A new method of identifying glioblastoma subtypes and creation of corresponding animal models
A new method of identifying glioblastoma subtypes and creation of corresponding animal models
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DOI：
10.1038/s41388-018-0305-1
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发表时间：
2018-08-30
期刊：
影响因子：
8
通讯作者：
Zhao, Xudong
中科院分区：
文献类型：
--
作者：
Zhou, Xia;Li, Gonghua;Zhao, Xudong
胶质母细胞瘤（GBM）占脑实质肿瘤的50%。它是最恶性的脑癌类型，生存率很低，治疗方法有限。癌症分型对于癌症研究和治疗是重要的。在这里，我们报告了一种新的基于CDKN 2A和TP 53基因的遗传变异的GBM亚型分型方法。CDKN 2A和TP 53是最常见的突变基因，突变率分别为60%和30%。我们发现CDKN 2A缺失的患者比TP 53突变的患者具有更差的生存率。有趣的是，同时具有TP 53突变和CDKN 2A缺失的患者的生存率并不比仅具有其中一种遗传改变的患者差，但与仅具有TP 53突变的患者相似。接下来，我们研究了TP 53和CDKN 2A样品之间基因表达谱的差异。与存活数据一致，具有TP 53突变和CDKN 2A缺失的样品显示出与仅具有TP 53突变的那些样品相似的基因表达谱。最后，我们发现RAS通路的激活加上Cdkn 2a/B沉默可以诱导GBM，其方式与RAS激活加上TP 53沉默的肿瘤诱导相似。总之，我们表明，CDKN 2A和TP 53的遗传变异可以用来分层GBM，并产生了新的动物模型匹配这种分层方法。
Glioblastoma (GBM) accounts for up to 50% of brain parenchymal tumors. It is the most malignant type of brain cancer with very poor survival and limited remedies. Cancer subtyping is important for cancer research and therapy. Here, we report a new subtyping method for GBM based on the genetic alterations of CDKN2A and TP53 genes. CDKN2A and TP53 are the most frequently mutated genes with mutation rates of 60 and 30%, respectively. We found that patients with deletion of CDKN2A possess worse survival than those with TP53 mutation. Interestingly, survival of patients with both TP53 mutation and CDKN2A deletion is no worse than for those with only one of these genetic alterations, but similar to those with TP53 mutation alone. Next, we investigated differences in the gene expression profile between TP53 and CDKN2A samples. Consistent with the survival data, the samples with both TP53 mutation and CDKN2A deletion showed a gene expression profile similar to those samples with TP53 mutation alone. Finally, we found that activation of RAS pathway plus Cdkn2a/b silencing can induce GBM, in a similar way to tumor induction by RAS activation plus TP53 silencing. In conclusion, we show that the genetic alterations of CDKN2A and TP53 may be used to stratify GBM, and the new animal models matching this stratification method were generated.