Translational cancer research · 2026
Comprehensive bioinformatics analysis identifies DNA methylation signatures associated with immune evasion and predicts immunotherapy response in breast cancer.
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Cheng Yurong, Wang Jing, Yan Dong
Аннотация
BACKGROUND: Breast cancer exhibits substantial immunological heterogeneity, and immune evasion is a key mechanism driving tumor progression and therapeutic resistance. However, robust epigenetic biomarkers reflecting immune escape at the genome-wide level remain lacking, limiting precise prognostic evaluation and immunotherapy stratification. Therefore, this study aimed to identify DNA methylation features associated with immune evasion and to develop a methylation-based score for prognostic assessment and immunotherapy response prediction in breast cancer.
METHODS: Genome-wide DNA methylation and transcriptomic data from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) cohort were analyzed to identify immune-evasion-related cytosine-phosphate-guanine (CpG) sites. A subset of functionally relevant CpGs was selected through differential methylation and correlation analyses, and an immune-evasion methylation score (IME-score) was constructed using principal component analysis (PCA). Immune infiltration, tumor microenvironment characteristics, pathway activity, and predicted immunotherapy response were systematically evaluated using Cell-Type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT), Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data (ESTIMATE), Gene Set Variation Analysis (GSVA), and Tumor Immune Dysfunction and Exclusion (TIDE), respectively. External validation was performed in an independent cohort.
RESULTS: The IME-score demonstrated high stability and reproducibility, and effectively stratified patient survival. Significant differences were observed between IME-score groups in immune cell infiltration patterns, tumor microenvironment scores, pathway enrichment profiles, and immune checkpoint expression. Notably, higher IME-scores were associated with increased TIDE scores and lower responder scores, indicating reduced predicted responsiveness to immunotherapy. These findings were consistently validated in independent datasets.
CONCLUSIONS: The IME-score represents a robust epigenetic indicator of immune evasion in breast cancer. It provides complementary value to existing biomarkers and may facilitate improved prognostic assessment and immunotherapy stratification.
METHODS: Genome-wide DNA methylation and transcriptomic data from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) cohort were analyzed to identify immune-evasion-related cytosine-phosphate-guanine (CpG) sites. A subset of functionally relevant CpGs was selected through differential methylation and correlation analyses, and an immune-evasion methylation score (IME-score) was constructed using principal component analysis (PCA). Immune infiltration, tumor microenvironment characteristics, pathway activity, and predicted immunotherapy response were systematically evaluated using Cell-Type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT), Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data (ESTIMATE), Gene Set Variation Analysis (GSVA), and Tumor Immune Dysfunction and Exclusion (TIDE), respectively. External validation was performed in an independent cohort.
RESULTS: The IME-score demonstrated high stability and reproducibility, and effectively stratified patient survival. Significant differences were observed between IME-score groups in immune cell infiltration patterns, tumor microenvironment scores, pathway enrichment profiles, and immune checkpoint expression. Notably, higher IME-scores were associated with increased TIDE scores and lower responder scores, indicating reduced predicted responsiveness to immunotherapy. These findings were consistently validated in independent datasets.
CONCLUSIONS: The IME-score represents a robust epigenetic indicator of immune evasion in breast cancer. It provides complementary value to existing biomarkers and may facilitate improved prognostic assessment and immunotherapy stratification.