Targeting of Rac GTPases blocks the spread of intact human breast cancer

High expression of Rac small GTPases in invasive breast ductal carcinoma is associated with poor prognosis, but its therapeutic value in human cancers is not clear. The aim of the current study was to determine the response of human primary breast cancers to Rac-based drug treatments ex vivo. Three-dimensional organotypic cultures were used to assess candidate therapeutic avenues in invasive breast cancers. Uniquely, in these primary cultures, the tumour is not disaggregated, with both epithelial and mesenchymal components maintained within a three-dimensional matrix of type I collagen. EHT 1864, a small molecule inhibitor of Rac GTPases, prevents spread of breast cancers in this setting, and also reduces proliferation at the invading edge. Rac1+ epithelial cells in breast tumours also contain high levels of the phosphorylated form of the transcription factor STAT3. The small molecule Stattic inhibits activation of STAT3 and induces effects similar to those seen with EHT 1864. Pan-Rac inhibition of proliferation precedes down-regulation of STAT3 activity, defining it as the last step in Rac activation during human breast cancer invasion. Our data highlights the potential use of Rac and STAT3 inhibition in treatment of invasive human breast cancer and the benefit of studying novel cancer treatments using three-dimensional primary tumour tissue explant cultures

The Role of Chromatin Structure in Regulating the Human Epidermal Differentiation Complex

The Epidermal Differentiation Complex (EDC) is a co-ordinately regulated locus that is evolutionarily conserved within mammals. It consists of a large number of genes, organised into clusters of gene families, which mainly encode structural constituents of the cornified envelope which replaces the plasma membrane of fully differentiated keratinocytes. It is thought that the developmental program of gene expression at the locus is regulated by specific changes in chromatin structure (Williams et al., 2002). To investigate this, I have characterised the chromatin structure of the EDC in cultured cell lines. These include a keratinocyte cell line, HaCaT cells, in which the locus is active and control cell lines where the locus is inactive. Chromatin is structured on a number of different levels, by the covalent modification of nucleosomes, the arrangement of nucleosomes into chromatin fibres and the arrangement of chromatin fibres into higher order structures within the interphase nucleus. I have assayed chromatin structure on all these levels using Chromatin Immunoprecipitation and Sucrose Gradient Sedimentation Analysis of Chromatin Fibre structure, partnered with oligonucleotide microarrays and Fluorescent In-Situ Hybridisation. By doing so I have examined the role each level of chromatin structure plays in regulating the human EDC and, characterised the relationships between the different levels across a large co-ordinately regulated locus in the human genome

Tissue of origin determines cancer-associated CpG island promoter hypermethylation patterns

ABSTRACT: BACKGROUND: Aberrant CpG island promoter DNA hypermethylation is frequently observed in cancer and is believed to contribute to tumor progression by silencing the expression of tumor suppressor genes. Previously, we observed that promoter hypermethylation in breast cancer reflects cell lineage rather than tumor progression and occurs at genes that are already repressed in a lineage-specific manner. To investigate the generality of our observation we analyzed the methylation profiles of 1,154 cancers from 7 different tissue types. RESULTS: We find that 1,009 genes are prone to hypermethylation in these 7 types of cancer. Nearly half of these genes varied in their susceptibility to hypermethylation between different cancer types. We show that the expression status of hypermethylation prone genes in the originator tissue determines their propensity to become hypermethylated in cancer; specifically, genes that are normally repressed in a tissue are prone to hypermethylation in cancers derived from that tissue. We also show that the promoter regions of hypermethylation-prone genes are depleted of repetitive elements and that DNA sequence around the same promoters is evolutionarily conserved. We propose that these two characteristics reflect tissue-specific gene promoter architecture regulating the expression of these hypermethylation prone genes in normal tissues. CONCLUSIONS: As aberrantly hypermethylated genes are already repressed in pre-cancerous tissue, we suggest that their hypermethylation does not directly contribute to cancer development via silencing. Instead aberrant hypermethylation reflects developmental history and the perturbation of epigenetic mechanisms maintaining these repressed promoters in a hypomethylated state in normal cells.Publisher PDFPeer reviewe

Cluster mean-field theory accurately predicts statistical properties of large-scale DNA methylation patterns

The accurate establishment and maintenance of DNA methylation patterns is vital for mammalian development and disruption to these processes causes human disease. Our understanding of DNA methylation mechanisms has been facilitated by mathematical modelling, particularly stochastic simulations. Megabase-scale variation in DNA methylation patterns is observed in development, cancer and ageing and the mechanisms generating these patterns are little understood. However, the computational cost of stochastic simulations prevents them from modelling such large genomic regions. Here, we test the utility of three different mean-field models to predict summary statistics associated with large-scale DNA methylation patterns. By comparison to stochastic simulations, we show that a cluster mean-field model accurately predicts the statistical properties of steady-state DNA methylation patterns, including the mean and variance of methylation levels calculated across a system of CpG sites, as well as the covariance and correlation of methylation levels between neighbouring sites. We also demonstrate that a cluster mean-field model can be used within an approximate Bayesian computation framework to accurately infer model parameters from data. As mean-field models can be solved numerically in a few seconds, our work demonstrates their utility for understanding the processes underpinning large-scale DNA methylation patterns

Using human disease mutations to understand de novo DNA methyltransferase function.

DNA methylation is a repressive epigenetic mark that is pervasive in mammalian genomes. It is deposited by DNA methyltransferase enzymes (DNMTs) that are canonically classified ashaving de novo (DNMT3A and DNMT3B) or maintenance (DNMT1) function. Mutations in DNMT3A and DNMT3B cause rare Mendelian diseases in humans and are cancer drivers. Mammalian DNMT3 methyltransferase activity is regulated by the non-catalytic region of the proteins which contain multiple chromatin reading domains responsible for DNMT3Aand DNMT3B recruitment to the genome. Characterising disease-causing missense mutations has been central in dissecting the function and regulation of DNMT3A and DNMT3B. These observations have also motivated biochemical studies that provide the molecular details as to how human DNMT3A and DNMT3B mutations drive disorders. Here, we review progress in this area highlighting recent work that has begun dissecting the function of the disordered N-terminal regions of DNMT3A and DNMT3B. These studies haveelucidated that the N-terminal regions of both proteins mediate novel chromatinrecruitment pathways that are central in our understanding of human disease mechanisms.We also discuss how disease mutations affect DNMT3A and DNMT3B oligomerisation, a process that is poorly understood in the context of whole proteins in cells. This dissection of de novo DNMT function using disease-causing mutations provides a paradigm of how genetics and biochemistry can synergise to drive our understanding of the mechanisms through which chromatin misregulation causes human diseas

Lactate, a product of glycolytic metabolism, inhibits histone deacetylase activity and promotes changes in gene expression

Chemical inhibitors of histone deacetylase (HDAC) activity are used as experimental tools to induce histone hyperacetylation and deregulate gene transcription, but it is not known whether the inhibition of HDACs plays any part in the normal physiological regulation of transcription. Using both in vitro and in vivo assays, we show that lactate, which accumulates when glycolysis exceeds the cell’s aerobic metabolic capacity, is an endogenous HDAC inhibitor, deregulating transcription in an HDAC-dependent manner. Lactate is a relatively weak inhibitor (IC(50) 40 mM) compared to the established inhibitors trichostatin A and butyrate, but the genes deregulated overlap significantly with those affected by low concentrations of the more potent inhibitors. HDAC inhibition causes significant up and downregulation of genes, but genes that are associated with HDAC proteins are more likely to be upregulated and less likely to be downregulated than would be expected. Our results suggest that the primary effect of HDAC inhibition by endogenous short-chain fatty acids like lactate is to promote gene expression at genes associated with HDAC proteins. Therefore, we propose that lactate may be an important transcriptional regulator, linking the metabolic state of the cell to gene transcription

Adenosine deaminases acting on RNA (ADARs): RNA-editing enzymes

Adenosine deaminases acting on RNA (ADARs) were discovered as a result of their ability extensively to deaminate adenosines in any long double-stranded RNA, converting them to inosines. Subsequently, ADARs were found to deaminate adenosines site-specifically within the coding sequences of transcripts encoding ion-channel subunits, increasing the diversity of these proteins in the central nervous system. ADAR1 is now known to be involved in defending the genome against viruses, and it may affect RNA interference. ADARs are found in animals but are not known in other organisms. It appears that ADARs evolved from a member of another family, adenosine deaminases acting on tRNAs (ADATs), by steps including fusion of two or more double-stranded-RNA binding domains to a common type of zinc-containing adenosine-deaminase domain

Genome-wide single-molecule analysis of long-read DNA methylation reveals heterogeneous patterns at heterochromatin that reflect nucleosome organisation

High-throughput sequencing technology is central to our current understanding of the human methylome. The vast majority of studies use chemical conversion to analyse bulk-level patterns of DNA methylation across the genome from a population of cells. While this technology has been used to probe single-molecule methylation patterns, such analyses are limited to short reads of a few hundred basepairs. DNA methylation can also be directly detected using Nanopore sequencing which can generate reads measuring megabases in length. However, thus far these analyses have largely focused on bulk-level assessment of DNA methylation. Here, we analyse DNA methylation in single Nanopore reads from human lymphoblastoid cells, to show that bulk-level metrics underestimate large-scale heterogeneity in the methylome. We use the correlation in methylation state between neighbouring sites to quantify single-molecule heterogeneity and find that heterogeneity varies significantly across the human genome, with some regions having heterogeneous methylation patterns at the single-molecule level and others possessing more homogeneous methylation patterns. By comparing the genomic distribution of the correlation to epigenomic annotations, we find that the greatest heterogeneity in single-molecule patterns is observed within heterochromatic partially methylated domains (PMDs). In contrast, reads originating from euchromatic regions and gene bodies have more ordered DNA methylation patterns. By analysing the patterns of single molecules in more detail, we show the existence of a nucleosome-scale periodicity in DNA methylation that accounts for some of the heterogeneity we uncover in long single-molecule DNA methylation patterns. We find that this periodic structure is partially masked in bulk data and correlates with DNA accessibility as measured by nanoNOMe-seq, suggesting that it could be generated by nucleosomes. Our findings demonstrate the power of single-molecule analysis of long-read data to understand the structure of the human methylome

Transcription factor binding predicts histone modifications in human cell lines

Gene expression in higher organisms is thought to be regulated by a complex network of transcription factor binding and chromatin modifications, yet the relative importance of these two factors remains a matter of debate. Here, we show that a computational approach allows surprisingly accurate prediction of histone modifications solely from knowledge of transcription factor binding both at promoters and at potential distal regulatory elements. This accuracy significantly and substantially exceeds what could be achieved by using DNA sequence as an input feature. Remarkably, we show that transcription factor binding enables strikingly accurate predictions across different cell lines. Analysis of the relative importance of specific transcription factors as predictors of specific histone marks recapitulated known interactions between transcription factors and histone modifiers. Our results demonstrate that reported associations between histone marks and gene expression may be indirect effects caused by interactions between transcription factors and histone-modifying complexes

Transition to naïve human pluripotency mirrors pan-cancer DNA hypermethylation.

Epigenetic reprogramming is a cancer hallmark, but how it unfolds during early neoplastic events and its role in carcinogenesis and cancer progression is not fully understood. Here we show that resetting from primed to naïve human pluripotency results in acquisition of a DNA methylation landscape mirroring the cancer DNA methylome, with gradual hypermethylation of bivalent developmental genes. We identify a dichotomy between bivalent genes that do and do not become hypermethylated, which is also mirrored in cancer. We find that loss of H3K4me3 at bivalent regions is associated with gain of methylation. Additionally, we observe that promoter CpG island hypermethylation is not restricted solely to emerging naïve cells, suggesting that it is a feature of a heterogeneous intermediate population during resetting. These results indicate that transition to naïve pluripotency and oncogenic transformation share common epigenetic trajectories, which implicates reprogramming and the pluripotency network as a central hub in cancer formation