This Article Full Text Full Text (PDF) Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Copyright Permission Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Eszlinger, M. Articles by Paschke, R. Search for Related Content PubMed PubMed Citation Articles by Eszlinger, M. Articles by Paschke, R.

Perspectives and Limitations of Microarray-Based Gene Expression Profiling of Thyroid Tumors

Markus Eszlinger, Knut Krohn, Aleksandra Kukulska, Barbara Jarzb and Ralf Paschke

III. Medical Department (M.E., K.K., R.P.), University of Leipzig, D-04103 Leipzig, Germany; Interdisciplinary Center for Clinical Research Leipzig (K.K.), D-04103 Leipzig, Germany; and Department of Nuclear Medicine and Endocrine Oncology (A.K., B.J.), Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, 44-100 Gliwice, Poland

Correspondence: Address all correspondence and requests for reprints to: R. Paschke, M.D., III. Medical Department, University of Leipzig, Ph.-Rosenthal-Str. 27, D-04103 Leipzig, Germany. E-mail: pasr{at}medizin.uni-leipzig.de

Microarray technology has become a powerful tool to analyze the gene expression of tens of thousands of genes simultaneously. Microarray-based gene expression profiles are available for malignant thyroid tumors (i.e., follicular thyroid carcinoma, and papillary thyroid carcinoma), and for benign thyroid tumors (such as autonomously functioning thyroid nodules and cold thyroid nodules). In general, the two main foci of microarray investigations are improved understanding of the pathophysiology/molecular etiology of thyroid neoplasia and the detection of genetic markers that could improve the differential diagnosis of thyroid tumors. Their results revealed new features, not known from one-gene studies. Simultaneously, the increasing number of microarray analyses of different thyroid pathologies raises the demand to efficiently compare the data. However, the use of different microarray platforms complicates cross-analysis. In addition, there are other important differences between these studies: 1) some studies use intraindividual comparisons, whereas other studies perform interindividual comparisons; 2) the reference tissue is defined as strictly nonnodular healthy tissue or also contains benign lesions such as goiter, follicular adenoma, and hyperplastic nodules in some studies; and 3) the widely used Affymetrix GeneChip platform comprises several GeneChip generations that are only partially compatible. Moreover, the different studies are characterized by strong differences in data analysis methods, which vary from simple empiric filters to sophisticated statistic algorithms. Therefore, this review summarizes and compares the different published reports in the context of their study design. It also illustrates perspectives and solutions for data set integration and meta-analysis, as well as the possibilities to combine array analysis with other genetic approaches.

This article has been cited by other articles:

				M. Eszlinger, K. Krohn, S. Hauptmann, H. Dralle, T. J. Giordano, and R. Paschke Perspectives for Improved and More Accurate Classification of Thyroid Epithelial Tumors J. Clin. Endocrinol. Metab., September 1, 2008; 93(9): 3286 - 3294. [Abstract] [Full Text] [PDF]