Biology subjects

Sharrocks, A.

Publications and source records attributed to Sharrocks, A..

10 recordsLinked to original sources

bioRxiv2026

ARID1A orchestrates the activity of FOXA1 and AP-2 transcription factors in lobular breast cancer cells

Mutations in components of the SWItch/Sucrose Non-Fermentable (SWI/SNF) chromatin-remodelling complex are among the most common genetic alterations in human cancers, yet their functional consequences are difficult to predict as they are highly context-dependent. ARID1A, a core subunit of the canonical BAF complex, is the most frequently mutated SWI/SNF gene and is recurrently altered in breast cancer, with a notable enrichment in the lobular carcinoma subtype. While previous studies in ductal breast cancer have linked ARID1A loss to deregulated oestrogen receptor (ER) signalling and endocrine resistance through its association with the pioneer factor FOXA1, the role of ARID1A in lobular cancer remains poorly understood. Here, we define the genomic, transcriptomic, and chromatin accessibility landscapes governed by ARID1A in lobular breast cancer cells. We show that ARID1A and its catalytic partner SMARCA4 co-occupy distal regulatory regions enriched for forkhead and AP-2 transcription factor motifs. ARID1A depletion leads predominantly to loss of chromatin accessibility at these putative enhancer regions and downregulation of associated genes, indicating a primary role in maintaining a permissive regulatory landscape. Extensive co-binding and reciprocal dependencies between ARID1A, FOXA1, and AP-2 transcription factors reveal a coordinated regulatory network distinct from that observed in ductal breast cancers. ARID1A loss does not impair ER-mediated transcriptional responses in the lobular subtype but instead alters basal expression of a subset of oestrogen-responsive genes. Importantly, ARID1A, FOXA1, and AP-2 jointly regulate genes implicated in skeletal system development and bone metastasis, mirroring mutational patterns observed in lobular breast cancer patient datasets. These findings highlight a unique ARID1A-centred transcriptional programme in lobular breast cancer with potential implications for metastatic behaviour and therapeutic vulnerability.

Cancer Biology↗

bioRxiv2026

Spartan: Spatial Activation Aware Transcriptomic Analysis Network

Spatial transcriptomics is rapidly advancing toward single-cell-level resolution, revealing complex tissue architectures organized across continuous anatomical gradients. However, accurate identification of spatial domains remains a central computational challenge, as many existing clustering approaches blur anatomical boundaries, merge transitional zones, or fail to resolve localized microstructures. Here we introduce Spartan, an activation-aware multiplex graph framework for high-resolution domain discovery. Spartan integrates spatial topology and Local Spatial Activation (LSA), a neighborhood deviation signal that captures localized transcriptional heterogeneity often attenuated by similarity-based clustering. By jointly modeling cohesion within domains and localized activation structure, Spartan recovers anatomically aligned partitions across spatially resolved transcriptomics technologies including Visium HD, MERFISH, Stereo-seq, and STARmap. We further demonstrate its utility in a high-resolution Visium HD section of developing human esophagus and stomach, where activation-aware graph integration enables precise delineation of complex transitional regions such as the gastroesophageal junction and supports stable multi-scale domain recovery without fragile hyperparameter tuning. Beyond domain identification, Spartan leverages activation-aware structure to detect spatially variable genes associated with localized tissue remodeling. Spartan scales near-linearly with dataset size, providing a robust and interpretable framework for spatial systems-level analysis.

bioinformatics↗

bioRxiv2024

The metaplastic precursor state to oesophageal adenocarcinoma represents reversion to a transient epithelial cell state in the developing oesophagus

In Barretts oesophagus (BO), the precursor of oesophageal adenocarcinoma, the adult stratified squamous epithelium is replaced by a simple columnar phenotype. This has been considered metaplasia; the inappropriate conversion from one adult cell-type to another. In fact, BO could be a reversal of mammalian embryogenesis when the early foregut is first lined by simple columnar epithelium. Exploring this hypothesis has been hampered by inadequate molecular details of human oesophageal development. Here, we adopted single cell transcriptomic and epigenomic approaches to discover and decode the cell types that constitute the initial primitive columnar, transitory and subsequently stratified lower oesophageal epithelium. Each stage is comprised of several previously undefined epithelial sub-populations. HNF4A, a major driver of the BO phenotype, is a prominent transcriptional regulator in the early foregut columnar cells, but not in the later ciliated or stratified cells, and is central to gene regulatory programmes known to be reactivated in BO. Moreover, GWAS susceptibility SNPs for BO mapped to putative regulatory regions in fetal epithelial cells, which are inaccessible in the corresponding adult epithelial cells. Collectively, these data argue that the path to BO involves reactivation of pathways that define primitive fetal epithelial cell states.

developmental biology↗

bioRxiv2024

Massively Parallel Reporter Assays identify enhancer elements in Oesophageal Adenocarcinoma.

Cancer is a disease underpinned by aberrant gene expression. Enhancers are regulatory elements that play a major role in transcriptional control and changes in active enhancer function are likely critical in the pathogenesis of oesophageal adenocarcinoma (OAC). Here, we utilise STARR-seq to profile the genome-wide enhancer landscape in OAC and identify hundreds of high-confidence enhancer elements. These regions are enriched in enhancer-associated chromatin marks, are actively transcribed and exhibit high levels of associated gene activity in OAC cells. These characteristics are maintained in human patient samples, demonstrating their disease relevance. This relevance is further underlined by their responsiveness to oncogenic ERBB2 inhibition and increased activity compared to the pre-cancerous Barretts state. Mechanistically, these enhancers are linked to the core OAC transcriptional network and in particular KLF5 binding is associated with high level activity, providing further support for a role of this transcription factor in defining the OAC transcriptome. Our results therefore uncover a set of enhancer elements with physiological significance, that widen our understanding of the molecular alterations in OAC and point to mechanisms through which response to targeted therapy may occur.

molecular biology↗

bioRxiv2023

Scalable joint non-negative matrix factorisation for paired single cell gene expression and chromatin accessibility data

Single cell multi-modal technologies provide powerful means to simultaneously profile components of the gene regulatory path-ways of individual cells. These are now being employed to study gene regulatory mechanisms in a variety of biological systems. Tailored computational methods for integration and analysis of these data are much-needed with desirable properties in terms of efficiency -to cope with high dimensionality of the data, inter-pretability -for downstream biological discovery and hypothesis generation, and flexibility -to be able to easily incorporate future modalities. Existing methods cover some but not all of the desirable properties for effective integration of these data. Here we present a highly efficient method, intNMF, for representation and integration of single cell multi-modal data using joint non-negative matrix factorisation which can facilitate discovery of linked regulatory topics in each modality. We provide thorough benchmarking using large publicly available datasets against five popular existing methods. intNMF performs comparably against the current state-of-the-art, and provides advantages in terms of computational efficiency and interpretability of discovered regulatory topics in the original feature space. We illustrate this enhanced interpretability in providing insights into cell state changes associated with Alzheimers disease. int-NMF is available as a Python package with extensive documentation and use-cases at https://github.com/wmorgans/quick_intNMF

bioinformatics↗

bioRxiv2023

A spatial map of human liver cirrhosis reveals the patho-architecture and gene signatures associated with cell state transitions during liver disease

Liver fibrosis is a major cause of death worldwide. As a progressive step in chronic liver disease, fibrosis is almost always diagnosed too late with limited treatment options. Here, we uncover the spatial transcriptional landscape driving human liver fibrosis using single nuclei RNA and Assay for Transposase-Accessible Chromatin (ATAC) sequencing to deconvolute multi-cell spatial transcriptomic profiling in human liver cirrhosis. Through multi-modal data integration, we define molecular signatures driving cell state transitions in liver disease and define an impaired cellular response and directional trajectory from hepatocytes to cholangiocytes associated with disease remodelling. We identify pro-fibrogenic signatures in non-parenchymal cell subpopulations co-localised within the fibrotic niche and localise transitional cell states at the scar interface. This combined approach provides a spatial atlas of gene regulation and defines molecular signatures associated liver disease for targeted therapeutics or as early diagnostic markers of progressive liver disease.

genomics↗

bioRxiv2023

ZMYM2 controls transposable element transcription through distinct co-regulatory complexes.

ZMYM2 is a zinc finger transcriptional regulator that plays a key role in promoting and maintaining cell identity. It has been implicated in several diseases such as congenital anomalies of the kidney where its activity is diminished and cancer where it participates in oncogenic fusion protein events. ZMYM2 is thought to function through promoting transcriptional repression and here we provide more evidence to support this designation. Here we studied ZMYM2 function in human cells and demonstrate that ZMYM2 is part of distinct chromatin-bound complexes including the established LSD1-CoREST-HDAC1 corepressor complex. We also identify new functional and physical interactions with ADNP and TRIM28/KAP1. The ZMYM2-TRIM28 complex forms in a SUMO-dependent manner and is associated with repressive chromatin. ZMYM2 and TRIM28 show strong functional similarity and co-regulate a large number of genes. However, there are no strong links between ZMYM2-TRIM28 binding events and nearby individual gene regulation. Instead, ZMYM2-TRIM28 appears to regulate genes in a more regionally defined manner within TADs where it can directly regulate co-associated retrotransposon expression. We find that different types of ZMYM2 binding complex associate with and regulate distinct subclasses of retrotransposons, with ZMYM2-ADNP complexes at SINEs and ZMYM2-TRIM28 complexes at LTR elements. We propose a model whereby ZMYM2 acts directly through retrotransposon regulation, which may then potentially affect the local chromatin environment and associated coding gene expression. Genome browser sessionUCSC browser session containing the peak tracks: http://genome.ucsc.edu/cgi-bin/hgTracks?db=hg19&position=chr1:18,078,462-18,084,961&hide=all&hgct_customText=http://bartzabel.ls.manchester.ac.uk/sharrockslab/yaoyong/ZNF198/index_file_hg19_chipSeq_ZMYM2_final.txt Original ChIP-seq and ATAC-seq data from U2OS cells can be viewed On ArrayExpress at: E-MTAB-12292 (ADNP and TRIM28 ChIP-seq), E-MTAB-12293 (SUMO ChIP-seq) and E-MTAB-12294 (ATAC-seq)

molecular biology↗

bioRxiv2022

Oncogenic ERRB2 signals through the AP-1 transcription factor to control mesenchymal-like properties of oesophageal adenocarcinoma

Oesophageal adenocarcinoma (OAC) is a deadly disease with poor survival statistics and few targeted therapies available. One of the most common molecular aberrations in OAC is amplification or activation of the gene encoding the receptor tyrosine kinase ERBB2, and ERBB2 is targeted in the clinic for this subset of patients. However, the downstream consequences of these ERBB2 activating events are not well understood. Here we used a combination of phosphoproteomics, open chromatin profiling and transcriptome analysis on cell line models and patient-derived datasets to interrogate the molecular pathways operating downstream from ERBB2. Integrated analysis of these data sets converge on a model where dysregulated ERBB2 signalling is mediated at the transcriptional level by the transcription factor AP-1. AP-1 in turn controls cell behaviour by acting on cohorts of genes that regulate cell migration and adhesion, features often associated with EMT. Our study therefore provides a valuable resource for the cancer cell signalling community and reveals novel molecular determinants underlying the dysregulated behaviour of OAC cells.

cancer biology↗

bioRxiv2022

eRNA profiling uncovers the enhancer landscape of oesophageal adenocarcinoma and reveals new deregulated pathways

Cancer is driven by both genetic and epigenetic changes that impact on gene expression profiles and the resulting tumourigenic phenotype. Enhancers are transcriptional regulatory elements that are key to our understanding of how this rewiring of gene expression is achieved in cancer cells. Here we have harnessed the power of RNA-seq data from hundreds of patients with oesophageal adenocarcinoma (OAC) or its precursor state Barretts oesophagus (BO) coupled with open chromatin maps to identify potential enhancer RNAs (eRNAs) and their associated enhancer regions in this cancer. We identify [~]1000 OAC-specific enhancers and use this data to uncover new cellular pathways that are operational in OAC. Among these are enhancers for JUP, MYBL2 and CCNE1, and we show that their activity is required for cancer cell viability. We also demonstrate the clinical utility of our dataset for identifying disease stage and patient prognosis. Our data therefore identify an important set of regulatory elements that enhance our molecular understanding of OAC and point to potential new therapeutic directions.

cancer biology↗

bioRxiv2018

ZIC3 controls the transition from naïve to primed pluripotency.

Embryonic stem cells (ESCs) are pluripotent in nature, meaning that they have the capacity to differentiate into any cell in the body. However, to do so they must transition through a series of intermediate cell states before becoming terminally differentiated. A lot is known about how ESCs maintain their pluripotent state but comparatively less about how they exit this state and begin the transition towards differentiated cells. Here we investigated the earliest events in this transition by determining the changes in the open chromatin landscape as naive mouse ESCs transition to epiblast-like cells (EpiLCs). Motif enrichment analysis of the newly opening regions coupled with expression analysis identified ZIC3 as a potential regulator of this cell fate transition. Chromatin binding and genome-wide transcriptional profiling confirmed ZIC3 as an important regulatory transcription factor and among its targets are genes encoding a number of transcription factors. Among these is GRHL2 which acts through enhancer switching to maintain the expression of a subset of genes from the ESC state. Our data therefore place ZIC3 at the top of a cascade of transcriptional regulators and provide an important advance in our understanding of the regulatory factors governing the earliest steps in ESC differentiation.\n\nHighlightsO_LIThe transcription factor ZIC3 drives gene expression changes in the ESC to EpiLC transition.\nC_LIO_LIExtensive changes occur in the open chromatin landscape as ESCs progress to EpiLCs.\nC_LIO_LIZIC3 activates the expression of a network of transcription factors.\nC_LIO_LIZIC3 activated genes in EpiLCs are upregulated in the post-implantation epiblast.\nC_LI

developmental biology↗