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A multi-cancer risk prediction model which constructed based on H4C6 methylation level and cfDNA concentration / 安徽医科大学学报
Article in Zh | WPRIM | ID: wpr-1038567
Responsible library: WPRO
ABSTRACT
Objective@#To explore the difference in H4 clustered histone 6(H4C6) methylation level and circulating cell-free DNA (cfDNA) concentration between 94 normal group and 122 tumor groups (65 patients with lung cancer,22 patients with gastric cancer,23 patients with colorectal cancer,and 12 patients with liver cancer) ,and the age of total 216 subjects were between 18 and 85 years old.To construct a cancer risk prediction model based on H4C6 methylation level and cfDNA concentration and evaluate the predictive performance of the model.@*Methods@#cfDNA was extracted from blood samples using magnetic beads.Qubit 4. 0 fluorescence quantitative meter was used to detect the concentration of cfDNA. Real-time quantitative PCR( RT-qPCR) technology was used to detect the methylation level of H4C6 in cfDNALogistic regression algorithm was used to construct a cancer risk prediction model of H4C6 methylation level combined with cfDNA concentration.The accuracy of the model was assessed using receiver operating characteristic (ROC) curve and calibration curve.The clinical benefit of the model was as- sessed using decision curve analysis (DCA) . @*Results@#The model was constructed by combining H4C6 methylation level and cfDNA concentration to distinguish lung cancerliver cancercolorectal cancergastric cancer,pancancer from healthy control group had the area under curve (AUC) of 0. 769,0. 988,0. 934,0. 922,0. 830,respectively.The mean absolute error of the calibration curve was less than 0. 05 ; the net benefit of the DCA curve was greater than 0.@*Conclusion@#The cancer risk prediction model based on H4C6 methylation level and cfDNA concentration has good predictive performance,which helps to provide reasonable and effective suggestions for preclinical decision-making,and ultimately may provide patients with targeted and personalized cancer detection and diagnosis program.
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Full text: 1 Index: WPRIM Language: Zh Journal: Acta Universitatis Medicinalis Anhui Year: 2023 Type: Article
Full text: 1 Index: WPRIM Language: Zh Journal: Acta Universitatis Medicinalis Anhui Year: 2023 Type: Article