SynthesisClinical epigenetics2021
Development of a prognostic risk model for clear cell renal cell carcinoma by systematic evaluation of DNA methylation markers.
Synthesis in Clinical epigenetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.
- Renal cell carcinoma detection: a systematic review in diagnostic urinary biomarkers.BMC cancer · 2025Pooled it
- Unveiling the epigenetic landscape: transforming renal cell carcinoma treatment.Clinical epigenetics · 2026Review
- Development of a prognostic risk model for clear cell renal cell carcinoma by systematic evaluation of DNA methylation markers: an update after ISUP/WHO 2022 classification.The journal of pathology. Clinical research · 2025Article
- Article
- Clinical promise and applications of epigenetic biomarkers.Clinical epigenetics · 2024Article
- Article
- The biology of SCUBE.Journal of biomedical science · 2023Review
- Histologic re‑evaluation of a population‑based series of renal cell carcinomas from The Netherlands Cohort Study according to the 2022 ISUP/WHO classification.Oncology letters · 2023Article
- Article
- Biomarkers in renal cell carcinoma and their targeted therapies: a review.Exploration of targeted anti-tumor therapy · 2023Review
- To re-examine the intersection of microglial activation and neuroinflammation in neurodegenerative diseases from the perspective of pyroptosis.Frontiers in aging neuroscience · 2023Review
- Identification of a Novel Renal Metastasis Associated CpG-Based DNA Methylation Signature (RMAMS).International journal of molecular sciences · 2022Article
- Technical considerations in PCR-based assay design for diagnostic DNA methylation cancer biomarkers.Clinical epigenetics · 2022Article
- DNA Methylation inCancers · 2021Article
- Article
- Identification of a Somatic Mutation-Derived Long Non-Coding RNA Signatures of Genomic Instability in Renal Cell Carcinoma.Frontiers in oncology · 2021Article
Corrections and comments
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Authors and funding
13 authors at 3 institutions in 3 countries.
Funding
Abstract
backgroundCurrent risk models for renal cell carcinoma (RCC) based on clinicopathological factors are sub-optimal in accurately identifying high-risk patients. Here, we perform a head-to-head comparison of previously published DNA methylation markers and propose a potential prognostic model for clear cell RCC (ccRCC). PATIENTS AND
methodsPromoter methylation of PCDH8, BNC1, SCUBE3, GREM1, LAD1, NEFH, RASSF1A, GATA5, SFRP1, CDO1, and NEURL was determined by nested methylation-specific PCR. To identify clinically relevant methylated regions, The Cancer Genome Atlas (TCGA) was used to guide primer design. Formalin-fixed paraffin-embedded (FFPE) tissue samples from 336 non-metastatic ccRCC patients from the prospective Netherlands Cohort Study (NLCS) were used to develop a Cox proportional hazards model using stepwise backward elimination and bootstrapping to correct for optimism. For validation purposes, FFPE ccRCC tissue of 64 patients from the University Hospitals Leuven and a series of 232 cases from The Cancer Genome Atlas (TCGA) were used.
resultsMethylation of GREM1, GATA5, LAD1, NEFH, NEURL, and SFRP1 was associated with poor ccRCC-specific survival, independent of age, sex, tumor size, TNM stage or tumor grade. Moreover, the association between GREM1, NEFH, and NEURL methylation and outcome was shown to be dependent on the genomic region. A prognostic biomarker model containing GREM1, GATA5, LAD1, NEFH and NEURL methylation in combination with clinicopathological characteristics, performed better compared to the model with clinicopathological characteristics only (clinical model), in both the NLCS and the validation population with a c-statistic of 0.71 versus 0.65 and a c-statistic of 0.95 versus 0.86 consecutively. However, the biomarker model had limited added prognostic value in the TCGA series with a c-statistic of 0.76 versus 0.75 for the clinical model.
conclusionIn this study we performed a head-to-head comparison of potential prognostic methylation markers for ccRCC using a novel approach to guide primers design which utilizes the optimal location for measuring DNA methylation. Using this approach, we identified five methylation markers that potentially show prognostic value in addition to currently known clinicopathological factors.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.