Future Science Group
Supplemental_Table_S4.xlsx (15.18 kB)
Download file

Supplementary Table 4: Investigating and modeling the differential DNA methylation for early lung adenocarcinoma diagnosis

Download (15.18 kB)
posted on 2022-08-11, 08:36 authored by Figshare Future Science GroupFigshare Future Science Group, Xiaohua Shi, Ting Feng, Yang Xu, Xue Wu, Yang ShaoYang Shao, Zhiyong LiangZhiyong Liang

Background: Aberrant DNA methylations serve as rich sources of diagnostic biomarkers, but a further improvement in their accuracy and clinical utility is warranted. Methods: Large panel bisulfite sequencing were performed on paired normal and stage I/IV tumors from 226 lung adenocarcinoma cancer patients to characterize the differentially methylated regions (DMRs). Results: Random forest model achieved high prediction accuracy (sensitivity 96% and specificity 97.56%) to separate normal controls from both early and advanced cancer samples, which is superior to most previous prediction models tested in lung adenocarcinoma. Conclusion: Our results suggest that combining the random forest model with targeted bisulfite sequencing have great clinical potentials to accurately predict and early diagnose lung adenocarcinoma during cancer screening.