A prognostic model correlated with fatty acid metabolism in Ewing's sarcoma based on bioinformatics analysis.

ABSTRACT:

Background

Ewing's sarcoma (EWS) is a highly aggressive malignant tumor that originates from bone or soft tissue. To date, there is no established prognostic model for EWS tumor. This study aims to identify prognostic genes and develop a predictive model associated with fatty acid metabolism in EWS using bioinformatics analysis.

Results

We analyzed the GSE17679 dataset and identified 25 differentially expressed genes related to fatty acid metabolism in EWS. A risk model composed of ACADM, ADH5, ACSL1, ELOVL4, ECI1, PPT1, and ACOT7 gene signatures was constructed. The AUC values at 3 and 5 years were both ≥0.7, indicating good predictive accuracy. GSVA analysis revealed significant differences in fatty acid metabolism pathway enrichment between high- and low-risk groups. Diff

SUBMITTER: Chen X 

PROVIDER: S-EPMC12355353 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature