AI Article Synopsis

  • The study applied metabolomics to identify potential biomarkers related to peritoneal metastasis in gastric cancer, analyzing peritoneal lavage fluid from 65 patients.
  • Using techniques like liquid chromatography-mass spectrometry and statistical methods like PCA, the research pinpointed differential metabolites that may indicate a higher risk of metastasis.
  • The findings suggest that several specific metabolites, including TG (54:2) and dodecanol, could serve as biomarkers for detecting peritoneal metastasis in gastric cancer patients, aiding in diagnosis and risk assessment.

Article Abstract

Background And Objective: Metabolomics has recently been applied in the field of oncology. In this study, we aimed to use metabolomics to explore biomarkers in peritoneal metastasis of gastric cancer.

Methods: Peritoneal lavage fluid (PLF) of 65 gastric cancer patients and related clinical data were collected from the First Hospital of Jilin University. The metabolic components were identified by liquid chromatography-mass spectrometry (LC-MS). Total ion current (TIC) spectra, principal component analysis (PCA), and the Student's -test were used to identify differential metabolites in PLF. A support vector machine (SVM) was used to screen the differential metabolites in PLF with a weight of 100%. Cluster analysis was used to evaluate the similarity between samples. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic ability of the metabolites. Univariate and multivariate logistic regression analyses were used to identify potential risk factors for peritoneal metastasis of gastric cancer.

Results: We found the differential levels of PLF metabolites by LC-MS, TIC spectra, PCA and the -test. Cluster analysis showed the co-occurrence of metabolites in the peritoneal metastasis group (p<0.05). ROC analysis showed the diagnostic ability of metabolites (p<0.05). Univariate and multivariate logistic regression analyses showed the potential independent risk factors for peritoneal metastasis in gastric cancer patients (p<0.05).

Conclusion: Through the statistical analysis of metabolomics, we found that TG (54:2), G3P, α-aminobutyric acid, α-CEHC, dodecanol, glutamyl alanine, 3-methylalanine, sulfite, CL (63:4), PE-NMe (40:5), TG (53:4), retinol, 3-hydroxysterol, tetradecanoic acid, MG (21:0/0:0/0:0), tridecanoic acid, myristate glycine and octacosanoic acid may be biomarkers for peritoneal metastasis of gastric cancer.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7394602PMC
http://dx.doi.org/10.2147/OTT.S245663DOI Listing

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