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From the Département d’Oncologie Moléculaire,* Institut Paoli-Calmettes and Institut National de la Santé et de la Recherche Medical U119, IFR57, Marseille; the Departements de Biopathologie and de Dépistage et Prévention, Institut Paoli-Calmettes, Marseille; the Département d’Oncologie Médicale, Institut Paoli-Calmettes, Université de la Méditerranée, Marseille; and the Laboratoire Technologies Avancées pour le Génome et la Clinique,¶ Centre d’Immunologie de Marseille-Luminy, Luminy, Marseille, France
Emerging high-throughput screening technologies are rapidly providing opportunities to identify new diagnostic and prognostic markers and new therapeutic targets in human cancer. Currently, cDNA arrays allow the quantitative measurement of thousands of mRNA expression levels simultaneously. Validation of this tool in hospital settings can be done on large series of archival paraffin-embedded tumor samples using the new technique of tissue microarray. On a series of 55 clinically and pathologically homogeneous breast tumors, we compared for 15 molecules with a proven or suspected role in breast cancer, the mRNA expression levels measured by cDNA array analysis with protein expression levels obtained using tumor tissue microarrays. The validity of cDNA array and tissue microarray data were first verified by comparison with quantitative reverse transcriptase-polymerase chain reaction measurements and immunohistochemistry on full tissue sections, respectively. We found a good correlation between cDNA and tissue array analyses in one-third of the 15 molecules, and no correlation in the remaining two-thirds. Furthermore, protein but not RNA levels may have prognostic value; this was the case for MUC1 protein, which was studied further using a tissue microarray containing 
600 tumor samples. For THBS1 the opposite was observed because only RNA levels had prognostic value. Thus, differences extended to clinical prognostic information obtained by the two methods underlining their complementarity and the need for a global molecular analysis of tumors at both the RNA and protein levels.
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