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Prognostic and predictive value of immune/stromal-related gene biomarkers in renal cell carcinoma

  • Authors:
    • Sen Wang
    • Xiangguang Zheng
    • Xinglu Chen
    • Xiaojun Shi
    • Sansan Chen
  • View Affiliations / Copyright

    Affiliations: Department of Urology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, Guangdong 510000, P.R. China, Department of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
    Copyright: © Wang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 308-316
    |
    Published online on: April 24, 2020
       https://doi.org/10.3892/ol.2020.11574
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Abstract

Immune/stromal-associated genes may be promising biomarkers for cancer diagnosis and the determination of clinical cancer treatment options. The aim of the present study was to identify prognostic stromal/immune-associated genes in renal cell carcinoma (RCC). RCC gene expression data (885 cases) were obtained from The Cancer Genome Atlas database. Immune/stromal scores were calculated by using the ESTIMATE package in R. Immune/stromal scores were significantly associated with Tumor-Node-Metastasis stage, clinical stage and overall survival rate (P<0.05). There were 419 differentially expressed genes (DEGs) based on immune scores and 738 DEGs based on stromal scores. Among these DEGs, 406 DEGs based on stromal scores and 252 DEGs based on immune scores were significantly associated with overall survival rate (P<0.05). The biological functions of these DEGs were primarily enriched in the ‘immune response’ and ‘regulation of cell migration and proliferation’. These DEGs were observed in a protein-protein interaction network. A LASSO Cox regression model was used to build a prognostic 6 gene-based classifier, including the IL21R, ATP6V1C2, GBP1, P2RY10, GBP4 and TNNC2 genes [area under the curve (AUC) =0.776]. The predictive model which combined this classifier with clinical prognostic factors had a high accuracy in predicting patient survival in RCC (combined AUC =0.899). Taken together, these results demonstrated that there are significant associations between immune/stromal scores and clinicopathological staging. A set of tumor microenvironment-associated genes that have powerful prognostic value in patients with RCC were identified in the present study.
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Copy and paste a formatted citation
Spandidos Publications style
Wang S, Zheng X, Chen X, Shi X and Chen S: Prognostic and predictive value of immune/stromal-related gene biomarkers in renal cell carcinoma. Oncol Lett 20: 308-316, 2020.
APA
Wang, S., Zheng, X., Chen, X., Shi, X., & Chen, S. (2020). Prognostic and predictive value of immune/stromal-related gene biomarkers in renal cell carcinoma. Oncology Letters, 20, 308-316. https://doi.org/10.3892/ol.2020.11574
MLA
Wang, S., Zheng, X., Chen, X., Shi, X., Chen, S."Prognostic and predictive value of immune/stromal-related gene biomarkers in renal cell carcinoma". Oncology Letters 20.1 (2020): 308-316.
Chicago
Wang, S., Zheng, X., Chen, X., Shi, X., Chen, S."Prognostic and predictive value of immune/stromal-related gene biomarkers in renal cell carcinoma". Oncology Letters 20, no. 1 (2020): 308-316. https://doi.org/10.3892/ol.2020.11574
Copy and paste a formatted citation
x
Spandidos Publications style
Wang S, Zheng X, Chen X, Shi X and Chen S: Prognostic and predictive value of immune/stromal-related gene biomarkers in renal cell carcinoma. Oncol Lett 20: 308-316, 2020.
APA
Wang, S., Zheng, X., Chen, X., Shi, X., & Chen, S. (2020). Prognostic and predictive value of immune/stromal-related gene biomarkers in renal cell carcinoma. Oncology Letters, 20, 308-316. https://doi.org/10.3892/ol.2020.11574
MLA
Wang, S., Zheng, X., Chen, X., Shi, X., Chen, S."Prognostic and predictive value of immune/stromal-related gene biomarkers in renal cell carcinoma". Oncology Letters 20.1 (2020): 308-316.
Chicago
Wang, S., Zheng, X., Chen, X., Shi, X., Chen, S."Prognostic and predictive value of immune/stromal-related gene biomarkers in renal cell carcinoma". Oncology Letters 20, no. 1 (2020): 308-316. https://doi.org/10.3892/ol.2020.11574
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