Xiangping Lin

Xiangping Lin

Postdoctoral scholar

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portfolio

publications

Plasma Metabolomics for Discovery of Early Metabolic Markers of Prostate Cancer Based on Ultra-High-Performance Liquid Chromatography-High Resolution Mass Spectrometry

Published in Cancers, 2021

Correct identification of subjects at high risk is critical in the prevention and early screening of prostate cancer (PCa). Analysis of metabolites in biofluids has shown to be a promising method to identify novel PCa biomarkers. To identify potential biomarkers of PCa, we conducted metabolic profiling of pre-diagnosis plasma metabolite profiles from a large prospective male cohort (n = 418), which included 146 males who developed PCa during a 13-year follow-up and 272 matched controls to investigate the relationship with long-term PCa risk. We show metabolite profiles discriminate males who subsequently developed PCa during the follow-up from matched controls with a high degree of accuracy (AU-ROC 0.92) and highlight 10 metabolites associated with a high risk of PCa. These results suggest that the dysregulation of amino acids and sphingolipid metabolism is associated with future risk of PCa.

Recommended citation: Lin X, Lécuyer L, Liu X, Triba MN, Deschasaux-Tanguy M, Demidem A, Liu Z, Palama T, Rossary A, Vasson MP, Hercberg S, Galan P, Savarin P, Xu G, Touvier M. Plasma Metabolomics for Discovery of Early Metabolic Markers of Prostate Cancer Based on Ultra-High-Performance Liquid Chromatography-High Resolution Mass Spectrometry. Cancers (Basel). 2021 Jun 23;13(13):3140. doi: 10.3390/cancers13133140.
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Plasma Metabolomic and Lipidomic Profiling of Metabolic Dysfunction-Associated Fatty Liver Disease in Humans Using an Untargeted Multiplatform Approach

Published in Metabolites, 2022

The objectives of our study were three-fold: (1) describe the relative plasma metabolome and lipidome changes in ST and NASH compared to health control (HC) obese patients; (2) investigate whether plasma metabolomic and lipidomic analysis could help to uncover potential metabolic markers or metabolic pathways associated with MAFLD, if any; (3) identify clinical, metabolomic and lipidomic patterns associated with the disease with the help of a computational multiblock omics framework.

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Paper Title Number 4

Published in GitHub Journal of Bugs, 2024

This paper is about fixing template issue #693.

Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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talks

teaching

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.

Introduction to Bioinformatics in Exposomics

Undergraduate course, University of Oulu, Faculty of Medicine, 2026

Overview

  • Designed and delivered a lecture on chemical exposomics covering mass spectrometry fundamentals, environmental health applications (PCBs, PFAS), and the exposomics framework.
  • Developed a complete, reproducible R workflow using publicly available LC-MS metabolomics data, guiding students through data cleaning, normalization, dimensionality reduction, and visualization.
  • Prepared accompanying lecture slides and annotated teaching materials to support independent student learning.