with reduced expression and lower immune cell infiltrates, especially in brain and liver metastases. These findings could have implications for treating individuals with metastatic breast cancer with immune- and HER2-targeting therapies.

CanMethdb: a database for genome-wide DNA methylation annotation in cancers

MOTIVATION

DNA methylation within gene body and promoters in cancer cells is well documented. An increasing number of studies showed that cytosine-phosphate-guanine (CpG) sites falling within other regulatory elements could also regulate target gene activation, mainly by affecting transcription factors (TFs) binding in human cancers. This led to the urgent need for comprehensively and effectively collecting distinct cis-regulatory elements and TF-binding sites (TFBS) to annotate DNA methylation regulation.

RESULTS

We developed a database (CanMethdb, http://meth.liclab.net/CanMethdb/) that focused on the upstream and downstream annotations for CpG-genes in cancers. This included upstream cis-regulatory elements, especially those involving distal regions to genes, and TFBS annotations for the CpGs and downstream functional annotations for the target genes, computed through integrating abundant DNA methylation and gene expression profiles in diverse cancers. Users could inquire CpG-target gene pairs for a cancer type through inputting a genomic region, a CpG, a gene name, or select hypo/hypermethylated CpG sets. The current version of CanMethdb documented a total of 38 986 060 CpG-target gene pairs (with 6 769 130 unique pairs), involving 385 217 CpGs and 18 044 target genes, abundant cis-regulatory elements and TFs for 33 TCGA cancer types. CanMethdb might help biologists perform in-depth studies of target gene regulations based on DNA methylations in cancer.

AVAILABILITY AND IMPLEMENTATION

The main program is available at https://github.com/chunquanlipathway/CanMethdb.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Subtype and cell type specific expression of lncRNAs provide insight into breast cancer

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.

Epigenetic Alterations of DNA Methylation and miRNA Contribution to Lung Adenocarcinoma

This study focused on the epigenetic alterations of DNA methylation and miRNAs for lung adenocarcinoma (LUAD) diagnosis and treatment using bioinformatics analyses. DNA methylation data and mRNA and miRNA expression microarray data were obtained from The Cancer Genome Atlas (TCGA) database. The differentially methylated genes (DMGs), differentially expressed genes (DEGs), and differentially expressed miRNAs were analyzed by using the limma package. The DAVID database performed GO and KEGG pathway enrichment analyses. Using STRING and Cytoscape, we constructed the protein-protein interaction (PPI) network and achieved visualization. The online analysis tool CMap was used to identify potential small-molecule drugs for LUAD. In LUAD, 607 high miRNA-targeting downregulated genes and 925 low miRNA-targeting upregulated genes, as well as 284 hypermethylated low-expression genes and 315 hypomethylated high-expression genes, were obtained. They were mainly enriched in terms of pathways in cancer, neuroactive ligand-receptor interaction, cAMP signaling pathway, and cytosolic DNA-sensing pathway. In addition, 40 upregulated and 84 downregulated genes were regulated by both aberrant alternations of DNA methylation and miRNAs. Five small-molecule drugs were identified as a potential treatment for LUAD, and five hub genes (SLC2A1, PAX6, LEP, KLF4, and FGF10) were found in PPI, and two of them (SLC2A1 and KLF4) may be related to the prognosis of LUAD. In summary, our study identified a series of differentially expressed genes associated with epigenetic alterations of DNA methylation and miRNA in LUAD. Five small-molecule drugs and five hub genes may be promising drugs and targets for LUAD treatment.

Comprehensive Analysis of the Immune Cell Infiltration Landscape and Immune-Related Methylation in Retinoblastoma

Retinoblastoma is a common pediatric intraocular cancer, originating from cone precursors. The development of immunotherapies can help eradicate the tumor without vision loss, which would largely improve the quality of life of patients with retinoblastoma. Investigation of the tumor immune microenvironment provides knowledge for developing novel immunotherapies in cancer. However, the immune cell infiltrative landscape of retinoblastoma is unknown. Here, we compared the relative expression of immune gene signatures among 59 patients with retinoblastoma. The patients were divided into two subgroups according to the 28 types of immune cell infiltration (ICI) scores. We found that a subgroup with high ICI scores had increased expression levels of late cone markers, while the other subgroup exhibited larger tumor size and metastasis propensity. Furthermore, hypermethylated genes in the high-ICI subgroup were associated with immune regulation in the tumor microenvironment, suggesting that DNA methylation may play a vital regulatory role in retinoblastoma immunity. Our study provides a comprehensive framework for the systemic analysis of the influences of epigenetic events on the tumor immune microenvironment. We anticipate that our assay can not only provide insights into tumor immune regulation but also open up the perspectives for the identification of novel immunotherapy targets for retinoblastoma.

DNMT3A and DNMT3B in Breast Tumorigenesis and Potential Therapy

Breast cancer has become a leading cause of cancer-related deaths in women worldwide. DNA methylation has been revealed to play an enormously important role in the development and progression of breast cancer. DNA methylation is regulated by DNA methyltransferases (DNMTs), including DNMT1, DNMT2, and DNMT3. DNMT3 family has three members: DNMT3A, DNMT3B, and DNMT3L. The roles and functions of DNMT1 in breast cancer have been well reviewed. In this article, the roles of DNMT3A and DNMT3B in breast tumorigenesis and development are reviewed. We also discuss the SNP and mutations of DNMT3A and DNMT3B in breast cancer. In addition, we summarize how DNMT3A and DNMT3B are regulated by non-coding RNAs and signaling pathways in breast cancer, and targeting the expression levels of DNMT3A and DNMT3B may be a promising therapeutic approach for breast cancer. This review will provide reference for further studies on the biological functions and molecular mechanisms of DNMT3A and DNMT3B in breast cancer.

Pioneer transcription factors are associated with the modulation of DNA methylation patterns across cancers

Methylation of cytosines on DNA is a prominent modification associated with gene expression regulation. Aberrant DNA methylation patterns have recurrently been linked to dysregulation of the regulatory program in cancer cells. To shed light on the underlying molecular mechanism driving this process, we hypothesised that aberrant methylation patterns could be controlled by the binding of specific transcription factors (TFs) across cancer types. By combining DNA methylation arrays and gene expression data with TF binding sites (TFBSs), we explored the interplay between TF binding and DNA methylation in 19 cancer types. We performed emQTL (expression–methylation quantitative trait loci) analyses independently in each cancer type and identified 13 TFs whose expression levels are correlated with local DNA methylation patterns around their binding sites in at least 2 cancer types. The 13 TFs are mainly associated with local demethylation and are enriched for pioneer function, suggesting a specific role for these TFs in modulating chromatin structure and transcription in cancer patients. Furthermore, we confirmed that de novo methylation is precluded across cancers at CpGs lying in genomic regions enriched for TF binding signatures associated with SP1, CTCF, NRF1, GABPA, KLF9, and/or YY1. The modulation of DNA methylation associated with TF binding was observed at cis-regulatory regions controlling immune- and cancer-associated pathways, corroborating that the emQTL signals were derived from both cancer and tumor-infiltrating cells. As a case example, we experimentally confirmed that FOXA1 knock-down is associated with higher methylation in regions bound by FOXA1 in breast cancer MCF-7 cells. Finally, we reported physical interactions between FOXA1 with TET1 and TET2 both in an in vitro setup and in vivo at physiological levels in MCF-7 cells, adding further support for FOXA1 attracting TET1 and TET2 to induce local demethylation in cancer cells.

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

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.

Pan-cancer predictions of transcription factors mediating aberrant DNA methylation

BACKGROUND

Aberrant DNA methylation is a hallmark of cancer cells. However, the mechanisms underlying changes in DNA methylation remain elusive. Transcription factors initially thought to be repressed from binding by DNA methylation, have recently emerged as being able to shape DNA methylation patterns.

RESULTS

Here, we integrated the massive amount of data available from The Cancer Genome Atlas to predict transcription factors driving aberrant DNA methylation in 13 cancer types. We identified differentially methylated regions between cancer and matching healthy samples, searched for transcription factor motifs enriched in those regions and selected transcription factors with corresponding changes in gene expression. We predict transcription factors known to be involved in cancer as well as novel candidates to drive hypo-methylated regions such as FOXA1 and GATA3 in breast cancer, FOXA1 and TWIST1 in prostate cancer and NFE2L2 in lung cancer. We also predict transcription factors that lead to hyper-methylated regions upon transcription factor loss such as EGR1 in several cancer types. Finally, we validate that FOXA1 and GATA3 mediate hypo-methylated regions in breast cancer cells.

CONCLUSION

Our work highlights the importance of some transcription factors as upstream regulators shaping DNA methylation patterns in cancer.

Strong parallel differential gene expression induced by hatchery rearing weakly associated with methylation signals in adult Coho Salmon (O. kisutch)

Human activities and resource exploitation led to a massive decline of wild salmonid populations, consequently, numerous conservation programs have been developed to supplement wild populations. However, many studies documented reduced fitness of hatchery-born relative to wild fish. Here, by using both RNA sequencing and Whole Genome Bisulfite Sequencing of hatchery and wild-born adult Coho salmon (Oncorhynchus kisutch) originating from two previously studied river systems, we show that early-life hatchery-rearing environment-induced significant and parallel gene expression differentiation is maintained until Coho come back to their natal river for reproduction. A total of 3,643 genes differentially expressed and 859 coexpressed genes were downregulated in parallel in hatchery-born fish from both rivers relative to their wild congeners. Among those genes, 26 displayed a significant relationship between gene expression and the median gene body methylation and 669 single CpGs displayed a significant correlation between methylation level and the associated gene expression. The link between methylation and gene expression was weak suggesting that DNA methylation is not the only player in mediating hatchery-related expression differences. Yet, significant gene expression differentiation was observed despite 18 months spent in a common environment (i.e., the sea). Finally, the differentiation is observed in parallel in two different river systems, highlighting the fact that early-life environment may account for at least some of the reduced fitness of the hatchery salmon in the wild. These results illustrate the relevance and importance of considering both epigenome and transcriptome to evaluate the costs and benefits of large-scale supplementation programs.

Epigenetic Therapies and Biomarkers in Breast Cancer

Simple Summary

Epigenetic therapies are promising agents for overcoming clinical resistance to conventional treatments in breast cancer. In the assessed trials, the use of epigenetic therapies for the management of breast cancer has not translated from the pre-clinical to clinical setting. However, novel epigenetic treatments remain promising, especially in the era of personalized medicine and improved genomic evaluation. The aim of our review was to assess the published evidence for the clinical utility of epigenetic therapies and their biomarkers in breast cancer and the potential value of epigenetic biomarkers to direct clinical management.

Abstract

Epigenetic therapies remain a promising, but still not widely used, approach in the management of patients with cancer. To date, the efficacy and use of epigenetic therapies has been demonstrated primarily in the management of haematological malignancies, with limited supportive data in solid malignancies. The most studied epigenetic therapies in breast cancer are those that target DNA methylation and histone modification; however, none have been approved for routine clinical use. The majority of pre-clinical and clinical studies have focused on triple negative breast cancer (TNBC) and hormone-receptor positive breast cancer. Even though the use of epigenetic therapies alone in the treatment of breast cancer has not shown significant clinical benefit, these therapies show most promise in use in combinations with other treatments. With improving technologies available to study the epigenetic landscape in cancer, novel epigenetic alterations are increasingly being identified as potential biomarkers of response to conventional and epigenetic therapies. In this review, we describe epigenetic targets and potential epigenetic biomarkers in breast cancer, with a focus on clinical trials of epigenetic therapies. We describe alterations to the epigenetic landscape in breast cancer and in treatment resistance, highlighting mechanisms and potential targets for epigenetic therapies. We provide an updated review on epigenetic therapies in the pre-clinical and clinical setting in breast cancer, with a focus on potential real-world applications. Finally, we report on the potential value of epigenetic biomarkers in diagnosis, prognosis and prediction of response to therapy, to guide and inform the clinical management of breast cancer patients.

JASPAR 2022: the 9th release of the open-access database of transcription factor binding profiles

JASPAR (http://jaspar.genereg.net/) is an open-access database containing manually curated, non-redundant transcription factor (TF) binding profiles for TFs across six taxonomic groups. In this 9th release, we expanded the CORE collection with 341 new profiles (148 for plants, 101 for vertebrates, 85 for urochordates, and 7 for insects), which corresponds to a 19% expansion over the previous release. We added 298 new profiles to the Unvalidated collection when no orthogonal evidence was found in the literature. All the profiles were clustered to provide familial binding profiles for each taxonomic group. Moreover, we revised the structural classification of DNA binding domains to consider plant-specific TFs. This release introduces word clouds to represent the scientific knowledge associated with each TF. We updated the genome tracks of TFBSs predicted with JASPAR profiles in eight organisms; the human and mouse TFBS predictions can be visualized as native tracks in the UCSC Genome Browser. Finally, we provide a new tool to perform JASPAR TFBS enrichment analysis in user-provided genomic regions. All the data is accessible through the JASPAR website, its associated RESTful API, the R/Bioconductor data package, and a new Python package, pyJASPAR, that facilitates serverless access to the data.

Subtype-Independent ANP32E Reduction During Breast Cancer Progression in Accordance with Chromatin Relaxation

BACKGROUND

Chromatin state provides a clear decipherable blueprint for maintenance of transcriptional patterns, exemplifying a mitotically stable form of cellular programming in dividing cells. In this regard, genomic studies of chromatin states within cancerous tissues have the potential to uncover novel aspects of tumor biology and unique mechanisms associated with disease phenotypes and outcomes. The degree to which chromatin state differences occur in accordance with breast cancer features has not been established.

METHODS

We applied a series of unsupervised computational methods to identify chromatin and molecular differences associated with discrete physiologies across human breast cancer tumors.

RESULTS

Chromatin patterns alone are capable of stratifying tumors in association with cancer subtype and disease progression. Major differences occur at DNA motifs for the transcription factor FOXA1, in hormone receptor-positive tumors, and motifs for SOX9 in Basal-like tumors. We find that one potential driver of this effect, the histone chaperone ANP32E, is inversely correlated with tumor progression and relaxation of chromatin at FOXA1 binding sites. Tumors with high levels of ANP32E exhibit an immune response and proliferative gene expression signature, whereas tumors with low ANP32E levels appear programmed for differentiation.

CONCLUSIONS

Our results indicate that ANP32E may function through chromatin state regulation to control breast cancer differentiation and tumor plasticity. This study sets a precedent for future computational studies of chromatin changes in carcinogenesis.

A comprehensive bioinformatic analysis of RanBP9 expression and its relation to prognosis in human breast cancer

Aim: To explore the role of RanBP9 in breast cancer. Materials & methods: Oncomine, TIMER, GEPIA, UALCAN, c-BioPortal databases and tissue microarray analysis were used in this study. Results: The expression level of RanBP9 is elevated in breast cancer tissues, which is associated with poor prognosis in breast cancer patients. RanBP9 exhibits genetic alterations and a decreased methylation level in cancer tissues. RanBP9 may also regulate cell cycle progression and is linked to tumor purity and the infiltrating levels of immune cells. Conclusions: RanBP9 may correlate with prognosis and immune infiltration in breast cancer, laying the foundation for future studies on the potential role of RanBP9 in breast cancer.

Epigenetic remodelling of enhancers in response to estrogen deprivation and re-stimulation

Estrogen hormones are implicated in a majority of breast cancers and estrogen receptor alpha (ER), the main nuclear factor mediating estrogen signaling, orchestrates a complex molecular circuitry that is not yet fully elucidated. Here, we investigated genome-wide DNA methylation, histone acetylation and transcription after estradiol (E2) deprivation and re-stimulation to better characterize the ability of ER to coordinate gene regulation. We found that E2 deprivation mostly resulted in DNA hypermethylation and histone deacetylation in enhancers. Transcriptome analysis revealed that E2 deprivation leads to a global down-regulation in gene expression, and more specifically of TET2 demethylase that may be involved in the DNA hypermethylation following short-term E2 deprivation. Further enrichment analysis of transcription factor (TF) binding and motif occurrence highlights the importance of ER connection mainly with two partner TF families, AP-1 and FOX. These interactions take place in the proximity of E2 deprivation-mediated differentially methylated and histone acetylated enhancers. Finally, while most deprivation-dependent epigenetic changes were reversed following E2 re-stimulation, DNA hypermethylation and H3K27 deacetylation at certain enhancers were partially retained. Overall, these results show that inactivation of ER mediates rapid and mostly reversible epigenetic changes at enhancers, and bring new insight into early events, which may ultimately lead to endocrine resistance.

MethylSPWNet and MethylCapsNet: Biologically Motivated Organization of DNAm Neural Networks, Inspired by Capsule Networks

DNA methylation (DNAm) alterations have been heavily implicated in carcinogenesis and the pathophysiology of diseases through upstream regulation of gene expression. DNAm deep-learning approaches are able to capture features associated with aging, cell type, and disease progression, but lack incorporation of prior biological knowledge. Here, we present modular, user-friendly deep-learning methodology and software, MethylCapsNet and MethylSPWNet, that group CpGs into biologically relevant capsules-such as gene promoter context, CpG island relationship, or user-defined groupings-and relate them to diagnostic and prognostic outcomes. We demonstrate these models' utility on 3,897 individuals in the classification of central nervous system (CNS) tumors. MethylCapsNet and MethylSPWNet provide an opportunity to increase DNAm deep-learning analyses' interpretability by enabling a flexible organization of DNAm data into biologically relevant capsules.

A method of sample-wise region-set enrichment analysis for DNA methylomics

Aim: Gene set analysis has commonly been used to interpret DNA methylome data. However, summarizing the DNA methylation level of a gene is challenging due to variability in the number, density and methylation levels of CpG sites, and the numerous intergenic CpGs. Instead, we propose to use region sets to annotate the DNA methylome. Methods: We developed single sample region-set enrichment analysis for DNA methylome (methyl-ssRSEA) to conduct sample-wise, region-set enrichment analysis. Results: Methyl-ssRSEA can handle both microarray- and sequencing-based platforms and reproducibly recover the known biology from the methylation profiles of peripheral blood cells and breast cancers. The performance was superior to existing tools for region-set analysis in discriminating blood cell types. Conclusion: Methyl-ssRSEA offers a novel way to functionally interpret the DNA methylome in the cell.

Identification and Validation of Immune-Related Methylation Clusters for Predicting Immune Activity and Prognosis in Breast Cancer

The role of DNA methylation of breast cancer-infiltrating immune cells has not been fully explored. We conducted a cohort-based retrospective study analyzing the genome-wide immune-related DNA methylation of 1057 breast cancer patients from the TCGA cohort and GSE72308 cohort. Based on patients' overall survival (OS), a prognostic risk score system using 18 immune-related methylation genes (IRMGs) was established and further validated in an independent cohort. Kaplan-Meier analysis showed a clear separation of OS between the low- and high-risk groups. Patients in the low-risk group had a higher immune score and stromal score compared with the high-risk group. Moreover, the characteristics based on 18-IRMGs signature were related to the tumor immune microenvironment and affected the abundance of tumor-infiltrating immune cells. Consistently, the 18-IRMGs signatures showed similar influences on immune modulation and survival in another external validation cohort (GSE72308). In conclusion, the proposed 18-IRMGs signature could be a potential marker for breast cancer prognostication.

An Assessment on Ethanol-Blended Gasoline/Diesel Fuels on Cancer Risk and Mortality

Although cancer is traditionally considered a genetic disease, the epigenetic abnormalities, including DNA hypermethylation, histone deacetylation, and/or microRNA dysregulation, have been demonstrated as a hallmark of cancer. Compared with gene mutations, aberrant epigenetic changes occur more frequently, and cellular epigenome is more susceptible to change by environmental factors. Excess cancer risks are positively associated with exposure to occupational and environmental chemical carcinogens, including those from gasoline combustion exhausted in vehicles. Of note, previous studies proposed particulate matter index (PMI) as a measure for gasoline sooting tendency, and showed that, compared with the other molecules in gasoline, 1,2,4-Trimethylbenzene, 2-methylnaphthalene and toluene significantly contribute to PMI of the gasoline blends. Mechanistically, both epigenome and genome are important in carcinogenicity, and the genotoxicity of chemical agents has been thoroughly studied. However, less effort has been put into studying the epigenotoxicity. Moreover, as the blending of ethanol into gasoline substitutes for carcinogens, like benzene, toluene, xylene, butadiene, and polycyclic aromatic hydrocarbons, etc., a reduction of secondary aromatics has been achieved in the atmosphere. This may lead to diminished cancer initiation and progression through altered cellular epigenetic landscape. The present review summarizes the most important findings in the literature on the association between exposures to carcinogens from gasoline combustion, cancer epigenetics and the potential epigenetic impacts of biofuels.

UniBind: maps of high-confidence direct TF-DNA interactions across nine species

BACKGROUND

Transcription factors (TFs) bind specifically to TF binding sites (TFBSs) at cis-regulatory regions to control transcription. It is critical to locate these TF-DNA interactions to understand transcriptional regulation. Efforts to predict bona fide TFBSs benefit from the availability of experimental data mapping DNA binding regions of TFs (chromatin immunoprecipitation followed by sequencing - ChIP-seq).

RESULTS

In this study, we processed ~ 10,000 public ChIP-seq datasets from nine species to provide high-quality TFBS predictions. After quality control, it culminated with the prediction of ~ 56 million TFBSs with experimental and computational support for direct TF-DNA interactions for 644 TFs in > 1000 cell lines and tissues. These TFBSs were used to predict > 197,000 cis-regulatory modules representing clusters of binding events in the corresponding genomes. The high-quality of the TFBSs was reinforced by their evolutionary conservation, enrichment at active cis-regulatory regions, and capacity to predict combinatorial binding of TFs. Further, we confirmed that the cell type and tissue specificity of enhancer activity was correlated with the number of TFs with binding sites predicted in these regions. All the data is provided to the community through the UniBind database that can be accessed through its web-interface ( https://unibind.uio.no/ ), a dedicated RESTful API, and as genomic tracks. Finally, we provide an enrichment tool, available as a web-service and an R package, for users to find TFs with enriched TFBSs in a set of provided genomic regions.

CONCLUSIONS

UniBind is the first resource of its kind, providing the largest collection of high-confidence direct TF-DNA interactions in nine species.

The epigenetics of breast cancer - Opportunities for diagnostics, risk stratification and therapy

The stage and molecular pathology-dependent prognosis of breast cancer, the limited treatment options for triple-negative carcinomas, as well as the development of resistance to therapies illustrate the need for improved early diagnosis and the development of new therapeutic approaches. Increasing data suggests that some answers to these challenges could be found in the area of epigenetics. In this study, we focus on the current research of the epigenetics of breast cancer, especially on the potential of epigenetics for clinical application in diagnostics, risk stratification and therapy. The differential DNA methylation status of specific gene regions has been used in the past to differentiate breast cancer cells from normal tissue. New technologies as detection of circulating nucleic acids including microRNAs to early detect breast cancer are emerging. Pattern of DNA methylation and expression of histone-modifying enzymes have been successfully used for risk stratification. However, all these epigenetic biomarkers should be validated in larger clinical studies. Recent preclinical and clinical studies show a therapeutic benefit of epigenetically active drugs for breast cancer entities that are still difficult to treat (triple negative, UICC stage IV). Remarkably, epigenetic therapies combined with chemotherapies or hormone-based therapies represent the most promising strategy. At the current stage, the integration of epigenetic substances into established breast cancer therapy protocols seems to hold the greatest potential for a clinical application of epigenetic research.

Multi-Omics Marker Analysis Enables Early Prediction of Breast Tumor Progression

Ductal carcinoma in situ (DCIS) is a preinvasive form of breast cancer with a highly variable potential of becoming invasive and affecting mortality of the patients. Due to the lack of accurate markers of disease progression, many women with detected DCIS are currently overtreated. To distinguish those DCIS cases who are likely to require therapy from those who should be left untreated, there is a need for robust and predictive biomarkers extracted from molecular or genetic profiles. We developed a supervised machine learning approach that implements multi-omics feature selection and model regularization for the identification of biomarker combinations that could be used to distinguish low-risk DCIS lesions from those with a higher likelihood of progression. To investigate the genetic heterogeneity of disease progression, we applied this approach to 40 pure DCIS and 259 invasive breast cancer (IBC) samples profiled with genome-wide transcriptomics, DNA methylation, and DNA copy number variation. Feature selection using the multi-omics Lasso-regularized algorithm identified both known genes involved in breast cancer development, as well as novel markers for early detection. Even though the gene expression-based model features led to the highest classification accuracy alone, methylation data provided a complementary source of features and improved especially the sensitivity of correctly classifying DCIS cases. We also identified a number of repeatedly misclassified DCIS cases when using either the expression or methylation markers. A small panel of 10 gene markers was able to distinguish DCIS and IBC cases with high accuracy in nested cross-validation (AU-ROC = 0.99). The marker panel was not specific to any of the established breast cancer subtypes, suggesting that the 10-gene signature may provide a subtype-agnostic and cost-effective approach for breast cancer detection and patient stratification. We further confirmed high accuracy of the 10-gene signature in an external validation cohort (AU-ROC = 0.95), profiled using distinct transcriptomic assay, hence demonstrating robustness of the risk signature.

Immune subgroup analysis for non-small cell lung cancer may be a good choice for evaluating therapeutic efficacy and prognosis

Due to its effectiveness, cancer immunotherapy has attracted widespread attention from clinicians and scientific researchers. Numerous studies have proven that effective stratification of cancer patients would promote the personalized application of immunotherapy. Therefore, we used the transcriptome data of nearly 1,000 patients with non-small cell lung cancer (NSCLC) to construct a new immune subgroup. We found that the new immune subgroup, named cluster 2, was a mixture of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), and showed poor overall survival, which was further verified in the independent validation set. Immune infiltration correlation analysis showed that the Mast cell type and its status subdivisions had a predictive effect on the prognosis of NSCLC, especially in LUAD. Phenotypic analysis suggested that epithelial-mesenchymal transition (EMT) was positively correlated with immunosuppression, supporting the correlation between tumor phenotype and immune background. Although immune subtypes failed to significantly distinguish the progression-free survival (PFS) of immunotherapy patients, they showed the expected trend; the sample size needs to be further expanded for verification. In addition, some results indicated that the two cancer types, LUAD and LUSC, might require independent analyses.

Chromosome 2q gain and epigenetic silencing of GATA3 in microglandular adenosis of the breast

Microglandular adenosis (MGA) represents a rare neoplasm of the mammary gland, which in a subset of cases may be associated with triple-negative breast cancer (BC). The biology of MGA is poorly understood. In this study, eight MGA cases (n = 4 with and n = 4 without associated BC) were subjected to a comprehensive characterization using immunohistochemistry, genome-wide DNA copy number (CN) profiling, fluorescence in situ hybridization (FISH), next-generation sequencing (NGS), and DNA methylation profiling using 850 K arrays and bisulfite pyrosequencing. Median patient age was 61 years (range 57-76 years). MGA lesions were estrogen receptor (ER)-negative, progesterone receptor-negative, HER2-negative, and S100-positive. DNA CN alterations (CNAs) were complex or limited to few gains and losses. CN gain on chromosome 2q was the most common CNA and was validated by FISH in five of eight cases. NGS demonstrated an average of two mutations per case (range 0-5) affecting 10 different genes (ARID1A, ATM, CTNNB1, FBXW7, FGFR2, MET, PIK3CA, PMS2, PTEN, and TP53). CNAs and mutations were similar in MGA and adjacent BC, indicating clonal relatedness. DNA methylation profiling identified aberrant hypermethylation of CpG sites within GATA3, a key transcription factor required for luminal differentiation. Immunohistochemistry showed regular GATA3 protein expression in the normal mammary epithelium and in ER-positive BC. Conversely, GATA3 was reduced or lost in all MGA cases tested (8/8). In conclusion, MGA is characterized by common CN gain on chromosome 2q and loss of GATA3. Epigenetic inactivation of GATA3 may provide a new clue to the peculiar biology of this rare neoplasia.

Crosstalk between microRNA expression and DNA methylation drives the hormone-dependent phenotype of breast cancer

BACKGROUND

Abnormal DNA methylation is observed as an early event in breast carcinogenesis. However, how such alterations arise is still poorly understood. microRNAs (miRNAs) regulate gene expression at the post-transcriptional level and play key roles in various biological processes. Here, we integrate miRNA expression and DNA methylation at CpGs to study how miRNAs may affect the breast cancer methylome and how DNA methylation may regulate miRNA expression.

METHODS

miRNA expression and DNA methylation data from two breast cancer cohorts, Oslo2 (n = 297) and The Cancer Genome Atlas (n = 439), were integrated through a correlation approach that we term miRNA-methylation Quantitative Trait Loci (mimQTL) analysis. Hierarchical clustering was used to identify clusters of miRNAs and CpGs that were further characterized through analysis of mRNA/protein expression, clinicopathological features, in silico deconvolution, chromatin state and accessibility, transcription factor binding, and long-range interaction data.

RESULTS

Clustering of the significant mimQTLs identified distinct groups of miRNAs and CpGs that reflect important biological processes associated with breast cancer pathogenesis. Notably, two major miRNA clusters were related to immune or fibroblast infiltration, hence identifying miRNAs associated with cells of the tumor microenvironment, while another large cluster was related to estrogen receptor (ER) signaling. Studying the chromatin landscape surrounding CpGs associated with the estrogen signaling cluster, we found that miRNAs from this cluster are likely to be regulated through DNA methylation of enhancers bound by FOXA1, GATA2, and ER-alpha. Further, at the hub of the estrogen cluster, we identified hsa-miR-29c-5p as negatively correlated with the mRNA and protein expression of DNA methyltransferase DNMT3A, a key enzyme regulating DNA methylation. We found deregulation of hsa-miR-29c-5p already present in pre-invasive breast lesions and postulate that hsa-miR-29c-5p may trigger early event abnormal DNA methylation in ER-positive breast cancer.

CONCLUSIONS

We describe how miRNA expression and DNA methylation interact and associate with distinct breast cancer phenotypes.

Epigenetic dynamics in cancer stem cell dormancy

Cancer remains one of the most challenging diseases despite significant advances of early diagnosis and therapeutic treatments. Cancerous tumors are composed of various cell types including cancer stem cells capable of self-renewal, proliferation, differentiation, and invasion of distal tumor sites. Most notably, these cells can enter a dormant cellular state that is resistant to conventional therapies. Thereby, cancer stem cells have the intrinsic potential for tumor initiation, tumor growth, metastasis, and tumor relapse after therapy. Both genetic and epigenetic alterations are attributed to the formation of multiple tumor types. This review is focused on how epigenetic dynamics involving DNA methylation and DNA oxidations are implicated in breast cancer and glioblastoma multiforme. The emergence and progression of these cancer types rely on cancer stem cells with the capacity to enter quiescence also known as a dormant cellular state, which dictates the distinct tumorigenic aggressiveness between breast cancer and glioblastomas.

Identification and validation of methylated differentially expressed miRNAs and immune infiltrate profile in EBV-associated gastric cancer

BACKGROUND

The recent discovery of cancer/tissue specificity of miRNA has indicated its great potential as a therapeutic target. In Epstein-Barr virus-associated gastric cancer (EBVaGC), host genes are affected by extensive DNA methylation, including miRNAs. However, the role of methylated miRNA in the development of EBVaGC and immune cell infiltration has largely remained elusive.

RESULTS

After crossmatching the DNA methylation and expression profile of miRNA and mRNA in the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas Research Network (TCGA), we discovered that miR-129-2-3p was significantly suppressed due to hypermethylation on its enhancer in EBVaGC. The differentially expressed genes (DEGs) added up to 30, among which AKAP12 and LARP6 were predicted to be the target genes of miR-129-2-3p and negatively correlated with patients' survival. Accordingly, miR-129-2-3p was significantly down-regulated in tumor samples in 26 (65%) out of 40 cases in our cohort (P < 0.0001). The proliferation, migration and invasion functions of GC cells were significantly promoted when transfected with miR-129-2-3p inhibitor and suppressed when transfected with mimics or treated with 5-aza-2'-deoxycytidine. Moreover, a comprehensive regulation network was established by combining the putative transcription factors, miRNA-mRNA and protein-protein interaction (PPI) analysis. Pathway enrichment analysis showed that cytokine activity, especially CCL20, was the most prominent biological process in EBVaGC development. Immune cell infiltration analysis demonstrated CD4+ T cell, macrophage and dendritic cell infiltrates were significantly enriched for the prognostic-indicated hub genes.

CONCLUSION

This study has provided a comprehensive analysis of differentially expressed miRNAs and mRNAs associated with genome-wide DNA methylation by integrating multi-source data including transcriptome, methylome and clinical data from GEO and TCGA, QPCR of tumor samples and cell function assays. It also gives a hint on the relationships between methylated miRNA, DEGs and the immune infiltration. Further experimental and clinical investigations are warranted to explore the underlying mechanism and validate our findings.

AtMAD: Arabidopsis thaliana multi-omics association database

Integration analysis of multi-omics data provides a comprehensive landscape for understanding biological systems and mechanisms. The abundance of high-quality multi-omics data (genomics, transcriptomics, methylomics and phenomics) for the model organism Arabidopsis thaliana enables scientists to study the genetic mechanism of many biological processes. However, no resource is available to provide comprehensive and systematic multi-omics associations for Arabidopsis. Here, we developed an Arabidopsis thaliana Multi-omics Association Database (AtMAD, http://www.megabionet.org/atmad), a public repository for large-scale measurements of associations between genome, transcriptome, methylome, pathway and phenotype in Arabidopsis, designed for facilitating identification of eQTL, emQTL, Pathway-mQTL, Phenotype-pathway, GWAS, TWAS and EWAS. Candidate variants/methylations/genes were identified in AtMAD for specific phenotypes or biological processes, many of them are supported by experimental evidence. Based on the multi-omics association strategy, we have identified 11 796 cis-eQTLs and 10 119 trans-eQTLs. Among them, 68 837 environment-eQTL associations and 149 622 GWAS-eQTL associations were identified and stored in AtMAD. For expression–methylation quantitative trait loci (emQTL), we identified 265 776 emQTLs and 122 344 pathway-mQTLs. For TWAS and EWAS, we obtained 62 754 significant phenotype-gene associations and 3 993 379 significant phenotype-methylation associations, respectively. Overall, the multi-omics associated network in AtMAD will provide new insights into exploring biological mechanisms of plants at multi-omics levels.

Short history of 5-methylcytosine: from discovery to clinical applications

Covalent modifications of nucleotides in genetic material have been known from the beginning of the last century. Currently, one of those modifications referred to as DNA methylation, is impacting personalised medicine both as a treatment target and a biomarker source for clinical disease management. In this short review, we describe landmark discoveries that led to the elucidation of the DNA methylation importance in the cell's physiology and clarification of its role as one of the major processes in disease pathology. We also describe turning points in the development of methodologies to study this modification, which ultimately resulted in the development of in-vitro diagnostic kits targeting disease related DNA methylation changes as biomarkers.

Targeting epigenetic regulatory machinery to overcome cancer therapy resistance

Drug resistance, either intrinsic or acquired, represents a major hurdle to achieving optimal therapeutic outcomes during cancer treatment. In addition to acquisition of resistance-conferring genetic mutations, accumulating evidence suggests an intimate involvement of the epigenetic machinery in this process as well. Recent studies have revealed that epigenetic reprogramming, such as altered expression or relocation of DNA/histone modulators accompanied with chromatin structure remodeling, can lead to transcriptional plasticity in tumor cells, thereby driving their transformation towards a persistent state. These "persisters" represent a pool of slow-growing cells that can either re-expand when treatment is discontinued or acquire permanent resistance. Targeting epigenetic reprogramming or plasticity represents a new strategy to prevent the emergence of drug-refractory populations and to enable more consistent clinical responses. With the growing numbers of drugs or drug candidates developed to target epigenetic regulators, more and more epigenetic therapies are under preclinical evaluation, early clinical trials or approved by FDA as single agent or in combination with existing antitumor drugs. In this review, we highlight latest discoveries in the mechanistic understanding of epigenetically-induced drug resistance. In parallel, we discuss the potential of combining epigenetic drugs with existing anticancer regimens as a promising strategy for overcoming cancer drug resistance.

Challenges and Opportunities of Genomic Approaches in Therapeutics Development

The magnitude of all therapeutic responses is significantly determined by genome structure, variation, and functional interactions. This determination occurs at many levels which are discussed in the current review. Well-established examples of structural variation between individuals are known to dictate an individual's response to numerous drugs, as clearly illustrated by warfarin. The exponential rate of genomic-based interrogation is coupled with an expanding repertoire of genomic technologies and applications. This is leading to an ever more sophisticated appreciation of how structural variation, regulation of transcription and genomic structure, both individually and collectively, define cell therapeutic responses.

DNA methylation-based lung adenocarcinoma subtypes can predict prognosis, recurrence, and immunotherapeutic implications

The marked heterogeneity of lung adenocarcinoma (LUAD) makes its diagnosis and treatment difficult. In addition, the aberrant DNA methylation profile contributes to tumor heterogeneity and alters the immune response. We used DNA methylation array data from publicly available databases to establish a predictive model for LUAD prognosis. Thirty-three methylation sites were identified as specific prognostic biomarkers, independent of patients' clinical characteristics. These methylation profiles were used to identify potential drug candidates and study the immune microenvironment of LUAD and response to immunotherapy. When compared with the high-risk group, the low-risk group had a lower recurrence rate and favorable prognosis. The tumor microenvironment differed between the two groups as reflected by the higher number of resting dendritic cells and a lower number of monocytes and resting mast cells in the low-risk group. Moreover, low-risk patients reported higher immune and stromal scores, lower tumor purity, and higher expression of HLA genes. Low-risk patients responded well to immunotherapy due to higher expression of immune checkpoint molecules and lower stemness index. Thus, our model predicted a favorable prognosis and increased overall survival for patients in the low-risk methylation group. Further, this model could provide potential drug targets to develop effective immunotherapies for LUAD.

A Novel Promoter CpG-Based Signature for Long-Term Survival Prediction of Breast Cancer Patients

DNA methylation has been reported as one of the most critical epigenetic aberrations during the tumorigenesis and development of breast cancer (BC). This study explored a novel promoter CpG-based signature for long-term survival prediction of BC patients. We used The Cancer Genome Atlas (TCGA) data as training set, and results were validated in an independent dataset from Gene Expression Omnibus (GEO). First, the differential methylation CpG sites were screened in TCGA dataset, of which the candidate promoter CpG sites were preliminarily identified with the univariate Cox regression analysis and the least absolute shrinkage and selection operator regression analysis. Second, the signature was constructed with stepwise regression analysis and multivariate Cox proportional hazards model, which was validated with the survival analysis of two cohorts each from TCGA and GEO databases. The 10-year receiver operating characteristic curves of risk score presented an area under the curve of over 0.7 for both cohorts. A nomogram was also constructed and released. Moreover, Gene Set Enrichment Analysis was performed to identify the more active pathways in high-risk patients. The CpG sites-target gene correlations and differential methylation regions were further explored. In conclusion, the promoter CpG-based signature exhibited good prognostic prediction efficacy in the long-term overall survival of BC patients.

Epigenetic regulation of the lineage specificity of primary human dermal lymphatic and blood vascular endothelial cells

Lymphatic and blood vascular endothelial cells (ECs) share several molecular and developmental features. However, these two cell types possess distinct phenotypic signatures, reflecting their different biological functions. Despite significant advances in elucidating how the specification of lymphatic and blood vascular ECs is regulated at the transcriptional level during development, the key molecular mechanisms governing their lineage identity under physiological or pathological conditions remain poorly understood. To explore the epigenomic signatures in the maintenance of EC lineage specificity, we compared the transcriptomic landscapes, histone composition (H3K4me3 and H3K27me3) and DNA methylomes of cultured matched human primary dermal lymphatic and blood vascular ECs. Our findings reveal that blood vascular lineage genes manifest a more ‘repressed’ histone composition in lymphatic ECs, whereas DNA methylation at promoters is less linked to the differential transcriptomes of lymphatic versus blood vascular ECs. Meta-analyses identified two transcriptional regulators, BCL6 and MEF2C, which potentially govern endothelial lineage specificity. Notably, the blood vascular endothelial lineage markers CD34, ESAM and FLT1 and the lymphatic endothelial lineage markers PROX1, PDPN and FLT4 exhibited highly differential epigenetic profiles and responded in distinct manners to epigenetic drug treatments. The perturbation of histone and DNA methylation selectively promoted the expression of blood vascular endothelial markers in lymphatic endothelial cells, but not vice versa. Overall, our study reveals that the fine regulation of lymphatic and blood vascular endothelial transcriptomes is maintained via several epigenetic mechanisms, which are crucial to the maintenance of endothelial cell identity.

COCOA: coordinate covariation analysis of epigenetic heterogeneity

A key challenge in epigenetics is to determine the biological significance of epigenetic variation among individuals. We present Coordinate Covariation Analysis (COCOA), a computational framework that uses covariation of epigenetic signals across individuals and a database of region sets to annotate epigenetic heterogeneity. COCOA is the first such tool for DNA methylation data and can also analyze any epigenetic signal with genomic coordinates. We demonstrate COCOA’s utility by analyzing DNA methylation, ATAC-seq, and multi-omic data in supervised and unsupervised analyses, showing that COCOA provides new understanding of inter-sample epigenetic variation. COCOA is available on Bioconductor (http://bioconductor.org/packages/COCOA).

Identification of Transcription Factor/Gene Axis in Colon Cancer Using a Methylome Approach

Colon cancer is one of the most commonly diagnosed cancers worldwide. Both environmental and molecular characters can influence its development. DNA methylation has been heralded as a promising marker for use in cancer prevention, diagnosis, and treatment. It has been shown to facilitate cancer progression through multiple mechanisms. Changes in DNA methylation can inhibit or promote the binding of transcription factors (TFs) and further disturb gene regulation. Detection of DNA methylation-mediated regulatory events in colon cancer are critical for mining novel biomarkers. Here, we explore the influence of CpG sites located at promoter regions of differentially expressed genes and identify methylation–gene relationships using expression–methylation quantitative trait loci. We find that promoter methylation sites mainly negatively regulate the corresponding genes. We also identify candidate TFs that can bind to these sites in a sequence-dependent manner. By integrating transcriptome and methylome profiles, we construct a TF–CpG–gene regulatory network for colon cancer, which is used to determine the roles of TFs and methylation in the transcription process. Finally, based on TF–CpG–gene relationships, we design a framework to evaluate patient prognosis, which shows that one TF–CpG–gene triplet is significantly associated with patient survival rate and represents a potential novel biomarker for use in colon cancer prognosis and treatment.

Epigenetic and breast cancer therapy: Promising diagnostic and therapeutic applications

The global burden of breast cancer (BC) is increasing significantly. This trend is caused by several factors such as late diagnosis, limited treatment options for certain BC subtypes, drug resistance which all lead to poor clinical outcomes. Recent research has reported the role of epigenetic alterations in the mechanism of BC pathogenesis and its hallmarks include drug resistance and stemness features. The understanding of these modifications and their significance in the management of BC carcinogenesis is challenging and requires further attention. Nevertheless, it promises to provide novel insight needed for utilizing these alterations as potential diagnostic, prognostic markers, predict treatment efficacy, as well as therapeutic agents. This highlights the importance of continuing research development to further advance the existing knowledge on epigenetics and BC carcinogenesis to overcome the current challenges. Hence, this review aims to shed light and discuss the current state of epigenetics research in the diagnosis and management of BC.

Enhancer prediction in the human genome by probabilistic modelling of the chromatin feature patterns

Background

The binding sites of transcription factors (TFs) and the localisation of histone modifications in the human genome can be quantified by the chromatin immunoprecipitation assay coupled with next-generation sequencing (ChIP-seq). The resulting chromatin feature data has been successfully adopted for genome-wide enhancer identification by several unsupervised and supervised machine learning methods. However, the current methods predict different numbers and different sets of enhancers for the same cell type and do not utilise the pattern of the ChIP-seq coverage profiles efficiently.

Results

In this work, we propose a PRobabilistic Enhancer PRedictIoN Tool (PREPRINT) that assumes characteristic coverage patterns of chromatin features at enhancers and employs a statistical model to account for their variability. PREPRINT defines probabilistic distance measures to quantify the similarity of the genomic query regions and the characteristic coverage patterns. The probabilistic scores of the enhancer and non-enhancer samples are utilised to train a kernel-based classifier. The performance of the method is demonstrated on ENCODE data for two cell lines. The predicted enhancers are computationally validated based on the transcriptional regulatory protein binding sites and compared to the predictions obtained by state-of-the-art methods.

Conclusion

PREPRINT performs favorably to the state-of-the-art methods, especially when requiring the methods to predict a larger set of enhancers. PREPRINT generalises successfully to data from cell type not utilised for training, and often the PREPRINT performs better than the previous methods. The PREPRINT enhancers are less sensitive to the choice of prediction threshold. PREPRINT identifies biologically validated enhancers not predicted by the competing methods. The enhancers predicted by PREPRINT can aid the genome interpretation in functional genomics and clinical studies.

Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

BACKGROUND

Estrogen receptor (ER) positive breast cancer is often effectively treated with drugs that inhibit ER signaling, i.e., tamoxifen (TAM) and aromatase inhibitors (AIs). However, 30% of ER+ breast cancer patients develop resistance to therapy leading to tumour recurrence. Changes in the methylation profile have been implicated as one of the mechanisms through which therapy resistance develops. Therefore, we aimed to identify methylation loci associated with endocrine therapy resistance.

METHODS

We used genome-wide DNA methylation profiles of primary ER+/HER2- tumours from The Cancer Genome Atlas in combination with curated data on survival and treatment to predict development of endocrine resistance. Association of individual DNA methylation markers with survival was assessed using Cox proportional hazards models in a cohort of ER+/HER2- tumours (N = 552) and two sub-cohorts corresponding to the endocrine treatment (AI or TAM) that patients received (N = 210 and N = 172, respectively). We also identified multivariable methylation signatures associated with survival using Cox proportional hazards models with elastic net regularization. Individual markers and multivariable signatures were compared with DNA methylation profiles generated in a time course experiment using the T47D ER+ breast cancer cell line treated with tamoxifen or deprived from estrogen.

RESULTS

We identified 134, 5 and 1 CpGs for which DNA methylation is significantly associated with survival in the ER+/HER2-, TAM and AI cohorts respectively. Multi-locus signatures consisted of 203, 36 and 178 CpGs and showed a large overlap with the corresponding single-locus signatures. The methylation signatures were associated with survival independently of tumour stage, age, AI treatment, and luminal status. The single-locus signature for the TAM cohort was conserved among the loci that were differentially methylated in endocrine-resistant T47D cells. Similarly, multi-locus signatures for the ER+/HER2- and AI cohorts were conserved in endocrine-resistant T47D cells. Also at the gene set level, several sets related to endocrine therapy and resistance were enriched in both survival and T47D signatures.

CONCLUSIONS

We identified individual and multivariable DNA methylation markers associated with therapy resistance independently of luminal status. Our results suggest that these markers identified from primary tumours prior to endocrine treatment are associated with development of endocrine resistance.