Abstract
Background: Abnormal epigenetic alterations can contribute to the development of human malignancies. Identification of these alterations for early screening and prognosis of clear cell renal cell carcinoma (ccRCC) has been a highly sought-after goal. Bioinformatic analysis of DNA methylation data provides broad prospects for discovery of epigenetic biomarkers. However, there is short of exploration of methylation-driven genes of ccRCC.Methods: Gene expression data and DNA methylation data in metastatic ccRCC were sourced from the Gene Expression Omnibus (GEO) database. Differentially methylated genes (DMGs) at 5′-C-phosphate-G- 3′ (CpG) sites and differentially expressed genes (DEGs) were screened and the overlapping genes in DMGs and DEGs were then subject to gene set enrichment analysis. Next, the weighted gene co-expression network analysis (WGCNA) was used to search hub DMGs associated with ccRCC. Cox regression and ROC analyses were performed to screen potential biomarkers and develop a prognostic model based on the screened hub genes.Results: Three hundred and fourteen overlapping DMGs were obtained from two independent GEO datasets. The turquoise module contained 79 hub DMGs, which represent the most significant module screened by WGCNA. Furthermore, a total of 12 hub genes (CETN3, DCAF7, GPX4, HNRNPA0, NUP54, SERPINB1, STARD5, TRIM52, C4orf3, C12orf51, and C17orf65) were identified in the TCGA database by multivariate Cox regression analyses. All the 12 genes were then used to generate the model for diagnosis and prognosis of ccRCC. ROC analysis showed that these genes exhibited good diagnostic efficiency for metastatic and non-metastatic ccRCC. Furthermore, the prognostic model with the 12 methylation-driven genes demonstrated a good prediction of 5-year survival rates for ccRCC patients.Conclusion: Integrative analysis of DNA methylation data identified 12 signature genes, which could be used as epigenetic biomarkers for prognosis of metastatic ccRCC. This prognostic model has a good prediction of 5-year survival for ccRCC patients.
Highlights
Abnormal epigenetic alterations can contribute to the development of human malignancies
All the relevant clinical data were collected from the GEO datasets: GSE113501 and GSE105260
Gene ontology (GO) analysis showed that 552 DMGs were linked to the biological pathways that involved in transcriptional regulation of cancers, cell cycle and metabolism, such as bladder cancer (Supplementary Table 5)
Summary
Abnormal epigenetic alterations can contribute to the development of human malignancies. Identification of these alterations for early screening and prognosis of clear cell renal cell carcinoma (ccRCC) has been a highly sought-after goal. Many patients with ccRCC have distant metastasis to lymphoid or other organs [2]. The therapeutic strategies for advanced ccRCC have evolved rapidly from a nonspecific immune approach to targeted therapy against vascular endothelial growth factor (VEGF), and recently to novel immunotherapy. Multiple agents like immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs) show promising results in the clinical trials and have been approved as the second-line even the first-line treatment for advanced ccRCC [4,5,6,7]. Targeted combination therapies have been explored as the first-line treatment in pioneer trials [8]
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