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Default NMR-based metabolomics analysis identifies discriminatory metabolic disturbances in tissue and biofluid samples for progressive prostate cancer.

NMR-based metabolomics analysis identifies discriminatory metabolic disturbances in tissue and biofluid samples for progressive prostate cancer.

Related Articles NMR-based metabolomics analysis identifies discriminatory metabolic disturbances in tissue and biofluid samples for progressive prostate cancer.

Clin Chim Acta. 2020 Feb;501:241-251

Authors: Zheng H, Dong B, Ning J, Shao X, Zhao L, Jiang Q, Ji H, Cai A, Xue W, Gao H

Abstract
BACKGROUND: Prostate cancer (PCa) is one of the most common cancers in men, but its metabolic characteristics during tumor progression are still far from being fully understood.
METHODS: The metabolic profiles of matched tissue, serum and urine samples from the same patients were analyzed using a 1H NMR-based metabolomics approach. We identified several important metabolites that significantly altered at different stages of PCa, including benign prostatic hyperplasia (BPH), early PCa (EPC), advanced PCa (APC), metastatic PCa (MPC) and castration-resistant PCa (CRPC). Metabolic correlation networks among tissue, serum and urine samples were examined using Pearson's correlation.
RESULTS: The changes in metabolic phenotypes during the progression of PCa were more noticeable in tissue samples when compared with serum and urine samples. Herein we identified a series of important metabolic disturbances, including decreased trends of citrate, creatinine, acetate, leucine, valine, glycine, lysine, histidine, glutamine and choline as well as increased trends of uridine and formate. These metabolites are mainly implicated in energy metabolism, amino acid metabolism, choline and fatty acid metabolism as well as uridine metabolism. We also found that energy metabolism in tumor tissues was positively associated with amino acid metabolism in serum and urine. Additionally, CRPC patients had a peculiar metabolic phenotype, especially decreased amino acid metabolism in serum.
CONCLUSIONS: The present study characterizes metabolic disturbances in both tissue and biofluid samples during PCa progression and provides potential diagnostic biomarkers and therapeutic targets for PCa.


PMID: 31758937 [PubMed - indexed for MEDLINE]



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