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Urinary Metabolomic Analysis of Prostate Cancer by UPLC-FTMS and UPLC-Ion Trap MSn

  • Chien Lun Chen
  • , Yi Ting Chen
  • , Wen Yu Liao
  • , Yu Sun Chang
  • , Jau Song Yu
  • , Bao Rong Juo*
  • *Corresponding author for this work
  • Chang Gung University

Research output: Contribution to journalJournal Article peer-review

6 Scopus citations

Abstract

Accumulative evidence suggests metabolic disorders correlate with prostate cancer. Metabolic profiling of urine allows the measurement of numerous metabolites simultaneously. This study set up a metabolomic platform consisting of UPLC-FTMS and UPLC-ion trap MSn for urine metabolome analysis. The platform improved retention time, mass accuracy, and signal stability. Additionally, the product ion spectrum obtained from ion trap MSn facilitated structure elucidation of candidate metabolites, especially when authentic standards were not available. Urine samples from six hernia patients and six BPH patients were used for the initial establishment of the analytic platform. This platform was further employed to analyze the urine samples of 27 PCa and 49 BPH patients. Choosing the upper and lower 16% of metabolites, 258 metabolite candidates were selected. Twenty-four of them with AUC values larger than 0.65 were further selected. Eighteen of the twenty-four features can be matched in METLIN and HMDB. Eleven of the eighteen features can be interpreted by MSn experiments. They were used for the combination achieving the best differential power. Finally, four metabolites were combined to reach the AUC value of 0.842 (CI 95, 0.7559 to 0.9279). This study demonstrates the urinary metabolomic analysis of prostate cancer and sheds light on future research.

Original languageEnglish
Article number2270
JournalDiagnostics
Volume13
Issue number13
DOIs
StatePublished - 04 07 2023

Bibliographical note

Publisher Copyright:
© 2023 by the authors.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • biomarker
  • prostate cancer
  • urinary metabolomics

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