Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, USA.
Nat Genet. 2021 Mar;53(3):342-353. doi: 10.1038/s41588-020-00774-y. Epub 2021 Feb 8.
Technological and computational advances in genomics and interactomics have made it possible to identify how disease mutations perturb protein-protein interaction (PPI) networks within human cells. Here, we show that disease-associated germline variants are significantly enriched in sequences encoding PPI interfaces compared to variants identified in healthy participants from the projects 1000 Genomes and ExAC. Somatic missense mutations are also significantly enriched in PPI interfaces compared to noninterfaces in 10,861 tumor exomes. We computationally identified 470 putative oncoPPIs in a pan-cancer analysis and demonstrate that oncoPPIs are highly correlated with patient survival and drug resistance/sensitivity. We experimentally validate the network effects of 13 oncoPPIs using a systematic binary interaction assay, and also demonstrate the functional consequences of two of these on tumor cell growth. In summary, this human interactome network framework provides a powerful tool for prioritization of alleles with PPI-perturbing mutations to inform pathobiological mechanism- and genotype-based therapeutic discovery.
基因组学和相互作用组学的技术和计算进展使得识别疾病突变如何扰乱人类细胞内的蛋白质-蛋白质相互作用（PPI）网络成为可能。在这里，我们表明与来自 1000 基因组和 ExAC 项目的健康参与者中鉴定的变体相比，与疾病相关的种系变体在编码 PPI 界面的序列中显著富集。与非界面相比，体细胞错义突变在 10861 个肿瘤外显子中也显著富集于 PPI 界面。我们在泛癌分析中通过计算方法鉴定了 470 个推定的致癌 PPI，并证明致癌 PPI 与患者的生存和耐药性/敏感性高度相关。我们使用系统的二元相互作用测定实验验证了 13 个致癌 PPI 的网络效应，还证明了其中两个对肿瘤细胞生长的功能后果。总之，这个人类相互作用组网络框架为优先考虑具有 PPI 扰乱突变的等位基因提供了一个有力的工具，以告知基于病理生物学机制和基因型的治疗发现。
