Metabolomics Profiling Discriminates Prostate Cancer From Benign Prostatic Hyperplasia Within the Prostate-Specific Antigen Gray Zone - Xu, Bei; Chen, Yan; Chen, Xi; Gan, Lingling; Zhang, Yamei; Feng, Jiafu; Yu, Lin (Frontiers in Oncology, 2021)
Objective: Prostate cancer (PCa) is the second most common male malignancy globally. Prostate-specific antigen (PSA) is an important biomarker for PCa diagnosis. However, it is not accurate in the diagnostic grey zone of 4-10 ng/mL PSA. Here, the performance of serum metabolomic profiling in discriminating PCa patients from benign prostatic hyperplasia (BPH) individuals with a PSA concentration in the range of 4-10 ng/mL was explored. Methods: A total of 220 individuals were enrolled. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) based non-targeted metabolomics method were utilized to characterize serum metabolic profiles of participants. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) methods were used for multivariate analysis. Receiver operating characteristic (ROC) curve analysis was performed to explore the diagnostic value of candidate metabolites in differentiating PCa from BPH. Correlation analysis was conducted to explore the relationship between serum metabolites and common clinically used fasting lipid profiles. Results: Several differential metabolites were identified. The top enriched pathways in PCa subjects such as glycerophospholipid and glycerolipid metabolisms were associated with lipid metabolism. Lipids and lipid-like compounds were the predominant metabolites within the top 50 differential metabolites selected using fold-change threshold >1.5 or <2/3, VIP>1 and Student’s t-test threshold P<0.05. Eighteen lipid or lipid related metabolites were selected including 4-oxoretinol, anandamide, palmitic acid, glycerol 1-hexadecanoate, Dl-dihydrosphingosine, 2-methoxy-6Z-hexadecenoic acid, 3-oxo-nonadecanoic acid, 2-hydroxy-nonadecanoic acid, N-palmitoyl glycine, 2-palmitoylglycerol, hexadecenal, D-erythro-sphingosine C-15, N-methyl arachidonoyl amine, 9-octadecenal, hexadecyl acetyl glycerol, 1-(9Z-pentadecenoyl)-2-eicosanoyl-glycero-3-phosphate, 3Z,6Z,9Z-octadecatriene, and glycidyl stearate. Selected metabolites effectively discriminated PCa from BPH when PSA levels were in the range of 4-10 ng/mL (AUC>0.80). Notably, the 18 identified metabolites were negatively corrected with TC, LDL-C, and Apo-B levels in PCa patients, and some were negatively correlated with HDL-C and Apo-A levels. However, the metabolites were not correlated with TG. Conclusion: The findings of the present study indicate that metabolic reprogramming, mainly lipid metabolism is a key signature of prostate cancer. The 18 lipid or lipid-associated metabolites identified in this study are potential diagnostic markers for differential diagnosis of PCa patients and BPH individuals within a PSA level in the grey zone of 4-10 ng/mL.