Biological Comparisons Among Three Derivative Models of Glioma Patient Cancers Under Microenvironmental Stress

微环境应激下胶质瘤患者癌症的三种衍生模型的生物学比较

• 批准号: 10475178
• 负责人: Jake Yue Chen
• 金额: $ 70.2万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-17 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10475178
• 关键词: 3-Dimensional; Address; Behavior; Biological; Biological Assay; Biological Markers; Biological Models; Biology; Brain; Brain Neoplasms; Cancer Biology; Cancer Model; Cancer Patient; Cancer cell line; Cell Fraction; Cell Line; Cell Proliferation; Clinical; Clinical Trials; Communities; Complex; Computer Models; Consensus; Coupled; Data; Data Science; Disease; Doctor of Philosophy; Elements; Environment; Exhibits; Extracellular Matrix; Extracellular Matrix Proteins; Failure; Funding; Generations; Genetic; Genetic Transcription; Genomics; Glioblastoma; Glioma; Glucose; Goals; Gold; Grant; Growth; Growth Factor; Human; Hypoxia; Immunocompromised Host; Implant; In Vitro; Investigation; Knowledge; Logistics; Malignant Neoplasms; Measurable; Measures; Methods; Modeling; Modification; Molecular; Molecular Profiling; Mus; Neurosphere; Nutrient; Oxygen; Parents; Patient Selection; Patients; Peptides; Performance; Phenotype; Phosphotransferases; Pre-Clinical Model; Preclinical Testing; Prediction of Response to Therapy; Predictive Cancer Model; Prognosis; Property; Radiation; Radiation Tolerance; Radiation therapy; Reproducibility; Research Personnel; Sampling; Serum; Signal Transduction; Standard Model; Stress; System; Testing; The Cancer Genome Atlas; Therapeutic; Tumor Biology; Tumor Stem Cells; United States National Institutes of Health; Xenograft procedure; anticancer research; cancer cell; cancer therapy; cell immortalization; chemoradiation; clinical practice; cost; data modeling; drug development; drug discovery; drug testing; established cell line; expectation; experience; human disease; human model; improved; in silico; in vivo; insight; molecular subtypes; multidisciplinary; neoplastic cell; novel; nutrient deprivation; patient derived xenograft model; patient response; pre-clinical; preclinical study; pressure; standard of care; stem; stem-like cell; stemness; stressor; temozolomide; therapy resistant; three dimensional cell culture; tool; transcriptome; transcriptome sequencing; transcriptomics; treatment response; tumor; tumor growth; tumor microenvironment; vector

PROJECT SUMMARY/ABSTRACT: Current methods of preclinical testing of potential therapeutics have been, for the most part, underwhelming in terms of their ability to yield a clinical impact. This is particularly true for glioblastoma (GBM) where prognosis has increased only by 2-3 months over the last 75 years with a 5-year survival of less than 4%. Many promising preclinical studies have failed to live up to expectations when tested clinically. This problem is likely due to: a) limitations of the preclinical model system and b) lack of reliable biomarkers for proper patient selection. To address these issues, investigators are increasingly utilizing patient-­derived models of cancer (PDMC) coupled with comprehensive molecular profiling. However, differences in model composition, growth conditions, and other microenvironmental factors limit reliability of these models and hamper interpretation. We believe that a careful investigation of tumor microenvironmental (TME) stressors on 3 patient­derived models (xenolines) of GBM, namely xenografts (PDX), spheroid cultures (neurospheres), and human biomatrix embedded 3D microtumors, will provide insight into critical aspects of tumor biology that are influenced by model and TME. These models pre­ and post­ TME perturbagen will also be comprehensively profiled at the genomic, transcriptomic, and kinomic (global kinase activity assessment through a peptide substrate microarray) level to generate a similarity distance metric. We hypothesize that application of TME stressors to the PDMC’s will improve both molecular and biological fidelity of the respective models to that of the original tumor or parent xenoline that can be visualized and in silico tested using an advanced computational data modeling system (GeneTerrain). Our preliminary data generated from prior NIH funded projects indicate that our existing xenolines recapitulate all four molecular subtypes of GBM identified in The Cancer Genome Atlas while reproducing the key hallmarks of GBM when implanted orthotopically in immunocompromised mice. Importantly, we can grow disaggregated xenoline tumors in a novel three-dimensional (3D) culture system incorporating many cells of the tumor microenvironment to produce 3D microtumors suitable for higher throughput drug testing. Moreover, we have preliminary evidence that TME manipulation of BTICs or 3D microtumors (e.g., hypoxia or nutrient deprivation) promotes a more aggressive tumor phenotype in vitro and in vivo that is accompanied by changes in kinomic signatures. Therefore, we will: 1) Generate 3 PDMC models from existing xenolines as well as de novo GBM patient tumors with comprehensive omic testing to calculate similarity distance metrics among the models with corresponding biological assessments including growth, chemoradiation sensitivity, and stemness markers;; 2) Perform TME perturbagen testing of the derivative PDMCs (neurospheres and 3D microtumors) and determine impact on tumor biology and similarity distance metric;; 3) Develop and validate GeneTerrain models of the various PDMCs with respect to TME and therapeutic sensitivity (radiation and temozolomide).

项目总结/摘要： 目前的潜在疗法的临床前测试方法在很大程度上没有给人留下深刻印象， 他们产生临床影响的能力。这对于胶质母细胞瘤（GBM）尤其如此， 在过去的75年中，仅增加了2-3个月，5年生存率不到4%。许多有前途 临床前研究在临床测试时未能达到预期。这个问题可能是由于：a） 临床前模型系统的局限性和B）缺乏用于适当患者选择的可靠生物标志物。到 为了解决这些问题，研究人员越来越多地利用患者来源的癌症模型（PDMC）， 进行全面的分子分析然而，模型组成、生长条件和 其他微环境因素限制了这些模型的可靠性并妨碍了解释。我们相信一个 在3个患者肿瘤衍生模型（Xenolines）上仔细研究肿瘤微环境（TME）应激源， GBM，即异种移植物（PDX）、球状体培养物（神经球）和人生物基质包埋3D 微肿瘤，将提供深入了解肿瘤生物学的关键方面，受模型和TME的影响。 还将在基因组上全面分析这些模型的干扰原前和干扰原后， 转录组学和激酶组学（通过肽底物微阵列进行的整体激酶活性评估）水平， 生成相似性距离度量。我们假设，应用TME应激源的PDMC的意愿， 提高各模型对原始肿瘤或母体的分子和生物学保真度 可以使用先进的计算数据建模系统进行可视化和计算机测试 （GeneTerrain）.我们从先前NIH资助的项目中获得的初步数据表明，我们现有的Xenolines 概括了在癌症基因组图谱中鉴定的GBM的所有四种分子亚型， 当原位植入免疫功能低下的小鼠时，GBM的关键标志。重要的是，我们可以 在一种新的三维（3D）培养系统中， 肿瘤微环境以产生适合于更高通量药物测试的3D微肿瘤。而且我们 有初步证据表明BTIC或3D微肿瘤的TME操作（例如，缺氧或营养 剥夺）在体外和体内促进更侵袭性的肿瘤表型， 在kinomic签名。因此，我们将：1）从现有的捕虏啉以及de生成3个PDMC模型 用综合组学测试计算原发GBM患者肿瘤之间的相似性距离度量， 具有相应生物学评估的模型，包括生长、放化疗敏感性和干性 2）对衍生的PDMC（神经球和3D微肿瘤）进行TME干扰原测试， 确定对肿瘤生物学和相似性距离度量的影响; 3）开发和验证GeneTerrain模型 各种PDMC的TME和治疗敏感性（放射和替莫唑胺）。