ArticleBioscience reports2020
Development of a novel prognostic signature for predicting the overall survival of bladder cancer patients.
Article in Bioscience reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
- DNA methylation of miR-181a-5p mediated by DNMT3b drives renal interstitial fibrosis developed from acute kidney injury.Epigenomics · 2024Article
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- CTSV (cathepsin V) promotes bladder cancer progression by increasing NF-κB activity.Bioengineered · 2022Article
Corrections and comments
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Authors and funding
12 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBladder cancer is one of the most common malignancies. So far, no effective biomarker for bladder cancer prognosis has been identified. Aberrant DNA methylation is frequently observed in the bladder cancer and holds considerable promise as a biomarker for predicting the overall survival (OS) of patients. MATERIALS AND
methodsWe downloaded the DNA methylation and transcriptome data for bladder cancer from The Cancer Genome Atlas (TCGA), a public database, screened hypo-methylated and up-regulated genes, similarly, hyper-methylation with low expression genes, then retrieved the relevant methylation sites. Cox regression analysis was used to identify a nine-methylation site signature of a training group. Predictive ability was validated in a test group by receiver operating characteristic (ROC) analysis.
resultsWe identified nine bladder cancer-specific methylation sites as potential prognostic biomarkers and established a risk score system based on the methylation site signature to evaluate the OS. The performance of the signature was accurate, with area under curve was 0.73 in the training group and 0.71 in the test group. Taking clinical features into consideration, we constructed a nomogram consisting of the nine-methylation site signature and patients' clinical variables, and found that the signature was an independent risk factor.
conclusionsOverall, the significant nine methylation sites could be novel prediction biomarkers, which could aid in treatment and also predict the overall survival likelihoods of bladder cancer patients.
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