Research Paper Volume 16, Issue 21 pp 13323—13339
A differentially-methylated-region signature predicts the recurrence risk for patients with early stage lung adenocarcinoma
- 1 Yunnan Cancer Hospital and The Third Affiliated Hospital of Kunming Medical University and Yunnan Cancer Center, Kunming, P.R. China
- 2 Chongqing University Fuling Hospital, Chongqing, P.R. China
- 3 Burning Rock Biotech, Guangzhou, P.R. China
- 4 Institute of Basic Medicine and Cancer, Chinese Academy of Sciences, Hangzhou, P.R. China
- 5 The Cancer Hospital of the University of Chinese Academy of Sciences, Hangzhou, P.R. China
- 6 Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, P.R. China
- 7 The First Affiliated Hospital of Southern University of Science and Technology (Shenzhen People’s Hospital), Shenzhen, P.R. China
Received: October 10, 2023 Accepted: September 2, 2024 Published: November 18, 2024
https://doi.org/10.18632/aging.206139How to Cite
Copyright: © 2024 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Predicting prognosis in lung cancer patients is important in establishing future treatment and monitoring plans. Lung adenocarcinoma (LUAD) is the most common and aggressive type of lung cancer with dismal prognosis and prognostic stratification would help to guide treatment. Aberrant DNA methylation in tumors occurs earlier than clinical variations, and keeps accumulating as cancer progresses. Preliminary studies have given us some clues that DNA methylation might serve as a promising biomarker for prognosis prediction. Herein, we aimed to study the potential utility of DNA methylation pattern in predicting the recurrence risk of early stage resectable LUAD and to develop a risk-modeling signature based on differentially methylated regions (DMRs). This study consisted of three cohorts of 244 patients with stage I–IIIA LUAD, including marker discovery cohort (n = 39), prognostic model training cohort (n = 117) and validation cohort (n = 80). 468 DMRs between LUAD tumor and adjacent tissues were screened out in the marker discovery cohort (adjusted P < 0.05), and a prognostic signature was developed based on 15 DMRs significantly related to disease-free survival in early stage LUAD patients. The DMR signature showed commendable performance in predicting the recurrence risk of LUAD patients both in model training cohort (P < 0.001; HR = 4.32, 95% CI = 2.39–7.80) and model validation cohort (P = 0.009; HR = 9.08, 95% CI = 1.20–68.80), which might be of great utility both for understanding the molecular basis of LUAD relapse, providing risk stratification of patients, and establishing future monitoring plans.