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. 2020 Nov 21;12(24):25304-25318.
doi: 10.18632/aging.104131. Epub 2020 Nov 21.

Identification of novel prognostic biomarkers in renal cell carcinoma

Yuanzhang Zou  1 , Qiu Lu  1 , Qin Yao  1 , Di Dong  1 , Binghai Chen  1
Affiliations

Identification of novel prognostic biomarkers in renal cell carcinoma

Yuanzhang Zou et al. Aging (Albany NY). .

Abstract

Objective: To identify novel prognostic biomarkers in renal cell carcinoma (RCC).

Results: 12 coding genes and one miRNA were finally identified as prognostic biomarkers. All of them were related to a poor prognosis. Lower expression levels of the coding genes were observed in higher clinical stages. Prognostic signatures including 7 biomarkers were identified. Patients in the high-risk group had worse survival than those in the low-risk group. The areas under the curves in different years indicated that it was a valuable signature in prognosis. It was found that elevated WDR72 inhibited the survival and invasion of 786-O and 769P cells in vitro.

Conclusions: Thirteen prognostic biomarkers of RCC were identified. Among them, 7 biomarkers comprised a signature to evaluate the RCC prognosis. WDR72 was a cancer suppressor and a potential therapeutic target in RCC.

Methods: Differentially expressed genes/miRNAs (DEGs/DEMs) and prognosis-related genes/miRNAs were acquired from public database. Prognostic biomarkers were identified by overlapping the significant DEGs/DEMs and prognosis-related genes/miRNAs. The associations between these biomarkers and the clinical stages were analyzed. All of these prognostic biomarkers were further investigated with multi-variable Cox regression. Finally, the inhibitory effect of WDR72 on the growth and invasion of RCC cells was studied.

Keywords: DFS; OS; WDR72; prognostic signature; renal cell carcinoma.

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Conflict of interest statement

CONFLICTS OF INTEREST: All authors contributing to this work declare that they have no conflicts of interest.

Figures

Figure 1
Figure 1
DEGs/DEMs and prognosis-related genes/miRNAs identification in different datasets and databases. (A) A standardized procedure for the identification of prognostic biomarkers; (B) Volcano plot of DEGs from GSE105288; (C) Volcano plot of DEMs from GSE116251; (D) Intersection of the upregulated genes and (E) downregulated genes from the GSE105288 dataset and the GEPIA2 database; (F) Intersection of 49 prognostic miRNAs from the Oncolnc database and 7 DEMs from the GSE116251 dataset.
Figure 2
Figure 2
Results of DEGs for the GO and KEGG pathway analysis. (A) The enriched GO biological processes and (B) KEGG pathways of the significant upregulated DEGs; (C) The enriched GO biological processes and (D) the KEGG pathways of significant downregulated DEGs.
Figure 3
Figure 3
Expressionss of the prognostic biomarkers and their coexpression in RCC. (A) The 12 coding genes were downregulated and (B) hsa-miR-21-5p was upregulated in tumor samples compared with normal samples; (C) Showing the coexpression of prognostic coding genes and hsa-miR-21-5p in RCC, among which 11 coding genes (WDR72, ALDH6A1, CDS1, SLC25A4, MTURN, ERBB2, NR3C2, OGDHL, BSPRY, HADH, DNASE1L3) were negatively related to the expression of hsa-miR-21-5p. CLDN10 was the only gene with a P value over 0.05.
Figure 4
Figure 4
Kaplan-Meier curves of OS and DFS of 12 prognostic coding genes. Lower expression of all 12 coding genes was relevant to both unfavorable OS (A) and worse DFS (B) in patients with RCC.
Figure 5
Figure 5
The association of the prognostic biomarkers and clinical stages. Lower levels of the 12 coding genes were observed in higher clinical stages. However, the level of hsa-miR-21-5p was elevated in higher clinical stages.
Figure 6
Figure 6
OS of the signature with multiple genes in RCC. (A) Patients were classified by risk score and their survival status; (B) OS of the signature of multiple genes in this model, which indicated that patients in the low-risk group had a more favorable OS than those in the high-risk group. (C) ROC curves suggested that the accuracy of this model was 76.6%, 71.6% and 72.9% at 1, 3 and 5 years, respectively.
Figure 7
Figure 7
DFS of the signature with multiple genes in RCC. (A) Patients were classified by risk score and their survival status; (B) DFS of the signature of multiple genes in this model, which indicated that patients in the low-risk group had a better DFS than those in the high-risk group. (C) ROC curves suggested that the accuracy of this model was 74.3%, 74.7% and 77.4% at 1, 3 and 5 years, respectively.
Figure 8
Figure 8
Role of WDR72 overexpression in cell survival and invasion of RCC. (A) The results of western blot showed that WDR72 was successfully overexpressed in 769-P and 786-O cells; overexpression of WDR72 remarkably decreased the survival (B) and invasiveness (C) of 769-P and 786-O cells.
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