MicroRNA expression and gene regulation drive breast cancer progression and metastasis in PyMT mice.
MicroRNA expression and gene regulation drive breast cancer progression and metastasis in PyMT mice.
复制标题
DOI：
10.1186/s13058-016-0735-z
复制
发表时间：
2016-07-22
期刊：
影响因子：
--
通讯作者：
Zhang ZD
中科院分区：
文献类型：
--
作者：
Nogales-Cadenas R;Cai Y;Lin JR;Zhang Q;Zhang W;Montagna C;Zhang ZD
microRNA（miRNAs）是一种约22个核苷酸的非编码小RNA分子，其功能是沉默其靶基因的表达。大量研究表明，miRNAs不仅是重要细胞过程的关键调节因子，而且也是许多疾病，特别是癌症发展的驱动因素。雌激素受体阳性管腔型B是第二常见但研究最少的乳腺癌亚型。只有少数研究检测了miRNAs在管腔型B乳腺癌中的表达谱，其在癌症进展中的调节作用还有待研究。在这项研究中，使用多瘤中T抗原（PyMT）小鼠，一种广泛使用的管腔B乳腺癌模型，我们分析了microRNA（miRNA）表达在四个时间点，代表癌症进展的不同关键发展阶段。我们考虑了在这些时间点的miRNA和信使RNA（mRNA）的表达，以提高对miRNA调控靶点的鉴定。通过将基因功能和通路注释与miRNA-mRNA相互作用相结合，我们创建了PyMT特异性三方miRNA-mRNA通路网络，并确定了新的功能调控程序（FRPs）。我们鉴定了151个差异表达的miRNAs，它们在疾病进展的整个过程中具有严格的上调或下调的双重性质。在82个新发现的乳腺癌相关miRNAs中，有35个miRNAs基于其序列互补性和表达谱可能调控271个蛋白质编码基因。我们还确定了驱动特定癌症相关生物学过程的miRNA-mRNA调控模块。在这项研究中，我们分析了PyMT小鼠模型中乳腺癌进展过程中miRNA的表达。通过整合miRNA和mRNA表达谱，我们鉴定了差异表达的miRNA及其靶基因，这些基因涉及癌症的几个标志。我们将一种新型的聚类方法应用于注释的miRNA-mRNA调控网络，并识别了参与特定癌症相关生物过程的网络模块。本文的在线版本（doi：10.1186/s13058-016-0735-z）包含补充材料，可供授权用户使用。
MicroRNAs (miRNAs) are small non-coding RNA molecules of about 22 nucleotides which function to silence the expression of their target genes. Numerous studies have shown that miRNAs are not only key regulators in important cellular processes but are also drivers in the development of many diseases, especially cancer. Estrogen receptor positive luminal B is the second most common but the least studied subtype of breast cancer. Only a few studies have examined the expression profiles of miRNAs in luminal B breast cancer, and their regulatory roles in cancer progression have yet to be investigated. In this study, using polyoma middle T antigen (PyMT) mice, a widely used luminal B breast cancer model, we profiled microRNA (miRNA) expression at four time points that represent different key developmental stages of cancer progression. We considered the expression of both miRNAs and messenger RNAs (mRNAs) at these time points to improve the identification of regulatory targets of miRNAs. By combining gene functional and pathway annotation with miRNA-mRNA interactions, we created a PyMT-specific tripartite miRNA-mRNA-pathway network and identified novel functional regulatory programs (FRPs). We identified 151 differentially expressed miRNAs with a strict dual nature of either upregulation or downregulation during the whole course of disease progression. Among 82 newly discovered breast-cancer-related miRNAs, 35 can potentially regulate 271 protein-coding genes based on their sequence complementarity and expression profiles. We also identified miRNA-mRNA regulatory modules driving specific cancer-related biological processes. In this study we profiled the expression of miRNAs during breast cancer progression in the PyMT mouse model. By integrating miRNA and mRNA expression profiles, we identified differentially expressed miRNAs and their target genes involved in several hallmarks of cancer. We applied a novel clustering method to an annotated miRNA-mRNA regulatory network and identified network modules involved in specific cancer-related biological processes. The online version of this article (doi:10.1186/s13058-016-0735-z) contains supplementary material, which is available to authorized users.