Rapid Characterization of Candidate Biomarkers for Pancreatic Cancer Using Cell Microarrays (CMAs)
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- 作者：Min-Sik Kim ; Sarada V. Kuppireddy ; Sruthi Sakamuri ; Mukul Singal ; Derese Getnet ; H. C. Harsha ; Renu Goel ; Lavanya Balakrishnan ; Harrys K. C. Jacob ; Manoj K. Kashyap ; Shantal G. Tankala ; Anirban Maitra ; Christine A. Iacobuzio-Donahue ; Elizabeth Jaffee ; Michael G. Goggins ; Victor E. Velculescu ; Ralph H. Hruban ; Akhilesh Pandey
- 刊名：Journal of Proteome Research
- 出版年：2012
- 出版时间：November 2, 2012
- 年：2012
- 卷：11
- 期：11
- 页码：5556-5563
- 全文大小：471K
- 年卷期：v.11,no.11(November 2, 2012)
- ISSN：1535-3907
文摘
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.