Abstract
Acquired erlotinib resistance (AER) during cancer treatment remains a major clinical challenge that results in the recurrence and metastasis of cancers. Therefore, we sought to identify differentially expressed genes (DEGs) by performing a meta-analysis of AER-related microarray datasets and discover biomarkers by conducting a systemic in-silico analysis. Using the RankProd algorithm, we identified 775 DEGs (536 up-regulated and 239 down-regulated). Functional enrichment analyses of the total DEG s suggested that “cell adhesion” and “cytokine-cytokine receptor interactions” may be closely associated with AER process. Some DEGs shared target sites of the potential micro-RNA including miR-21, miR-200b/c, miR-429 and miR-9. Target sites of FOXJ1, NFAT, FOXO4, and JUN were also significantly enriched. From the proteinprotein interaction network, we clustered four functional modules by p-value and node density and found hub genes with many interacting neighbors. Finally, we identified seven candidate hub DEGs (TIMP3, SPARC, ITGA1, CCNA1, SOX2, KRT14, and PTPRZ1) for AER development.
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Lee, Y.S., Kim, J.K., Park, T.H. et al. Systematic identification of novel biomarker signatures associated with acquired erlotinib resistance in cancer cells. Mol. Cell. Toxicol. 12, 139–148 (2016). https://doi.org/10.1007/s13273-016-0018-x
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DOI: https://doi.org/10.1007/s13273-016-0018-x