Bioinformatic Analysis Identifies Potential Key Genes in the Pathogenesis of Melanoma

Yanjie Han,Biao Gao,Zhen Zhang,Xin Wang,Hong Pan,Xinxin Li,Xiaoli Zheng,Jiliang Yan,Xin-Ying Ji,Chunyan Ma

doi:10.3389/fonc.2020.581985

Abstract

Melanoma is the deadliest skin tumor and is prone to distant metastases. The incidence of melanoma has increased rapidly in the past few decades, and current trends indicate that this growth is continuing. This study was aimed to explore the molecular mechanisms of melanoma pathogenesis and discover underlying pathways and genes associated with melanoma. We used high-throughput expression data to study differential expression profiles of related genes in melanoma. The differentially expressed genes (DEGs) of melanoma in GSE15605, GSE46517, GSE7553, and the Cancer Genome Atlas (TCGA) datasets were analyzed. Differentially expressed genes (DEGs) were identified by paired t-test. Then the DEGs were performed cluster and principal component analyses and protein–protein interaction (PPI) network construction. After that, we analyzed the differential genes through bioinformatics and got hub genes. Finally, the expression of hub genes was confirmed in the TCGA databases and collected patient tissue samples. Total 144 up-regulated DEGs and 16 down-regulated DEGs were identified. A total of 17 gene ontology analysis (GO) terms and 11 pathways were closely related to melanoma. Pathway of pathways in cancer was enriched in 8 DEGs, such as junction plakoglobin (JUP) and epidermal growth factor receptor (EGFR). In the PPI networks, 9 hub genes were obtained, such as loricrin (LOR), filaggrin (FLG), keratin 5 (KRT5), corneodesmosin (CDSN), desmoglein 1 (DSG1), desmoglein 3 (DSG3), keratin 1 (KRT1), involucrin (IVL), and EGFR. The pathway of pathways in cancer and its enriched DEGs may play important roles in the process of melanoma. The hub genes of DEGs may become promising melanoma candidate genes. Five key genes FLG, DSG1, DSG3, IVL, and EGFR were identified in the TCGA database and melanoma tissues. The results suggested that FLG, DSG1, DSG3, IVL, and EGFR might play important roles and potentially be valuable in the prognosis and treatment of melanoma. These hub genes might well have clinical significance as diagnostic markers.

Highlights

Melanoma is the most lethal tumor of skin tumors, and prone to distant metastasis [1, 2]
According to the inclusion criteria, three Gene Expression Omnibus (GEO) datasets and the Cancer Genome Atlas (TCGA) dataset were obtained in our study: GSE15605, GSE46517, GSE7553, and TCGA skin cutaneous melanoma data
differentially expressed genes (DEGs) 1,078, 407, 892, and 2,148 from the expression profile datasets GSE15605, GSE46517, GSE7553, and TCGA dataset were extracted, respectively. 160 consistently expressed genes were identified by Venn analysis (Figure 1)

Summary

Introduction

Melanoma is the most lethal tumor of skin tumors, and prone to distant metastasis [1, 2]. The incidence of melanoma has increased rapidly over the past few decades, and current trends indicate that this growth has still been continuing [3,4,5]. Despite encouraging trends related to improved screening and the introduction of new therapies, melanoma remains a major public health problem [6, 7]. There are currently an estimated 1.2 million melanoma survivors in the United States alone [9]. While many previous studies have examined factors associated with survival [10,11,12,13], exhaustive research on the pathogenic genes and markers of melanoma pathogenicity remain scarcely. Data on tumor markers of melanoma can generate important information that can guide treatment, monitoring plans, and point the way for future melanoma research

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