Medical College, Soochow University, Suzhou 215213, Jiangsu Province, China.
World J Gastroenterol. 2011 Feb 14;17(6):727-34. doi: 10.3748/wjg.v17.i6.727.
To gain new insights into tumor metabolism and to identify possible biomarkers with potential diagnostic values to predict tumor metastasis.
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).
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).
The urinary metabolomic profile is different, and the selected metabolites might be instructive to clinical diagnosis or screening metastasis for gastric cancer.
深入了解肿瘤代谢，并寻找具有潜在诊断价值的生物标志物，以预测肿瘤转移。
将人胃癌 SGC-7901 细胞植入 24 只重症联合免疫缺陷（SCID）小鼠中，随机分为转移组（n=8）、非转移组（n=8）和正常组（n=8）。采用气相色谱/质谱（GC/MS）法获取尿代谢组学信息。
三组间存在明显的代谢差异（t 检验，P<0.05）。正常组与癌症组（非转移组与转移组）之间有 10 种代谢物存在显著差异，非转移组与转移组之间也有 7 种代谢物存在显著差异。通过主成分分析（PCA）分别构建了胃癌和转移的两个诊断模型。这些 PCA 模型通过相应的接受者操作特征分析（曲线下面积=1.00）得到了验证。
尿代谢组图谱不同，所选代谢物可能有助于临床诊断或筛选胃癌转移。
