{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T09:01:17Z","timestamp":1773392477002,"version":"3.50.1"},"reference-count":67,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,7,22]],"date-time":"2022-07-22T00:00:00Z","timestamp":1658448000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Genet."],"abstract":"<jats:p><jats:bold>Background:<\/jats:bold> Skin Cutaneous Melanoma (SKCM) is known as an aggressive malignant cancer, which could be directly derived from melanocytic nevi. However, the molecular mechanisms underlying the malignant transformation of melanocytes and melanoma tumor progression still remain unclear. Increasing research showed significant roles of epigenetic modifications, especially DNA methylation, in melanoma. This study focused on the identification and analysis of methylation-regulated differentially expressed genes (MeDEGs) between melanocytic nevus and malignant melanoma in genome-wide profiles.<\/jats:p><jats:p><jats:bold>Methods:<\/jats:bold> The gene expression profiling datasets (GSE3189 and GSE114445) and gene methylation profiling datasets (GSE86355 and GSE120878) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified via GEO2R. MeDEGs were obtained by integrating the DEGs and DMGs. Then, a functional enrichment analysis of MeDEGs was performed. STRING and Cytoscape were used to describe the protein-protein interaction (PPI) network. Furthermore, survival analysis was implemented to select the prognostic hub genes. Next, we conducted gene set enrichment analysis (GSEA) of hub genes. To validate, SKCM cell culture and lentivirus infection was performed to reveal the expression and behavior pattern of KIF2C. Patients and specimens were collected and then immunohistochemistry (IHC) staining was conducted.<\/jats:p><jats:p><jats:bold>Results:<\/jats:bold> We identified 237 hypomethylated, upregulated genes and 182 hypermethylated, downregulated genes. Hypomethylation-upregulated genes were enriched in biological processes of the oxidation-reduction process, cell proliferation, cell division, phosphorylation, extracellular matrix disassembly and protein sumoylation. Pathway enrichment showed selenocompound metabolism, small cell lung cancer and lysosome. Hypermethylation-downregulated genes were enriched in biological processes of positive regulation of transcription from RNA polymerase II promoter, cell adhesion, cell proliferation, positive regulation of transcription, DNA-templated and angiogenesis. The most significantly enriched pathways involved the transcriptional misregulation in cancer, circadian rhythm, tight junction, protein digestion and absorption and Hippo signaling pathway. After PPI establishment and survival analysis, seven prognostic hub genes were CKS2, DTL, KIF2C, KPNA2, MYBL2, TPX2, and FBL. Moreover, the most involved hallmarks obtained by GSEA were E2F targets, G2M checkpoint and mitotic spindle. Importantly, among the 7 hub genes, we found that down-regulated level of KIF2C expression significantly inhibited the proliferative ability of SKCM cells and suppressed the metastasis capacity of SKCM cells.<\/jats:p><jats:p><jats:bold>Conclusions:<\/jats:bold> Our study identified potential aberrantly methylated-differentially expressed genes participating in the process of malignant transformation from nevus to melanoma tissues based on comprehensive genomic profiles. Transcription profiles of CKS2, DTL, KIF2C, KPNA2, MYBL2, TPX2, and FBL provided clues of aberrantly methylation-based biomarkers, which might improve the development of precision medicine. KIF2C plays a pro-tumorigenic role and potentially inhibited the proliferative ability in SKCM.<\/jats:p>","DOI":"10.3389\/fgene.2022.817656","type":"journal-article","created":{"date-parts":[[2022,7,22]],"date-time":"2022-07-22T14:40:55Z","timestamp":1658500855000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Identification of aberrantly methylated differentially expressed genes and pro-tumorigenic role of KIF2C in melanoma"],"prefix":"10.3389","volume":"13","author":[{"given":"Chun-Hui","family":"Huang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi-Zhu","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guo-Liang","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2022,7,22]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"1518","DOI":"10.1158\/0008-5472.CAN-11-1971","article-title":"Tpx2 controls spindle integrity, genome stability, and tumor development","volume":"72","author":"Aguirre-Portoles","year":"2012","journal-title":"Cancer Res."},{"key":"B2","doi-asserted-by":"publisher","first-page":"1560","DOI":"10.1080\/15384101.2017.1348080","article-title":"How TPX2 helps microtubules branch out","volume":"16","author":"Alfaro-Aco","year":"2017","journal-title":"Cell Cycle"},{"key":"B3","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1038\/75556","article-title":"Gene ontology: Tool for the unification of biology. 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