Tian Dan, Solodin Natalia M, Rajbhandari Prashant, Bjorklund Kelsi, Alarid Elaine T, Kreeger Pamela K
*Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA; Department of Oncology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA; and University of Wisconsin Carbone Cancer Center, Madison, Wisconsin, USA.
*Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA; Department of Oncology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA; and University of Wisconsin Carbone Cancer Center, Madison, Wisconsin, USA
FASEB J. 2015 May;29(5):2022-31. doi: 10.1096/fj.14-265637. Epub 2015 Feb 3.
Receptor levels are a key mechanism by which cells regulate their response to stimuli. The levels of estrogen receptor-α (ERα) impact breast cancer cell proliferation and are used to predict prognosis and sensitivity to endocrine therapy. Despite the clinical application of this information, it remains unclear how different cellular processes interact as a system to control ERα levels. To address this question, experimental results from the ERα-positive human breast cancer cell line (MCF-7) treated with 17-β-estradiol or vehicle control were used to develop a mass-action kinetic model of ERα regulation. Model analysis determined that RNA dynamics could be captured through phosphorylated ERα (pERα)-dependent feedback on transcription. Experimental analysis confirmed that pERα-S118 binds to the estrogen receptor-1 (ESR1) promoter, suggesting that pERα can feedback on ESR1 transcription. Protein dynamics required a separate mechanism in which the degradation rate for pERα was 8.3-fold higher than nonphosphorylated ERα. Using a model with both mechanisms, the root mean square error was 0.078. Sensitivity analysis of this combined model determined that while multiple mechanisms regulate ERα levels, pERα-dependent feedback elicited the strongest effect. Combined, our computational and experimental results identify phosphorylation of ERα as a critical decision point that coordinates the cellular circuitry to regulate ERα levels.
受体水平是细胞调节其对刺激反应的关键机制。雌激素受体-α(ERα)的水平影响乳腺癌细胞的增殖,并用于预测预后和对内分泌治疗的敏感性。尽管这一信息已在临床应用,但尚不清楚不同的细胞过程如何作为一个系统相互作用以控制ERα水平。为了解决这个问题,我们使用了用17-β-雌二醇或载体对照处理的ERα阳性人乳腺癌细胞系(MCF-7)的实验结果,来建立一个ERα调节的质量作用动力学模型。模型分析确定,RNA动态可以通过磷酸化ERα(pERα)对转录的依赖性反馈来捕捉。实验分析证实,pERα-S118与雌激素受体-1(ESR1)启动子结合,这表明pERα可以对ESR1转录进行反馈。蛋白质动态需要一种单独的机制,其中pERα的降解速率比未磷酸化的ERα高8.3倍。使用包含这两种机制的模型,均方根误差为0.078。对这个组合模型的敏感性分析确定,虽然多种机制调节ERα水平,但pERα依赖性反馈产生的影响最强。综合来看,我们的计算和实验结果确定ERα的磷酸化是一个关键的决策点,它协调细胞回路以调节ERα水平。