Comprehensive analysis of aberrantly methylated differentially expressed genes and validation of CDC6 in melanoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39052109", "kind": "science-record", "revision": 3, "content_hash": "sha256:23bf24e1e5f1d4702a6973c8c64a7e0ebc70fa0351a27c37c4a62d593fb14aa5", "created_at": "2026-11-01T20:29:07Z", "updated_at": "2026-11-01T22:12:18Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Comprehensive analysis of aberrantly methylated differentially expressed genes and validation of CDC6 in melanoma.", "doi": "10.1007/s00432-024-05851-x", "pmid": "39052109", "authors": ["Li Liao", "Wei Han", "Yue Shen", "Guoliang Shen"], "journal": "Journal of cancer research and clinical oncology", "year": 2024, "abstract": "BACKGROUND: Skin Cutaneous Melanoma (SKCM) is a highly aggressive malignant tumor with a significant increase in mortality upon metastasis. The molecular mechanisms driving melanoma progression remain largely unclear. Recent studies have highlighted the importance of epigenetic alterations, especially DNA methylation, in melanoma development. This study aims to identify and analyze methylation-regulated differentially expressed genes (MeDEGs) in genome-wide profiles between primary and metastatic melanoma.\nMETHODS: Gene expression profiling datasets GSE8401 and gene methylation profiling datasets GSE86355 were collected from the GEO database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were systematically identified. Integration of DEGs and DMGs yielded a set of MeDEGs, which subsequently underwent functional enrichment analysis. The protein-protein interaction (PPI) network was constructed using STRING and visualized using Cytoscape software. Survival analysis was used to select prognostic hub genes. In addition, 37 SKCM and 37 normal skin tissues from the First Affiliated Hospital of Soochow University (FAHSU) were collected for immunohistochemical (IHC) staining and evaluation. Furthermore, DNA methylation patterns of CDC6 were analyzed. To validate these findings, SKCM cell cultures were utilized to elucidate the expression and behavioral characteristics of CDC6. Additionally, gene set enrichment analysis (GSEA) and immune infiltration analysis were conducted for CDC6.\nRESULTS: In our study, we discovered 120 hypomethylated-upregulated genes and 212 hypermethylated-downregulated genes. The hypomethylated-upregulated genes were notably associated with biological processes such as spindle assembly checkpoint signaling, mitotic spindle assembly, and negative regulation of mitotic metaphase/anaphase transition. Our pathway analysis revealed significant enrichment in pathways related to dilated cardiomyopathy, amino sugar metabolism, progesterone-mediated oocyte maturation, and chemical carcinogenesis. Conversely, hypermethylated-downregulated genes were found to be enriched in processes like epidermis development, keratinocyte differentiation, and skin development. Additionally, pathway analysis highlighted associations with estrogen signaling, Staphylococcus aureus infection, axon guidance, and arachidonic acid metabolism. Following the establishment of PPI networks and survival analysis, we identified 11 prognostic hub genes: CCNA2, CDC6, CDCA3, CKS2, DTL, HJURP, KRT5, KRT14, KRT15, KRT16, and NEK2. Notably, among the 11 hub genes, our findings indicate that CDC6 plays a pivotal role in enhancing the proliferation, migration, and invasion capabilities of melanoma cells in vitro.\nCONCLUSIONS: Our comprehensive genomic analyses reveal that genes with aberrant methylation exhibit differential expression during the transition from primary to metastatic melanoma. The identified genes, especially CDC6, which plays a crucial role in enhancing melanoma cell proliferation, migration, and invasion, provide valuable insights into potential methylation-based biomarkers. These findings could contribute significantly to advancing precision medicine in SKCM.", "claims": [{"id": "claim-method", "statement": "Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified using the GEO2R tool (http://www.ncbi.nlm.nih.gov/geo/geo2r/) with |t| > 2 and adj.p < 0.05 as significance criteria.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39052109", "locator": "sections[4] \"Data mining from public databases\" paragraph 3", "quote": "Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified using the GEO2R tool (http://www.ncbi.nlm.nih.gov/geo/geo2r/) with |t| > 2 and adj.p < 0.05 as significance criteria."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Data availabilityNo datasets were generated or analysed during the current study.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39052109", "locator": "sections[38] \"notes\" paragraph 1", "quote": "Data availabilityNo datasets were generated or analysed during the current study."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified 11 prognostic hub genes and found that high CDC6 expression was associated with poor prognosis in SKCM.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39052109", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Notably, among the 11 hub genes, our findings indicate that CDC6 plays a pivotal role in enhancing the proliferation, migration, and invasion capabilities of melanoma cells in vitro."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The study identified 11 prognostic hub genes and found that high CDC6 expression was associated with poor prognosis in SKCM.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:39052109"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. 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