Mining the Prognostic Role of DNA Methylation Heterogeneity in Lung Adenocarcinoma

Author:

Liao Hongying1ORCID,Luo Xiaolong2ORCID,Huang Yisheng3ORCID,Yang Xingping1ORCID,Zheng Yuzhen1ORCID,Qin Xianyu1ORCID,Tan Jian1ORCID,Shen Piao4ORCID,Tian Renjiang4ORCID,Cai Weijie1ORCID,Shi Xiaoshun5ORCID,Deng Xiaofang6ORCID

Affiliation:

1. Department of Thoracic Surgery, Thoracic Cancer Center, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China

2. Department of Thoracic Surgery, Zhanjiang Central People’s Hospital, Chikan District, Zhanjiang City, Guangdong Province, China

3. Department of Oncology, Maoming People’s Hospital, Maoming, China

4. Department of Thoracic Surgery, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China

5. Department of Thoracic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China

6. Department of Internal Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou Key Laboratory of Translational Medicine on Malignant Tumor Treatment, Guangzhou, China

Abstract

Purpose. DNA methylation heterogeneity is a type of tumor heterogeneity in the tumor microenvironment, but studies on the identification of the molecular heterogeneity of the lung adenocarcinoma genome with respect to DNA methylation sites and their roles in lung cancer progression and prognosis are scarce. Methods. Prognosis-associated DNA methylation subtypes were filtered by the Cox proportional hazards model and then established by unsupervised cluster analysis. Association analysis of these subtypes with clinical features and functional analysis of annotated genes potentially affected by methylation sites were performed. The robustness of the model was further tested by a Bayesian network classifier. Results. Over 7 thousand methylation sites were associated with lung adenocarcinoma prognosis. We identified seven molecular methylation subtypes, including 630 methylation sites. The subtypes yielded the most stable results for differentiating methylation profiles, prognosis, and gene expression patterns. The annotated genes potentially affected by these methylation sites are enriched in biological processes such as morphogenesis and cell adhesion, but their individual impact on the tumor microenvironment and prognosis is multifaceted. Discussion. We revealed that DNA methylation heterogeneity could be clustered and associated with the clinical features and prognosis of lung adenocarcinoma, which could lead to the development of a novel molecular tool for clinical evaluation.

Funder

China Postdoctoral Science Foundation

Publisher

Hindawi Limited

Subject

Biochemistry (medical),Clinical Biochemistry,Genetics,Molecular Biology,General Medicine

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