ArticleMedicine2020
Identification of biomarkers of clear cell renal cell carcinoma by bioinformatics analysis.
Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 13 citations in OpenAlex.
- KIF23 in disease pathogenesis and therapeutics : from molecular mechanisms to clinical translation.Cancer cell international · 2026Review
- Ochratoxin A and Clear Cell Renal Cell Carcinoma: Exploring Potential Molecular Links Through Network Toxicology and Machine Learning.International journal of molecular sciences · 2026Article
- Integrative Meta-Analysis and WGCNA Reveal Candidate Diagnostic Hub Genes in Clear Cell Carcinoma.International journal of cell biology · 2026Article
- Bioinformatics screening of prognostic immune-related genes in renal clear cell carcinoma.Journal of applied genetics · 2025Article
- Common molecular links and therapeutic insights between type 2 diabetes and kidney cancer.PloS one · 2025Article
- SPACA6-hosted miR-99b~125a~let-7e cluster shapes melanoma resistance by modulating mTOR-mediated immunosuppression.Frontiers in immunology · 2025Article
- The Role of ADCY1 in Regulating the Sensitivity of Platinum-Based Chemotherapy in NSCLC.Pharmaceuticals (Basel, Switzerland) · 2024Article
- The Clinical Significance and Involvement in Molecular Cancer Processes of Chemokine CXCL1 in Selected Tumors.International journal of molecular sciences · 2024Review
- Potential Value of Visfatin, Omentin-1, Nesfatin-1 and Apelin in Renal Cell Carcinoma (RCC): A Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2022Review
- Expression ofFrontiers in genetics · 2021Article
- The Choice of Candidates in Survival Markers Based on Coordinated Gene Expression in Renal Cancer.Frontiers in oncology · 2021Article
- CENPF as a Potential Biomarker Associated with the Immune Microenvironment of Renal Cancer.Technology in cancer research & treatmentArticle
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cancer, and more and more researches find that the occurrence of ccRCC is associated with genetic changes, but the molecular mechanism still remains unclear. The present study aimed to identify aggregation trend of differentially expressed genes (DEGs) in ccRCC, which would be beneficial to the treatment of ccRCC and provide research ideas using a series of bioinformatics approach. Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) analysis were used to get the enrichment trend of DEGs of GSE53757 and GSE16449. Draw Venn Diagram was applied for co-expression of DEGs. Cytoscape with the Retrieval of Interacting Gene (STRING) datasets and Molecular Complex Detection (MCODE) were performed protein-protein interaction (PPI) of DEGs. The Kaplan-Meier Plotter analysis of top 15 upregulated and top 15 downregulated were selected in Gene Expression Profiling Interactive Analysis (GEPIA). Then, the expression level of hub genes between normal renal tissue and different pathological stages of ccRCC tissue, which significantly correlated with overall survival in ccRCC patients, were also analyzed by Ualcan based on The Cancer Genome Atlas (TCGA) database. In this study, we got 167 co-expression DEGs, including 72 upregulated DEGs and 95 downregulated DEGs. We identified 11 hub genes had significantly correlated with overall survival in ccRCC patients. Among them, KIF23, APLN, ADCY1, GREB1, TLR4, IRF8, CXCL1, CXCL2, deserved our attention.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.