Enduring epigenetic landmarks define the cancer microenvironment.

The growth and progression of solid tumors involves dynamic cross-talk between cancer epithelium and the surrounding microenvironment. To date, molecular profiling has largely been restricted to the epithelial component of tumors; therefore, features underpinning the persistent protumorigenic phenotype of the tumor microenvironment are unknown. Using whole-genome bisulfite sequencing, we show for the first time that cancer-associated fibroblasts (CAFs) from localized prostate cancer display remarkably distinct and enduring genome-wide changes in DNA methylation, significantly at enhancers and promoters, compared to nonmalignant prostate fibroblasts (NPFs). Differentially methylated regions associated with changes in gene expression have cancer-related functions and accurately distinguish CAFs from NPFs. Remarkably, a subset of changes is shared with prostate cancer epithelial cells, revealing the new concept of tumor-specific epigenome modifications in the tumor and its microenvironment. The distinct methylome of CAFs provides a novel epigenetic hallmark of the cancer microenvironment and promises new biomarkers to improve interpretation of diagnostic samples.

Three-dimensional disorganization of the cancer genome occurs coincident with long-range genetic and epigenetic alterations.

A three-dimensional chromatin state underpins the structural and functional basis of the genome by bringing regulatory elements and genes into close spatial proximity to ensure proper, cell-type-specific gene expression profiles. Here, we performed Hi-C chromosome conformation capture sequencing to investigate how three-dimensional chromatin organization is disrupted in the context of copy-number variation, long-range epigenetic remodeling, and atypical gene expression programs in prostate cancer. We find that cancer cells retain the ability to segment their genomes into megabase-sized topologically associated domains (TADs); however, these domains are generally smaller due to establishment of additional domain boundaries. Interestingly, a large proportion of the new cancer-specific domain boundaries occur at regions that display copy-number variation. Notably, a common deletion on 17p13.1 in prostate cancer spanning the TP53 tumor suppressor locus results in bifurcation of a single TAD into two distinct smaller TADs. Change in domain structure is also accompanied by novel cancer-specific chromatin interactions within the TADs that are enriched at regulatory elements such as enhancers, promoters, and insulators, and associated with alterations in gene expression. We also show that differential chromatin interactions across regulatory regions occur within long-range epigenetically activated or silenced regions of concordant gene activation or repression in prostate cancer. Finally, we present a novel visualization tool that enables integrated exploration of Hi-C interaction data, the transcriptome, and epigenome. This study provides new insights into the relationship between long-range epigenetic and genomic dysregulation and changes in higher-order chromatin interactions in cancer.

MicroRNA profiling of the pubertal mouse mammary gland identifies miR-184 as a candidate breast tumour suppressor gene.

INTRODUCTION: The study of mammalian development has offered many insights into the molecular aetiology of cancer. We previously used analysis of mammary morphogenesis to discover a critical role for GATA-3 in mammary developmental and carcinogenesis. In recent years an important role for microRNAs (miRNAs) in a myriad of cellular processes in development and in oncogenesis has emerged. METHODS: microRNA profiling was conducted on stromal and epithelial cellular subsets microdissected from the pubertal mouse mammary gland. miR-184 was reactivated by transient or stable overexpression in breast cancer cell lines and examined using a series of in vitro (proliferation, tumour-sphere and protein synthesis) assays. Orthotopic xenografts of breast cancer cells were used to assess the effect of miR-184 on tumourigenesis as well as distant metastasis. Interactions between miR-184 and its putative targets were assessed by quantitative PCR, microarray, bioinformatics and 3' untranslated region Luciferase reporter assay. The methylation status of primary patient samples was determined by MBD-Cap sequencing. Lastly, the clinical prognostic significance of miR-184 putative targets was assessed using publicly available datasets. RESULTS: A large number of microRNA were restricted in their expression to specific tissue subsets. MicroRNA-184 (miR-184) was exclusively expressed in epithelial cells and markedly upregulated during differentiation of the proliferative, invasive cells of the pubertal terminal end bud (TEB) into ductal epithelial cells in vivo. miR-184 expression was silenced in mouse tumour models compared to non-transformed epithelium and in a majority of breast cancer cell line models. Ectopic reactivation of miR-184 inhibited the proliferation and self-renewal of triple negative breast cancer (TNBC) cell lines in vitro and delayed primary tumour formation and reduced metastatic burden in vivo. Gene expression studies uncovered multi-factorial regulation of genes in the AKT/mTORC1 pathway by miR-184. In clinical breast cancer tissues, expression of miR-184 is lost in primary TNBCs while the miR-184 promoter is methylated in a subset of lymph node metastases from TNBC patients. CONCLUSIONS: These studies elucidate a new layer of regulation in the PI3K/AKT/mTOR pathway with relevance to mammary development and tumour progression and identify miR-184 as a putative breast tumour suppressor.

Identification of sequence-structure RNA binding motifs for SELEX-derived aptamers.

MOTIVATION: Systematic Evolution of Ligands by EXponential Enrichment (SELEX) represents a state-of-the-art technology to isolate single-stranded (ribo)nucleic acid fragments, named aptamers, which bind to a molecule (or molecules) of interest via specific structural regions induced by their sequence-dependent fold. This powerful method has applications in designing protein inhibitors, molecular detection systems, therapeutic drugs and antibody replacement among others. However, full understanding and consequently optimal utilization of the process has lagged behind its wide application due to the lack of dedicated computational approaches. At the same time, the combination of SELEX with novel sequencing technologies is beginning to provide the data that will allow the examination of a variety of properties of the selection process. RESULTS: To close this gap we developed, Aptamotif, a computational method for the identification of sequence-structure motifs in SELEX-derived aptamers. To increase the chances of identifying functional motifs, Aptamotif uses an ensemble-based approach. We validated the method using two published aptamer datasets containing experimentally determined motifs of increasing complexity. We were able to recreate the author's findings to a high degree, thus proving the capability of our approach to identify binding motifs in SELEX data. Additionally, using our new experimental dataset, we illustrate the application of Aptamotif to elucidate several properties of the selection process.

Inferring physical protein contacts from large-scale purification data of protein complexes.

Recent large-scale data sets of protein complex purifications have provided unprecedented insights into the organization of cellular protein complexes. Several computational methods have been developed to detect co-complexed proteins in these data sets. Their common aim is the identification of biologically relevant protein complexes. However, much less is known about the network of direct physical protein contacts within the detected protein complexes. Therefore, our work investigates whether direct physical contacts can be computationally derived by combining raw data of large-scale protein complex purifications. We assess four established scoring schemes and introduce a new scoring approach that is specifically devised to infer direct physical protein contacts from protein complex purifications. The physical contacts identified by the five methods are comprehensively benchmarked against different reference sets that provide evidence for true physical contacts. Our results show that raw purification data can indeed be exploited to determine high-confidence physical protein contacts within protein complexes. In particular, our new method outperforms competing approaches at discovering physical contacts involving proteins that have been screened multiple times in purification experiments. It also excels in the analysis of recent protein purification screens of molecular chaperones and protein kinases. In contrast to previous findings, we observe that physical contacts inferred from purification experiments of protein complexes can be qualitatively comparable to binary protein interactions measured by experimental high-throughput assays such as yeast two-hybrid. This suggests that computationally derived physical contacts might complement binary protein interaction assays and guide large-scale interactome mapping projects by prioritizing putative physical contacts for further experimental screens.

On the applicability of elastic network normal modes in small-molecule docking.

Incorporating backbone flexibility into protein-ligand docking is still a challenging problem. In protein-protein docking, normal mode analysis (NMA) has become increasingly popular as it can be used to describe the collective motions of a biological system, but the question of whether NMA can also be useful in predicting the conformational changes observed upon small-molecule binding has only been addressed in a few case studies. Here, we describe a large-scale study on the applicability of NMA for protein-ligand docking using 433 apo/holo pairs of the Astex data sets. On the basis of sets of the first normal modes from the apo structure, we first generated for each paired holo structure a set of conformations that optimally reproduce its C(α) trace with respect to the underlying normal mode subspace. Using AutoDock, GOLD, and FlexX we then docked the original ligands into these conformations to assess how the docking performance depends on the number of modes used to reproduce the holo structure. The results of our study indicate that, even for such a best-case scenario, the use of normal mode analysis in small-molecule docking is restricted and that a general rule on how many modes to use does not seem to exist or at least is not easy to find.

DNA methylation is required to maintain both DNA replication timing precision and 3D genome organization integrity.

DNA replication timing and three-dimensional (3D) genome organization are associated with distinct epigenome patterns across large domains. However, whether alterations in the epigenome, in particular cancer-related DNA hypomethylation, affects higher-order levels of genome architecture is still unclear. Here, using Repli-Seq, single-cell Repli-Seq, and Hi-C, we show that genome-wide methylation loss is associated with both concordant loss of replication timing precision and deregulation of 3D genome organization. Notably, we find distinct disruption in 3D genome compartmentalization, striking gains in cell-to-cell replication timing heterogeneity and loss of allelic replication timing in cancer hypomethylation models, potentially through the gene deregulation of DNA replication and genome organization pathways. Finally, we identify ectopic H3K4me3-H3K9me3 domains from across large hypomethylated domains, where late replication is maintained, which we purport serves to protect against catastrophic genome reorganization and aberrant gene transcription. Our results highlight a potential role for the methylome in the maintenance of 3D genome regulation.

Why do hubs in the yeast protein interaction network tend to be essential: reexamining the connection between the network topology and essentiality.

The centrality-lethality rule, which notes that high-degree nodes in a protein interaction network tend to correspond to proteins that are essential, suggests that the topological prominence of a protein in a protein interaction network may be a good predictor of its biological importance. Even though the correlation between degree and essentiality was confirmed by many independent studies, the reason for this correlation remains illusive. Several hypotheses about putative connections between essentiality of hubs and the topology of protein-protein interaction networks have been proposed, but as we demonstrate, these explanations are not supported by the properties of protein interaction networks. To identify the main topological determinant of essentiality and to provide a biological explanation for the connection between the network topology and essentiality, we performed a rigorous analysis of six variants of the genomewide protein interaction network for Saccharomyces cerevisiae obtained using different techniques. We demonstrated that the majority of hubs are essential due to their involvement in Essential Complex Biological Modules, a group of densely connected proteins with shared biological function that are enriched in essential proteins. Moreover, we rejected two previously proposed explanations for the centrality-lethality rule, one relating the essentiality of hubs to their role in the overall network connectivity and another relying on the recently published essential protein interactions model.

Replication timing and epigenome remodelling are associated with the nature of chromosomal rearrangements in cancer.

DNA replication timing is known to facilitate the establishment of the epigenome, however, the intimate connection between replication timing and changes to the genome and epigenome in cancer remain largely uncharacterised. Here, we perform Repli-Seq and integrated epigenome analyses and demonstrate that genomic regions that undergo long-range epigenetic deregulation in prostate cancer also show concordant differences in replication timing. A subset of altered replication timing domains are conserved across cancers from different tissue origins. Notably, late-replicating regions in cancer cells display a loss of DNA methylation, and a switch in heterochromatin features from H3K9me3-marked constitutive to H3K27me3-marked facultative heterochromatin. Finally, analysis of 214 prostate and 35 breast cancer genomes reveal that late-replicating regions are prone to cis and early-replication to trans chromosomal rearrangements. Together, our data suggests that the nature of chromosomal rearrangement in cancer is related to the spatial and temporal positioning and altered epigenetic states of early-replicating compared to late-replicating loci.

DNA Hypermethylation Encroachment at CpG Island Borders in Cancer Is Predisposed by H3K4 Monomethylation Patterns.

Promoter CpG islands are typically unmethylated in normal cells, but in cancer a proportion are subject to hypermethylation. Using methylome sequencing we identified CpG islands that display partial methylation encroachment across the 5' or 3' CpG island borders. CpG island methylation encroachment is widespread in prostate and breast cancer and commonly associates with gene suppression. We show that the pattern of H3K4me1 at CpG island borders in normal cells predicts the different modes of cancer CpG island hypermethylation. Notably, genetic manipulation of Kmt2d results in concordant alterations in H3K4me1 levels and CpG island border DNA methylation encroachment. Our findings suggest a role for H3K4me1 in the demarcation of CpG island methylation borders in normal cells, which become eroded in cancer.

Methylome and transcriptome maps of human visceral and subcutaneous adipocytes reveal key epigenetic differences at developmental genes.

Adipocytes support key metabolic and endocrine functions of adipose tissue. Lipid is stored in two major classes of depots, namely visceral adipose (VA) and subcutaneous adipose (SA) depots. Increased visceral adiposity is associated with adverse health outcomes, whereas the impact of SA tissue is relatively metabolically benign. The precise molecular features associated with the functional differences between the adipose depots are still not well understood. Here, we characterised transcriptomes and methylomes of isolated adipocytes from matched SA and VA tissues of individuals with normal BMI to identify epigenetic differences and their contribution to cell type and depot-specific function. We found that DNA methylomes were notably distinct between different adipocyte depots and were associated with differential gene expression within pathways fundamental to adipocyte function. Most striking differential methylation was found at transcription factor and developmental genes. Our findings highlight the importance of developmental origins in the function of different fat depots.

Structural footprinting in protein structure comparison: the impact of structural fragments.

BACKGROUND: One approach for speeding-up protein structure comparison is the projection approach, where a protein structure is mapped to a high-dimensional vector and structural similarity is approximated by distance between the corresponding vectors. Structural footprinting methods are projection methods that employ the same general technique to produce the mapping: first select a representative set of structural fragments as models and then map a protein structure to a vector in which each dimension corresponds to a particular model and "counts" the number of times the model appears in the structure. The main difference between any two structural footprinting methods is in the set of models they use; in fact a large number of methods can be generated by varying the type of structural fragments used and the amount of detail in their representation. How do these choices affect the ability of the method to detect various types of structural similarity? RESULTS: To answer this question we benchmarked three structural footprinting methods that vary significantly in their selection of models against the CATH database. In the first set of experiments we compared the methods' ability to detect structural similarity characteristic of evolutionarily related structures, i.e., structures within the same CATH superfamily. In the second set of experiments we tested the methods' agreement with the boundaries imposed by classification groups at the Class, Architecture, and Fold levels of the CATH hierarchy. CONCLUSION: In both experiments we found that the method which uses secondary structure information has the best performance on average, but no one method performs consistently the best across all groups at a given classification level. We also found that combining the methods' outputs significantly improves the performance. Moreover, our new techniques to measure and visualize the methods' agreement with the CATH hierarchy, including the threshholded affinity graph, are useful beyond this work. In particular, they can be used to expose a similar composition of different classification groups in terms of structural fragments used by the method and thus provide an alternative demonstration of the continuous nature of the protein structure universe.

Comprehensive evaluation of genome-wide 5-hydroxymethylcytosine profiling approaches in human DNA.

BACKGROUND: The discovery that 5-methylcytosine (5mC) can be oxidized to 5-hydroxymethylcytosine (5hmC) by the ten-eleven translocation (TET) proteins has prompted wide interest in the potential role of 5hmC in reshaping the mammalian DNA methylation landscape. The gold-standard bisulphite conversion technologies to study DNA methylation do not distinguish between 5mC and 5hmC. However, new approaches to mapping 5hmC genome-wide have advanced rapidly, although it is unclear how the different methods compare in accurately calling 5hmC. In this study, we provide a comparative analysis on brain DNA using three 5hmC genome-wide approaches, namely whole-genome bisulphite/oxidative bisulphite sequencing (WG Bis/OxBis-seq), Infinium HumanMethylation450 BeadChip arrays coupled with oxidative bisulphite (HM450K Bis/OxBis) and antibody-based immunoprecipitation and sequencing of hydroxymethylated DNA (hMeDIP-seq). We also perform loci-specific TET-assisted bisulphite sequencing (TAB-seq) for validation of candidate regions. RESULTS: We show that whole-genome single-base resolution approaches are advantaged in providing precise 5hmC values but require high sequencing depth to accurately measure 5hmC, as this modification is commonly in low abundance in mammalian cells. HM450K arrays coupled with oxidative bisulphite provide a cost-effective representation of 5hmC distribution, at CpG sites with 5hmC levels >~10%. However, 5hmC analysis is restricted to the genomic location of the probes, which is an important consideration as 5hmC modification is commonly enriched at enhancer elements. Finally, we show that the widely used hMeDIP-seq method provides an efficient genome-wide profile of 5hmC and shows high correlation with WG Bis/OxBis-seq 5hmC distribution in brain DNA. However, in cell line DNA with low levels of 5hmC, hMeDIP-seq-enriched regions are not detected by WG Bis/OxBis or HM450K, either suggesting misinterpretation of 5hmC calls by hMeDIP or lack of sensitivity of the latter methods. CONCLUSIONS: We highlight both the advantages and caveats of three commonly used genome-wide 5hmC profiling technologies and show that interpretation of 5hmC data can be significantly influenced by the sensitivity of methods used, especially as the levels of 5hmC are low and vary in different cell types and different genomic locations.

Secondary structure spatial conformation footprint: a novel method for fast protein structure comparison and classification.

BACKGROUND: Recently a new class of methods for fast protein structure comparison has emerged. We call the methods in this class projection methods as they rely on a mapping of protein structure into a high-dimensional vector space. Once the mapping is done, the structure comparison is reduced to distance computation between corresponding vectors. As structural similarity is approximated by distance between projections, the success of any projection method depends on how well its mapping function is able to capture the salient features of protein structure. There is no agreement on what constitutes a good projection technique and the three currently known projection methods utilize very different approaches to the mapping construction, both in terms of what structural elements are included and how this information is integrated to produce a vector representation. RESULTS: In this paper we propose a novel projection method that uses secondary structure information to produce the mapping. First, a diverse set of spatial arrangements of triplets of secondary structure elements, a set of structural models, is automatically selected. Then, each protein structure is mapped into a high-dimensional vector of "counts" or footprint, where each count corresponds to the number of times a given structural model is observed in the structure, weighted by the precision with which the model is reproduced. We perform the first comprehensive evaluation of our method together with all other currently known projection methods. CONCLUSION: The results of our evaluation suggest that the type of structural information used by a projection method affects the ability of the method to detect structural similarity. In particular, our method that uses the spatial conformations of triplets of secondary structure elements outperforms other methods in most of the tests.

Genome-wide DNA methylation profiling in triple-negative breast cancer reveals epigenetic signatures with important clinical value.

Analysis of cancer methylomes has dramatically changed our concept of the potential of diagnostic and prognostic methylation biomarkers in disease stratification. Through whole-genome methylation capture sequencing of triple-negative breast cancers (TNBCs) we recently identified differentially methylated regions with diagnostic and prognostic value that promise to stratify TNBCs for more personalized management.

Genome-scale methylation assessment did not identify prognostic biomarkers in oral tongue carcinomas.

BACKGROUND: DNA methylation profiling of heterogeneous head and neck squamous cell carcinoma (HNSCC) cohorts has been reported to predict patient outcome. We investigated if a prognostic DNA methylation profile could be found in tumour tissue from a single uniform subsite, the oral tongue. The methylation status of 109 comprehensively annotated oral tongue squamous cell carcinoma (OTSCC) formalin-fixed paraffin-embedded (FFPE) samples from a single institution were examined with the Illumina HumanMethylation450K (HM450K) array. Data pre-processing, quality control and analysis were performed using R packages. Probes mapping to SNPs, sex chromosomes and unreliable probes were accounted for prior to downstream analyses. The relationship between methylation and patient survival was examined using both agnostic approaches and feature selection. The cohort was enlarged by incorporation of 331 The Cancer Genome Atlas (TCGA) HNSCC samples, which included 91 TCGA OTSCC samples with HM450K and survival data available. RESULTS: Given the use of FFPE-derived DNA, we defined different cohorts for separate analyses. Overall, similar results were found between cohorts. With an unsupervised approach, no distinct hypermethylated group of samples was identified and nor was a prognostic methylation profile identified. The use of multiple downstream feature selection approaches, including a linear models for microarray data (LIMMA), centroid feature selection (CFS), and recursive feature elimination (RFE) support vector machines, similarly failed to identify a significant methylation signature informative for patient prognosis or any clinicopathological data available. Furthermore, we were unable to confirm the prognostic methylation profiles or specific prognostic loci reported within the literature for HNSCC. CONCLUSIONS: With genome-scale assessment of DNA methylation using HM450K in one of the largest OTSCC cohorts to date, we were unable to identify a hypermethylated group of tumours or a prognostic methylation signature. This suggests that either DNA methylation in isolation is not likely to be of prognostic value or larger cohorts are required to identify such a biomarker for OTSCC.

Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling.

BACKGROUND: In recent years the Illumina HumanMethylation450 (HM450) BeadChip has provided a user-friendly platform to profile DNA methylation in human samples. However, HM450 lacked coverage of distal regulatory elements. Illumina have now released the MethylationEPIC (EPIC) BeadChip, with new content specifically designed to target these regions. We have used HM450 and whole-genome bisulphite sequencing (WGBS) to perform a critical evaluation of the new EPIC array platform. RESULTS: EPIC covers over 850,000 CpG sites, including >90 % of the CpGs from the HM450 and an additional 413,743 CpGs. Even though the additional probes improve the coverage of regulatory elements, including 58 % of FANTOM5 enhancers, only 7 % distal and 27 % proximal ENCODE regulatory elements are represented. Detailed comparisons of regulatory elements from EPIC and WGBS show that a single EPIC probe is not always informative for those distal regulatory elements showing variable methylation across the region. However, overall data from the EPIC array at single loci are highly reproducible across technical and biological replicates and demonstrate high correlation with HM450 and WGBS data. We show that the HM450 and EPIC arrays distinguish differentially methylated probes, but the absolute agreement depends on the threshold set for each platform. Finally, we provide an annotated list of probes whose signal could be affected by cross-hybridisation or underlying genetic variation. CONCLUSION: The EPIC array is a significant improvement over the HM450 array, with increased genome coverage of regulatory regions and high reproducibility and reliability, providing a valuable tool for high-throughput human methylome analyses from diverse clinical samples.

Coordinated epigenetic remodelling of transcriptional networks occurs during early breast carcinogenesis.

BACKGROUND: Dysregulation of the epigenome is a common event in malignancy; however, deciphering the earliest cancer-associated epigenetic events remains a challenge. Cancer epigenome studies to date have primarily utilised cancer cell lines or clinical samples, where it is difficult to identify the initial epigenetic lesions from those that occur over time. Here, we analysed the epigenome of human mammary epithelial cells (HMEC) and a matched variant cell population (vHMEC) that have spontaneously escaped senescence and undergone partial carcinogenic transformation. Using this model of basal-like breast carcinogenesis, we provide striking new insights into the very first epigenetic changes that occur during the initial stages of malignancy. RESULTS: The first phase of malignancy is defined by coordinated changes in the epigenome. At the chromatin level, this is embodied in long-range epigenetic deregulation, which involves the concomitant but atypical acquisition or loss of active and repressive histone modifications across large regional blocks. Changes in DNA methylation also occurs in a highly coordinated manner. We identified differentially methylated regions (DMRs) in the very earliest passages of vHMECs. Notably, we find that differential methylation targets loci regulated by key transcription factors including p53, AHR and E2F family members suggesting that epigenetic deregulation of transcription factor binding is a key event in breast carcinogenesis. Interestingly, DMRs identified in vHMEC are extensively methylated in breast cancer, with hypermethylation frequently encroaching into neighbouring regions. A subset of vHMEC DMRs exhibited a strong basal-like cancer specific hypermethylation. CONCLUSIONS: Here, we generated epigenome-wide maps of the earliest phase of breast malignancy and show long-range epigenetic deregulation and coordinated DNA hypermethylation targets loci regulated by key transcription factors. These findings support a model where induction of breast cancer occurs through epigenetic disruption of transcription factor binding leading to deregulation of cancer-associated transcriptional networks. With their stability and very early occurrence, vHMECs hypermethylated loci could serve as excellent biomarkers for the initial detection of basal breast cancer.

DNA methylation of oestrogen-regulated enhancers defines endocrine sensitivity in breast cancer.

Expression of oestrogen receptor (ESR1) determines whether a breast cancer patient receives endocrine therapy, but does not guarantee patient response. The molecular factors that define endocrine response in ESR1-positive breast cancer patients remain poorly understood. Here we characterize the DNA methylome of endocrine sensitivity and demonstrate the potential impact of differential DNA methylation on endocrine response in breast cancer. We show that DNA hypermethylation occurs predominantly at oestrogen-responsive enhancers and is associated with reduced ESR1 binding and decreased gene expression of key regulators of ESR1 activity, thus providing a novel mechanism by which endocrine response is abated in ESR1-positive breast cancers. Conversely, we delineate that ESR1-responsive enhancer hypomethylation is critical in transition from normal mammary epithelial cells to endocrine-responsive ESR1-positive cancer. Cumulatively, these novel insights highlight the potential of ESR1-responsive enhancer methylation to both predict ESR1-positive disease and stratify ESR1-positive breast cancer patients as responders to endocrine therapy.

Methylome sequencing in triple-negative breast cancer reveals distinct methylation clusters with prognostic value.

Epigenetic alterations in the cancer methylome are common in breast cancer and provide novel options for tumour stratification. Here, we perform whole-genome methylation capture sequencing on small amounts of DNA isolated from formalin-fixed, paraffin-embedded tissue from triple-negative breast cancer (TNBC) and matched normal samples. We identify differentially methylated regions (DMRs) enriched with promoters associated with transcription factor binding sites and DNA hypersensitive sites. Importantly, we stratify TNBCs into three distinct methylation clusters associated with better or worse prognosis and identify 17 DMRs that show a strong association with overall survival, including DMRs located in the Wilms tumour 1 (WT1) gene, bi-directional-promoter and antisense WT1-AS. Our data reveal that coordinated hypermethylation can occur in oestrogen receptor-negative disease, and that characterizing the epigenetic framework provides a potential signature to stratify TNBCs. Together, our findings demonstrate the feasibility of profiling the cancer methylome with limited archival tissue to identify regulatory regions associated with cancer.