ArticlePloS one2015
The identification of specific methylation patterns across different cancers.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed, 58 citations in OpenAlex.
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- Downregulation of SALL1 and its association with poor prognosis and the immune cell landscape in clear cell renal cell carcinoma.Frontiers in oncology · 2025Article
- Comprehensive in silico CpG methylation analysis in hepatocellular carcinoma identifies tissue- and tumor-type specific marks disconnected from gene expression.Journal of physiology and biochemistry · 2024Article
- The Role of Methylation in Chronic Lymphocytic Leukemia and Its Prognostic and Therapeutic Impacts in the Disease: A Systematic Review.Advances in hematology · 2024Review
- DNA hypomethylation mediates immune response in pan-cancer.Epigenetics · 2023Article
- In Silico Gene Prioritization Highlights the Significance of Bone Morphogenetic Protein 4 (International journal of molecular sciences · 2023Article
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- Consistent DNA Hypomethylations in Prostate Cancer.International journal of molecular sciences · 2022Article
- Epigenetically regulated PCDHB15 impairs aggressiveness of metastatic melanoma cells.Clinical epigenetics · 2022Article
- DNA Methylation of HOXA11 Gene as Prognostic Molecular Marker in Human Gastric Adenocarcinoma.Diagnostics (Basel, Switzerland) · 2022Article
- Methylated DNA markers for plasma detection of ovarian cancer: Discovery, validation, and clinical feasibility.Gynecologic oncology · 2022Article
- PCDHB15 as a potential tumor suppressor and epigenetic biomarker for breast cancer.Oncology letters · 2022Article
- SALL Proteins; Common and Antagonistic Roles in Cancer.Cancers · 2021Review
- Charting differentially methylated regions in cancer with Rocker-meth.Communications biology · 2021Article
- Article
- Different methylation signatures at diagnosis in patients with high-risk myelodysplastic syndromes and secondary acute myeloid leukemia predict azacitidine response and longer survival.Clinical epigenetics · 2021Article
- Bayesian Gene Selection Based on Pathway Information and Network-Constrained Regularization.Computational and mathematical methods in medicine · 2021Article
- Blood-Based Detection of Colorectal Cancer Using Cancer-Specific DNA Methylation Markers.Diagnostics (Basel, Switzerland) · 2020Article
- Review
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Abnormal DNA methylation is known as playing an important role in the tumorgenesis. It is helpful for distinguishing the specificity of diagnosis and therapeutic targets for cancers based on characteristics of DNA methylation patterns across cancers. High throughput DNA methylation analysis provides the possibility to comprehensively filter the epigenetics diversity across various cancers. We integrated whole-genome methylation data detected in 798 samples from seven cancers. The hierarchical clustering revealed the existence of cancer-specific methylation pattern. Then we identified 331 differentially methylated genes across these cancers, most of which (266) were specifically differential methylation in unique cancer. A DNA methylation correlation network (DMCN) was built based on the methylation correlation between these genes. It was shown the hubs in the DMCN were inclined to cancer-specific genes in seven cancers. Further survival analysis using the part of genes in the DMCN revealed high-risk group and low-risk group were distinguished by seven biomarkers (PCDHB15, WBSCR17, IGF1, GYPC, CYGB, ACTG2, and PRRT1) in breast cancer and eight biomarkers (ZBTB32, OR51B4, CCL8, TMEFF2, SALL3, GPSM1, MAGEA8, and SALL1) in colon cancer, respectively. At last, a protein-protein interaction network was introduced to verify the biological function of differentially methylated genes. It was shown that MAP3K14, PTN, ACVR1 and HCK sharing different DNA methylation and gene expression across cancers were relatively high degree distribution in PPI network. The study suggested that not only the identified cancer-specific genes provided reference for individual treatment but also the relationship across cancers could be explained by differential DNA methylation.
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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.