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. 2021 Feb 18:11:637320.
doi: 10.3389/fgene.2020.637320. eCollection 2020.

Integrated Bioinformatics Analysis Exhibits Pivotal Exercise-Induced Genes and Corresponding Pathways in Malignant Melanoma

Jun Zhu  1 , Suyu Hao  2 , Xinyue Zhang  3 , Jingyue Qiu  4 , Qin Xuan  5 , Liping Ye  6
Affiliations

Integrated Bioinformatics Analysis Exhibits Pivotal Exercise-Induced Genes and Corresponding Pathways in Malignant Melanoma

Jun Zhu et al. Front Genet. .

Abstract

Malignant melanoma represents a sort of neoplasm deriving from melanocytes or cells developing from melanocytes. The balance of energy and energy-associated body composition and body mass index could be altered by exercise, thereby directly affecting the microenvironment of neoplasm. However, few studies have examined the mechanism of genes induced by exercise and the pathways involved in melanoma. This study used three separate datasets to perform comprehensive bioinformatics analysis and then screened the probable genes and pathways in the process of exercise-promoted melanoma. In total, 1,627 differentially expressed genes (DEGs) induced by exercise were recognized. All selected genes were largely enriched in NF-kappa B, Chemokine signaling pathways, and the immune response after gene set enrichment analysis. The protein-protein interaction network was applied to excavate DEGs and identified the most relevant and pivotal genes. The top 6 hub genes (Itgb2, Wdfy4, Itgam, Cybb, Mmp2, and Parp14) were identified, and importantly, 5 hub genes (Itgb2, Wdfy4, Itgam, Cybb, and Parp14) were related to weak disease-free survival and overall survival (OS). In conclusion, our findings demonstrate the prognostic value of exercise-induced genes and uncovered the pathways of these genes in melanoma, implying that these genes might act as prognostic biomarkers for melanoma.

Keywords: Disease-free survival; exercise; integrated bioinformatics analysis; malignant melanoma; prognosis.

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Conflict of interest statement

SH was employed by company Shuangwu Information Technical Company Ltd, China. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
The heatmap analysis of GSE62628.
FIGURE 2
FIGURE 2
GO and KEGG pathway enrichment analysis. (A) GO analysis of all DEGs. The chart lists the richest Go terms of BP. (B) KEGG pathway analysis of all DEGs. The figure shows the most abundant KEGG pathway.
FIGURE 3
FIGURE 3
The protein-protein interaction (PPI) of DEGs exported from STRING is visualized using Cytoscape software.
FIGURE 4
FIGURE 4
Expression of hub genes in different melanoma stages in the TCGA database. (A) The TCGA database was used to analyze the expression of WDFY4 in melanoma and normal samples. (B) The TCGA database was used to analyze the expression of PARP14 in melanoma and normal samples. (C) The TCGA database was used to analyze the expression of CYBB in melanoma and normal samples. (D) The TCGA database was used to analyze the expression of ITGB2 in melanoma and normal samples. (E) The TCGA database was used to analyze the expression of ITGAM in melanoma and normal samples. (F) The TCGA database was used to analyze the expression of MMP2 in melanoma and normal samples.
FIGURE 5
FIGURE 5
Expression of hub genes was analyzed in the GSE62628 database. (A) The GSE62628 database was used to analyze the expression of WDFY4 in exercise and non-exercise samples. (B) The GSE62628 database was used to analyze the expression of PARP14 in exercise and non-exercise samples. (C) The GSE62628 database was used to analyze the expression of CYBB in exercise and non-exercise samples. (D) The GSE62628 database was used to analyze the expression of ITGB2 in exercise and non-exercise samples. (E) The GSE62628 database was used to analyze the expression of ITGAM in exercise and non-exercise samples. (F) The GSE62628 database was used to analyze the expression of MMP2 in exercise and non-exercise samples.
FIGURE 6
FIGURE 6
Overall survival (OS) analysis of hub genes in melanoma patients in GEPIA database. (A) OS of melanoma patients with the WDFY4 high expression level group (purple) and low expression level group (orange). (B) OS of melanoma patients with the PARP14 high expression level group (purple) and low expression level group (orange). (C) OS of melanoma patients with the CYBB high expression level group (purple) and low expression level group (orange). (D) OS of melanoma patients with the ITGB2 high expression level group (purple) and low expression level group (orange). (E) OS of melanoma patients with the ITGAM high expression level group (purple) and low expression level group (orange). (F) OS of melanoma patients with the MMP2 high expression level group (purple) and low expression level group (orange).
FIGURE 7
FIGURE 7
Disease-free survival (DFS) analysis of hub genes in melanoma patients in GEPIA database. (A) DFS of melanoma patients with the WDFY4 high expression level group (purple) and low expression level group (orange). (B) DFS of melanoma patients with the PARP14 high expression level group (purple) and low expression level group (orange). (C) DFS of melanoma patients with the CYBB high expression level group (purple) and low expression level group (orange). (D) DFS of melanoma patients with the ITGB2 high expression level group (purple) and low expression level group (orange). (E) DFS of melanoma patients with the ITGAM high expression level group (purple) and low expression level group (orange). (F) DFS of melanoma patients with the MMP2 high expression level group (purple) and low expression level group (orange).
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