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III. Medizinische Klinik und Poliklinik, Johannes Gutenberg Universität Mainz, D-55131 Mainz, Germany;
* Roche Genomic and Information Sciences, Hoffmann-La Roche Inc., Nutley, New Jersey, USA;
Institut für Pathologie, Klinikum Bamberg, 96049 Bamberg, Germany; and
Department of Surgery, Neuenheimer Feld 110, 69120 Heidelberg, Germany
1Correspondence: III. Medizinische Klinik, Johannes-Gutenberg Universität Mainz, Verfügungsgebäude für Forschung und Entwicklung, Obere Zahlbacher Str. 63, D-55131 Mainz, Germany. E-mail: Tureci{at}mail.uni-mainz.de
Microarray profiles of bulk tumor tissues reflect gene expression corresponding to malignant cells as well as to many different types of contaminating normal cells. In this report, we assess the feasibility of querying baseline multitissue transcriptome databases to dissect disease-specific genes. Using colon cancer as a model tumor, we show that the application of Boolean operators (AND, OR, BUTNOT) for database searches leads to genes with expression patterns of interest. The BUTNOT operator for example allows the assignment of "expression signatures" to normal tissue specimens. These expression signatures were then used to computationally identify contaminating cells within conventionally dissected tissue specimens. The combination of several logic operators together with an expression database based on multiple human tissue specimens can resolve the problem of tissue contamination, revealing novel cancer-specific gene expression. Several markers, previously not known to be colon cancer associated, are provided.—Türeci, O., Ding, J., Hilton, H., Bian, H., Ohkawa, H., Braxenthaler, M., Seitz, G., Raddrizzani, L., Friess, H., Buchler, M., Sahin, U., Hammer, J. Computational dissection of tissue contamination for identification of colon cancer-specific expression profiles.
Key Words: expression signature • colorectal cancer • profile
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