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Impacts of heavy smoking on non-coding RNA expression for patients with esophageal carcinoma
BACKGROUND: Smoking is a well-recognized risk factor for esophageal carcinoma, but the underlying molecular mechanism remains unclear. Previous studies have demonstrated the predictive value of non-coding RNA (ncRNA) for the prognosis of esophageal carcinoma; however, the expression of smoking-relat...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10324184/ https://www.ncbi.nlm.nih.gov/pubmed/37407980 http://dx.doi.org/10.1186/s12920-023-01574-z |
Sumario: | BACKGROUND: Smoking is a well-recognized risk factor for esophageal carcinoma, but the underlying molecular mechanism remains unclear. Previous studies have demonstrated the predictive value of non-coding RNA (ncRNA) for the prognosis of esophageal carcinoma; however, the expression of smoking-related ncRNAs has not been systematically characterized. Herein, we comprehensively assessed the hazard of heavy smoking and its impact on ncRNA expression patterns in patients with esophageal carcinoma. METHODS: Transcriptome and clinical features of patients with esophageal carcinoma were acquired from The Cancer Genome Atlas (TCGA) database. Cox regression analysis was employed to calculate the hazard ratio (HR) of smoking behavior. Differential expression analysis was conducted with the “edgeR” package. The smoking-related RNA regulatory network was based on lncRNA‒miRNA and miRNA‒mRNA pairs and visualized by Cytoscape 3.7.1. We applied Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for functional annotation. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used for model construction. We applied Kaplan‒Meier analysis with a log-rank test for survival analysis, with group comparison by the Wilcoxon signed ranked test. RESULTS: Heavy smoking contributed to the poor overall survival of esophageal carcinoma, with an HR of 3.167 (95% CI: 1.077–9.312). A total of 195 lncRNAs and 73 miRNAs were differentially expressed between patients with or without smoking behavior. We constructed smoking-related RNA regulatory networks, and functional annotation enriched a series of cancer-related pathways. We generated a smoking-related prognostic risk score and found that patients with a high score had a poor prognosis. Fourteen out of 23 immune cell types differentially infiltrated into a distinct risk group, while no correlation was observed between the risk score and immune cells. CONCLUSION: Altogether, we profiled smoking-related ncRNA expression patterns and constructed an RNA regulatory network, providing a landscape of smoking-related molecular mechanisms of esophageal carcinoma. The smoking-related risk score, which was related to prognosis, revealed that tobacco smoking could suppress tumor immunity via the ncRNA mechanism. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01574-z. |
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