microRNA regulation of drug sensitivity in non-small cell lung cancer

microRNA对非小细胞肺癌药物敏感性的调节

• 批准号: 7908495
• 负责人: ALEXANDER PERTSEMLIDIS
• 金额: $ 22.73万
• 依托单位: UT SOUTHWESTERN MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7908495
• 关键词: Address; Affect; Antineoplastic Agents; Bioinformatics; Biological Assay; Cancer cell line; Cell Culture Techniques; Cell Cycle; Cell Line; Computer Simulation; Computing Methodologies; Cultured Cells; Data; Data Set; Diagnostic; Disease; Drug effect disorder; Drug resistance; Epithelial; Gene Expression; Gene Targeting; Genes; Genetic Translation; Goals; Human; In Vitro; Malignant Neoplasms; Malignant neoplasm of lung; Measurement; Messenger RNA; Methods; MicroRNAs; Modeling; Molecular; Molecular Profiling; Non-Small-Cell Lung Carcinoma; Nucleotides; Organism; Pattern; Pharmaceutical Preparations; Play; Principal Investigator; Regulation; Reporter; Research Design; Research Personnel; Resistance; Role; Suppressor Genes; System; Testing; Translations; Tumor Suppressor Genes; Work; base; cancer cell; cancer initiation; cancer type; chemotherapeutic agent; chemotherapy; drug sensitivity; human disease; inhibitor/antagonist; insight; lung small cell carcinoma; overexpression; programs; response; therapeutic target; tool

DESCRIPTION (provided by applicant): The primary objective of this proposal is to determine if microRNAs participate in the regulation of critical genes implicated in lung cancer drug sensitivity. We have developed a computational method to predict interactions between miRNAs and mRNAs. Based on this method, we predict that a number of oncogenes, tumor suppressor genes, and genes relevant to drug resistance are regulated by miRNAs. We have confirmed several of these predictions using miRNA expression profiling data on a small number of cell lines, including small cell lung cancer (SCLC), non-small cell lung cancer (NSCLC) and immortalized human bronchial epithelial (HBEC) cell lines. We will use a combination of in silico and in vitro approaches to address the following questions: Are specific microRNA expression profiles correlated with differential drug sensitivity in lung cancer cell lines? Do microRNAs play a functional role in drug sensitivity/resistance of lung cancer cells? Can microRNA expression levels be manipulated to increase drug sensitivity of lung cancer cells in cell culture? Study design: We will use microRNA microarray to identify miRNAs that are differentially expressed across a panel of lung cancer cell lines. We will then predict the mRNA targets of the regulated miRNAs using both our own bioinformatics tools as well as those developed by other investigators. We will perform studies in cultured cells using a reporter assay system to determine if expression of the miRNA is associated with repressed translation of the predicted target mRNA in cultured cells. Finally, we will determine if over-expression or silencing of the microRNAs affects mRNA translation of the target gene(s) and results in specific changes in sensitivity to widely-used anti-cancer drugs. Cancer relevance: Identifying aberrant miRNA expression consistent with the models of miRNA involvement in cancer can provide new insight into lung cancer disease mechanisms, and a new set of diagnostic markers and therapeutic targets which could play a significant role in the treatment of human disease.

描述（由申请人提供）：本申请的主要目的是确定microrna是否参与肺癌药物敏感性相关关键基因的调控。我们开发了一种计算方法来预测mirna和mrna之间的相互作用。基于这种方法，我们预测了许多致癌基因、肿瘤抑制基因和与耐药相关的基因受到miRNAs的调控。我们利用少量细胞系（包括小细胞肺癌（SCLC）、非小细胞肺癌（NSCLC）和永生化人支气管上皮（HBEC）细胞系）的miRNA表达谱数据证实了其中的一些预测。我们将使用计算机和体外方法的结合来解决以下问题：特定的microRNA表达谱是否与肺癌细胞系的不同药物敏感性相关？microrna在肺癌细胞的药敏/耐药中是否起功能作用？在细胞培养中，能否通过调控microRNA表达水平来提高肺癌细胞的药物敏感性？研究设计：我们将使用microRNA微阵列来鉴定在一组肺癌细胞系中差异表达的microRNA。然后，我们将使用我们自己的生物信息学工具以及其他研究人员开发的工具来预测受调节的mirna的mRNA靶标。我们将在培养细胞中使用报告基因检测系统进行研究，以确定miRNA的表达是否与培养细胞中预测目标mRNA的翻译抑制有关。最后，我们将确定microrna的过表达或沉默是否会影响靶基因的mRNA翻译，并导致对广泛使用的抗癌药物的敏感性发生特异性变化。癌症相关性：发现与miRNA参与癌症模型一致的异常miRNA表达，可以为肺癌发病机制提供新的认识，并提供一套新的诊断标志物和治疗靶点，可能在人类疾病的治疗中发挥重要作用。