ArticleCancer cell international2020
Identifying the novel key genes in renal cell carcinoma by bioinformatics analysis and cell experiments.
Article in Cancer cell international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 18 citations in OpenAlex.
- PRKAB2 as a tumor suppressor in renal cell carcinoma: inhibiting mitophagy via the LRPPRC-PRKN/parkin interaction and cardiolipin biosynthesis.Autophagy · 2026Article
- Integrative Meta-Analysis and WGCNA Reveal Candidate Diagnostic Hub Genes in Clear Cell Carcinoma.International journal of cell biology · 2026Article
- Downregulation of Aging-Associated Gene SUCLG1 Marks the Aggressiveness of Liver Disease.Cancers · 2025Article
- Integrating network pharmacology and transcriptomics to identify solasonine's anti-osteosarcoma targets and experimental validation.Frontiers in oncology · 2025Article
- Glycine Decarboxylase Regulates Renal Carcinoma Progression via Interferon Stimulated Gene Factor 3-Mediated Pathway.International journal of biological sciences · 2025Article
- Biomarker Identification and Risk Prediction Model Development for Differentiated Thyroid Carcinoma Lung Metastasis Based on Primary Lesion Proteomics.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024Article
- Article
- Association ofInternational journal of molecular sciences · 2023Article
- ReGeNNe: genetic pathway-based deep neural network using canonical correlation regularizer for disease prediction.Bioinformatics (Oxford, England) · 2023Article
- Correction: Identifying the novel key genes in renal cell carcinoma by bioinformatics analysis and cell experiments.Cancer cell international · 2022Article
- Novel amino acid metabolism-related gene signature to predict prognosis in clear cell renal cell carcinoma.Frontiers in genetics · 2022Article
- A Cluster of Metabolic-Related Genes Serve as Potential Prognostic Biomarkers for Renal Cell Carcinoma.Frontiers in genetics · 2022Article
- Identification of TYROBP and FCER1G as Key Genes with Prognostic Value in Clear Cell Renal Cell Carcinoma by Bioinformatics Analysis.Biochemical genetics · 2021Article
- SDHB Suppresses the Tumorigenesis and Development of ccRCC by Inhibiting Glycolysis.Frontiers in oncology · 2021Article
- Overexpression of SHMT2 Predicts a Poor Prognosis and Promotes Tumor Cell Growth in Bladder Cancer.Frontiers in genetics · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAlthough major driver gene have been identified, the complex molecular heterogeneity of renal cell cancer (RCC) remains unclear. Therefore, more relevant genes need to be identified to explain the pathogenesis of renal cancer.
methodsMicroarray datasets GSE781, GSE6344, GSE53000 and GSE68417 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by employing GEO2R tool, and function enrichment analyses were performed by using DAVID. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using STRING and Cytoscape. Survival analysis was performed using GEPIA. Differential expression was verified in Oncomine. Cell experiments (cell viability assays, transwell migration and invasion assays, wound healing assay, flow cytometry) were utilized to verify the roles of the hub genes on the proliferation of kidney cancer cells (A498 and OSRC-2 cell lines).
resultsA total of 215 DEGs were identified from four datasets. Six hub gene (SUCLG1, PCK2, GLDC, SLC12A1, ATP1A1, PDHA1) were identified and the overall survival time of patients with RCC were significantly shorter. The expression levels of these six genes were significantly decreased in six RCC cell lines(A498, OSRC-2, 786- O, Caki-1, ACHN, 769-P) compared to 293t cell line. The expression level of both mRNA and protein of these genes were downregulated in RCC samples compared to those in paracancerous normal tissues. Cell viability assays showed that overexpressions of SUCLG1, PCK2, GLDC significantly decreased proliferation of RCC. Transwell migration, invasion, wound healing assay showed overexpression of three genes(SUCLG1, PCK2, GLDC) significantly inhibited the migration, invasion of RCC. Flow cytometry analysis showed that overexpression of three genes(SUCLG1, PCK2, GLDC) induced G1/S/G2 phase arrest of RCC cells.
conclusionBased on our current findings, it is concluded that SUCLG1, PCK2, GLDC may serve as a potential prognostic marker of RCC.
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Registered trials
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