Stockholm Bioinformatics Centre, Stockholm University, Stockholm, Sweden.
Mol Cell Proteomics. 2010 Apr;9(4):648-55. doi: 10.1074/mcp.M900227-MCP200. Epub 2009 Dec 3.
Genes involved in cancer susceptibility and progression can serve as templates for searching protein networks for novel cancer genes. To this end, we introduce a general network searching method, MaxLink, and apply it to find and rank cancer gene candidates by their connectivity to known cancer genes. Using a comprehensive protein interaction network, we searched for genes connected to known cancer genes. First, we compiled a new set of 812 genes involved in cancer, more than twice the number in the Cancer Gene Census. Their network neighbors were then extracted. This candidate list was refined by selecting genes with unexpectedly high levels of connectivity to cancer genes and without previous association to cancer. This produced a list of 1891 new cancer candidates with up to 55 connections to known cancer genes. We validated our method by cross-validation, Gene Ontology term bias, and differential expression in cancer versus normal tissue. An example novel cancer gene candidate is presented with detailed analysis of the local network and neighbor annotation. Our study provides a ranked list of high priority targets for further studies in cancer research. Supplemental material is included.
涉及癌症易感性和进展的基因可以作为在蛋白质网络中搜索新型癌症基因的模板。为此，我们引入了一种通用的网络搜索方法 MaxLink，并应用它通过与已知癌症基因的连接性来寻找和排列癌症基因候选物。我们使用综合蛋白质相互作用网络来搜索与已知癌症基因相连的基因。首先，我们编译了一组新的 812 个涉及癌症的基因，数量是癌症基因目录的两倍多。然后提取了它们的网络邻居。通过选择与癌症基因连接性异常高且以前与癌症无关的基因，对候选列表进行了细化。这产生了一个包含 1891 个新的癌症候选物的列表，它们与已知癌症基因的连接多达 55 个。我们通过交叉验证、基因本体论术语偏差和癌症与正常组织之间的差异表达来验证我们的方法。提供了一个新的癌症基因候选物的示例，并对局部网络和邻居注释进行了详细分析。我们的研究提供了一份癌症研究中进一步研究的高优先级目标的排序清单。提供了补充材料。
