Taniwaki Masaya, Daigo Yataro, Ishikawa Nobuhisa, Takano Atsushi, Tsunoda Tatsuhiko, Yasui Wataru, Inai Kouki, Kohno Nobuoki, Nakamura Yusuke
Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan.
Int J Oncol. 2006 Sep;29(3):567-75.
To characterize the molecular mechanisms involved in the carcinogenesis and progression of small-cell lung cancer (SCLC) and identify molecules to be applied as novel diagnostic markers and/or for development of molecular-targeted drugs, we applied cDNA microarray profile analysis coupled with purification of cancer cells by laser-microbeam microdissection (LMM). Expression profiles of 32,256 genes in 15 SCLCs identified 252 genes that were commonly up-regulated and 851 transcripts that were down-regulated in SCLC cells compared with non-cancerous lung tissue cells. An unsupervised clustering algorithm applied to the expression data easily distinguished SCLC from the other major histological type of non-small cell lung cancer (NSCLC) and identified 475 genes that may represent distinct molecular features of each of the two histological types. In particular, SCLC was characterized by altered expression of genes related to neuroendocrine cell differentiation and/or growth such as ASCL1, NRCAM, and INSM1. We also identified 68 genes that were abundantly expressed both in advanced SCLCs and advanced adenocarcinomas (ADCs), both of which had been obtained from patients with extensive chemotherapy treatment. Some of them are known to be transcription factors and/or gene expression regulators such as TAF5L, TFCP2L4, PHF20, LMO4, TCF20, RFX2, and DKFZp547I048 as well as those encoding nucleotide-binding proteins such as C9orf76, EHD3, and GIMAP4. Our data provide valuable information for better understanding of lung carcinogenesis and chemoresistance.
为了阐明小细胞肺癌(SCLC)发生发展过程中涉及的分子机制,并确定可作为新型诊断标志物和/或用于开发分子靶向药物的分子,我们采用了cDNA微阵列分析,并结合激光微束显微切割(LMM)技术纯化癌细胞。与非癌性肺组织细胞相比,对15例SCLC中32256个基因的表达谱分析发现,有252个基因在SCLC细胞中普遍上调,851个转录本下调。将无监督聚类算法应用于表达数据,可轻松区分SCLC与其他主要组织学类型的非小细胞肺癌(NSCLC),并鉴定出475个可能代表这两种组织学类型各自独特分子特征的基因。特别是,SCLC的特征在于与神经内分泌细胞分化和/或生长相关的基因表达改变,如ASCL1、NRCAM和INSM1。我们还鉴定出68个在晚期SCLC和晚期腺癌(ADC)中均大量表达的基因,这两种癌症均来自接受广泛化疗的患者。其中一些已知是转录因子和/或基因表达调节因子,如TAF5L、TFCP2L4、PHF20、LMO4、TCF20、RFX2和DKFZp547I048,以及编码核苷酸结合蛋白的基因,如C9orf76、EHD3和GIMAP4。我们的数据为更好地理解肺癌发生和化疗耐药性提供了有价值的信息。