Amatschek Stefan, Koenig Ulrich, Auer Herbert, Steinlein Peter, Pacher Margit, Gruenfelder Agnes, Dekan Gerhard, Vogl Sonja, Kubista Ernst, Heider Karl-Heinz, Stratowa Christian, Schreiber Martin, Sommergruber Wolfgang
Department of Dermatology, University of Vienna, Vienna, Austria.
Cancer Res. 2004 Feb 1;64(3):844-56. doi: 10.1158/0008-5472.can-03-2361.
With the objective of discovering novel putative intervention sites for anticancer therapy, we compared transcriptional profiles of breast cancer, lung squamous cell cancer (LSCC), lung adenocarcinoma (LAC), and renal cell cancer (RCC). Each of these tumor types still needs improvement in medical treatment. Our intention was to search for genes not only highly expressed in the majority of patient samples but which also exhibit very low or even absence of expression in a comprehensive panel of 16 critical (vital) normal tissues. To achieve this goal, we combined two powerful technologies, PCR-based cDNA subtraction and cDNA microarrays. Seven subtractive libraries consisting of approximately 9250 clones were established and enriched for tumor-specific transcripts. These clones, together with approximately 1750 additional tumor-relevant genes, were used for cDNA microarray preparation. Hybridizations were performed using a pool of 16 critical normal tissues as a reference in all experiments. In total, we analyzed 20 samples of breast cancer, 11 of LSCC, 11 of LAC, and 8 of RCC. To select for genes with low or even no expression in normal tissues, expression profiles of 22 different normal tissues were additionally analyzed. Importantly, this tissue-wide expression profiling allowed us to eliminate genes, which exhibit also high expression in normal tissues. Similarly, expression signatures of genes, which are derived from infiltrating cells of the immune system, were eliminated as well. Cluster analysis resulted in the identification of 527 expressed sequence tags specifically up-regulated in these tumors. Gene-wise hierarchical clustering of these clones clearly separated the different tumor types with RCC exhibiting the most homogeneous and LAC the most diverse expression profile. In addition to already known tumor-associated genes, the majority of identified genes have not yet been brought into context with tumorigenesis such as genes involved in bone matrix mineralization (OSN, OPN, and OSF-2) in lung, breast, and kidney cancer or genes controlling Ca(2+) homeostasis (RCN1,CALCA, S100 protein family). EGLN3, which recently has been shown to be involved in regulation of hypoxia-inducible factor, was found to be highly up-regulated in all RCCs and in half of the LSCCs analyzed. Furthermore, 42 genes, the expression level of which correlated with the overall survival of breast cancer patients, were identified. The gene dendogram clearly separates two groups of genes, those up-regulated such as cyclin B1, TGF-beta 3, B-Myb, Erg2, VCAM-1, and CD44 and those down-regulated such as MIG-6, Esp15, and CAK in patients with short survival time.
为了发现抗癌治疗新的潜在干预位点,我们比较了乳腺癌、肺鳞状细胞癌(LSCC)、肺腺癌(LAC)和肾细胞癌(RCC)的转录谱。这些肿瘤类型中的每一种在医学治疗方面仍需改进。我们的目的是寻找不仅在大多数患者样本中高表达,而且在16种关键(重要)正常组织的综合面板中表达非常低甚至缺失的基因。为了实现这一目标,我们结合了两种强大的技术,基于PCR的cDNA消减和cDNA微阵列。建立了7个由约9250个克隆组成的消减文库,并富集了肿瘤特异性转录本。这些克隆与另外约1750个肿瘤相关基因一起用于制备cDNA微阵列。在所有实验中,使用16种关键正常组织的混合样本作为参考进行杂交。我们总共分析了20个乳腺癌样本、11个LSCC样本、11个LAC样本和8个RCC样本。为了筛选在正常组织中低表达甚至不表达的基因,还分析了22种不同正常组织的表达谱。重要的是,这种全组织表达谱分析使我们能够排除那些在正常组织中也高表达的基因。同样,来自免疫系统浸润细胞的基因表达特征也被排除。聚类分析导致鉴定出527个在这些肿瘤中特异性上调的表达序列标签。这些克隆的基因层次聚类清楚地将不同肿瘤类型分开,RCC表现出最均匀的表达谱,而LAC表现出最多样化的表达谱。除了已知的肿瘤相关基因外,大多数鉴定出的基因尚未与肿瘤发生联系起来,例如参与肺、乳腺和肾癌骨基质矿化的基因(OSN、OPN和OSF-2)或控制Ca(2+)稳态的基因(RCN1、CALCA、S100蛋白家族)。最近已证明EGLN3参与缺氧诱导因子的调节,发现在所有分析的RCC和一半的LSCC中高度上调。此外,鉴定出42个基因,其表达水平与乳腺癌患者的总生存期相关。基因树状图清楚地将两组基因分开,一组是在生存期短的患者中上调的基因,如细胞周期蛋白B1、TGF-β3、B-Myb、Erg2、VCAM-1和CD44,另一组是下调的基因,如MIG-6、Esp15和CAK。