scholarly journals Dysregulation of DNA methylation patterns may identify patients with breast cancer resistant to endocrine therapy: A predictive classifier based on differentially methylated regions

2019 ◽  
Author(s):  
Fan Zhang ◽  
Yukun Cui
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Endocrine Therapy ◽  
Differentially Methylated Regions ◽  
Methylation Patterns

scholarly journals DNA Methylation Patterns Can Estimate Nonequivalent Outcomes of Breast Cancer with the Same Receptor Subtypes

PLoS ONE ◽  
2015 ◽  
Vol 10 (11) ◽  
pp. e0142279 ◽  
Author(s):  
Min Zhang ◽  
Shaojun Zhang ◽  
Yanhua Wen ◽  
Yihan Wang ◽  
Yanjun Wei ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Receptor Subtypes ◽  
Methylation Patterns

scholarly journals Co-enzyme Q10, riboflavin and niacin supplementation on alteration of DNA repair enzyme and DNA methylation in breast cancer patients undergoing tamoxifen therapy

2008 ◽  
Vol 100 (6) ◽  
pp. 1179-1182 ◽  
Author(s):  
Vummidi Giridhar Premkumar ◽  
Srinivasan Yuvaraj ◽  
Palanivel Shanthi ◽  
Panchanatham Sachdanandam
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Dna Repair ◽  
Cancer Patients ◽  
Good Prognosis ◽  
Breast Cancer Patients ◽  
Repair Enzymes ◽  
Methylation Patterns ◽  
To Receive ◽  
Supplement Therapy

In the present study, eighty-four breast cancer patients were randomized to receive a daily supplement of 100 mg co-enzyme Q10, 10 mg riboflavin and 50 mg niacin (CoRN), one dosage per d along with 10 mg tamoxifen twice per d. A significant increase in poly(ADP-ribose) polymerase levels and disappearance of RASSF1A DNA methylation patterns were found in patients treated with supplement therapy along with tamoxifen compared to untreated breast cancer patients and tamoxifen alone-treated patients. An increase in DNA repair enzymes and disappearance of DNA methylation patterns attributes to reduction in tumour burden and may suggest good prognosis and efficacy of the treatment.

scholarly journals Identifying Potential Drivers of Differential DNA Methylation Patterns in Breast Cancer Cells

2015 ◽  
Vol 29 (S1) ◽  
Author(s):  
Alexis Fennoy ◽  
Jerry Fong ◽  
Jared Andrews ◽  
Andrew Gasparrini ◽  
John Edwards
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Methylation Patterns

scholarly journals DNA Methylation Heterogeneity Patterns in Breast Cancer Cell Lines

2016 ◽  
Vol 15s4 ◽  
pp. CIN.S40300
Author(s):  
Sunny Tian ◽  
Karina Bertelsmann ◽  
Linda Yu ◽  
Shuying Sun
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Cell Lines ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
Cancer Cell Lines ◽  
Breast Cancer Cell Lines ◽  
Hub Genes ◽  
Methylation State ◽  
Methylation Patterns

Heterogeneous DNA methylation patterns are linked to tumor growth. In order to study DNA methylation heterogeneity patterns for breast cancer cell lines, we comparatively study four metrics: variance, I2 statistic, entropy, and methylation state. Using the categorical metric methylation state, we select the two most heterogeneous states to identify genes that directly affect tumor suppressor genes and high- or moderate-risk breast cancer genes. Utilizing the Gene Set Enrichment Analysis software and the ConsensusPath Database visualization tool, we generate integrated gene networks to study biological relations of heterogeneous genes. This analysis has allowed us to contribute 19 potential breast cancer biomarker genes to cancer databases by locating “hub genes” – heterogeneous genes of significant biological interactions, selected from numerous cancer modules. We have discovered a considerable relationship between these hub genes and heterogeneously methylated oncogenes. Our results have many implications for further heterogeneity analyses of methylation patterns and early detection of breast cancer susceptibility.

scholarly journals Breast tumor DNA methylation patterns associated with smoking in the Carolina Breast Cancer Study

2017 ◽  
Vol 163 (2) ◽  
pp. 349-361 ◽  
Author(s):  
Kathleen Conway ◽  
Sharon N. Edmiston ◽  
Eloise Parrish ◽  
Christopher Bryant ◽  
Chiu-Kit Tse ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Breast Tumor ◽  
Cancer Study ◽  
Breast Cancer Study ◽  
Methylation Patterns ◽  
Tumor Dna ◽  
Carolina Breast Cancer Study

scholarly journals Down-regulation of BRCA1 in human sporadic breast cancer; analysis of DNA methylation patterns of the putative promoter region

Oncogene ◽  
1998 ◽  
Vol 17 (24) ◽  
pp. 3169-3176 ◽  
Author(s):  
Frédérique Magdinier ◽  
Stéphane Ribieras ◽  
Gilbert M Lenoir ◽  
Lucien Frappart ◽  
Robert Dante
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Promoter Region ◽  
Sporadic Breast Cancer ◽  
Down Regulation ◽  
Putative Promoter ◽  
Putative Promoter Region ◽  
Methylation Patterns

scholarly journals Investigating Different DNA Methylation Patterns at the Resolution of Methylation Haplotypes

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiaoqing Peng ◽  
Yiming Li ◽  
Xiangyan Kong ◽  
Xiaoshu Zhu ◽  
Xiaojun Ding
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Stem Cells ◽  
Cell Types ◽  
Specific Gene ◽  
Breast Cancer Sample ◽  
Homologous Chromosomes ◽  
Differentiated Cells ◽  
Cancer Sample ◽  
Methylation Patterns

Different DNA methylation patterns presented on different tissues or cell types are considered as one of the main reasons accounting for the tissue-specific gene expressions. In recent years, many methods have been proposed to identify differentially methylated regions (DMRs) based on the mixture of methylation signals from homologous chromosomes. To investigate the possible influence of homologous chromosomes on methylation analysis, this paper proposed a method (MHap) to construct methylation haplotypes for homologous chromosomes in CpG dense regions. Through comparing the methylation consistency between homologous chromosomes in different cell types, it can be found that majority of paired methylation haplotypes derived from homologous chromosomes are consistent, while a lower methylation consistency was observed in the breast cancer sample. It also can be observed that the hypomethylation consistency of differentiated cells is higher than that of the corresponding undifferentiated stem cells. Furthermore, based on the methylation haplotypes constructed on homologous chromosomes, a method (MHap_DMR) is developed to identify DMRs between differentiated cells and the corresponding undifferentiated stem cells, or between the breast cancer sample and the normal breast sample. Through comparing the methylation haplotype modes of DMRs in two cell types, the DNA methylation changing directions of homologous chromosomes in cell differentiation and cancerization can be revealed. The code is available at: https://github.com/xqpeng/MHap_DMR.

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