Research Paper Volume 14, Issue 19 pp 7824—7850
DNA methylation regulator-mediated modification patterns and tumor microenvironment characterization in glioma
- 1 Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, China
- 2 Jiangxi Key Laboratory of Neurological Tumors and Cerebrovascular Diseases, Nanchang, Jiangxi Province, China
- 3 East China Institute of Digital Medical Engineering, Shangrao, Jiangxi Province, China
- 4 Institute of Neuroscience, Nanchang University, Nanchang, Jiangxi Province, China
- 5 Department of Obstetrics and Gynecology, Suizhou Central Hospital, Hubei University of Medicine, Suizhou, Hubei Province, China
Received: June 16, 2022 Accepted: August 29, 2022 Published: September 21, 2022
https://doi.org/10.18632/aging.204291How to Cite
Copyright: © 2022 Luo 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.
Abstract
Growing evidences indicate DNA methylation plays a crucial regulatory role in inflammation, innate immunity, and immunotherapy. However, the overall landscape of various DNA methylation regulatory genes and their relationship with the infiltration of immune cells into the tumor microenvironment (TME) as well as the response to immunotherapy in gliomas is still not clear. Therefore, we comprehensively analyzed the correlation between DNA methylation regulator patterns, infiltration of immune cell-types, and tumor immune response status in gather glioma cohorts. Furthermore, we calculated the DNA methylation score (DMS) for individual glioma samples, then evaluated the relationship between DMS, clinicopathological characteristics, and overall survival (OS) in patients with gliomas. Our results showed three distinct DNA methylation regulator patterns among the glioma patients which correlated with three distinct tumor immune response phenotypes, namely, immune-inflamed, immune-excluded, and immune desert. We then calculated DMS for individual glioma samples based on the expression of DNA methylation-related gene clusters. Furthermore, DMS, tumor mutation burden (TMB), programmed death 1 (PD-1) expression, immune cell infiltration status in the TME, and Tumor Immune Dysfunction and Exclusion (TIDE) scores were associated with survival outcomes and clinical responses to immune checkpoint blockade therapy. We also validated the predictive value of DMS in two independent immunotherapy cohorts. In conclusion, our results demonstrated that three DNA methylation regulator patterns that correlated with three tumor immune response phenotypes. Moreover, we demonstrated that DMS was an independent predictive biomarker that correlated with survival outcomes of glioma patients and their responses to immunotherapy therapeutic regimens.