ArticleFrontiers in immunology2025
A prognostic signature derived from ac4C-associated genes stratifies survival and tumor immune microenvironment in cutaneous melanoma.
Article in Frontiers in immunology, 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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1 citing paper in PubMed.
- Ferroptosis-related lncRNA signature predicts prognosis and treatment response in colon cancer.Translational cancer research · 2026Article
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Abstract
The clinical management of cutaneous melanoma (SKCM) is particularly challenging due to the disease's high degree of heterogeneity, which leads to unpredictable patient outcomes and highly variable responses to therapy. Clinicians are in urgent need of a reliable molecular profile system to predict patient trajectory and guide therapeutic decisions. Recent research emphasizes the pivotal role of N4-acetylcytidine (ac4C) modification, a novel epigenetic mechanism, in promoting diverse human diseases pathogenesis and progression. Nevertheless, its specific impact and the clinical relevance of ac4C-associated genes in SKCM remain to be elucidated. This study aimed to develop an "ac4C-associated Gene Signature" (AGS) to stratify patient prognosis, inform therapeutic decisions, and advance biological insight into cutaneous melanoma. Through integrative analysis of ac4C-related genes in SKCM, we identified 41 differentially expressed candidates and derived three molecular subtypes with distinct clinical outcomes. We subsequently constructed a stable seven-gene signature using Cox-LASSO regression, which effectively stratified patients into high- and low-risk groups in the TCGA cohort and was validated in an independent GEO dataset. The AGS not only predicted survival but also characterized the tumor-immune microenvironment, distinguishing immunologically "hot" from "cold" phenotypes, and suggested potential responses to immunotherapy and chemotherapy. Additional support from the HPA database, cell line models, and RT-qPCR experiments supported the model's biological relevance. In summary, this study provides a clinically applicable prognostic tool for risk stratification and personalized treatment planning in SKCM.
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