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Identification of prognostic biomarkers for malignant melanoma using microarray datasets

  • Authors:
    • Guanyu Lin
    • Guoqian Yin
    • Yuyong Yan
    • Bojie Lin
  • View Affiliations / Copyright

    Affiliations: Department of Plastic and Aesthetic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
    Copyright: © Lin et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 5243-5254
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    Published online on: September 24, 2019
       https://doi.org/10.3892/ol.2019.10914
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Abstract

Malignant melanoma is one of the most common types of cancer worldwide. Efforts have been made to elucidate the pathology of malignant melanoma. However, its molecular mechanisms remain unclear. Therefore, the microarray datasets GSE3189, GSE4570 and GSE4587 from the Gene Expression Omnibus database were used for the elucidation of candidate genes involved in the initiation and progression of melanoma. Assessment of the microarray datasets led to the identification of differentially expressed genes (DEGs), which were subsequently used for function enrichment analysis. These data were utilized in the construction of the protein‑protein interaction network and module analysis was conducted using STRING and Cytoscape software. The results of these analyses led to the identification of a total of 182 DEGs, including 52 downregulated and 130 upregulated genes. The functions and pathways found to be enriched in the DEGs were GTPase activity, transcription from RNA polymerase II promoter, apoptotic processes, cell adhesion, membrane related pathways, calcium signaling cascade and the PI3K‑Akt signaling pathway. The identified genes were demonstrated to belong to a set of 10 hub genes biologically involved in proliferation, apoptosis, cytokinesis, adhesion and migration. Survival analysis and Oncomine database analysis revealed that the calmodulin gene family, BAX and VEGFA genes, may be associated with the initiation, invasion or recurrence of melanoma. In conclusion, the DEGs and hub genes identified in the present study may be used to understand the molecular pathways involved in the initiation and progression of malignant melanoma. Furthermore, the present study may aid in the identification of possible targets for the diagnosis and treatment of melanoma.
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Copy and paste a formatted citation
Spandidos Publications style
Lin G, Yin G, Yan Y and Lin B: Identification of prognostic biomarkers for malignant melanoma using microarray datasets. Oncol Lett 18: 5243-5254, 2019.
APA
Lin, G., Yin, G., Yan, Y., & Lin, B. (2019). Identification of prognostic biomarkers for malignant melanoma using microarray datasets. Oncology Letters, 18, 5243-5254. https://doi.org/10.3892/ol.2019.10914
MLA
Lin, G., Yin, G., Yan, Y., Lin, B."Identification of prognostic biomarkers for malignant melanoma using microarray datasets". Oncology Letters 18.5 (2019): 5243-5254.
Chicago
Lin, G., Yin, G., Yan, Y., Lin, B."Identification of prognostic biomarkers for malignant melanoma using microarray datasets". Oncology Letters 18, no. 5 (2019): 5243-5254. https://doi.org/10.3892/ol.2019.10914
Copy and paste a formatted citation
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Spandidos Publications style
Lin G, Yin G, Yan Y and Lin B: Identification of prognostic biomarkers for malignant melanoma using microarray datasets. Oncol Lett 18: 5243-5254, 2019.
APA
Lin, G., Yin, G., Yan, Y., & Lin, B. (2019). Identification of prognostic biomarkers for malignant melanoma using microarray datasets. Oncology Letters, 18, 5243-5254. https://doi.org/10.3892/ol.2019.10914
MLA
Lin, G., Yin, G., Yan, Y., Lin, B."Identification of prognostic biomarkers for malignant melanoma using microarray datasets". Oncology Letters 18.5 (2019): 5243-5254.
Chicago
Lin, G., Yin, G., Yan, Y., Lin, B."Identification of prognostic biomarkers for malignant melanoma using microarray datasets". Oncology Letters 18, no. 5 (2019): 5243-5254. https://doi.org/10.3892/ol.2019.10914
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