ArticleInternational journal of general medicine2022
Comprehensive Analysis and Prognosis Prediction of N6-Methyladenosine-Related lncRNAs in Immune Microenvironment Infiltration of Gastric Cancer.
Article in International journal of general medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 9 citations in OpenAlex.
- Gene Variations in RNA Modification Pathway Linked to Poor Survival After Gastric Cancer Surgery.Genes · 2026Article
- The regulatory mechanism of m6A modification in gastric cancer.Discover oncology · 2024Review
- Article
- Cuproptosis-related lncRNAs predict the prognosis and immune response in hepatocellular carcinoma.Clinical and experimental medicine · 2023Article
- Article
- N6-methylandenosine-related immune genes correlate with prognosis and immune landscapes in gastric cancer.Frontiers in oncology · 2022Article
- SLC25A25-AS1 over-expression could be predicted the dismal prognosis and was related to the immune microenvironment in prostate cancer.Frontiers in oncology · 2022Article
- Machine learning-based identification of a novel prognosis-related long noncoding RNA signature for gastric cancer.Frontiers in cell and developmental biology · 2022Article
- Expression profiles of m6A RNA methylation regulators, PD-L1 and immune infiltrates in gastric cancer.Frontiers in oncology · 2022Article
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5 authors at 1 institution in 1 country.
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Abstract
Purpose: N6-methyladenosine (m6A) RNA modification plays an important role in regulating tumor microenvironment (TME) infiltration. However, the relationship between the expression pattern of m6A-related long non-coding RNAs (lncRNAs) and the immune microenvironment of gastric cancer (GC) is unclear. Methods: In this study, 23 m6A-related lncRNAs were identified by Pearson's correlation analysis and univariate Cox regression analysis. According to the expression of these lncRNAs, we identified two distinct molecular clusters by consensus clustering and compared the differences of the TME and enriched pathways between the two clusters. We further constructed a prognostic risk signature and verified it using The Cancer Genome Atlas training and testing cohorts. Results: The results showed that cluster 1 was associated with tumor-related and immune activation-related pathways. In addition, cluster 1 was also associated with higher ImmuneScore, StromalScore, and ESTIMATEScore. The results of the stratified survival analysis and independent prognosis analysis indicated that the risk signature is an independent prognostic indicator for patients with GC. In addition, it can effectively predict survival status in patients with different clinical characteristics. Furthermore, we found that the risk signature was associated with a variety of tumor-infiltrating immune cells, and that low risk scores were significantly correlated with high expression of programmed death-1 (PD-1) and cytotoxic T-lymphocyte associated protein 4 (CTLA4), as well as sensitivity to chemotherapeutic drugs (eg, fluorouracil and oxaliplatin). Conclusion: This evidence contributes to our understanding of the regulation of TME infiltration by m6A-related lncRNAs and may lead to more effective immunotherapy and chemotherapy for patients with GC.
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