Basic & Clinical Medicine ›› 2025, Vol. 45 ›› Issue (6): 793-799.doi: 10.16352/j.issn.1001-6325.2025.06.0793

• Original Articles • Previous Articles     Next Articles

Non-targeted metabolomics screening for serum biomarkers in colorectal cancer patients

WANG Aiwei1, LIU Jiaqi2, LIU Xiaoyan1, SUN Haidan1, GUO Zhengguang1, HE Chengyan2, SUN Wei1*   

  1. 1. Department of Pharmacology, Institute of Basic Medical Sciences CAMS, School of Basic Medicine PUMC, Beijing 100005;
    2. Department of Clinical Laboratory, China-Japan Union Hospital of Jilin University, Changchun 130033, China
  • Received:2025-03-12 Revised:2025-04-03 Online:2025-06-05 Published:2025-05-26

Abstract: Objective To identify potential serum metabolic biomarkers in colorectal cancer (CRC) patients using untargeted metabolomics and to evaluate their diagnostic and staging value. Methods Serum samples from 100 healthy controls and 100 CRC patients were analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). After data normalization, differential metabolites were screened using multivariate statistical analyses (PCA, OPLS-DA) and subjected to pathway enrichment analysis. Diagnostic performance was assessed via univariate and multivariate regression, while Mfuzz clustering was applied to analyze stage-related metabolites (Ⅰ-Ⅳ). Results A total of 432 metabolites were identified with 59 showing significant alterations. Starch and sucrose metabolism and glycerophospholipid metabolism pathways were significantly enriched. A three-metabolite panel (4,8- dimethylnonanoyl carnitine, 9,13-dihydroxy-4-megastigmen-3-one 9-glucoside and C17 sphingosine-1-phosphate) achieved a diagnostic AUC of 0.907, while L-Carnitine and L-Norleucine showed an AUC of 0.776 in staging analysis. Conclusions Specific serum metabolite panel exhibit high diagnostic accuracy, and dysregulated metabolic pathways are associated with CRC progression, suggesting their potential value as biomarkers.

Key words: colorectal cancer, untargeted metabolomics, UPLC-MS, serum biomarkers

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