Noncoding somatic and inherited single-nucleotide variants converge to promote ESR1 expression in breast cancer

Enhancer regulatory networks globally connect non-coding breast cancer loci to cancer genes

BACKGROUND

Genetic studies have associated thousands of enhancers with breast cancer (BC). However, the vast majority have not been functionally characterized. Thus, it remains unclear how BC-associated enhancers contribute to cancer.

RESULTS

Here, we perform single-cell CRISPRi screens of 3513 regulatory elements associated with breast cancer to measure the impact of these regions on transcriptional phenotypes. Analysis of > 500,000 single-cell transcriptomes in two breast cancer cell lines shows that perturbation of BC-associated enhancers disrupts breast cancer gene programs. We observe BC-associated enhancers that directly or indirectly regulate the expression of cancer genes. We also find one-to-multiple and multiple-to-one network motifs where enhancers indirectly regulate cancer genes. Notably, multiple BC-associated enhancers indirectly regulate TP53. Comparative studies illustrate subtype specific functions between enhancers in ER + and ER - cells. Finally, we develop the pySpade package to facilitate analysis of single-cell enhancer screens.

CONCLUSIONS

Overall, we demonstrate that enhancers form regulatory networks that link cancer genes in the genome, providing a more comprehensive understanding of the contribution of enhancers to breast cancer development.

HiChIP-Based Epigenomic Footprinting Identifies a Promoter Variant of UXS1 That Confers Genetic Susceptibility to Gastroesophageal Cancer

Genome-wide association studies (GWAS) have identified more than a hundred single nucleotide variants (SNV) associated with the risk of gastroesophageal cancer (GEC). The majority of the identified SNVs map to noncoding regions of the genome. Uncovering the causal SNVs and genes they modulate could help improve GEC prevention and treatment. Herein, we used HiChIP against histone 3 lysine 27 acetylation (H3K27ac) to simultaneously annotate active promoters and enhancers, identify the interactions between them, and detect nucleosome-free regions (NFR) harboring potential causal SNVs in a single assay. The application of H3K27ac HiChIP in GEC relevant models identified 61 potential functional SNVs that reside in NFRs and interact with 49 genes at 17 loci. The approach led to a 67% reduction in the number of SNVs in linkage disequilibrium at these 17 loci, and at 7 loci, a single putative causal SNV was identified. One SNV, rs147518036, located within the promoter of the UDP-glucuronate decarboxylase 1 (UXS1) gene, seemed to underlie the GEC risk association captured by the rs75460256 index SNV. The rs147518036 SNV creates a GABPA DNA recognition motif, resulting in increased promoter activity, and CRISPR-mediated inhibition of the UXS1 promoter reduced the viability of the GEC cells. These findings provide a framework that simplifies the identification of potentially functional regulatory SNVs and target genes underlying risk-associated loci. In addition, the study implicates increased expression of the enzyme UXS1 and activation of its metabolic pathway as a predisposition to gastric cancer, which highlights potential therapeutic avenues to treat this disease. Significance: Epigenomic footprinting using a histone posttranslational modification targeted 3D genomics methodology elucidates functional noncoding sequence variants and their target genes at cancer risk loci.

Hidden secrets of the cancer genome: unlocking the impact of non-coding mutations in gene regulatory elements

Discoveries in the field of genomics have revealed that non-coding genomic regions are not merely "junk DNA", but rather comprise critical elements involved in gene expression. These gene regulatory elements (GREs) include enhancers, insulators, silencers, and gene promoters. Notably, new evidence shows how mutations within these regions substantially influence gene expression programs, especially in the context of cancer. Advances in high-throughput sequencing technologies have accelerated the identification of somatic and germline single nucleotide mutations in non-coding genomic regions. This review provides an overview of somatic and germline non-coding single nucleotide alterations affecting transcription factor binding sites in GREs, specifically involved in cancer biology. It also summarizes the technologies available for exploring GREs and the challenges associated with studying and characterizing non-coding single nucleotide mutations. Understanding the role of GRE alterations in cancer is essential for improving diagnostic and prognostic capabilities in the precision medicine era, leading to enhanced patient-centered clinical outcomes.

A transcriptional enhancer regulates cardiac maturation

Cardiomyocyte maturation is crucial for generating adult cardiomyocytes and the application of human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs). However, regulation at the cis-regulatory element level and its role in heart disease remain unclear. Alpha-actinin 2 (ACTN2) levels increase during CM maturation. In this study, we investigated a clinically relevant, conserved ACTN2 enhancer's effects on CM maturation using hPSC and mouse models. Heterozygous ACTN2 enhancer deletion led to abnormal CM morphology, reduced function and mitochondrial respiration. Transcriptomic analyses in vitro and in vivo showed disrupted CM maturation and upregulated anabolic mammalian target for rapamycin (mTOR) signaling, promoting senescence and hindering maturation. As confirmation, ACTN2 enhancer deletion induced heat shock protein 90A expression, a chaperone mediating mTOR activation. Conversely, targeting the ACTN2 enhancer via enhancer CRISPR activation (enCRISPRa) promoted hPSC-CM maturation. Our studies reveal the transcriptional enhancer's role in cardiac maturation and disease, offering insights into potentially fine-tuning gene expression to modulate cardiomyocyte physiology.

Integrated variant allele frequency analysis pipeline and R package: easyVAF

Somatic sequence variants are associated with cancer diagnosis, prognostic stratification, and treatment response. Variant allele frequency (VAF), the percentage of sequence reads with a specific DNA variant over the read depth at that locus, has been used as a metric to quantify mutation rates in these applications. VAF has the potential for feature detection by reflecting changes in tumor clonal composition across treatments or time points. Although there are several packages, including Genome Analysis Toolkit and VarScan, designed for variant calling and rare mutation identification, there is no readily available package for comparing VAFs among and between groups to identify loci of interest. To this end, we have developed the R package easyVAF, which includes parametric and nonparametric tests to compare VAFs among multiple groups. It is accompanied by an interactive R Shiny app. With easyVAF, the investigator has the option between three statistical tests to maximize power while maintaining an acceptable type I error rate. This paper presents our proposed pipeline for VAF analysis, from quality checking to group comparison. We evaluate our method in a wide range of simulated scenarios and show that choosing the appropriate test to limit the type I error rate is critical. For situations where data is sparse, we recommend comparing VAFs with the beta-binomial likelihood ratio test over Fisher's exact test and Pearson's χ2 test.

Enhancer regulatory networks globally connect non-coding breast cancer loci to cancer genes

Genetic studies have associated thousands of enhancers with breast cancer. However, the vast majority have not been functionally characterized. Thus, it remains unclear how variant-associated enhancers contribute to cancer. Here, we perform single-cell CRISPRi screens of 3,512 regulatory elements associated with breast cancer to measure the impact of these regions on transcriptional phenotypes. Analysis of >500,000 single-cell transcriptomes in two breast cancer cell lines shows that perturbation of variant-associated enhancers disrupts breast cancer gene programs. We observe variant-associated enhancers that directly or indirectly regulate the expression of cancer genes. We also find one-to-multiple and multiple-to-one network motifs where enhancers indirectly regulate cancer genes. Notably, multiple variant-associated enhancers indirectly regulate TP53. Comparative studies illustrate sub-type specific functions between enhancers in ER+ and ER- cells. Finally, we developed the pySpade package to facilitate analysis of single-cell enhancer screens. Overall, we demonstrate that enhancers form regulatory networks that link cancer genes in the genome, providing a more comprehensive understanding of the contribution of enhancers to breast cancer development.

Recapitulation of patient-specific 3D chromatin conformation using machine learning

Regulatory networks containing enhancer-gene edges define cellular states. Multiple efforts have revealed these networks for reference tissues and cell lines by integrating multi-omics data. However, the methods developed cannot be applied for large patient cohorts due to the infeasibility of chromatin immunoprecipitation sequencing (ChIP-seq) for limited biopsy material. We trained machine-learning models using chromatin interaction analysis with paired-end tag sequencing (ChIA-PET) and high-throughput chromosome conformation capture combined with chromatin immunoprecipitation (HiChIP) data that can predict connections using only assay for transposase-accessible chromatin using sequencing (ATAC-seq) and RNA-seq data as input, which can be generated from biopsies. Our method overcomes limitations of correlation-based approaches that cannot distinguish between distinct target genes of given enhancers or between active vs. poised states in different samples, a hallmark of network rewiring in cancer. Application of our model on 371 samples across 22 cancer types revealed 1,780 enhancer-gene connections for 602 cancer genes. Using CRISPR interference (CRISPRi), we validated enhancers predicted to regulate ESR1 in estrogen receptor (ER)+ breast cancer and A1CF in liver hepatocellular carcinoma.

Dr.Nod: computational framework for discovery of regulatory non-coding drivers in tissue-matched distal regulatory elements

The discovery of cancer driver mutations is a fundamental goal in cancer research. While many cancer driver mutations have been discovered in the protein-coding genome, research into potential cancer drivers in the non-coding regions showed limited success so far. Here, we present a novel comprehensive framework Dr.Nod for detection of non-coding cis-regulatory candidate driver mutations that are associated with dysregulated gene expression using tissue-matched enhancer-gene annotations. Applying the framework to data from over 1500 tumours across eight tissues revealed a 4.4-fold enrichment of candidate driver mutations in regulatory regions of known cancer driver genes. An overarching conclusion that emerges is that the non-coding driver mutations contribute to cancer by significantly altering transcription factor binding sites, leading to upregulation of tissue-matched oncogenes and down-regulation of tumour-suppressor genes. Interestingly, more than half of the detected cancer-promoting non-coding regulatory driver mutations are over 20 kb distant from the cancer-associated genes they regulate. Our results show the importance of tissue-matched enhancer-gene maps, functional impact of mutations, and complex background mutagenesis model for the prediction of non-coding regulatory drivers. In conclusion, our study demonstrates that non-coding mutations in enhancers play a previously underappreciated role in cancer and dysregulation of clinically relevant target genes.

Association of the Estrogen Receptor 1 Polymorphisms rs2046210 and rs9383590 with the Risk, Age at Onset and Prognosis of Breast Cancer

Estrogen receptor α (ERα), encoded by the ESR1 gene, is a key prognostic and predictive biomarker firmly established in routine diagnostics and as a therapeutic target of breast cancer, and it has a central function in breast cancer biology. Genetic variants at 6q25.1, containing the ESR1 gene, were found to be associated with breast cancer susceptibility. The rs2046210 and rs9383590 single nucleotide variants (SNVs) are located in the same putative enhancer region upstream of ESR1 and were separately identified as candidate causal variants responsible for these associations. Here, both SNVs were genotyped in a hospital-based case-control study of 409 female breast cancer patients and 422 female controls of a Central European (Austrian) study population. We analyzed the association of both SNVs with the risk, age at onset, clinically and molecularly relevant characteristics and prognosis of breast cancer. We also assessed the concordances between both SNVs and the associations of each SNV conditional on the other SNV. The minor alleles of both SNVs were found to be non-significantly associated with an increased breast cancer risk. Significant associations were found in specific subpopulations, particularly in patients with an age younger than 55 years. The minor homozygotes of rs2046210 and the minor homozygotes plus heterozygotes of rs9383590 exhibited a several-years-younger age at onset than the common homozygotes, which was more pronounced in ER-positive and luminal patients. Importantly, the observed associations of each SNV were not consistently nullified upon correction for the other SNV nor upon analyses in common homozygotes for the other SNV. We conclude that both SNVs remain independent candidate causal variants.

Chromatin Variants Reveal the Genetic Determinants of Oncogenesis in Breast Cancer

Breast cancer presents as multiple distinct disease entities. Each tumor harbors diverse cell populations defining a phenotypic heterogeneity that impinges on our ability to treat patients. To date, efforts mainly focused on genetic variants to find drivers of inter- and intratumor phenotypic heterogeneity. However, these efforts have failed to fully capture the genetic basis of breast cancer. Through recent technological and analytical approaches, the genetic basis of phenotypes can now be decoded by characterizing chromatin variants. These variants correspond to polymorphisms in chromatin states at DNA sequences that serve a distinct role across cell populations. Here, we review the function and causes of chromatin variants as they relate to breast cancer inter- and intratumor heterogeneity and how they can guide the development of treatment alternatives to fulfill the goal of precision cancer medicine.

Transcriptional enhancers at 40: evolution of a viral DNA element to nuclear architectural structures

Gene regulation by transcriptional enhancers is the dominant mechanism driving cell type- and signal-specific transcriptional diversity in metazoans. However, over four decades since the original discovery, how enhancers operate in the nuclear space remains largely enigmatic. Recent multidisciplinary efforts combining real-time imaging, genome sequencing, and biophysical strategies provide insightful but conflicting models of enhancer-mediated gene control. Here, we review the discovery and progress in enhancer biology, emphasizing the recent findings that acutely activated enhancers assemble regulatory machinery as mesoscale architectural structures with distinct physical properties. These findings help formulate novel models that explain several mysterious features of the assembly of transcriptional enhancers and the mechanisms of spatial control of gene expression.

Interpretation of the role of germline and somatic non-coding mutations in cancer: expression and chromatin conformation informed analysis

BACKGROUND

There has been extensive scrutiny of cancer driving mutations within the exome (especially amino acid altering mutations) as these are more likely to have a clear impact on protein functions, and thus on cell biology. However, this has come at the neglect of systematic identification of regulatory (non-coding) variants, which have recently been identified as putative somatic drivers and key germline risk factors for cancer development. Comprehensive understanding of non-coding mutations requires understanding their role in the disruption of regulatory elements, which then disrupt key biological functions such as gene expression.

MAIN BODY

We describe how advancements in sequencing technologies have led to the identification of a large number of non-coding mutations with uncharacterized biological significance. We summarize the strategies that have been developed to interpret and prioritize the biological mechanisms impacted by non-coding mutations, focusing on recent annotation of cancer non-coding variants utilizing chromatin states, eQTLs, and chromatin conformation data.

CONCLUSION

We believe that a better understanding of how to apply different regulatory data types into the study of non-coding mutations will enhance the discovery of novel mechanisms driving cancer.

Association between Ancestry-Specific 6q25 Variants and Breast Cancer Subtypes in Peruvian Women

BACKGROUND

Breast cancer incidence in the United States is lower in Hispanic/Latina (H/L) compared with African American/Black or Non-Hispanic White women. An Indigenous American breast cancer-protective germline variant (rs140068132) has been reported near the estrogen receptor 1 gene. This study tests the association of rs140068132 and other polymorphisms in the 6q25 region with subtype-specific breast cancer risk in H/Ls of high Indigenous American ancestry.

METHODS

Genotypes were obtained for 5,094 Peruvian women with (1,755) and without (3,337) breast cancer. Associations between genotype and overall and subtype-specific risk for the protective variant were tested using logistic regression models and conditional analyses, including other risk-associated polymorphisms in the region.

RESULTS

We replicated the reported association between rs140068132 and breast cancer risk overall [odds ratio (OR), 0.53; 95% confidence interval (CI), 0.47-0.59], as well as the lower odds of developing hormone receptor negative (HR-) versus HR+ disease (OR, 0.77; 95% CI, 0.61-0.97). Models, including HER2, showed further heterogeneity with reduced odds for HR+HER2+ (OR, 0.68; 95% CI, 0.51-0.92), HR-HER2+ (OR, 0.63; 95% CI, 0.44-0.90) and HR-HER2- (OR, 0.77; 95% CI, 0.56-1.05) compared with HR+HER2-. Inclusion of other risk-associated variants did not change these observations.

CONCLUSIONS

The rs140068132 polymorphism is associated with decreased risk of breast cancer in Peruvians and is more protective against HR- and HER2+ diseases independently of other breast cancer-associated variants in the 6q25 region.

IMPACT

These results could inform functional analyses to understand the mechanism by which rs140068132-G reduces risk of breast cancer development in a subtype-specific manner. They also illustrate the importance of including diverse individuals in genetic studies.

Convergence of case-specific epigenetic alterations identify a confluence of genetic vulnerabilities tied to opioid overdose

Opioid use disorder is a highly heterogeneous disease driven by a variety of genetic and environmental risk factors which have yet to be fully elucidated. Opioid overdose, the most severe outcome of opioid use disorder, remains the leading cause of accidental death in the United States. We interrogated the effects of opioid overdose on the brain using ChIP-seq to quantify patterns of H3K27 acetylation in dorsolateral prefrontal cortical neurons isolated from 51 opioid-overdose cases and 51 accidental death controls. Among opioid cases, we observed global hypoacetylation and identified 388 putative enhancers consistently depleted for H3K27ac. Machine learning on H3K27ac patterns predicted case-control status with high accuracy. We focused on case-specific regulatory alterations, revealing 81,399 hypoacetylation events, uncovering vast inter-patient heterogeneity. We developed a strategy to decode this heterogeneity based on convergence analysis, which leveraged promoter-capture Hi-C to identify five genes over-burdened by alterations in their regulatory network or "plexus": ASTN2, KCNMA1, DUSP4, GABBR2, ENOX1. These convergent loci are enriched for opioid use disorder risk genes and heritability for generalized anxiety, number of sexual partners, and years of education. Overall, our multi-pronged approach uncovers neurobiological aspects of opioid use disorder and captures genetic and environmental factors perpetuating the opioid epidemic.

The landscape of GWAS validation; systematic review identifying 309 validated non-coding variants across 130 human diseases

Background

The remarkable growth of genome-wide association studies (GWAS) has created a critical need to experimentally validate the disease-associated variants, 90% of which involve non-coding variants.

Methods

To determine how the field is addressing this urgent need, we performed a comprehensive literature review identifying 36,676 articles. These were reduced to 1454 articles through a set of filters using natural language processing and ontology-based text-mining. This was followed by manual curation and cross-referencing against the GWAS catalog, yielding a final set of 286 articles.

Results

We identified 309 experimentally validated non-coding GWAS variants, regulating 252 genes across 130 human disease traits. These variants covered a variety of regulatory mechanisms. Interestingly, 70% (215/309) acted through cis-regulatory elements, with the remaining through promoters (22%, 70/309) or non-coding RNAs (8%, 24/309). Several validation approaches were utilized in these studies, including gene expression (n = 272), transcription factor binding (n = 175), reporter assays (n = 171), in vivo models (n = 104), genome editing (n = 96) and chromatin interaction (n = 33).

Conclusions

This review of the literature is the first to systematically evaluate the status and the landscape of experimentation being used to validate non-coding GWAS-identified variants. Our results clearly underscore the multifaceted approach needed for experimental validation, have practical implications on variant prioritization and considerations of target gene nomination. While the field has a long way to go to validate the thousands of GWAS associations, we show that progress is being made and provide exemplars of validation studies covering a wide variety of mechanisms, target genes, and disease areas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01216-w.

Androgen Receptor-Mediated Transcription in Prostate Cancer

Androgen receptor (AR)-mediated transcription is critical in almost all stages of prostate cancer (PCa) growth and differentiation. This process involves a complex interplay of coregulatory proteins, chromatin remodeling complexes, and other transcription factors that work with AR at cis-regulatory enhancer regions to induce the spatiotemporal transcription of target genes. This enhancer-driven mechanism is remarkably dynamic and undergoes significant alterations during PCa progression. In this review, we discuss the AR mechanism of action in PCa with a focus on how cis-regulatory elements modulate gene expression. We explore emerging evidence of genetic variants that can impact AR regulatory regions and alter gene transcription in PCa. Finally, we highlight several outstanding questions and discuss potential mechanisms of this critical transcription factor.

Mutations in Noncoding Cis-Regulatory Elements Reveal Cancer Driver Cistromes in Luminal Breast Cancer

Whole-genome sequencing of primary breast tumors enabled the identification of cancer driver genes and noncoding cancer driver plexuses from somatic mutations. However, differentiating driver from passenger events among noncoding genetic variants remains a challenge. Herein, we reveal cancer-driver cis-regulatory elements linked to transcription factors previously shown to be involved in development of luminal breast cancers by defining a tumor-enriched catalogue of approximately 100,000 unique cis-regulatory elements from 26 primary luminal estrogen receptor (ER)⁺ progesterone receptor (PR)⁺ breast tumors. Integrating this catalog with somatic mutations from 350 publicly available breast tumor whole genomes, we uncovered cancer driver cistromes, defined as the sum of binding sites for a transcription factor, for ten transcription factors in luminal breast cancer such as FOXA1 and ER, nine of which are essential for growth in breast cancer with four exclusive to the luminal subtype. Collectively, we present a strategy to find cancer driver cistromes relying on quantifying the enrichment of noncoding mutations over cis-regulatory elements concatenated into a functional unit. IMPLICATIONS: Mapping the accessible chromatin of luminal breast cancer led to discovery of an accumulation of mutations within cistromes of transcription factors essential to luminal breast cancer. This demonstrates coopting of regulatory networks to drive cancer and provides a framework to derive insight into the noncoding space of cancer.

TranSNPs: A class of functional SNPs affecting mRNA translation potential revealed by fraction-based allelic imbalance

Few studies have explored the association between SNPs and alterations in mRNA translation potential. We developed an approach to identify SNPs that can mark allele-specific protein expression levels and could represent sources of inter-individual variation in disease risk. Using MCF7 cells under different treatments, we performed polysomal profiling followed by RNA sequencing of total or polysome-associated mRNA fractions and designed a computational approach to identify SNPs showing a significant change in the allelic balance between total and polysomal mRNA fractions. We identified 147 SNPs, 39 of which located in UTRs. Allele-specific differences at the translation level were confirmed in transfected MCF7 cells by reporter assays. Exploiting breast cancer data from TCGA we identified UTR SNPs demonstrating distinct prognosis features and altering binding sites of RNA-binding proteins. Our approach produced a catalog of tranSNPs, a class of functional SNPs associated with allele-specific translation and potentially endowed with prognostic value for disease risk.

Biomolecular condensates in cancer biology

Understanding the characteristics of cancer cells is essential for the development of improved diagnosis and therapeutics. From a gene regulation perspective, the super‐enhancer concept has been introduced to systematically understand the molecular mechanisms underlying the identities of various cell types and has been extended to the analysis of cancer cells and cancer genome alterations. In addition, several characteristic features of super‐enhancers have led to the recognition of the link between gene regulation and biomolecular condensates, which is often mediated by liquid‐liquid phase separation. Several lines of evidence have suggested molecular and biophysical principles and their alterations in cancer cells, which are particularly associated with gene regulation and cell signaling (“ transcriptional” and “signaling” condensates). These findings collectively suggest that the modification of biomolecular condensates represents an important mechanism by which cancer cells acquire various cancer hallmark traits and establish functional innovation for cancer initiation and progression. The condensate model also provides the molecular basis of the vulnerability of cancer cells to transcriptional perturbation and further suggests the possibility of therapeutic targeting of condensates. This review summarizes recent findings regarding the relationships between super‐enhancers and biomolecular condensate models, multiple scenarios of condensate alterations in cancers, and the potential of the condensate model for therapeutic development.

Mechanistic insights into genetic susceptibility to prostate cancer

Prostate cancer (PCa) is the second most common cancer in men and is a highly heritable disease that affects millions of individuals worldwide. Genome-wide association studies have to date discovered nearly 270 genetic loci harboring hundreds of single nucleotide polymorphisms (SNPs) that are associated with PCa susceptibility. In contrast, the functional characterization of the mechanisms underlying PCa risk association is still growing. Given that PCa risk-associated SNPs are highly enriched in noncoding cis-regulatory genomic regions, accumulating evidence suggests a widespread modulation of transcription factor chromatin binding and allelic enhancer activity by these noncoding SNPs, thereby dysregulating gene expression. Emerging studies have shown that a proportion of noncoding variants can modulate the formation of transcription factor complexes at enhancers and CTCF-mediated 3D genome architecture. Interestingly, DNA methylation-regulated CTCF binding could orchestrate a long-range chromatin interaction between PCa risk enhancer and causative genes. Additionally, one-causal-variant-two-risk genes or multiple-risk-variant-multiple-genes are prevalent in some PCa risk-associated loci. In this review, we will discuss the current understanding of the general principles of SNP-mediated gene regulation, experimental advances, and functional evidence supporting the mechanistic roles of several PCa genetic loci with potential clinical impact on disease prevention and treatment.

Positive Regulation of Estrogen Receptor Alpha in Breast Tumorigenesis

Estrogen receptor alpha (ERα, NR3A1) contributes through its expression in different tissues to a spectrum of physiological processes, including reproductive system development and physiology, bone mass maintenance, as well as cardiovascular and central nervous system functions. It is also one of the main drivers of tumorigenesis in breast and uterine cancer and can be targeted by several types of hormonal therapies. ERα is expressed in a subset of luminal cells corresponding to less than 10% of normal mammary epithelial cells and in over 70% of breast tumors (ER+ tumors), but the basis for its selective expression in normal or cancer tissues remains incompletely understood. The mapping of alternative promoters and regulatory elements has delineated the complex genomic structure of the ESR1 gene and shed light on the mechanistic basis for the tissue-specific regulation of ESR1 expression. However, much remains to be uncovered to better understand how ESR1 expression is regulated in breast cancer. This review recapitulates the current body of knowledge on the structure of the ESR1 gene and the complex mechanisms controlling its expression in breast tumors. In particular, we discuss the impact of genetic alterations, chromatin modifications, and enhanced expression of other luminal transcription regulators on ESR1 expression in tumor cells.

Reorganization of the 3D genome pinpoints non-coding drivers of primary prostate tumors

Prostate cancer is a heterogeneous disease whose progression is linked to genome instability. However, the impact of this instability on the non-coding genome and its three-dimensional organization to aid progression is unclear. Using primary benign and tumor tissue, we find a high concordance in higher order three-dimensional genome organization. This concordance argues for constraints to the topology of prostate tumor genomes. Nonetheless, we identified changes in focal chromatin interactions, typical of loops bridging non-coding cis-regulatory elements, and showed how structural variants can induce these changes to guide cis-regulatory element hijacking. Such events resulted in opposing differential expression of genes found at antipodes of rearrangements. Collectively, these results argue that changes to focal chromatin interactions, as opposed to higher order genome organization, allow for aberrant gene regulation and are repeatedly mediated by structural variants in primary prostate cancer.

Non-coding driver mutations in human cancer

Tumour formation involves random mutagenic events and positive evolutionary selection acting on a subset of such events, referred to as driver mutations. A decade of careful surveying of tumour DNA using exome-based analyses has revealed a multitude of protein-coding somatic driver mutations, some of which are clinically actionable. Today, a transition towards whole-genome analysis is well under way, technically enabling the discovery of potential driver mutations occurring outside protein-coding sequences. Mutations are abundant in this vast non-coding space, which is more than 50 times larger than the coding exome, but reliable identification of selection signals in non-coding DNA remains a challenge. In this Review, we discuss recent findings in the field, where the emerging landscape is one in which non-coding driver mutations appear to be relatively infrequent. Nevertheless, we highlight several notable discoveries. We consider possible reasons for the relative absence of non-coding driver events, as well as the difficulties associated with detecting signals of positive selection in non-coding DNA.

Pathogenic noncoding variants in the neurofibromatosis and schwannomatosis predisposition genes

Neurofibromatosis type 1 (NF1), type 2 (NF2), and schwannomatosis are a group of autosomal dominant disorders that predispose to the development of nerve sheath tumors. Pathogenic variants (PVs) that cause NF1 and NF2 are located in the NF1 and NF2 loci, respectively. To date, most variants associated with schwannomatosis have been identified in the SMARCB1 and LZTR1 genes, and a missense variant in the DGCR8 gene was recently reported to predispose to schwannomas. In spite of the high detection rate for PVs in NF1 and NF2 (over 90% of non-mosaic germline variants can be identified by routine genetic screening) underlying PVs for a proportion of clinical cases remain undetected. A higher proportion of non-NF2 schwannomatosis cases have no detected PV, with PVs currently only identified in around 70%-86% of familial cases and 30%-40% of non-NF2 sporadic schwannomatosis cases. A number of variants of uncertain significance have been observed for each disorder, many of them located in noncoding, regulatory, or intergenic regions. Here we summarize noncoding variants in this group of genes and discuss their established or potential role in the pathogenesis of NF1, NF2, and schwannomatosis.

Systematic dissection of transcriptional regulatory networks by genome-scale and single-cell CRISPR screens

Millions of putative transcriptional regulatory elements (TREs) have been cataloged in the human genome, yet their functional relevance in specific pathophysiological settings remains to be determined. This is critical to understand how oncogenic transcription factors (TFs) engage specific TREs to impose transcriptional programs underlying malignant phenotypes. Here, we combine cutting edge CRISPR screens and epigenomic profiling to functionally survey ≈15,000 TREs engaged by estrogen receptor (ER). We show that ER exerts its oncogenic role in breast cancer by engaging TREs enriched in GATA3, TFAP2C, and H3K27Ac signal. These TREs control critical downstream TFs, among which TFAP2C plays an essential role in ER-driven cell proliferation. Together, our work reveals novel insights into a critical oncogenic transcription program and provides a framework to map regulatory networks, enabling to dissect the function of the noncoding genome of cancer cells.

Functional mapping of androgen receptor enhancer activity

Background

Androgen receptor (AR) is critical to the initiation, growth, and progression of prostate cancer. Once activated, the AR binds to cis-regulatory enhancer elements on DNA that drive gene expression. Yet, there are 10–100× more binding sites than differentially expressed genes. It is unclear how or if these excess binding sites impact gene transcription.

Results

To characterize the regulatory logic of AR-mediated transcription, we generated a locus-specific map of enhancer activity by functionally testing all common clinical AR binding sites with Self-Transcribing Active Regulatory Regions sequencing (STARRseq). Only 7% of AR binding sites displayed androgen-dependent enhancer activity. Instead, the vast majority of AR binding sites were either inactive or constitutively active enhancers. These annotations strongly correlated with enhancer-associated features of both in vitro cell lines and clinical prostate cancer samples. Evaluating the effect of each enhancer class on transcription, we found that AR-regulated enhancers frequently interact with promoters and form central chromosomal loops that are required for transcription. Somatic mutations of these critical AR-regulated enhancers often impact enhancer activity.

Conclusions

Using a functional map of AR enhancer activity, we demonstrated that AR-regulated enhancers act as a regulatory hub that increases interactions with other AR binding sites and gene promoters.

CNCDatabase: a database of non-coding cancer drivers

Most mutations in cancer genomes occur in the non-coding regions with unknown impact on tumor development. Although the increase in the number of cancer whole-genome sequences has revealed numerous putative non-coding cancer drivers, their information is dispersed across multiple studies making it difficult to understand their roles in tumorigenesis of different cancer types. We have developed CNCDatabase, Cornell Non-coding Cancer driver Database (https://cncdatabase.med.cornell.edu/) that contains detailed information about predicted non-coding drivers at gene promoters, 5′ and 3′ UTRs (untranslated regions), enhancers, CTCF insulators and non-coding RNAs. CNCDatabase documents 1111 protein-coding genes and 90 non-coding RNAs with reported drivers in their non-coding regions from 32 cancer types by computational predictions of positive selection using whole-genome sequences; differential gene expression in samples with and without mutations; or another set of experimental validations including luciferase reporter assays and genome editing. The database can be easily modified and scaled as lists of non-coding drivers are revised in the community with larger whole-genome sequencing studies, CRISPR screens and further experimental validations. Overall, CNCDatabase provides a helpful resource for researchers to explore the pathological role of non-coding alterations in human cancers.

Single-cell chromatin accessibility profiling of glioblastoma identifies an invasive cancer stem cell population associated with lower survival

Chromatin accessibility discriminates stem from mature cell populations, enabling the identification of primitive stem-like cells in primary tumors, such as glioblastoma (GBM) where self-renewing cells driving cancer progression and recurrence are prime targets for therapeutic intervention. We show, using single-cell chromatin accessibility, that primary human GBMs harbor a heterogeneous self-renewing population whose diversity is captured in patient-derived glioblastoma stem cells (GSCs). In-depth characterization of chromatin accessibility in GSCs identifies three GSC states: Reactive, Constructive, and Invasive, each governed by uniquely essential transcription factors and present within GBMs in varying proportions. Orthotopic xenografts reveal that GSC states associate with survival, and identify an invasive GSC signature predictive of low patient survival, in line with the higher invasive properties of Invasive state GSCs compared to Reactive and Constructive GSCs as shown by in vitro and in vivo assays. Our chromatin-driven characterization of GSC states improves prognostic precision and identifies dependencies to guide combination therapies.

DORGE: Discovery of Oncogenes and tumoR suppressor genes using Genetic and Epigenetic features

Data-driven discovery of cancer driver genes, including tumor suppressor genes (TSGs) and oncogenes (OGs), is imperative for cancer prevention, diagnosis, and treatment. Although epigenetic alterations are important for tumor initiation and progression, most known driver genes were identified based on genetic alterations alone. Here, we developed an algorithm, DORGE (Discovery of Oncogenes and tumor suppressoR genes using Genetic and Epigenetic features), to identify TSGs and OGs by integrating comprehensive genetic and epigenetic data. DORGE identified histone modifications as strong predictors for TSGs, and it found missense mutations, super enhancers, and methylation differences as strong predictors for OGs. We extensively validated DORGE-predicted cancer driver genes using independent functional genomics data. We also found that DORGE-predicted dual-functional genes (both TSGs and OGs) are enriched at hubs in protein-protein interaction and drug-gene networks. Overall, our study has deepened the understanding of epigenetic mechanisms in tumorigenesis and revealed previously undetected cancer driver genes.

Intrinsic and Extrinsic Factors Governing the Transcriptional Regulation of ESR1

Transcriptional regulation of ESR1, the gene that encodes for estrogen receptor α (ER), is critical for regulating the downstream effects of the estrogen signaling pathway in breast cancer such as cell growth. ESR1 is a large and complex gene that is regulated by multiple regulatory elements, which has complicated our understanding of how ESR1 expression is controlled in the context of breast cancer. Early studies characterized the genomic structure of ESR1 with subsequent studies focused on identifying intrinsic (chromatin environment, transcription factors, signaling pathways) and extrinsic (tumor microenvironment, secreted factors) mechanisms that impact ESR1 gene expression. Currently, the introduction of genomic sequencing platforms and additional genome-wide technologies has provided additional insight on how chromatin structures may coordinate with these intrinsic and extrinsic mechanisms to regulate ESR1 expression. Understanding these interactions will allow us to have a clearer understanding of how ESR1 expression is regulated and eventually provide clues on how to influence its regulation with potential treatments. In this review, we highlight key studies concerning the genomic structure of ESR1, mechanisms that affect the dynamics of ESR1 expression, and considerations towards affecting ESR1 expression and hormone responsiveness in breast cancer.

Breast Cancer: A Molecularly Heterogenous Disease Needing Subtype-Specific Treatments

Breast cancer is the most commonly occurring cancer in women. There were over two-million new cases in world in 2018. It is the second leading cause of death from cancer in western countries. At the molecular level, breast cancer is a heterogeneous disease, which is characterized by high genomic instability evidenced by somatic gene mutations, copy number alterations, and chromosome structural rearrangements. The genomic instability is caused by defects in DNA damage repair, transcription, DNA replication, telomere maintenance and mitotic chromosome segregation. According to molecular features, breast cancers are subdivided in subtypes, according to activation of hormone receptors (estrogen receptor and progesterone receptor), of human epidermal growth factors receptor 2 (HER2), and or BRCA mutations. In-depth analyses of the molecular features of primary and metastatic breast cancer have shown the great heterogeneity of genetic alterations and their clonal evolution during disease development. These studies have contributed to identify a repertoire of numerous disease-causing genes that are altered through different mutational processes. While early-stage breast cancer is a curable disease in about 70% of patients, advanced breast cancer is largely incurable. However, molecular studies have contributed to develop new therapeutic approaches targeting HER2, CDK4/6, PI3K, or involving poly(ADP-ribose) polymerase inhibitors for BRCA mutation carriers and immunotherapy.

Noncoding Variants Connect Enhancer Dysregulation with Nuclear Receptor Signaling in Hematopoietic Malignancies

Mutations in protein-coding genes are well established as the basis for human cancer, yet how alterations within noncoding genome, a substantial fraction of which contain cis-regulatory elements (CRE), contribute to cancer pathophysiology remains elusive. Here, we developed an integrative approach to systematically identify and characterize noncoding regulatory variants with functional consequences in human hematopoietic malignancies. Combining targeted resequencing of hematopoietic lineage-associated CREs and mutation discovery, we uncovered 1,836 recurrently mutated CREs containing leukemia-associated noncoding variants. By enhanced CRISPR/dCas9-based CRE perturbation screening and functional analyses, we identified 218 variant-associated oncogenic or tumor-suppressive CREs in human leukemia. Noncoding variants at KRAS and PER2 enhancers reside in proximity to nuclear receptor (NR) binding regions and modulate transcriptional activities in response to NR signaling in leukemia cells. NR binding sites frequently colocalize with noncoding variants across cancer types. Hence, recurrent noncoding variants connect enhancer dysregulation with nuclear receptor signaling in hematopoietic malignancies. SIGNIFICANCE: We describe an integrative approach to identify noncoding variants in human leukemia, and reveal cohorts of variant-associated oncogenic and tumor-suppressive cis-regulatory elements including KRAS and PER2 enhancers. Our findings support a model in which noncoding regulatory variants connect enhancer dysregulation with nuclear receptor signaling to modulate gene programs in hematopoietic malignancies.See related commentary by van Galen, p. 646.This article is highlighted in the In This Issue feature, p. 627.

Differential Allele-Specific Expression Uncovers Breast Cancer Genes Dysregulated by Cis Noncoding Mutations

Identifying cancer-relevant mutations in noncoding regions is challenging due to the large numbers of such mutations, their low levels of recurrence, and difficulties in interpreting their functional impact. To uncover genes that are dysregulated due to somatic mutations in cis, we build upon the concept of differential allele-specific expression (ASE) and introduce methods to identify genes within an individual's cancer whose ASE differs from what is found in matched normal tissue. When applied to breast cancer tumor samples, our methods detect the known allele-specific effects of copy number variation and nonsense-mediated decay. Further, genes that are found to recurrently exhibit differential ASE across samples are cancer relevant. Genes with cis mutations are enriched for differential ASE, and we find 147 potentially functional noncoding mutations cis to genes that exhibit significant differential ASE. We conclude that differential ASE is a promising means for discovering gene dysregulation due to cis noncoding mutations.

Noncoding mutations target cis-regulatory elements of the FOXA1 plexus in prostate cancer

Prostate cancer is the second most commonly diagnosed malignancy among men worldwide. Recurrently mutated in primary and metastatic prostate tumors, FOXA1 encodes a pioneer transcription factor involved in disease onset and progression through both androgen receptor-dependent and androgen receptor-independent mechanisms. Despite its oncogenic properties however, the regulation of FOXA1 expression remains unknown. Here, we identify a set of six cis-regulatory elements in the FOXA1 regulatory plexus harboring somatic single-nucleotide variants in primary prostate tumors. We find that deletion and repression of these cis-regulatory elements significantly decreases FOXA1 expression and prostate cancer cell growth. Six of the ten single-nucleotide variants mapping to FOXA1 regulatory plexus significantly alter the transactivation potential of cis-regulatory elements by modulating the binding of transcription factors. Collectively, our results identify cis-regulatory elements within the FOXA1 plexus mutated in primary prostate tumors as potential targets for therapeutic intervention.

FOXA1 pioneer transcription factor is recurrently mutated in primary and metastatic prostate tumors. Here, authors identify a set of six cis-regulatory elements in the FOXA1 regulatory plexus harboring somatic SNVs in primary prostate tumors and characterize their role in regulating FOXA1 expression and prostate cancer cell growth.

Chromatin interactome mapping at 139 independent breast cancer risk signals

BACKGROUND

Genome-wide association studies have identified 196 high confidence independent signals associated with breast cancer susceptibility. Variants within these signals frequently fall in distal regulatory DNA elements that control gene expression.

RESULTS

We designed a Capture Hi-C array to enrich for chromatin interactions between the credible causal variants and target genes in six human mammary epithelial and breast cancer cell lines. We show that interacting regions are enriched for open chromatin, histone marks for active enhancers, and transcription factors relevant to breast biology. We exploit this comprehensive resource to identify candidate target genes at 139 independent breast cancer risk signals and explore the functional mechanism underlying altered risk at the 12q24 risk region.

CONCLUSIONS

Our results demonstrate the power of combining genetics, computational genomics, and molecular studies to rationalize the identification of key variants and candidate target genes at breast cancer GWAS signals.

Cistrome Partitioning Reveals Convergence of Somatic Mutations and Risk Variants on Master Transcription Regulators in Primary Prostate Tumors

Thousands of noncoding somatic single-nucleotide variants (SNVs) of unknown function are reported in tumors. Partitioning the genome according to cistromes reveals the enrichment of somatic SNVs in prostate tumors as opposed to adjacent normal tissue cistromes of master transcription regulators, including AR, FOXA1, and HOXB13. This parallels enrichment of prostate cancer genetic predispositions over these transcription regulators' tumor cistromes, exemplified at the 8q24 locus harboring both risk variants and somatic SNVs in cis-regulatory elements upregulating MYC expression. However, Massively Parallel Reporter Assays reveal that few SNVs can alter the transactivation potential of individual cis-regulatory elements. Instead, similar to inherited risk variants, SNVs accumulate in cistromes of master transcription regulators required for prostate cancer development.

BRCA1-associated R-loop affects transcription and differentiation in breast luminal epithelial cells

BRCA1-associated basal-like breast cancer originates from luminal progenitor cells. Breast epithelial cells from cancer-free BRCA1 mutation carriers are defective in luminal differentiation. However, how BRCA1 deficiency leads to lineage-specific differentiation defect is not clear. BRCA1 is implicated in resolving R-loops, DNA-RNA hybrid structures associated with genome instability and transcriptional regulation. We recently showed that R-loops are preferentially accumulated in breast luminal epithelial cells of BRCA1 mutation carriers. Here, we interrogate the impact of a BRCA1 mutation-associated R-loop located in a putative transcriptional enhancer upstream of the ERα-encoding ESR1 gene. Genetic ablation confirms the relevance of this R-loop-containing region to enhancer-promoter interactions and transcriptional activation of the corresponding neighboring genes, including ESR1, CCDC170 and RMND1. BRCA1 knockdown in ERα+ luminal breast cancer cells increases intensity of this R-loop and reduces transcription of its neighboring genes. The deleterious effect of BRCA1 depletion on transcription is mitigated by ectopic expression of R-loop-removing RNase H1. Furthermore, RNase H1 overexpression in primary breast cells from BRCA1 mutation carriers results in a shift from luminal progenitor cells to mature luminal cells. Our findings suggest that BRCA1-dependent R-loop mitigation contributes to luminal cell-specific transcription and differentiation, which could in turn suppress BRCA1-associated tumorigenesis.

Bone Marrow Stromal Cells Transcriptionally Repress ESR1 but Cannot Overcome Constitutive ESR1 Mutant Activity

Estrogen receptor α (ER) is the target of endocrine therapies in ER-positive breast cancer (BC), but their therapeutic effectiveness diminishes with disease progression. Most metastatic BCs retain an ER-positive status, but ER expression levels are reduced. We asked how the bone tumor microenvironment (TME) regulates ER expression. We observed ESR1 mRNA and ER protein downregulation in BC cells treated with conditioned media (CM) from patient-derived, cancer-activated bone marrow stromal cells (BMSCs) and the BMSC cell line HS5. Decreases in ESR1 mRNA were attributed to decreases in nascent transcripts as well as decreased RNA polymerase II occupancy and H3K27Ac levels on the ESR1 promoter and/or distal enhancer (ENH1). Repression extended to neighboring genes of ESR1, including ARMT1 and SYNE1. Although ERK/MAPK signaling pathway can repress ER expression by other TME cell types, MAPK inhibition did not reverse decreases in ER expression by BMSC-CM. ESR1 mRNA and ER protein half-lives in MCF7 cells were unchanged by BMSC-CM treatment. Whereas ER phosphorylation was induced, ER activity was repressed by BMSC-CM as neither ER occupancy at known binding sites nor estrogen response element-luciferase activity was detected. BMSC-CM also repressed expression of ER target genes. In cells expressing the Y537S and D538G ESR1 mutations, BMSC-CM reduced ESR1, but expression of target genes PGR and TFF1 remained significantly elevated compared with that of control wild-type cells. These studies demonstrate that BMSCs can transcriptionally corepress ESR1 with neighboring genes and inhibit receptor activity, but the functional consequences of the BMSC TME can be limited by metastasis-associated ESR1 mutations.

A DNA electrochemical biosensor based on triplex DNA-templated Ag/Pt nanoclusters for the detection of single-nucleotide variant

A label-free electrochemical biosensor based on the triplex DNA-templated Ag/Pt bimetallic nanoclusters (triplex-Ag/PtNCs) and locked nucleic acid (LNA) modified X-shaped DNA probe was developed for the detection of single-nucleotide variant (SNV) related to β-thalassemia. Firstly, using triplex DNA as template, a site-specific and homogeneous Ag/PtNCs was prepared, which can effectively catalyze the 3,3,5,5-tetramethylbenzidine-H₂O₂ system and thus be employed as a signal reporter in the field of electrochemical biosensor. Secondly, the LNA modified X-shaped probes were assembled on gold electrode surface, which can only be dissociated in the presence of target, leading to the hybridization with triplex-Ag/PtNCs and significant increase of current signal. In this way, the detection limit for SNV of β-thalassemia was 0.8 fM with variant allele frequency (VAF) as low as 0.0001%.

Mapping and Making Sense of Noncoding Mutations in the Genome

Whole-genome sequencing efforts of tumors and normal tissues have identified numerous genetic mutations, both somatic and germline, that do not overlap with coding genomic sequences. Attributing a functional role to these noncoding mutations and characterizing them using experimental methods has been more challenging compared with coding mutations. In this review, we provide a brief introduction to the world of noncoding mutations. We discuss recent progress in identifying noncoding mutations and the analytic and experimental approaches utilized to interpret their functional roles. We also highlight the potential mechanisms by which a noncoding mutation may exert its effect and discuss future challenges and opportunities.

DiseaseEnhancer: a resource of human disease-associated enhancer catalog

Large-scale sequencing studies discovered substantial genetic variants occurring in enhancers which regulate genes via long range chromatin interactions. Importantly, such variants could affect enhancer regulation by changing transcription factor bindings or enhancer hijacking, and in turn, make an essential contribution to disease progression. To facilitate better usage of published data and exploring enhancer deregulation in various human diseases, we created DiseaseEnhancer (http://biocc.hrbmu.edu.cn/DiseaseEnhancer/), a manually curated database for disease-associated enhancers. As of July 2017, DiseaseEnhancer includes 847 disease-associated enhancers in 143 human diseases. Database features include basic enhancer information (i.e. genomic location and target genes); disease types; associated variants on the enhancer and their mediated phenotypes (i.e. gain/loss of enhancer and the alterations of transcription factor bindings). We also include a feature on our website to export any query results into a file and download the full database. DiseaseEnhancer provides a promising avenue for researchers to facilitate the understanding of enhancer deregulation in disease pathogenesis, and identify new biomarkers for disease diagnosis and therapy.

Transcriptional regulation of normal human mammary cell heterogeneity and its perturbation in breast cancer

The mammary gland in adult women consists of biologically distinct cell types that differ in their surface phenotypes. Isolation and molecular characterization of these subpopulations of mammary cells have provided extensive insights into their different transcriptional programs and regulation. This information is now serving as a baseline for interpreting the heterogeneous features of human breast cancers. Examination of breast cancer mutational profiles further indicates that most have undergone a complex evolutionary process even before being detected. The consequent intra-tumoral as well as inter-tumoral heterogeneity of these cancers thus poses major challenges to deriving information from early and hence likely pervasive changes in potential therapeutic interest. Recently described reproducible and efficient methods for generating human breast cancers de novo in immunodeficient mice transplanted with genetically altered primary cells now offer a promising alternative to investigate initial stages of human breast cancer development. In this review, we summarize current knowledge about key transcriptional regulatory processes operative in these partially characterized subpopulations of normal human mammary cells and effects of disrupting these processes in experimentally produced human breast cancers.

Identification of Cancer Drivers at CTCF Insulators in 1,962 Whole Genomes

Recent studies have shown that mutations at non-coding elements, such as promoters and enhancers, can act as cancer drivers. However, an important class of non-coding elements, namely CTCF insulators, has been overlooked in the previous driver analyses. We used insulator annotations from CTCF and cohesin ChIA-PET and analyzed somatic mutations in 1,962 whole genomes from 21 cancer types. Using the heterogeneous patterns of transcription-factor-motif disruption, functional impact, and recurrence of mutations, we developed a computational method that revealed 21 insulators showing signals of positive selection. In particular, mutations in an insulator in multiple cancer types, including 16% of melanoma samples, are associated with TGFB1 up-regulation. Using CRISPR-Cas9, we find that alterations at two of the most frequently mutated regions in this insulator increase cell growth by 40%-50%, supporting the role of this boundary element as a cancer driver. Thus, our study reveals several CTCF insulators as putative cancer drivers.

Dynamic genome and transcriptional network-based biomarkers and drugs: precision in breast cancer therapy

Despite remarkable progress in medium-term overall survival benefit in the adjuvant, neoadjuvant and metastatic settings, with multiple recent targeted drug approvals, acquired resistance, late relapse, and cancer-related death rates remain challenging. Integrated technological systems have been developed to overcome these unmet needs. The characterization of structural and functional noncoding genome elements through next-generation sequencing (NGS) systems, Hi-C and CRISPR/Cas9, as well as computational models, allows for whole genome and transcriptome analysis. Rapid progress in large-scale single-biopsy genome analysis has identified several novel breast cancer driver genes and oncotargets. The exploration of spatiotemporal tumor evolution has returned exciting while inconclusive data on dynamic intratumor heterogeneity (ITH) through multiregional NGS and single-cell DNA/RNA sequencing and circulating genomic subclones (cGSs) by serial circulating cell-free DNA NGS to predict and overcome intrinsic and acquired therapeutic resistance. This review discusses reliable breast cancer genome analysis data and focuses on two major crucial perspectives. The validation of ITH, cGSs, and intrapatient genetic/genomic heterogeneity as predictive biomarkers, as well as the valid discovery of novel oncotargets within patient-centric genomic trials, encouraging early drug development, could optimize primary and secondary therapeutic decision-making. A longer-term goal is to identify the individualized landscape of both coding and noncoding key mutations. This progress will enable the understanding of molecular mechanisms perturbating regulatory networks, shaping the pharmaceutical controllability of deregulated transcriptional biocircuits.

AhR controls redox homeostasis and shapes the tumor microenvironment in BRCA1-associated breast cancer

Cancer cells have higher reactive oxygen species (ROS) than normal cells, due to genetic and metabolic alterations. An emerging scenario is that cancer cells increase ROS to activate protumorigenic signaling while activating antioxidant pathways to maintain redox homeostasis. Here we show that, in basal-like and BRCA1-related breast cancer (BC), ROS levels correlate with the expression and activity of the transcription factor aryl hydrocarbon receptor (AhR). Mechanistically, ROS triggers AhR nuclear accumulation and activation to promote the transcription of both antioxidant enzymes and the epidermal growth factor receptor (EGFR) ligand, amphiregulin (AREG). In a mouse model of BRCA1-related BC, cancer-associated AhR and AREG control tumor growth and production of chemokines to attract monocytes and activate proangiogenic function of macrophages in the tumor microenvironment. Interestingly, the expression of these chemokines as well as infiltration of monocyte-lineage cells (monocyte and macrophages) positively correlated with ROS levels in basal-like BC. These data support the existence of a coordinated link between cancer-intrinsic ROS regulation and the features of tumor microenvironment. Therapeutically, chemical inhibition of AhR activity sensitizes human BC models to Erlotinib, a selective EGFR tyrosine kinase inhibitor, suggesting a promising combinatorial anticancer effect of AhR and EGFR pathway inhibition. Thus, AhR represents an attractive target to inhibit redox homeostasis and modulate the tumor promoting microenvironment of basal-like and BRCA1-associated BC.

Inhibition of histone methyltransferase DOT1L silences ERα gene and blocks proliferation of antiestrogen-resistant breast cancer cells

Breast cancer (BC) resistance to endocrine therapy results from constitutively active or aberrant estrogen receptor α (ERα) signaling, and ways to block ERα pathway in these tumors are sought after. We identified the H3K79 methyltransferase DOT1L as a novel cofactor of ERα in BC cell chromatin, where the two proteins colocalize to regulate estrogen target gene transcription. DOT1L blockade reduces proliferation of hormone-responsive BC cells in vivo and in vitro, consequent to cell cycle arrest and apoptotic cell death, with widespread effects on ER-dependent gene transcription, including ERα and FOXA1 gene silencing. Antiestrogen-resistant BC cells respond to DOT1L inhibition also in mouse xenografts, with reduction in ERα levels, H3K79 methylation, and tumor growth. These results indicate that DOT1L is an exploitable epigenetic target for treatment of endocrine therapy-resistant ERα-positive BCs.

Japanese GWAS identifies variants for bust-size, dysmenorrhea, and menstrual fever that are eQTLs for relevant protein-coding or long non-coding RNAs

Traits related to primary and secondary sexual characteristics greatly impact females during puberty and day-to-day adult life. Therefore, we performed a GWAS analysis of 11,348 Japanese female volunteers and 22 gynecology-related phenotypic variables, and identified significant associations for bust-size, menstrual pain (dysmenorrhea) severity, and menstrual fever. Bust-size analysis identified significant association signals in CCDC170-ESR1 (rs6557160; P = 1.7 × 10-16) and KCNU1-ZNF703 (rs146992477; P = 6.2 × 10-9) and found that one-third of known European-ancestry associations were also present in Japanese. eQTL data points to CCDC170 and ZNF703 as those signals' functional targets. For menstrual fever, we identified a novel association in OPRM1 (rs17181171; P = 2.0 × 10-8), for which top variants were eQTLs in multiple tissues. A known dysmenorrhea signal near NGF replicated in our data (rs12030576; P = 1.1 × 10-19) and was associated with RP4-663N10.1 expression, a putative lncRNA enhancer of NGF, while a novel dysmenorrhea signal in the IL1 locus (rs80111889; P = 1.9 × 10-16) contained SNPs previously associated with endometriosis, and GWAS SNPs were most significantly associated with IL1A expression. By combining regional imputation with colocalization analysis of GWAS/eQTL signals along with integrated annotation with epigenomic data, this study further refines the sets of candidate causal variants and target genes for these known and novel gynecology-related trait loci.

CRISPR-based strategies for studying regulatory elements and chromatin structure in mammalian gene control

The development of high-throughput methods has enabled the genome-wide identification of putative regulatory elements in a wide variety of mammalian cells at an unprecedented resolution. Extensive genomic studies have revealed the important role of regulatory elements and genetic variation therein in disease formation and risk. In most cases, there is only correlative evidence for the roles of these elements and non-coding changes within these elements in pathogenesis. With the advent of genome- and epigenome-editing tools based on the CRISPR technology, it is now possible to test the functional relevance of the regulatory elements and alterations on a genomic scale. Here, we review the various CRISPR-based strategies that have been developed to functionally validate the candidate regulatory elements in mammals as well as the non-coding genetic variants found to be associated with human disease. We also discuss how these synthetic biology tools have helped to elucidate the role of three-dimensional nuclear architecture and higher-order chromatin organization in shaping functional genome and controlling gene expression.