Abstract
BackgroundVirtUaL ChIP-seq Analysis through Networks (VULCAN) infers regulatory interactions of transcription factors by overlaying networks generated from publicly available tumor expression data onto ChIP-seq data. We apply our method to dissect the regulation of estrogen receptor-alpha activation in breast cancer to identify potential co-regulators of the estrogen receptor’s transcriptional response.ResultsVULCAN analysis of estrogen receptor activation in breast cancer highlights the key components of the estrogen receptor complex alongside a novel interaction with GRHL2. We demonstrate that GRHL2 is recruited to a subset of estrogen receptor binding sites and regulates transcriptional output, as evidenced by changes in estrogen receptor-associated eRNA expression and stronger estrogen receptor binding at active enhancers after GRHL2 knockdown.ConclusionsOur findings provide new insight into the role of GRHL2 in regulating eRNA transcription as part of estrogen receptor signaling. These results demonstrate VULCAN, available from Bioconductor, as a powerful predictive tool.
Highlights
Breast cancer is the most common form of cancer in women in North America and Europe accounting for 31% of all new cancer cases
The initial ChIP-seq data is converted into genomic regions, and if multiple conditions are supplied, the changes in the transcription factor affinity are calculated
We first benchmark VirtUaL ChIP-seq Analysis through Networks (VULCAN)’s performance in a comprehensive comparison to alternative approaches. We apply it to our data on temporal estrogen receptor-alpha (ER) binding, which identifies GRHL2 as a novel ER cofactor, and we explore its function
Summary
Breast cancer is the most common form of cancer in women in North America and Europe accounting for 31% of all new cancer cases. The majority of breast cancers, approximately 70%, are associated with deregulated signaling by the estrogen receptor-alpha (ER), which drives tumor growth. ChIP-seq enables the identification of potential site-specific interactions at common binding sites between transcription factors and their cofactors; to fully characterize all potential cofactors of a single project on this scale is laborious and expensive. To follow up all potential cofactors identified by a chromatin-wide proteomics method, e.g., RIME [9] or ChIP-MS [10], would take hundreds of individual ChIP-seq experiments. VirtUaL ChIP-seq Analysis through Networks (VULCAN) infers regulatory interactions of transcription factors by overlaying networks generated from publicly available tumor expression data onto ChIP-seq data. We apply our method to dissect the regulation of estrogen receptor-alpha activation in breast cancer to identify potential co-regulators of the estrogen receptor’s transcriptional response
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