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Molecular & Cellular Proteomics 5:1471-1483, 2006.
© 2006 by The American Society for Biochemistry and Molecular Biology, Inc.

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Research

Proteomics-based Validation of Genomic Data

Applications in Colorectal Cancer Diagnosis ^{* ,S}

Juan Madoz-Gúrpide^,,¶, Paula López-Serra^,,||, Jorge Luis Martínez-Torrecuadrada, Lydia Sánchez^**, Luis Lombardía and J. Ignacio Casal^,

From the Protein Technology, ^** Histology and Immunohistochemistry, and Genomics Units, Biotechnology Programme, Centro Nacional de Investigaciones Oncológicas (CNIO), 28029 Madrid, Spain

Multiple factors are involved in the translation of functional genomic results into proteins for proteome research and target validation on tumoral tissues. In this report, genes were selected by using DNA microarrays on a panel of colorectal cancer (CRC) paired samples. A large number of up-regulated genes in colorectal cancer patients were investigated for cellular location, and those corresponding to membrane or extracellular proteins were used for a non-biased expression in Escherichia coli. We investigated different sources of cDNA clones for protein expression as well as the influence of the protein size and the different tags with respect to protein expression levels and solubility in E. coli. From 29 selected genes, 21 distinct proteins were finally expressed as soluble proteins with, at least, one different fusion protein. In addition, seven of these potential markers (ANXA3, BMP4, LCN2, SPARC, SPP1, MMP7, and MMP11) were tested for antibody production and/or validation. Six of the seven proteins (all except SPP1) were confirmed to be overexpressed in colorectal tumoral tissues by using immunoblotting and tissue microarray analysis. Although none of them could be associated to early stages of the tumor, two of them (LCN2 and MMP11) were clearly overexpressed in late Dukes’ stages (B and C). This proteomic study reveals novel clues for the assembly of a robust and highly efficient high throughput system for the validation of genomic data. Moreover it illustrates the different difficulties and bottlenecks encountered for performing a quick conversion of genomic results into clinically useful proteins.

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