ArticleFrontiers in oncology2021
Identification of Hub Genes Associated With Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed, 29 citations in OpenAlex.
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- EFHD1 expression is correlated with tumor-infiltrating neutrophils and predicts prognosis in gastric cancer.Heliyon · 2023Article
- EFHD1, a novel mitochondrial regulator of tumor metastasis in clear cell renal cell carcinoma.Cancer science · 2023Article
- Bioinformatics identification of prognostic genes and potential interaction analysis in renal cell carcinoma.Translational cancer research · 2023Article
- NDC80 status pinpoints mitotic kinase inhibitors as emerging therapeutic options in clear cell renal cell carcinoma.iScience · 2023Article
- Increased RTN3 phenocopies nonalcoholic fatty liver disease by inhibiting the AMPK-IDH2 pathway.MedComm · 2023Article
- Low expression of SLC34A1 is associated with poor prognosis in clear cell renal cell carcinoma.BMC urology · 2023Article
- Construction of a prognostic prediction model for renal clear cell carcinoma combining clinical traits.Scientific reports · 2023Article
- A novel lipid metabolism gene signature for clear cell renal cell carcinoma using integrated bioinformatics analysis.Frontiers in cell and developmental biology · 2023Article
- Exploration and Validation of Pancreatic Cancer Hub Genes Based on Weighted Gene Co-Expression Network Analysis and Immune Infiltration Score Analysis.Pharmacogenomics and personalized medicine · 2023Article
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- Novel prognostic matrisome-related gene signature of head and neck squamous cell carcinoma.Frontiers in cell and developmental biology · 2022Article
- Construction of a 12-Gene Prognostic Risk Model and Tumor Immune Microenvironment Analysis Based on the Clear Cell Renal Cell Carcinoma Model.Cancer control : journal of the Moffitt Cancer CenterArticle
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8 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundClear cell renal cell carcinoma (ccRCC) is a common genitourinary cancer type with a high mortality rate. Due to a diverse range of biochemical alterations and a high level of tumor heterogeneity, it is crucial to select highly validated prognostic biomarkers to be able to identify subtypes of ccRCC early and apply precision medicine approaches.
methodsTranscriptome data of ccRCC and clinical traits of patients were obtained from the GSE126964 dataset of Gene Expression Omnibus and The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) database. Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) screening were applied to detect common differentially co-expressed genes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analysis, survival analysis, prognostic model establishment, and gene set enrichment analysis were also performed. Immunohistochemical analysis results of the expression levels of prognostic genes were obtained from The Human Protein Atlas. Single-gene RNA sequencing data were obtained from the GSE131685 and GSE171306 datasets.
resultsIn the present study, a total of 2,492 DEGs identified between ccRCC and healthy controls were filtered, revealing 1,300 upregulated genes and 1,192 downregulated genes. Using WGCNA, the turquoise module was identified to be closely associated with ccRCC. Hub genes were identified using the maximal clique centrality algorithm. After having intersected the hub genes and the DEGs in GSE126964 and TCGA-KIRC dataset, and after performing univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses,
conclusionsThe present results demonstrated that
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