ArticleBMC cancer2021
Characteristic of molecular subtypes in lung adenocarcinoma based on m6A RNA methylation modification and immune microenvironment.
Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- A novel disulfidptosis-related prognostic gene signature and experimental validation identifyCancer biomarkers : section A of Disease markers · 2025Article
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- Identification of molecular subgroups and establishment of risk model based on the response to oxidative stress to predict overall survival of patients with lung adenocarcinoma.European journal of medical research · 2023Article
- The critical roles of m6A RNA methylation in lung cancer: from mechanism to prognosis and therapy.British journal of cancer · 2023Review
- Article
- Aberrant Expression and Prognostic Potential of IL-37 in Human Lung Adenocarcinoma.Biomedicines · 2022Article
- ERBB3 methylation and immune infiltration in tumor microenvironment of cervical cancer.Scientific reports · 2022Article
- Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures.Frontiers in oncology · 2022Article
- Integrative Analysis of m6A RNA Methylation Regulators and the Tumor Immune Microenvironment in Non-Small-Cell Lung Cancer.Disease markers · 2022Article
- Comprehensive Analysis Revealed the Potential Implications of m6A Regulators in Lung Adenocarcinoma.Frontiers in molecular biosciences · 2022Article
- Characterization of Necroptosis-Related Molecular Subtypes and Therapeutic Response in Lung Adenocarcinoma.Frontiers in genetics · 2022Article
- The regulation and potential roles of m6A modifications in early embryonic development and immune tolerance at the maternal-fetal interface.Frontiers in immunology · 2022Review
- N6-Methyladenosine RNA Modification in the Tumor Immune Microenvironment: Novel Implications for Immunotherapy.Frontiers in immunology · 2021Review
- Prognosis and Immunotherapy Response With a Novel Golgi Apparatus Signature-Based Formula in Lung Adenocarcinoma.Frontiers in cell and developmental biology · 2021Article
- Genomics and Prognosis Analysis of NFrontiers in genetics · 2021Article
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Authors and funding
8 authors.
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Abstract
backgroundLung adenocarcinoma (LUAD) is a major subtype of lung cancer and closely associated with poor prognosis. N6-methyladenosine (m6A), one of the most predominant modifications in mRNAs, is found to participate in tumorigenesis. However, the potential function of m6A RNA methylation in the tumor immune microenvironment is still murky.
methodsThe gene expression profile cohort and its corresponding clinical data of LUAD patients were downloaded from TCGA database and GEO database. Based on the expression of 21 m6A regulators, we identified two distinct subgroups by consensus clustering. The single-sample gene-set enrichment analysis (ssGSEA) algorithm was conducted to quantify the relative abundance of the fraction of 28 immune cell types. The prognostic model was constructed by Lasso Cox regression. Survival analysis and receiver operating characteristic (ROC) curves were used to evaluate the prognostic model.
resultConsensus classification separated the patients into two clusters (clusters 1 and 2). Those patients in cluster 1 showed a better prognosis and were related to higher immune scores and more immune cell infiltration. Subsequently, 457 differentially expressed genes (DEGs) between the two clusters were identified, and then a seven-gene prognostic model was constricted. The survival analysis showed poor prognosis in patients with high-risk score. The ROC curve confirmed the predictive accuracy of this prognostic risk signature. Besides, further analysis indicated that there were significant differences between the high-risk and low-risk groups in stages, status, clustering subtypes, and immunoscore. Low-risk group was related to higher immune score, more immune cell infiltration, and lower clinical stages. Moreover, multivariate analysis revealed that this prognostic model might be a powerful prognostic predictor for LUAD. Ultimately, the efficacy of this prognostic model was successfully validated in several external cohorts (GSE30219, GSE50081 and GSE72094).
conclusionOur study provides a robust signature for predicting patients' prognosis, which might be helpful for therapeutic strategies discovery of LUAD.
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