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• W4283277715 abstract "Abstract Purpose To identify metabolites in humans that can be associated with the presence of malignant disturbances of the prostate. Methods In the present study, we selected male patients aged between 46 and 82 years who were considered at risk of prostate cancer due to elevated levels of prostate-specific antigen (PSA) or abnormal results on the digital rectal examination. All selected patients came from two university hospitals (Hospital Universitario del Valle and Clínica Rafael Uribe Uribe) and were divided into 2 groups: cancer (12 patients) and non-cancer (20 patients). Cancer was confirmed by histology, and none of the patients underwent any previous treatment. Standard protocols were applied to all the collected blood samples. The resulting plasma samples were kept at -80°C, and a profile of each one was acquired by nuclear magnetic resonance (NMR) using established experiments. Multivariate analyses were applied to this dataset, first to establish the quality of the data and identify outliers, and then, to model the data. Results We included 12 patients with cancer and 20 without it. Two patients were excluded due to contamination with ethanol. The remaining ones were used to build an Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) model (including 15 non-cancer and 10 cancer patients), with acceptable discrimination (Q2 = 0.33). This model highlighted the role of lactate and lipids, with a positive association of these two metabolites and prostate cancer. Conclusions The primary discriminative metabolites between patients with and without prostate cancer were lactate and lipids. These might be the most reliable biomarkers to trace the development of cancer in the prostate." @default.
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• W4283277715 date "2022-06-01" @default.
• W4283277715 modified "2023-10-14" @default.
• W4283277715 title "Metabolomic Profile in Patients with Malignant Disturbances of the Prostate: An Experimental Approach" @default.
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• W4283277715 doi "https://doi.org/10.1055/s-0042-1744253" @default.
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