Fig. 2: Reprogrammed plasma metabolic landscape of GC patients compared with non-GC controls.
From: Metabolomic machine learning predictor for diagnosis and prognosis of gastric cancer
a Principal Component Analysis (PCA) of the Cohort 1 (n = 426) plasma-targeted metabolomics data comparing GC patients (colored in purple) and NGC controls (colored in green). b Volcano plot of the detected metabolites in Cohort 1 plasma metabolomics (GC patients versus NGC controls). Significantly differential metabolites are colored in purple (upregulated) and green (downregulated); the others are colored in gray. Two-sided Wilcoxon rank-sum test followed by Benjamini–Hochberg (BH) multiple comparison test with false discovery rate (FDR) < 0.05 and fold change (FC) > 1.25 or < 0.8. c Mfuzz clustering of metabolic trajectories during GC progression using the differential metabolites according to the metabolic changes’ similarity. Representative metabolites of each cluster are presented on the side. d Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways enriched by significantly differential metabolites between GC patients and NGC controls. One-sided Fisher’s exact test followed by BH multiple comparison tests was used and only pathways with FDR < 0.05 were presented. Source data are provided as a Source Data file.
