ArticlePeerJ2019
Bioinformatic analysis identifies potentially key differentially expressed genes in oncogenesis and progression of clear cell renal cell carcinoma.
Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 24 citations in OpenAlex.
- KIF4A in disease pathogenesis and therapeutics: from molecular mechanisms to clinical translation.Biology direct · 2025Review
- Prognostic Significance of Overexpression of BCL9 and TPX2 in High-Grade Clear Cell Renal Cell Carcinoma: Prognostic Markers for Metastasis and Survival.International journal of molecular sciences · 2025Article
- Novel 4-Chromanone-Derived Compounds as Plant Immunity Inducers against CMV Disease inMolecules (Basel, Switzerland) · 2024Article
- Article
- Low expression of SLC34A1 is associated with poor prognosis in clear cell renal cell carcinoma.BMC urology · 2023Article
- Chitosan oligosaccharide as a plant immune inducer on theFrontiers in plant science · 2023Article
- Identification of Differentially Methylated Genes Associated with Clear Cell Renal Cell Carcinoma and Their Prognostic Values.Journal of environmental and public health · 2023Article
- Article
- Overexpression of NCAPG in ovarian cancer is associated with ovarian cancer proliferation and apoptosis via p38 MAPK signaling pathway.Journal of ovarian research · 2022Article
- AC099850.3/NCAPG Axis Predicts Poor Prognosis and is Associated with Resistance to EGFR Tyrosine-Kinase Inhibitors in Lung Adenocarcinoma.International journal of general medicine · 2022Article
- Inhibition of KIF20A by transcription factor IRF6 affects the progression of renal clear cell carcinoma.Cancer cell international · 2021Article
- A systematic analysis of a potential metabolism-related prognostic signature for breast cancer patients.Annals of translational medicine · 2021Article
- The Choice of Candidates in Survival Markers Based on Coordinated Gene Expression in Renal Cancer.Frontiers in oncology · 2021Article
- The kinesin motor protein KIF4A as a potential therapeutic target in renal cell carcinoma.Investigational new drugs · 2020Article
- mRNA Profile in Milk Extracellular Vesicles from Bovine Leukemia Virus-Infected Cattle.Viruses · 2020Article
- Identification of Prognostic Gene Signatures for Survival of Patients With Phaeochromocytoma, Paraganglioma, and Other Tumor Types.Cancer diagnosis & prognosisArticle
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Clear cell renal cell carcinoma (ccRCC) is one of the most common and lethal types of cancer within the urinary system. Great efforts have been made to elucidate the pathogeny. However, the molecular mechanism of ccRCC is still not well understood. The aim of this study is to identify key genes in the carcinogenesis and progression of ccRCC. The mRNA microarray dataset GSE53757 was downloaded from the Gene Expression Omnibus database. The GSE53757 dataset contains tumor and matched paracancerous specimens from 72 ccRCC patients with clinical stage I to IV. The linear model of microarray data (limma) package in R language was used to identify differentially expressed genes (DEGs). The protein-protein interaction (PPI) network of the DEGs was constructed using the search tool for the retrieval of interacting genes (STRING). Subsequently, we visualized molecular interaction networks by Cytoscape software and analyzed modules with MCODE. A total of 1,284, 1,416, 1,610 and 1,185 up-regulated genes, and 932, 1,236, 1,006 and 929 down-regulated genes were identified from clinical stage I to IV ccRCC patients, respectively. The overlapping DEGs among the four clinical stages contain 870 up-regulated and 645 down-regulated genes. The enrichment analysis of DEGs in the top module was carried out with DAVID. The results showed the DEGs of the top module were mainly enriched in microtubule-based movement, mitotic cytokinesis and mitotic chromosome condensation. Eleven up-regulated genes and one down-regulated gene were identified as hub genes. Survival analysis showed the high expression of CENPE, KIF20A, KIF4A, MELK, NCAPG, NDC80, NUF2, TOP2A, TPX2 and UBE2C, and low expression of ACADM gene could be involved in the carcinogenesis, invasion or recurrence of ccRCC. Literature retrieval results showed the hub gene NDC80, CENPE and ACADM might be novel targets for the diagnosis, clinical treatment and prognosis of ccRCC. In conclusion, the findings of present study may help us understand the molecular mechanisms underlying the carcinogenesis and progression of ccRCC, and provide potential diagnostic, therapeutic and prognostic biomarkers.
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