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5-methylcytosine RNA methylation regulators affect prognosis and tumor microenvironment in lung adenocarcinoma

BACKGROUND: Accumulating evidence has shown that 5-methylcytosinec (m5C) RNA methylation plays an essential role in tumorigenesis. However, the roles of m5C regulators in the prognosis, tumor microenvironment (TME), and immunotherapy responses of lung adenocarcinoma (LUAD) have not been fully analyz...

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Detalles Bibliográficos
Autores principales: Liu, Taisheng, Hu, Xiaoshan, Lin, Chunxuan, Shi, Xiaoshun, He, Yujing, Zhang, Jian, Cai, Kaican
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8987885/
https://www.ncbi.nlm.nih.gov/pubmed/35402591
http://dx.doi.org/10.21037/atm-22-500
Descripción
Sumario:BACKGROUND: Accumulating evidence has shown that 5-methylcytosinec (m5C) RNA methylation plays an essential role in tumorigenesis. However, the roles of m5C regulators in the prognosis, tumor microenvironment (TME), and immunotherapy responses of lung adenocarcinoma (LUAD) have not been fully analyzed. METHODS: Based on 14 m5C RNA regulators, we evaluated the m5C RNA modification patterns in patients with LUAD (n=594) in The Cancer Genome Atlas (TCGA). Unsupervised clustering analysis was performed to confirm distinct m5C modification patterns. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to investigate the biological functions of differentially expressed genes (DEGs) among different m5C RNA modification patterns. An m5C signature (m5Csig) was constructed using least absolute shrinkage and selection operator (LASSO) algorithms. The GSE72094 cohort (n=442) from the Gene Expression Omnibus (GEO) was used to validate m5Csig. A receiver operating characteristic (ROC) model was constructed to evaluate the sensitivity and specificity of m5Csig. Tumor-infiltrating immune cells (TIICs) between the high- and low-risk groups were estimated using the Cell Type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm. RESULTS: We identified 3 m5C RNA modification clusters. Overall survival (OS) differed among the 3 clusters. The m5Csig, including TRDMT1, NSUN1, NSUN4, NSUN7, and ALYREF, was constructed to classify patients with LUAD into high- and low-risk groups. The high-risk group, with more immune cell infiltration, had a significantly poorer OS than that the low-risk group, which was associated with better response to immune checkpoint blockade therapy. CONCLUSIONS: The present study revealed that m5C RNA regulators play a significant role in TME regulation in LUAD. The m5Csig can predict the prognosis of patients with LUAD and might provide novel strategies for tumor immunotherapy.