ArticleTranslational andrology and urology2021
Stemness-associated senescence genes as potential novel risk factors for papillary renal cell carcinoma.
Article in Translational andrology and urology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- N-acetyltransferase 10 as a novel prognostic biomarker in papillary renal cell carcinoma: a machine learning and experimental validation study.Translational cancer research · 2024Article
- Integrated analysis of histone modification features in clear cell renal cancer for risk stratification and therapeutic prediction.Translational oncology · 2024Article
- Article
- Senescence Promotes the Recovery of Stemness among Cancer Cells via Reprograming.Biomolecules · 2024Review
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9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPapillary renal cell carcinoma (PRCC) is the 2nd most common type of renal carcinoma; however, there is limited data about PRCC, and strategies for the diagnosis and treatment of PRCC need to be identified.
methodsIn this study, the stemness-associated senescence (SAS) phenotype of PRCC was obtained by a bioinformatics analysis. We acquired the gene expression profiles of patients with PRCC and calculated the PRCC messenger ribonucleic acid stemness index (mRNAsi). We then screened the SAS genes from the GenAge database. A least absolute shrinkage and selection operator-Cox regression was conducted to examine correlations between risk signatures and the abundance of the SAS genes in the PRCC samples. Functional enrichment analyses were then performed via molecular co-expression studies of mRNAsi, and the risk scores of PRCC patients were calculated.
resultsWe identified the following 8 SAS signatures that were strongly associated with prognosis in PRCC patients: cyclin-dependent kinase 1, heat shock protein family D member 1, platelet-derived growth factor receptor A, cyclin-dependent kinase inhibitor 2B, pyrroline-5-carboxylate reductase 1, sequestosome-1, sirtuin-3, and cyclin-dependent kinase inhibitor 1A. The SAS signatures were significantly associated with the stage and type of PRCC. The calculated risk scores can be used to divide PRCC patients into low- and high-risk groups, and provide guidance in determining treatment plans.
conclusionsWe have developed a reliable prognostic tool to predict the clinical outcomes of PRCC patients. This tool could improve treatment decisions regarding drug therapy, surgery, and conservative options.
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