Exploring methylation signatures for high de novo recurrence risk in hepatocellular carcinoma
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...
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Korean Association for the Study of the Liver
2025-04-01
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| Series: | Clinical and Molecular Hepatology |
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| Online Access: | http://e-cmh.org/upload/pdf/cmh-2024-0899.pdf |
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| author | Da-Won Kim Jin Hyun Park Suk Kyun Hong Min-Hyeok Jung Ji-One Pyeon Jin-Young Lee Kyung-Suk Suh Nam-Joon Yi YoungRok Choi Kwang-Woong Lee Young-Joon Kim |
| author_facet | Da-Won Kim Jin Hyun Park Suk Kyun Hong Min-Hyeok Jung Ji-One Pyeon Jin-Young Lee Kyung-Suk Suh Nam-Joon Yi YoungRok Choi Kwang-Woong Lee Young-Joon Kim |
| author_sort | Da-Won Kim |
| collection | DOAJ |
| description | 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 (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% confidence interval [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 (area under the curve 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. |
| format | Article |
| id | doaj-art-ddbb8bfac487423287cc3c7e96f6e6b6 |
| institution | DOAJ |
| issn | 2287-2728 2287-285X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Korean Association for the Study of the Liver |
| record_format | Article |
| series | Clinical and Molecular Hepatology |
| spelling | doaj-art-ddbb8bfac487423287cc3c7e96f6e6b62025-08-20T03:18:50ZengKorean Association for the Study of the LiverClinical and Molecular Hepatology2287-27282287-285X2025-04-0131256357610.3350/cmh.2024.08992144Exploring methylation signatures for high de novo recurrence risk in hepatocellular carcinomaDa-Won Kim0Jin Hyun Park1Suk Kyun Hong2Min-Hyeok Jung3Ji-One Pyeon4Jin-Young Lee5Kyung-Suk Suh6Nam-Joon Yi7YoungRok Choi8Kwang-Woong Lee9Young-Joon Kim10 Interdisciplinary Program of Integrated OMICS for Biomedical Science, Yonsei University, Seoul, Korea Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul National University College of Medicine, Seoul, Korea Department of Surgery, Seoul National University Hospital, Seoul, Korea R&D center, LepiDyne Inc, Seoul, Korea R&D center, LepiDyne Inc, Seoul, Korea Department of Biochemistry, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea Department of Surgery, Seoul National University Hospital, Seoul, Korea Department of Surgery, Seoul National University Hospital, Seoul, Korea Department of Surgery, Seoul National University Hospital, Seoul, Korea Department of Surgery, Seoul National University Hospital, Seoul, Korea R&D center, LepiDyne Inc, Seoul, KoreaBackground/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 (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% confidence interval [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 (area under the curve 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.http://e-cmh.org/upload/pdf/cmh-2024-0899.pdfhepatocellular carcinomadna methylationbiomarkerrecurrencemachine learning |
| spellingShingle | Da-Won Kim Jin Hyun Park Suk Kyun Hong Min-Hyeok Jung Ji-One Pyeon Jin-Young Lee Kyung-Suk Suh Nam-Joon Yi YoungRok Choi Kwang-Woong Lee Young-Joon Kim Exploring methylation signatures for high de novo recurrence risk in hepatocellular carcinoma Clinical and Molecular Hepatology hepatocellular carcinoma dna methylation biomarker recurrence machine learning |
| title | Exploring methylation signatures for high de novo recurrence risk in hepatocellular carcinoma |
| title_full | Exploring methylation signatures for high de novo recurrence risk in hepatocellular carcinoma |
| title_fullStr | Exploring methylation signatures for high de novo recurrence risk in hepatocellular carcinoma |
| title_full_unstemmed | Exploring methylation signatures for high de novo recurrence risk in hepatocellular carcinoma |
| title_short | Exploring methylation signatures for high de novo recurrence risk in hepatocellular carcinoma |
| title_sort | exploring methylation signatures for high de novo recurrence risk in hepatocellular carcinoma |
| topic | hepatocellular carcinoma dna methylation biomarker recurrence machine learning |
| url | http://e-cmh.org/upload/pdf/cmh-2024-0899.pdf |
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