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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

基本信息

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
项目类别：
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

项目摘要

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