Biomarker Screening and Prognostic Significance Analysis for Renal Cell Carcinoma

• Main Authors: Meng X, Yuan H, Li W, Xiao W, Zhang X
• Format: Article
• Language: English
• Published: Dove Medical Press 2021-09-01
• Series: International Journal of General Medicine
• Subjects: advanced ccrcc; biomarker; progression; differentially expressed genes
• Online Access: https://www.dovepress.com/biomarker-screening-and-prognostic-significance-analysis-for-renal-cel-peer-reviewed-fulltext-article-IJGM

Xiangui Meng,1– 3,* Hongwei Yuan,1– 3,* Weiquan Li,1– 3,* Wen Xiao,1– 3 Xiaoping Zhang1– 3 1Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People’s Republic of China; 2Shenzhen Huazhong University of Science and Technology Research Institute, Shenzhen, 518000, People’s Republic of China; 3Institute of Urology, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiaoping Zhang; Wen XiaoDepartment of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 Jiefang Avenue, Wuhan, Hubei Province, 430022, People’s Republic of ChinaTel [phone]Fax [phone]Email [e-mail]; [e-mail]: Studies report that conventional treatment of clear cell renal cell carcinoma (ccRCC) is effective, but several advanced patients present with poor prognosis. The current study explored potential new tumor markers and therapeutic targets in advanced ccRCC.Methods: Biomarker gene expression of ccRCC was retrieved from GEO database and the Cancer Genome Atlas Kidney Clear Cell Carcinoma (TCGA-KIRC) database. Gene ontology (GO) analysis and protein–protein interaction (PPI) networks of biomarker genes were constructed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) tool. Kaplan–Meier analysis and receiver operating characteristic curve (ROC) analysis were performed to explore the prognostic and diagnostic roles of these genes. Gene set enrichment analysis (GSEA) analysis was used to determine hallmark functions of the biomarker genes. qRT-PCR was used to verify the reliability of the analysis results in tumor tissues.Results: A total of 21 upregulated genes were identified between advanced ccRCC and early ccRCC (grade III+IV vs grade I+II). Gene ontology analysis showed that the 21 upregulated genes were mainly implicated in biological processes including metabolic and lipid transport. The findings showed that 7 out of the 21 genes were significantly upregulated in 72-paired samples retrieved from the TCGA-KIRC. High expression of 5 genes indicated a poor prognosis of overall survival and disease-free survival in KIRC. Three genes effectively distinguished renal cancer tissue and adjacent renal tissues in a total of 533 ccRCC samples. GSEA showed that the 3 biomarkers were significantly enriched in epithelial–mesenchymal transition, G2M checkpoint, and angiogenesis. The results of qRT-PCR showed that STEAP3, IBSP, and AQP9 had a significant identification effect in ccRCC.Conclusion: The findings showed that 3 biomarkers were significantly upregulated in advanced ccRCC and could be used for diagnosis, prediction, and potential novel therapeutic targets for progression of ccRCC.Keywords: advanced ccRCC, biomarker, progression, differentially expressed genes