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Survival analysis of genome-wide profiles coupled with Connectivity Map database mining to identify potential therapeutic targets for cholangiocarcinoma

  • Authors:
    • Peng Lin
    • Xiao-Zhu Zhong
    • Xiao-Dong Wang
    • Jian-Jun Li
    • Rui-Qi Zhao
    • Yu He
    • Yan-Qiu Jiang
    • Xian-Wen Huang
    • Gang Chen
    • Yun He
    • Hong Yang
  • View Affiliations / Copyright

    Affiliations: Department of Medical Ultrasonics, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China, Department of Medical Ultrasonics, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China, Department of General Surgery, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China, Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China, Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China, Department of Traditional Chinese Medicine, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China
    Copyright: © Lin et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 3189-3198
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    Published online on: September 18, 2018
       https://doi.org/10.3892/or.2018.6710
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Abstract

Cholangiocarcinoma (CCA) is one of the most common epithelial cell malignancies worldwide. However, its prognosis is poor. The aim of the present study was to examine the prognostic landscape and potential therapeutic targets for CCA. RNA sequencing data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) dataset and processed. A total of 172 genes that were significantly associated with overall survival of patients with CCA were identified using the univariate Cox regression method. Bioinformatics tools were applied using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO). It was identified that ‘Wnt signaling pathway’, ‘cytoplasm’ and ‘AT DNA binding’ were the three most significant GO categories of CCA survival-associated genes. ‘Transcriptional misregulation in cancer’ was the most significant pathway identified in the KEGG analysis. Using the Drug-Gene Interaction database, a drug-gene interaction network was constructed, and 31 identified genes were involved in it. The most meaningful potential therapeutic targets were selected via protein-protein and gene-drug interactions. Among these genes, polo-like kinase 1 (PLK1) was identified to be a potential target due to its significant upregulation in CCA. To rapidly find molecules that may affect these genes, the Connectivity Map was queried. A series of molecules were selected for their potential anti-CCA functions. 0297417-0002B and tribenoside exhibited the highest connection scores with PLK1 via molecular docking. These findings may offer novel insights into treatment and perspectives on the future innovative treatment of CCA.
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Copy and paste a formatted citation
Spandidos Publications style
Lin P, Zhong X, Wang X, Li J, Zhao R, He Y, Jiang Y, Huang X, Chen , He Y, He Y, et al: Survival analysis of genome-wide profiles coupled with Connectivity Map database mining to identify potential therapeutic targets for cholangiocarcinoma. Oncol Rep 40: 3189-3198, 2018.
APA
Lin, P., Zhong, X., Wang, X., Li, J., Zhao, R., He, Y. ... Yang, H. (2018). Survival analysis of genome-wide profiles coupled with Connectivity Map database mining to identify potential therapeutic targets for cholangiocarcinoma. Oncology Reports, 40, 3189-3198. https://doi.org/10.3892/or.2018.6710
MLA
Lin, P., Zhong, X., Wang, X., Li, J., Zhao, R., He, Y., Jiang, Y., Huang, X., Chen, ., He, Y., Yang, H."Survival analysis of genome-wide profiles coupled with Connectivity Map database mining to identify potential therapeutic targets for cholangiocarcinoma". Oncology Reports 40.6 (2018): 3189-3198.
Chicago
Lin, P., Zhong, X., Wang, X., Li, J., Zhao, R., He, Y., Jiang, Y., Huang, X., Chen, ., He, Y., Yang, H."Survival analysis of genome-wide profiles coupled with Connectivity Map database mining to identify potential therapeutic targets for cholangiocarcinoma". Oncology Reports 40, no. 6 (2018): 3189-3198. https://doi.org/10.3892/or.2018.6710
Copy and paste a formatted citation
x
Spandidos Publications style
Lin P, Zhong X, Wang X, Li J, Zhao R, He Y, Jiang Y, Huang X, Chen , He Y, He Y, et al: Survival analysis of genome-wide profiles coupled with Connectivity Map database mining to identify potential therapeutic targets for cholangiocarcinoma. Oncol Rep 40: 3189-3198, 2018.
APA
Lin, P., Zhong, X., Wang, X., Li, J., Zhao, R., He, Y. ... Yang, H. (2018). Survival analysis of genome-wide profiles coupled with Connectivity Map database mining to identify potential therapeutic targets for cholangiocarcinoma. Oncology Reports, 40, 3189-3198. https://doi.org/10.3892/or.2018.6710
MLA
Lin, P., Zhong, X., Wang, X., Li, J., Zhao, R., He, Y., Jiang, Y., Huang, X., Chen, ., He, Y., Yang, H."Survival analysis of genome-wide profiles coupled with Connectivity Map database mining to identify potential therapeutic targets for cholangiocarcinoma". Oncology Reports 40.6 (2018): 3189-3198.
Chicago
Lin, P., Zhong, X., Wang, X., Li, J., Zhao, R., He, Y., Jiang, Y., Huang, X., Chen, ., He, Y., Yang, H."Survival analysis of genome-wide profiles coupled with Connectivity Map database mining to identify potential therapeutic targets for cholangiocarcinoma". Oncology Reports 40, no. 6 (2018): 3189-3198. https://doi.org/10.3892/or.2018.6710
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