Zhang Denan, Huo Diwei, Xie Hongbo, Wu Lingxiang, Zhang Juan, Liu Lei, Jin Qing, Chen Xiujie
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
The 2nd Affiliated Hospital of Harbin Medical University, Harbin, China.
Front Genet. 2020 Feb 5;11:29. doi: 10.3389/fgene.2020.00029. eCollection 2020.
The analysis of cancer diversity based on a logical framework of hallmarks has greatly improved our understanding of the occurrence, development and metastasis of various cancers.
We designed Cancer Hallmark Genes (CHG) database which focuses on integrating hallmark genes in a systematic, standard way and annotates the potential roles of the hallmark genes in cancer processes. Following the conceptual criteria description of hallmark function the keywords for each hallmark were manually selected from the literature. Candidate hallmark genes collected were derived from 301 pathways of KEGG database by Lucene and manually corrected.
Based on the variation data, we finally identified the hallmark genes of various types of cancer and constructed CHG. And we also analyzed the relationships among hallmarks and potential characteristics and relationships of hallmark genes based on the topological structures of their networks. We manually confirm the hallmark gene identified by CHG based on literature and database. We also predicted the prognosis of breast cancer, glioblastoma multiforme and kidney papillary cell carcinoma patients based on CHG data.
In summary, CHG, which was constructed based on a hallmark feature set, provides a new perspective for analyzing the diversity and development of cancers.
基于癌症特征逻辑框架对癌症多样性进行分析，极大地增进了我们对各类癌症发生、发展及转移的理解。
我们设计了癌症特征基因（CHG）数据库，该数据库专注于以系统、标准的方式整合特征基因，并注释特征基因在癌症进程中的潜在作用。依据特征功能的概念性标准描述，从文献中手动选取每个特征的关键词。收集的候选特征基因通过Lucene从KEGG数据库的301条通路中获取，并进行人工校正。
基于变异数据，我们最终确定了各类癌症的特征基因并构建了CHG。我们还基于其网络拓扑结构分析了特征之间的关系以及特征基因的潜在特性和关系。我们根据文献和数据库人工确认了CHG鉴定出的特征基因。我们还基于CHG数据预测了乳腺癌、多形性胶质母细胞瘤和肾乳头状细胞癌患者的预后。
总之，基于特征集构建的CHG为分析癌症的多样性和发展提供了新视角。
