Gawne, R. T. | bioRxiv Science

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↗

bioRxiv2025

Familial ALS/FTD-associated RNA-Binding deficient TDP-43 mutants cause neuronal and synaptic dysregulation in vitro

TDP-43 is an RNA-binding protein constituting the pathological inclusions observed in [~]95% of ALS and [~]50% of FTD patients. In ALS and FTD, TDP-43 mislocalises to the cytoplasm and forms insoluble, hyperphosphorylated and ubiquitinated aggregates that enhance cytotoxicity and contribute to neurodegeneration. Despite its primary role as an RNA/DNA-binding protein, how RNA-binding deficiencies contribute to disease onset and progression are little understood. Among many identified familial mutations in TDP-43 causing ALS/FTD, only two mutations cause an RNA-binding deficiency, K181E and K263E. In this study, we used CRISPR/Cas9 to knock-in the two disease-linked RNA-binding deficient mutations in SH-SY5Y cells, generating both homozygous and heterozygous versions of the mutant TDP-43 to investigate TDP-43-mediated neuronal disruption. Significant changes were identified in the transcriptomic profiles of these cells, in particular, between K181E homozygous and heterozygous cells, with the most affected genes involved in neuronal differentiation and synaptic pathways. This result was validated in cell studies where the neuronal differentiation efficiency and neurite morphology were compromised in TDP-43 cells compared to unmodified control. Interestingly, divergent neuronal regulation was observed in K181E-TDP-43 homozygous and heterozygous cells, suggesting a more complex signalling network associated with TDP-43 genotypes and expression level which warrants further study. Overall, our data using cell models expressing the ALS/FTD disease-causing RNA-binding deficient TDP-43 mutations at endogenous levels show a robust impact on transcriptomic profiles at the whole gene and transcript isoform level that compromise neuronal differentiation and processing, providing further insights on TDP-43-mediated neurodegeneration.

neuroscience↗