Measuring the transcriptomic response to targeting kinases correlated with estrogen receptor activity in Breast Cancer

We undertook a phosophotranscriptomic network analysis of published patient tumour RNA-seq and phosphoproteomic data to identify kinases that correltated with Estrogen Receptor activity in Breast Cancer. The most sucessful canidates were selected for targeting by siRNA and the effects monitored by RNA-seq. The code for generation of the expression matrix is available from https://github.com/andrewholding/SimonaVIPER Expression data characterising the effects of siRNAs targeting CAMK2D, CDK8, CSNK1A1, ESR1, GRB2, HIPK4, KSR1, LIMK1, MKNK2, NEK9 in both MCF7 and T47D.

本研究针对已发表的乳腺癌患者肿瘤RNA测序（RNA-seq）与磷酸蛋白质组学（phosphoproteomic）数据开展磷酸转录组（phosphotranscriptomic）网络分析，旨在筛选与雌激素受体（Estrogen Receptor）活性相关的激酶。最终选取表现最优的候选激酶通过小干扰RNA（siRNA, small interfering RNA）进行靶向干预，并借助RNA-seq监测其干预效果。用于生成表达矩阵的代码可从https://github.com/andrewholding/SimonaVIPER获取。本数据集包含靶向CAMK2D、CDK8、CSNK1A1、ESR1、GRB2、HIPK4、KSR1、LIMK1、MKNK2、NEK9的siRNA在MCF7与T47D两种细胞系中的表达效应数据。