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Burwinkel, B.

Publications and source records attributed to Burwinkel, B..

3 recordsLinked to original sources

Dissection of demethylation and toxicity induced gene expression changes after decitabine treatment.

The DNA methyltransferase inhibitor decitabine (DAC) is a widely used drug for both fundamental epigenetics studies and anti-cancer therapy. Besides DNA demethylation, DAC also induces cell toxicity associated with DNA damage. The dual-mode of DAC action on cells provides a significant hurdle to study genes which expression is regulated by CpG methylation. In this work, we performed the analysis of global DNA methylation levels in cultured cancer cells after treatment with increasing doses of DAC and have found the U-shaped curve of the de-methylation efficacy induced by the drug. Specifically, high doses of DAC induced significantly lower DNA hypomethylation as compared to hundred-fold less concentrated doses. At the same time, the impact of DAC on cell viability was dose-dependent. These findings allowed dissecting the demethylation and the cell toxicity impact of DAC on gene expression in subsequent mRNA-seq experiments. Surprisingly, the number of genes that were upregulated due to DNA hypomethylation was comparable to the number of genes induced by DAC toxicity. Furthermore, we show that high DAC concentrations induce downregulation of housekeeping genes which are most widely used for RT-qPCR normalization (including GAPDH, actin and tubulin). The latter suggests that genes unaffected by DAC treatment would manifest themselves as upregulated when their expression is normalized on a downregulated housekeeping reference. Finally, we show that expression of most human oncogenes and tumor-suppressor genes remains unaffected after DAC treatment, and only a few of them were upregulated due to DNA hypomethylation. Our work stresses the importance of closely studying the correlation of the degree of DNA demethylation induced by varying doses of DAC with changes in gene expression levels to avoid erroneous conclusions regarding epigenetic silencing of a gene.

molecular biology↗

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype. To identify novel loci, we performed a genome-wide association study (GWAS) including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status and tumor grade. We identified 32 novel susceptibility loci (P<5.0x10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate <0.05). Five loci showed associations (P<0.05) in opposite directions between luminal- and non-luminal subtypes. In-silico analyses showed these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 37.6% for triple-negative and 54.2% for luminal A-like disease. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

genetics↗

Common breast cancer risk loci predispose to distinct tumor subtypes

BackgroundGenome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER), but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. MethodsAmong 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. ResultsEighty-five of 173 variants were associated with at least one tumor feature (false discovery rate <5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at P<0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. ConclusionThis report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.

genetics↗