ArticleBMC nephrology2022
Construction and validation of a prognostic model of RNA binding proteins in clear cell renal carcinoma.
Article in BMC nephrology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Identification and validation of a gap junction protein related signature for predicting the prognosis of renal clear cell carcinoma.Frontiers in oncology · 2024Article
- Diverse targets of SMN2-directed splicing-modulating small molecule therapeutics for spinal muscular atrophy.Nucleic acids research · 2023Article
- Correction: Construction and validation of a prognostic model of RNA binding proteins in clear cell renal carcinoma.BMC nephrology · 2022Article
- Development of a polyamine gene expression score for predicting prognosis and treatment response in clear cell renal cell carcinoma.Frontiers in immunology · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe dysfunction of RNA binding proteins (RBPs) is associated with various inflammation and cancer. The occurrence and progression of tumors are closely related to the abnormal expression of RBPs. There are few studies on RBPs in clear cell renal carcinoma (ccRCC), which allows us to explore the role of RBPs in ccRCC.
methodsWe obtained the gene expression data and clinical data of ccRCC from the Cancer Genome Atlas (TCGA) database and extracted all the information of RBPs. We performed differential expression analysis of RBPs. Risk model were constructed based on the differentially expressed RBPs (DERBPs). The expression levels of model markers were examined by reverse transcription-quantitative PCR (RT-qPCR) and analyzed for model-clinical relevance. Finally, we mapped the model's nomograms to predict the 1, 3 and 5-year survival rates for ccRCC patients.
resultsThe results showed that the five-year survival rate for the high-risk group was 40.2% (95% CI = 0.313 ~ 0.518), while the five-year survival rate for the low-risk group was 84.3% (95% CI = 0.767 ~ 0.926). The ROC curves (AUC = 0.748) also showed that our model had stable predictive power. Further RT-qPCR results were in accordance with our analysis (p < 0.05). The results of the independent prognostic analysis showed that the model could be an independent prognostic factor for ccRCC. The results of the correlation analysis also demonstrated the good predictive ability of the model.
conclusionIn summary, the 4-RBPs (EZH2, RPL22L1, RNASE2, U2AF1L4) risk model could be used as a prognostic indicator of ccRCC. Our study provides a possibility for predicting the survival of ccRCC.
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