Lipid metabolism characterization in gastric cancer identifies signatures to predict prognostic and therapeutic responses.

ABSTRACT: Purpose: Increasing evidence has elucidated the significance of lipid metabolism in predicting therapeutic efficacy. Obviously, a systematic analysis of lipid metabolism characterizations of gastric cancer (GC) needs to be reported. Experimental design: Based on two proposed computational algorithms (TCGA-STAD and GSE84437), the lipid metabolism characterization of 367 GC patients and its systematic relationship with genomic characteristics, clinicopathologic features, and clinical outcomes of GC were analyzed in our study. Differentially expressed genes (DEGs) were identified based on the lipid metabolism cluster. At the same time, we applied single-factor Cox regression and random forest to screen signature genes to construct a prognostic model, namely, the lipid metabolism

SUBMITTER: Zeng J 

PROVIDER: S-EPMC9669965 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature