. Completeness of drug-target engagement and appropriately addressing cellular heterogeneity are critical for the success of anti-cancer therapeutics. Immune checkpoint therapeutics are no exception, for it is poorly understood why the majority of patients (70%) do not respond. Current immune checkpoint therapy patient stratification (tumor immunohistochemistry) makes projection of results highly unpredictable for determining suitable candidacy of individual patients. Total PD-L1 target levels and their engagement by therapeutic antibodies (mAbs) at the tumor are crucial for biological activity. However, technology to non-invasively measure these levels is unavailable. We propose a novel method that can be used to predict efficacy at every identifiable tumor by measuring target expression levels and drug-target engagement in real-time. We will perform these studies to evaluate binding of therapeutic mAbs to programmed death ligand-1 (PD-L1), an immune checkpoint protein that forms the backbone of therapeutic efforts in immuno-oncology today. All the approved PD-L1 therapeutics are mAbs. mAb therapeutics pose unique challenges to pharmacodynamics measurements due to their size and limited penetration into tumors. T cell-based pharmacodynamic measurements from peripheral blood are used in dose-finding of immune checkpoint therapeutics. However, lesion occupancy levels have not been calculated in vivo using mAbs, in part due to their prolonged circulation time, which could be addressed by using a peptide instead. Moreover, tumor concentrations of mAbs are significantly influenced by dynamic changes in target expression, as well as parameters intrinsic to tumor, such as interstitial pressure, and extrinsic parameters related to their complex PK. These findings underscore the need to develop non-invasive tools to assess total PD-L1 levels, delivery, retention and engagement of PD-L1 mAbs at all identifiable lesions. Positron emission tomography (PET) is increasingly used to guide cancer immunotherapy. Precision PET radiotracers can provide dynamic in vivo assessment of PD-L1 expression, and can improve responses and outcomes of these therapies. However, they have not been used for the evaluation of PD-L1 therapeutics. We recently developed a high-affinity human PD-L1-specific PET imaging peptide that provides high image contrast to guide immune checkpoint therapy. The goals of this proposal are to establish our PD-L1 PET tracer performance to measure total tumor PD-L1 levels, evaluate drug delivery and PD-L1 engagement at the tumor by different mAbs, and determine dose-exposure-response of mAbs to enhance and accelerate immune checkpoint therapy management. This new technology enables provision of an empirical means to determine who will benefit from immune checkpoint therapy, aid/enable/advance dose selection and optimization, assist drug development and evaluation, and identification of off-target liabilities to reduce adverse effects that are observed in patients receiving immune checkpoint therapeutics.

Public Health Relevance

. Programmed death ligand-1 (PD-L1) is an immune checkpoint protein involved in tumor immune suppression and an important therapeutic target for cancer immunotherapy. Total PD-L1 target levels and their engagement at the tumor by therapeutic antibodies are crucial for biological activity, however research on assessing responses in cancer immunotherapy is hampered by the absence of technology for their non-invasive quantification. Therefore, a new non-invasive approach will be developed to establish a direct link between dose of antibodies to PD-L1 drug-target engagement at the tumor (exposure) and tumor response to therapy.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
1R01CA236616-01
Application #
9604512
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Tata, Darayash B
Project Start
2018-08-01
Project End
2023-07-31
Budget Start
2018-08-01
Budget End
2019-07-31
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Johns Hopkins University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21205
De Silva, Ravindra A; Kumar, Dhiraj; Lisok, Ala et al. (2018) Peptide-Based 68Ga-PET Radiotracer for Imaging PD-L1 Expression in Cancer. Mol Pharm 15:3946-3952