ArticlePloS one2010
Array-based DNA methylation profiling for breast cancer subtype discrimination.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 1 of them a synthesis that pooled it.
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Who cites it
50 citing papers in PubMed, 1 synthesis or guideline pooled it, 101 citations in OpenAlex.
- Integrative DNA methylation and gene expression analysis to assess the universality of the CpG island methylator phenotype.Human genomics · 2015Pooled it
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- Expression of G-quadruplex coordinates BRCA1, CDH1, and RASSF1 via DNA methylation in mouse breast cancer cells.Epigenomics · 2025Article
- Breast cancer metastasis progression is associated with elevated activity of kynurenine monooxygenase and kynureninase.British journal of cancer · 2024Article
- Development and validation of prognostic signatures of NAD+ metabolism and immune-related genes in colorectal cancer.Heliyon · 2024Article
- DNA methylation profile of inflammatory breast cancer and its impact on prognosis and outcome.Clinical epigenetics · 2024Article
- Mutational landscape of inflammatory breast cancer.Journal of translational medicine · 2024Article
- A Bayesian model for identifying cancer subtypes from paired methylation profiles.Briefings in bioinformatics · 2023Article
- Recent advances in understanding DNA methylation of prostate cancer.Frontiers in oncology · 2023Review
- PAIP1 is a novel oncogene in human hepatocellular carcinoma.Discover oncology · 2022Article
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- DNMT3A and DNMT3B in Breast Tumorigenesis and Potential Therapy.Frontiers in cell and developmental biology · 2022Review
- High endogenous CCL2 expression promotes the aggressive phenotype of human inflammatory breast cancer.Nature communications · 2021Article
- Hemoglobin overexpression and splice signature as new features of inflammatory breast cancer?Journal of advanced research · 2021Article
- miRNome and Functional Network Analysis of PGRMC1 Regulated miRNA Target Genes Identify Pathways and Biological Functions Associated With Triple Negative Breast Cancer.Frontiers in oncology · 2021Article
- Epigenetics in Inflammatory Breast Cancer: Biological Features and Therapeutic Perspectives.Cells · 2020Review
- Identification of novel biomarkers affecting the metastasis of colorectal cancer through bioinformatics analysis and validation through qRT-PCR.Cancer cell international · 2020Article
- Genomic region detection via Spatial Convex Clustering.PloS one · 2018Article
- miR‑342‑5p promotes Zmpste24‑deficient mouse embryonic fibroblasts proliferation by suppressing GAS2.Molecular medicine reports · 2017Article
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAbnormal DNA methylation is well established for breast cancer and contributes to its progression by silencing tumor suppressor genes. DNA methylation profiling platforms might provide an alternative approach to expression microarrays for accurate breast tumor subtyping. We sought to determine whether the distinction of the inflammatory breast cancer (IBC) phenotype from the non-IBC phenotype by transcriptomics could be sustained by methylomics. METHODOLOGY/PRINCIPAL
findingsWe performed methylation profiling on a cohort of IBC (N = 19) and non-IBC (N = 43) samples using the Illumina Infinium Methylation Assay. These results were correlated with gene expression profiles. Methylation values allowed separation of breast tumor samples into high and low methylation groups. This separation was significantly related to DNMT3B mRNA levels. The high methylation group was enriched for breast tumor samples from patients with distant metastasis and poor prognosis, as predicted by the 70-gene prognostic signature. Furthermore, this tumor group tended to be enriched for IBC samples (54% vs. 24%) and samples with a high genomic grade index (67% vs. 38%). A set of 16 CpG loci (14 genes) correctly classified 97% of samples into the low or high methylation group. Differentially methylated genes appeared to be mainly related to focal adhesion, cytokine-cytokine receptor interactions, Wnt signaling pathway, chemokine signaling pathways and metabolic processes. Comparison of IBC with non-IBC led to the identification of only four differentially methylated genes (TJP3, MOGAT2, NTSR2 and AGT). A significant correlation between methylation values and gene expression was shown for 4,981 of 6,605 (75%) genes. CONCLUSIONS/SIGNIFICANCE: A subset of clinical samples of breast cancer was characterized by high methylation levels, which coincided with increased DNMT3B expression. Furthermore, an association was observed with molecular signatures indicative of poor patient prognosis. The results of the current study also suggest that aberrant DNA methylation is not the main force driving the molecular biology of IBC.
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