Literature DB >> 35444465

1H-NMR Based Metabolomics Technology Identifies Potential Serum Biomarkers of Colorectal Cancer Lung Metastasis in a Mouse Model.

Junfei Zhang1, Yuanxin Du2,3, Yongcai Zhang4, Yanan Xu5, Yanying Fan2,3, Yan Li2,3.   

Abstract

Background: Lung metastasis is a common metastasis site of colorectal cancer which largely reduces the quality of life and survival rates of patients. The discovery of potential novel diagnostic biomarkers is very meaningful for the early diagnosis of colorectal cancer with lung metastasis.
Methods: In the present study, the metabonomic profiling of serum samples of lung metastasis mice was analyzed by 1H-nuclear magnetic resonance (1H-NMR). Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to elucidate the distinguishing metabolites between different groups, and all achieved excellent separations, which indicated that metastatic mice could be differentiated from control mice based on the metabolic profiles at serum levels. Furthermore, during lung metastasis of colorectal cancer, metabolic phenotypes changed significantly, and some of metabolites were identified.
Results: Among these metabolites, approximately 15 were closely associated with the lung metastasis process. Pathway enrichment analysis results showed deregulation of metabolic pathways participating in the process of lung metastasis, such as synthesis and degradation of ketone bodies pathway, amino acid metabolism pathway and pyruvate metabolism pathway.
Conclusion: The present study demonstrated the metabolic disturbances of serum samples of mice during the lung metastasis process of colorectal cancer and provides potential diagnostic biomarkers for the disease.
© 2022 Zhang et al.

Entities:  

Keywords:  1H-NMR; biomarkers; colorectal cancer; metabolomics; metastasis

Year:  2022        PMID: 35444465      PMCID: PMC9015044          DOI: 10.2147/CMAR.S348981

Source DB:  PubMed          Journal:  Cancer Manag Res        ISSN: 1179-1322            Impact factor:   3.602


  49 in total

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Journal:  EMBO J       Date:  2019-09-16       Impact factor: 11.598

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