Genome-Wide DNA Methylation Markers Associated With Metabolic Liver Cancer
Metabolic liver disease is the fastest-rising cause of hepatocellular carcinoma (HCC), but the underlying molecular processes that drive HCC development in the setting of metabolic perturbations are unclear. We investigated the role of aberrant DNA methylation in metabolic HCC development in a multi...
| Autores: | , , , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:dnet:idus________::a23947d840d948575e3070a74a1d6d89 |
| Acceso en línea: | https://hdl.handle.net/11441/185889 |
| Access Level: | acceso abierto |
| Palabra clave: | Liver Cancer HCC MASLD NAFLD Metabolic Dysfunction-Associated Steatotic Liver Disease |
| Sumario: | Metabolic liver disease is the fastest-rising cause of hepatocellular carcinoma (HCC), but the underlying molecular processes that drive HCC development in the setting of metabolic perturbations are unclear. We investigated the role of aberrant DNA methylation in metabolic HCC development in a multicenter international study. METHODS: We used a case-control design, frequency-matched on age, sex, and study site. Genome-wide profiling of peripheral blood leukocyte DNA was performed using the 850k EPIC array. The study sample was split 80% and 20% for training and validation. Cell type proportions were estimated from the methylation data. Differential methylation analysis was performed adjusting for cell type, generating area under the receiver-operating characteristic curves (AUC-ROC). RESULTS: We enrolled 272 metabolic HCC patients and 316 control patients with metabolic liver disease from 6 sites. Fifty-five differentially methylated CpGs were identified; 33 hypermethylated and 22 hypomethylated in cases vs controls. The panel of 55 CpGs discriminated between the cases and controls with AUC ¼ 0.79 (95% confidence interval [CI] ¼ 0.71–0.87), sensitivity ¼ 0.77 (95% CI ¼ 0.66–0.89), and specificity ¼ 0.74 (95% CI ¼ 0.64–0.85). The 55-CpG classifier panel performed better than a base model that comprised age, sex, race, and diabetes mellitus (AUC ¼ 0.65, 95% CI ¼ 0.55–0.75; sensitivity ¼ 0.62, 95% CI ¼ 0.49–0.75; and specificity ¼ 0.64, 95% CI ¼ 0.52–0.75). A multifactorial model that combined the 55 CpGs with age, sex, race, and diabetes yielded AUC ¼ 0.78 (95% CI ¼ 0.70–0.86), sensitivity ¼ 0.81 (95% CI ¼ 0.71–0.92), and specificity ¼ 0.67 (95% CI ¼ 0.55–0.78). CONCLUSION: A panel of 55 blood leukocyte DNA methylation markers differentiates patients with metabolic HCC from control patients with benign metabolic liver disease, with a slightly higher sensitivity when combined with demographic and clinical information. |
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