ArticleBMC cancer2021
Bioinformatics analysis of C3 and CXCR4 demonstrates their potential as prognostic biomarkers in clear cell renal cell carcinoma (ccRCC).
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 8 papers.
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Who cites it
8 citing papers in PubMed.
- Integrative Meta-Analysis and WGCNA Reveal Candidate Diagnostic Hub Genes in Clear Cell Carcinoma.International journal of cell biology · 2026Article
- PLAUR, C3, and EMP3 coordinate tumor progression and immune evasion in clear cell renal cell carcinoma.Discover oncology · 2025Article
- Identification of CXCR4 as a potential preventive gene in clear cell renal cell carcinoma from machine learning and immune analysis.Scientific reports · 2025Article
- Changes in complement C3a in the immunotherapy of advanced clear cell renal cell carcinoma.Translational andrology and urology · 2024Article
- The convergence of tumor suppressors on the type I interferon pathway in clear cell renal cell carcinoma and its therapeutic implications.American journal of physiology. Cell physiology · 2022Review
- Article
- Prognostic significance of CKAP2L expression in patients with clear cell renal cell carcinoma.Frontiers in genetics · 2022Article
- Crosstalk of necroptosis and pyroptosis defines tumor microenvironment characterization and predicts prognosis in clear cell renal carcinoma.Frontiers in immunology · 2022Article
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7 authors.
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Abstract
backgroundThe molecular prognostic biomarkers of clear cell renal cell carcinoma (ccRCC) are still unknown. We aimed at researching the candidate biomarkers and potential therapeutic targets of ccRCC.
methodsThree ccRCC expression microarray datasets (include GSE14762, GSE66270 and GSE53757) were downloaded from the gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) between ccRCC and normal tissues were explored. The potential functions of identified DEGs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). And then the protein - protein interaction network (PPI) was established to screen the hub genes. After that, the expressions of hub genes were identified by the oncomine database. The hub genes' prognostic values of patients with ccRCC were analyzed by GEPIA database.
resultsA total of 137 DEGs were identified by utilizing the limma package and RRA method, including 63 upregulated genes and 74 downregulated genes. It is found that 137 DEGs were mainly enriched in 82 functional terms and 24 pathways in accordance with the research results. Thirteen highest-scoring genes were screened as hub genes (include 10 upregulated genes and 3 downregulated candidate genes) by utilizing the PPI network and module analysis. Through integrating the oncoming database and GEPIA database, the author found that C3 and CXCR4 are not only overexpressed in ccRCC, but also associated with the prognosis of ccRCC. Further results could reveal that patients with high C3 expression had a poor overall survival (OS), while patients with high CTSS and TLR3 expressions had a good OS; patients with high C3 and CXCR4 expressions had a poor disease-free survival (DFS), while ccRCC patients with high TLR3 expression had a good DFS.
conclusionThese findings suggested that C3 and CXCR4 were the candidate biomarkers and potential therapeutic targets of ccRCC patients.
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