ArticleCancer cell international2019
A six-gene prognostic model predicts overall survival in bladder cancer patients.
Article in Cancer cell international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed, 73 citations in OpenAlex.
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- Biomarker-Based Nomogram to Predict Neoadjuvant Chemotherapy Response in Muscle-Invasive Bladder Cancer.Biomedicines · 2025Article
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- Gene signature for response prediction to immunotherapy and prognostic markers in metastatic urothelial carcinoma.Frontiers in immunology · 2025Article
- Development and validation of a prognostic model based on m6A-related lncRNAs to predict prognosis for papillary renal cell cancer patients.Scientific reports · 2024Article
- Machine learning and single-cell RNA sequencing reveal relationship between intratumor CD8Cancer cell international · 2024Article
- Prognostic and chemotherapeutic response prediction by proliferation essential gene signature: Investigating POLE2 in bladder cancer progression and cisplatin resistance.Journal of Cancer · 2024Article
- Serum cytokine levels and other associated factors as possible immunotherapeutic targets and prognostic indicators for lung cancer.Frontiers in oncology · 2023Review
- Identification of a Prognostic Colorectal Cancer Model Including LncRNA FOXP4-AS1 and LncRNA BBOX1-AS1 Based on Bioinformatics Analysis.Cancer biotherapy & radiopharmaceuticals · 2022Article
- A novel focal adhesion-related risk model predicts prognosis of bladder cancer -- a bioinformatic study based on TCGA and GEO database.BMC cancer · 2022Article
- An immune-related lncRNA model for predicting prognosis, immune landscape and chemotherapeutic response in bladder cancer.Scientific reports · 2022Article
- SIGNET: single-cell RNA-seq-based gene regulatory network prediction using multiple-layer perceptron bagging.Briefings in bioinformatics · 2022Article
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- Construction of the Six-lncRNA Prognosis Signature as a Novel Biomarker in Esophageal Squamous Cell Carcinoma.Frontiers in genetics · 2022Article
- Pro-metastatic and mesenchymal gene expression signatures characterize circulating tumor cells of neuroblastoma patients with bone marrow metastases and relapse.Frontiers in oncology · 2022Article
- Prognostic Analysis of Differentially Expressed DNA Damage Repair Genes in Bladder Cancer.Pathology oncology research : POR · 2022Article
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- Effect of unfolded protein response on the immune infiltration and prognosis of transitional cell bladder cancer.Annals of medicine · 2021Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe fatality and recurrence rates of bladder cancer (BC) have progressively increased. DNA methylation is an influential regulator associated with gene transcription in the pathogenesis of BC. We describe a comprehensive epigenetic study performed to analyse DNA methylation-driven genes in BC.
methodsData related to DNA methylation, the gene transcriptome and survival in BC were downloaded from The Cancer Genome Atlas (TCGA). MethylMix was used to detect BC-specific hyper-/hypo-methylated genes. Metascape was used to carry out gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. A least absolute shrinkage and selection operator (LASSO)-penalized Cox regression was conducted to identify the characteristic dimension decrease and distinguish prognosis-related methylation-driven genes. Subsequently, we developed a six-gene risk evaluation model and a novel prognosis-related nomogram to predict overall survival (OS). A survival analysis was carried out to explore the individual prognostic significance of the six genes.
resultsIn total, 167 methylation-driven genes were identified. Based on the LASSO Cox regression, six genes, i.e., ARHGDIB, LINC00526, IDH2, ARL14, GSTM2, and LURAP1, were selected for the development of a risk evaluation model. The Kaplan-Meier curve indicated that patients in the low-risk group had considerably better OS (P = 1.679e-05). The area under the curve (AUC) of this model was 0.698 at 3 years of OS. The verification performed in subgroups demonstrated the validity of the model. Then, we designed an OS-associated nomogram that included the risk score and clinical factors. The concordance index of the nomogram was 0.694. The methylation levels of IDH2 and ARL14 were appreciably related to the survival results. In addition, the methylation and gene expression-matched survival analysis revealed that ARHGDIB and ARL14 could be used as independent prognostic indicators. Among the six genes, 6 methylation sites in ARHGDIB, 3 in GSTM2, 1 in ARL14, 2 in LINC00526 and 2 in LURAP1 were meaningfully associated with BC prognosis. In addition, several abnormal methylated sites were identified as linked to gene expression.
conclusionWe discovered differential methylation in BC patients with better and worse survival and provided a risk evaluation model by merging six gene markers with clinical characteristics.
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