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: 8898227
• 负责人: JUN QIN
• 金额: $ 30.47万
• 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 2017-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8898227
• 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; Estrogen Receptor alpha; Event; FDA approved; Family; Gefitinib; Genome; Goals; Gold; Guilt; Health; Hela Cells; HepG2; 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; PPAR gamma; 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; response; small molecule; targeted treatment; 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 ERα, GR, PR, AR, and - more recently - PPARγ. 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作为一个药物家族的细胞调节剂。我们从很少的NR及其激动剂/拮抗剂配体中了解了NR的生物学和药理学。在这些被充分研究的NR中，有ERα、GR、PR、AR和最近的PPARγ。提到的前四个NR占NR相关同行评议研究的绝大多数，占FDA批准的NR靶向治疗的一半。在人类中有48个NR蛋白家族成员，对于其余的NR还有很多东西需要了解。至少有两种方法可以为NR类药物寻找和优先考虑制药机会。一个是找到与充分研究的NR和TF协同工作或受其调节的NR-这构成了转录调节因子之间的转录串扰的发现和表征，暗示了已知疾病靶标的相互作用物的“关联内疚”功能。另一种方法是鉴定由主要细胞信号传导途径激活的NR，或信号转导级联的NR“效应物”。为了丰富我们对可药用基因组的理解，我们建议收集关于NR激活的动态和NR与其他转录因子（TF）在不同信号事件下的串扰的数据。我们的第一个主要目标（Aim 1）是从已知作用但尚未完全表征疾病机制的NR中学习。我们将使用转录因子反应元件下拉（catTFRE）-一种我们最近开发的方法，用于直接分析TF DNA与其同源DNA反应元件的结合活性-找到转录效应子（NR，其辅助调节因子和其他相互作用的转录因子）对已知小分子调节剂的细胞反应的更好的研究NR。一种补充方法是使用catTFRE技术来发现由7个主要信号通路激活的NR、TF和辅调节子（Aim 2）。这项研究将连接信号事件与NR激活和关闭实质性的差距，了解全球整合转录影响的信号通路。目标2数据将在肺癌病理学的背景下收集。目标3开发信息学解决方案，以解决对目标1和2所获数据进行技术和生物医学分析的问题。重要的是，我们将开发用户友好的应用程序和一个门户网站，以展示和分享这项建议的结果。