Natural Products with Selective Cytoxicity to Non Small Cell Lung Cancer

该应用旨在确定新的治疗弱点（药物靶点或靶向途径）， 在一组约130个非小细胞肺癌（NSCLC）细胞中利用天然产物化学品（NP） 线这些细胞系中的许多是由Minna实验室（合作者）从人类肿瘤中建立的 并概括了其起源肿瘤的约85%的分子特征。此外，我们的目标是将这些 通过分析体细胞突变，基因表达， 在UTSW获得的细胞系组蛋白质组学和代谢组学数据。此外，我们将执行 使用UTSW开发的方法进行作用机制研究，即功能签名本体论 （融合）将基因表达谱与给定的作用机制联系起来。该平台将提供 作用机制假说，我们可以进一步研究详细的生化和细胞生物学 方法。在对约6，000种天然产物级分的初步筛选中，我们鉴定了约75种天然产物 部分，其杀死NSCLC细胞系的亚群，但不杀死永生化的人支气管上皮细胞系。 这些将是进一步研究的起点。 我们的目标是从约75种天然产物馏分中鉴定出活性天然产物， 已经给出了独特的签名，并确定1）分子靶标或途径，2）确定推定的 预测对天然产物的敏感性的生物标志物，3）验证类器官中的选择性毒性， 肺癌的体内模型。重要的是，我们已经证实了我们的公正，数据驱动， 生物信息学管道使用UT西南部产生的数据，并通过其他大的努力（TCGA， COSMIC等）。对于非小细胞肺癌，我们已经制定了生物标志物和干扰素的治疗假设， 我们筛选的所有合成小分子和天然产物组分的关系。 !

This application aims to identify novel therapeutic vulnerabilities (drug targets or target pathways) that can be exploited by natural product chemicals (NPs) in a panel of ~130 non-small cell lung cancer (NSCLC) cell lines. Many of these cell lines were established from human tumors by the Minna laboratory (collaborator) and recapitulate ~85% of the molecular features of their originating tumor. In addition, we aim to link these selective vulnerabilities to biomarkers through the analysis of somatic mutations, gene expression, proteomics and metabolomics data obtained at UTSW on the cell line panel. Furthermore, we will carry out mechanism of action studies utilizing a method developed at UTSW, Functional Signature Ontology (FUSION) to link gene expression profiles to a given mechanism of action. The platform will give mechanism of action hypotheses that we can further investigate with detailed biochemical and cell biology approaches. In initial screening of ~6,000 natural product fractions, we identified ~75 natural product fractions, that kill subsets of the NSCLC cell lines but not immortalized human bronchial epithelial cell lines. These will be the starting point for further studies. Our goal in this proposal is to identify the active natural product from the ~75 natural product fractions that have given unique signatures and to identify 1) a molecular target or pathway, 2) identify a putative biomarker that predicts sensitivity to the natural product, 3) validate the selective toxicity in organoid and in vivo models of lung cancer. Importantly, we have substantiated the utility of our unbiased, data-driven, bioinformatics pipeline using data generated at UT Southwestern, and through other large efforts (TCGA, COSMIC, etc.). For NSCLC, we have formulated therapeutic hypotheses of biomarker and perturbagen relationships for all of the synthetic small molecules and natural product fractions we've screened. !