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细胞调节药物家族。我们从极少数的 NR 及其激动剂/拮抗剂配体中学到了很多 NR 生物学和药理学知识。这些经过充分研究的 NR 包括 ERa、GR、PR、AR 以及最近的 PPARg。提到的前四个 NR 占 NR 相关同行评审研究的绝大多数，并且基本上占 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 NR 仍有很多需要了解的地方。至少有两种方法可以找到并优先考虑 NR 类别的制药机会。一是找到与经过充分研究的NR和TF协同作用或受其调节的NR——这构成了转录调节因子之间转录串扰的发现和表征，意味着已知疾病靶标相互作用者的“关联罪”功能。另一种方法是识别由主要细胞信号传导途径激活的 NR，或信号转导级联的 NR“效应器”。为了丰富我们对可药物基因组的理解，我们建议收集有关不同信号事件下 NR 激活动态以及 NR 与其他转录因子 (TF) 串扰的数据。我们的第一个主要目标（目标 1）是向在疾病中具有已知作用但尚未完全表征的机制的 NR 学习。我们将使用转录因子反应元件下拉 (catTFRE)——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——来寻找细胞对经过更好研究的 NR 的已知小分子调节剂的反应。一种补充方法是使用 catTFRE 技术来查找由 7 个主要信号通路激活的 NR、TF 和辅助调节因子（目标 2）。这项研究将信号事件与 NR 激活联系起来，并弥合对信号通路整体整合转录影响的理解上的巨大差距。目标 2 数据将在肺癌病理学背景下收集。目标 3 开发信息学解决方案，以解决从目标 1 和 2 获取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，用于表示和共享该提案的研究结果。