A Novel Prognostic Four-Gene Signature of Breast Cancer Identified by Integrated Bioinformatics Analysis
文献类型：期刊论文
| 作者 | Zhao, Xiaoyu; Yan, Huimin5; Yan, Xueqing4; Chen, Zhilin1; Zhuo, Rui3 |
| 刊名 | DISEASE MARKERS
 |
| 出版日期 | 2022 |
| 卷号 | 2022 |
| ISSN号 | 0278-0240 |
| DOI | 10.1155/2022/5925982 |
| 文献子类 | Article |
| 英文摘要 | 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. |
| 学科主题 | Biotechnology & Applied Microbiology ; Genetics & Heredity ; Medicine, Research & Experimental ; Pathology |
| 电子版国际标准刊号 | 1875-8630 |
| 出版地 | LONDON |
| WOS关键词 | SIGNALING PATHWAY ; GENE FAMILY ; NFATC2 ; WOMEN ; INFLAMMATION ; MIGRATION ; GPC6 |
| WOS研究方向 | Science Citation Index Expanded (SCI-EXPANDED) |
| 语种 | 英语 |
| 出版者 | HINDAWI LTD |
| WOS记录号 | WOS:000790517300005 |
| 源URL | [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.Chinese Acad Sci, Inst Bot, State Key Lab Systemat & Evolutionary Bot, Beijing 100000, Peoples R China 2.Guilin TCM Hosp China, Dept Breast Surg, Guilin 5410022, Peoples R China 3.Hainan Med Univ, Dept Breast & Thorac Oncol Surg, Affiliated Hosp 1, Haikou 570102, Peoples R China 4.Peoples Liberat Army Gen Hosp, Dept Pediat, Med Ctr 1, Beijing 100000, Peoples R China 5.Xuchang Univ, Med Coll, Xuchang 461000, 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). |
入库方式： OAI收割
来源：植物研究所
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