Aberrant transcriptional activities have been documented in breast cancers. Studies often find some transcription factors to be inappropriately regulated and enriched in certain pathological states. The promoter regions of most target genes have binding sites for their transcription factors. An ample of evidence supports their combinatorial effect on their shared target gene expressions.
Here, we used a new statistic method, bivariate CID, to predict combinatorial interaction activity between ERα and a transcription factor (E2F1or GATA3 or ERRα) in regulating target gene expression via four regulatory mechanisms. We identified gene sets in three signal transduction pathways perturbed in breast tumors: cell cycle, VEGF, and PDGFRB. Bivariate network analysis revealed several target genes previously implicated in tumor angiogenesis are among the predicted shared targets, including VEGFA, PDGFRB. In summary, our analysis suggests the importance for the multivariate space of an inferred ERα transcriptional regulatory network in breast cancer diagnostic and therapeutic development.
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Compared with other journals we considered for publishing, Cancer Informatics provided extremely rapid but quality turnaround from draft submission to a flawlessly typeset final publication. Moreover, sharing the article is now as easy as sharing a link with no subscriptions required, and additional code and data files are equally accessible, supporting reproducible research. Because it has published many of our references we feel confident that our target readership must follow the journal. This is further ...
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