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利用细胞微阵列(CMAs)快速鉴定胰腺癌候选生物标志物。

Rapid characterization of candidate biomarkers for pancreatic cancer using cell microarrays (CMAs).

机构信息

McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.

出版信息

J Proteome Res. 2012 Nov 2;11(11):5556-63. doi: 10.1021/pr300483r. Epub 2012 Oct 11.

Abstract

Tissue microarrays have become a valuable tool for high-throughput analysis using immunohistochemical labeling. However, the large majority of biochemical studies are carried out in cell lines to further characterize candidate biomarkers or therapeutic targets with subsequent studies in animals or using primary tissues. Thus, cell line-based microarrays could be a useful screening tool in some situations. Here, we constructed a cell microarray (CMA) containing a panel of 40 pancreatic cancer cell lines available from American Type Culture Collection in addition to those locally available at Johns Hopkins. As proof of principle, we performed immunocytochemical labeling of an epithelial cell adhesion molecule (Ep-CAM), a molecule generally expressed in the epithelium, on this pancreatic cancer CMA. In addition, selected molecules that have been previously shown to be differentially expressed in pancreatic cancer in the literature were validated. For example, we observed strong labeling of CA19-9 antigen, a prognostic and predictive marker for pancreatic cancer. We also carried out a bioinformatics analysis of a literature curated catalog of pancreatic cancer biomarkers developed previously by our group and identified two candidate biomarkers, HLA class I and transmembrane protease, serine 4 (TMPRSS4), and examined their expression in the cell lines represented on the pancreatic cancer CMAs. Our results demonstrate the utility of CMAs as a useful resource for rapid screening of molecules of interest and suggest that CMAs can become a universal standard platform in cancer research.

摘要

组织微阵列已成为使用免疫组织化学标记进行高通量分析的有价值的工具。然而,绝大多数生化研究都是在细胞系中进行的,以便进一步对候选生物标志物或治疗靶点进行特征描述,然后在动物或使用原发性组织中进行后续研究。因此,基于细胞系的微阵列在某些情况下可能是一种有用的筛选工具。在这里,我们构建了一个细胞微阵列 (CMA),其中包含了美国典型培养物保藏中心提供的 40 种胰腺癌细胞系,以及约翰霍普金斯大学提供的本地细胞系。作为原理验证,我们对这种胰腺癌 CMA 上的上皮细胞黏附分子 (Ep-CAM) 进行了免疫细胞化学标记,这是一种通常在上皮细胞中表达的分子。此外,我们还验证了文献中先前证明在胰腺癌中表达差异的选定分子。例如,我们观察到 CA19-9 抗原的强烈标记,CA19-9 抗原是胰腺癌的预后和预测标志物。我们还对我们小组之前开发的胰腺癌生物标志物文献编目进行了生物信息学分析,鉴定了两个候选生物标志物,HLA Ⅰ类和跨膜蛋白酶丝氨酸 4 (TMPRSS4),并在胰腺癌 CMA 上代表的细胞系中检查了它们的表达。我们的结果表明 CMA 可作为快速筛选感兴趣分子的有用资源,并且表明 CMA 可以成为癌症研究的通用标准平台。

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