{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Hao Y"],"funding":["Basic and Applied Basic Research Foundation of Guangdong Province","National Natural Science Foundation of China","The Kelin Outstanding Young Scientist of the First Affiliated Hospital, Sun Yat-sen University","Natural Science Foundation for Distinguished Youths of Guangdong Province"],"pagination":["276"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9720918"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["27(1)"],"pubmed_abstract":["<h4>Background and aim</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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."],"journal":["European journal of medical research"],"pubmed_title":["Identification of DNA methylation signatures for hepatocellular carcinoma detection and microvascular invasion prediction."],"pmcid":["PMC9720918"],"funding_grant_id":["2019B151502009","Y12002","82173191","82172047","2022B1515020060","R08030","81825013"],"pubmed_authors":["Xu L","Chen Z","Hu H","Peng S","Weng Z","Kuang M","Hao Y","Yang Q","Su Z","He Q","Chen S"],"additional_accession":[]},"is_claimable":false,"name":"Identification of DNA methylation signatures for hepatocellular carcinoma detection and microvascular invasion prediction.","description":"<h4>Background and aim</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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.","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Dec","modification":"2024-11-13T14:46:33.276Z","creation":"2024-11-13T14:46:33.276Z"},"accession":"S-EPMC9720918","cross_references":{"pubmed":["36464701"],"doi":["10.1186/s40001-022-00910-w"]}}