Ontology highlight
ABSTRACT: Background
The 5-year survival rate of oesophageal squamous cell carcinoma (ESCC) is approximately 20%. The prognosis and drug response exhibit substantial heterogeneity in ESCC, impeding progress in survival outcomes. Our goal is to identify a signature for tumour subtype classification, enabling precise clinical treatments.Methods
Utilising pre-treatment multi-omics data from an ESCC dataset (n = 310), an enhancer methylation-eRNA-target gene regulation network was constructed and validated by in vitro experiments. Four machine learning methods collectively identified core target genes, establishing an Enhancer Demethylation-Regulated Gene Score (EDRGS) model for classification. The molecular function of EDRGS subtyping was explored in scRNA-seq (n = 60) and bulk-seq (n =
SUBMITTER: Gao W
PROVIDER: S-EPMC11259699 | biostudies-literature | 2024 Jul
REPOSITORIES: biostudies-literature