4.7 Article

Transcriptional landscape of cholangiocarcinoma revealed by weighted gene coexpression network analysis

期刊

BRIEFINGS IN BIOINFORMATICS
卷 22, 期 4, 页码 -

出版社

OXFORD UNIV PRESS
DOI: 10.1093/bib/bbaa224

关键词

cholangiocarcinoma; weighted gene coexpression network analysis; hub gene; tumor differentiation; prognosis

资金

  1. High-level Teachers at Beijing Municipal Universities in the Period of 13th Five-year Plan [IDHT20190510]
  2. Ministry of Science and Technology of the People's Republic of China [2014CB910100]
  3. National Natural Science Foundation of China [81171899, 81372230, 81972652]
  4. International Science and Technology Cooperation Projects [2016YFE0107100]
  5. Capital Special Research Project for Health Development [2014-2-4012]
  6. Beijing Natural Science Foundation [L172055, 7192158]
  7. National Ten-thousand Talent Program
  8. Fundamental Research Funds for the Central Universities [3332018032]
  9. CAMS Innovation Fund for Medical Science (CIFMS) [2017-I2M-4-003, 2018-I2M-3-001]
  10. Shenzhen Science and Technology Plan [CKCY20180323174659823]
  11. National Science Foundation for Young Scientists of China [81802735]

向作者/读者索取更多资源

By employing WGCNA method, this study analyzed gene expression profiles and clinical features of 36 CCA patients, identifying 1478 aberrantly expressed genes in CCA. Seven coexpression modules significantly correlated with clinical traits were identified, with green and blue modules showing significant association with tumor differentiation. Survival analysis revealed 17 hub genes as prognostic biomarkers for CCA patients.
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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据