SummaryOestrogen receptor-α (ER) is the defining and driving transcription factor in the majority of breast cancers and its target genes dictate cell growth and endocrine response, yet genomic understanding of ER function has been restricted to model systems1-3. We now map genome-wide ER binding events, by chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq), in primary breast cancers from patients with different clinical outcome and in distant ER positive (ER+) metastases. We find that drug resistant cancers still have ER-chromatin occupancy, but that ER binding is a dynamic process, with the acquisition of unique ER binding regions in tumours from patients that are likely to relapse. The acquired, poor outcome ER regulatory regions observed in primary tumours reveal gene signatures that predict clinical outcome in ER+ disease exclusively. We find that the differential ER binding programme observed in tumours from patients with poor outcome is not due to the selection of a rare subpopulation of cells, but is due to the FoxA1-mediated reprogramming of ER binding on a rapid time scale. The parallel redistribution of ER and FoxA1 cis-regulatory elements in drug resistant cellular contexts is supported by histological co-expression of ER and FoxA1 in metastatic samples. By establishing transcription factor mapping in primary tumour material, we show that there is plasticity in ER binding capacity, with distinct combinations of cis-regulatory elements linked with the different clinical outcomes.

Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs.Results: Here we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform.Availability: BMIQ is freely available from http://code.google.com/p/bmiq/.Contact: a.teschendorff@ucl.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online

(http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. microRNA expression profiling of human breast cancer

Integrated analysis of miRNA expression and genomic changes in human breast tumors allows the classification of tumor subtypes. Abstract Background: MicroRNAs (miRNAs), a class of short non-coding RNAs found in many plants and animals, often act post-transcriptionally to inhibit gene expression.

Polycomb group proteins (PCGs) are involved in repression of genes that are required for stem cell differentiation. Recently, it was shown that promoters of PCG target genes (PCGTs) are 12-fold more likely to be methylated in cancer than non-PCGTs. Age is the most important demographic risk factor for cancer, and we hypothesized that its carcinogenic potential may be referred by irreversibly stabilizing stem cell features. To test this, we analyzed the methylation status of over 27,000 CpGs mapping to promoters of ;14,000 genes in whole blood samples from 261 postmenopausal women. We demonstrate that stem cell PCGTs are far more likely to become methylated with age than non-targets (odds ratio = 5.3 [3.8-7.4], P < 10 À10

Recent advances in next generation sequencing have made it possible to precisely characterize all somatic coding mutations that occur during the development and progression of individual cancers. Here we used these approaches to sequence the genomes (>43-fold coverage) and transcriptomes of an oestrogen-receptor-alpha-positive metastatic lobular breast cancer at depth. We found 32 somatic non-synonymous coding mutations present in the metastasis, and measured the frequency of these somatic mutations in DNA from the primary tumour of the same patient, which arose 9 years earlier. Five of the 32 mutations (in ABCB11, HAUS3, SLC24A4, SNX4 and PALB2) were prevalent in the DNA of the primary tumour removed at diagnosis 9 years earlier, six (in KIF1C, USP28, MYH8, MORC1, KIAA1468 and RNASEH2A) were present at lower frequencies (1-13%), 19 were not detected in the primary tumour, and two were undetermined. The combined analysis of genome and transcriptome data revealed two new RNA-editing events that recode the amino acid sequence of SRP9 and COG3. Taken together, our data show that single nucleotide mutational heterogeneity can be a property of low or intermediate grade primary breast cancers and that significant evolution can occur with disease progression.

ChAMP is implemented as a Bioconductor package in R. The package and the vignette can be downloaded at bioconductor.org

A feature selection method was used in an analysis of three major microarray expression datasets to identify molecular subclasses and prognostic markers in estrogen receptor-negative breast cancer, showing that it is a heterogeneous disease with at least four main subtypes.

IntroductionThe organisation of the mammary epithelial hierarchy is poorly understood. Our hypothesis is that the luminal cell compartment is more complex than initially described, and that an understanding of the developmental relationships within this lineage will help in understanding the cellular context in which breast tumours occur.MethodsWe used fluorescence-activated cell sorting along with in vitro and in vivo functional assays to examine the growth and differentiation properties of distinct subsets of human and mouse mammary epithelial cells. We also examined how loss of steroid hormones influenced these populations in vivo. Gene expression profiles were also obtained for all the purified cell populations and correlated to those obtained from breast tumours.ResultsThe luminal cell compartment of the mouse mammary gland can be resolved into nonclonogenic oestrogen receptor-positive (ER+) luminal cells, ER+ luminal progenitors and oestrogen receptor-negative (ER-) luminal progenitors. The ER+ luminal progenitors are unique in regard to cell survival, as they are relatively insensitive to loss of oestrogen and progesterone when compared with the other types of mammary epithelial cells. Analysis of normal human breast tissue reveals a similar hierarchical organisation composed of nonclonogenic luminal cells, and relatively differentiated (EpCAM+CD49f+ALDH-) and undifferentiated (EpCAM+CD49f+ALDH+) luminal progenitors. In addition, approximately one-quarter of human breast samples examined contained an additional population that had a distinct luminal progenitor phenotype, characterised by low expression of ERBB3 and low proliferative potential. Parent-progeny relationship experiments demonstrated that all luminal progenitor populations in both species are highly plastic and, at low frequencies, can generate progeny representing all mammary cell types. The ER- luminal progenitors in the mouse and the ALDH+ luminal progenitors in the human appear to be analogous populations since they both have gene signatures that are associated with alveolar differentiation and resemble those obtained from basal-like breast tumours.ConclusionThe luminal cell compartment in the mammary epithelium is more heterogeneous than initially perceived since progenitors of varying levels of luminal cell differentiation and proliferative capacities can be identified. An understanding of these cells will be essential for understanding the origins and the cellular context of human breast tumours.