Co-expression Network Analysis Identifies Fourteen Hub Genes Associated with Prognosis in Clear Cell Renal Cell Carcinom
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40(4):773-785,2020
773
Co-expression Network Analysis Identifies Fourteen Hub Genes Associated with Prognosis in Clear Cell Renal Cell Carcinoma* Jia-yi CHEN1, 2†, Yan SUN1, 2†, Nan QIAO1, 2, Yang-yang GE1, 2, Jian-hua LI1, 2, Yun LIN1, 2#, Shang-long YAO1, 2# 1 Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China 2 Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China Huazhong University of Science and Technology 2020
Summary: Renal cancer is a common genitourinary malignance, of which clear cell renal cell carcinoma (ccRCC) has high aggressiveness and leads to most cancer-related deaths. Identification of sensitive and reliable biomarkers for predicting tumorigenesis and progression has great significance in guiding the diagnosis and treatment of ccRCC. Here, we identified 2397 common differentially expressed genes (DEGs) using paired normal and tumor ccRCC tissues from GSE53757 and The Cancer Genome Atlas (TCGA). Then, we performed weighted gene co-expression network analysis and protein-protein interaction network analysis, 17 candidate hub genes were identified. These candidate hub genes were further validated in GSE36895 and Oncomine database and 14 real hub genes were identified. All the hub genes were up-regulated and significantly positively correlated with pathological stage and histologic grade of ccRCC. Survival analysis showed that the higher expression level of each hub gene tended to predict a worse clinical outcome. ROC analysis showed that all the hub genes can accurately distinguish between tumor and normal samples, and between early stage and advanced stage ccRCC. Moreover, all the hub genes were positively associated with distant metastasis, lymph node infiltration, tumor recurrence and the expression of MKi67, suggesting these genes might promote tumor proliferation, invasion and metastasis. Furthermore, the functional annotation demonstrated that most genes were enriched in cell-cycle related biological function. In summary, our study identified 14 potential biomarkers for predicting tumorigenesis and progression, which might contribute to early diagnosis, prognosis prediction and therapeutic intervention. Key words: bioinformatics; clear cell renal cell carcinoma; weighted gene co-expression network analysis; biomarker
Renal cell carcinoma (RCC) is the third most common genitourinary malignancies[1]. Clear cell renal cell carcinoma (ccRCC), a histological subtype of RCC, accounts for approximately 80% to 90% of all cases[2]. To date, surgical resection, including radical or partial nephrectomy, has been the standard procedure for localized ccRCC with excellent overall survival rates[3]. In term of advanced ccRCC, the introduction of targeted therapy and immunotherapy improves the prognosis. However, the therapeutic effect is still not Jia-yi CHEN, E-mail: [email protected]; Yan SUN, E-mail: 93640010
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