Microarray Analysis of Gene Expression Profiles in Primary and Secondary Glloblastomas

多形性胶质母细胞瘤分为两个亚型：一种是“原发(新发)胶质母细胞瘤”，它发生在没有既往病变的老年人身上；另一种是“继发性胶质母细胞瘤”，它发生在有良性星形细胞瘤病史的年轻人身上。本研究旨在分析这两个亚群的mRNA表达谱，揭示其潜在的分子病理性质，并了解导致这两个亚群之间生物学和临床差异的机制。通过本研究，我们获得了以下结果：1)我们建立了一种基于酵母的终止密码子分析方法，以鉴定与p53突变负相关的PTEN基因突变，从而对胶质母细胞瘤进行分类(癌基因)。2)我们构建了一个由1300个基因组成的原始DNA阵列。3)分析了U251 MG、SF268、SF295、SF539、SNB-75和SNB-78等胶质母细胞瘤细胞株的P53、APC和PTEN突变状态及其表达谱。我们共鉴定出85个与P53突变状态相关的基因。4)我们发现应用特征子集选择算法和神经网络来提取基因表达的特征模式。我们目前正在对一些胶质母细胞瘤的临床病例进行研究。

Glioblastoma multiforme is classified into two subsets : one is 'primary (de novo) glioblastoma' which arises in relatively elderly persons without a preceding lesion, and another is 'secondary glioblastoma' which arises in young persons with a preceding benign astrocytoma. The present study aimed to analyze mRNA expression profiles of the both subsets, disclose their underlying molecular pathological natures, and know the mechanism which causes the biological and clinical differences between the both subsets.We obtained the following results through this study : 1) We developed a yeast-based stop codon assay to identify PTEN gene mutations that inversely correlate with p53 mutations to classify glioblastomas (Oncogene).2) We developed an original DNA array consisting of 1300 genes. We analyzed 119 cancer cell lines including glioblastoma cells with the array, and obtained successful results.3) We analyzed glioblastoma cell lines including U251MG, SF268, SF295, SF539, SNB-75, and SNB-78, for their p53-, APC- and PTEN-mutational states and their expression profiles. We identified a total of 85 genes that associated with the p53 mutational status.4) We found that application of feature subset selection algorithms and neural networks to extract characteristic patterns of gene expression. We are now undertaking studies on a number of clinical cases of glioblastoma.