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Metabolic markers in blood can separate prostate cancer from benign prostatic hyperplasia.

ABSTRACT: An individualised risk-stratified screening for prostate cancer (PCa) would select the patients who will benefit from further investigations as well as therapy. Current detection methods suffer from low sensitivity and specificity, especially for separating PCa from benign prostatic conditions. We have investigated the use of metabolomics analyses of blood samples for separating PCa patients and controls with benign prostatic hyperplasia (BPH).Blood plasma and serum samples from 29 PCa patient and 21 controls with BPH were analysed by metabolomics analysis using magnetic resonance spectroscopy, mass spectrometry and gas chromatography. Differences in blood metabolic patterns were examined by multivariate and univariate statistics.By combining results from different methodological platforms, PCa patients and controls were separated with a sensitivity and specificity of 81.5% and 75.2%, respectively.The combined analysis of serum and plasma samples by different metabolomics measurement techniques gave successful discrimination of PCa and controls, and provided metabolic markers and insight into the processes characteristic of PCa. Our results suggest changes in fatty acid (acylcarnitines), choline (glycerophospholipids) and amino acid metabolism (arginine) as markers for PCa compared with BPH.

SUBMITTER: Giskeodegard GF

PROVIDER: S-EPMC4702000 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Metabolic markers in blood can separate prostate cancer from benign prostatic hyperplasia.

Giskeødegård Guro F GF Hansen Ailin Falkmo AF Bertilsson Helena H Gonzalez Susana Villa SV Kristiansen Kåre Andre KA Bruheim Per P Mjøs Svein A SA Angelsen Anders A Bathen Tone Frost TF Tessem May-Britt MB

British journal of cancer 20151203 12

<h4>Background</h4>An individualised risk-stratified screening for prostate cancer (PCa) would select the patients who will benefit from further investigations as well as therapy. Current detection methods suffer from low sensitivity and specificity, especially for separating PCa from benign prostatic conditions. We have investigated the use of metabolomics analyses of blood samples for separating PCa patients and controls with benign prostatic hyperplasia (BPH).<h4>Methods</h4>Blood plasma and ...[more]

PMID: 26633561

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Project description: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.

Dataset Information

Metabolic markers in blood can separate prostate cancer from benign prostatic hyperplasia.

Publications

Metabolic markers in blood can separate prostate cancer from benign prostatic hyperplasia.

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