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Systematic tracking of altered modules identifies the key biomarkers involved in chronic lymphocytic leukemia

  • Authors:
    • Xin Lu
    • Zhen Wu
    • Xue‑Ying Zhao
    • Chun‑Feng Li
    • Shi‑Feng Kan
  • View Affiliations / Copyright

    Affiliations: Department of Blood Transfusion, Second Hospital of Shandong University, Jinan, Shandong 250033, P.R. China, Department of Laboratory Medicine, Qilu Hospital of Shandong University, Jinan, Shandong 250012, P.R. China
    Copyright: © Lu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 2351-2355
    |
    Published online on: December 7, 2018
       https://doi.org/10.3892/ol.2018.9812
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Abstract

Key genes in chronic lymphocytic leukemia (CLL) were investigated through systematically tracking the dysregulated modules from protein‑protein interaction (PPI) networks. Microarray data of normal subjects and CLL patients recruited from ArrayExpress database were applied to extract differentially expressed genes (DEGs). Additionally, we re‑weighted the PPI network of normal and CLL conditions by means of Pearson's correlation coefficient (PCC). Furthermore, clique‑merging method was applied to extract the modules and then the altered modules were screened out. The intersection genes were selected from miss and add genes in the altered modules. The common genes were screened from the intersection genes and DEGs in CLL. A total of 734 DEGs were screened by statistical analysis. In this investigation, there were 1,805 and 703 modules in normal as well as disease PPI network. In addition, 875 altered modules were obtained which included 145 miss genes, 353 add genes and 85 intersection genes. Finally, in‑depth analysis revealed 9 mutual genes between the intersection genes and DEGs in CLL. Our analysis revealed several key genes associated with CLL by systematically tracking the dysregulated modules, which might be candidate targets for diagnosis and management of CLL.
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Copy and paste a formatted citation
Spandidos Publications style
Lu X, Wu Z, Zhao XY, Li CF and Kan SF: Systematic tracking of altered modules identifies the key biomarkers involved in chronic lymphocytic leukemia. Oncol Lett 17: 2351-2355, 2019.
APA
Lu, X., Wu, Z., Zhao, X., Li, C., & Kan, S. (2019). Systematic tracking of altered modules identifies the key biomarkers involved in chronic lymphocytic leukemia. Oncology Letters, 17, 2351-2355. https://doi.org/10.3892/ol.2018.9812
MLA
Lu, X., Wu, Z., Zhao, X., Li, C., Kan, S."Systematic tracking of altered modules identifies the key biomarkers involved in chronic lymphocytic leukemia". Oncology Letters 17.2 (2019): 2351-2355.
Chicago
Lu, X., Wu, Z., Zhao, X., Li, C., Kan, S."Systematic tracking of altered modules identifies the key biomarkers involved in chronic lymphocytic leukemia". Oncology Letters 17, no. 2 (2019): 2351-2355. https://doi.org/10.3892/ol.2018.9812
Copy and paste a formatted citation
x
Spandidos Publications style
Lu X, Wu Z, Zhao XY, Li CF and Kan SF: Systematic tracking of altered modules identifies the key biomarkers involved in chronic lymphocytic leukemia. Oncol Lett 17: 2351-2355, 2019.
APA
Lu, X., Wu, Z., Zhao, X., Li, C., & Kan, S. (2019). Systematic tracking of altered modules identifies the key biomarkers involved in chronic lymphocytic leukemia. Oncology Letters, 17, 2351-2355. https://doi.org/10.3892/ol.2018.9812
MLA
Lu, X., Wu, Z., Zhao, X., Li, C., Kan, S."Systematic tracking of altered modules identifies the key biomarkers involved in chronic lymphocytic leukemia". Oncology Letters 17.2 (2019): 2351-2355.
Chicago
Lu, X., Wu, Z., Zhao, X., Li, C., Kan, S."Systematic tracking of altered modules identifies the key biomarkers involved in chronic lymphocytic leukemia". Oncology Letters 17, no. 2 (2019): 2351-2355. https://doi.org/10.3892/ol.2018.9812
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