Signaling Networks of Nuclear Receptor Transcriptional Crosstalk in Lung Cancer

肺癌核受体转录串扰的信号网络

• 批准号: 8785287
• 负责人: JUN QIN
• 金额: $ 31.08万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8785287
• 关键词: Accounting; Address; Affinity; Agonist; Bioinformatics; Biological; Biological Assay; Biology; Cell Line; Cells; Communities; Cyclic AMP; DNA; DNA Binding; Data; Data Analyses; Data Quality; Data Set; Disease; Drug Targeting; Event; FDA approved; Family; Gefitinib; Genome; Goals; Gold; Guilt; Hela Cells; Human; Informatics; Internet; Investigation; Learning; Ligands; Link; Malignant Epithelial Cell; Malignant neoplasm of lung; Methodology; Methods; Mining; NR4A1 gene; Non-Small-Cell Lung Carcinoma; Nuclear Receptors; Oncogenic; Outcome; Pathology; Pathway interactions; Pattern; Pharmacologic Substance; Pharmacology; Play; Protein Family; Proteins; Proto-Oncogene Proteins c-akt; Research; Research Peer Review; Research Personnel; Resistance; Response Elements; Rest; Role; Signal Pathway; Signal Transduction; Solutions; Techniques; Tissues; Transcriptional Regulation; Translating; Tyrosine Kinase Inhibitor; Work; base; cancer type; data mining; drug development; human FRAP1 protein; interest; member; programs; public health relevance; response; small molecule; tool; transcription factor; user-friendly

DESCRIPTION: Nuclear receptors have been proven to be successful as a druggable family of cellular regulators. We learned much of NR biology and pharmacology from very few NRs and their agonist/antagonist ligands. Among these well-studied NRs are ERa, GR, PR, AR, and - more recently - PPARg. The first four NRs mentioned account for the vast majority of NR-related peer reviewed research and essentially half of FDA-approved NR targeting therapies. There are 48 members of the NR protein family in humans, and much remains to be learned for the rest of the NRs. There are at least two ways to find and prioritize pharmaceutical opportunities for the NR class. One is to find NRs that work synergistically with or regulated by the well-studied NRs and TFs - this constitutes discovery and characterization of transcriptional crosstalk between transcriptional regulators, implying "guilt of association" functions for interactors of known disease targets. The other way is to identify NRs that are activated by the major cellular signaling pathways, or NRs "effectors" of a signaling transduction cascades. To enrich our understanding of the druggable genome, we propose to gather data about dynamics of NR activation and NR crosstalk with other transcription factors (TFs) under different signaling events. Our first major goal (Aim 1) is to learn from NRs with known roles, but not fully characterized mechanisms, in disease. We will use transcription factor response element pulldown (catTFRE) - a method that we recently developed for direct profiling of TF DNA binding activity to their cognate DNA response elements - to find transcriptional effectors (NRs, their coregulators, and other interacting transcription factors) of cellular response to known small molecule modulators of better-studied NRs. A complementary approach is to use catTFRE technique to find NRs, TFs, and coregulators that are activated by 7 major signaling pathways (Aim 2). This study will link signaling events with NR activation and close substantial gaps in understanding of global integrative transcriptional impact of signaling pathways. Aim 2 data will be gathered in the context of lung cancer pathology. Aim 3 develops informatics solutions to address issues in technical and biomedical analysis of data acquired from Aims 1 and 2. Importantly, we will develop user-friendly applications and a web portal for representation and sharing of findings from this proposal.

描述：核受体已被证明是成功的药物细胞调节家族。我们从很少的NR及其激动剂/拮抗剂配体中了解了许多NR生物学和药理学。在这些被充分研究的nr中有ERa， GR， PR， AR，以及最近的ppar。前面提到的四种NR占了绝大多数与NR相关的同行评审研究，基本上占了fda批准的NR靶向治疗的一半。人类NR蛋白家族有48个成员，其余的NR蛋白还有很多有待研究。至少有两种方法可以发现并优先考虑NR类的制药机会。一种是找到与已被充分研究的nr和tf协同工作或受其调控的nr——这构成了转录调控因子之间转录串扰的发现和表征，暗示了已知疾病靶点相互作用物的“关联罪责”功能。另一种方法是识别被主要细胞信号传导途径激活的NRs，或信号转导级联的NRs“效应器”。为了丰富我们对可药物基因组的认识，我们建议收集不同信号事件下NR激活和NR与其他转录因子（tf）串扰的动态数据。我们的第一个主要目标（目标1）是从疾病中具有已知作用但尚未完全表征的机制的nr中学习。我们将使用转录因子反应元件下拉（catTFRE）——这是我们最近开发的一种方法，用于直接分析TF DNA与其同源DNA反应元件的结合活性——来寻找细胞对已知的rna小分子调节剂的反应的转录效应因子（rna、它们的共调节因子和其他相互作用的转录因子）。一种互补的方法是使用catfre技术寻找被7个主要信号通路激活的NRs、tf和共调节因子（Aim 2）。这项研究将把信号事件与NR激活联系起来，并在理解信号通路的全球综合转录影响方面缩小实质性差距。目的2将在肺癌病理背景下收集数据。目标3开发信息学解决方案，以解决从目标1和目标2获得的数据的技术和生物医学分析问题。重要的是，我们将开发用户友好的应用程序和门户网站，以表示和分享这项建议的结果。