DNA methylation is a fundamental epigenetic mark that governs gene expression and chromatin organization, thus providing a window into cellular identity and developmental processes1. Current datasets typically include only a fraction of methylation sites and are often based either on cell lines that underwent massive changes in culture or on tissues containing unspecified mixtures of cells2–5. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing, allowing fragment-level analysis across thousands of unique markers for 39 cell types sorted from 205 healthy tissue samples. Replicates of the same cell type are more than 99.5% identical, demonstrating the robustness of cell identity programmes to environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny and identifies methylation patterns retained since embryonic development. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely hypermethylated loci are rare and are enriched for CpG islands, Polycomb targets and CTCF binding sites, suggesting a new role in shaping cell-type-specific chromatin looping. The atlas provides an essential resource for study of gene regulation and disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies.

ERCP, biliary sphincterotomy and temporary internal stenting, together with percutaneous drainage of intra-abdominal or intrahepatic bile collections, represent a safe and effective strategy for the management of bile leaks following both blunt and penetrating hepatic trauma.

Background: Tumor-derived circulating cell-free DNA (cfDNA) is present in the plasma of individuals with cancer. Assays aimed at detecting common cancer mutations in cfDNA are being developed for the detection of several cancer types. In breast cancer, however, such assays have failed to detect the disease at a sensitivity relevant for clinical use, in part due to the absence of multiple common mutations that can be co-detected in plasma. Unlike individual mutations that exist only in a subset of tumors, unique DNA methylation patterns are universally present in cells of a common type and therefore may be ideal biomarkers. Here we describe the detection and quantification of breast-derived cfDNA using a breast-specific DNA methylation signature. Patients and methods: We collected plasma from patients with localized breast cancer before and throughout treatment with neoadjuvant chemotherapy and surgery (N ¼ 235 samples). Results: Pretreatment breast cfDNA was detected in patients with localized disease with a sensitivity of 80% at 97% specificity. High breast cfDNA levels were associated with aggressive molecular tumor profiles and metabolic activity of the disease. During neoadjuvant chemotherapy, breast cfDNA levels decreased dramatically. Importantly, the presence of breast cfDNA towards the end of the chemotherapy regimen reflected the existence of residual disease. Conclusion: We propose that breast-specific cfDNA is a universal and powerful marker for the detection and monitoring of breast cancer.

Differentiation events contribute to phenotypic cellular heterogeneity within tumors and influence disease progression and response to therapy. Here, we dissect mechanisms controlling intratumoral heterogeneity within triple-negative basal-like breast cancers. Tumor cells expressing the cytokeratin K14 possess a differentiation state that is associated with that of normal luminal progenitors, and K14-negative cells are in a state closer to that of mature luminal cells. We show that cells can transition between these states through asymmetric divisions, which produce one K14 and one K14 daughter cell, and that these asymmetric divisions contribute to the generation of cellular heterogeneity. We identified several regulators that control the proportion of K14 cells in the population. EZH2 and Notch increase the numbers of K14 cells and their rates of symmetric divisions, and FOXA1 has an opposing effect. Our findings demonstrate that asymmetric divisions generate differentiation transitions and heterogeneity, and identify pathways that control breast cancer cellular composition.