Identification of cancer prognosis-associated functional modules using differential co-expression networks

doi:10.18632/oncotarget.22878

NWIPB OpenIR

	Identification of cancer prognosis-associated functional modules using differential co-expression networks
	Yu, Wenshuai 1; Zhao, Shengjie 1,2; Wang, Yongcui 3; Zhao, Brian Nlong 4; Zhao, Weiling 5,6; Zhou, Xiaobo 7,8,9
	2017-12-22
发表期刊	ONCOTARGET
ISSN	1949-2553
卷号	8 期号:68 页码:112928-112941
文章类型	Article
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.
关键词	Co-expression Network Prognosis Ho-gsvd Gene Module Cancer
WOS标题词	Science & Technology ; Life Sciences & Biomedicine
DOI	10.18632/oncotarget.22878
关键词[WOS]	MATRIX FACTORIZATION ; EXTRACELLULAR-MATRIX ; EXPRESSION DATA ; MIR-200 FAMILY ; GENE ; GROWTH ; PROGRESSION ; METASTASIS ; PERIOSTIN ; INVASION
收录类别	SCI
语种	英语
项目资助者	National Basic Research Program of China (973 Program)(2014CB340404) ; National Science Foundation of China(61471267 ; Fundamental Research Funds for the Central Universities ; National Institutes of Health(1U01CA166886 ; 61373105 ; 1U01AR069395 ; 61672422) ; 1R01GM123037)
WOS研究方向	Oncology ; Cell Biology
WOS类目	Oncology ; Cell Biology
WOS记录号	WOS:000419569800065
出版者	IMPACT JOURNALS LLC
引用统计	被引频次：7[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://210.75.249.4/handle/363003/13304
专题	中国科学院西北高原生物研究所
通讯作者	Zhao, Shengjie; Zhou, Xiaobo
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.