Identifying the novel key genes in renal cell carcinoma by bioinformatics analysis and cell experiments
Posted on 2020-07-22 - 06:20
Abstract Background Although 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. Methods Microarray 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). Results A 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. Conclusion Based on our current findings, it is concluded that SUCLG1, PCK2, GLDC may serve as a potential prognostic marker of RCC.
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Chen, Yeda; Gu, Di; Wen, Yaoan; Yang, Shuxin; Duan, Xiaolu; Lai, Yongchang; et al. (2020). Identifying the novel key genes in renal cell carcinoma by bioinformatics analysis and cell experiments. figshare. Collection. https://doi.org/10.6084/m9.figshare.c.5069709.v1
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AUTHORS (11)
YC
Yeda Chen
DG
Di Gu
YW
Yaoan Wen
SY
Shuxin Yang
XD
Xiaolu Duan
YL
Yongchang Lai
JY
Jianan Yang
DY
Daozhang Yuan
AK
Aisha Khan
WW
Wenqi Wu
GZ
Guohua Zeng
KEYWORDS
genes needsurvival analysisbioinformatics analysiscell carcinoma12AGEO 2R toolSUCLGcell experimentscell cancersurvival timemodule analysiskidney cancer cells215 DEGsPCKcell experiments Abstract Backgroundflow cytometryGLDCPDHAwound healing assaycell viability assaysprognostic markerfunction enrichment analysesprotein-protein interaction networkGene Expression Omnibus1AATP769- Pexpression levelACHNinvasion assaysDifferential expressionflow cytometry analysis293 t cell lineexpression levelsRCC samplesGEPIAtranswell migrationOSRC -2 cell linesGSE 68417PPIdriver genehub geneSLChub genesTranswell migrationRCC cells