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Abstract: FR-PO188

Identification of Pathologic Grading-Related Gene Modules Associated With Kidney Renal Clear Cell Carcinoma Based on Analysis of the Gene Expression Omnibus and The Cancer Genome Atlas

Session Information

Category: Onconephrology

  • 1600 Onconephrology


  • Xiong, Weijian, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
  • Li, Ying, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
  • Li, Wu Li, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
  • Xuan, Gao, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China

Renal cell carcinoma (RCC) originates from the renal epithelium and is the most common type of renal cancer with a poor prognosis. As the pathogenesis of kidney renal clear cell carcinoma (KIRC) has not been elucidated, which is necessary to be further explored.


An expression analysis dataset (GSE126964) was downloaded from the GEO database. Differentially expressed genes (DEGs) between KIRC and normal tissue samples were identified using edgeR and limma analysis. Based on the systematic biology approach of WGCNA, a gene co-expression network was constructed to screen potential biomarkers and therapeutic targets of this disease. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed in the DAVID database.Kaplan-Meier Plotter was used to identify the hub genes associated with overall survival (OS) time of KIRC patients.


A total of 1863 DEGs were identified between the two datasets. Ten co-expressed gene modules were identified using the WGCNA method. GO and KEGG analysis findings revealed that the most enrichment pathways included Notch binding, cell migration, cell cycle, cell senescence, apoptosis, focal adhesions and autophagosomes. Twenty-seven hub genes were identified, among which FLT1, HNRNPU, ATP6V0D2, ATP6V1A, and ATP6V1H were positively correlated with the OS rate of KIRC patients.


In conclusion, DEGs present in both KIRC and normal kidney tissues, which can be considered as the KIRC biomarkers.


  • Government Support – Non-U.S.