A multi-cancer risk prediction model which constructed based on H4C6 methylation level and cfDNA concentration
10.19405/j.cnki.issn1000-1492.2023.04.013
- Author:
Yulian Hu
1
,
2
;
Jian Qi
1
,
3
;
Shujie Wang
3
,
4
;
Bo Hong
3
,
4
;
Xiaojun Sun
3
,
4
;
Hongzhi Wang
3
,
4
;
Jinfu Nie
3
,
4
,
5
Author Information
1. College of Life Sciences，University of Science and Technology of China，Hefei 230026
2. Guangzhou Institutes of Biomedicine and Health，Chinese Academy of Sciences，Guangzhou 510535
3. Anhui Province Key Laboratory of Medical Physics and Technology，Center of Medical Physics and Technology，Hefei Institutes of Physical Science，Chinese Academy of Sciences，Hefei 230031
4. Dept of Clinical Laboratory，Hefei Cancer Hospital，Chinese Academy of Sciences，Hefei 230031
5. Guangzhou Institutes of Biomedicine and HealthChinese Academy of Sciences，Guangzhou 510535
- Publication Type:Journal Article
- Keywords:
H4C6 methylation level;
cfDNA concentration;
cancer risk prediction
- From:
Acta Universitatis Medicinalis Anhui
2023;58(4):587-603
- CountryChina
- Language:Chinese
-
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 cfDNA．Logistic 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 cancer，liver cancer，colorectal cancer，gastric 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.
- Full text:2024071711150748834基于H4C6甲基化水平和c...构建多癌种癌症风险预测模型_胡玉莲.pdf
