ArticleAnnals of translational medicine2022
Identification of significant genes with a poor prognosis in skin cutaneous malignant melanoma based on a bioinformatics analysis.
Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Polyamine Metabolism and the DHPS/eIF5A Hypusination Axis: From Metabolic Reprogramming to a Therapeutic Achilles' Heel in Melanoma.Biomolecules · 2026Review
- Pigmentation-dependent expression of pheomelanogenesis-related genes in human melanoma cells.Postepy dermatologii i alergologii · 2026Article
- Identification of multiple prognostic biomarker sets for risk stratification in SKCM.Frontiers in bioinformatics · 2025Article
- A Mendelian randomization study of genetic liability to cutaneous melanoma and sunburns.Frontiers in oncology · 2024Article
- An Inflammation-Associated Prognosis Model for Hepatocellular Carcinoma Based on Adenylate Uridylate- (AU-) Rich Element Genes.Mediators of inflammation · 2023Article
- The clinical significance, immune infiltration, and tumor mutational burden of angiogenesis-associated lncRNAs in kidney renal clear cell carcinoma.Frontiers in immunology · 2022Article
- Upregulation of SERPINE2 Results in Poor Prognosis of Hepatoblastoma via Promoting Invasion Abilities.Disease markers · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Skin cutaneous malignant melanoma (SKCM) is a deadly mutated malignancy that arises from melanocytes in the basal layer of the skin. This study sought to identify effective treatment targets that could serve as prospective therapeutic targets to improve patient outcomes. Methods: The GSE83583, GSE111766, and GSE104849 data sets from the GPL10558 platform in the Gene Expression Omnibus (GEO) were used in this study. The candidate genes were identified using the GEO2R tool and a Venn diagram. The Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Gene and Genome (KEGG) preliminary analyses of the differentially expressed genes (DEGs) were conducted using the Database for Annotation, Visualization and Integrated Discovery, and R software. The protein-protein interaction (PPI) network was examined using Cytoscape software. The survminer package was used to examine the overall survival of patients with the identified genes. The Human Protein Atlas (HPA) was used to verify the protein levels of significant genes with poor prognosis. The highly expressed genes in the melanoma tissues were visualized using the ggplot2 package. Results: In total, 160 DEGs from 124 melanoma tissues and 9 normal melanocyte tissues were examined in this study. Cytoscape displayed 19 central nodes from the 160 DEGs. The re-analysis showed that the cytochrome P450 family 1 subfamily B member 1 ( Conclusions:
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