Prediction of gastric cancer metastasis through urinary metabolomic investigation using GC/MS

AIM：To gain new insights into tumor metabolism and to identify possible biomarkers with potential diagnostic values to predict tumor metastasis.METHODS：Human gastric cancer SGC-7901 cells were implanted into 24 severe combined immune deficiency （SCID） mice,which were randomly divided into metastasis...

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Bibliographic Details
Published in:World journal of gastroenterology : WJG 2011-02, Vol.17 (6), p.727-734
Main Authors: Hu, Jun-Duo, Tang, Hui-Qing, Zhang, Qiang, Fan, Jing, Hong, Jing, Gu, Jian-Zhong, Chen, Jin-Lian
Format: Article
Language:English
Subjects:
Animals
Biomarkers, Tumor - urine
Cell Line, Tumor
Gas Chromatography-Mass Spectrometry - methods
Humans
Male
Metabolomics - methods
Mice
Mice, SCID
Neoplasm Metastasis
Neoplasm Transplantation
Original
PCA模型
Principal Component Analysis
Random Allocation
ROC Curve
SGC
Stomach Neoplasms - pathology
Stomach Neoplasms - urine
代谢物
尿
气相色谱/质谱
胃癌
预测值
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Summary:AIM：To gain new insights into tumor metabolism and to identify possible biomarkers with potential diagnostic values to predict tumor metastasis.METHODS：Human gastric cancer SGC-7901 cells were implanted into 24 severe combined immune deficiency （SCID） mice,which were randomly divided into metastasis group （n=8）,non-metastasis group （n=8）,and normal group （n=8）.Urinary metabolomic information was obtained by gas chromatography/mass spectrometry （GC/MS）.RESULTS：There were significant metabolic differences among the three groups （t test,P 0.05）.Ten selected metabolites were different between normal and cancer groups （non-metastasis and metastasis groups）,and seven metabolites were also different between non-metastasis and metastasis groups.Two diagnostic models for gastric cancer and metastasis were constructed respectively by the principal component analysis （PCA）.These PCA models were confirmed by corresponding receiver operating characteristic analysis （area under the curve=1.00）.CONCLUSION：The urinary metabolomic profile is different,and the selected metabolites might be instructive to clinical diagnosis or screening metastasis for gastric cancer.
ISSN:1007-9327
2219-2840
DOI:10.3748/wjg.v17.i6.727