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: 9120927
• 负责人: JUN QIN
• 金额: $ 24万
• 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 2018-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9120927
• 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; Estrogen Receptor alpha; Event; FDA approved; FRAP1 gene; Family; Gefitinib; Genome; Goals; Gold; Guilt; Health; Hela Cells; HepG2; Human; Informatics; 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; Techniques; Tissues; Transcriptional Regulation; Translating; Tyrosine Kinase Inhibitor; Work; base; cancer type; data mining; drug development; interest; member; new therapeutic target; programs; response; small molecule; targeted treatment; tool; transcription factor; user-friendly; web portal

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：核受体已被证明是一类可用药的细胞调节剂家族。我们从很少的NRs及其激动剂/拮抗剂配体那里学到了大量的NR生物学和药理学知识。在这些被研究得很好的NRs中有ERα、GR、PR、AR和最近的PPARγ。提到的前四个NRs占了NR相关同行评议研究的绝大多数，基本上占FDA批准的NR靶向疗法的一半。在人类中，有48个NR蛋白家族的成员，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类找到制药机会并确定其优先顺序。一是寻找与研究充分的NRs和TF协同工作或受其调控的NRs--这构成了转录调控因子之间转录串扰的发现和表征，这意味着已知疾病靶标的相互作用者的“关联内疚”功能。另一种方法是识别由主要细胞信号通路激活的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理解，我们建议收集关于不同信号事件下NR激活的动态以及NR与其他转录因子(TF)的串扰的数据。我们的第一个主要目标(目标1)是向NRS学习，这些NRS在疾病中具有已知的作用，但尚未完全确定其机制。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直接测定TFDNA与其同源DNA反应元件结合活性的方法--来寻找细胞对已知小分子调节剂的转录效应因子(NRs、其辅助调节因子和其他相互作用的转录因子)，这些小分子调节剂是研究得更好的NRs的小分子调节器。一种补充的方法是使用catTFRE技术来寻找由7条主要信号通路激活的NR、TF和辅助调节因子(目标2)。这项研究将把信号事件与NR激活联系起来，并填补在理解信号通路的全球整合转录影响方面的实质性差距。AIM 2的数据将在肺癌病理学的背景下收集。AIM 3开发信息学解决方案，以解决从AIM 1和2获得的数据的技术和生物医学分析方面的问题。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，用于陈述和分享这项提案的结果。

项目成果

A proteomics landscape of circadian clock in mouse liver.

小鼠肝脏生物钟的蛋白质组学景观

• DOI: 10.1038/s41467-018-03898-2
• 发表时间: 2018-04-19
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Wang Y;Song L;Liu M;Ge R;Zhou Q;Liu W;Li R;Qie J;Zhen B;Wang Y;He F;Qin J;Ding C
• 通讯作者: Ding C

A mouse tissue transcription factor atlas.

• DOI: 10.1038/ncomms15089
• 发表时间: 2017-04-21
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Zhou Q;Liu M;Xia X;Gong T;Feng J;Liu W;Liu Y;Zhen B;Wang Y;Ding C;Qin J
• 通讯作者: Qin J

A proteomic landscape of diffuse-type gastric cancer.

弥漫型胃癌的蛋白质组学景观

• DOI: 10.1038/s41467-018-03121-2
• 发表时间: 2018-03-08
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Ge S;Xia X;Ding C;Zhen B;Zhou Q;Feng J;Yuan J;Chen R;Li Y;Ge Z;Ji J;Zhang L;Wang J;Li Z;Lai Y;Hu Y;Li Y;Li Y;Gao J;Chen L;Xu J;Zhang C;Jung SY;Choi JM;Jain A;Liu M;Song L;Liu W;Guo G;Gong T;Huang Y;Qiu Y;Huang W;Shi T;Zhu W;Wang Y;He F;Shen L;Qin J
• 通讯作者: Qin J