ArticleJournal of cellular and molecular medicine2020
Screening and identification of potential prognostic biomarkers in metastatic skin cutaneous melanoma by bioinformatics analysis.
Article in Journal of cellular and molecular medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 27 citations in OpenAlex.
- Filaggrin as a potential biomarker in gastric cancer: insights from multi-omics analysis and experimental validation.Frontiers in immunology · 2026Article
- Experimentally validated oxidative stress -associated prognostic signatures describe the immune landscape and predict the drug response and prognosis of SKCM.Frontiers in immunology · 2024Article
- Envoplakin Inhibits Macrophage Polarization by Altering the Inflammatory Tumor Microenvironment of Melanoma Through the RAS / ERK Signaling Pathway.Journal of inflammation research · 2024Article
- Prognostic assessment capability of a five-gene signature in pancreatic cancer: a machine learning based-study.BMC gastroenterology · 2023Article
- Construction and comprehensive analysis of a novel prognostic signature associated with pyroptosis molecular subtypes in patients with pancreatic adenocarcinoma.Frontiers in immunology · 2023Article
- Bioinformatic analysis identifies epidermal development genes that contribute to melanoma progression.Medical oncology (Northwood, London, England) · 2022Article
- Revisiting miRNA Association with Melanoma Recurrence and Metastasis from a Machine Learning Point of View.International journal of molecular sciences · 2022Review
- Identification of Biomarkers Associated With CD4Frontiers in immunology · 2022Article
- Genomic and Transcriptomic Underpinnings of Melanoma Genesis, Progression, and Metastasis.Cancers · 2021Review
- Review
- Identification of small proline-rich protein 1B (SPRR1B) as a prognostically predictive biomarker for lung adenocarcinoma by integrative bioinformatic analysis.Thoracic cancer · 2021Article
- Integration Analysis of m6A Related Genes in Skin Cutaneous Melanoma and the Biological Function Research of the SPRR1B.Frontiers in oncology · 2021Article
- Screening and identification of potential prognostic biomarkers in metastatic skin cutaneous melanoma by bioinformatics analysis.Journal of cellular and molecular medicine · 2020Article
- Identification of lncRNA-mRNA Regulatory Module to Explore the Pathogenesis and Prognosis of Melanoma.Frontiers in cell and developmental biology · 2020Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Skin cutaneous melanoma (SKCM) is a multifactorial disease that presents a poor prognosis due to its rapid progression towards metastasis. This study focused on the identification of prognostic differentially expressed genes (DEGs) between primary and metastatic SKCM. DEGs were obtained using three chip data sets from the Gene Expression Omnibus database. The protein-protein interaction network was described by STRING and Cytoscape. Kaplan-Meier curves were implemented to evaluate survival benefits within distinct groups. A total of 258 DEGs were distinguished as possible candidate biomarkers. Besides, survival curves indicated that DSG3, DSC3, PKP1, EVPL, IVL, FLG, SPRR1A and SPRR1B were of significant value to predict the metastatic transformation of melanoma. To further validate our hypotheses, functional enrichment and significant pathways of the hub genes were performed to indicate that the most involved considerable path. In summary, this study identified substantial DEGs participating in melanoma metastasis. DGS3, DSC3, PKP1, EVPL, IVL, FLG, SPRR1A and SPRR1B may be considered as new biomarkers in the therapeutics of metastatic melanoma, which might help us predict the potential metastatic capability of SKCM patients, thus provide earlier precautionary treatments. However, further experiments are still required to support the specific mechanisms of these hub genes.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.