Gene-expression profiling reveals distinct expression patterns for Classic versus Variant Merkel cell phenotypes and new classifier genes to distinguish Merkel cell from small-cell lung carcinoma.

Autor: Van Gele, Mireille, Boyle, Glen M., Cook, Anthony L., Vandesompele, Jo, Boonefaes, Tom, Rottiers, Pieter, Van Roy, Nadine, De Paepe, Anne, Parsons, Peter G., Leonard, J. Helen, Speleman, Frank
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Zdroj: Oncogene; 4/8/2004, Vol. 23 Issue 15, p2732-2742, 11p, 1 Diagram, 3 Charts, 2 Graphs
Abstrakt: Merkel cell carcinoma (MCC) is a rare aggressive skin tumor which shares histopathological and genetic features with small-cell lung carcinoma (SCLC), both are of neuroendocrine origin. Comparable to SCLC, MCC cell lines are classified into two different biochemical subgroups designated as ‘Classic’ and ‘Variant’. With the aim to identify typical gene-expression signatures associated with these phenotypically different MCC cell lines subgroups and to search for differentially expressed genes between MCC and SCLC, we used cDNA arrays to profile 10 MCC cell lines and four SCLC cell lines. Using significance analysis of microarrays, we defined a set of 76 differentially expressed genes that allowed unequivocal identification of Classic and Variant MCC subgroups. We assume that the differential expression levels of some of these genes reflect, analogous to SCLC, the different biological and clinical properties of Classic and Variant MCC phenotypes. Therefore, they may serve as useful prognostic markers and potential targets for the development of new therapeutic interventions specific for each subgroup. Moreover, our analysis identified 17 powerful classifier genes capable of discriminating MCC from SCLC. Real-time quantitative RT-PCR analysis of these genes on 26 additional MCC and SCLC samples confirmed their diagnostic classification potential, opening opportunities for new investigations into these aggressive cancers.Oncogene (2004) 23, 2732-2742. doi:10.1038/sj.onc.1207421 Published online 2 February 2004 [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index