Cooperation and antagonism among cancer genes: the renal cancer paradigm.
Cooperation and antagonism among cancer genes: the renal cancer paradigm.
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癌基因之间的合作与拮抗作用：肾脏癌范式。
DOI：
10.1158/0008-5472.can-13-0360
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发表时间：
2013-07-15
期刊：
影响因子：
11.2
通讯作者：
Brugarolas J
中科院分区：
文献类型：
--
作者：
Peña-Llopis S;Christie A;Xie XJ;Brugarolas J
人们对癌症基因中的驱动突变如何共同促进肿瘤发展知之甚少。肾细胞癌（RCC）为研究癌症基因之间的复杂关系提供了独特的机会。透明细胞型RCC（最常见的类型）中最常见的四种突变基因是两次击中肿瘤抑制基因，它们聚集在染色体3p上的43 Mb区域，在约90%的肿瘤中缺失：VHL（突变约80%），PBRM 1（约50%），BAP 1（约15%）和SET D2（约15%）。我们进行的荟萃分析显示，PBRM 1和SET D2突变在肿瘤中共同发生的频率高于单独偶然发生的预期，表明这些突变可能在肿瘤发生中协同作用。相反，与我们以前的结果一致，PBRM 1和BAP 1的突变往往是相互排斥的。突变排他性分析（通常由于缺乏统计功效而混淆）提高了功能冗余的可能性。然而，突变排他性可能表明负面的遗传相互作用，如本文所提出的PBRM 1和BAP 1，这些基因中的突变定义了具有不同病理特征，基因表达谱和结果的RCC。癌症基因之间的负遗传相互作用指向癌症基因作用的更广泛的背景依赖性，而不仅仅是组织依赖性。了解癌症基因的依赖性可能会揭示可以用于治疗的漏洞。
It is poorly understood how driver mutations in cancer genes work together to promote tumor development. Renal cell carcinoma (RCC) offers a unique opportunity to study complex relationships among cancer genes. The four most commonly mutated genes in RCC of clear-cell type (the most common type) are two-hit tumor suppressor genes and they cluster in a 43 Mb region on chromosome 3p that is deleted in ~90% of tumors: VHL (mutated in ~80%), PBRM1 (~50%), BAP1 (~15%) and SETD2 (~15%). Meta-analyses that we conducted show that mutations in PBRM1 and SETD2 co-occur in tumors at a frequency higher than expected by chance alone, indicating that these mutations may cooperate in tumorigenesis. In contrast, consistent with our previous results, mutations in PBRM1 and BAP1 tend to be mutually exclusive. Mutation exclusivity analyses (often confounded by lack of statistical power) raise the possibility of functional redundancy. However, mutation exclusivity may indicate negative genetic interactions, as proposed herein for PBRM1 and BAP1, and mutations in these genes define RCC with different pathologic features, gene expression profiles, and outcomes. Negative genetic interactions among cancer genes point toward broader context-dependencies of cancer gene action beyond tissue dependencies. Understanding cancer genes dependencies may unravel vulnerabilities that can be exploited therapeutically.