A large‐scale transcriptome analysis identified ELANE and PRTN3 as novel methylation prognostic signatures for clear cell renal cell carcinoma

• Published in: Journal of cellular physiology Vol. 235; no. 3; pp. 2582 - 2589
• Main Authors: Wei, Zhongheng, Wu, Bo, Wang, Li, Zhang, Juan
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.03.2020
• Subjects: Biomarkers; Cancer; Carcinoma, Renal Cell - genetics; Carcinoma, Renal Cell - pathology; clear cell renal cell carcinoma; Clear cell-type renal cell carcinoma; CpG islands; Datasets; Deoxyribonucleic acid; Disease-Free Survival; DNA; DNA methylation; DNA Methylation - genetics; ELANE; Female; Gene expression; Gene Expression Profiling - methods; Gene Expression Regulation, Neoplastic - genetics; Humans; Kidney cancer; Leukocyte Elastase - genetics; Male; Medical prognosis; Metastases; methylation; Middle Aged; Myeloblastin - genetics; Network analysis; Prognosis; Protein interaction; Proteins; PRTN3; Ribonucleic acid; RNA; Search algorithms; Survival; Transcriptome - genetics; PRTN3; clear cell renal cell carcinoma; prognosis; methylation; ELANE
• ISSN: 0021-9541; 1097-4652; 1097-4652
• DOI: 10.1002/jcp.29162

DNA methylation was involved in the progress of many types of cancer including clear cell renal cell carcinomas (ccRCCs). This study aimed to identify the prognostic DNA methylation biomarkers for the ccRCCs by a large‐scale RNA‐seq analysis. The DNA methylation data and the corresponding clinical information of the patients with ccRCCs were extracted from TCGA database and randomly divided into the training group and the validation group. The differentially expressed CpG sites and the survival‐related CpG sites were further identified, which was combined into CpG sites pair and followed by screening the survival‐related pairs. The C‐index and the forward search algorithms were constructed to identify the prognostic signatures for the patients with ccRCCs. The prognostic signatures were verified by the validation dataset and the protein–protein interactions (PPI) network analysis was performed on the CPG sites of the signature. A total of 9,861 differentially expressed CPG sites were identified and 567 CpG sites were found to relate to the overall survival (OS) of the patients with ccRCCs. Besides, 1,146 CPG sites pairs were found to be related to the OS of the ccRCCs samples and the signature composed of seven CpG sites pairs were obtained to predict the prognosis of patients with ccRCCs and the results were verified in the validation dataset. Besides, the PPI network analysis showed that ELANE and PRTN3 gene may be associated with the invasion and metastasis of ccRCCs and could function as potential prognostic and therapeutic signatures for ccRCCs. This study identified ELANE and PRTN3 as novel methylation prognostic signatures for clear cell renal cell carcinoma.