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加权基因共表达网络分析揭示的胆管癌转录组全景。

Transcriptional landscape of cholangiocarcinoma revealed by weighted gene coexpression network analysis.

机构信息

Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.

Department of Immunology, School of Basic Medical Sciences; Advanced Innovation Center for Human Brain Protection, Beijing Key Laboratory for Cancer Invasion and Metastasis, Department of Oncology, Capital Medical University, Beijing, China.

出版信息

Brief Bioinform. 2021 Jul 20;22(4). doi: 10.1093/bib/bbaa224.

Abstract

Cholangiocarcinoma (CCA) is a type of cancer with limited treatment options and a poor prognosis. Although some important genes and pathways associated with CCA have been identified, the relationship between coexpression and phenotype in CCA at the systems level remains unclear. In this study, the relationships underlying the molecular and clinical characteristics of CCA were investigated by employing weighted gene coexpression network analysis (WGCNA). The gene expression profiles and clinical features of 36 patients with CCA were analyzed to identify differentially expressed genes (DEGs). Subsequently, the coexpression of DEGs was determined by using the WGCNA method to investigate the correlations between pairs of genes. Network modules that were significantly correlated with clinical traits were identified. In total, 1478 mRNAs were found to be aberrantly expressed in CCA. Seven coexpression modules that significantly correlated with clinical characteristics were identified and assigned representative colors. Among the 7 modules, the green and blue modules were significantly related to tumor differentiation. Seventy-eight hub genes that were correlated with tumor differentiation were found in the green and blue modules. Survival analysis showed that 17 hub genes were prognostic biomarkers for CCA patients. In addition, we found five new targets (ISM1, SULT1B1, KIFC1, AURKB and CCNB1) that have not been studied in the context of CCA and verified their differential expression in CCA through experiments. Our results not only promote our understanding of the relationship between the transcriptome and clinical data in CCA but will also guide the development of targeted molecular therapy for CCA.

摘要

胆管癌(CCA)是一种治疗选择有限且预后不良的癌症。尽管已经确定了一些与 CCA 相关的重要基因和途径,但在系统水平上,CCA 中基因表达与表型之间的关系仍不清楚。在这项研究中,通过采用加权基因共表达网络分析(WGCNA)来研究 CCA 分子和临床特征的内在关系。分析了 36 例 CCA 患者的基因表达谱和临床特征,以确定差异表达基因(DEGs)。随后,通过 WGCNA 方法确定 DEGs 的共表达,以研究基因对之间的相关性。鉴定了与临床特征显著相关的共表达网络模块。总共发现 1478 个 mRNAs 在 CCA 中异常表达。确定了与临床特征显著相关的 7 个共表达模块,并赋予代表性颜色。在 7 个模块中,绿色和蓝色模块与肿瘤分化显著相关。在绿色和蓝色模块中发现了 78 个与肿瘤分化相关的枢纽基因。生存分析显示,17 个枢纽基因是 CCA 患者的预后生物标志物。此外,我们发现了五个以前未在 CCA 背景下研究过的新靶点(ISM1、SULT1B1、KIFC1、AURKB 和 CCNB1),并通过实验验证了它们在 CCA 中的差异表达。我们的研究结果不仅促进了我们对 CCA 中转录组和临床数据之间关系的理解,而且还将指导针对 CCA 的靶向分子治疗的发展。

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