Vlad Ungureanu

3 weeks ago | biorxiv.org | Vlad Ungureanu |Richard Gawne |Simon Baker |Pontus Eriksson

AbstractMuscle-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).