An integrative transcriptomics approach identifies miR-503 as a candidate master regulator of the estrogen response [miRNA-seq]

Estrogen receptor α (ERα) is an important biomarker of breast cancer severity and a common therapeutic target. Recent studies have demonstrated that in addition to its role in promoting proliferation, ERα also protects tumors against metastatic transformation. Current therapeutics antagonize ERα and interfere with both beneficial and detrimental signaling pathways stimulated by ERα. The goal of this study is to uncover the dynamics of coding and non-coding RNA (microRNA) expression in response to estrogen stimulation and identify potential therapeutic targets that more specifically inhibit ERα-stimulated growth and survival pathways without interfering with its protective features. To achieve this, we exposed MCF7 cells (an estrogen receptor positive model cell line for breast cancer) to estrogen and prepared a time course of paired mRNA and miRNA sequencing libraries at ten time points throughout the first 24 hours of the response to estrogen. From these data, we identified three primary expression trends—transient, induced, and repressed—that were each enriched for genes with distinct cellular functions. Integrative analysis of paired mRNA and microRNA temporal expression profiles identified miR-503 as the strongest candidate master regulator of the estrogen response, in part through suppression of ZNF217—an oncogene that is frequently amplified in cancer. We confirmed experimentally that miR-503 directly targets ZNF217 and that over-expression of miR-503 suppresses breast cancer cell proliferation. Overall, these data indicate that miR-503 acts as a potent estrogen-induced tumor suppressor microRNA that opposes cellular proliferation and has promise as a therapeutic for breast cancer. More generally, our work provides a systems-level framework for identifying functional interactions that shape the temporal dynamics of gene expression. Quantification of miRNAs in MCF7 cells responding to estrogen following a period of estrogen starvation. Three independent biological replicates (30 samples: 3 replicates x 10 time points) of MCF7 cells were exposed to 10nM Estradiol for 0, 1, 2, 3, 4, 5, 6, 8, 12 , or 24 hours, and total RNA was extracted from the samples. Total RNA was used to generate paired RNA and miRNA sequencing. The miRNA libraries were prepared using the Bioo Scientific NextFLEX v2 library preparation kit.

雌激素受体α（Estrogen receptor α, ERα）是乳腺癌恶性程度的重要生物标志物，亦是常见的治疗靶点。已有研究表明，ERα除了促进细胞增殖外，还可抑制肿瘤发生转移转化。当前的临床治疗手段通过拮抗ERα发挥抗肿瘤作用，但同时也会干扰ERα介导的有益与有害信号通路。本研究旨在解析雌激素刺激下编码RNA与非编码RNA（微小RNA，microRNA, miRNA）、信使RNA（mRNA）的表达动态变化，并筛选出可特异性抑制ERα介导的增殖与存活信号通路、同时不干扰其保护性功能的潜在治疗靶点。为此，我们将MCF7细胞（一种雌激素受体阳性的乳腺癌模型细胞系）置于雌激素环境中培养，并在雌激素刺激后的前24小时内选取10个时间点，制备成对的mRNA与miRNA测序文库的时间序列样本。基于上述数据，我们鉴定出三类主要的表达模式：瞬时表达、诱导表达与抑制表达，每类模式均富集于具有特定细胞功能的基因。通过对成对的mRNA与miRNA时序表达谱进行整合分析，我们鉴定出miR-503是雌激素应答反应中最具潜力的核心调控因子，其调控作用部分通过抑制ZNF217实现——ZNF217是一种在多种癌症中频繁扩增的癌基因。我们通过实验证实，miR-503可直接靶向ZNF217，且miR-503的过表达可抑制乳腺癌细胞的增殖。综上，上述数据表明，miR-503是一种强效的雌激素诱导型抑癌miRNA，可拮抗细胞增殖，有望成为乳腺癌的治疗候选靶点。从更广泛的意义上来说，本研究为解析调控基因表达时序动态的功能互作网络提供了一套系统级研究框架。本数据集为经雌激素饥饿预处理的MCF7细胞在雌激素应答过程中的miRNA定量数据。本实验设置3次独立生物学重复（共30份样本：3次重复×10个时间点）：将MCF7细胞置于10nM雌二醇（Estradiol）环境中分别培养0、1、2、3、4、5、6、8、12及24小时，随后提取样本中的总RNA。利用总RNA构建成对的RNA与miRNA测序文库，其中miRNA文库采用Bioo Scientific NextFLEX v2文库制备试剂盒完成构建。