开发转化成像工具作为抗 PD-1/PD-L1 免疫疗法的预测生物标志物-猫眼课题宝

开发转化成像工具作为抗 PD-1/PD-L1 免疫疗法的预测生物标志物

批准号：

9904618

负责人：

Michael John Evans

金额：

$59.13万

依托单位：

UNIVERSITY OF CALIFORNIA, SAN FRANCISCO

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：

已结题

起止时间：

2018-07-01 至 2022-03-31

来源：

https://reporter.nih.gov/project-details/9904618

关键词：

Address Algorithms Amides Animal Model Antibody Affinity Antigens Binding Biochemical Biodistribution Biopsy Cancer Model Chemistry Clinical Combined Modality Therapy Communities Data Detection Development Disease Dose Doxorubicin Drug Targeting Enzymes Epitopes Fluorides Fluorine Formulation Foundations Goals Gold Human IgG1 Image Imaging Device Immunocompetent Immunocompromised Host Immunoglobulin G Immunohistochemistry Immunotherapy In Vitro Investigational Therapies Ionizing radiation Label Lesion Ligase Lysine Malignant Neoplasms Measures Mind Modeling Molecular Weight Mus Neoplasm Metastasis Non-Small-Cell Lung Carcinoma Normal tissue morphology Oncology Paclitaxel Patient imaging Patients Peptides Pharmacology Positron-Emission Tomography Process Production Property Publishing Radiation therapy Radiolabeled Recombinants Research Scanning Side Site Technology Testing Thioctic Acid Time Translations amino group analog anti-PD-1/PD-L1 anti-PD-L1 anti-PD-L1 antibodies anti-PD-L1 therapy base cancer immunotherapy chemotherapy clinical translation clinically relevant companion diagnostics cost extracellular frontier human imaging imaging probe imaging study immunoreactivity in vivo innovation man melanoma novel preclinical study predictive marker preference programmed cell death ligand 1 programmed cell death protein 1 prospective protein expression quantitative imaging radiochemical radiotracer response serial imaging standard of care tool tumor tumor immunology

项目摘要

项目成果

Michael John Evans的其他基金

相似基金

相关文献

中文摘要

翻译

点击翻译按钮获取中文摘要

英文摘要

Project Abstract Discovering predictive biomarkers that better identify which patients will respond to cancer immunotherapies is a major unmet clinical need for oncology. Immunohistochemistry of antigen status is fraught with false positives and negatives for drug targets like PD-1 and PD-L1, and on this basis, measuring antigen levels with quantitative imaging may provide a more global assessment of drug target expression in all cancer lesions within a patient. These data may in turn empower more sophisticated and robust algorithms for identifying potential responders. With these considerations in mind, this project will develop a high sensitivity imaging tool targeting PD-L1 that is responsive to the special demands of human translation. For instance, we will develop a radiotracer based on a human recombinant Fab against PD-L1, which will both preclude the need for a costly humanization process and minimize the absorbed dose to normal tissues in patients. Moreover, we will radiofluorinate the Fab using a new chemoenzymatic technology that we recently developed and published. The radiolabeling technology may facilitate more rapid translation as it is site specific and it results in higher specific activity and radiochemical yield compared to the current gold standard in the field, N-succinimidyl-[18F]- 4-fluorobenzoate. In three specific aims, the Fab will be radiolabeled and characterized in vitro, proof of concept imaging studies will be conducted to show specific binding in models of cancer known to respond to anti-PD-1/PD-L1 therapies, and longitudinal imaging studies will be conducted to determine if the Fab can detect PD-L1 expression changes due to chemo or radiation therapy that can enhance the impact of anti-PD- 1/PD-L1 immunotherapy. In summary, the data from this project could significantly contribute to the community wide effort to develop better translational predictive biomarkers for important cancer immunotherapies.

期刊论文(0)

专著(0)

科研奖励(0)

会议论文