Alteration of expression profiling related the biological characteristics of renal cell carcinoma using cDNA microarray.

【目的】为了评估影响肾细胞癌（rcc）临床特征（如转移或治疗反应）的基因组背景，我们使用由4000个人类cDNA克隆组成的微阵列技术分析了肾细胞癌（rcc）的基因表达谱。结果包括以下两个部分。【结果】(1)为了研究转移相关的特征，我们比较了原发或转移灶的RCC细胞系与正常肾近端小管细胞系（RPTEC）的基因表达谱。对选取的62个基因进行聚类分析，发现来自转移灶的SKRC-17和SKRC-29细胞的谱型相似。另一个来自转移灶的细胞系SKRC-52，其形态呈现独特的纺锤形，表达谱与其他细胞系不同。我们发现转移灶细胞系中有几个基因上调。独特的基因谱分析模式…更多的基因表达与细胞形态和转移潜力明显相关，这些谱分析可能有助于确定与RCC临床特征相关的基因。(2)由于干扰素- α (IFN-a)对RCC的应答率较低，因此在为RCC患者量身定制治疗时，需要预测干扰素- α的良好候选药物。采用MTT法筛选6株SKRC细胞株，分别为IFN-a敏感细胞株（SKRC-1、14、29、59）和耐药细胞株（SKRC- 33、52），添加1,000 ~ 10,000 IU/ml IFN-a。利用RT-PCR和Northern blot技术证实了敏感细胞系和耐药细胞系基因表达的差异。根据SKRC系列和RPTEC之间的表达变化，最终选择了1,401个基因。通过对这1401个基因的聚类分析，6个细胞系可分为两组，这与对IFN-a的敏感性一致。此外，在敏感细胞系和耐药细胞系中，干扰素调节因子4等10个基因的表达发生了显著变化。微阵列分析为RCC细胞系中IFN-a的敏感性提供了有用的信息。所选基因集的这种聚类和/或表达模式可能可用于选择ifn -a应答的患者。少

[Purpose] To evaluate the genomic background affecting clinical characteristics like metastasis, or response to treatment, we analyzed gene expression profiles of the renal cell carcinomas (RCCs) by microarray technology consisting of 4000 human cDNA clones using SKRC cell lines. Results consists of following 2 sections.[Results] (1) To investigate the metastasis related characteristics, We compared gene expression profiles between RCC cell lines originated from primary or metastasis lesions with the normal renal proximal tubular cell line(RPTEC) as a control. The clustering with the selected 62 genes revealed similarity of profiling pattern between SKRC-17 and SKRC-29 cells which were derived from the metastatic lesion. Another line from metastatic lesion, SKRC-52, whose morphology showed unique spindle shape, had different pattern of expression profiling from the other cell lines. We found several genes up-regulated in the cell lines from the metastatic lesion. Unique profiling patte … More rn on gene expression clearly correlated to cell morphology and metastatic potential and these profiling might contribute to identify the genes involved in clinical characteristics of RCC. (2) Because response rate of interferon-alpha (IFN-a) against RCC is low, prediction of good candidates of IFN-a is required in terms of tailor-made treatment for patients with RCC. Six SKRC cell lines were selected as IFN-a-sensitive (SKRC-1, 14, 29, 59) or resistant (33, 52) cell line by means of MTT assay with addition of 1,000 to 10,000 IU/ml of IFN-a. Alteration of gene expression that differs between sensitive and resistant cell lines were confirmed using RT-PCR and Northern blot. Based on the alteration of expression between SKRC series and RPTEC, 1,401 genes were eventually selected. According to clustering analysis with these 1,401 genes, 6 cell lines could be divided into two groups, which were concordant with the sensitivity against IFN-a. In addition, remarkable alteration of gene expression between sensitive and resistant cell lines were observed in 10 genes, e.g. interferon regulatory factor 4. Microarray analysis provided a useful information concerning sensitivity of IFN-a in RCC cell lines. This clustering and/or expression pattern of selected gene set might be available to select patients who is IFN-a-responder. Less