Development of a translational imaging tool as a predictive biomarker for anti-PD-1/PD-L1 immunotherapies

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

基本信息

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
起止时间：
2018-07-01 至 2022-03-31
项目状态：
已结题

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

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.

项目摘要发现预测生物标志物可以更好地识别哪些患者将对癌症免疫疗法产生反应肿瘤学的一个重大未满足的临床需求。抗原状态的免疫组织化学充满假阳性以及 PD-1 和 PD-L1 等药物靶点的阴性结果，并在此基础上，用以下方法测量抗原水平：定量成像可以对所有癌症病变中的药物靶点表达提供更全面的评估患者体内。这些数据反过来可能会赋予更复杂和更强大的算法来识别潜在的响应者。考虑到这些因素，该项目将开发一种高灵敏度成像工具以 PD-L1 为靶点，响应人类翻译的特殊需求。例如，我们将开发一个基于针对 PD-L1 的人类重组 Fab 的放射性示踪剂，这将消除对昂贵的人性化过程并最大限度地减少患者正常组织的吸收剂量。此外，我们将使用我们最近开发和发布的新化学酶技术对 Fab 进行放射性氟化。放射性标记技术可以促进更快速的翻译，因为它是位点特异性的，并且可以产生更高的翻译结果。与该领域当前的金标准 N-琥珀酰亚胺基-[18F]- 相比，比活性和放射化学产率 4-氟苯甲酸酯。为了实现三个具体目标，该工厂将在体外进行放射性标记和表征，证明将进行概念成像研究，以显示已知响应的癌症模型中的特异性结合将进行抗 PD-1/PD-L1 疗法和纵向成像研究，以确定 Fab 是否可以检测化疗或放疗导致的 PD-L1 表达变化，从而增强抗 PD-治疗的效果 1/PD-L1免疫疗法。总之，该项目的数据可以为社区做出重大贡献广泛努力为重要的癌症免疫疗法开发更好的转化预测生物标志物。