Biology subjects

Southgate, J.

Publications and source records attributed to Southgate, J..

3 recordsLinked to original sources

bioRxiv2025

Label-free DIA-NN enabled RIME (DIANNeR) reveals glucocorticoid receptor interaction networks in breast, bladder, and blood across normaluntransformed cells, cancer cell lines, and PDXs

Understanding how transcription factors execute tissue-specific programmes requires defining their protein interaction networks in physiologically relevant contexts. However, profiling normal untransformed cells presents fundamental challenges due to intrinsically limited input material. To meet this challenge we integrated data-independent acquisition (DIA), ion mobility separation, and library-free analysis to achieve a 2-fold increase in detection without loss in enrichment. Applied to the glucocorticoid receptor (GR), a ubiquitously expressed nuclear receptor driving pleiotropic responses to standard-of-care anti-inflammatory therapeutics, DIANNeR (DIA-NN enabled RIME) resolves distinct, context-dependent networks across breast, ureter and blood in normal and transformed contexts. Key findings include: detection of a HOXA5-GR interaction in normal epithelium which was undetected in malignant models; an epithelial-restricted SMARCD3-GR interaction with prognostic relevance; and a FOXP3-BCL11B-GR network in primary CD4+ T cell populations undetected by data dependant acquisition (DDA). By defining normal GR tissue interactomes, DIANNeR provides the essential comparator for interpreting network rewiring that drives disease.

cancer biology↗

bioRxiv2025

Biologically-informed machine learning identifies a new clinically-actionable bladder cancer subgroup characterised by NRF2 overactivity

Muscle-invasive bladder cancer is a diverse disease where subtyping is ambiguous. Gene expression profiling followed by unsupervised machine learning (ML) has broadened our understanding of tumour biology, but has failed to provide high-confidence clinically-actionable subgroups. To focus on tissue-specific urothelial biology, we generated co-expression networks from histologically normal bladder, including multiple differentiation states and prioritising transcription factors (TFs). This strategy revealed an emergent set of 98 TFs which we used to stratify The Cancer Genome Atlas bladder cancer cohort, revealing a subdivision of basal tumours characterised by the detoxification and glutaminolysis activity of NRF2, rendering them resistant to standard bladder cancer interventions. These 20 tumours (4.9%) expressed squamous markers, were highly aggressive (15% 2-year survival), and had signatures of active PI3K, MTOR and retinoic acid signalling. Intriguingly, only half of the subgroup had activating mutations in the NRF2/KEAP1 pathway, whilst half of putative driver NFE2L2 mutations were excluded. This highlighted the importance of expression-based classification, particularly as re-analysis of NFE2L2-mutated lung cancer trial data showed only mutations consistent with our classification strategy responded to NRF2 inhibition. Our approach provides the first direct evidence that unsupervised ML can be biologically-informative in identifying clinically-actionable subgroups.

cancer biology↗

bioRxiv2021

BK polyomavirus (BKPyV) is a risk factor for bladder cancer through induction of APOBEC3-mediated genomic damage

Limited understanding of bladder cancer aetiopathology hampers progress in reducing incidence. BK polyomavirus (BKPyV) is a common childhood infection that can be reactivated in the adult kidney leading to viruria. Here we used a mitotically-quiescent, differentiated, normal human urothelial in vitro model to study BKPyV infection. BKPyV infection led to significantly elevated APOBEC3A and APOBEC3B protein, increased deaminase activity and greater numbers of apurinic/apyrimidinic sites in the host urothelial genome. BKPyV Large T antigen (LT-Ag) stimulated re-entry into the cell cycle via inhibition of Retinoblastoma protein and activation of EZH2, E2F1 and FOXM1, which combined to push urothelial cells from G0 into an arrested G2 cell cycle state. The single-stranded DNA displacement loops formed during BKPyV-infection, provide a substrate for APOBEC3 enzymes where they interacted with LT-Ag. These results support reactivated BKPyV infections in adults as a risk factor for bladder cancer in immune-insufficient populations, including transplant patients and the elderly.

cancer biology↗