Development of a fatty acid metabolism (FAM)-related gene signature for prognosis prediction and personalized therapy in lower grade gliomas.

ABSTRACT:

Background

Lower grade gliomas (LGGs) exhibit significant molecular and clinical heterogeneity, challenging accurate prognosis and treatment strategies based on current parameters. Alterations in fatty acid metabolism (FAM) have been implicated in tumor initiation, proliferation, and metastasis. This study investigates the role of FAM in LGGs to enhance patient management.

Methods

Gene expression data from The Cancer Genome Atlas (TCGA) database were analyzed to identify FAM-related genes with differential expression in LGGs. A prognostic model was constructed using Cox regression and least absolute shrinkage and selection operator regression. The model's predictive efficacy was validated using both TCGA test and Chinese Glioma Genome Atlas databases. Functional analyses inc

SUBMITTER: Du F 

PROVIDER: S-EPMC12776228 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature