Identification of cancer prognosis-associated functional modules using differential co-expression networks
文献类型：期刊论文
| 作者 | Yu, Wenshuai1; Zhao, Shengjie1,2; Wang, Yongcui3; Zhao, Brian Nlong4; Zhao, Weiling5,6; Zhou, Xiaobo7,8,9 |
| 刊名 | ONCOTARGET
 |
| 出版日期 | 2017-12-22 |
| 卷号 | 8期号:68页码:112928-112941 |
| 关键词 | Co-expression Network Prognosis Ho-gsvd Gene Module Cancer |
| DOI | 10.18632/oncotarget.22878 |
| 英文摘要 | The rapid accumulation of cancer-related data owing to high-throughput technologies has provided unprecedented choices to understand the progression of cancer and discover functional networks in multiple cancers. Establishment of co-expression networks will help us to discover the systemic properties of carcinogenesis features and regulatory mechanisms of multiple cancers. Here, we proposed a computational workflow to identify differentially co-expressed gene modules across 8 cancer types by using combined gene differential expression analysis methods and a higher-order generalized singular value decomposition. Four co-expression modules were identified; and oncogenes and tumor suppressors were significantly enriched in these modules. Functional enrichment analysis demonstrated the significantly enriched pathways in these modules, including ECM-receptor interaction, focal adhesion and PI3K-Akt signaling pathway. The top-ranked miRNAs (mir-199, mir-29, mir-200) and transcription factors (FOXO4, E2A, NFAT, and MAZ) were identified, which play an important role in deregulating cellular energetics; and regulating angiogenesis and cancer immune system. The clinical significance of the co-expressed gene clusters was assessed by evaluating their predictability of cancer patients' survival. The predictive power of different clusters and subclusters was demonstrated. Our results will be valuable in cancer-related gene function annotation and for the evaluation of cancer patients' prognosis. |
| 语种 | 英语 |
| WOS记录号 | WOS:000419569800065 |
| 源URL | [http://ir.nwipb.ac.cn/handle/363003/13304]  |
| 专题 | 西北高原生物研究所_中国科学院西北高原生物研究所 |
| 作者单位 | 1.Tongji Univ, Key Lab Embedded Syst & Serv Comp, Coll Elect & Informat Engn, Minist Educ, Shanghai, Peoples R China 2.Tongji Univ, Coll Software Engn, Shanghai, Peoples R China 3.Chinese Acad Sci, Northwest Inst Plateau Biol, Key Lab Adaptat & Evolut Plateau Biota, Xining, Qinghai, Peoples R China 4.Shanghai High Sch Int Div, Shanghai, Peoples R China 5.Wake Forest Univ, Sch Med, Dept Radiol, Winston Salem, NC 27109 USA 6.Wake Forest Univ, Sch Med, Ctr Comprehens Canc, Winston Salem, NC 27109 USA 7.Tongji Univ, Coll Elect & Informat Engn, Shanghai, Peoples R China 8.Tongji Univ, Ctr Big Data Sci & Network Secur, Shanghai, Peoples R China 9.Wake Forest Univ, Sch Med, Ctr Bioinformat & Syst Biol, Winston Salem, NC 27109 USA |
| 推荐引用方式 GB/T 7714 | Yu, Wenshuai,Zhao, Shengjie,Wang, Yongcui,et al. Identification of cancer prognosis-associated functional modules using differential co-expression networks[J]. ONCOTARGET,2017,8(68):112928-112941. |
| APA | Yu, Wenshuai,Zhao, Shengjie,Wang, Yongcui,Zhao, Brian Nlong,Zhao, Weiling,&Zhou, Xiaobo.(2017).Identification of cancer prognosis-associated functional modules using differential co-expression networks.ONCOTARGET,8(68),112928-112941. |
| MLA | Yu, Wenshuai,et al."Identification of cancer prognosis-associated functional modules using differential co-expression networks".ONCOTARGET 8.68(2017):112928-112941. |
入库方式： OAI收割
来源：西北高原生物研究所
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