Nakahara Yukiko, Shiraishi Tetsuya, Okamoto Hiroaki, Mineta Toshihiro, Oishi Tsuyoshi, Sasaki Kohsuke, Tabuchi Kazuo
Department of Neurosurgery, Faculty of Medicine, Saga University, Saga 849-850, Japan.
Neuro Oncol. 2004 Oct;6(4):281-9. doi: 10.1215/S1152851703000632).
We examined whole genomic aberrations of biopsied samples from 19 independent glioblastomas by array-based comparative genomic hybridization analysis. The highest frequencies of copy number gains were observed on RFC2 (73.3%), EGFR (63.2%), and FGR, ELN, CDKN1C , FES, TOP2A, and ARSA (57.9% each). The highest frequencies of copy number losses were detected on TBR1 (52.6%), BMI1 (52.6%), EGR2 (47.4%), DMBT1 (47.4%), MTAP (42.1%), and FGFR2 (42.1%). The copy number gains of CDKN1C and INS and the copy number losses of TBR1 were significantly correlated with longer survival of patients. High-level amplifications were identified on EGFR, SAS/CDK4, PDGFRA, MDM2, and ARSA. These genes are assumed to be involved in tumorigenesis or progression of glioblastomas. The first attempts to apply detrended fluctuation analysis to copy number profiles by considering the reading direction as the time axis demonstrated that higher long-term fractal scaling exponents (alpha2) correlated well with longer survival of glioblastoma patients. The present study indicates that array-based comparative genomic hybridization analysis has great potential for assessment of copy number changes and altered chromosomal regions of brain tumors. Furthermore, we show that nonlinear analysis methods of whole genome copy number profiles may provide prognostic information about glioblastoma patients.
我们通过基于阵列的比较基因组杂交分析,检测了来自19例独立胶质母细胞瘤活检样本的全基因组畸变。拷贝数增加频率最高的是RFC2(73.3%)、EGFR(63.2%)以及FGR、ELN、CDKN1C、FES、TOP2A和ARSA(各为57.9%)。拷贝数减少频率最高的是TBR1(52.6%)、BMI1(52.6%)、EGR2(47.4%)、DMBT1(47.4%)、MTAP(42.1%)和FGFR2(42.1%)。CDKN1C和INS的拷贝数增加以及TBR1的拷贝数减少与患者较长生存期显著相关。在EGFR、SAS/CDK4、PDGFRA、MDM2和ARSA上发现了高水平扩增。这些基因被认为参与了胶质母细胞瘤的肿瘤发生或进展。首次尝试通过将读取方向视为时间轴,将去趋势波动分析应用于拷贝数图谱,结果表明较高的长期分形标度指数(alpha2)与胶质母细胞瘤患者较长生存期密切相关。本研究表明,基于阵列的比较基因组杂交分析在评估脑肿瘤的拷贝数变化和染色体区域改变方面具有巨大潜力。此外,我们表明全基因组拷贝数图谱的非线性分析方法可能为胶质母细胞瘤患者提供预后信息。