使用多平台人血清代谢组学系统进行胰腺癌筛查。
Pancreatic cancer screening using a multiplatform human serum metabolomics system.
作者信息
Sakai Arata, Suzuki Makoto, Kobayashi Takashi, Nishiumi Shin, Yamanaka Kodai, Hirata Yuichi, Nakagawa Takashi, Azuma Takeshi, Yoshida Masaru
机构信息
Division of Gastroenterology, Department of Internal Medicine, Kobe University Graduate School of Medicine, 7-5-1, Kusunoki-cho, Chuo-ku, Kobe, Hyogo 650-0017, Japan.
Division of Metabolomics Research, Department of Internal Related, Kobe University Graduate School of Medicine, 7-5-1, Kusunoki-cho, Chuo-ku, Kobe, Hyogo 650-0017, Japan.
出版信息
Biomark Med. 2016 Jun;10(6):577-86. doi: 10.2217/bmm-2016-0020. Epub 2016 May 12.
AIM
To examine a novel screening method for pancreatic cancer involving gas chromatography/mass spectrometry and liquid chromatography/mass spectrometry-based metabolomics analysis.
MATERIALS & METHODS: Sera from pancreatic cancer patients (n = 59) and healthy volunteers (n = 59) were allocated to the training set or validation set. Serum metabolome analysis was carried out using our multiplatform metabolomics system. A diagnostic model was constructed using a two-phase screening method that was newly advocated.
RESULTS
When the training set was used, the constructed diagnostic model exhibited high sensitivity (100%) and specificity (80%) for pancreatic cancer. When the validation set was used, the model displayed high sensitivity (84.1%) and specificity (84.1%).
CONCLUSION
We successfully developed a diagnostic model for pancreatic cancer using a multiplatform serum metabolomics system.
目的
研究一种基于气相色谱/质谱联用和液相色谱/质谱联用的代谢组学分析的新型胰腺癌筛查方法。
材料与方法
将胰腺癌患者（n = 59）和健康志愿者（n = 59）的血清分配到训练集或验证集。使用我们的多平台代谢组学系统进行血清代谢组分析。采用新提倡的两阶段筛查方法构建诊断模型。
结果
当使用训练集时，构建的诊断模型对胰腺癌表现出高灵敏度（100%）和特异性（80%）。当使用验证集时，该模型显示出高灵敏度（84.1%）和特异性（84.1%）。
结论
我们成功地使用多平台血清代谢组学系统开发了一种胰腺癌诊断模型。
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