ArticleMolecular oncology2018
Specific breast cancer prognosis-subtype distinctions based on DNA methylation patterns.
Article in Molecular oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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Who cites it
53 citing papers in PubMed.
- Can DNA Methylation in Peritumoral and Contralateral Breast Tissue Predict Recurrence or Second Breast Cancers?Current issues in molecular biology · 2026Article
- BRCA1/2 methylation and expression dynamics in hereditary breast and ovarian cancer: insights from gene, protein, and TCGA analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- A review of the use of tumour DNA methylation for breast cancer subtyping and prediction of outcomes.Clinical epigenetics · 2025Review
- Evaluation of agreement between common clustering strategies for DNA methylation-based subtyping of breast tumours.Epigenomics · 2025Article
- Development and validation of a 14-CpG DNA methylation signature and drug targets for prognostic prediction in breast cancer.Frontiers in medicine · 2025Article
- A review on trends in development and translation of omics signatures in cancer.Computational and structural biotechnology journal · 2024Review
- Integrative analysis of homologous recombination repair patterns unveils prognostic signatures and immunotherapeutic insights in breast cancer.Journal of applied genetics · 2024Article
- Genome-wide analyses reveal the regulatory roles of DNA methylation-regulated alternative promoter transcripts in breast cancer.Human genetics · 2024Article
- Abnormal methylation of HOXA11 promoter promotes tumor progression in testicular germ cell tumor.American journal of translational research · 2024Article
- SLC31A1 Identifying a Novel Biomarker with Potential Prognostic and Immunotherapeutic Potential in Pan-Cancer.Biomedicines · 2023Article
- A First Computational Frame for Recognizing Heparin-Binding Protein.Diagnostics (Basel, Switzerland) · 2023Article
- Recall DNA methylation levels at low coverage sites using a CNN model in WGBS.PLoS computational biology · 2023Article
- Bioinformatics analysis based on DNA methylation data identified in lung adenocarcinoma subgroups with different immune characteristics and clinical outcomes.Journal of thoracic disease · 2023Article
- Computational prediction of promotors inFrontiers in microbiology · 2023Article
- Classification of Subgroups with Immune Characteristics Based on DNA Methylation in Luminal Breast Cancer.International journal of molecular sciences · 2022Article
- Article
- Identification of cervical squamous cell carcinoma feature genes and construction of a prognostic model based on immune-related features.BMC women's health · 2022Article
- DNA methylation changes in response to neoadjuvant chemotherapy are associated with breast cancer survival.Breast cancer research : BCR · 2022Article
- miR-142-5p Inhibits Cell Invasion and Migration by Targeting DNMT1 in Breast Cancer.Oncology research · 2022Article
- A Novel Five-Gene Signature Related to Clinical Outcome and Immune Microenvironment in Breast Cancer.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumour heterogeneity is an obstacle to effective breast cancer diagnosis and therapy. DNA methylation is an important regulator of gene expression, thus characterizing tumour heterogeneity by epigenetic features can be clinically informative. In this study, we explored specific prognosis-subtypes based on DNA methylation status using 669 breast cancers from the TCGA database. Nine subgroups were distinguished by consensus clustering using 3869 CpGs that significantly influenced survival. The specific DNA methylation patterns were reflected by different races, ages, tumour stages, receptor status, histological types, metastasis status and prognosis. Compared with the PAM50 subtypes, which use gene expression clustering, DNA methylation subtypes were more elaborate and classified the Basal-like subtype into two different prognosis-subgroups. Additionally, 1252 CpGs (corresponding to 888 genes) were identified as specific hyper/hypomethylation sites for each specific subgroup. Finally, a prognosis model based on Bayesian network classification was constructed and used to classify the test set into DNA methylation subgroups, which corresponded to the classification results of the train set. These specific classifications by DNA methylation can explain the heterogeneity of previous molecular subgroups in breast cancer and will help in the development of personalized treatments for the new specific subtypes.
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