Bioinformatic Analysis Identifies Potential Key Genes in the Pathogenesis of Melanoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33178610", "kind": "science-record", "revision": 7, "content_hash": "sha256:8f94209df0ecb95545ff7b6a2cbbd944a24c08c0be94fdf6a2f6e30fbd98d554", "created_at": "2026-11-01T15:41:15Z", "updated_at": "2026-11-01T22:02:29Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatic Analysis Identifies Potential Key Genes in the Pathogenesis of Melanoma.", "doi": "10.3389/fonc.2020.581985", "pmid": "33178610", "authors": ["Yanjie Han", "Xinxin Li", "Jiliang Yan", "Chunyan Ma", "Xin Wang", "Hong Pan", "Xiaoli Zheng", "Zhen Zhang", "Biao Gao", "Xin-Ying Ji"], "journal": "Frontiers in oncology", "year": 2020, "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.", "claims": [{"id": "claim-method", "statement": "Available TCGA patient survival data were used for Kaplan–Meier survival analysis and to generate overall survival plots.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33178610", "locator": "sections[9] \"Hub Genes Expression Level and Survival Analysis\" paragraph 2", "quote": "Available TCGA patient survival data were used for Kaplan–Meier survival analysis and to generate overall survival plots."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/geo/, https://cancergenome.nih.gov/abouttcga/overview.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33178610", "locator": "sections[21] \"Data Availability Statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. 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RAB25 CALML3 KCNK7 EXPH5 TACC2 SPINK5 NEBL DSG3 ADH1B FERMT1 PKP3 DUOX1 CEBPA SLC24A3 ALOX15B CDS1 PTPRF HLA-DQB2 ARHGEF4 GJB3 PDZD2 CLEC3B NMU SPINT2 BCL11A LY6G6C MMP28 C1orf68 SCGB1D2 GPR87 F2RL1 DEFB1 LAD1 LAMB4 MAOA ALOXE3 PAMR1 NTRK2 SLC15A1 ARG1 KRT19 HLF C1orf106 PDZK1IP1 PALMD RNF39 PPP1R13L AIM1 ACSBG1 AKR1C2 PLLP NPY1R AP1M2 KRT31 KRT7 FAT2 PTGS1 IVL CDHR1 ZBTB16 SCNN1B IRF6 ATP2C2 IRX4 ACSL1"], ["Down-regulated genes", "TRIB2 SLC16A4 SNX10 BCL2A1 AP1S2 ALX1 UPP1 PHLDA1 SOX10 ETV5 PLAT LEF1 CITED1 IGF2BP3 SERPINE2 SPP1"]], "row_count": 3, "column_count": 2, "numeric_cells": 2, "header_rows": 1, "locator": "section[12]/table-wrap[1]#T1"}}, {"id": "asset:table:pmid:33178610:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:86b851fcef0c2fd5f3a2a05f36bbee93cb72b3f80afc2920494e376b16a9db36", "bytes": 356, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[15]/table-wrap[1]#T2", "version": null, "note": "The statistical results of connectivity degrees of the PPI network.", "structure": {"pmcid": "PMC7596746", "section_index": 15, "section_title": "PPI Network Analysis", "row_count": 10, "column_count": 2}, "table": {"label": "Table 2", "caption": "The statistical results of connectivity degrees of the PPI network.", "rows": [["Gene", "Degree"], ["LOR", "26"], ["FLG", "25"], ["KRT5", "24"], ["CDSN", "24"], ["DSG1", "22"], ["DSG3", "22"], ["KRT1", "21"], ["IVL", "21"], ["EGFR", "21"]], "row_count": 10, "column_count": 2, "numeric_cells": 9, "header_rows": 1, "locator": "section[15]/table-wrap[1]#T2"}}], "gaps": ["asset:data:geo:GSE15605 not downloaded", "asset:data:geo:GSE15605 licence not read", "asset:data:geo:GSE46517 not downloaded", "asset:data:geo:GSE46517 licence not read", "asset:data:geo:GSE7553 not downloaded", "asset:data:geo:GSE7553 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": 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catalogue: ppi_network."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE15605", "GSE46517", "GSE7553"], "resolved_accessions": ["GSE15605", "GSE46517", "GSE7553"], "statements": ["Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/geo/, https://cancergenome.nih.gov/abouttcga/overview."], "basis": "The paper names GSE15605, GSE46517, GSE7553 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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