In Silico Prediction for Regulation of Transcription Factors onTheir Shared Target Genes Indicates Relevant Clinical Implications in a Breast Cancer Population.

Cancer Informatics
Li-Yu Daisy LiuFon-Jou Hsieh

Abstract

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.

References

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Citations

Sep 15, 2015·International Journal of Genomics·Li-Yun ChangFon-Jou Hsieh
Sep 4, 2007·Experimental Hematology·Sven SchwemmersHeike L Pahl
Dec 10, 2015·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·Ya-Chun Hsiao, Li-Yu Daisy Liu
Oct 26, 2016·Molecular Medicine Reports·Paulo R D V GodoyElza T Sakamoto-Hojo

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Datasets Mentioned

BETA
GSE24124

Methods Mentioned

BETA
ESR

Software Mentioned

CART
Gene Spring GX
Express
ontotools
Onto
R
Pathway - Express

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