Haploinsufficiency networks identify targetable patterns of allelic deficiency in low mutation ovarian cancer.
Haploinsufficiency networks identify targetable patterns of allelic deficiency in low mutation ovarian cancer.
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DOI：
10.1038/ncomms14423
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发表时间：
2017-02-15
影响因子：
16.6
通讯作者：
Stupack DG
中科院分区：
文献类型：
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作者：
Delaney JR;Patel CB;Willis KM;Haghighiabyaneh M;Axelrod J;Tancioni I;Lu D;Bapat J;Young S;Cadassou O;Bartakova A;Sheth P;Haft C;Hui S;Saenz C;Schlaepfer DD;Harismendy O;Stupack DG
特异性致癌基因变化的鉴定使得现代一代的靶向癌症治疗成为可能。在高级别浆液性卵巢癌（OV）中，大部分遗传变化不是体细胞点突变，而是体细胞拷贝数改变（SCNA）。SCNA对肿瘤生物学的影响仍然知之甚少。在这里，我们建立单倍不足网络分析，以确定哪些SCNA模式是最具破坏性的OV。在所有KEGG通路中（N=187），自噬是最显著的被同时发生的基因缺失破坏。与其他20种癌症类型相比，OV在自噬和代偿性蛋白质稳态途径中受到最严重的破坏。网络分析将MAP1LC3B（LC3）和BECN 1列为最具影响力。LC3和BECN 1表达的敲低赋予了对经历自噬应激的细胞的敏感性，而与铂抗性状态无关。这些结果支持使用通路网络工具来评估肿瘤的拷贝数景观如何指导治疗。癌症累积多个单拷贝数改变，但其影响尚不清楚。在这里，作者通过计算证明了卵巢癌中与自噬相关的基因的破坏，显示了对自噬通量的影响，并注意到自噬药物在临床前模型中的疗效。
Identification of specific oncogenic gene changes has enabled the modern generation of targeted cancer therapeutics. In high-grade serous ovarian cancer (OV), the bulk of genetic changes is not somatic point mutations, but rather somatic copy-number alterations (SCNAs). The impact of SCNAs on tumour biology remains poorly understood. Here we build haploinsufficiency network analyses to identify which SCNA patterns are most disruptive in OV. Of all KEGG pathways (N=187), autophagy is the most significantly disrupted by coincident gene deletions. Compared with 20 other cancer types, OV is most severely disrupted in autophagy and in compensatory proteostasis pathways. Network analysis prioritizes MAP1LC3B (LC3) and BECN1 as most impactful. Knockdown of LC3 and BECN1 expression confers sensitivity to cells undergoing autophagic stress independent of platinum resistance status. The results support the use of pathway network tools to evaluate how the copy-number landscape of a tumour may guide therapy. Cancers accumulate multiple single copy number alterations, but their impact is unclear. Here, the authors computationally demonstrate a disruption of genes associated with autophagy in ovarian cancer, show impact on autophagic flux, and note the efficacy of autophagy drugs in preclinical models.