ArticleTranslational andrology and urology2020
Prognostic model of 10 immune-related genes and identification of small molecule drugs in bladder urothelial carcinoma (BLCA).
Article in Translational andrology and urology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 18 citations in OpenAlex.
- TGF-β signaling and tumor microenvironment dynamics in bladder cancer progression post-BCG therapy: a longitudinal single-nucleus RNA-seq study.BMC cancer · 2025Article
- Integrative multi-omics analysis for identifying novel therapeutic targets and predicting immunotherapy efficacy in lung adenocarcinoma.Cancer drug resistance (Alhambra, Calif.) · 2025Article
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- Ethanol promoting the upregulation of C-X-C Motif Chemokine Ligand 1（CXCL1） and C-X-C Motif Chemokine Ligand 6（CXCL6） in models of early alcoholic liver disease.Bioengineered · 2022Article
- Nucleolar protein NOP2 could serve as a potential prognostic predictor for clear cell renal cell carcinoma.Bioengineered · 2021Article
- A novel immune-related gene pair prognostic signature for predicting overall survival in bladder cancer.BMC cancer · 2021Article
- The landscape of tumors-infiltrate immune cells in papillary thyroid carcinoma and its prognostic value.PeerJ · 2021Article
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6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWe aimed to establish an immune-related gene (IRG) based signature that could provide guidance for clinical bladder cancer (BC) prognostic surveillance.
methodsDifferentially expressed IRGs and transcription factors (TFs) between BCs and normal tissues were extracted from transcriptome data downloaded from the TCGA database. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out to identify related pathways based on differently expressed IRGs. Then, univariate Cox regression analysis was performed to investigate IRGs with prognostic values and LASSO penalized Cox regression analysis was utilized to develop the prognostic index (PI) model.
resultsA total of 411 BC tissue samples and 19 normal bladder tissues in the TCGA database were enrolled in this study and 259 differentially expressed IRGs were identified. Networks between TFs and IRGs were also provided to seek the upstream regulators of differentially expressed IRGs. By means of univariate Cox regression analysis, 57 IRGs were analyzed with prognostic values and 10 IRGs were finally identified by LASSO penalized Cox regression analysis to construct the PI model. This model could significantly classified BC patients into high-risk group and low-risk group in terms of OS (P=9.923e-07) and its AUC reached 0.711. By means of univariate and multivariate COX regression analysis, this PI was proven to be a valuable independent prognostic factor (HR =1.119, 95% CI =1.066-1.175, P<0.001). CMap database analysis was also utilized to screen out 10 small molecules drugs with the potential for the treatment of BC.
conclusionsOur study successfully provided a novel PI based on IRGs with the potential to predict the prognosis of BC and screened out 10 small molecules drugs with the potential to treat BC. Besides, networks between TFs and IRGs were also displayed to seek its upstream regulators for future researches.
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