Exploration and establishment of the prediction model for lung adenocarcinoma prognosis based on DNA methylation sites

LU Jing-ya; FANG Zi-han; ZENG Chang-yi; CHEN Xue-jiao; WANG Ke; WEI Sheng

doi:10.16462/j.cnki.zhjbkz.2022.08.017

Volume 26 Issue 8

Aug. 2022

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LU Jing-ya, FANG Zi-han, ZENG Chang-yi, CHEN Xue-jiao, WANG Ke, WEI Sheng. Exploration and establishment of the prediction model for lung adenocarcinoma prognosis based on DNA methylation sites[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2022, 26(8): 974-981. doi: 10.16462/j.cnki.zhjbkz.2022.08.017

Citation:

LU Jing-ya, FANG Zi-han, ZENG Chang-yi, CHEN Xue-jiao, WANG Ke, WEI Sheng. Exploration and establishment of the prediction model for lung adenocarcinoma prognosis based on DNA methylation sites[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2022, 26(8): 974-981. doi: 10.16462/j.cnki.zhjbkz.2022.08.017

Citation:

LU Jing-ya, FANG Zi-han, ZENG Chang-yi, CHEN Xue-jiao, WANG Ke, WEI Sheng. Exploration and establishment of the prediction model for lung adenocarcinoma prognosis based on DNA methylation sites[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2022, 26(8): 974-981. doi: 10.16462/j.cnki.zhjbkz.2022.08.017

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Exploration and establishment of the prediction model for lung adenocarcinoma prognosis based on DNA methylation sites

doi: 10.16462/j.cnki.zhjbkz.2022.08.017

1.
Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College of Huazhong University of Science & Technology, Wuhan 430030, China
2.
School of Basic Medicine, Hubei University of Arts and Science, Xiangyang 441053, China

Funds:

National Natural Science Foundation of China 81773520

National Natural Science Foundation of China 82073661

Innovation Training Program for College Students S2020105109031

The Research Foundation for Teacher Cultivation of Hubei University of Arts and Science 2020kypyfy030

More Information

Corresponding author: WANG Ke, E-mail: mqlhome76@163.com; WEI Sheng, E-mail: shengwei@hust.edu.cn
Received Date: 2021-09-08
Rev Recd Date: 2022-01-17

Available Online: 2022-08-23

Publish Date: 2022-08-10

Abstract

Abstract

Objective To explore and build a prediction model for the prognosis of lung adenocarcinoma based on DNA methylation sites according to the public omics database and evaluate the prediction efficacy of the prediction model. Methods The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used for analysis and validation. The least Absolute Shrinkage and Selection Operator (LASSO) Cox regression model was performed to screen DNA methylation sites associated with the prognosis of lung adenocarcinoma. Multivariate Cox regression was used to evaluate the relationship between methylation signature and prognosis of lung adenocarcinoma. The prognostic prediction model of lung adenocarcinoma was estimated using Harrell's C statistics. Results Two methylation sites (cg02909790 and cg19378330) associated with the prognosis of lung adenocarcinoma were selected by LASSO Cox regression. Cox regression analysis showed a significant relationship between methylation signature and lung adenocarcinoma prognosis (HR=8.32, 95% CI: 2.41-28.69, P < 0.001). The C statistical value of the prognostic prediction model based on methylation signature for lung adenocarcinoma was 0.81 (95% CI: 0.78-0.83) according to Harrell's C statistical analysis. Conclusions The prediction model of lung adenocarcinoma based on cg02909790 and cg19378330 has a good prognostic prediction efficacy and may be potential personalized tumor molecular markers in the development and progression of lung adenocarcinoma.
- Public omics database,
- Methylation signature,
- Lung adenocarcinoma,
- Prediction model,
- LASSO Cox model

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References(19)

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