Prognostic genes of triple-negative breast cancer identified by weighted gene co-expression network analysis
Prognostic genes of triple-negative breast cancer identified by weighted gene co-expression network analysis
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DOI：
10.3892/ol.2019.11079
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发表时间：
2020-01-01
期刊：
影响因子：
2.9
通讯作者：
Bao, Maode
中科院分区：
文献类型：
--
作者：
Bao, Ligang;Guo, Ting;Bao, Maode
三阴性乳腺癌（TNBC）的特点是雌激素受体（ER）、孕激素受体（PR）和HER2/neu基因缺乏。与其他亚型乳腺癌患者相比，TNBC患者远端复发和死亡率的可能性增加。目前的研究旨在确定TNBC的新生物标志物。采用加权基因共表达网络分析法（WGCNA）构建基因共表达网络；这些被用来探索mRNA谱与临床数据之间的相关性，从而确定与美国癌症- tnm阶段TNBC联合委员会相关的最重要的共表达网络。WGCNA使用从加州大学圣克鲁兹分校下载的癌症基因组图谱中的RNAseq数据集，通过K-means聚类确定了23个模块。最重要的模块由248个基因组成，随后对其进行基因本体分析。然后应用差异表达基因（DEG）分析来确定正常组织和肿瘤组织之间的DEG。共有42个基因位于deg和最显著模块之间的重叠处。通过生存分析，选择PIPC PDZ结构域含家族成员1 （GIPC1）、家族bHLH转录因子6 （HES6）、钙调素调控谱蛋白相关蛋白家族成员3 （KIAA1543）、肌球蛋白轻链激酶2 （MYLK2）和彼得潘同源物（PPAN） 5个基因，研究它们与美国癌症- tnm诊断阶段的关系。这些基因在不同病理阶段的表达水平不同，但在更晚期的病理阶段有增加的趋势。通过受体工作特征曲线分析，这5个基因的表达对肿瘤和正常组织具有准确的识别能力。GIPC1、HES6、KIAA1543、MYLK2和PPAN的高表达导致TNBC患者总生存期（OS）较差。综上所述，通过无监督聚类方法，构建了一个具有高度互联性的共表达基因网络，并鉴定出5个基因作为TNBC的生物标志物。
Triple-negative breast cancer (TNBC)is characterized by a deficiency in the estrogen receptor (ER), progesterone receptor (PR) and HER2/neu genes. Patients with TNBC have an increased likelihood of distant recurrence and mortality, compared with patients with other subtypes of breast cancer. The current study aimed to identify novel biomarkers for TNBC. Weighted gene co-expression network analysis (WGCNA) was applied to construct gene co-expression networks; these were used to explore the correlation between mRNA profiles and clinical data, thus identifying the most significant co-expression network associated with the American Joint Committee on Cancer-TNM stage of TNBC. Using RNAseq datasets from The Cancer Genome Atlas, downloaded from the University of California, Santa Cruz, WGCNA identified 23 modules via K-means clustering. The most significant module consisted of 248 genes, on which gene ontology analysis was subsequently performed. Differently Expressed Gene (DEG) analysis was then applied to determine the DEGs between normal and tumor tissues. A total of 42 genes were positioned in the overlap between DEGs and the most significant module. Following survival analysis, 5 genes PIPC PDZ domain containing family member 1 (GIPC1), hes family bHLH transcription factor 6 (HES6), calmodulin-regulated spectrin-associated protein family member 3 (KIAA1543), myosin light chain kinase 2 (MYLK2) and peter pan homolog (PPAN)] were selected and their association with the American Joint Committee on Cancer-TNM diagnostic stage was investigated. The expression level of these genes in different pathological stages varied, but tended to increase in more advanced pathological stages. The expression of these 5 genes exhibited accurate capacity for the identification of tumor and normal tissues via receiver operating characteristic curve analysis. High expression of GIPC1, HES6, KIAA1543, MYLK2 and PPAN resulted in poor overall survival (OS) in patients with TNBC. In conclusion, via unsupervised clustering methods, a co-expressed gene network with high inter-connectivity was constructed, and 5 genes were identified as biomarkers for TNBC.