Research Paper Volume 16, Issue 10 pp 8998—9022
Breast cancer clinical outcomes and tumor immune microenvironment: cross-dialogue of multiple epigenetic modification profiles
- 1 Department of Oncology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
- 2 Oncology, Harbin Medical University, Harbin, Heilongjiang, China
- 3 School of Nursing, Harbin Medical University, Harbin, Heilongjiang, China
Received: July 27, 2023 Accepted: February 29, 2024 Published: May 22, 2024
https://doi.org/10.18632/aging.205853How to Cite
Copyright: © 2024 Teng 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
The discovery of RNA methylation alterations associated with cancer holds promise for their utilization as potential biomarkers in cancer diagnosis, prognosis, and prediction. RNA methylation has been found to impact the immunological microenvironment of tumors, but the specific role of methylation-related genes (MRGs), particularly in breast cancer (BC), the most common cancer among women globally, within the tumor microenvironment remains unknown. In this study, we obtained data from TCGA and GEO databases to investigate the expression patterns of MRGs in both genomic and transcriptional domains in BC. By analyzing the data, we identified two distinct genetic groupings that were correlated with clinicopathological characteristics, prognosis, degree of TME cell infiltration, and other abnormalities in MRGs among patients. Subsequently, an MRG model was developed to predict overall survival (OS) and its accuracy was evaluated in BC patients. Additionally, a highly precise nomogram was created to enhance the practical usability of the MRG model. In low-risk groups, we observed lower TBM values and higher TIDE scores. We further explored how MRGs influence a patient’s prognosis, clinically significant characteristics, response to therapy, and the TME. These risk signatures have the potential to improve treatment strategies for BC patients and could be applied in future clinical settings. Moreover, they may also be utilized to determine prognosis and biological features in these patients.