SynthesisBioMed research international2019
Identification of EGFR as a Novel Key Gene in Clear Cell Renal Cell Carcinoma (ccRCC) through Bioinformatics Analysis and Meta-Analysis.
Synthesis in BioMed research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- A systematic investigation of clear cell renal cell carcinoma using meta-analysis and systems biology approaches.Molecular genetics and genomics : MGG · 2024Pooled it
- Multi-omics data integration for enhanced cancer subtyping via interactive multi-kernel learning.Briefings in bioinformatics · 2025Article
- Characterization of Cell Surface Glycoproteins Using Enzymatic Treatment and Mass Spectrometry.Analytical chemistry · 2024Article
- Article
- Identification and Validation of Cytotoxicity-Related Features to Predict Prognostic and Immunotherapy Response in Patients with Clear Cell Renal Cell Carcinoma.Genetics research · 2024Article
- ITGAX promotes gastric cancer progression via epithelial-mesenchymal transition pathway.Frontiers in pharmacology · 2024Article
- Article
- Stage-specific coexpression network analysis of Myc in cohorts of renal cancer.Scientific reports · 2023Article
- Solute carrier-related signature for assessing prognosis and immunity in patients with clear-cell renal cell carcinoma.Oncology research · 2023Article
- Multiomics surface receptor profiling of the NCI-60 tumor cell panel uncovers novel theranostics for cancer immunotherapy.Cancer cell international · 2022Article
- LRRK2 is a candidate prognostic biomarker for clear cell renal cell carcinoma.Cancer cell international · 2021Article
- Identification of an independent immune-genes prognostic index for renal cell carcinoma.BMC cancer · 2021Article
- Oncological Ligand-Target Binding Systems and Developmental Approaches for Cancer Theranostics.Molecular biotechnology · 2021Review
- Article
- An Immune-Related Gene Pairs Signature for Predicting Survival in Glioblastoma.Frontiers in oncology · 2021Article
- Identification of significant genes with prognostic influence in clear cell renal cell carcinoma via bioinformatics analysis.Translational andrology and urology · 2020Article
- Construction of a novel gene-based model for prognosis prediction of clear cell renal cell carcinoma.Cancer cell international · 2020Article
- Identification of a Glucose Metabolism-related Signature for prediction of Clinical Prognosis in Clear Cell Renal Cell Carcinoma.Journal of Cancer · 2020Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Clear cell renal cell carcinoma (ccRCC) was the most aggressive histological type of renal cell carcinoma (RCC) and accounted for 70-80% of cases of all RCC. The aim of this study was to identify the potential biomarker in ccRCC and explore their underlying mechanisms. Four profile datasets were downloaded from the GEO database to identify DEGs. GO and KEGG analysis of DEGs were performed by DAVID. A protein-protein interaction (PPI) network was constructed to predict hub genes. The hub gene expression within ccRCC across multiple datasets and the overall survival analysis were investigated utilizing the Oncomine Platform and UALCAN dataset, separately. A meta-analysis was performed to explore the relationship between the hub genes: EGFR and ccRCC. 127 DEGs (55 upregulated genes and 72 downregulated genes) were identified from four profile datasets. Integrating the result from PPI network, Oncomine Platform, and survival analysis, EGFR, FLT1, and EDN1 were screened as key factors in the prognosis of ccRCC. GO and KEGG analysis revealed that 127 DEGs were mainly enriched in 21 terms and 4 pathways. The meta-analysis showed that there was a significant difference of EGFR expression between ccRCC tissues and normal tissues, and the expression of EGFR in patients with metastasis was higher. This study identified 3 importance genes (EGFR, FLT1, and EDN1) in ccRCC, and EGFR may be a potential prognostic biomarker and novel therapeutic target for ccRCC, especially patients with metastasis.
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