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Smoking-related epigenetic modifications are associated with the prognosis and chemotherapeutics of patients with bladder cancer
OBJECTIVE: Epidemiologic studies have linked smoking to various malignancies, including bladder cancer, but its underlying biological functions remain elusive. Currently, we aimed to identify the smoking-related epigenetic modifications and disclose their impacts on prognosis and therapies in bladde...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10074629/ https://www.ncbi.nlm.nih.gov/pubmed/37011378 http://dx.doi.org/10.1177/03946320231166774 |
Sumario: | OBJECTIVE: Epidemiologic studies have linked smoking to various malignancies, including bladder cancer, but its underlying biological functions remain elusive. Currently, we aimed to identify the smoking-related epigenetic modifications and disclose their impacts on prognosis and therapies in bladder cancer. METHODS: DNA methylation, transcriptome, and clinical profiles were acquired from The Cancer Genome Atlas (TCGA) using “TCGAbiolinks” Differential expression analyses were performed with “limma” and visualized by the “pheatmap” package. Smoking-related interactions were displayed using Cytoscape. Least absolute shrinkage and selection operator (LASSO) algorithm was for generation of a smoking-related prognostic model. Kaplan–Meier analysis with log-rank test was for survival analysis, followed by a prognostic nomogram. The Gene Set Enrichment Analysis (GSEA) was used for functional analysis. The “oncoPredict” package was applied for drug sensitivity analysis. RESULTS: We recruited all types of bladder cancers and found that smoking was involved in poor prognosis, with the hazard ratio (HR) of 1.600 (95%CI: 1.028–2.491). A total of 1078 smoking-related DNA methylations (526 hypermethylation and 552 hypomethylation) were identified and 9 methylation-driven genes differentially expressed in bladder cancer. Also, 506lncRNAs (448 upregulated and 58 downregulated lncRNAs) and 102 miRNAs (74 upregulated and 28 downregulated miRNAs) were determined as smoking-related ncRNAs. We then calculated the smoking-related risk score and observed that cases of high risk were predicted with poor prognosis. We constructed a prognostic nomogram to predict the 1-, 3-, and 5-year overall survival rates. Several cancer-related pathways were enriched in the high-risk group, and patients with high-risk were more sensitive to Gemcitabine, Wnt-C59, JAK1_8709, KRAS (G12C) Inhibitor-12, and LY2109761. Whereas, those with low-risk were more sensitive to Cisplatin, AZ960, and Buparlisib. CONCLUSIONS: Totally, we initially identified the smoking-related epigenetic modifications in bladder cancer and constructed a corresponding prognostic model, which was also linked to disparate sensitivities to chemotherapeutics. Our findings would provide novel insights into the carcinogenesis, prognosis, and therapies in bladder cancer. |
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