Literature DB >> 21618647

Analysis of pathway mutation profiles highlights collaboration between cancer-associated superpathways.

Yunyan Gu1, Wenyuan Zhao, Jiguang Xia, Yuannv Zhang, Ruihong Wu, Chenguang Wang, Zheng Guo.   

Abstract

The biological interpretation of the complexity of cancer somatic mutation profiles is a major challenge in current cancer research. It has been suggested that mutations in multiple genes that participate in different pathways are collaborative in conferring growth advantage to tumor cells. Here, we propose a powerful pathway-based approach to study the functional collaboration of gene mutations in carcinogenesis. We successfully identify many pairs of significantly comutated pathways for a large-scale somatic mutation profile of lung adenocarcinoma. We find that the coordinated pathway pairs detected by comutations are also likely to be coaltered by other molecular changes, such as alterations in multifunctional genes in cancer. Then, we cluster comutated pathways into comutated superpathways and show that the derived superpathways also tend to be significantly coaltered by DNA copy number alterations. Our results support the hypothesis that comprehensive cooperation among a few basic functions is required for inducing cancer. The results also suggest biologically plausible models for understanding the heterogeneous mechanisms of cancers. Finally, we suggest an approach to identify candidate cancer genes from the derived comutated pathways. Together, our results provide guidelines to distill the pathway collaboration in carcinogenesis from the complexity of cancer somatic mutation profiles.
© 2011 Wiley-Liss, Inc.

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Year:  2011        PMID: 21618647     DOI: 10.1002/humu.21541

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  5 in total

1.  Personalized pathway enrichment map of putative cancer genes from next generation sequencing data.

Authors:  Peilin Jia; Zhongming Zhao
Journal:  PLoS One       Date:  2012-05-18       Impact factor: 3.240

2.  Individualized analysis reveals CpG sites with methylation aberrations in almost all lung adenocarcinoma tissues.

Authors:  Haidan Yan; Qingzhou Guan; Jun He; Yunqing Lin; Juan Zhang; Hongdong Li; Huaping Liu; Yunyan Gu; Zheng Guo; Fei He
Journal:  J Transl Med       Date:  2017-02-08       Impact factor: 5.531

3.  Pathway Based Analysis of Mutation Data Is Efficient for Scoring Target Cancer Drugs.

Authors:  Marianna A Zolotovskaia; Maxim I Sorokin; Anna A Emelianova; Nikolay M Borisov; Denis V Kuzmin; Pieter Borger; Andrew V Garazha; Anton A Buzdin
Journal:  Front Pharmacol       Date:  2019-01-23       Impact factor: 5.810

4.  Identification of Common and Subtype-Specific Mutated Sub-Pathways for a Cancer.

Authors:  Haidan Yan; Xusheng Deng; Haifeng Chen; Jun Cheng; Jun He; Qingzhou Guan; Meifeng Li; Jiajing Xie; Jie Xia; Yunyan Gu; Zheng Guo
Journal:  Front Genet       Date:  2019-11-28       Impact factor: 4.599

5.  Discovery of co-occurring driver pathways in cancer.

Authors:  Junhua Zhang; Ling-Yun Wu; Xiang-Sun Zhang; Shihua Zhang
Journal:  BMC Bioinformatics       Date:  2014-08-09       Impact factor: 3.169

  5 in total

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