Towards understanding the breast cancer epigenome: a comparison of genome-wide DNA methylation and gene expression data

Methods in DNA methylation array dataset analysis: A review

Understanding the intricate relationships between gene expression levels and epigenetic modifications in a genome is crucial to comprehending the pathogenic mechanisms of many diseases. With the advancement of DNA Methylome Profiling techniques, the emphasis on identifying Differentially Methylated Regions (DMRs/DMGs) has become crucial for biomarker discovery, offering new insights into the etiology of illnesses. This review surveys the current state of computational tools/algorithms for the analysis of microarray-based DNA methylation profiling datasets, focusing on key concepts underlying the diagnostic/prognostic CpG site extraction. It addresses methodological frameworks, algorithms, and pipelines employed by various authors, serving as a roadmap to address challenges and understand changing trends in the methodologies for analyzing array-based DNA methylation profiling datasets derived from diseased genomes. Additionally, it highlights the importance of integrating gene expression and methylation datasets for accurate biomarker identification, explores prognostic prediction models, and discusses molecular subtyping for disease classification. The review also emphasizes the contributions of machine learning, neural networks, and data mining to enhance diagnostic workflow development, thereby improving accuracy, precision, and robustness.

Transcriptomics and epigenetic data integration learning module on Google Cloud

Multi-omics (genomics, transcriptomics, epigenomics, proteomics, metabolomics, etc.) research approaches are vital for understanding the hierarchical complexity of human biology and have proven to be extremely valuable in cancer research and precision medicine. Emerging scientific advances in recent years have made high-throughput genome-wide sequencing a central focus in molecular research by allowing for the collective analysis of various kinds of molecular biological data from different types of specimens in a single tissue or even at the level of a single cell. Additionally, with the help of improved computational resources and data mining, researchers are able to integrate data from different multi-omics regimes to identify new prognostic, diagnostic, or predictive biomarkers, uncover novel therapeutic targets, and develop more personalized treatment protocols for patients. For the research community to parse the scientifically and clinically meaningful information out of all the biological data being generated each day more efficiently with less wasted resources, being familiar with and comfortable using advanced analytical tools, such as Google Cloud Platform becomes imperative. This project is an interdisciplinary, cross-organizational effort to provide a guided learning module for integrating transcriptomics and epigenetics data analysis protocols into a comprehensive analysis pipeline for users to implement in their own work, utilizing the cloud computing infrastructure on Google Cloud. The learning module consists of three submodules that guide the user through tutorial examples that illustrate the analysis of RNA-sequence and Reduced-Representation Bisulfite Sequencing data. The examples are in the form of breast cancer case studies, and the data sets were procured from the public repository Gene Expression Omnibus. The first submodule is devoted to transcriptomics analysis with the RNA sequencing data, the second submodule focuses on epigenetics analysis using the DNA methylation data, and the third submodule integrates the two methods for a deeper biological understanding. The modules begin with data collection and preprocessing, with further downstream analysis performed in a Vertex AI Jupyter notebook instance with an R kernel. Analysis results are returned to Google Cloud buckets for storage and visualization, removing the computational strain from local resources. The final product is a start-to-finish tutorial for the researchers with limited experience in multi-omics to integrate transcriptomics and epigenetics data analysis into a comprehensive pipeline to perform their own biological research.This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [16] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.

HIGHLIGHTS

Translating genetic findings to epigenetics: identifying the mechanisms associated with aging after high-radiation exposure on earth and in space

Purpose

Exposure to radiation is a health concern within and beyond the Earth's atmosphere for aircrew and astronauts in their respective austere environments. The biological effects of radiation exposure from a multiomics standpoint are relatively unexplored and stand to shed light on tailored monitoring and treatment for those in these career fields. To establish a reference variable for genetic damage, biological age seems to be closely associated with the effect of radiation. Following a genetic-based study, this study explores the epigenetic landscape of radiation exposure along with its associative effects on aging processes.

Methods

We imported the results of the genetics-based study that was a secondary analysis of five publicly available datasets (noted as Data1). The overlap of these genes with new data involving methylation data from two datasets (noted as Data2) following similar secondary analysis procedures is the basis of this study. We performed the standard statistical analysis on these datasets along with supervised and unsupervised learning to create preranked gene lists used for functional analysis in Ingenuity Pathway Analysis (IPA).

Results

There were 664 genes of interest from Data1 and 577 genes from Data2. There were 40 statistically significant methylation probes within 500 base pairs of the gene's transcription start site and 10 probes within 100 base pairs, which are discussed in depth. IPA yielded 21 significant pathways involving metabolism, cellular development, cell death, and diseases. Compared to gold standards for gestational age, we observed relatively low error and standard deviation using newly identified biomarkers.

Conclusion

We have identified 17 methylated genes that exhibited particular interest and potential in future studies. This study suggests that there are common trends in oxidative stress, cell development, and metabolism that indicate an association between aging processes and the effects of ionizing radiation exposure.

Mechanisms of immune modulation in the tumor microenvironment and implications for targeted therapy

The efficacy of cancer therapies is limited to a great extent by immunosuppressive mechanisms within the tumor microenvironment (TME). Numerous immune escape mechanisms have been identified. These include not only processes associated with tumor, immune or stromal cells, but also humoral, metabolic, genetic and epigenetic factors within the TME. The identification of immune escape mechanisms has enabled the development of small molecules, nanomedicines, immune checkpoint inhibitors, adoptive cell and epigenetic therapies that can reprogram the TME and shift the host immune response towards promoting an antitumor effect. These approaches have translated into series of breakthroughs in cancer therapies, some of which have already been implemented in clinical practice. In the present article the authors provide an overview of some of the most important mechanisms of immunosuppression within the TME and the implications for targeted therapies against different cancers.

Immuno-oncology trends: preclinical models, biomarkers, and clinical development

The landscape in immuno-oncology (I-O) has undergone profound changes since its early beginnings up through the rapid advances happening today. The current drug development pipeline consists of thousands of potential I-O therapies and therapy combinations, many of which are being evaluated in clinical trials. The efficient and successful development of these assets requires the investment in and utilization of appropriate tools and technologies that can facilitate the rapid transitions from preclinical evaluation through clinical development. These tools include (i) appropriate preclinical models, (ii) biomarkers of pharmacodynamic, predictive and monitoring utility, and (iii) evolving clinical trial designs that allow rapid and efficient evaluation during the development process. This article provides an overview of how novel discoveries and insights into each of these three areas have the potential to further address the clinical management needs for patients with cancer.

Curcumin from Turmeric Rhizome: A Potential Modulator of DNA Methylation Machinery in Breast Cancer Inhibition

One of the most systematically studied bioactive nutraceuticals for its benefits in the management of various diseases is the turmeric-derived compounds: curcumin. Turmeric obtained from the rhizome of a perennial herb Curcuma longa L. is a condiment commonly used in our diet. Curcumin is well known for its potential role in inhibiting cancer by targeting epigenetic machinery, with DNA methylation at the forefront. The dynamic DNA methylation processes serve as an adaptive mechanism to a wide variety of environmental factors, including diet. Every healthy tissue has a precise DNA methylation pattern that changes during cancer development, forming a cancer-specific design. Hypermethylation of tumor suppressor genes, global DNA demethylation, and promoter hypomethylation of oncogenes and prometastatic genes are hallmarks of nearly all types of cancer, including breast cancer. Curcumin has been shown to modulate epigenetic events that are dysregulated in cancer cells and possess the potential to prevent cancer or enhance the effects of conventional anti-cancer therapy. Although mechanisms underlying curcumin-mediated changes in the epigenome remain to be fully elucidated, the mode of action targeting both hypermethylated and hypomethylated genes in cancer is promising for cancer chemoprevention. This review provides a comprehensive discussion of potential epigenetic mechanisms of curcumin in reversing altered patterns of DNA methylation in breast cancer that is the most commonly diagnosed cancer and the leading cause of cancer death among females worldwide. Insight into the other bioactive components of turmeric rhizome as potential epigenetic modifiers has been indicated as well.

Meta-analysis of gene expression profiling reveals novel basal gene signatures in MCF-10A cells transformed with cadmium

Cadmium (Cd2+) is an environmental toxicant and a human carcinogen. Several studies show an association of Cd2+ exposure to the development of breast cancer. Previously, we have transformed the immortalized non-tumorigenic cell line MCF-10A with Cd2+ and have demonstrated that the transformed cells have anchorage independent growth. In a separate study, we showed that transformation of the immortalized urothelial cells with the environmental carcinogen arsenite (As3+) results in an increase in expression of genes associated with the basal subtype of bladder cancer. In this study, we determined if transformation of the MCF-10A cells with Cd2+ would have a similar effect on the expression of basal genes. The results of our study indicate that there is a decrease in expression of genes associated with keratinization and cornification and this gene signature includes the genes associated with the basal subtype of breast cancer. An analysis of human breast cancer databases indicates an increased expression of this gene signature is associated with a positive correlation to patient survival whereas a reduced expression/absence of this gene signature is associated with poor patient survival. Thus, our study suggests that transformation of the MCF-10A cells with Cd2+ produces a decreased basal gene expression profile that correlates to patient outcome.

The Influence of Physical Activity and Epigenomics On Cognitive Function and Brain Health in Breast Cancer

The risk of breast cancer increases with age, with the majority of women diagnosed with breast cancer being postmenopausal. It has been estimated that 25-75% of women with breast cancer experience changes in cognitive function (CF) related to disease and treatment, which compromises psychological well-being, decision making, ability to perform daily activities, and adherence to cancer therapy. Unfortunately, the mechanisms that underlie neurocognitive changes in women with breast cancer remain poorly understood, which in turn limits the development of effective treatments and prevention strategies. Exercise has great potential as a non-pharmaceutical intervention to mitigate the decline in CF in women with breast cancer. Evidence suggests that DNA methylation, an epigenetic mechanism for gene regulation, impacts CF and brain health (BH), that exercise influences DNA methylation, and that exercise impacts CF and BH. Although investigating DNA methylation has the potential to uncover the biologic foundations for understanding neurocognitive changes within the context of breast cancer and its treatment as well as the ability to understand how exercise mitigates these changes, there is a dearth of research on this topic. The purpose of this review article is to compile the research in these areas and to recommend potential areas of opportunity for investigation.

MicroRNAs and Epigenetics Strategies to Reverse Breast Cancer

Breast cancer is a sporadic disease with genetic and epigenetic components. Genomic instability in breast cancer leads to mutations, copy number variations, and genetic rearrangements, while epigenetic remodeling involves alteration by DNA methylation, histone modification and microRNAs (miRNAs) of gene expression profiles. The accrued scientific findings strongly suggest epigenetic dysregulation in breast cancer pathogenesis though genomic instability is central to breast cancer hallmarks. Being reversible and plastic, epigenetic processes appear more amenable toward therapeutic intervention than the more unidirectional genetic alterations. In this review, we discuss the epigenetic reprogramming associated with breast cancer such as shuffling of DNA methylation, histone acetylation, histone methylation, and miRNAs expression profiles. As part of this, we illustrate how epigenetic instability orchestrates the attainment of cancer hallmarks which stimulate the neoplastic transformation-tumorigenesis-malignancy cascades. As reversibility of epigenetic controls is a promising feature to optimize for devising novel therapeutic approaches, we also focus on the strategies for restoring the epistate that favor improved disease outcome and therapeutic intervention.

Development of curcumin-loaded gemini surfactant nanoparticles: Synthesis, characterization and evaluation of anticancer activity against human breast cancer cell lines

BACKGROUND

Curcumin, the polyphenolic constituent of turmeric, has been recognized as an effective anticancer agent in the treatment of breast cancer. However, the poor bioavailability of curcumin triggers finding of new approaches for elevating its therapeutic efficiency.

PURPOSE

We aimed to use gemini surfactant nanocarriers for curcumin in order to overcome its limitations.

STUDY DESIGN

We investigated the in vitro characterization of gemini surfactant-curcumin (Gemini-Cur) and examined its antiproliferative & apoptotic activities on breast cancer cell lines.

METHODS

Gemini-Cur polymersomes were synthesized through nanoprecipitation method and characterized by dynamic light scattering (DLS), transmission and scanning electron microscopies, HPLC and X-ray diffraction (XRD). The anticancer effect of Gemini-Cur nanoparticles was studied on three different breast cancer cell lines including MCF-7, SkBr-3 and MDA-MB-231 through uptake kinetics, viability & cytotoxicity recordings and apoptotic assays. Furthermore, qRT-PCR was performed to evaluate the expression of apoptotic genes including p16INK4a, p14ARF, Bax and Bcl-2.

RESULTS

According to physicochemical analysis, the average particle size, zeta potential value and drug entrapment efficiency for Gemini-Cur compound were recorded as 161 ± 6.2 nm, +5.32 mV and 89.13% ± 0.93, respectively. XRD analysis also confirmed the incorporation of curcumin in gemini surfactant micelles. Regarding the enhanced cellular uptake of sphere shaped Gemini-Cur, our data showed that this nano compound suppresses cancer cell proliferation via induction of apoptosis. Moreover, qRT-PCR analysis revealed that Gemini-Cur could effectively upregulate the expression of p16INK4a, p14ARF and Bax, while significantly decreasing the Bcl-2 expression in these breast cancer cells.

CONCLUSION

Our data demonstrates the great potential of gemini surfactants for efficient delivery of curcumin and subsequently, the improvement of its anticancer effect. Therefore, it is sagacious to support the idea that Gemini-Cur nano compound might have the potential to be considered as an anticancer agent.

MVisAGe Identifies Concordant and Discordant Genomic Alterations of Driver Genes in Squamous Tumors

Integrated analyses of multiple genomic datatypes are now common in cancer profiling studies. Such data present opportunities for numerous computational experiments, yet analytic pipelines are limited. Tools such as the cBioPortal and Regulome Explorer, although useful, are not easy to access programmatically or to implement locally. Here, we introduce the MVisAGe R package, which allows users to quantify gene-level associations between two genomic datatypes to investigate the effect of genomic alterations (e.g., DNA copy number changes on gene expression). Visualizing Pearson/Spearman correlation coefficients according to the genomic positions of the underlying genes provides a powerful yet novel tool for conducting exploratory analyses. We demonstrate its utility by analyzing three publicly available cancer datasets. Our approach highlights canonical oncogenes in chr11q13 that displayed the strongest associations between expression and copy number, including CCND1 and CTTN, genes not identified by copy number analysis in the primary reports. We demonstrate highly concordant usage of shared oncogenes on chr3q, yet strikingly diverse oncogene usage on chr11q as a function of HPV infection status. Regions of chr19 that display remarkable associations between methylation and gene expression were identified, as were previously unreported miRNA-gene expression associations that may contribute to the epithelial-to-mesenchymal transition.Significance: This study presents an important bioinformatics tool that will enable integrated analyses of multiple genomic datatypes. Cancer Res; 78(12); 3375-85. ©2018 AACR.

Analysis of bladder cancer tumor CpG methylation and gene expression within The Cancer Genome Atlas identifies GRIA1 as a prognostic biomarker for basal-like bladder cancer

Increased methylation levels at cytosines proximal to guanines (CpG) in the promoter regions of tumor suppressor genes have been reported to play an important role in the development and progression of bladder cancer. In this study, we conducted a genome-wide analysis using data from The Cancer Genome Atlas to better characterize CpG methylation and mRNA expression patterns in urothelial carcinomas and to identify new epigenetic biomarkers of survival. Across 408 tumors, we identified 223 genes that displayed significant relationships between CpG methylation and mRNA expression levels. Hypermethylation within 200 base pairs upstream of the transcription start site and hypomethylation within the 3' untranslated region and body region were associated with gene silencing. These 223 genes were functionally enriched for their role in glutamate receptor signaling and among them was a novel, tumor-stage-independent epigenetic biomarker of overall mortality, GRIA1. GRIA1 hypermethylation and elevated mRNA expression levels were associated with significantly worse survival outcomes in patients with basal-like urothelial carcinomas. Furthermore, 70 genes associated with glutamate receptor signaling were differentially expressed between basal (n = 203 tumors) and luminal (n = 205 tumors) subtypes of bladder cancer, including genes involved in glutamate receptor-mediated activation of the calmodulin, PI3K/Akt, and EGFR signaling pathways. The majority of genes displayed increased expression levels in basal-like subtypes. This research highlights glutamate receptors as targets for investigation in the development and pharmacological treatment of urothelial cancer.

Curcumin: the spicy modulator of breast carcinogenesis

Worldwide breast cancer is the most common cancer in women. For many years clinicians and the researchers are examining and exploring various therapeutic modalities for breast cancer. Yet the disease has remained unconquered and the quest for cure is still going on. Present-day strategy of breast cancer therapy and prevention is either combination of a number of drugs or a drug that modulates multiple targets. In this regard natural products are now becoming significant options. Curcumin exemplifies a promising natural anticancer agent for this purpose. This review primarily underscores the modulatory effect of curcumin on the cancer hallmarks. The focus is its anticancer effect in the complex pathways of breast carcinogenesis. Curcumin modulates breast carcinogenesis through its effect on cell cycle and proliferation, apoptosis, senescence, cancer spread and angiogenesis. Largely the NFkB, PI3K/Akt/mTOR, MAPK and JAK/STAT are the key signaling pathways involved. The review also highlights the curcumin mediated modulation of tumor microenvironment, cancer immunity, breast cancer stem cells and cancer related miRNAs. Using curcumin as a therapeutic and preventive agent in breast cancer is perplexed by its diverse biological activity, much of which remains inexplicable. The information reviewed here should point toward potential scope of future curcumin research in breast cancer.

The Genomic Impact of DNA CpG Methylation on Gene Expression; Relationships in Prostate Cancer

The process of DNA CpG methylation has been extensively investigated for over 50 years and revealed associations between changing methylation status of CpG islands and gene expression. As a result, DNA CpG methylation is implicated in the control of gene expression in developmental and homeostasis processes, as well as being a cancer-driver mechanism. The development of genome-wide technologies and sophisticated statistical analytical approaches has ushered in an era of widespread analyses, for example in the cancer arena, of the relationships between altered DNA CpG methylation, gene expression, and tumor status. The remarkable increase in the volume of such genomic data, for example, through investigators from the Cancer Genome Atlas (TCGA), has allowed dissection of the relationships between DNA CpG methylation density and distribution, gene expression, and tumor outcome. In this manner, it is now possible to test that the genome-wide correlations are measurable between changes in DNA CpG methylation and gene expression. Perhaps surprisingly is that these associations can only be detected for hundreds, but not thousands, of genes, and the direction of the correlations are both positive and negative. This, perhaps, suggests that CpG methylation events in cancer systems can act as disease drivers but the effects are possibly more restricted than suspected. Additionally, the positive and negative correlations suggest direct and indirect events and an incomplete understanding. Within the prostate cancer TCGA cohort, we examined the relationships between expression of genes that control DNA methylation, known targets of DNA methylation and tumor status. This revealed that genes that control the synthesis of S-adenosyl-l-methionine (SAM) associate with altered expression of DNA methylation targets in a subset of aggressive tumors.