Category

Archives

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 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.

Comments:

As per the study, the researchers aimed to identify smoking-related epigenetic modifications and their impact on prognosis and therapies in bladder cancer. They acquired DNA methylation, transcriptome, and clinical profiles from The Cancer Genome Atlas (TCGA) using TCGAbiolinks and performed differential expression analyses with limma, visualized by the pheatmap package. Smoking-related interactions were displayed using Cytoscape, and a smoking-related prognostic model was generated using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. The researchers used Kaplan-Meier analysis with log-rank test for survival analysis and constructed a prognostic nomogram. They used Gene Set Enrichment Analysis (GSEA) for functional analysis and the oncoPredict package for drug sensitivity analysis.

The study found that smoking was associated with poor prognosis in all types of bladder cancer, with a hazard ratio (HR) of 1.600 (95%CI: 1.028-2.491). They identified 1078 smoking-related DNA methylations (526 hypermethylation and 552 hypomethylation), 9 methylation-driven genes differentially expressed in bladder cancer, 506 lncRNAs (448 upregulated and 58 downregulated lncRNAs), and 102 miRNAs (74 upregulated and 28 downregulated miRNAs) as smoking-related ncRNAs. They calculated the smoking-related risk score and found that high-risk cases were associated with poor prognosis. The researchers 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.

In conclusion, this study identified smoking-related epigenetic modifications in bladder cancer and constructed a corresponding prognostic model, which was linked to different sensitivities to chemotherapeutics. These findings provide new insights into the carcinogenesis, prognosis, and therapies of bladder cancer.

Related Products

Cat.No. Product Name Information
S7037 Wnt-C59 (C59) Wnt-C59 (C59) is a PORCN inhibitor for Wnt3A-mediated activation of a multimerized TCF-binding site driving luciferase with IC50 of 74 pM in HEK293 cells.

Related Targets

PORCN