Ontology highlight
ABSTRACT: Background
The high lethal rate of pancreatic cancer is partly due to a lack of efficient biomarkers for screening and early diagnosis. We attempted to develop effective and noninvasive methods using 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) markers from circulating cell-free DNA (cfDNA) for the detection of pancreatic ductal adenocarcinoma (PDAC).Results
A 24-feature 5mC model that can accurately discriminate PDAC from healthy controls (area under the curve (AUC) = 0.977, sensitivity = 0.824, specificity = 1) and a 5hmC prediction model with 27 features demonstrated excellent detection power in two distinct validation sets (AUC = 0.992 and 0.960, sensitivity = 0.786 and 0.857, specificity = 1 and 0.993). The 51-feature model combining 5mC and 5hmC markers outperformed both of the individual models, with an AUC of 0.997 (sensitivity = 0.938, specificity = 0.955) and particularly an improvement in the prediction sensitivity of PDAC. In addition, the weighted diagnosis score (wd-score) calculated with the 5hmC model can distinguish stage I patients from stage II-IV patients.Conclusions
Both 5mC and 5hmC biomarkers in cfDNA are effective in PDAC detection, and the 5mC-5hmC integrated model significantly improve the detection sensitivity.
SUBMITTER: Cao F
PROVIDER: S-EPMC7376965 | biostudies-literature | 2020 Jul
REPOSITORIES: biostudies-literature
Cao Feng F Wei Ailin A Hu Xinlei X He Yijing Y Zhang Jun J Xia Lin L Tu Kailing K Yuan Jue J Guo Ziheng Z Liu Hongying H Xie Dan D Li Ang A
Clinical epigenetics 20200723 1
<h4>Background</h4>The high lethal rate of pancreatic cancer is partly due to a lack of efficient biomarkers for screening and early diagnosis. We attempted to develop effective and noninvasive methods using 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) markers from circulating cell-free DNA (cfDNA) for the detection of pancreatic ductal adenocarcinoma (PDAC).<h4>Results</h4>A 24-feature 5mC model that can accurately discriminate PDAC from healthy controls (area under the curve (AUC) ...[more]