Literature DB >> 24771271

Gene co-expression analysis identifies common modules related to prognosis and drug resistance in cancer cell lines.

Wei Liu1, Li Li, Weidong Li.   

Abstract

To discover a common gene co-expression network in cancer cell, we applied weighted gene co-expression network analysis to transcriptional profiles of 917 cancer cell lines. Fourteen biologically meaningful modules were identified, including cytoskeleton, cell cycle, RNA splicing, signaling pathway, transcription, translation and others. These modules were robust in an independent human cancer microarray dataset. Furthermore, we collected 11 independent cancer microarray datasets, and correlated these modules with clinical outcome. Most of these modules could predict patient survival in one or more cancer types. Some modules were predictive of relapse, metastasis and drug resistance. Novel regulatory mechanisms were also implicated. In summary, our findings, for the first time, provide a modular map for cancer cell lines, new targets for therapy and modules for regulatory mechanism of cancer development and drug resistance.
© 2014 UICC.

Entities:  

Keywords:  cancer; cell line; drug resistance; module; prognosis

Mesh:

Substances:

Year:  2014        PMID: 24771271     DOI: 10.1002/ijc.28935

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  16 in total

1.  From Saccharomyces cerevisiae to human: The important gene co-expression modules.

Authors:  Wei Liu; Li Li; Hua Ye; Haiwei Chen; Weibiao Shen; Yuexian Zhong; Tian Tian; Huaqin He
Journal:  Biomed Rep       Date:  2017-07-06

2.  Network-based expression analysis reveals key genes related to glucocorticoid resistance in infant acute lymphoblastic leukemia.

Authors:  Zaynab Mousavian; Abbas Nowzari-Dalini; Ronald W Stam; Yasir Rahmatallah; Ali Masoudi-Nejad
Journal:  Cell Oncol (Dordr)       Date:  2016-10-31       Impact factor: 6.730

3.  Network-based survival-associated module biomarker and its crosstalk with cell death genes in ovarian cancer.

Authors:  Nana Jin; Hao Wu; Zhengqiang Miao; Yan Huang; Yongfei Hu; Xiaoman Bi; Deng Wu; Kun Qian; Liqiang Wang; Changliang Wang; Hongwei Wang; Kongning Li; Xia Li; Dong Wang
Journal:  Sci Rep       Date:  2015-06-23       Impact factor: 4.379

4.  Oxidative phosphorylation activation is an important characteristic of DOX resistance in hepatocellular carcinoma cells.

Authors:  Li Wu; Jiayu Zhao; Kexin Cao; Xiao Liu; Hao Cai; Jiaqi Wang; Weidong Li; Zhipeng Chen
Journal:  Cell Commun Signal       Date:  2018-02-05       Impact factor: 5.712

5.  Optimizing prognosis-related key miRNA-target interactions responsible for cancer metastasis.

Authors:  Hongying Zhao; Huating Yuan; Jing Hu; Chaohan Xu; Gaoming Liao; Wenkang Yin; Liwen Xu; Li Wang; Xinxin Zhang; Aiai Shi; Jing Li; Yun Xiao
Journal:  Oncotarget       Date:  2017-11-27

6.  An integrative and comparative study of pan-cancer transcriptomes reveals distinct cancer common and specific signatures.

Authors:  Zhen Cao; Shihua Zhang
Journal:  Sci Rep       Date:  2016-09-16       Impact factor: 4.379

7.  Revisiting Connectivity Map from a gene co-expression network analysis.

Authors:  Wei Liu; Wei Tu; Li Li; Yingfu Liu; Shaobo Wang; Ling Li; Huan Tao; Huaqin He
Journal:  Exp Ther Med       Date:  2018-06-08       Impact factor: 2.447

8.  Quantitative Identification of Compound-Dependent On-Modules and Differential Allosteric Modules From Homologous Ischemic Networks.

Authors:  B Li; J Liu; Y Y Zhang; P Q Wang; Y N Yu; R X Kang; H L Wu; X X Zhang; Z Wang; Y Y Wang
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2016-10-19

9.  Transcriptome-derived stromal and immune scores infer clinical outcomes of patients with cancer.

Authors:  Wei Liu; Hua Ye; Ying-Fu Liu; Chao-Qun Xu; Yue-Xian Zhong; Tian Tian; Shi-Wei Ma; Huan Tao; Ling Li; Li-Chun Xue; Hua-Qin He
Journal:  Oncol Lett       Date:  2018-01-25       Impact factor: 2.967

10.  Reference Module-Based Analysis of Ovarian Cancer Transcriptome Identifies Important Modules and Potential Drugs.

Authors:  Xuedan Lai; Peihong Lin; Jianwen Ye; Wei Liu; Shiqiang Lin; Zhou Lin
Journal:  Biochem Genet       Date:  2021-06-25       Impact factor: 1.890

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.