Evidence map›Paper›PMID 40452146›Full record

ArticleBriefings in bioinformatics2025

Simulation-guided pan-cancer analysis identifies a novel regulator of CpG island hypermethylation heterogeneity.

Xianglin Zhang, Wei Zhang, Jinyi Zhang, Xiuhong Lyu, Haoran Pan, Tianwei Jia, Ting Wang, Xiaowo Wang, Haiyang Guo

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2025. 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

9 authors.

Xianglin ZhangDepartment of Clinical Laboratory, the Second Hospital, Cheeloo College of Medicine, Shandong University, 247 Beiyuan Street, Tianqiao District, Jinan, 250033, Shandong, China.
Wei ZhangCenter of Intelligent Medicine, School of Control Science and Engineering, Shandong University, 17923 Jingshi Road, Lixia District, Jinan, 250061, Shandong, China.
Jinyi ZhangDepartment of Clinical Laboratory, the Second Hospital, Cheeloo College of Medicine, Shandong University, 247 Beiyuan Street, Tianqiao District, Jinan, 250033, Shandong, China.
Xiuhong LyuDepartment of Emergency Medical Center, the Second Hospital, Cheeloo College of Medicine, Shandong University, 247 Beiyuan Street, Tianqiao District, Jinan, 250033, Shandong, China.
Haoran PanDepartment of Clinical Laboratory, the Second Hospital, Cheeloo College of Medicine, Shandong University, 247 Beiyuan Street, Tianqiao District, Jinan, 250033, Shandong, China.
Tianwei JiaDepartment of Clinical Laboratory, the Second Hospital, Cheeloo College of Medicine, Shandong University, 247 Beiyuan Street, Tianqiao District, Jinan, 250033, Shandong, China.
Ting WangDepartment of Genetics, The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, 4515 McKinley Avenue, St. Louis, MO 63110, United States.
Xiaowo WangMinistry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, No 1 Qinghuayuan Street, Haidian District, Beijing 100084, China.
Haiyang GuoDepartment of Clinical Laboratory, the Second Hospital, Cheeloo College of Medicine, Shandong University, 247 Beiyuan Street, Tianqiao District, Jinan, 250033, Shandong, China.

Funding

National Key Research and Development Program of China 2019YFA0111400National Natural Science Foundation of China 62303267National Natural Science Foundation of China 82173052Natural Science Foundation of Shandong Province ZR2021YQ49Natural Science Foundation of Shandong Province ZR2023QF099Taishan Scholar Project of Shandong Province tsqn201812136Taishan Scholar Project of Shandong Province tsqn202312340
6 · The paper itself

Abstract

CpG island hypermethylation, a hallmark of cancer, exhibits substantial heterogeneity across tumors, presenting both opportunities and challenges for cancer diagnostics and therapeutics. While this heterogeneity offers potential for patient stratification to predict clinical outcomes and personalize treatments, it complicates the development of robust biomarkers for early detection. Understanding the mechanisms driving this heterogeneity is essential for advancing biomarker design. Here, simulation-based analyses demonstrate that tumor purity and the high prevalence of low epi-mutation samples significantly obscure the identification of negative, rather than positive, regulators of CpG island hypermethylation, limiting a comprehensive understanding of heterogeneity sources. By addressing these confounders, we identify impaired DNA methylation maintenance, as indicated by global hypomethylation levels, as the primary contributor to CpG island hypermethylation variability among known regulators. This finding is supported by integrative analyses of datasets from The Cancer Genome Atlas (TCGA) Pan-Cancer Atlas, Genomics of Drug Sensitivity in Cancer (GDSC1000) cancer cell lines, and epi-allele analyses of two independent whole-genome bisulfite sequencing cohorts, using a newly developed method, MeHist (https://github.com/vhang072/MeHist). Furthermore, we assess widely used hypermethylation biomarkers across ten cancer types and find that 65 out of 246 (26.4%) are significantly influenced by impaired methylation maintenance. Incorporating hypomethylation and hypermethylation markers improves the robustness of cancer detection, as validated across multiple plasma cell-free DNA datasets. In summary, our findings highlight the value of simulation-guided integrative analysis in mitigating confounding effects and identify impaired DNA methylation maintenance as a key regulator of CpG island hypermethylation heterogeneity.

Indexed as

CpG IslandsDNA MethylationGenetic HeterogeneityNeoplasmsBiomarkers, TumorComputer SimulationHumansBiomarkers, TumorCpG island methylator phenotypeDNA methylationheterogeneitynegative association identificationtumor purity

Identifiers

PMID40452146
PMCPMC12127147

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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.