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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

机译:基因表达谱揭示了默克尔与变异默克尔细胞表型和新分类器基因的不同表达模式,以区分默克尔细胞与小细胞肺癌

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摘要

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.
机译:默克尔细胞癌(MCC)是一种罕见的侵袭性皮肤肿瘤,与小细胞肺癌(SCLC)具有组织病理学和遗传学特征,两者都是神经内分泌起源的。与SCLC相比,MCC细胞系分为两个不同的生化亚组,分别称为“经典”和“变种”。为了确定与这些表型不同的MCC细胞系亚组相关的典型基因表达特征,并寻找MCC和SCLC之间差异表达的基因,我们使用cDNA阵列对10个MCC细胞系和4个SCLC细胞系进行了分析。使用微阵列的显着性分析,我们定义了一组76个差异表达的基因,可以明确鉴定经典和变异MCC亚组。我们假设其中一些基因的差异表达水平反映了类似于SCLC的经典和变异MCC表型的不同生物学和临床特性。因此,它们可以作为有用的预后标志物和潜在靶标,用于开发针对每个亚组的新治疗干预措施。此外,我们的分析鉴定出了17种强大的分类器基因,能够将MCC与SCLC区分开。对另外26个MCC和SCLC样品上的这些基因进行实时定量RT-PCR分析,证实了它们的诊断分类潜力,为这些侵略性癌症的新研究提供了机会。

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