CHG: A Systematically Integrated Database of Cancer Hallmark Genes
Author(s) -
Denan Zhang,
Diwei Huo,
Hongbo Xie,
Lingxiang Wu,
Juan Zhang,
Lei Liu,
Qing Jin,
Xiujie Chen
Publication year - 2020
Publication title -
frontiers in genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.413
H-Index - 81
ISSN - 1664-8021
DOI - 10.3389/fgene.2020.00029
Subject(s) - gene , kegg , cancer , computational biology , function (biology) , biology , glioblastoma , database , computer science , gene ontology , cancer research , genetics , gene expression
Background 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. Methods 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. Results 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. Conclusions In summary, CHG, which was constructed based on a hallmark feature set, provides a new perspective for analyzing the diversity and development of cancers.
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