ArticleBMC cancer2021
Identification of a novel metabolism-related gene signature associated with the survival of bladder cancer.
Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Epigenomics-Guided Multi-Omics Integration Uncovers a Lipid-Metabolic Signature with Translational Utility in Bladder Cancer.Computational and structural biotechnology journal · 2026Article
- A multi-cohort validated OXPHOS signature predicts survival and immune profiles in grade II/III glioma patients.Frontiers in immunology · 2025Article
- Expression of amine oxidase-related proteins in breast phyllodes tumor.Histology and histopathology · 2025Article
- Identification of inflammation related gene signatures for bladder cancer prognosis prediction.Scientific reports · 2024Article
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- Identification and immune landscape analysis of fatty acid metabolism genes related subtypes of gastric cancer.Scientific reports · 2023Article
- Article
- LDL receptor related protein 1 is an adverse prognostic biomarker that correlates with stromal remodeling and macrophages infiltration in bladder cancer.Frontiers in immunology · 2023Article
- Construction of cancer- associated fibroblasts related risk signature based on single-cell RNA-seq and bulk RNA-seq data in bladder urothelial carcinoma.Frontiers in oncology · 2023Article
- Article
- Ogt Demonstrated Conspicuous Clinical Significance in Cancers, from Pan-Cancer to Small-Cell Lung Cancer.Journal of oncology · 2022Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBladder cancer (BC) is one of the most common malignancies and has a relatively poor outcome worldwide. In this study, we attempted to construct a novel metabolism-related gene (MRG) signature for predicting the survival probability of BC patients.
methodsFirst, differentially expressed MRGs between BC and normal samples were identified and used to construct a protein-protein interaction (PPI) network and perform mutation analysis. Next, univariate Cox regression analysis was utilized to select prognostic genes, and multivariate Cox regression analysis was applied to establish an MRG signature for predicting the survival probability of BC patients. Moreover, Kaplan-Meier (KM) survival analysis and receiver operating characteristic (ROC) analysis were performed to evaluate the predictive capability of the MRG signature. Finally, a nomogram based on the MRG signature was established to better predict the survival of BC.
resultsIn the present study, 27 differentially expressed MRGs were identified, most of which presented mutations in BC patients, and LRP1 showed the highest mutation rate. Next, an MRG signature, including MAOB, FASN and LRP1, was established by using univariate and multivariate Cox regression analysis. Furthermore, survival analysis indicated that BC patients in the high-risk group had a dramatically lower survival probability than those in the low-risk group. Finally, Cox regression analysis showed that the risk score was an independent prognostic factor, and a nomogram integrating age, pathological tumor stage and risk score was established and presented good predictive ability.
conclusionWe successfully constructed a novel MRG signature to predict the prognosis of BC patients, which might contribute to the clinical treatment of BC.
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