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首页> 外文期刊>Oncogene >Identification of novel genomic markers related to progression to glioblastoma through genomic profiling of 25 primary glioma cell lines
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Identification of novel genomic markers related to progression to glioblastoma through genomic profiling of 25 primary glioma cell lines

机译:通过25种原发性神经胶质瘤细胞系的基因组分析鉴定与胶质母细胞瘤进展相关的新型基因组标记

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摘要

Identification of genetic copy number changes in glial tumors is of importance in the context of improved/refined diagnostic, prognostic procedures and therapeutic decision-making. In order to detect recurrent genomic copy number changes that might play a role in glioma pathogenesis and/or progression, we characterized 25 primary glioma cell lines including 15 non glioblastoma (non GBM) (I–III WHO grade) and 10 GBM (IV WHO grade), by array comparative genomic hybridization, using a DNA microarray comprising approx. 3500 BACs covering the entire genome with a 1Mb resolution and additional 800 BACs covering chromosome 19 at tiling path resolution. Combined evaluation by single clone and whole chromosome analysis plus 'moving average (MA) approach' enabled us to confirm most of the genetic abnormalities previously identified to be associated with glioma progression, including +1q32, +7, -10, -22q, PTEN and p16 loss, and to disclose new small genomic regions, some correlating with grade malignancy. Grade I–III gliomas exclusively showed losses at 3p26 (53%), 4q13–21 (33%) and 7p15–p21 (26%), whereas only GBMs exhibited 4p16.1 losses (40%). Other recurrent imbalances, such as losses at 4p15, 5q22–q23, 6p23–25, 12p13 and gains at 11p11–q13, were shared by different glioma grades. Three intervals with peak of loss could be further refined for chromosome 10 by our MA approach. Data analysis of full-coverage chromosome 19 highlighted two main regions of copy number gain, never described before in gliomas, at 19p13.11 and 19q13.13–13.2. The well-known 19q13.3 loss of heterozygosity area in gliomas was not frequently affected in our cell lines. Genomic hotspot detection facilitated the identification of small intervals resulting in positional candidate genes such as PRDM2 (1p36.21), LRP1B (2q22.3), ADARB2 (10p15.3), BCCIP (10q26.2) and ING1 (13q34) for losses and ECT2 (3q26.3), MDK, DDB2, IG20 (11p11.2) for gains. These data increase our current knowledge about cryptic genetic changes in gliomas and may facilitate the further identification of novel genetic elements, which may provide us with molecular tools for the improved diagnostics and therapeutic decision-making in these tumors.
机译:在改善/改进的诊断,预后程序和治疗决策的背景下,鉴定神经胶质瘤中基因拷贝数变化是重要的。为了检测可能在神经胶质瘤发病机理和/或进展中起作用的复发性基因组拷贝数变化,我们鉴定了25种原发性神经胶质瘤细胞系,包括15种非胶质母细胞瘤(非GBM)(I–III WHO级)和10 GBM(IV WHO)等级),通过阵列比较基因组杂交,使用包含约3500个BAC以1Mb的分辨率覆盖整个基因组,另外800个BAC以平铺路径的分辨率覆盖19号染色体。通过单克隆和整个染色体分析以及“移动平均(MA)方法”的综合评估使我们能够确认以前鉴定出的与胶质瘤进展相关的大多数遗传异常,包括+ 1q32,+ 7,-10,-22q,PTEN和p16缺失,并揭示新的小基因组区域,其中一些与恶性程度相关。 I–III级神经胶质瘤仅在3p26(53 %),4q13–21(33 %)和7p15–p21(26 %)时表现出损失,而只有GBM表现出4p16.1的损失(40 %)。其他复发性失衡,例如4p15、5q22–q23、6p23–25、12p13的损失和11p11–q13的收益,则由不同的神经胶质瘤级别共享。通过我们的MA方法,可以进一步完善10号染色体的三个损失峰。全覆盖19号染色体的数据分析突出显示了两个主要的拷贝数增加区域,这在神经胶质瘤中从未描述过,分别位于19p13.11和19q13.13-13.2。在我们的细胞系中,胶质瘤中众所周知的19q13.3杂合子区域的丢失并不常见。基因组热点检测有利于鉴定小区间,从而产生位置候选基因,例如PRDM2(1p36.21),LRP1B(2q22.3),ADARB2(10p15.3),BCCIP(10q26.2)和ING1(13q34)和ECT2(3q26.3),MDK,DDB2,IG20(11p11.2)获得收益。这些数据增加了我们目前对神经胶质瘤隐性遗传变化的认识,并可能有助于进一步鉴定新的遗传元件,这可能为我们提供分子工具,以改善这些肿瘤的诊断和治疗决策。

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