A qualitative prognostic biomarker for melanoma based on the relative methylation orderings of CpG loci
Skin cutaneous melanoma (SKCM) is an aggressive tumor with a poor prognosis. We developed SKCM-P8, a novel qualitative prognostic biomarker based on the relative methylation orderings of eight pairs of loci. Analysis of a training cohort and two independent validation datasets revealed a significant...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Epigenetics |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/15592294.2025.2487316 |
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| Summary: | Skin cutaneous melanoma (SKCM) is an aggressive tumor with a poor prognosis. We developed SKCM-P8, a novel qualitative prognostic biomarker based on the relative methylation orderings of eight pairs of loci. Analysis of a training cohort and two independent validation datasets revealed a significant difference in overall survival between high- and low-risk groups stratified by SKCM-P8 (p < 0.05, log-rank test), with average area under the curve values of 0.83, 0.80, and 0.61, respectively. The differential methylation loci between high- and low-risk patients were enriched in immune-related biological processes and signaling pathways. Furthermore, low-risk patients exhibited higher CD8+ T cells and B levels, while high-risk patients had higher monocytes. The methylation levels of SKCM-P8 were also correlated with immune cell levels, indicating that they can reflect prognosis-related immune information. The low-risk group had a significantly higher mutation burden (p < 0.05, Wilcoxon test), suggesting potential benefits from immune checkpoint inhibitors. Patients stratified by SKCM-P8 displayed differential responses to therapy and immunotherapy (p < 0.05, Wilcoxon test), with low-risk patients showing better sensitivity and response. Furthermore, SKCM-P8 demonstrated super-predictive accuracy compared to six published models. Overall, SKCM-P8 offers a promising tool for predicting prognosis and guiding therapeutic decisions in SKCM. |
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| ISSN: | 1559-2294 1559-2308 |