Unveiling fatty acid subtypes: immunometabolic interplay and therapeutic opportunities in gastric cancer.

ABSTRACT:

Background

The goal of this study was to develop a predictive signature using genes associated with fatty acid metabolism to evaluate the prognosis of individuals with gastric cancer (GC).

Method

A total of 24 prognostic-related genes were identified by intersecting differentially expressed genes with 525 fatty acid metabolism (FAM) -related genes and applying a univariate Cox proportional hazards model. By performing consensus clustering of 24 genes associated with FAM, two distinct clusters of GC patients were identified. Subsequently, a risk model was constructed using 39 differentially expressed mRNAs from the two clusters through a random forest model and univariate Cox regression.

Results

An R package, "GCFAMS", was developed to assess GC patients' prognosis bas

SUBMITTER: Liu H 

PROVIDER: S-EPMC12146350 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature