MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Cell Rep. 2024 Nov 26;43(11):114905. doi: 10.1016/j.celrep.2024.114905. Epub 2024 Oct 22.
Advances in protein structure determination and modeling allow us to study the structural context of human genetic variants on an unprecedented scale. Here, we analyze millions of cancer-associated missense mutations based on their structural locations and predicted perturbative effects. By considering the collective properties of mutations at the level of individual proteins, we identify distinct patterns associated with tumor suppressors and oncogenes. Tumor suppressors are enriched in structurally damaging mutations, consistent with loss-of-function mechanisms, while oncogene mutations tend to be structurally mild, reflecting selection for gain-of-function driver mutations and against loss-of-function mutations. Although oncogenes are difficult to distinguish from genes with no role in cancer using only structural damage, we find that the three-dimensional clustering of mutations is highly predictive. These observations allow us to identify candidate driver genes and speculate about their molecular roles, which we expect will have general utility in the analysis of cancer sequencing data.
蛋白质结构测定和建模的进展使我们能够以前所未有的规模研究人类遗传变异的结构背景。在这里，我们根据结构位置和预测的干扰效应分析了数百万个与癌症相关的错义突变。通过考虑单个蛋白质水平上突变的集体特性，我们确定了与肿瘤抑制因子和癌基因相关的不同模式。肿瘤抑制因子富含结构破坏性突变，与失活机制一致，而癌基因突变往往结构温和，反映了对功能获得驱动突变的选择，以及对失活突变的选择。尽管仅使用结构损伤很难将癌基因与在癌症中没有作用的基因区分开来，但我们发现突变的三维聚类具有高度预测性。这些观察结果使我们能够识别候选驱动基因并推测它们的分子作用，我们期望这将在癌症测序数据分析中具有普遍的应用价值。
