4.5 Article

Identification of DNA methylation signatures for hepatocellular carcinoma detection and microvascular invasion prediction

期刊

出版社

BMC
DOI: 10.1186/s40001-022-00910-w

关键词

Hepatocellular carcinoma; Microvascular invasion; DNA methylation; Circulating free DNA

资金

  1. National Natural Science Foundation of China
  2. Natural Science Foundation for Distinguished Youths of Guangdong Province [2022B1515020060, 2019B151502009, R08030, Y12002]
  3. Guangdong Basic and Applied Basic Research Foundation [82173191]
  4. Kelin Outstanding Young Scientist of the First Affiliated Hospital, Sun Yat-sen University [81825013]
  5. [82172047]
  6. [82072029]

向作者/读者索取更多资源

In this study, we developed and established a preoperative predictive model for microvascular invasion (MVI) status in patients with hepatocellular carcinoma (HCC) based on DNA methylation markers. The model showed high accuracy and is important for surgical strategy determination in HCC patients.
Background and aim: Preoperative evaluation of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) is important for surgical strategy determination. We aimed to develop and establish a preoperative predictive model for MVI status based on DNA methylation markers. Methods: A total of 35 HCC tissues and the matched peritumoral normal liver tissues as well as 35 corresponding HCC patients' plasma samples and 24 healthy plasma samples were used for genome-wide methylation sequencing and subsequent methylation haplotype block (MHB) analysis. Predictive models were constructed based on selected MHB markers and 3-cross validation was used. Results; We grouped 35 HCC patients into 2 categories, including the MVI- group with 17 tissue and plasma samples, and MVI + group with 18 tissue and plasma samples. We identified a tissue DNA methylation signature with an AUC of 98.0% and a circulating free DNA (cfDNA) methylation signature with an AUC of 96.0% for HCC detection. Furthermore, we established a tissue DNA methylation signature for MVI status prediction, and achieved an AUC of 85.9%. Based on the MVI status predicted by the DNA methylation signature, the recurrence-free survival (RFS) and overall survival (OS) were significantly better in the predicted MVI- group than that in the predicted MVI + group. Conclusions: In this study, we identified a cfDNA methylation signature for HCC detection and a tissue DNA methylation signature for MVI status prediction with high accuracy.

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