Open Access

Pathway deviation-based biomarker and multi-effect target identification in asbestos-related squamous cell carcinoma of the lung

  • Authors:
    • Jiang Du
    • Lin Zhang
  • View Affiliations

  • Published online on: February 6, 2017     https://doi.org/10.3892/ijmm.2017.2878
  • Pages: 579-586
  • Copyright: © Du et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Asbestos-related lung carcinoma is one of the most devastating occupational cancers, and effective techniques for early diagnosis are still lacking. In the present study, a systematic approach was applied to detect a potential biomarker for asbestos-related lung cancer (ARLC); in particular asbestos-related squamous cell carcinoma (ARLC-SCC). Microarray data (GSE23822) were retrieved from the Gene Expression Omnibus database, including 26 ARLC-SCCs and 30 non-asbestos-related squamous cell lung carcinomas (NARLC-SCCs). Differentially expressed genes (DEGs) were identified by the limma package, and then a protein-protein interaction (PPI) network was constructed according to the BioGRID and HPRD databases. A novel scoring approach integrating an expression deviation score and network degree of the gene was then proposed to weight the DEGs. Subsequently, the important genes were uploaded to DAVID for pathway enrichment analysis. Pathway correlation analysis was carried out using Spearman's rank correlation coefficient of the pathscore. In total, 1,333 DEGs, 391 upregulated and 942 downregulated, were obtained between the ARLC-SCCs and NARLC-SCCs. A total of 524 important genes for ARLC-SCC were significantly enriched in 22 KEGG pathways. Correlation analysis of these pathways showed that the pathway of SNARE interactions in vesicular transport was significantly correlated with 12 other pathways. Additionally, obvious correlations were found between multiple pathways by sharing cross-talk genes (EGFR, PRKX, PDGFB, PIK3R3, SLK, IGF1, CDC42 and PRKCA). On the whole, our data demonstrate that 8 cross-talk genes were found to bridge multiple ARLC-SCC-specific pathways, which may be used as candidate biomarkers and potential multi-effect targets. As these genes are involved in multiple pathways, it is possible that drugs targeting these genes may thus be able to influence multiple pathways simultaneously.
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March-2017
Volume 39 Issue 3

Print ISSN: 1107-3756
Online ISSN:1791-244X

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Spandidos Publications style
Du J and Du J: Pathway deviation-based biomarker and multi-effect target identification in asbestos-related squamous cell carcinoma of the lung. Int J Mol Med 39: 579-586, 2017
APA
Du, J., & Du, J. (2017). Pathway deviation-based biomarker and multi-effect target identification in asbestos-related squamous cell carcinoma of the lung. International Journal of Molecular Medicine, 39, 579-586. https://doi.org/10.3892/ijmm.2017.2878
MLA
Du, J., Zhang, L."Pathway deviation-based biomarker and multi-effect target identification in asbestos-related squamous cell carcinoma of the lung". International Journal of Molecular Medicine 39.3 (2017): 579-586.
Chicago
Du, J., Zhang, L."Pathway deviation-based biomarker and multi-effect target identification in asbestos-related squamous cell carcinoma of the lung". International Journal of Molecular Medicine 39, no. 3 (2017): 579-586. https://doi.org/10.3892/ijmm.2017.2878