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

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 1 H-nuclear magnetic resonance ( 1 H-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.

Differential Correlations Informed Metabolite Set Enrichment Analysis to Decipher Metabolic Heterogeneity of Disease

“…Also, there are some pathways that are identified in two clusters, which cannot be selected if the whole cancer group is compared with the controls. For example, biosynthesis of unsaturated fatty acids , a pathway of interest in colorectal cancer, is selected for both clusters-1 and clusters-2, but the pathway is not selected if the whole cancer group is compared with the controls . The other pathways of interest that are selected by the present heterogeneity analysis include alpha-linolenic acid metabolism , which affects the mitochondrial protein import pathway and the citric acid cycle pathway; thus, it is of interest as a potential target for colorectal cancer prevention .…”

“…For example, biosynthesis of unsaturated fatty acids, a pathway of interest in colorectal cancer, is selected for both clusters-1 and clusters-2, but the pathway is not selected if the whole cancer group is compared with the controls. 31 The other pathways of interest that are selected by the present heterogeneity analysis include alpha-linolenic acid metabolism, which affects the mitochondrial protein import pathway and the citric acid cycle pathway; thus, it is of interest as a potential target for colorectal cancer prevention. 32 The present results showed that for a similar disease the dci-MSEA-based heterogeneity analysis may highlight samples from different clusters with their own potential disease-related mechanism.…”