Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.
Sci Rep. 2020 Oct 14;10(1):17198. doi: 10.1038/s41598-020-74293-5.
Although next-generation sequencing has demonstrated great potential for novel gene discovery, confirming disease-causing genes after initial discovery remains challenging. Here, we applied a network analysis approach to prioritize candidate genes identified from whole-exome sequencing analysis of 98 cutaneous melanoma patients from 27 families. Using a network propagation method, we ranked candidate genes by their similarity to known disease genes in protein-protein interaction networks and identified gene clusters with functional connectivity. Using this approach, we identified several new candidate susceptibility genes that warrant future investigations such as NGLY1, IL1RN, FABP2, PRKDC, and PROSER2. The propagated network analysis also allowed us to link families that did not have common underlying genes but that carried variants in genes that interact on protein-protein interaction networks. In conclusion, our study provided an analysis perspective for gene prioritization in the context of genetic heterogeneity across families and prioritized top potential candidate susceptibility genes in our dataset.
虽然下一代测序技术在发现新基因方面显示出巨大的潜力，但在初步发现后确认致病基因仍然具有挑战性。在这里，我们应用网络分析方法对从 27 个家族的 98 例皮肤黑素瘤患者的全外显子组测序分析中鉴定出的候选基因进行优先级排序。我们使用网络传播方法，根据候选基因与蛋白质相互作用网络中已知疾病基因的相似性对其进行排序，并鉴定出具有功能连通性的基因簇。使用这种方法，我们确定了一些新的候选易感基因，这些基因值得进一步研究，例如 NGLY1、IL1RN、FABP2、PRKDC 和 PROSER2。传播网络分析还使我们能够将没有共同潜在基因的家族联系起来，但这些家族在蛋白质相互作用网络上相互作用的基因中携带变异。总之，我们的研究为在家族间遗传异质性的背景下进行基因优先级排序提供了分析视角，并确定了我们数据集的顶级潜在候选易感基因。
