Title :
An ERα/modulator regulatory network in the breast cancer cells
Author :
Wu, Heng-Yi ; Wang, Yu ; Zheng, P. ; Jiang, G. ; Liu, Yunlong ; Huang, Tim H M ; Nephew, Kenneth P. ; Li, Lang
Author_Institution :
Center for Comput. Biol. & Bioinf., Indiana Univ., Indianapolis, IN, USA
Abstract :
Estrogens control multiple functions of hormone-responsive breast cancer (BC) cells [1]. They regulate diverse physiological processes in various tissues through genomic and non-genomic mechanisms that result in activation or repression of gene expression. Transcription regulation upon estrogen stimulation is a critical biological process underlying the onset and progress of the majority of breast cancer [2]. However, ERα requires distinct co-regulator complex or modulators for efficient transcriptional regulation. To have insight into the regulatory network of ERα and discover the novel modulators of ERα which acted by distinct mechanisms, we proposed an analytical method based on a linear regression model to identify translational modulators and the relationship between genes for network. To comprehend the network associated with ERα, a dynamic gene expression profile and ChIP-Seq data shown to characterize the breast cancer cell response to estrogens are utilized. The role of modulators within molecular mechanism can be learned from the exploration of these two data sets. Based on the active or repressive function of the ERα, active or repressive function of a modulator, and agonist or antagonist effect of a modulator on the ERα, the ERα/modulator/target relationships were categorized into 27 classes.
Keywords :
biological tissues; cancer; genomics; proteins; regression analysis; ChIP-Seq data; ERα-modulator regulatory network; biological process; coregulator complex; dynamic gene expression profile; estrogen receptor alpha; estrogen stimulation; gene expression activation; gene expression repression; hormone-responsive breast cancer cells; linear regression model; molecular mechanism; nongenomic mechanisms; physiological process; tissues; transcription regulation; translational modulators; Bioinformatics; Breast cancer; Decision support systems; Erbium; Gene expression; Linear regression; Modulation; ChIP-Seq; Estrogen receptor; breast cancer; microarray; modulator; transcription factor;
Conference_Titel :
Genomic Signal Processing and Statistics (GENSIPS), 2011 IEEE International Workshop on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4673-0491-7
Electronic_ISBN :
2150-3001
DOI :
10.1109/GENSiPS.2011.6169427