Prognostic Genes of Breast Cancer Identified by Gene Co-expression Network Analysis.
Prognostic Genes of Breast Cancer Identified by Gene Co-expression Network Analysis.
复制标题
DOI：
10.3389/fonc.2018.00374
复制
发表时间：
2018
影响因子：
4.7
通讯作者：
Wu G
中科院分区：
文献类型：
--
作者：
Tang J;Kong D;Cui Q;Wang K;Zhang D;Gong Y;Wu G
乳腺癌是最常见的恶性肿瘤之一。其发病机制的分子机制仍有待进一步研究。本研究的目的是确定与乳腺癌进展相关的潜在基因。加权基因共表达网络分析（WGCNA）用于构建自由尺度基因共表达网络，以探索基因集与临床特征之间的关联，并识别候选生物标志物。GSE 1561的基因表达谱选自Gene Expression Omnibus（GEO）数据库。使用来自TCGA的乳腺癌的RNA-seq数据和临床信息进行验证。通过平均连锁系统聚类，共确定了18个模块。在显著性模块（R2 = 0.48）中，共鉴定出42个网络枢纽基因。基于癌症基因组图谱（TCGA）数据，5个枢纽基因（CCNB 2、FBXO 5、KIF 4A、MCM 10和TPX 2）与不良预后相关。受试者工作特征（ROC）曲线验证了这5个基因的mRNA水平对正常组织和肿瘤组织具有良好的诊断效率。此外，这5个基因在肿瘤组织中的蛋白水平也明显高于正常组织。其中，CCNB 2、KIF 4A和TPX 2在晚期肿瘤阶段进一步上调。总之，共表达网络分析确定了5个候选生物标志物，可用于乳腺癌的进一步基础和临床研究。
Breast cancer is one of the most common malignancies. The molecular mechanisms of its pathogenesis are still to be investigated. The aim of this study was to identify the potential genes associated with the progression of breast cancer. Weighted gene co-expression network analysis (WGCNA) was used to construct free-scale gene co-expression networks to explore the associations between gene sets and clinical features, and to identify candidate biomarkers. The gene expression profiles of GSE1561 were selected from the Gene Expression Omnibus (GEO) database. RNA-seq data and clinical information of breast cancer from TCGA were used for validation. A total of 18 modules were identified via the average linkage hierarchical clustering. In the significant module (R2 = 0.48), 42 network hub genes were identified. Based on the Cancer Genome Atlas (TCGA) data, 5 hub genes (CCNB2, FBXO5, KIF4A, MCM10, and TPX2) were correlated with poor prognosis. Receiver operating characteristic (ROC) curve validated that the mRNA levels of these 5 genes exhibited excellent diagnostic efficiency for normal and tumor tissues. In addition, the protein levels of these 5 genes were also significantly higher in tumor tissues compared with normal tissues. Among them, CCNB2, KIF4A, and TPX2 were further upregulated in advanced tumor stage. In conclusion, 5 candidate biomarkers were identified for further basic and clinical research on breast cancer with co-expression network analysis.
登录
查看更多内容
影响因子：
3.7
作者：
Geiger TR;Ha NH;Faraji F;Michael HT;Rodriguez L;Walker RC;Green JE;Simpson RM;Hunter KW
通讯作者：
Hunter KW
WGCNA：用于加权相关网络分析的 R 包。
影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
ISL1是CCNB1、CCNB2和c-MYC基因的新型调节因子，促进胃癌细胞增殖和肿瘤生长
影响因子：
--
作者：
Shi Q;Wang W;Jia Z;Chen P;Ma K;Zhou C
通讯作者：
Zhou C
影响因子：
4
作者：
Pan HW;Su HH;Hsu CW;Huang GJ;Wu TT
通讯作者：
Wu TT
影响因子：
8
作者：
Farmer, P;Bonnefoi, H;Iggo, R
通讯作者：
Iggo, R