Identification of Common Driver Gene Modules and Associations between Cancers through Integrated Network Analysis,Global Challenges

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Identification of Common Driver Gene Modules and Associations between Cancers through Integrated Network Analysis
Global Challenges ( IF 4.4 ) Pub Date : 2021-06-19 , DOI: 10.1002/gch2.202100006
Bo Gao _{1,

2,

3,

4,

5} , Yue Zhao _{1,

3} , Yonghang Gao _{1,

3} , Guojun Li _{2,

6} , Ling-Yun Wu _{1,

3}

Affiliation

High-throughput biological data has created an unprecedented opportunity for illuminating the mechanisms of tumor emergence and evolution. An important and challenging problem in deciphering cancers is to investigate the commonalities of driver genes and pathways and the associations between cancers. Aiming at this problem, a tool ComCovEx is developed to identify common cancer driver gene modules between two cancers by searching for the candidates in local signaling networks using an exclusivity-coverage iteration strategy and outputting those with significant coverage and exclusivity for both cancers. The associations of the cancer pairs are further evaluated by Fisher's exact test. Being applied to 11 TCGA cancer datasets, ComCovEx identifies 13 significantly associated cancer pairs with plenty of biologically significant common gene modules. The novel results of cancer relationship and common gene modules reveal the relevant pathological basis of different cancer types and provide new clues to diagnosis and drug treatment in associated cancers.

中文翻译：

通过综合网络分析识别常见驱动基因模块和癌症之间的关联

高通量生物数据为阐明肿瘤出现和进化机制创造了前所未有的机会。破译癌症的一个重要且具有挑战性的问题是研究驱动基因和通路的共性以及癌症之间的关联。针对这个问题，开发了一种工具ComCovEx，通过使用排他性覆盖迭代策略在局部信号网络中搜索候选者，并输出对两种癌症具有显着覆盖性和排他性的候选者，来识别两种癌症之间常见的癌症驱动基因模块。通过 Fisher 精确检验进一步评估癌症对的关联。ComCovEx 应用于 11 个 TCGA 癌症数据集，识别出 13 个显着相关的癌症对以及大量具有生物学意义的常见基因模块。癌症关系和共同基因模块的新结果揭示了不同癌症类型的相关病理基础，为相关癌症的诊断和药物治疗提供了新的线索。

更新日期：2021-06-19

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