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Full Project 4

Full Project 4
完整项目 4
批准号:
10762319
负责人:
ITE A OFFRINGA
金额:
$12.52万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
未结题
起止时间:
2018-09-20 至 2028-08-31
关键词:
3-DimensionalAddressAffectAfrican AmericanAfrican American populationAlveolarAmidesAngiogenesis InhibitionBAY 54-9085BRAF geneBioinformaticsBiologicalBiological FactorsBiological ModelsBiomedical EngineeringBlack AmericanBlack PopulationsBlack raceBronchiolo-Alveolar AdenocarcinomaCaliforniaCarcinogensCaringCell LineCell SurvivalCellsCollectionCombined Modality TherapyDNAData AnalysesDevelopmentDisparityDoctor of PhilosophyDrug CombinationsEducationEpidermal Growth Factor ReceptorEpithelial CellsErlotinibEthnic OriginEthnic PopulationFloridaFormalinFundingGelGelatinGene MutationGenesGeneticGrowthIn VitroIndividualInhalationInvadedKRAS2 geneKnowledgeLeukocytesLung AdenocarcinomaMAP Kinase GeneMalignant Bone NeoplasmMalignant NeoplasmsMalignant neoplasm of lungMeasuresMedicineMetabolismMetastatic Neoplasm to the BoneMethodologyMethodsModelingMolecularMutateMutationNeoplasm MetastasisNicotineOrganoidsPIK3CG geneParaffin EmbeddingPathway interactionsPatientsPatternPerfusionPharmaceutical PreparationsPorosityPrintingRaceResourcesRisk FactorsSTK11 geneSamplingSiteSourceSystemTP53 geneTestingTherapeuticTimeTissue ModelTobacco smokeTreatment EfficacyVariantVascular Endothelial CellWomanWorkalpelisibalveolar epitheliumanti-cancer therapeuticanticancer researchblack menblack womenbonecancer cellcancer health disparitycytotoxicitydriver mutationdrug developmenteffective therapyexome sequencingexposure to cigarette smokefollow-uphealth disparityhealth equityhigh riskin vitro Modelinhibitorinnovationinterdisciplinary collaborationmembermenmigrationmutantneoplasm registrynovelnovel therapeuticsosteogenicprogenitorracial differenceracial populationresponsetargeted treatmenttherapeutic evaluationtherapeutic targettooltreatment responsetwo-dimensional

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中文摘要
翻译
摘要-完整项目4肺 肺癌是癌症健康差距的一个突出来源,特别是在黑人男性中。虽然他们有较低的 吸烟是肺癌最常见的危险因素,黑人男性患肺癌的风险高出37%。 比白色男性更容易得肺癌。此外,黑人男性和女性的5年生存率低于白色 科目许多原因可能导致这些差异,包括遗传差异。后者可能会影响 尼古丁/烟草烟雾成分的代谢、对治疗的反应以及癌症驱动因素的差异 基因突变了解种族/民族之间的遗传差异对肺癌的影响 发展和治疗,我们需要表征肺腺癌的驱动突变(LUAD, 最常见的肺癌类型),并开发体外肺癌模型系统, 在正确的遗传背景下反映相关突变。存在显著的缺乏细胞系模型, 来自美国黑人的肺腺癌,没有来自肺泡上皮细胞的Black细胞系(LUAD 祖细胞)和仅5种已知的LUAD细胞系(与67种白色细胞系相比)。虽然靶向治疗是 但是,对于LUAD的一个子集来说,在美国黑人中测试治疗方法的体外系统非常缺乏。我们 假设由于遗传差异,黑人的LUAD将具有独特的癌症驱动基因库 并且对靶向治疗的反应与白色LUAD不同。该提案代表了一个跨学科的 合作,其中一个医药(生物)化学家从FAMU(博士Lamango),生物医学工程师从UF(博士。 Huang博士和南加州大学的分子遗传学家Offringa博士联合收割机他们的创新资源来解决这个问题。 在美国黑人肺癌中存在明显的健康差异。我们将通过三个具体目标来实现这一目标: 目的1,我们将从100名美国黑人中鉴定肺腺癌的主要驱动突变特征, 他们在突变研究中的代表性不足5倍。在目标2中,我们将开发新的永生化肺泡和 来自黑人受试者的肺腺癌细胞系,并使用这些和现有的细胞系来开发2- 三维(2D)和三维(3D)体外模型。我们将测试有前途的药物(聚异戊二烯化 半胱氨酰酰胺抑制剂(PCAIs))由Lamango实验室开发,靶向KRAS途径, 在LUAD中经常发生突变。随着时间的推移,我们还将测试其他靶向疗法和组合, 毒品在目标3中,我们将开发一种新的3D打印骨癌转移模型,以研究 PCAIs和其他靶向疗法对癌细胞的细胞毒性、迁移和侵袭的影响。骨头是最 LUAD的常见转移部位。这三个拟议的具体目标解决了对癌症缺乏了解的问题 在美国黑人肺腺癌中的驱动基因,产生了正常肺泡和肺腺癌的集合。 来自黑人受试者的腺癌细胞系,将用于建立适合种族的模型, 为其他人提供了很好的资源,并允许使用2D,3D, 和骨转移模型。
英文摘要
ABSTRACT – FULL PROJECT 4 LUNG Lung cancer is a prominent source of cancer health disparity, particularly in Black men. While they have lower exposure to cigarette smoke, the most common risk factor for lung cancer, Black men have a 37% higher risk for lung cancer than White men. In addition, the 5-year survival of Black men and women is below that of White subjects. Numerous causes likely underlie these differences, including genetic differences. The latter may affect the metabolism of nicotine/tobacco smoke components, responses to therapy, and differences in cancer driver gene mutations. To understand the effects of the genetic differences between racial/ethnic groups on lung cancer development and treatment, we need to characterize the driver mutations in lung adenocarcinoma (LUAD, the most common type of lung cancer) in Black Americans and develop in vitro lung cancer model systems that reflect the relevant mutations in the correct genetic background. There is a notable lack of cell line models for lung adenocarcinoma from Black Americans, with no Black cell lines from alveolar epithelial cells (the LUAD progenitors) and only 5 known LUAD cell lines (compared to 67 White cell lines). While targeted therapies are available for a subset of LUAD, in vitro systems to test therapeutics in Black Americans are sorely lacking. We hypothesize that due to genetic differences, LUAD in Blacks will have a unique repertoire of cancer driver genes and will respond to targeted therapies distinctly from white LUAD. This proposal represents an interdisciplinary collaboration in which a medicinal (bio)chemist from FAMU (Dr. Lamango), a biomedical engineer from UF (Dr. Huang), and a molecular geneticist from USC (Dr. Offringa) combine their innovative resources to tackle the pronounced health disparities in lung cancer in Black Americans. We will do so through three Specific Aims: In Aim 1, we will identify the main driver mutational signatures of lung adenocarcinoma from 100 Black Americans, who are 5-fold underrepresented in mutational studies. In Aim 2, we will develop new immortalized alveolar and lung adenocarcinoma cell lines from Black subjects and use these and existing cell lines to develop 2- dimensional (2D) and 3-dimensional (3D) in vitro models. We will test promising drugs (polyisoprenylated cysteinyl amide inhibitors (PCAIs)) developed by the Lamango lab, that target the KRAS pathway which is frequently mutated in LUAD. As time allows we will also test other targeted therapeutics and combinations of drugs. In Aim 3 we will develop a novel 3D-printed bone cancer metastasis model to study the differential efficacy of PCAIs and other targeted therapeutics on cancer cell cytotoxicity, migration, and invasion. Bone is the most common metastatic site of LUAD. The three proposed Specific Aims address the lack of knowledge about cancer driver genes in Black American lung adenocarcinoma, generate a collection of normal alveolar and lung adenocarcinoma cell lines from Black subjects that will be used to establish race-appropriate models and will be a great resource for others, and allow the testing of therapeutics on cells from Black Americans using 2D, 3D, and bone metastasis models.
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