ArticleClinical, cosmetic and investigational dermatology2025
Multi-Omics Integration with Machine Learning and Molecular Docking Reveals Crosstalk Mechanisms and Drug Candidates in Metastatic Melanoma and Vitiligo.
Article in Clinical, cosmetic and investigational dermatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Ultra-High-Frequency Ultrasound of Melanoma Excision Scars for Detection of Clinically Occult Local Recurrence: A Single-Center Retrospective Study.Clinical, cosmetic and investigational dermatology · 2026Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The aim of this study was to systematically elucidate the crosstalk mechanisms between metastatic melanoma and vitiligo and to establish vitiligo and metastasis-based biomarkers as well as to find drug candidates. Methods: The genes associated with vitiligo and metastatic melanoma were obtained through differential expression analysis and WGCNA using publicly available data from GEO and TCGA. A prognostic model and nomogram for melanoma were subsequently constructed using hub genes based on machine learning algorithms. A comprehensive assessment was conducted of the correlation between hub genes and overall survival, functional annotations, immune cells and immune checkpoint genes. At the single-cell level, we conducted scoring using the AUCell algorithm and CellChat analysis to facilitate more profound biological exploration. The Cmap database and molecular docking methods were used to screen drug candidates. Results: Following the screening process, a total of six hub genes ( Conclusion: Our study firstly provides new insight into the genetic crosstalk between metastatic melanoma and vitiligo that may facilitate the development of personalized treatments.
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