ArticleFrontiers in cell and developmental biology2022
Identification of a Methylation-Regulating Genes Prognostic Signature to Predict the Prognosis and Aid Immunotherapy of Clear Cell Renal Cell Carcinoma.
Article in Frontiers in cell and developmental biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- Unveiling the epigenetic landscape: transforming renal cell carcinoma treatment.Clinical epigenetics · 2026Review
- Machine learning-based integration of tumor deposit molecular signatures improves prognostic stratification in colon adenocarcinoma.International journal of colorectal disease · 2026Article
- Construction of a novel G2/M checkpoint-related gene signature for prognosis in hepatocellular carcinoma based on machine learning.Discover oncology · 2025Article
- Review
- Novel prognostic signature for hepatocellular carcinoma using a comprehensive machine learning framework to predict prognosis and guide treatment.Frontiers in immunology · 2024Article
- Article
- Analysis of Pyroptosis-Related Immune Signatures and Identification of Pyroptosis-Related LncRNA Prognostic Signature in Clear Cell Renal Cell Carcinoma.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Methylation is one of the most extensive modifications of biological macromolecules and affects cell-fate determination, development, aging, and cancer. Several methylation modifications, including 5-methylcytosine and N6-methyladenosine, play an essential role in many cancers. However, little is known about the relationship between methylation and the prognosis of clear cell renal cell carcinoma (ccRCC). Here, we established a methylation-regulating genes prognostic signature (MRGPS) to predict the prognoses of ccRCC patients. We obtained ccRCC samples from The Cancer Genome Atlas and identified methylation-regulatingd genes (MRGs) from the Gene Set Enrichment Analysis database. We also determined differentially expressed genes (DEGs) and performed cluster analysis to identify candidate genes. Subsequently, we established and validated an MRGPS to predict the overall survival of ccRCC patients. This was also verified in 15 ccRCC samples collected from the Fujian Provincial Hospital via quantitative real-time transcription (qRT-PCR). While 95 MRGs were differentially expressed (DEGs1) between tumor and normal tissues, 17 MRGs were differentially expressed (DEGs2) between cluster 1 and 2. Notably, 13 genes common among DEGs1 and DEGs2 were identified as hub genes. In fact, we established three genes (
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