A Novel Prognostic Four-Gene Signature of Breast Cancer Identified by Integrated Bioinformatics Analysis

doi:10.1155/2022/5925982

	A Novel Prognostic Four-Gene Signature of Breast Cancer Identified by Integrated Bioinformatics Analysis
	Zhao, Xiaoyu ; Yan, Huimin 1; Yan, Xueqing 2; Chen, Zhilin 3; Zhuo, Rui 4
	2022
发表期刊	DISEASE MARKERS
ISSN	0278-0240
卷号	2022
摘要	Molecular analysis facilitates the prediction of overall survival (OS) of breast cancer and decision-making of the treatment plan. The current study was designed to identify new prognostic genes for breast cancer and construct an effective prognostic signature with integrated bioinformatics analysis. Differentially expressed genes in breast cancer samples from The Cancer Genome Atlas (TCGA) dataset were filtered by univariate Cox regression analysis. The prognostic model was optimized by the Akaike information criterion and further validated using the TCGA dataset (n=1014) and Gene Expression Omnibus (GEO) dataset (n=307). The correlation between the risk score and clinical information was assessed by univariate and multivariate Cox regression analyses. Functional pathways in relation to high-risk and low-risk groups were analyzed using gene set enrichment analysis (GSEA). Four prognostic genes (EXOC6, GPC6, PCK2, and NFATC2) were screened and used to construct a prognostic model, which showed robust performance in classifying the high-risk and low-risk groups. The risk score was significantly related to clinical features and OS. We identified 19 functional pathways significantly associated with the risk score. This study constructed a new prognostic model with a high prediction performance for breast cancer. The four-gene prognostic signature could serve as an effective tool to predict prognosis and assist the management of breast cancer patients.
学科领域	Biotechnology & Applied Microbiology ; Genetics & Heredity ; Medicine, Research & Experimental ; Pathology
DOI	10.1155/2022/5925982
收录类别	SCI
语种	英语
WOS关键词	SIGNALING PATHWAY ; GENE FAMILY ; NFATC2 ; WOMEN ; INFLAMMATION ; MIGRATION ; GPC6
WOS研究方向	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000790517300005
出版者	HINDAWI LTD
文献子类	Article
出版地	LONDON
EISSN	1875-8630
作者邮箱	abigial519@163.com ; 17337405336@163.com ; yanxueqing621@163.com ; charlychen@163.com ; merstudio@sina.com
作品OA属性	Green Published, gold
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ibcas.ac.cn/handle/2S10CLM1/28705
专题	系统与进化植物学国家重点实验室
作者单位	1.Xuchang Univ, Med Coll, Xuchang 461000, Peoples R China 2.Peoples Liberat Army Gen Hosp, Dept Pediat, Med Ctr 1, Beijing 100000, Peoples R China 3.Chinese Acad Sci, Inst Bot, State Key Lab Systemat & Evolutionary Bot, Beijing 100000, Peoples R China 4.Hainan Med Univ, Dept Breast & Thorac Oncol Surg, Affiliated Hosp 1, Haikou 570102, Peoples R China 5.Guilin TCM Hosp China, Dept Breast Surg, Guilin 5410022, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Xiaoyu,Yan, Huimin,Yan, Xueqing,et al. A Novel Prognostic Four-Gene Signature of Breast Cancer Identified by Integrated Bioinformatics Analysis[J]. DISEASE MARKERS,2022,2022.
APA	Zhao, Xiaoyu,Yan, Huimin,Yan, Xueqing,Chen, Zhilin,&Zhuo, Rui.(2022).A Novel Prognostic Four-Gene Signature of Breast Cancer Identified by Integrated Bioinformatics Analysis.DISEASE MARKERS,2022.
MLA	Zhao, Xiaoyu,et al."A Novel Prognostic Four-Gene Signature of Breast Cancer Identified by Integrated Bioinformatics Analysis".DISEASE MARKERS 2022(2022).

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