| Exploring Methylation Signatures for High De Novo Recurrence Risk in Hepatocellular carcinoma |
Da-Won Kim1,2, Jin Hyun Park3, Suk Kyun Hong4,5, Min-Hyeok Jung2,6, Ji-One Pyeon2, Jin-Young Lee6, Kyung-Suk Suh4,5, Nam-Joon Yi4,5, YoungRok Choi4,5, Kwang-Woong Lee4,5
, Young-Joon Kim2,6
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1Interdisciplinary Program of Integrated OMICS for Biomedical Science, Yonsei University, Seoul, Republic of Korea
2R&D center, LepiDyne Inc., Seoul, Republic of Korea
3Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul National University College of Medicine, Seoul, Republic of Korea
4Department of Surgery, Seoul National University Hospital, Seoul, Republic of Korea
5Department of Surgery, Seoul National University College of Medicine, Seoul, Republic of Korea
6Department of Biochemistry, College of Life Science and Biotechnology, Yonsei University, Seoul, Republic of Korea |
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Received: October 11, 2024 Revised: December 23, 2024 Accepted: January 7, 2025
*Da-Won Kim, Jin Hyun Park and Suk Kyun Hong contributed equally to this work. |
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| ABSTRACT |
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Background/Aims
Hepatocellular carcinoma (HCC) exhibits high de novo recurrence rates post-resection. Current post-surgery recurrence prediction methods are limited, emphasizing the need for reliable biomarkers to assess recurrence risk. We aimed to develop methylation-based markers for classifying HCC patients and predicting their risk of de novo recurrence post-surgery.
Methods
In this retrospective cohort study, we analyzed data from HCC patients who underwent surgical resection in Korea, excluding those with recurrence within one-year post-surgery. Using the Infinium Methylation EPIC array on 140 samples in the discovery cohort, we classified patients into low- and high-risk groups based on methylation profiles. Distinctive markers were identified through random forest analysis. These markers were validated in The Cancer Genome Atlas (TCGA; n=217), Validation Cohort 1 (n=63) and experimental validation using a methylation-sensitive high-resolution melting (MS-HRM) assay in Validation Cohort 1 and Validation Cohort 2 (n=63).
Results
The low-risk recurrence group (Methylation Group 1; MG1) showed a methylation average of 0.73 (95% CI, 0.69-0.77) with a 23.5% recurrence rate, while the high-risk group (MG2) had an average of 0.17 (95% CI, 0.14-0.20) with a 44.1% recurrence rate (p<0.03). Validation confirmed the applicability of methylation markers across diverse populations, showing high accuracy in predicting the probability of HCC recurrence risk (AUC 96.8%). The MS-HRM assay confirmed its effectiveness in predicting de novo recurrence with 95.5% sensitivity, 89.7% specificity, and 92.2% accuracy.
Conclusions
Methylation markers effectively classified HCC patients by de novo recurrence risk, enhancing prediction accuracy and potentially offering personalized management strategies. |
| KeyWords:
Hepatocellular carcinoma, DNA methylation, Biomarker, Recurrence, Machine learning |
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