ArticleTranslational cancer research2023
Bioinformatics identification of prognostic genes and potential interaction analysis in renal cell carcinoma.
Article in Translational cancer research, 2023. 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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Who cites it
3 citing papers in PubMed.
- SUMOylation-Driven Subtype Heterogeneity and Prognostic Biomarkers in Renal Cell Carcinoma.Current issues in molecular biology · 2026Article
- PFKP in malignant tumors: bridging metabolic reprogramming, post-translational modifications, and the immunosuppressive microenvironment.Frontiers in cell and developmental biology · 2026Review
- Article
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4 authors.
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Abstract
Background: Renal cell carcinoma (RCC) is one of the ten most prevalent cancers in the world and its incidence has been rising over the past decade. However, effective biomarkers to predict the prognosis of patients remains absent, and the exact molecular mechanism of the disease remains unclear. Therefore, the identification of key genes and their biological pathways are of great significance to identify the differential expressed genes associated with the prognosis for patients with RCC, and to further explore their potential protein-protein interactions (PPIs) in tumorigenesis. Methods: The gene expression microarray data for GSE15641 and GSE40435 were extracted from the Gene Expression Omnibus (GEO) database, including 150 primary tumors and their matched adjacent non-tumor tissues. Afterwards, gene expression for fold changes (FCs) and P value for tumor and non-tumor tissues were analyzed using online tool GEO2R. Gene expression with logFCs of greater than two combined with P value of lower than 0.01 were considered as candidate targets for treatment of RCC. The survival analysis of candidate genes was performed by online software OncoLnc. The PPI network was implemented with Search Tool for the Retrieval of Interacting Genes (STRING). Results: In total, there were 625 differentially expressed genes (DEGs) in GSE15641, including 415 increased and 210 decreased genes. A total of 343 DEGs were identified in the GSE40435 with 101 upregulated and 242 downregulated genes, the 20 genes with highest FC in high or low expression in each database were summarized. Five candidate genes were overlapped genes in the two GEO datasets. However, aldolase, fructose-bisphosphate B (ALDOB) was found to be the only gene affecting the prognosis. A number of critical genes were identified behind the mechanism, of which they interacted with ALDOB. Among them, phosphofructokinase, platelet ( Conclusions: Five genes were found to be overlappingly expressed in the top 20 greatest FC in two human GEO datasets. This is of great value in the treatment and prognosis of RCC.
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