Figure 1 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population

Lipidomics analysis. A, Lipid class assignments as a percentage of species reaching P < 0.05 by the Mann–Whitney u test comparing controls with ovarian cancer. B, PLSDA analysis of controls and ovarian cancer (OC) for each cohort. C, Lipid class assignments as a percentage of species reaching P < 0.05 by the Mann Whitney U test comparing controls with early-stage ovarian cancer. D, PLSDA analysis of controls and early-stage ovarian cancer (Early OC) for each cohort. E, Scatter plots depicting relative abundance of representative lipid species across cohorts 1 and 2 for control, ovarian cancer (OC), and early-stage ovarian cancer (EOC). Cer, ceramide; CL, cardiolipin; DG, diacylglycerol; FFA, free fatty acid; GlcCer, glucosylceramide; GM3, GM3 ganglioside; LacCer, lactosylceramide; LPA, lysophosphatidic acid; LPC, lysophosphatidylcholine; LPE, lysophosphatidylethanolamine; LPG, lysophosphatidylglycerol; LPI, lysophosphatidylinositol; LPS, lysophosphatidylserine; MG, monoacylglycerol; PA, phosphatidic acid; PC, phosphatidylcholine; PE, phosphatidylethanolamine; PG, phosphatidylglycerol; PGP, phosphatidylglycerophosphate; PI, phosphatidylinositol; PS, phosphatidylserine; SM, sphingomyelin; TG, triacylglycerol. Statistical testing used Mann Whitney U with significance defined as: ns, P > 0.05; **, P ≤ 0.01; ***, P ≤ 0.001; ****, P ≤ 0.0001.