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ABSTRACT: Background
Skin cutaneous melanoma (SKCM) is extremely malignant, leading to poor prognosis. Epigenetic dysregulation, particularly histone modifications, contributes to disease progression. However, effective histone-based prognostic biomarkers are still lacking in clinical practice.Methods
Transcriptomic data from TCGA-SKCM and five GEO datasets were analyzed. Ten machine learning algorithms were integrated to build 101 prognostic models. The optimal model, based on seven histone-related genes, showed the highest C-index and was validated in both training and validation cohorts. WDR77 was identified as the hub gene by random forest analysis. The expression of WDR77 was profiled in SKCM. Survival analysis, pathway enrichment analyses, single-cell and spatial transcriptomic
SUBMITTER: Zhang H
PROVIDER: S-EPMC12711826 | biostudies-literature | 2025
REPOSITORIES: biostudies-literature