Metabolomics Profiling Discriminates Prostate Cancer From Benign Prostatic Hyperplasia Within the Prostate-Specific Antigen Gray Zone

Abstract

ObjectiveProstate 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 gray zone of 4–10 ng/ml of PSA. In the current study, the performance of serum metabolomics 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.MethodsA total of 220 individuals, including patients diagnosed with PCa and BPH within PSA levels in the range of 4–10 ng/ml and healthy controls, were enrolled in the study. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based non-targeted metabolomics method was 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.ResultsSeveral 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, variable importance in projection (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 (area under the curve (AUC) > 0.80). Notably, the 18 identified metabolites were negatively corrected with total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and Apo-B levels in PCa patients; and some were negatively correlated with high-density lipoprotein cholesterol (HDL-C) and Apo-A levels. However, the metabolites were not correlated with triglycerides (TG).ConclusionThe findings of the present study indicate that metabolic reprogramming, mainly lipid metabolism, is a key signature of PCa. 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 gray zone of 4–10 ng/ml.

Relevance of emerging metabolomics-based biomarkers of prostate cancer: a systematic review

“…Stringent statistical analysis showed that the following 18 lipid or lipid-related metabolites were able to differentiate PC from BPH efficiently and had AUC >0.80: 4-oxoretinol, anandamide, palmitic acid, glycerol 1-hexadecanoate, dl -dihydrosphingosine, 2-methoxy-6 Z -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-(9 Z pentadecenoyl)-2-eicosanoyl- glycero -3-phosphate, 3 Z ,6 Z ,9 Z -octadecatriene and glycidyl stearate (Ref. 47).…”

From Omics to Multi-Omics Approaches for In-Depth Analysis of the Molecular Mechanisms of Prostate Cancer

“…Comparison between prostate cancer tumor and normal adjacent tissue reveals high accumulation of cholesteryl esters [ 234 ]. Another, larger effort compared prostate cancer and benign prostate hyperplasia samples in 220 patients and also showed marked modifications in pathways linked to lipid metabolism [ 235 ]. Increased abundance of monounsaturated lipids and of elongated fatty-acid chains in phosphatidylinositol and phosphatidylserine lipids are noticed in prostate tumors, and importantly, phospholipid composition is altered in patients with response to AR inhibition [ 236 ].…”

Diagnostic Possibilities of PET/CT with 18F-PSMA in Patients with Suspected Prostate Cancer

“…Проблема в том, что данные симптомы не специфичны для РПЖ и могут возникать при других заболеваниях -уретрите, простатите, доброкачественной гиперплазии предстательной железы (ДГПЖ) и прочих [3]. Аналогичная ситуация складывается в отношении уровня простатического специфического антигена (ПСА): повышение может быть обусловлено воспалительными изменениями, ДГПЖ, инфарктом простаты, проведением пальцевого ректального исследования и рядом других факторов [4]. При уровне ПСА > 10 нг/мл РПЖ выявляется более чем у 60% пациентов, а при уровне ПСА в так называемой «серой зоне» (2-10 нг/мл) -только у 25-40% пациентов [5].…”