Quantification of DNA Methylation for Diagnosis and Monitoring of Hepatocellular Carcinoma

DNA甲基化定量分析在肝细胞癌诊断和监测中的应用

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Abstract

BACKGROUND: Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related mortality worldwide, with early detection and accurate monitoring of tumor burden being critical for improving patient outcomes. Existing biomarkers such as alpha-fetoprotein (AFP) have limited sensitivity and specificity, underscoring the need for more reliable diagnostic and prognostic tools. STUDY DESIGN: In this retrospective cohort study, we developed the HCC beta methylation value (HBMV) using 2 targeted CpG amplicon panels, HBMV-6 and HBMV-28. HBMV values were calculated by summing beta methylation values across predefined loci and validated using The Cancer Genome Atlas, 15 Gene Expression Omnibus datasets comprising more than 1,400 liver tissue samples, and a prospective plasma cohort including 18 patients with HCC and 4 noncancer controls. Diagnostic, prognostic, and longitudinal performance was compared with AFP. RESULTS: Both HBMV panels accurately distinguished HCC from noncancer liver tissue, achieving area under the receiver operating characteristic curve values greater than 0.9 in tissue and greater than 0.8 in plasma. Across independent tissue cohorts, HBMV-28 values increased stepwise from normal liver to cirrhosis, dysplasia, and HCC. Higher HBMV values were associated with larger tumor size and worse overall survival. In longitudinal plasma analyses, HBMV decreased after surgical resection or transplantation and increased during disease progression, effectively distinguishing progression from nonprogression with an area under the curve up to 0.87. In contrast, AFP demonstrated modest sensitivity and failed to reliably track treatment response. CONCLUSIONS: HBMV is a sensitive and biologically grounded biomarker for HCC diagnosis, prognosis, and real-time disease monitoring. These findings support further prospective evaluation of HBMV as a noninvasive tool for clinical surveillance and assessment of treatment response.

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