ArticleAnnals of translational medicine2021
Correlation of m6A methylation with immune infiltrates and poor prognosis in non-small cell lung cancer via a comprehensive analysis of RNA expression profiles.
Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- Emerging Concepts in Immuno-Oncology: Insights from Natural Language Processing-Driven Co-Occurrence Analysis.ACS omega · 2025Review
- M6A RNA modification: focusing on non-small cell lung cancer progression, therapeutic strategies and challenges.Frontiers in oncology · 2025Review
- The critical roles of m6A RNA methylation in lung cancer: from mechanism to prognosis and therapy.British journal of cancer · 2023Review
- ORC6, a novel prognostic biomarker, correlates with T regulatory cell infiltration in prostate adenocarcinoma: a pan-cancer analysis.BMC cancer · 2023Article
- A novel algorithm for lung adenocarcinoma based on N6 methyladenosine-related immune long noncoding RNAs as a reliable biomarker for predicting survival outcomes and selecting sensitive anti-tumor therapies.Journal of clinical laboratory analysis · 2022Article
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Authors and funding
10 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundNon-small cell lung cancer (NSCLC) is a common type of lung cancer with a poor prognosis. N6-methyladenosine (m6A) methylation, which is a reversible ribonucleic acid (RNA) modification, plays an important role in the occurrence and development of NSCLC. However, the potential effect of m6A methylation on immune infiltrates and prognosis remains unclear.
methodsIn this study, a weighted gene co-expression network analysis was used to screen out messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs) that were co-expressed with m6A regulators. Additionally, 2 molecular subtypes (Clusters 1 and 2) were determined via consensus clustering. Subsequently, a prognostic risk model was constructed using both co-expressed mRNAs and ncRNAs. Based on the risk scores calculated by the prognostic model, the patients were divided into the high-risk group or low-risk group. Finally, the altered patterns of the tumor immune microenvironments (TIMEs) between the 2 stratification methods were thoroughly investigated, and a gene set enrichment analysis was conducted to further examine the potential mechanism.
resultsPatients in Cluster 1 had lower immunoscores, higher programmed death-ligand 1 (PD-L1) expression, and shorter overall survival (OS) compared to patients in Cluster 2. A further investigation based on the prognostic model revealed that the PD-L1 expression levels of patients in the high-risk group were significantly upregulated, and the immunoscores were lower than those in the low-risk group. The immune cells with a high infiltration in Cluster 1 showed a significant positive correlation with the risk score; those with low infiltration showed a significant negative correlation. The hallmarks of the Myelocytomatosis viral oncogene (MYC) targets, the second Gap/Mitosis (G2/M) checkpoint, E2 transcription Factor (E2F) targets, glycolysis, deoxyribonucleic acid (DNA) repair, and unfolded protein response were significantly enriched in Cluster 1, the low-immunoscore group, and the high-risk group.
conclusionsThis study revealed that m6A methylation is closely related to the poor prognosis of NSCLC patients via interference with the TIME, which suggests that m6A may play a role in optimizing individualized immunotherapy management and improving prognosis.
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