Prediction Of Gastric Cancer Metastasis Through Urinarymetabolomic Investigation

AIM: To gain new insights into tumor metabolism and to identify possible biomarkers with potential diagnostic value. We also investigated whether possible biomarkers could predict tumor metastasis.METHODS: Human gastric cancer SGC-7901 cells were implanted into twenty-four SCID mice, which randomly divided into metastasis group (n=8), non-metastasis group (n=8), and normal group (n=8). Urinary metabolomic information was investigated by GC/MS.RESULTS: These three groups had significant metabolic differences (T test, P<0.05). Ten metabolites were selected differently between normal and cancer group (non-metastasis and metastasis group), and seven metabolites were also found differently between non-metastasis and metastasis group. Two diagnostic models for gastric cancer and metastasis, respectively, were constructed by principal component analysis (PCA). These PCA models were confirmed by corresponding receiver operating characteristic (ROC) analysis (AUC=1.00).CONCLUSION: The urinary metabolomic profiling of each group is different, and the selected metabolites might be instructive to clinical diagnosis or screening metastasis for gastric cancer.