Research Paper Volume 12, Issue 24 pp 25275—25293
DNA methylation-based lung adenocarcinoma subtypes can predict prognosis, recurrence, and immunotherapeutic implications
- 1 Department of Respiratory Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
- 2 State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
- 3 Department of Pulmonology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- 4 Department of Endocrinology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
- 5 Department of Rheumatology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
Received: May 7, 2020 Accepted: September 19, 2020 Published: November 21, 2020https://doi.org/10.18632/aging.104129
How to Cite
Copyright: © 2020 Xu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The marked heterogeneity of lung adenocarcinoma (LUAD) makes its diagnosis and treatment difficult. In addition, the aberrant DNA methylation profile contributes to tumor heterogeneity and alters the immune response. We used DNA methylation array data from publicly available databases to establish a predictive model for LUAD prognosis. Thirty-three methylation sites were identified as specific prognostic biomarkers, independent of patients’ clinical characteristics. These methylation profiles were used to identify potential drug candidates and study the immune microenvironment of LUAD and response to immunotherapy. When compared with the high-risk group, the low-risk group had a lower recurrence rate and favorable prognosis. The tumor microenvironment differed between the two groups as reflected by the higher number of resting dendritic cells and a lower number of monocytes and resting mast cells in the low-risk group. Moreover, low-risk patients reported higher immune and stromal scores, lower tumor purity, and higher expression of HLA genes. Low-risk patients responded well to immunotherapy due to higher expression of immune checkpoint molecules and lower stemness index. Thus, our model predicted a favorable prognosis and increased overall survival for patients in the low-risk methylation group. Further, this model could provide potential drug targets to develop effective immunotherapies for LUAD.