Identification of potential metabolite markers for colon cancer and rectal cancer using serum metabolomics

Background To determine the metabolic characteristics of patients with colon cancer (CC) and rectal cancer (RC) using gas chromatography‐mass spectrometry (GC‐MS)‐based metabolomics. Methods In this study, serum samples were collected from 22 CC patients and 23 RC patients preoperatively and postope...

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Bibliographic Details
Published in:Journal of clinical laboratory analysis 2020-08, Vol.34 (8), p.e23333-n/a
Main Authors: Wu, Jianping, Wu, Minyi, Wu, Qianxia
Format: Article
Language:English
Subjects:
Antigens
biomarker
Colon cancer
Colorectal cancer
Diagnosis
Discriminant analysis
Gallbladder diseases
Gas chromatography
Isoleucine
Mannose
Mass spectroscopy
Medical prognosis
Medical screening
Metabolism
Metabolites
Metabolomics
Mortality
Principal components analysis
Quality control
rectal cancer
Rectum
Software
Statistical analysis
Studies
Temperature
Tryptophan
Urea
Uric acid
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Summary:Background To determine the metabolic characteristics of patients with colon cancer (CC) and rectal cancer (RC) using gas chromatography‐mass spectrometry (GC‐MS)‐based metabolomics. Methods In this study, serum samples were collected from 22 CC patients and 23 RC patients preoperatively and postoperatively and 45 healthy volunteers (HVs), and subjected to metabolomics analysis by GC‐MS. Differential metabolites in the preoperative RC and CC samples and HVs were identified as potential biomarkers and evaluated for their utilities by receiver operating characteristic analyses. Results The different metabolic markers between CC and RC patients were identified, which may assist in distinguishing the two types of cancers. The area under the curve (AUC) was 0.805 for combination of d‐glucose and d‐mannose for CC diagnosis, and 0.889 for combination of 2‐aminobutanoic acid, 3‐hydroxypyridine, d‐glucose, d‐mannose, isoleucine, l‐tryptophan, urea, and uric acid for RC diagnosis. The combinations of metabolite markers showed a better predictability than CEA and CA199 two commonly used protein markers for CRC diagnosis in clinical practice. Combining the metabolite markers with these two protein markers effectively improved the diagnostic accuracy with the AUC reaching 0.936 and 0.937 for CC and RC diagnosis, respectively. Conclusions Metabolic profiles are different in the blood samples between CC and RC patients. The study has established a panel of metabolic markers as a predictive and multiplexing signature for CC and RC diagnosis.
ISSN:0887-8013
1098-2825
DOI:10.1002/jcla.23333