Development and pan-cancer validation of an epigenetics-based random survival forest model for prognosis prediction and drug response in OS.

ABSTRACT:

Background

Osteosarcoma (OS) exhibits significant epigenetic heterogeneity, yet its systematic characterization and clinical implications remain largely unexplored.

Methods

We analyzed single-cell transcriptomes of five primary OS samples, identifying cell type-specific epigenetic features and their evolutionary trajectories. An epigenetics-based Random Survival Forest (RSF) model was constructed using 801 curated epigenetic factors and validated in multiple independent cohorts.

Results

Our analysis revealed distinct epigenetic states in the OS microenvironment, with particular activity in OS cells and osteoclasts. The RSF model identified key predictive genes including OLFML2B, ACTB, and C1QB, and demonstrated broad applicability across multiple cancer types. Risk st

SUBMITTER: Yin C 

PROVIDER: S-EPMC11803151 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature