Serum metabolomics as a novel diagnostic approach for pancreatic cancer
Serum metabolomics as a novel diagnostic approach for pancreatic cancer
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DOI：
10.1007/s11306-010-0224-9
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发表时间：
2010-12-01
期刊：
影响因子：
3.6
通讯作者：
Yoshida, Masaru
中科院分区：
文献类型：
--
作者：
Nishiumi, Shin;Shinohara, Masakazu;Yoshida, Masaru
胰腺癌是癌症相关死亡的主要原因之一，目前治愈的希望不大，因为没有有效的生物标志物用于早期检测。因此，寻找新的生物标志物，将允许胰腺癌的早期检测正在进行中。在这项研究中，通过代谢组学评估了患有III期、IVa期或IVb期疾病的胰腺癌患者（n = 20）和健康志愿者（n = 9）的代谢组之间的差异，代谢组学是组学级联的终点，因此是级联中表型之前的最后一步。在我们的实验条件下，使用气相色谱/质谱（GC/MS），共检测到60种代谢物在血清中，和胰腺癌患者的水平与健康志愿者相比，60种代谢物的18个显着变化。然后，进行主成分分析（PCA），这是多分类分析的基本形式，并且基于60种代谢物的PCA评分图突出了胰腺癌患者和健康志愿者之间的代谢组学差异。还通过偏最小二乘判别分析（PLS-DA）（多分类分析之一）评估了胰腺癌不同阶段之间的差异，我们发现可以区分III期、IVa期和IVb期组。此外，1例I期胰腺癌患者中9种代谢物的值与从III期、IVa期和IVb期胰腺癌患者中获得的值相似。我们的研究结果将有助于发现新的生物标志物，从而通过代谢组学方法早期检测胰腺癌。
Pancreatic cancer is one of the leading causes of cancer-related death, and there is currently little hope of a cure because there are no effective biomarkers for its early detection. Therefore, the search for novel biomarkers that would allow the early detection of pancreatic cancer is ongoing. In this study, the differences between the metabolomes of pancreatic cancer patients with Stage III, Stage IVa, or Stage IVb disease (n = 20) and healthy volunteers (n = 9) were evaluated by metabolomics, which is the endpoint of the Omics cascade and therefore the last step in the cascade before the phenotype. In our experimental conditions using gas chromatography mass spectrometry (GC/MS), a total of 60 metabolites were detected in serum, and the levels of 18 of the 60 metabolites were significantly changed in pancreatic cancer patients compared with those in healthy volunteers. Then, Principal Component Analysis (PCA), which is a basic form of Multiple Classification Analysis, was performed, and the PCA scores plots based on the 60 metabolites highlighted the metabolomic differences between the pancreatic cancer patients and healthy volunteers. The differences between different stages of pancreatic cancer were also assessed by Partial Least Squares Discriminant Analysis (PLS-DA), which is one of Multiple Classification Analysis, and we found that it was possible to discriminate among the Stage III, Stage IVa, and Stage IVb groups. In addition, values of the 9 metabolites in 1 Stage I pancreatic cancer patient were similar to those obtained from the Stage III, Stage IVa, and Stage IVb pancreatic cancer patients. Our findings will aid the discovery of novel biomarkers that allow the early detection of pancreatic cancer by metabolomic approaches.