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DNA methylation loss coupled with mitotic cell division promotes immune evasion of tumours with high mutation load [RNA-seq]

ABSTRACT: Mitotic cell division increases tumour mutation burden and copy number load, predictive markers of the clinical benefit of immunotherapy. Cell division correlates also with genomic demethylation involving methylation loss in late-replicating partial methylation domains. Here we find that immunomodulatory pathway genes are concentrated in these domains and transcriptionally repressed in demethylated tumours with CpG island promoter hypermethylation. Global methylation loss correlated with immune evasion signatures independently of mutation burden and aneuploidy. Methylome data of our cohort (n = 60) and a published cohort (n = 81) in lung cancer and a melanoma cohort (n = 40) consistently demonstrated that genomic methylation alterations counteract the contribution of high mutation burden and increase immunotherapeutic resistance. Higher predictive power was observed for methylation loss than mutation burden. We also found that genomic hypomethylation correlates with the immune escape signatures of aneuploid tumours. Hence, DNA methylation alterations implicate epigenetic modulation in precision immunotherapy.

ORGANISM(S): Homo sapiens

PROVIDER: GSE135222 | GEO | 2019/08/02

REPOSITORIES: GEO

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Project description:Abstract: Immunotherapy has emerged as a crucial treatment approach for lung adenocarcinoma (LUAD), yet a notable percentage of patients do not exhibit the anticipated prognosis and therapeutic response. In this study, we embarked on a comprehensive analysis of immune infiltration-related genes in LUAD by integrating transcriptome sequencing data and TCGA dataset. And an immune risk prognosis model was developed, which accurately forecasts the prognosis and predicts the immunotherapy efficacy in LUAD. Patients with LUAD were categorized into high-risk and low-risk groups based on the model's risk value. The high-risk group exhibited a poorer prognosis, higher tumor mutation burden (TMB), greater genomic heterogeneity and lower immune scores. In contrast, the low-risk group manifested characteristics conducive to immunotherapy, including a more favorable prognosis, heightened sensitivity to immunotherapy and reduced likelihood of immune escape. The robustness of the model's predictive capability was corroborated using the GEO dataset, Nomogram and an independent immunotherapy cohort. Furthermore, the model risk value was found to be significantly associated with the prognosis of LUAD patients, genomic heterogeneity, immune cell infiltration, immune regulation and immunotherapy outcomes. Additionally, we characterized the significance of the model's feature factors using single-cell clustering and pseudo-temporal analysis, revealing that the model's feature genes are predominantly located in tumor-infiltrating T cells, particularly in the exhausted and effector subtypes. TNFRSF11A emerged as a key gene in the model, promoting LUAD cell proliferation, migration, and apoptosis, and involvement in LUAD M6A methylation and PD-L1-mediated immune escape. TNFRSF11A was mainly expressed in T cell clusters and represented a potential immune system regulatory factor associated with T cell exhaustion, fostering malignant progression in LUAD cells. Our study offers new mechanistic insights and therapeutic targets for the biological behaviors and immune suppression in LUAD.

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DNA methylation loss coupled with mitotic cell division promotes immune evasion of tumours with high mutation load [RNA-seq]

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