DNA methylation signatures for breast cancer classification and prognosis

Differential methylation region detection via an array-adaptive normalized kernel-weighted model

A differentially methylated region (DMR) is a genomic region that has significantly different methylation patterns between biological conditions. Identifying DMRs between different biological conditions is critical for developing disease biomarkers. Although methods for detecting DMRs in microarray data have been introduced, developing methods with high precision, recall, and accuracy in determining the true length of DMRs remains a challenge. In this study, we propose a normalized kernel-weighted model to account for similar methylation profiles using the relative probe distance from "nearby" CpG sites. We also extend this model by proposing an array-adaptive version in attempt to account for the differences in probe spacing between Illumina's Infinium 450K and EPIC bead array respectively. We also study the asymptotic results of our proposed statistic. We compare our approach with a popular DMR detection method via simulation studies under large and small treatment effect settings. We also discuss the susceptibility of our method in detecting the true length of the DMRs under these two settings. Lastly, we demonstrate the biological usefulness of our method when combined with pathway analysis methods on oral cancer data. We have created an R package called idDMR, downloadable from GitHub repository with link: https://github.com/DanielAlhassan/idDMR, that allows for the convenient implementation of our array-adaptive DMR method.

Promoter hypermethylation of RARB and GSTP1 genes in plasma cell-free DNA as breast cancer biomarkers in Peruvian women

BACKGROUND

Promoter hypermethylation is one of the enabling mechanisms of hallmarks of cancer. Tumor suppressor genes like RARB and GSTP1 have been reported as hypermethylated in breast cancer tumors compared with normal tissues in several populations. This case-control study aimed to determine the association between the promoter methylation ratio (PMR) of RARB and GSTP1 genes (separately and as a group) with breast cancer and its clinical-pathological variables in Peruvian patients, using a liquid biopsy approach.

METHODS

A total of 58 breast cancer patients and 58 healthy controls, matched by age, participated in the study. We exacted cell-free DNA (cfDNA) from blood plasma and converted it by bisulfite salts. Methylight PCR was performed to obtain the PMR value of the studied genes. We determined the association between PMR and breast cancer, in addition to other clinicopathological variables. The sensitivity and specificity of the PMR of these genes were obtained.

RESULTS

A significant association was not found between breast cancer and the RARB PMR (OR = 1.90; 95% CI [0.62-6.18]; p = 0.210) or the GSTP1 PMR (OR = 6.57; 95% CI [0.75-307.66]; p = 0.114). The combination of the RARB + GSTP1 PMR was associated with breast cancer (OR = 2.81; 95% CI [1.02-8.22]; p = 0.026), controls under 50 years old (p = 0.048), patients older than 50 (p = 0.007), and postmenopausal (p = 0.034). The PMR of both genes showed a specificity of 86.21% and a sensitivity of 31.03%.

CONCLUSION

Promoter hypermethylation of RARB + GSTP1 genes is associated with breast cancer, older age, and postmenopausal Peruvian patients. The methylated promoter of the RARB + GSTP1 genes needs further validation to be used as a biomarker for liquid biopsy and as a recommendation criterion for additional tests in asymptomatic women younger than 50 years.

Attention-based GCN integrates multi-omics data for breast cancer subtype classification and patient-specific gene marker identification

Breast cancer is a heterogeneous disease and can be divided into several subtypes with unique prognostic and molecular characteristics. The classification of breast cancer subtypes plays an important role in the precision treatment and prognosis of breast cancer. Benefitting from the relation-aware ability of a graph convolution network (GCN), we present a multi-omics integrative method, the attention-based GCN (AGCN), for breast cancer molecular subtype classification using messenger RNA expression, copy number variation and deoxyribonucleic acid methylation multi-omics data. In the extensive comparative studies, our AGCN models outperform state-of-the-art methods under different experimental conditions and both attention mechanisms and the graph convolution subnetwork play an important role in accurate cancer subtype classification. The layer-wise relevance propagation (LRP) algorithm is used for the interpretation of model decision, which can identify patient-specific important biomarkers that are reported to be related to the occurrence and development of breast cancer. Our results highlighted the effectiveness of the GCN and attention mechanisms in multi-omics integrative analysis and the implement of the LRP algorithm can provide biologically reasonable insights into model decision.

Attention-based generative adversarial networks improve prognostic outcome prediction of cancer from multimodal data

The prediction of prognostic outcome is critical for the development of efficient cancer therapeutics and potential personalized medicine. However, due to the heterogeneity and diversity of multimodal data of cancer, data integration and feature selection remain a challenge for prognostic outcome prediction. We proposed a deep learning method with generative adversarial network based on sequential channel-spatial attention modules (CSAM-GAN), a multimodal data integration and feature selection approach, for accomplishing prognostic stratification tasks in cancer. Sequential channel-spatial attention modules equipped with an encoder-decoder are applied for the input features of multimodal data to accurately refine selected features. A discriminator network was proposed to make the generator and discriminator learning in an adversarial way to accurately describe the complex heterogeneous information of multiple modal data. We conducted extensive experiments with various feature selection and classification methods and confirmed that the CSAM-GAN via the multilayer deep neural network (DNN) classifier outperformed these baseline methods on two different multimodal data sets with miRNA expression, mRNA expression and histopathological image data: lower-grade glioma and kidney renal clear cell carcinoma. The CSAM-GAN via the multilayer DNN classifier bridges the gap between heterogenous multimodal data and prognostic outcome prediction.

Molecular mechanisms of multi-omic regulation in breast cancer

Breast cancer is a complex disease that is influenced by the concurrent influence of multiple genetic and environmental factors. Recent advances in genomics and other high throughput biomolecular techniques (-omics) have provided numerous insights into the molecular mechanisms underlying breast cancer development and progression. A number of these mechanisms involve multiple layers of regulation. In this review, we summarize the current knowledge on the role of multiple omics in the regulation of breast cancer, including the effects of DNA methylation, non-coding RNA, and other epigenomic changes. We comment on how integrating such diverse mechanisms is envisioned as key to a more comprehensive understanding of breast carcinogenesis and cancer biology with relevance to prognostics, diagnostics and therapeutics. We also discuss the potential clinical implications of these findings and highlight areas for future research. Overall, our understanding of the molecular mechanisms of multi-omic regulation in breast cancer is rapidly increasing and has the potential to inform the development of novel therapeutic approaches for this disease.

Targeting and Sensitization of Breast Cancer Cells to Killing with a Novel Interleukin-13 Receptor α2-Specific Hybrid Cytolytic Peptide

Highly metastatic breast cancers, such as triple-negative subtypes (TNBC), require the most effective treatments. Since interleukin-13 receptor (IL-13R)α2 is reportedly over-expressed in some cancers, we investigated here its expression and the feasibility of therapeutically targeting this receptor in breast cancer using a novel hybrid cytolytic peptide (Pep-1-Phor21) consisting of IL-13Rα2-binding (Pep-1) and cytolytic (Phor21) domains. This study demonstrates that particularly TNBC tissues and cells display the prominent expression of IL-13Rα2. Furthermore, Pep-1-Phor21 induced the rapid necrosis of tumor cells expressing cell-surface IL-13Rα2. Notably, IL-13Rα2 expression was found to be epigenetically regulated in breast cancer cells in that the inhibition of histone deacetylase (HDAC) or DNA methyltransferase (DNMT) upregulated IL-13Rα2 expression, thereby sensitizing them to Pep-1-Phor21. IL-13Rα2-negative non-malignant cells were refractory to these epigenetic effects. Consistent with its cytolytic activity, Pep-1-Phor21 readily destroyed IL-13Rα2-expressing breast cancer spheroids with HDAC or DNMT inhibition, further enhancing cytolytic activity. Therefore, the Pep-1-Phor21-mediated targeting of IL-13Rα2 is a potentially novel therapeutic strategy for TNBC. Given that tumor cells can be selectively sensitized to Pep-1-Phor21 via the epigenetic up-regulation of IL-13Rα2, a combined adjuvant approach involving Pep-1-Phor21 and epigenetic inhibitors may be an effective strategy.

HpaII-assisted and linear amplification-enhanced isothermal exponential amplification fluorescent strategy for rapid and sensitive detection of DNA methyltransferase activity

The detection of methyltransferase (MTase) activity is of great significance in methylation-related disease diagnosis and drug screening. Herein, a HpaII-assisted and linear amplification-enhanced exponential amplification strategy is proposed for sensitive and label-free detection of M.SssI MTase activity. The P1 probe contains self-complementary sequence 5'-CTAGCCGGCTAG-3' at 3'-terminal. After denaturation and annealing, P1 probes hybridize with itself to generate P1 duplexes. M.SssI MTase induces methylation of cytosine at 5'-CG-3' in P1 duplexes, and thus, HpaII fails to cleave at 5'-CCGG-3' due to methylation sensitivity, leaving P1 duplex intact. Then, these intact P1 duplexes are extended along 3'-terminal through Vent (exo^-) DNA polymerase to generate dsDNA, which is recognized and nicked at the recognition sites by Nt.BstNBI, releasing two copies of primer X. Primer X hybridizes with X' at the amplification template T1 (X'-Y'-X') and then serves as primers to trigger the exponential amplification reaction (EXPAR). The point of inflection (POI) values of real-time fluorescence curves is linearly correlated with the logarithm of M.SssI MTase concentration in the range of 0.125 [Formula: see text] 8 U mL^-1 with a low detection limit of 0.034 U mL^-1. In the absence of M.SssI, P1 duplexes are cut by HpaII and separated into ssDNA under the executed temperature of EXPAR and thus unable to trigger the amplification. The strategy provides good selectivity against other types of MTases and protein and is able to detect M.SssI activity in human serum. Furthermore, the analytical method has the generality and can be extended to the analysis of other types of DNA MTases.

Signature literature review reveals AHCY, DPYSL3, and NME1 as the most recurrent prognostic genes for neuroblastoma

Neuroblastoma is a childhood neurological tumor which affects hundreds of thousands of children worldwide, and information about its prognosis can be pivotal for patients, their families, and clinicians. One of the main goals in the related bioinformatics analyses is to provide stable genetic signatures able to include genes whose expression levels can be effective to predict the prognosis of the patients. In this study, we collected the prognostic signatures for neuroblastoma published in the biomedical literature, and noticed that the most frequent genes present among them were three: AHCY, DPYLS3, and NME1. We therefore investigated the prognostic power of these three genes by performing a survival analysis and a binary classification on multiple gene expression datasets of different groups of patients diagnosed with neuroblastoma. Finally, we discussed the main studies in the literature associating these three genes with neuroblastoma. Our results, in each of these three steps of validation, confirm the prognostic capability of AHCY, DPYLS3, and NME1, and highlight their key role in neuroblastoma prognosis. Our results can have an impact on neuroblastoma genetics research: biologists and medical researchers can pay more attention to the regulation and expression of these three genes in patients having neuroblastoma, and therefore can develop better cures and treatments which can save patients' lives.

An Optimized CoBRA Method for the Microfluidic Electrophoresis Detection of Breast Cancer Associated RASSF1 Methylation

Although breast cancer screening assays exist, many are inaccessible and have high turnaround times, leaving a significant need for better alternatives. Hypermethylation of tumor suppressor genes is a common epigenetic marker of breast cancer. Methylation tends to occur most frequently in the promoter and first exon regions of genes. Preliminary screening tests are crucial for informing patients whether they should pursue more involved testing. We selected RASSF1, previously demonstrated to be aberrantly methylated in liquid biopsies from breast cancer patients, as our gene of interest. Using CoBRA as our method for methylation quantification, we designed unique primer sets that amplify a portion of the CpG island spanning the 5' end of the RASSF1 first exon. We integrated the CoBRA approach with a microfluidics-based electrophoresis quantification system (LabChip) and optimized the assay such that insightful results could be obtained without post-PCR purification or concentration, two steps traditionally included in CoBRA assays. Circumventing these steps resulted in a decreased turnaround time and mitigated the laboratory machinery and reagent requirements. Our streamlined technique has an estimated limit of detection of 9.1 ng/μL of input DNA and was able to quantify methylation with an average error of 4.3%.

Searching for DNA methylation in patients triple-negative breast cancer: a liquid biopsy approach

INTRODUCTION

Liquid biopsies are proving to have diagnostic and prognostic value in many different cancers, and in breast cancer they have the potential to improve outcomes by providing valuable information throughout a patient's cancer journey. However, patients with triple negative breast cancer (TNBC) have received little benefit from such liquid biopsies due to underlying limitations in the discovery and utility of robust biomarkers. Here, we examine the development of DNA methylation-based liquid biopsy assays for breast cancer and how they pertain to TNBC.

AREAS COVERED

We conducted a systematic review of liquid biopsy assays for breast cancer and analyzed their relevance in TNBC. We show that the utility of DNA mutation-based assays is poor for TNBC due to the low mutational frequencies across the genome in this subtype. We offer a detailed review of mDETECT - a liquid biopsy specifically designed for assessing tumor burden in TNBC patients.

EXPERT OPINION

DNA methylation are foundational and robust events that occur in cancer evolution and may differentiate almost all forms of cancer, including TNBC. Longitudinal patient monitoring using DNA methylation-based liquid biopsies offers great potential for improving the detection and management of TNBC.

The crucial role of epigenetic regulation in breast cancer anti-estrogen resistance: Current findings and future perspectives

Breast cancer (BC) cell de-sensitization to Tamoxifen (TAM) or other selective estrogen receptor (ER) modulators (SERM) is a complex process associated with BC heterogeneity and the transformation of ER signalling. The most influential resistance-related mechanisms include modifications in ER expression and gene regulation patterns. During TAM/SERM treatment, epigenetic mechanisms can effectively silence ER expression and facilitate the development of endocrine resistance. ER status is efficiently regulated by specific epigenetic tools including hypermethylation of CpG islands within ER promoters, increased histone deacetylase activity in the ER promoter, and/or translational repression by miRNAs. Over-methylation of the ER α gene (ESR1) promoter by DNA methyltransferases was associated with poor prognosis and indicated the development of resistance. Moreover, BC progression and spreading were marked by transformed chromatin remodelling, post-translational histone modifications, and expression of specific miRNAs and/or long non-coding RNAs. Therefore, targeted inhibition of histone acetyltransferases (e.g. MYST3), deacetylases (e.g. HDAC1), and/or demethylases (e.g. lysine-specific demethylase LSD1) was shown to recover and increase BC sensitivity to anti-estrogens. Indicated as a powerful molecular instrument, the administration of epigenetic drugs can regain ER expression along with the activation of tumour suppressor genes, which can in turn prevent selection of resistant cells and cancer stem cell survival. This review examines recent advances in the epigenetic regulation of endocrine drug resistance and evaluates novel anti-resistance strategies. Underlying molecular mechanisms of epigenetic regulation will be discussed, emphasising the utilization of epigenetic enzymes and their inhibitors to re-program irresponsive BCs.

Role of Immune Cell-Specific Hypermethylation Signatures in Classification and Risk Stratification of Breast Cancer

Background: Epigenetic regulation, including DNA methylation, plays a major role in shaping the identity and function of immune cells. Innate and adaptive immune cells recruited into tumor tissues contribute to the formation of the tumor immune microenvironment (TIME), which is closely involved in tumor progression in breast cancer (BC). However, the specific methylation signatures of immune cells have not been thoroughly investigated yet. Additionally, it remains unknown whether immune cells-specific methylation signatures can identify subgroups and stratify the prognosis of BC patients. Methods: DNA methylation profiles of six immune cell types from eight datasets downloaded from the Gene Expression Omnibus were collected to identify immune cell-specific hypermethylation signatures (IC-SHMSs). Univariate and multivariate cox regression analyses were performed using BC data obtained from The Cancer Genome Atlas to identify the prognostic value of these IC-SHMSs. An unsupervised clustering analysis of the IC-SHMSs with prognostic value was performed to categorize BC patients into subgroups. Multiple Cox proportional hazard models were constructed to explore the role of IC-SHMSs and their relationship to clinical characteristics in the risk stratification of BC patients. Integrated discrimination improvement (IDI) was performed to determine whether the improvement of IC-SHMSs on clinical characteristics in risk stratification was statistically significant. Results: A total of 655 IC-SHMSs of six immune cell types were identified. Thirty of them had prognostic value, and 10 showed independent prognostic value. Four subgroups of BC patients, which showed significant heterogeneity in terms of survival prognosis and immune landscape, were identified. The model incorporating nine IC-SHMSs showed similar survival prediction accuracy as the clinical model incorporating age and TNM stage [3-year area under the curve (AUC): 0.793 vs. 0.785; 5-year AUC: 0.735 vs. 0.761]. Adding the IC-SHMSs to the clinical model significantly improved its prediction accuracy in risk stratification (3-year AUC: 0.897; 5-year AUC: 0.856). The results of IDI validated the statistical significance of the improvement (p < 0.05). Conclusions: Our study suggests that IC-SHMSs may serve as signatures of classification and risk stratification in BC. Our findings provide new insights into epigenetic signatures, which may help improve subgroup identification, risk stratification, and treatment management.

Epigenetic Regulation of Breast Cancer Stem Cells Contributing to Carcinogenesis and Therapeutic Implications

Globally, breast cancer has remained the most commonly diagnosed cancer and the leading cause of cancer death among women. Breast cancer is a highly heterogeneous and phenotypically diverse group of diseases, which require different selection of treatments. Breast cancer stem cells (BCSCs), a small subset of cancer cells with stem cell-like properties, play essential roles in breast cancer progression, recurrence, metastasis, chemoresistance and treatments. Epigenetics is defined as inheritable changes in gene expression without alteration in DNA sequence. Epigenetic regulation includes DNA methylation and demethylation, as well as histone modifications. Aberrant epigenetic regulation results in carcinogenesis. In this review, the mechanism of epigenetic regulation involved in carcinogenesis, therapeutic resistance and metastasis of BCSCs will be discussed, and finally, the therapies targeting these biomarkers will be presented.

A High Epigenetic Risk Score Shapes the Non-Inflamed Tumor Microenvironment in Breast Cancer

Background: Epigenetic dysregulation via aberrant DNA methylation has gradually become recognized as an efficacious signature for predicting tumor prognosis and response to therapeutic targets. However, reliable DNA methylation biomarkers describing tumorigenesis remain to be comprehensively explored regarding their prognostic and therapeutic potential in breast cancer (BC). Methods: Whole-genome methylation datasets integrated from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were profiled (n = 1,268). A three-stage selection procedure (discovery, training, and external validation) was utilized to screen out the prominent biomarkers and establish a robust risk score from more than 300,000 CpG sites after quality control, rigorous filtering, and reducing dimension. Moreover, gene set enrichment analyses guided us to systematically correlate this epigenetic risk score with immunological characteristics, including immunomodulators, anti-cancer immunity cycle, immune checkpoints, tumor-infiltrating immune cells and a series of signatures upon modulating components within BC tumor microenvironment (TME). Multi-omics data analyses were performed to decipher specific genomic alterations in low- and high-risk patients. Additionally, we also analyzed the role of risk score in predicting response to several treatment options. Results: A 10-CpG-based prognostic signature which could significantly and independently categorize BC patients into distinct prognoses was established and sufficiently validated. And we hypothesize that this signature designs a non-inflamed TME in BC based on the evidence that the derived risk score is negatively correlated with tumor-associated infiltrating immune cells, anti-cancer immunity cycle, immune checkpoints, immune cytolytic activity, T cell inflamed score, immunophenoscore, and the vast majority of immunomodulators. The identified high-risk patients were characterized by upregulation of immune inhibited oncogenic pathways, higher TP53 mutation and copy number burden, but lower response to cancer immunotherapy and chemotherapy. Conclusion: Our work highlights the complementary roles of 10-CpG-based signature in estimating overall survival in BC patients, shedding new light on investigating failed events concerning immunotherapy at present.

The Roles of DNA Demethylases in Triple-Negative Breast Cancer

Triple-negative breast cancers (TNBCs) are very heterogenous, molecularly diverse, and are characterized by a high propensity to relapse or metastasize. Clinically, TNBC remains a diagnosis of exclusion by the lack of hormone receptors (Estrogen Receptor (ER) and Progesterone Receptor (PR)) as well as the absence of overexpression and/or amplification of HER2. DNA methylation plays an important role in breast cancer carcinogenesis and TNBCs have a distinct DNA methylation profile characterized by marked hypomethylation and lower gains of methylations compared to all other subtypes. DNA methylation is regulated by the balance of DNA methylases (DNMTs) and DNA demethylases (TETs). Here, we review the roles of TETs as context-dependent tumor-suppressor genes and/or oncogenes in solid tumors, and we discuss the current understandings of the oncogenic role of TET1 and its therapeutic implications in TNBCs.

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.

Identification of epigenetic regulators in the estrogen signaling pathway via siRNA screening

Breast cancer is the most prevalent malignant disease among women across the globe. Notably, estrogen signaling plays a vital role in the progression of estrogen receptor-positive breast cancer. Therefore, targeting epigenetic regulators is a promising therapy for cancer. To identify epigenetic regulators, we conducted a siRNA screening targeting 140 epigenetic genes by which 32 positive and 15 negative regulators of estrogen signaling were obtained. The protein-protein interaction network of the candidate genes was constructed and the topological parameters of the network were calculated. As a result, the top 10 genes with higher MCC (Maximal Clique Centrality) scores were considered as hub genes. Notably, the hub genes all belong to polycomb group genes. The transcription levels of the above genes were compared between breast cancer and normal tissues using the UALCAN database. Then, the survival analysis of the hub genes was conducted using the Kaplan-Meier Plotter online database. Lastly, the effect of hub genes on MCF-7 cell proliferation and ER target gene expression were investigated. These results indicate that PcG genes regulate estrogen signaling and breast cancer development.

Deciphering the nexus between the tumor immune microenvironment and DNA methylation in subgrouping estrogen receptor-positive breast cancer

BACKGROUND

Based on variable DNA methylation (DNAm), estrogen receptor (ER)-positive breast cancer (BRCA) is composed of two major subtypes, with the hypomethylated subgroup displaying good survival. Evidence indicates that the tumor microenvironment (TME) plays an important role in tumor progression and metastasis; however, its role and biological characteristics in DNAm-based subtypes of ER-positive BRCA remain largely unknown.

METHODS

Transcriptome data and matched clinical information of BRCA were downloaded from the Cancer Genome Atlas. Immune (ISs) and stromal scores (SSs) of BRCA patients were calculated using the ESTIMATE algorithm. Inferred fractions of 22 types of infiltrating immune cells of BRCA were collected from the Cancer Immunome Atlas.

RESULTS

The hypomethylated ER-positive BRCA subtype displayed high ISs, echoing the finding that higher ISs are associated with good BRCA survival. In addition, we analyzed the differentially expressed genes between the hypo-high-IS and hyper-low-IS BRCA subtypes in ER-positive patients and identified a co-expressed gene module (i.e., red module) enriched in immune-related biological processes (e.g., leukocyte activation involved in immune response). Moreover, four hub genes (i.e., PLEK, CD53, EVI2B, and CD4) in this module showed significant association between their expression and ER-positive BRCA survival.

CONCLUSIONS

We found differences in the tumor immune microenvironment (TIME) between DNAm-based BRCA subgroups in ER-positive patients and identified a specific module and hub genes involved to these differences. These findings elucidate the immunological basis for ER-positive BRCA progression and classification and provide potential gene biomarkers and targets for ER-positive BRCA diagnosis and treatment.

An Information Theoretical Multilayer Network Approach to Breast Cancer Transcriptional Regulation

Breast cancer is a complex, highly heterogeneous disease at multiple levels ranging from its genetic origins and molecular processes to clinical manifestations. This heterogeneity has given rise to the so-called intrinsic or molecular breast cancer subtypes. Aside from classification, these subtypes have set a basis for differential prognosis and treatment. Multiple regulatory mechanisms-involving a variety of biomolecular entities-suffer from alterations leading to the diseased phenotypes. Information theoretical approaches have been found to be useful in the description of these complex regulatory programs. In this work, we identified the interactions occurring between three main mechanisms of regulation of the gene expression program: transcription factor regulation, regulation via noncoding RNA, and epigenetic regulation through DNA methylation. Using data from The Cancer Genome Atlas, we inferred probabilistic multilayer networks, identifying key regulatory circuits able to (partially) explain the alterations that lead from a healthy phenotype to different manifestations of breast cancer, as captured by its molecular subtype classification. We also found some general trends in the topology of the multi-omic regulatory networks: Tumor subtype networks present longer shortest paths than their normal tissue counterpart; epigenomic regulation has frequently focused on genes enriched for certain biological processes; CpG methylation and miRNA interactions are often part of a regulatory core of conserved interactions. The use of probabilistic measures to infer information regarding theoretical-derived multilayer networks based on multi-omic high-throughput data is hence presented as a useful methodological approach to capture some of the molecular heterogeneity behind regulatory phenomena in breast cancer, and potentially other diseases.

Genome-wide 5-hydroxymethylcytosine Profiling Analysis Identifies MAP7D1 as A Novel Regulator of Lymph Node Metastasis in Breast Cancer

Although DNA 5-hydroxymethylcytosine (5hmC) is recognized as an important epigenetic mark in cancer, its precise role in lymph node metastasis remains elusive. In this study, we investigated how 5hmC associates with lymph node metastasis in breast cancer. Accompanying with high expression of TET1 and TET2 proteins, large numbers of genes in the metastasis-positive primary tumors exhibit higher 5hmC levels than those in the metastasis-negative primary tumors. In contrast, the TET protein expression and DNA 5hmC decrease significantly within the metastatic lesions in the lymph nodes compared to those in their matched primary tumors. Through genome-wide analysis of 8 sets of primary tumors, we identified 100 high-confidence metastasis-associated 5hmC signatures, and it is found that increased levels of DNA 5hmC and gene expression of MAP7D1 associate with high risk of lymph node metastasis. Furthermore, we demonstrate that MAP7D1, regulated by TET1, promotes tumor growth and metastasis. In conclusion, the dynamic 5hmC profiles during lymph node metastasis suggest a link between DNA 5hmC and lymph node metastasis. Meanwhile, the role of MAP7D1 in breast cancer progression suggests that the metastasis-associated 5hmC signatures are potential biomarkers to predict the risk for lymph node metastasis, which may serve as diagnostic and therapeutic targets for metastatic breast cancer.

OPCML Methylation and the Risk of Ovarian Cancer: A Meta and Bioinformatics Analysis

Background: The association of opioid binding protein cell adhesion molecule-like (OPCML) gene methylation with ovarian cancer risk remains unclear. Methods: We identified eligible studies by searching the PubMed, Web of Science, ScienceDirect, and Wanfang databases. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to determine the association of OPCML methylation with ovarian cancer risk. Meta-regression and subgroup analysis were used to assess the sources of heterogeneity. Additionally, we analyzed the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets to validate our findings. Results: Our study included 476 ovarian cancer patients and 385 controls from eight eligible studies. The pooled OR was 33.47 (95% CI = 12.43-90.16) in the cancer group vs. the control group under the random-effects model. The association was still significant in subgroups according to sample type, control type, methods, and sample sizes (all P < 0.05). Sensitivity analysis showed that the finding was robust. No publication bias was observed in Begg's (P = 0.458) and Egger's tests (P = 0.261). We further found that OPCML methylation was related to III/IV (OR = 4.20, 95% CI = 1.59-11.14) and poorly differentiated grade (OR = 4.37; 95% CI = 1.14-16.78). Based on GSE146552 and GSE155760, we validated that three CpG sites (cg16639665, cg23236270, cg15964611) in OPCML promoter region were significantly higher in cancer tissues compared to normal tissues. However, we did not observe the associations of OPCML methylation with clinicopathological parameters and overall survival based on TCGA ovarian cancer data. Conclusion: Our findings support that OPCML methylation is associated with an increased risk of ovarian cancer.

RNA m6A Methylation Regulators Subclassify Luminal Subtype in Breast Cancer

RNA N⁶-methyladenosine (m⁶A) methylation is the most prevalent epitranscriptomic modification in mammals, with a complex and fine-tuning regulatory system. Recent studies have illuminated the potential of m⁶A regulators in clinical applications including diagnosis, therapeutics, and prognosis. Based on six datasets of breast cancer in The Cancer Genome Atlas (TCGA) database and two additional proteomic datasets, we provide a comprehensive view of all the known m⁶A regulators in their gene expression, copy number variations (CNVs), DNA methylation status, and protein levels in breast tumors and their association with prognosis. Among four breast cancer subtypes, basal-like subtype exhibits distinct expression and genomic alteration in m⁶A regulators from other subtypes. Accordingly, four representative regulators (IGF2BP2, IGF2BP3, YTHDC2, and RBM15) are identified as basal-like subtype-featured genes. Notably, luminal A/B samples are subclassified into two clusters based on the methylation status of those four genes. In line with its similarity to basal-like subtype, cluster1 shows upregulation in immune-related genes and cell adhesion molecules, as well as an increased number of tumor-infiltrating lymphocytes. Besides, cluster1 has worse disease-free and progression-free survival, especially among patients diagnosed with stage II and luminal B subtype. Together, this study highlights the potential functions of m⁶A regulators in the occurrence and malignancy progression of breast cancer. Given the heterogeneity within luminal subtype and high risk of recurrence and metastasis in a portion of patients, the prognostic stratification of luminal A/B subtypes utilizing basal-featured m⁶A regulators may help to improve the accuracy of diagnosis and therapeutics of breast cancer.

Non-Invasive Biomarkers for Early Detection of Breast Cancer

Breast cancer is the most common cancer in women worldwide. Accurate early diagnosis of breast cancer is critical in the management of the disease. Although mammogram screening has been widely used for breast cancer screening, high false-positive and false-negative rates and radiation from mammography have always been a concern. Over the last 20 years, the emergence of "omics" strategies has resulted in significant advances in the search for non-invasive biomarkers for breast cancer diagnosis at an early stage. Circulating carcinoma antigens, circulating tumor cells, circulating cell-free tumor nucleic acids (DNA or RNA), circulating microRNAs, and circulating extracellular vesicles in the peripheral blood, nipple aspirate fluid, sweat, urine, and tears, as well as volatile organic compounds in the breath, have emerged as potential non-invasive diagnostic biomarkers to supplement current clinical approaches to earlier detection of breast cancer. In this review, we summarize the current progress of research in these areas.

Hypomethylating Agent Azacitidine Is Effective in Treating Brain Metastasis Triple-Negative Breast Cancer Through Regulation of DNA Methylation of Keratin 18 Gene

Breast cancer patients presenting with symptomatic brain metastases have poor prognosis, and current chemotherapeutic agents are largely ineffective. In this study, we evaluated the hypomethylating agent azacitidine (AZA) for its potential as a novel therapeutic in preclinical models of brain metastasis of breast cancer. We used the parental triple-negative breast cancer MDA-MB-231 (231) cells and their brain colonizing counterpart (231Br) to ascertain phenotypic differences in response to AZA. We observed that 231Br cells have higher metastatic potential compared to 231 cells. With regard to therapeutic value, the AZA IC50 value in 231Br cells is significantly lower than that in parental cells (P < .01). AZA treatment increased apoptosis and inhibited the Wnt signaling transduction pathway, angiogenesis, and cell metastatic capacity to a significantly higher extent in the 231Br line. AZA treatment in mice with experimental brain metastases significantly reduced tumor burden (P = .0112) and increased survival (P = .0026) compared to vehicle. Lastly, we observed a decreased expression of keratin 18 (an epithelial maker) in 231Br cells due to hypermethylation, elucidating a potential mechanism of action of AZA in treating brain metastases from breast cancer.

11p15.5 epimutations in children with Wilms tumor and hepatoblastoma detected in peripheral blood

Background

Constitutional or somatic mosaic epimutations are increasingly recognized as a mechanism of gene dysregulation resulting in cancer susceptibility. Beckwith‐Wiedemann syndrome is the cancer predisposition syndrome most commonly associated with epimutation and is extremely variable in its phenotypic presentation, which can include isolated tumors. Because to the authors' knowledge large‐scale germline DNA sequencing studies have not included methylation analysis, the percentage of pediatric cancer predisposition that is due to epimutations is unknown.

Methods

Germline methylation testing at the 11p15.5 locus was performed in blood for 24 consecutive patients presenting with hepatoblastoma (3 patients) or Wilms tumor (21 patients).

Results

Six individuals with Wilms tumor and 1 patient with hepatoblastoma were found to have low‐level gain of methylation at imprinting control 1, and a child with hepatoblastoma was found to have loss of methylation at imprinting control 2. The loss of methylation at imprinting control 2 was found to be maternally inherited, despite not being associated with any detectable genomic alteration.

Conclusions

Overall, 33% of patients (8 of 24 patients) with Wilms tumor or hepatoblastoma were found to have an epigenetic susceptibility that was detectable in the blood. It is interesting to note that low‐level gain of methylation at imprinting control 1 predominantly was detected in females with bilateral Wilms tumors. Further studies in larger cohorts are needed to determine the efficacy of testing all patients with Wilms tumor or hepatoblastoma for 11p15.5 epimutations in the blood as part of DNA analysis because this hallmark of predisposition will not be detected by sequencing‐based approaches and detecting a cancer predisposition may modify treatment.

In the current study, all patients presenting with Wilms tumor or hepatoblastoma undergo 11p15.5 methylation analysis. Approximately one‐third are found to have an epimutation at this locus that is detectable in peripheral blood.

Integrating DNA methylation measures to improve clinical risk assessment: are we there yet? The case of BRCA1 methylation marks to improve clinical risk assessment of breast cancer

Current risk prediction models estimate the probability of developing breast cancer over a defined period based on information such as family history, non-genetic breast cancer risk factors, genetic information from high and moderate risk breast cancer susceptibility genes and, over the past several years, polygenic risk scores (PRS) from more than 300 common variants. The inclusion of additional data such as PRS improves risk stratification, but it is anticipated that the inclusion of epigenetic marks could further improve model performance accuracy. Here, we present the case for including information on DNA methylation marks to improve the accuracy of these risk prediction models, and consider how this approach contrasts genetic information, as identifying DNA methylation marks associated with breast cancer risk differs inherently according to the source of DNA, approaches to the measurement of DNA methylation, and the timing of measurement. We highlight several DNA-methylation-specific challenges that should be considered when incorporating information on DNA methylation marks into risk prediction models, using BRCA1, a highly penetrant breast cancer susceptibility gene, as an example. Only after careful consideration of study design and DNA methylation measurement will prospective performance of the incorporation of information regarding DNA methylation marks into risk prediction models be valid.

Methylome and transcriptome analyses reveal insights into the epigenetic basis for the good survival of hypomethylated ER-positive breast cancer subtype

Background

Breast cancer (BRCA) is a heterogeneous disease, characterized by different histopathological and clinical features and responses to various therapeutic measures. Despite the research progress of DNA methylation in classification and diagnosis of BRCA and the close relationship between DNA methylation and hormone receptor status, especially estrogen receptor (ER), the epigenetic mechanisms in various BRCA subtypes and the biomarkers associated with diagnostic characteristics of patients under specific hormone receptor status remain elusive.

Results

In this study, we collected and analyzed methylation data from 785 invasive BRCA and 98 normal breast tissue samples from The Cancer Genome Atlas (TCGA) database. Consensus classification analysis revealed that ER-positive BRCA samples were constitutive of two distinct methylation subgroups; with the hypomethylated subgroup showing good survival probability. This finding was further supported by another cohort of ER-positive BRCA containing 30 subjects. Additionally, we identified 977 hypomethylated CpG loci showing significant associations with good survival probability in ER-positive BRCA. Genes with these loci were enriched in cancer-related pathways (e.g., Wnt signaling pathway). Among them, the upregulated 47 genes were also in line with good survival probability of ER-positive BRCA, while they showed significantly negative correlations between their expression and methylation level of certain hypomethylated loci. Functional assay in numerous literatures provided further evidences supporting that some of the loci have close links with the modulation of tumor-suppressive mechanisms via regulation gene transcription (e.g., SFRP1 and WIF1).

Conclusions

Our study identified a hypomethylated ER-positive BRCA subtype. Notably, this subgroup presented the best survival probability compared with the hypermethylated ER-positive and hypomethylated ER-negative BRCA subtypes. Specifically, we found that certain upregulated genes (e.g., SFRP1 and WIF1) have great potential to suppress the progression of ER-positive BRCA, concurrently exist negative correlations between their expression and methylation of corresponding hypomethylated CpG loci. Therefore, our study indicates that different epigenetic mechanisms likely exist in ER-positive BRCA and provides novel clinical biomarkers specific to ER-positive BRCA diagnosis and therapy.

ZMYND10, an epigenetically regulated tumor suppressor, exerts tumor-suppressive functions via miR145-5p/NEDD9 axis in breast cancer

Background

Recent studies suggested that ZMYND10 is a potential tumor suppressor gene in multiple tumor types. However, the mechanism by which ZMYND10 inhibits breast cancer remains unclear. Here, we investigated the role and mechanism of ZMYND10 in breast cancer inhibition.

Results

ZMYND10 was dramatically reduced in multiple breast cancer cell lines and tissues, which was associated with promoter hypermethylation. Ectopic expression of ZMYND10 in silenced breast cancer cells induced cell apoptosis while suppressed cell growth, cell migration and invasion in vitro, and xenograft tumor growth in vivo. Furthermore, molecular mechanism studies indicated that ZMYND10 enhances expression of miR145-5p, which suppresses the expression of NEDD9 protein through directly targeting the 3'-untranslated region of NEDD9 mRNA.

Conclusions

Results from this study show that ZMYND10 suppresses breast cancer tumorigenicity by inhibiting the miR145-5p/NEDD9 signaling pathway. This novel discovered signaling pathway may be a valid target for small molecules that might help to develop new therapies to better inhibit the breast cancer metastasis.

A Review of the Potential Role of Human Cytomegalovirus (HCMV) Infections in Breast Cancer Carcinogenesis and Abnormal Immunity

Previously recognized classical human onco-viruses can regulate complex neoplastic events, and are estimated to play a role during carcinogenesis in 15-20% of cancer cases. Although the DNA and gene products of several viruses have been found in breast tumors, none of the classical onco-viruses have definitely been linked to the initiation of breast cancer. However, recent evidence shows that human cytomegalovirus (HCMV) gene products are found in >90% of tumors and metastases of breast cancers, and their increased expression can be correlated to a more aggressive breast cancer phenotype. Supporting the active role of HCMV in breast cancer, a specific HCMV strain, HCMV-DB, was recently shown to exert oncogenic transformational activity in breast epithelial cells in vitro, and to give rise to fast-growing, triple-negative breast tumors when injected into immune deficient mice. The same observation holds true for clinical studies implying increased HCMV protein expression in triple negative breast cancer biopsies. In addition to functionally being able to hijack tumor-promoting cellular events, HCMV is known to exhibit a wide range of immunosuppressive effects, which can have radical impact on the tumor microenvironment. HCMV infected cells can avoid recognition and elimination by the immune system by orchestrating polarization of immunosuppressive type II macrophages, preventing antigen presentation, by expressing T cell inhibitory molecules, and possibly, by the induction of regulatory T (Treg) cell responses. These actions would be especially deleterious for the antigenic activation and proliferation of tumor specific CD8⁺ cytotoxic T lymphocytes (CTLs), whose effector functions have recently been targeted by successful, experimental immunotherapy protocols. The recognition of alternative causes and drivers of breast cancer is a pivotal research topic for the development of diagnostics and novel, effective preventive and therapeutic strategies targeting both tumor cells and their microenvironments.

Targeting DNA methylation for treating triple-negative breast cancer

Triple-negative breast cancer (TNBC) accounts for 15-20% of all invasive breast cancers and tends to have aggressive histological features and poor clinical outcomes. Unlike, estrogen receptor- or HER2-positive diseases, TNBC patients currently lack the US FDA-approved targeted therapies. DNA methylation is a critical mechanism of epigenetic modification. It is well known that aberrant DNA methylation contributes to the malignant transformation of cells by silencing critical tumor suppressor genes. DNA methyltransferase inhibitors reactivate silenced tumor suppressor genes and result in tumor growth arrest, with therapeutic effects observed in patients with hematologic malignancies. The antitumor effect of these DNA methyltransferase inhibitors has also been explored in solid tumors, especially in TNBC that currently lacks targeted therapies.

The Many Faces of Gene Regulation in Cancer: A Computational Oncogenomics Outlook

Cancer is a complex disease at many different levels. The molecular phenomenology of cancer is also quite rich. The mutational and genomic origins of cancer and their downstream effects on processes such as the reprogramming of the gene regulatory control and the molecular pathways depending on such control have been recognized as central to the characterization of the disease. More important though is the understanding of their causes, prognosis, and therapeutics. There is a multitude of factors associated with anomalous control of gene expression in cancer. Many of these factors are now amenable to be studied comprehensively by means of experiments based on diverse omic technologies. However, characterizing each dimension of the phenomenon individually has proven to fall short in presenting a clear picture of expression regulation as a whole. In this review article, we discuss some of the more relevant factors affecting gene expression control both, under normal conditions and in tumor settings. We describe the different omic approaches that we can use as well as the computational genomic analysis needed to track down these factors. Then we present theoretical and computational frameworks developed to integrate the amount of diverse information provided by such single-omic analyses. We contextualize this within a systems biology-based multi-omic regulation setting, aimed at better understanding the complex interplay of gene expression deregulation in cancer.

Artificial Light at Night of Different Spectral Compositions Differentially Affects Tumor Growth in Mice: Interaction With Melatonin and Epigenetic Pathways

Lighting technology is rapidly advancing toward shorter wavelength illuminations that offer energy-efficient properties. Along with this advantage, the increased use of such illuminations also poses some health challenges, particularly breast cancer progression. Here, we evaluated the effects of artificial light at night (ALAN) of 4 different spectral compositions (500-595 nm) at 350 Lux on melatonin suppression by measuring its urine metabolite 6-sulfatoxymelatonin, global DNA methylation, tumor growth, metastases formation, and urinary corticosterone levels in 4T1 breast cancer cell-inoculated female BALB/c mice. The results revealed an inverse dose-dependent relationship between wavelength and melatonin suppression. Short wavelength increased tumor growth, promoted lung metastases formation, and advanced DNA hypomethylation, while long wavelength lessened these effects. Melatonin treatment counteracted these effects and resulted in reduced cancer burden. The wavelength suppression threshold for melatonin-induced tumor growth was 500 nm. These results suggest that short wavelength increases cancer burden by inducing aberrant DNA methylation mediated by the suppression of melatonin. Additionally, melatonin suppression and global DNA methylation are suggested as promising biomarkers for early diagnosis and therapy of breast cancer. Finally, ALAN may manifest other physiological responses such as stress responses that may challenge the survival fitness of the animal under natural environments.

Diagnostic utility of epigenetics in breast cancer - A review

Epigenetic alterations are clearly involved in cancer initiation and progression as recent epigenetic studies of genomic DNA, histone modifications and micro-RNA alterations suggest that these are playing an important role in the incidence of breast cancer. Epigenetic information has recently gained the attention of researchers because epigenetic modification of the genome in breast cancer is still an evolving area for researchers. Several active compounds present in foods, poisons, drugs, and industrial chemicals may as a result of epigenetic mechanisms increase or decrease the risk of breast cancer. 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 addition to the use of epigenetic alterations as a means of screening, epigenetic alterations in a tumor or adjacent tissues or peripheral blood may also help clinicians in determining prognosis and treatment of breast cancer. As we understand specific epigenetic alterations contributing to breast tumorigenesis and prognosis, these discoveries will lead to significant advances for breast cancer treatment, like in therapeutics that target methylation and histone modifications in breast cancer and the newer versions of the drugs are likely to play an important role in future clinical treatment.

Regional methylome profiling reveals dynamic epigenetic heterogeneity and convergent hypomethylation of stem cell quiescence-associated genes in breast cancer following neoadjuvant chemotherapy

Background

Neoadjuvant chemotherapy (NAC) induces a pathological complete response (pCR) in ~ 30% of patients with breast cancer. However, aberrant DNA methylation alterations are frequent events during breast cancer progression and acquisition of chemoresistance. We aimed to characterize the inter- and intra-tumor methylation heterogeneity (MH) in breast cancer following NAC.

Methods

DNA methylation profiles of spatially separated regions of breast tumors before and after NAC treatment were investigated using high-density methylation microarray. Methylation levels of genes of interest were further examined using multiplexed MethyLight droplet digital PCR (ddPCR).

Results

We have discovered different levels of intra-tumor MH in breast cancer patients. Moreover, NAC dramatically altered the methylation profiles and such changes were highly heterogeneous between the patients. Despite the high inter-patient heterogeneity, we identified that stem cell quiescence-associated genes ALDH1L1, HOPX, WNT5A and SOX9 were convergently hypomethylated across all the samples after NAC treatment. Furthermore, by using MethyLight ddPCR, we verified that the methylation levels of these 4 genes were significantly lower in breast tumor samples after NAC than those before NAC.

Conclusions

Our study has revealed that NAC dramatically alters epigenetic heterogeneity in breast cancer and induces convergent hypomethylation of stem cell quiescence-associated genes, ALDH1L1, HOPX, WNT5A and SOX9, which can potentially be developed as therapeutic targets or biomarkers for chemoresistance.

Electronic supplementary material

The online version of this article (10.1186/s13578-019-0278-y) contains supplementary material, which is available to authorized users.

A sensitive photoelectrochemical methyltransferase activity assay based on a novel “Z-scheme” CdSe QD/afGQD heterojunction and multiple signal amplification strategies

Based on a “Z-scheme” CdSe QD/afGQD heterojunction and multiple signal amplification strategies, a sensitive photoelectrochemical methyltransferase activity assay was carried out.

Relationship Between DNA Methylation in Key Region and the Differential Expressions of Genes in Human Breast Tumor Tissue

Breast cancer has a high mortality rate for females. Aberrant DNA methylation plays a crucial role in the occurrence and progression of breast carcinoma. By comparing DNA methylation differences between tumor breast tissue and normal breast tissue, we calculate and analyze the distributions of the hyper- and hypomethylation sites in different function regions. Results indicate that enhancer regions are often hypomethylated in breast cancer. CpG islands (CGIs) are mainly hypermethylated, while the flanking CGI (shores and shelves) is more easily hypomethylated. The hypomethylation in gene body region is related to the upregulation of gene expression, and the hypomethylation of enhancer regions is closely associated with gene expression upregulation in breast cancer. Some key hypomethylation sites in enhancer regions and key hypermethylation sites in CGIs for regulating key genes are, respectively, found, such as oncogenes ESR1 and ERBB2 and tumor suppressor genes FBLN2, CEBPA, and FAT4. This suggests that the recognizing methylation status of these genes will be useful for the diagnosis of breast cancer.

The transcriptome of human mammary epithelial cells infected with the HCMV-DB strain displays oncogenic traits

Increasing evidence indicates that human cytomegalovirus (HCMV) populations under the influence of host environment, can either be stable or rapidly differentiating, leading to tissue compartment colonization. We isolated previously from a 30-years old pregnant woman, a clinical isolate of HCMV, that we refered to as the HCMV-DB strain (accession number KT959235). The HCMV-DB clinical isolate demonstrated its ability to infect primary macrophages and to upregulate the proto-oncogene Bcl-3. We observed in this study that the genome of HCMV-DB strain is close to the genomes of other primary clinical isolates including the Toledo and the JP strains with the later having been isolated from a glandular tissue, the prostate. Using a phylogenetic analysis to compare the genes involved in virus entry, we observed that the HCMV-DB strain is close to the HCMV strain Merlin, the prototype HCMV strain. HCMV-DB infects human mammary epithelial cells (HMECs) which in turn display a ER−/PR−/HER2− phenotype, commonly refered to as triple negative. The transcriptome of HCMV-DB-infected HMECs presents the characteristics of a pro-oncogenic cellular environment with upregulated expression of numerous oncogenes, enhanced activation of pro-survival genes, and upregulated markers of cell proliferation, stemcellness and epithelial mesenchymal transition (EMT) that was confirmed by enhanced cellular proliferation and tumorsphere formation in vitro. Taken together our data indicate that some clinical isolates could be well adapted to the mammary tissue environment, as it is the case for the HCMV-DB strain. This could influence the viral fitness, ultimately leading to breast cancer development.

Gene-specific methylation profiles in BRCA-mutation positive and BRCA-mutation negative male breast cancers

Male breast cancer (MBC) is a rare disease. Due to its rarity, MBC research and clinical approach are mostly based upon data derived from female breast cancer (FBC). Increasing evidence indicate that on molecular level MBC may be an heterogeneous disease different from FBC. In order to investigate whether epigenetic signatures could define molecular subgroups of MBCs, we performed promoter methylation analysis of genes involved in signal transduction and hormone signalling in BRCA1/2 mutation-positive and -negative MBCs. We examined 69 MBCs, paired blood samples, and 15 normal tissues for promoter methylation of hTERT, ESR1, RASSF1, AR, MYC and WNT1 genes. MBCs showed higher gene promoter methylation levels compared to paired blood and normal breast samples. Significantly higher RASSF1 methylation levels were observed in association with BRCA1/2 mutations, HER2 expression and high tumor grade. Significantly higher AR methylation levels were observed in BRCA1/2 wild-type cases and higher WNT1 methylation levels in PR negative cases. Overall, our results indicate that alterations in gene methylation profiles are common in MBC and that methylation pattern of tumor-associated genes may allow for the identification of MBC molecular subgroups, that could have implications in clinical management of MBC patients.

Mediator complex (MED) 7: a biomarker associated with good prognosis in invasive breast cancer, especially ER+ luminal subtypes

Background

Mediator complex (MED) proteins have a key role in transcriptional regulation, some interacting with the oestrogen receptor (ER). Interrogation of the METABRIC cohort suggested that MED7 may regulate lymphovascular invasion (LVI). Thus MED7 expression was assessed in large breast cancer (BC) cohorts to determine clinicopathological significance.

Methods

MED7 gene expression was investigated in the METABRIC cohort (n = 1980) and externally validated using bc-GenExMiner v4.0. Immunohistochemical expression was assessed in the Nottingham primary BC series (n = 1280). Associations with clinicopathological variables and patient outcome were evaluated.

Results

High MED7 mRNA and protein expression was associated with good prognostic factors: low grade, smaller tumour size, good NPI, positive hormone receptor status (p < 0.001), and negative LVI (p = 0.04) status. Higher MED7 protein expression was associated with improved BC-specific survival within the whole cohort and ER+/luminal subgroup. Pooled MED7 gene expression data in the external validation cohort confirmed association with better survival, corroborating with the protein expression. On multivariate analysis, MED7 protein was independently predictive of longer BC-specific survival in the whole cohort and Luminal A subtype (p < 0.001).

Conclusions

MED7 is an important prognostic marker in BC, particularly in ER+luminal subtypes, associated with improved survival and warrants future functional analysis.

Epigenome-wide SRC-1-Mediated Gene Silencing Represses Cellular Differentiation in Advanced Breast Cancer

Purpose: Despite the clinical utility of endocrine therapies for estrogen receptor-positive (ER) breast cancer, up to 40% of patients eventually develop resistance, leading to disease progression. The molecular determinants that drive this adaptation to treatment remain poorly understood. Methylome aberrations drive cancer growth yet the functional role and mechanism of these epimutations in drug resistance are poorly elucidated.Experimental Design: Genome-wide multi-omics sequencing approach identified a differentially methylated hub of prodifferentiation genes in endocrine resistant breast cancer patients and cell models. Clinical relevance of the functionally validated methyl-targets was assessed in a cohort of endocrine-treated human breast cancers and patient-derived ex vivo metastatic tumors.Results: Enhanced global hypermethylation was observed in endocrine treatment resistant cells and patient metastasis relative to sensitive parent cells and matched primary breast tumor, respectively. Using paired methylation and transcriptional profiles, we found that SRC-1-dependent alterations in endocrine resistance lead to aberrant hypermethylation that resulted in reduced expression of a set of differentiation genes. Analysis of ER-positive endocrine-treated human breast tumors (n = 669) demonstrated that low expression of this prodifferentiation gene set significantly associated with poor clinical outcome (P = 0.00009). We demonstrate that the reactivation of these genes in vitro and ex vivo reverses the aggressive phenotype.Conclusions: Our work demonstrates that SRC-1-dependent epigenetic remodeling is a 'high level' regulator of the poorly differentiated state in ER-positive breast cancer. Collectively these data revealed an epigenetic reprograming pathway, whereby concerted differential DNA methylation is potentiated by SRC-1 in the endocrine resistant setting. Clin Cancer Res; 24(15); 3692-703. ©2018 AACR.

BRCA1 Promoter Methylation and Expression - Associations with ER+, PR+ and HER2+ Subtypes of Breast Carcinoma

Introduction: Considering the increasing trend in incidence rates, morbidity and mortality of breast cancer, there is an urgent need to identify and validate new biomarkers for early detection and better management. The purpose of the study was to investigate BRCA1 protein expression and promoter methylation of the BRCA1 gene and their association with molecular subtypes based on estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) positivity. Materials and Methods: A total of 114 breast cancer tissue biopsies were collected for methylation specific PCR (MSP) and immunohistochemical (IHC) analysis. Results: Seven tissue microarrays were constructed. BRCA1 protein expression was reduced in 55/114 (48.2%) and in the majority of ER-negative tumors (73.3%) (p<0.001). Similarly BRCA1 expression was reduced in the majority of PR-negative tumors (69.2%) but without statistical significance (p value=0.083). BRCA1 methylation was positive in 59.6% cases. A subset regarding ER+, PR+ and HER2+ was identified which consisted of 31.6% in which an inverse relationship between BRCA1 methylation and protein expression was noted. Conclusion: Reduced expression was associated with ER and PR negative status which is linked with a poor prognosis. BRCA1 protein expression might thus be used as a prognostic indicator to predict treatment response to hormone therapy.

Landscape of genome-wide age-related DNA methylation in breast tissue

Despite known age-related DNA methylation (aDNAm) changes in breast tumors, little is known about aDNAm in normal breast tissues. Breast tissues from a cross-sectional study of 121 cancer-free women, were assayed for genome-wide DNA methylation. mRNA expression was assayed by microarray technology. Analysis of covariance was used to identify aDNAm’s. Altered methylation was correlated with expression of the corresponding gene and with DNA methyltransferase protein DNMT3A, assayed by immunohistochemistry. Publically-available TCGA-BRCA data were used for replication. 1,214 aDNAm’s were identified; 97% with increased methylation, and all on autosomes. Sites with increased methylation were predominantly in CpG lslands and non-enhancers. aDNAm’s with decreased methylation were generally located in intergenic regions, non-CpG Islands, and enhancers. Of the aDNAm’s identified, 650 are known to be involved in cancer, including ESR1 and beta-estradiol responsive genes. Expression of DNMT3A was positively associated with age. Two aDNAm’s showed borderline significant associations with DNMT3A expression; KRR1 (OR 6.57, 95% CI: 2.51–17.23) and DHRS12 (OR 6.08, 95% CI: 2.33–15.86). A subset of aDNAm’s co-localized within vulnerable regions for somatic mutations in cancers including breast cancer. Expression of C19orf48 was inversely and significantly correlated with its methylation level. In the TCGA dataset, 84% and 64% of the previously identified aDNAm’s were correlated with age in both normal-adjacent and tumor breast tissues, with differential associations by histological subtype. Given the similarity of findings in the breast tissues of healthy women and breast tumors, aDNAm’s may be one pathway for increased breast cancer risk with age.

Nightshift work, chronotype, and genome-wide DNA methylation in blood

Molecular mechanisms underlying the negative health effects of shift work are poorly understood, which remains a barrier to developing intervention strategies to protect the long-term health of shift workers. We evaluated genome-wide differences in DNA methylation (measured in blood) between 111 actively employed female nightshift and 86 actively employed female dayshift workers from the Seattle metropolitan area. We also explored the effect of chronotype (i.e., measure of preference for activity earlier or later in the day) on DNA methylation among 110 of the female nightshift workers and an additional group of 131 male nightshift workers. Methylation data were generated using the Illumina Infinium HumanMethylation450 BeadChip (450K) Array. After applying the latest methylation data processing methods, we compared methylation levels at 361,210 CpG loci between the groups using linear regression models adjusted for potential confounders and applied the false-discovery rate (FDR) ≤ 0.05 to account for multiple comparisons. No statistically significant associations at the genome-wide level were observed with shift work or chronotype, though based on raw P values and absolute effect sizes, there were suggestive associations in genes that have been previously linked with cancer (e.g., BACH2, JRK, RPS6KA2) and type-2 diabetes (e.g., KCNQ1). Given that our study was underpowered to detect moderate effects, examining these suggestive results in well-powered independent studies or in pooled data sets may improve our understanding of the pathways underlying the negative health effects of shift work and the influence of personal factors such as chronotype. Such an approach may help identify potential interventions that can be used to protect the long-term health of shift workers.

Label-Free Sensitive Detection of DNA Methyltransferase by Target-Induced Hyperbranched Amplification with Zero Background Signal

DNA methyltransferases (MTases) may specifically recognize the short palindromic sequences and transfer a methyl group from S-adenosyl-l-methionine to target cytosine/adenine. The aberrant DNA methylation is linked to the abnormal DNA MTase activity, and some DNA MTases have become promising targets of anticancer/antimicrobial drugs. However, the reported DNA MTase assays often involve laborious operation, expensive instruments, and radio-labeled substrates. Here, we develop a simple and label-free fluorescent method to sensitively detect DNA adenine methyltransferase (Dam) on the basis of terminal deoxynucleotidyl transferase (TdT)-activated Endonuclease IV (Endo IV)-assisted hyperbranched amplification. We design a hairpin probe with a palindromic sequence in the stem as the substrate and a NH₂-modified 3' end for the prevention of nonspecific amplification. The substrate may be methylated by Dam and subsequently cleaved by DpnI, producing three single-stranded DNAs, two of which with 3'-OH termini may be amplified by hyperbranched amplification to generate a distinct fluorescence signal. Because high exactitude of TdT enables the amplification only in the presence of free 3'-OH termini and Endo IV only hydrolyzes the intact apurinic/apyrimidinic sites in double-stranded DNAs, zero background signal can be achieved. This method exhibits excellent selectivity and high sensitivity with a limit of detection of 0.003 U/mL for pure Dam and 9.61 × 10^-6 mg/mL for Dam in E. coli cells. Moreover, it can be used to screen the Dam inhibitors, holding great potentials in disease diagnosis and drug development.

miRNA-148a regulates the expression of the estrogen receptor through DNMT1-mediated DNA methylation in breast cancer cells

Breast cancer remains the most prevalent cancer among women worldwide. The expression of estrogen receptor-α (ER-α) is an important marker for prognosis. ER-α status may be positive or negative in breast cancer cells, although the cause of negative or positive status is not yet fully characterized. In the present study, the expression of ER-α and miRNA-148a was assessed in two breast cancer cell lines, HCC1937 and MCF7. An association between ER-α and miRNA-148a expression was identified. It was then demonstrated that DNA methyltransferase 1 (DNMT1) is a target of miRNA-148a, which may suppress the expression of ER-α via DNA methylation. Finally, an miRNA-148a mimic or inhibitor was transfected into MCF7 cells; the miRNA-148a mimic increased ER-α expression whereas the miRNA-148a inhibitor decreased ER-α expression. In conclusion, it was identified that miRNA-148a regulates ER-α expression through DNMT1-mediated DNA methylation in breast cancer cells. This may represent a potential miRNA-based strategy to modulate the expression of ER-α and provide a novel perspective for investigating the role of miRNAs in treating breast cancer.

Potential therapeutic targets of triple-negative breast cancer based on its intrinsic subtype

Triple-negative breast cancer (TNBC) is an aggressive subgroup of human breast cancer, which is characterized as estrogen receptor (ER) negative, progesterone receptor (PR) negative, and human epidermal growth factor receptor 2 (HER2) negative. TNBC is the most difficult breast cancer subgroup to treat, due to its unresponsiveness to current clinical targeted therapies, high rate of recurrence, and poor prognosis. Thus, there is an urgent medical need to identify therapeutic targets and develop more effective stratified medicine for the treatment of TNBC. Here we review the potential therapeutic targets for TNBC based on its intrinsic subtype. We also review the aberrant activated signals found in different subgroups of TNBC, including androgen receptor (AR) and PI3K/AKT/mTOR, Notch, Wnt/β-catenin, Hedge-hog, and TGF-β signaling pathways, which play essential roles in multiple development stages of TNBC. The careful analysis of these signaling pathways and therapeutic targets would have significant impact on the drug development and clinical trials, leading to effective therapies for this deadly disease.