Regulation of anti-endocrine resistance of breast cancer by a network of non-codi

非codi网络对乳腺癌抗内分泌耐药性的调节

• 批准号: 8226638
• 负责人: Peter Kabos
• 金额: $ 17.17万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8226638
• 关键词: 3' Untranslated Regions; Address; Adjuvant; Antibodies; Binding; Biochemical; Bioinformatics; Biological; Biology; Breast; Breast Cancer Cell; Cancer Biology; Cancer cell line; Clinical; Clinical Skills; Colorado; Complex; Data; Development; Diagnostic; Distant; Down-Regulation; Endocrine; Environment; Estrogen Nuclear Receptor; Estrogen Receptors; Estrogen receptor positive; Estrogens; Failure; Functional RNA; Gene Expression; Gene Expression Regulation; Genes; Goals; Grant; Hormone Receptor; Hormones; Immunoprecipitation; Individual; Knowledge; Lead; Link; MCF7 cell; Malignant Neoplasms; Measurement; Mentors; Messenger RNA; Methodology; MicroRNAs; Modeling; Modification; Molecular; Molecular Profiling; Molecular and Cellular Biology; NCOA3 gene; Neoplasm Metastasis; Normal Cell; Nuclear; Pathogenesis; Patients; Physiological; Predictive Value; Proteins; RNA; RNA Sequences; RNA-Induced Silencing Complex; Radiation; Receptor Protein-Tyrosine Kinases; Recurrence; Regulation; Regulator Genes; Reporter; Repression; Research Personnel; Resistance; Role; Sampling; Small RNA; Study models; Systems Biology; Techniques; Testing; Therapeutic; Tissue Sample; Toxic effect; Training; Transcript; Translating; Ultraviolet Rays; Universities; Vertebral column; base; career development; crosslink; falls; hormone therapy; human tissue; improved; in vitro Model; in vivo; knock-down; malignant breast neoplasm; member; next generation; novel diagnostics; novel therapeutics; programs; protein complex; research study; response; skills; treatment response; tumorigenesis

DESCRIPTION (provided by applicant): Regulation of anti-endocrine resistance of breast cancer by a network of non-coding RNAs The discovery of regulatory non-coding RNAs has added a layer of complexity to understanding how precise regulation of gene expression is achieved in normal cells and how their dysregulation may contribute to pathological states including cancer. MicroRNAs (miRNAs or miRs) are the best defined class amongst these non-coding RNAs. MiRs are thought to function by binding to their target messenger RNAs in a sequence- specific fashion and cause repression. Abnormal expression of miRs has been linked to the pathogenesis of several malignancies including breast cancer. Conventional techniques employed to study miR-mRNA interactions include profiling of expression (by either microarray or high throughput sequencing), bio-informatic prediction of miR-mRNA targets, over-expression and knock-down of miRs followed by measurement of changes in transcript and protein level, and reporter-based analysis of 3' untranslated region-binding of miRs. Although these approaches have provided valuable information about miR-mRNA interactions, they fall short in directly demonstrating specific miR-mRNA interactions in vivo. To address these shortcomings, a biochemical technique of High Throughput Sequencing following Cross-Linked Immunoprecipitation (HITS-CLIP) was recently described, which directly isolates the miR-mRNA interactome. This technique relies on the ability of ultraviolet light (UV) to cross-link miRs and mRNAs to the argonaute proteins followed by the isolation of RNA- protein complexes by immune precipitation, isolation and sequencing of the RNA. We have successfully adapted this technique to define the miR-mRNA interactome of breast cancer cells. This application for a Mentored Career Development Grant seeks to apply a systems biology approach based on HITS-CLIP to define the role of miRs in resistance to anti-endocrine therapy in breast cancer. Given their high efficacy and low toxicity, anti-endocrine therapies form the backbone of treatments for all patients with estrogen receptor positive breast cancer. However, both primary and secondary resistance remains a problem. Results from other investigators have suggested that multiple miRs (including miR-221) are involved in estrogen receptor regulation in breast cancer. In aim 1, specific changes brought about by estrogen in the miR-mRNA interactome of breast cancer will be characterized. In aim 2, we will test our hypothesis that a specific network of miRs contributes to the responsiveness and / or resistance of breast cancer to anti-endocrine therapy. Specific miR network defined from the first two aims will be validated in clinical samples in aim 3. The training and mentoring program proposed under the guidance Drs. Thorburn and Elias will provide the applicant with an in depth expertise in the biology of small RNAs and breast cancer. University of Colorado provides an outstanding academic environment that combines expertise in breast cancer biology, RNA and bioinformatics. Data from these studies is hoped to contribute to a better understanding of the role of small RNAs in hormone responsiveness and resistance of breast cancer and ultimately to novel diagnostics and therapeutics.

描述（由申请人提供）：通过非编码RNA网络调节乳腺癌的抗内分泌抗性调节性非编码RNA的发现增加了一层复杂性，以理解如何在正常细胞中实现基因表达的精确调节以及它们的失调如何导致包括癌症在内的病理状态。microRNA（miRNAs或miRs）是这些非编码RNA中定义最好的一类。miR被认为通过以序列特异性方式与其靶信使RNA结合来发挥作用并引起抑制。miR的异常表达与包括乳腺癌在内的几种恶性肿瘤的发病机制有关。用于研究miR-mRNA相互作用的常规技术包括表达谱分析（通过微阵列或高通量测序）、miR-mRNA靶标的生物信息学预测、miR的过表达和敲低，随后测量转录物和蛋白质水平的变化，以及miR的3'非翻译区结合的基于PCR的分析。尽管这些方法提供了关于miR-mRNA相互作用的有价值的信息，但它们在直接证明体内特异性miR-mRNA相互作用方面不足。为了解决这些缺点，最近描述了一种生物化学技术，即交联免疫沉淀后的高重复测序（HITS-CLIP），其直接分离miR-mRNA相互作用组。该技术依赖于紫外光（UV）将miR和mRNA交联至argonaute蛋白的能力，随后通过免疫沉淀分离RNA-蛋白复合物，分离和测序RNA。我们已经成功地采用这种技术来定义乳腺癌细胞的miR-mRNA相互作用组。这项指导职业发展补助金的申请旨在应用基于HITS-CLIP的系统生物学方法来确定miR在乳腺癌抗内分泌治疗耐药性中的作用。鉴于其高疗效和低毒性，抗内分泌疗法形成了所有雌激素受体阳性乳腺癌患者治疗的支柱。然而，主要和次要阻力仍然是一个问题。其他研究者的结果表明，多种miR（包括miR-221）参与乳腺癌中雌激素受体的调节。在目标1中，将表征由雌激素在乳腺癌的miR-mRNA相互作用组中引起的特异性变化。在目标2中，我们将检验我们的假设，即miR的特定网络有助于乳腺癌对抗内分泌疗法的反应性和/或抗性。由前两个目标定义的特异性miR网络将在目标3的临床样品中验证。Thorburn和Elias博士指导下提出的培训和指导计划将为申请人提供小RNA和乳腺癌生物学方面的深入专业知识。科罗拉多大学提供了一个优秀的学术环境，结合了乳腺癌生物学，RNA和生物信息学的专业知识。希望这些研究的数据有助于更好地理解小RNA在乳腺癌激素反应性和耐药性中的作用，并最终有助于新的诊断和治疗。