Brain tumour genetic network signatures of survival.
Ontology highlight
ABSTRACT: Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic success across neuro-oncology. Gliomas are characterized by distinct combinations of genetic and epigenetic alterations, resulting in complex interactions across multiple molecular pathways. Predicting disease evolution and prescribing individually optimal treatment requires statistical models complex enough to capture the intricate (epi)genetic structure underpinning oncogenesis. Here, we formalize this task as the inference of distinct patterns of connectivity within hierarchical latent representations of genetic networks. Evaluating multi-institutional clinical, genetic and outcome data from 4023 glioma patients over 14 years, across 12 countries, we employ Bayesian generative stochastic block modelling t
SUBMITTER: Ruffle JK
PROVIDER: S-EPMC10629773 | biostudies-literature | 2023 Nov
REPOSITORIES: biostudies-literature
ACCESS DATA