Identification of methylation‐driven genes related to prognosis in clear‐cell renal cell carcinoma

Abstract

With the participation of the existing treatment methods, the prognosis of advanced clear‐cell renal cell carcinoma (ccRCC) is poor. More evidence indicates the presence of methylation in ccRCC cancer cells, but there is a lack of studies on methylation‐driven genes in ccRCC. We analyzed the open data of ccRCC in The Cancer Genome Atlas database to obtain ccRCC‐related methylation‐driven genes, and then carried out pathway enrichment, survival, and joint survival analyses. More important, we deeply explored the correlation between differential methylation sites and the expression of these driving genes. Finally, we screened 29 methylation‐driven genes via MethylMix, of which six were significantly associated with the survival of ccRCC patients. This study demonstrated that the effect of hypermethylation or hypomethylation on prognosis is different, and the level of methylation of key methylation sites is associated with gene expression. We identified methylation‐driven genes independently predicting prognosis in ccRCC, which offers theoretical support in bioinformatics for the study of methylation in ccRCC and a new perspective for the epigenetic study of ccRCC.

Novel prognostic prediction model constructed through machine learning on the basis of methylation-driven genes in kidney renal clear cell carcinoma

“…We have used the negative correlation between the gene methylation level and expression value to select methylation-driven genes via the R package MethylMix, a generally accepted method [ 21 , 22 ]. Otherwise, establishing the corresponding relationship between methylation and expression value is difficult.…”

Construction and Validation of a Prognostic Nomogram for Clear Cell Renal Cell Carcinoma Based on DNA Methylation-driven Differentially Expressed Genes

“…However, these studies focused on a single gene or only used DNAm data. (Wang et al 2020) We combined DNAm data with transcriptome data through various statistical algorithms and selected the ve genes that were most relevant to prognosis. On this basis, we rst developed and validated a prognostic risk model based on the DNAm signature, and an OS nomogram was constructed to predict the prognosis of ccRCC patients by integrating age, histologic grade, pathological stage, and risk level (divided by the risk score) in the model.…”

“…DNA methylation (DNAm) has been shown to be associated with the occurrence and development of tumors. (Lo and Huang 2002) Although the relationship between abnormal DNAm and ccRCC occurrence has been studied (Wang et al 2020) (Yin et al 2020), there have been few reports on prognostic models based on DNAm genes.…”

The Landscape of Iron Metabolism-Related and Methylated Genes in the Prognosis Prediction of Clear Cell Renal Cell Carcinoma

“…The incidence of RCC has been increasing in the recent decades, which accounts for 3% of all adult malignancies and ranks the 13th most common malignancy diagnosed worldwide annually. RCC originates from renal epithelial cells (1), and nearly 70-80% cases of RCC is ccRCC pathologic subtype (2). Late diagnosis is a major obstacle to improving ccRCC outcomes, with the fact of about 33% of ccRCC patients initially diagnosed as advanced stage and 40% of those will eventually have distant metastasis.…”