Dataset Information

A systematic dissection of the epigenomic heterogeneity of lung adenocarcinoma reveals two different subclasses with distinct prognosis and core regulatory networks [tumor]

ABSTRACT: Lung adenocarcinoma (LUAD) is a high malignant tumor mostly occurs in adult patients, which is also a highly heterogeneous disease that involved multi different alterations. Some alterations such like EGFR mutations are frequently observed in LUAD patients, but the mechanisms that drive LUAD tumorigenesis and progression remain largely unclear, which need further researches. For example, epigenetic processes play important roles in cancers, but the variations in the enhancer and super enhancer landscapes of LUAD patients have rarely been studied. Here, to provide an in-depth understanding of the epigenomic heterogeneity of LUAD, we investigate the H3K27ac histone modification profiles of the tumor and adjacent normal lung tissues from 42 LUAD patients and explore the role of epigenetic alterations in LUAD progression.

ORGANISM(S): Homo sapiens

PROVIDER: GSE150976 | GEO | 2020/05/22

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

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.

Dataset Information

A systematic dissection of the epigenomic heterogeneity of lung adenocarcinoma reveals two different subclasses with distinct prognosis and core regulatory networks [tumor]

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets