Division of Gynecologic Oncology, Department of Reproductive Medicine, UCSD School of Medicine and UCSD Moores Cancer Center, 3855 Health Sciences Drive, La Jolla, California 39216, USA.
Centre de recherche en Cancérologie, INSERM 1052, CNRS 5286, Centre Léon Bérard, Université de Lyon, Lyon, France.
Nat Commun. 2017 Feb 15;8:14423. doi: 10.1038/ncomms14423.
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.
特定致癌基因变化的鉴定使现代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（SCNAs）。SCNAs 对肿瘤生物学的影响仍知之甚少。在这里，我们构建了杂合不足网络分析，以确定在 OV 中哪种 SCNA 模式最具破坏性。在所有 KEGG 途径（N=187）中，自噬受到基因缺失的影响最大。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的干扰最为严重。网络分析将 MAP1LC3B（LC3）和 BECN1 确定为最具影响力的基因。LC3 和 BECN1 表达的敲低使正在经历自噬应激的细胞对铂类耐药状态不敏感。结果支持使用途径网络工具来评估肿瘤的拷贝数景观如何指导治疗。
