Credentialing next-generation human glioma models for precision therapeutics

认证下一代人类神经胶质瘤模型的精准治疗

• 批准号: 10830654
• 负责人: Frank Furnari
• 金额: $ 13.15万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10830654
• 关键词: Affinity; Award; Bioinformatics; Biology; Chemicals; Clustered Regularly Interspaced Short Palindromic Repeats; Collaborations; Combined Modality Therapy; Coupled; Credentialing; Data; Drug Targeting; Drug resistance; Engineering; Epidermal Growth Factor Receptor; Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor; Failure; Foundations; Genetic Engineering; Glioma; Goals; Human; Immobilization; Investigational Therapies; Isotopes; Kinetics; Malignant Neoplasms; Mass Spectrum Analysis; Measures; Modeling; Molecular; Monitor; Parents; Peptides; Phosphorylation; Phosphotransferases; Pre-Clinical Model; Precision therapeutics; Primary Brain Neoplasms; Protein-Serine-Threonine Kinases; Proteins; Proteomics; Reaction; Sampling; Sepharose; Serine; Technology; Therapeutic Uses; Tyrosine; Tyrosine Kinase Inhibitor; Update; Work; combat; design; experience; genome editing; induced pluripotent stem cell; inhibitor; insight; interest; microchip; model design; mutant; next generation; next generation sequencing; novel; preclinical development; response; small molecule; success; time use; treatment response; tumor

ABSTRACT This application is being submitted in response to the Notice of Special Interest (NOSI) identified as NOT- CA-23-045. Despite notable successes in other cancers, precision therapeutics have failed in EGFR-driven gliomas, the most common and deadly primary brain tumors. Reasons for failure include the lack of preclinical models that faithfully recapitulate the biology of EGFR-driven gliomas and adaptive responses to therapy. Through our multi-PI (MPI) parent award R01 CA258248, we are developing and molecularly credentialing novel EGFR mutant-driven human glioma models for use in preclinical development of tyrosine kinase inhibitor (TKI)-based therapies. The foundation of our modeling work comes from the Furnari Lab (UCSD), who developed a novel platform for engineering glioma models from human induced pluripotent stem cells (iPSC) using CRISPR genome editing. The Miller Lab has extensive experience in small molecule experimental therapeutics using genetically engineered (GE) glioma models, next- generation sequencing, and proteomics. Our parent award proposed to leverage our established collaboration with the Johnson Lab (UNC) to profile kinase expression en masse using multiplex inhibitor beads coupled with mass spectrometry (MIB-MS). We previously used this approach to show that dynamic kinome reprogramming contributes to targeted drug resistance in glioma models. In this Multi-PI supplement, we will extend our originally proposed work through integration of two distinct, but complementary kinome profiling approaches. The Johnson Lab has developed an updated version of MIB- MS termed SureQuant. MIB-MS requires affinity-based enrichment of active kinases using broad-spectrum inhibitors chemically coupled to Sepharose beads and is limited to relative quantification of kinase expression. SureQuant uses isotopically “heavy” peptides, designed from MIB-enriched, proteolytically digested human kinases, and parallel reaction monitoring (PRM) to absolutely quantify kinase expression in otherwise un-enriched protein samples. This advance will be coupled with a second complimentary approach: the PamStation technology from the Kinome Core (Willey Lab) at UAB. This approach monitors the kinetics of tyrosine or serine/threonine kinase activity (phosphorylation) in real time using specific peptide substrates immobilized on microchips. Thus, whereas SureQuant accurately measures kinase expression, PamStation monitors substrate-level kinase activity. We hypothesize that a combination of these two approaches, and bioinformatic integration of the resulting data, will provide novel insights into the glioma kinome and its dynamic response to targeted EGFR TKI.

摘要 本申请是为了回应特别利益通知（NOSI）而提交的，该通知被确定为不- CA-23-045尽管在其他癌症中取得了显着的成功，但精确治疗在EGFR驱动的癌症中失败了。 神经胶质瘤是最常见和致命的原发性脑肿瘤。失败的原因包括缺乏 临床前模型，忠实地概括了EGFR驱动的胶质瘤的生物学和对EGFR的适应性反应。 疗法通过我们的多PI（MPI）母体奖R 01 CA 258248，我们正在开发和分子 用于临床前开发的新EGFR突变驱动的人神经胶质瘤模型的认证 酪氨酸激酶抑制剂（TKI）为基础的治疗。我们建模工作的基础来自于 Furnari Lab（UCSD）开发了一种新的平台，用于从人类诱导的神经胶质瘤模型中构建神经胶质瘤模型。 利用CRISPR基因组编辑的多能干细胞（iPSC）。米勒实验室在以下方面拥有丰富的经验： 使用基因工程（GE）胶质瘤模型的小分子实验疗法，接下来- 代测序和蛋白质组学。我们的母公司奖提议利用我们建立的 与约翰逊实验室（JPL）合作，使用多重抑制剂对激酶表达进行分析 微珠与质谱联用（MIB-MS）。我们以前使用这种方法来证明动态 激酶组重编程有助于胶质瘤模型中的靶向药物抗性。在这个多PI 作为补充，我们将通过整合两个不同的，但 互补激酶组分析方法。约翰逊实验室开发了MIB的更新版本- MS称为SureQuant。MIB-MS需要使用广谱的多核苷酸对活性激酶进行基于亲和性的富集。 抑制剂化学偶联到琼脂糖凝胶珠，并限于相对定量的激酶 表情SureQuant使用同位素“重”肽，由富含MIB的蛋白水解 消化的人激酶和平行反应监测（PRM），以绝对定量激酶表达 在其他未富集的蛋白质样品中。这一进步将与第二次免费赠送相结合 方法：来自UAB Kinome Core（Willey Lab）的PamStation技术。这种方法监测 使用特异性的酪氨酸或丝氨酸/苏氨酸激酶活性（磷酸化）的真实的动力学 固定在微芯片上的肽底物。因此，尽管SureQuant准确测量激酶 表达，PamStation监测底物水平激酶活性。我们假设 这两种方法，以及由此产生的数据的生物信息学整合，将提供新的见解， 胶质瘤激酶组及其对靶向EGFR TKI的动态反应。