Evidence map›Paper›PMID 41572384›Full record

ArticleClinical epigenetics2026

Epigenomic subtypes and prognostic methylation signatures in clear cell renal cell carcinoma.

Laura Iisager, Cecilie Lindgaard, Johanne Ahrenfeldt, Jesper Jespersen, Karoline Kondrup, Laura Zanini, Anna K Keller, Line Raaby, Mie G Thorlund, Karina D Sørensen and 2 more

Abstract read
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Article in Clinical epigenetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Laura IisagerDepartment of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark.
Cecilie LindgaardDepartment of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark.
Johanne AhrenfeldtDepartment of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark.
Jesper JespersenDepartment of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark.
Karoline KondrupDepartment of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark.
Laura ZaniniDepartment of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark.
Anna K KellerDepartment of Clinical Medicine, Aarhus University, Aarhus, Denmark.
Line RaabyDepartment of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark.
Mie G ThorlundDepartment of Urology, Odense University Hospital, Odense, Denmark.
Karina D SørensenDepartment of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark.
Niels FristrupDepartment of Clinical Medicine, Aarhus University, Aarhus, Denmark.
Iben LyskjærDepartment of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark. iben.lyskjar@clin.au.dk.

Funding

Danmarks Frie Forskningsfond 2100-00017BKræftens Bekæmpelse R413-2022-606Lundbeck Foundation R413-2022-606
6 · The paper itself

Abstract

backgroundClear cell renal cell carcinoma (ccRCC) is characterized by marked epigenetic dysregulation, contributing to aberrant gene expression and tumor progression. To expand current knowledge on genome-wide methylation patterns in ccRCC, we performed Methylated DNA Immunoprecipitation sequencing (MeDIP-seq) on tumor samples from 116 ccRCC patients and 34 adjacent normal renal tissues. We identified differentially methylated regions (DMRs) and integrated these findings with genome-wide copy number alterations.

resultsccRCC tumors exhibited global hypomethylation combined with focal hypermethylation, particularly within intergenic and repetitive genomic regions. Unsupervised clustering revealed three distinct subtypes, including one subtype characterized by chromosomal instability, synchronous metastasis, and poor survival outcomes. We developed a novel methylation score (MethScore), based on hypermethylated regions, which strongly correlated with disease stage and independently predicted overall survival beyond age and clinical stage. Notably, high methylation levels of specific DMRs were linked to recurrence and advanced disease. Validation with TCGA Kidney Renal Clear Cell Carcinoma methylation data supported the prognostic value of these hypermethylated regions. Additionally, MeDIP-seq accurately detected critical copy number alterations, particularly chromosome 3p loss, which were found in 88% of tumors.

conclusionsTogether, our findings demonstrate that genome-wide methylation profiling can resolve clinically relevant ccRCC subtypes, uncover novel biomarkers of disease aggressiveness, and improve patient risk stratification beyond current clinical models.

Indexed as

Carcinoma, Renal CellDNA MethylationEpigenomeKidney NeoplasmsAgedBiological Specimen BanksBiomarkers, TumorDenmarkDNA Copy Number VariationsEpigenomicsFemaleGene Expression Regulation, NeoplasticHumansMaleMiddle AgedNeoplasm StagingBiomarkers, TumorBiomarkerClear cell renal cell carcinomaDNA methylationEpigenomicsMeDIP-seq

Identifiers

PMID41572384
PMCPMC12908367

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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.