Abstract
BackgroundAberrant DNA methylation patterns are involved in the pathogenesis of papillary renal cell carcinoma (pRCC). This study aimed to investigate the potential of methylation-driven genes as biomarkers in determining the prognosis of pRCC by bioinformatics analysis.MethodsDNA methylation and transcriptome profiling data were downloaded from The Cancer Genome Atlas database. Methylation-driven genes (MDGs) were obtained using MethylMix R package. A Cox regression model was used to screen for pRCC prognosis-related MDGs, and a linear risk model based on MDG methylation profiles was constructed. A combined methylation and gene expression survival analysis was performed to further explore the prognostic value of MDGs independently.ResultsA total of 31 MDGs were obtained. Univariate and multivariate Cox regression analysis identified eight genes (CASP1, CD68, HOXD3, HHLA2, HOXD9, HOXA10-AS, TMEM71, and PLA2G16), which were used to construct a predictive model associated with overall survival in pRCC patients. Combined DNA methylation and gene expression survival analysis revealed that C19orf33, GGT6, GIPC2, HHLA2, HOXD3, HSD17B14, PLA2G16, and TMEM71 were significantly associated with patients’ survival.ConclusionThrough the analysis of MDGs in pRCC, this study identified potential biomarkers for precision treatment and prognosis prediction, and provided the basis for future research into the molecular mechanism of pRCC.
Highlights
Aberrant DNA methylation patterns are involved in the pathogenesis of papillary renal cell carcinoma
Some previous studies have explored the relationships between methylationdriven genes and the prognosis of certain cancers, such as esophageal squamous cell carcinoma [14], lung adenocarcinoma [15], and bladder cancer [16], but currently, there is no such report for papillary renal cell carcinoma (pRCC)
The results show that a risk model consisting of eight methylation-driven genes can effectively predict the prognosis of patients with pRCC
Summary
Aberrant DNA methylation patterns are involved in the pathogenesis of papillary renal cell carcinoma (pRCC). This study aimed to investigate the potential of methylation-driven genes as biomarkers in determining the prognosis of pRCC by bioinformatics analysis. Renal cell carcinoma (RCC), a common malignant tumor in the urinary system, accounts for 2–3% of human cancers [1]. Papillary renal cell carcinoma (pRCC) represents the second most common pathological subtype of RCC, accounting for 18.5% [2, 3]. Methylation, one of the most important epigenetic modifications, is involved in many cellular processes, including cell differentiation, genome stability, and gene imprinting [12], and it intimately relates with tumorigenesis [13]. Changes in DNA methylation can provide important evidence for the early diagnosis and prognosis of cancer, and offer new ideas for further clinical applications. Some previous studies have explored the relationships between methylationdriven genes and the prognosis of certain cancers, such as esophageal squamous cell carcinoma [14], lung adenocarcinoma [15], and bladder cancer [16], but currently, there is no such report for pRCC
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