Feng Li1, Yi Jin2, Xiaolu Pei3, Peiyuan Guo4, Keqin Dong5, Haoyuan Wang6, Yujia Chen7, Peng Guo8, Ling-Bing Meng9, Zhiyu Wang10. 1. Department of Urology, The Fourth Hospital of Hebei Medical University, No.12 Jiankang Road Shijiazhuang, 050011, Hebei Province, China. Electronic address: fengliorod@yeah.net. 2. Department of Oncology, Affiliated Xing Tai People Hospital of Hebei Medical University, Xingtai, 054001, Hebei Province, China. Electronic address: hbykdx16benshuodkq@163.com. 3. Department of Oncology, The Heibei General Hospital, No.348 Heping Road Shijiazhuang, 050051, Hebei Province, China. Electronic address: XiaoluPei@yeah.net. 4. School of Basic Medical Sciences, Hebei Medical University, 361 Zhongshan East Road, Shijiazhuang, Hebei, 050017, China. Electronic address: 15303296723@163.com. 5. School of Basic Medical Sciences, Hebei Medical University, 361 Zhongshan East Road, Shijiazhuang, Hebei, 050017, China. Electronic address: d1714157094@163.com. 6. School of Basic Medical Sciences, Hebei Medical University, 361 Zhongshan East Road, Shijiazhuang, Hebei, 050017, China. Electronic address: haoyuanbhj@yeah.net. 7. School of Basic Medical Sciences, Hebei Medical University, 361 Zhongshan East Road, Shijiazhuang, Hebei, 050017, China. Electronic address: yujiarjj@yeah.net. 8. Department of Orthopedics, The Fourth Hospital of Hebei Medical University, No.12 Jiankang Road Shijiazhuang, 050011, Hebei Province, China. Electronic address: pengguo9919@163.com. 9. School of Basic Medical Sciences, Hebei Medical University, 361 Zhongshan East Road, Shijiazhuang, Hebei, 050017, China. Electronic address: 314597690@qq.com. 10. Department of Immuno-oncology, The Fourth Hospital of Hebei Medical University, No.12 Jiankang Road Shijiazhuang, 050011, Hebei Province, China. Electronic address: zhiyuwbj021@yeah.net.
Abstract
BACKGROUND: It is estimated that there are 338,000 new renal-cell carcinoma releases every year in the world. Renal cell carcinoma (RCC) is a heterogeneous tumor, of which more than 70% is clear cell renal cell carcinoma (ccRCC). It is estimated that about 30% of new renal-cell carcinoma patients have metastases at the time of diagnosis. However, the pathogenesis of renal clear cell carcinoma has not been elucidated. Therefore, it is necessary to further study the pathogenesis of ccRCC. METHODS: Two expression profiling datasets (GSE68417, GSE71963) were downloaded from the GEO database. Differentially expressed genes (DEGs) between ccRCC and normal tissue samples were identified by GEO2R. Functional enrichment analysis was made by the DAVID tool. Protein-protein interaction (PPI) network was constructed. The hub genes were excavated. The clustering analysis of expression level of hub genes was performed by UCSC (University of California Santa Cruz) Xena database. The hub gene on overall survival rate (OS) in patients with ccRCC was performed by Kaplan-Meier Plotter. Finally, we used the ccRCC renal tissue samples to verify the hub genes. RESULTS: 1182 common DEGs between the two datasets were identified. The results of GO and KEGG analysis revealed that variations in were predominantly enriched in intracellular signaling cascade, oxidation reduction, intrinsic to membrane, integral to membrane, nucleoside binding, purine nucleoside binding, pathways in cancer, focal adhesion, cell adhesion molecules. 10 hub genes ITGAX, CD86, LY86, TLR2, TYROBP, FCGR2A, FCGR2B, PTPRC, ITGB2, ITGAM were identified. FCGR2B and TYROBP were negatively correlated with the overall survival rate in patients with ccRCC (P < 0.05). RT-qPCR analysis showed that the relative expression levels of CD86, FCGR2A, FCGR2B, TYROBP, LY86, and TLR2 were significantly higher in ccRCC samples, compared with the adjacent renal tissue groups. CONCLUSIONS: In summary, bioinformatics technology could be a useful tool to predict the progression of ccRCC. In addition, there are DEGs between ccRCC tumor tissue and normal renal tissue, and these DEGs might be considered as biomarkers for ccRCC.
BACKGROUND: It is estimated that there are 338,000 new renal-cell carcinoma releases every year in the world. Renal cell carcinoma (RCC) is a heterogeneous tumor, of which more than 70% is clear cell renal cell carcinoma (ccRCC). It is estimated that about 30% of new renal-cell carcinomapatients have metastases at the time of diagnosis. However, the pathogenesis of renal clear cell carcinoma has not been elucidated. Therefore, it is necessary to further study the pathogenesis of ccRCC. METHODS: Two expression profiling datasets (GSE68417, GSE71963) were downloaded from the GEO database. Differentially expressed genes (DEGs) between ccRCC and normal tissue samples were identified by GEO2R. Functional enrichment analysis was made by the DAVID tool. Protein-protein interaction (PPI) network was constructed. The hub genes were excavated. The clustering analysis of expression level of hub genes was performed by UCSC (University of California Santa Cruz) Xena database. The hub gene on overall survival rate (OS) in patients with ccRCC was performed by Kaplan-Meier Plotter. Finally, we used the ccRCC renal tissue samples to verify the hub genes. RESULTS: 1182 common DEGs between the two datasets were identified. The results of GO and KEGG analysis revealed that variations in were predominantly enriched in intracellular signaling cascade, oxidation reduction, intrinsic to membrane, integral to membrane, nucleoside binding, purine nucleoside binding, pathways in cancer, focal adhesion, cell adhesion molecules. 10 hub genes ITGAX, CD86, LY86, TLR2, TYROBP, FCGR2A, FCGR2B, PTPRC, ITGB2, ITGAM were identified. FCGR2B and TYROBP were negatively correlated with the overall survival rate in patients with ccRCC (P < 0.05). RT-qPCR analysis showed that the relative expression levels of CD86, FCGR2A, FCGR2B, TYROBP, LY86, and TLR2 were significantly higher in ccRCC samples, compared with the adjacent renal tissue groups. CONCLUSIONS: In summary, bioinformatics technology could be a useful tool to predict the progression of ccRCC. In addition, there are DEGs between ccRCC tumor tissue and normal renal tissue, and these DEGs might be considered as biomarkers for ccRCC.