FIGURE 2.

APOC2 is upregulated in GC patients with PM. (A) KEGG pathway enrichment analysis of DEGs. (B) Lipid metabolism gene expression was negatively correlated with survival prognosis according to TCGA STAD data set (HR = 1.99 [95%IC:1.43–2.78]; log‐rank p value = 3.8×10^–5). GSVA algorithm with the R package GSVA (version 1.36.2) was used to score the gene set for 375 cancer samples in TCGA‐STAD cohort.The normalized score, ranging from 0.1184 to 0.1836, along with the clinical prognosis data of TCGA‐STAD cohort was further submitted to the R package survminer (version 0.4.8) to find the best cutoff point to plot the Kaplan–Meier survival curve. TCGA‐STAD cohort was subdivided into lipid metabolism active group (n = 116) and lipid metabolism inactive group (n = 259) based on the best cutoff point. (C) Volcano plot showed the fold change of identified proteins between PM tissues (n = 5) and GC tissues (n = 5) in the gene set of “regulation of lipid metabolic process.” (D) GSEA analysis revealed that APOC2 was mainly related to lipid absorption, transport, and metabolism of cells based on TCGA STAD database. (E) Western blot analysis of APOC2 protein levels in various GC cell lines and normal gastric epithelial cell line GES‐1. (F) Western blot was used to detect protein expression of APOC2 from eight patients with GC in tumor tissues, adjacent noncancerous gastric tissues (ANTs), and PM tissues. (G) Immunohistochemical (IHC) staining analysis of APOC2 protein levels in patients with GC. Representative images of APOC2 levels in ANTs, GC tissues, and GC PM tissues are shown. (H–K) The overall survival of patients with high or low APOC2 expression in GC tissues. Kaplan–Meier test was used to analyze p values. Data represent mean ± SD, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, based on Student's t‐test