Biology subjects

Coke, B.

Publications and source records attributed to Coke, B..

3 recordsLinked to original sources

bioRxiv2025

sampleclusteR: A lightweight R package for automated clustering of transcriptomics samples using metadata

BackgroundAs technologies for genome-wide gene-expression analysis continue to develop, the databases storing the resulting data have grown accordingly. The Gene Expression Omnibus (GEO) has grown to over 250,000 data series across more than 25,000 omics platforms. Likewise, ArrayExpress is comprised of over 70,000 transcriptome and methylome datasets. Conducting meta-analyses of data from these databases can be challenging, typically requiring extensive manual grouping of samples to identify experimental groups for comparison. ResultsHere we present sampleclusteR, a lightweight R package which automates the clustering of gene-expression study samples based on their metadata. To demonstrate the utility of the approach to large scale analysis of GEO data series, 275 GEO data series were analysed using the package. sampleclusteR was able to correctly cluster 4694 of the 5081 samples across the 275 data sets in an unsupervised manner. In addition, 250 datasets from ArrayExpress were analysed by the package with 8547 of the 9154 samples being automatically clustered into correct groups. We show how sampleclusteR can be used to automate analysis of gene-expression datasets by conducting a meta-analysis of multiple GEO data series related to the Wnt signaling pathway. sampleclusteR correctly assigned all samples to the correct experimental groups and identified sets of differentially expressed genes for downstream analysis. ConclusionssampleclusteR enables large-scale analysis of data from GEO or ArrayExpress by automating the clustering of both GEO and ArrayExpress metadata tables using text mining of their associated metadata.

bioinformatics↗

bioRxiv2024

Multiomics analysis reveals key immunogenic signatures induced by oncolytic Zika virus infection of paediatric brain tumour cells

Brain tumours disproportionately affect children and are the largest cause of paediatric cancer-related death. Despite decades of research, paediatric standard-of-care therapy still predominantly relies on surgery, radiotherapy, and systemic use of cytotoxic chemotherapeutic agents, all of which can result in debilitating acute and late effects. Novel therapies that engage the immune system, such as oncolytic viruses (OVs), hold great promise and are desperately needed. Zika virus (ZIKV) infects and destroys aggressive cells from paediatric medulloblastoma, atypical teratoid rhabdoid tumour (ATRT), diffuse midline glioma (DMG), ependymoma and neuroblastoma. Despite this, the molecular mechanisms underpinning this therapeutic response are grossly unknown. By profiling the transcriptome across a time-course, we comprehensively investigated the response of paediatric medulloblastoma and ATRT brain tumour cells to ZIKV infection at the transcriptome level for the first time. We observed conserved TNF signalling pathway and cytokine signalling-related signatures following ZIKV infection. We demonstrated that the canonical TNF-alpha signalling pathway is implicated in oncolysis by reducing the viability of ZIKV-infected brain tumour cells and is a likely contributor to the anti-tumoural immune response through TNF-alpha secretion. Our findings have highlighted TNF-alpha as a potential prognostic marker for oncolytic ZIKV virotherapy. Performing a 49-plex ELISA, we generated the most comprehensive ZIKV-infected cancer cell secretome to date. We demonstrated that ZIKV infection induces a clinically relevant and diverse pro-inflammatory brain tumour cell secretome, thus circumventing the need for transgene modification to boost efficacy. We assessed publicly available scRNA-Seq data to model how the ZIKV-induced secretome may (i) interact with medulloblastoma tumour microenvironment (TME) cells via paracrine signalling and (ii) polarise lymph node immune cells via endocrine signalling. Our modelling has provided significant insight into the cytokine response that orchestrates the diverse anti-tumoural immune response during oncolytic ZIKV infection of brain tumours. Our findings have significantly contributed to understanding the molecular mechanisms governing oncolytic ZIKV infection and will help pave the way towards ZIKV-based virotherapy.

cancer biology↗

bioRxiv2024

Knockdown proteomics reveals USP7 as a regulator of cell-cell adhesion in colorectal cancer via AJUBA

Ubiquitin-specific protease 7 (USP7) is implicated in many cancers including colorectal cancer in which it regulates cellular pathways such as Wnt signalling and the P53-MDM2 pathway. With the discovery of small-molecule inhibitors, USP7 has also become a promising target for cancer therapy, and therefore systematically identifying USP7 deubiquitinase interaction partners and substrates has become an important goal. In this study, we selected a colorectal cancer cell model that is highly dependent on USP7 and in which USP7 knockdown significantly inhibited colorectal cancer cell viability, colony formation, and cell-cell adhesion. We then used inducible knockdown of USP7 followed by LC-MS/MS to quantify USP7 dependent proteins. We identified the Ajuba LIM domain protein as an interacting partner of USP7 through co-IP, its substantially reduced protein levels in response to USP7 knockdown, and its sensitivity to the specific USP7 inhibitor FT671. The Ajuba protein has been shown to have oncogenic functions in colorectal and other tumours, including regulation of cell-cell adhesion. We show that both knockdown of USP7 or Ajuba results in a substantial reduction of cell-cell adhesion, with concomitant effects on other proteins associated with adherens junctions. Our findings underlie the role of USP7 in colorectal cancer through its protein interaction networks and show that the Ajuba protein is a component of USP7 protein networks present in colorectal cancer.

systems biology↗