Development of a lipid metabolism-related gene model to predict prognosis in patients with pancreatic cancer

Figure 1 Identification of differential lipid metabolites. A: Score scatter plot of the PCA model for the cancer group vs. the paracarcinoma tissue group; B: Score scatter plot of the orthogonal projections to latent structures-discriminant analysis (OPLS-DA) model for the cancer group vs. the paracancer group; C: Permutation test of the OPLS-DA model for the cancer group vs. the para-cancer group; D: Bar plot for the cancer group vs. the paracancer group. TAG: triacylglycerols; SM: sphingomyelin; SHeXcer: sulfatide; PS: phosphatidylserines; PMeOH: phosphatidylmethanol; PG: phosphatidylglycerols; PEtOH: phosphatidylethanol; PE: phosphatidylethanolamines; PC: phosphatidylcholines; MAG: myelin-associated glycoprotein; LPE: lyso-PE; LPC: lyso-PC; LDGTS: lyso-DGTS; HexCer: hexosylceramide; ACar: acaraben; DGTS: diacylglyceryl trimethylhomoserine; DGDG: digalactosyl diacylglycerols; DAG: diacylglycerols; Cer: ceramide; CE: cholesteryl esters; BMP: bis(monoacylglycerol)phosphate.