ArticleCancer control : journal of the Moffitt Cancer Center
DNA Methylation Based Molecular Subtypes Predict Prognosis in Breast Cancer Patients.
Article in Cancer control : journal of the Moffitt Cancer Center. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- The Great Potential of DNA Methylation in Triple-Negative Breast Cancer: From Biological Basics to Clinical Application.Biomedicines · 2026Review
- A review of the use of tumour DNA methylation for breast cancer subtyping and prediction of outcomes.Clinical epigenetics · 2025Review
- Methods in DNA methylation array dataset analysis: A review.Computational and structural biotechnology journal · 2024Review
- Role of hypermethylated SLC5A8 in follicular thyroid cancer diagnosis and prognosis prediction.World journal of surgical oncology · 2023Article
- Article
- Epigenetic Mechanisms in Breast Adenocarcinoma: Novel DNA Methylation Patterns.Cancer diagnosis & prognosisReview
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Authors and funding
3 authors.
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Abstract
backgroundEpigenetic changes are tightly linked to tumorigenesis development and malignant transformation' However, DNA methylation occurs earlier and is constant during tumorigenesis. It plays an important role in controlling gene expression in cancer cells.
methodsIn this study, we determining the prognostic value of molecular subtypes based on DNA methylation status in breast cancer samples obtained from The Cancer Genome Atlas database (TCGA).
resultsSeven clusters and 204 corresponding promoter genes were identified based on consensus clustering using 166 CpG sites that significantly influenced survival outcomes. The overall survival (OS) analysis showed a significant prognostic difference among the 7 groups (p<0.05). Finally, a prognostic model was used to estimate the results of patients on the testing set based on the classification findings of a training dataset DNA methylation subgroups.
conclusionsThe model was found to be important in the identification of novel biomarkers and could be of help to patients with different breast cancer subtypes when predicting prognosis, clinical diagnosis and management.
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