Quantitative Analysis of Target Coverage and Germinal Center Response by a CXCL13 Neutralizing Antibody in a T-Dependent Mouse Immunization Model

Quantifying Antibody Binding Kinetics on Fixed Cells and Tissues via Fluorescence Lifetime Imaging

We present a method for monitoring spatially localized antigen-antibody binding events on physiologically relevant substrates (cell and tissue sections) using fluorescence lifetime imaging. Specifically, we use the difference between the fluorescence decay times of fluorescently tagged antibodies in free solution and in the bound state to track the bound fraction over time and hence deduce the binding kinetics. We make use of a microfluidic probe format to minimize the mass transport effects and localize the analysis to specific regions of interest on the biological substrates. This enables measurement of binding constants (k_on) on surface-bound antigens and on cell blocks using model biomarkers. Finally, we directly measure p53 kinetics with differential biomarker expression in ovarian cancer tissue sections, observing that the degree of expression corresponds to the changes in k_on, with values of 3.27-3.50 × 10³ M^-1 s^-1 for high biomarker expression and 2.27-2.79 × 10³ M^-1 s^-1 for low biomarker expression.

Novel T Follicular Helper-like T-Cell Lymphoma Therapies: From Preclinical Evaluation to Clinical Reality

Simple Summary

This work reviews the multiple efforts that have been and are being invested by researchers as well as clinicians to improve the treatment of a specific T-cell lymphoma called follicular helper peripheral T-cell lymphoma. Still, though treatments for B-cell lymphomas have improved, this particular T-cell lymphoma has little to no new therapeutic options that show marked improvements in the survival of the patients compared to treatment with chemotherapy. We report here the evaluation of targeted new therapies for this T-cell lymphoma in new preclinical models for this cancer or in clinical trials with the objective to offer better (combination) treatment options.

Abstract

The classification of peripheral T-cell lymphomas (PTCL) is constantly changing and contains multiple subtypes. Here, we focus on Tfh-like PTCL, to which angioimmunoblastic T-cell lymphoma (AITL) belongs, according to the last WHO classification. The first-line treatment of these malignancies still relies on chemotherapy but gives very unsatisfying results for these patients. Enormous progress in the last decade in terms of understanding the implicated genetic mutations leading to signaling and epigenetic pathway deregulation in Tfh PTCL allowed the research community to propose new therapeutic approaches. These findings point towards new biomarkers and new therapies, including hypomethylating agents, such as azacytidine, and inhibitors of the TCR-hyperactivating molecules in Tfh PTCL. Additionally, metabolic interference, inhibitors of the NF-κB and PI3K-mTOR pathways and possibly novel immunotherapies, such as antibodies and chimeric antigen receptors (CAR) directed against Tfh malignant T-cell surface markers, are discussed in this review among other new treatment options.

A Mechanistic Site-Of-Action Model: A Tool for Informing Right Target, Right Compound, And Right Dose for Therapeutic Antagonistic Antibody Programs

Quantitative modeling is increasingly utilized in the drug discovery and development process, from the initial stages of target selection, through clinical studies. The modeling can provide guidance on three major questions–is this the right target, what are the right compound properties, and what is the right dose for moving the best possible candidate forward. In this manuscript, we present a site-of-action modeling framework which we apply to monoclonal antibodies against soluble targets. We give a comprehensive overview of how we construct the model and how we parametrize it and include several examples of how to apply this framework for answering the questions postulated above. The utilities and limitations of this approach are discussed.

T Cells That Help B Cells in Chronically Inflamed Tissues

Chronically inflamed tissues commonly accrue lymphocyte aggregates that facilitate local T cell-B cell interactions. These aggregates can range from small, loosely arranged lymphocyte clusters to large, organized ectopic lymphoid structures. In some cases, ectopic lymphoid structures develop germinal centers that house prototypical T follicular helper (Tfh) cells with high expression of Bcl6, CXCR5, PD-1, and ICOS. However, in many chronically inflamed tissues, the T cells that interact with B cells show substantial differences from Tfh cells in their surface phenotypes, migratory capacity, and transcriptional regulation. This review discusses observations from multiple diseases and models in which tissue-infiltrating T cells produce factors associated with B cell help, including IL-21 and the B cell chemoattractant CXCL13, yet vary dramatically in their resemblance to Tfh cells. Particular attention is given to the PD-1^hi CXCR5⁻ Bcl6^low T peripheral helper (Tph) cell population in rheumatoid arthritis, which infiltrates inflamed synovium through expression of chemokine receptors such as CCR2 and augments synovial B cell responses via CXCL13 and IL-21. The factors that regulate CD4⁺ T cell production of CXCL13 and IL-21 in these settings are also discussed. Understanding the range of T cell populations that can provide help to B cells within chronically inflamed tissues is essential to recognize these cells in diverse inflammatory conditions and to optimize either broad or selective therapeutic targeting of B cell-helper T cells.

Biomeasures and mechanistic modeling highlight PK/PD risks for a monoclonal antibody targeting Fn14 in kidney disease

Discovery of the upregulation of fibroblast growth factor-inducible-14 (Fn14) receptor following tissue injury has prompted investigation into biotherapeutic targeting of the Fn14 receptor for the treatment of conditions such as chronic kidney diseases. In the development of monoclonal antibody (mAb) therapeutics, there is an increasing trend to use biomeasures combined with mechanistic pharmacokinetic/pharmacodynamic (PK/PD) modeling to enable decision making in early discovery. With the aim of guiding preclinical efforts on designing an antibody with optimized properties, we developed a mechanistic site-of-action (SoA) PK/PD model for human application. This model incorporates experimental biomeasures, including concentration of soluble Fn14 (sFn14) in human plasma and membrane Fn14 (mFn14) in human kidney tissue, and turnover rate of human sFn14. Pulse-chase studies using stable isotope-labeled amino acids and mass spectrometry indicated the sFn14 half-life to be approximately 5 hours in healthy volunteers. The biomeasures (concentration, turnover) of sFn14 in plasma reveals a significant hurdle in designing an antibody against Fn14 with desired characteristics. The projected dose (>1 mg/kg/wk for 90% target coverage) derived from the human PK/PD model revealed potential high and frequent dosing requirements under certain conditions. The PK/PD model suggested a unique bell-shaped relationship between target coverage and antibody affinity for anti-Fn14 mAb, which could be applied to direct the antibody engineering towards an optimized affinity. This investigation highlighted potential applications, including assessment of PK/PD risks during early target validation, human dose prediction and drug candidate optimization.

Optimal Affinity of a Monoclonal Antibody: Guiding Principles Using Mechanistic Modeling

Affinity optimization of monoclonal antibodies (mAbs) is essential for developing drug candidates with the highest likelihood of clinical success; however, a quantitative approach for setting affinity requirements is often lacking. In this study, we computationally analyzed the in vivo mAb-target binding kinetics to delineate general principles for defining optimal equilibrium dissociation constant ([Formula: see text]) of mAbs against soluble and membrane-bound targets. Our analysis shows that in general [Formula: see text] to achieve 90% coverage for a soluble target is one tenth of its baseline concentration ([Formula: see text]), and is independent of the dosing interval, target turnover rate or the presence of competing ligands. For membrane-bound internalizing targets, it is equal to the ratio of internalization rate of mAb-target complex and association rate constant ([Formula: see text]). In cases where soluble and membrane-bound forms of the target co-exist, [Formula: see text] lies within a range determined by the internalization rate ([Formula: see text]) of the mAb-membrane target complex and the ratio of baseline concentrations of soluble and membrane-bound forms ([Formula: see text]). Finally, to demonstrate practical application of these general rules, we collected target expression and turnover data to project [Formula: see text] for a number of marketed mAbs against soluble (TNFα, RANKL, and VEGF) and membrane-bound targets (CD20, EGFR, and HER2).

Physiologically relevant binding affinity quantification of monoclonal antibody PF-00547659 to mucosal addressin cell adhesion molecule for in vitro in vivo correlation

Background and Purpose

A monoclonal antibody (PF‐00547659) against mucosal addressin cell adhesion molecule (MAdCAM), expressed as both soluble (sMAdCAM) and trans‐membrane (mMAdCAM) target forms, showed over 30‐fold difference in antibody‐target K_D between in vitro (Biacore) and clinically derived (K_D,in‐vivo) values. Back‐scattering interferometry (BSI) was applied to acquire physiologically relevant K_D values which were used to establish in vitro and in vivo correlation (IVIVC).

Experimental Approach

BSI was applied to obtain K_D values between PF‐00547659 and recombinant human MAdCAM in buffer or CHO cells and endogenous MAdCAM in human serum or colon tissue. CHO cells and tissue were minimally processed to yield homogenate containing membrane vesicles and soluble proteins. A series of binding affinities in serum with various dilution factors was used to estimate both K_D,in‐vivo and target concentrations; MAdCAM concentrations were also measured using LC–MS/MS.

Key Results

BSI measurements revealed low K_D values (higher affinity) for sMAdCAM in buffer and serum, yet a 20‐fold higher K_D value (lower affinity) for mMAdCAM in CHO, mMAdCAM and sMAdCAM in tissue. BSI predicted K_D,in‐vivo in serum was similar to clinically derived K_D,in‐vivo, and the BSI‐estimated serum sMAdCAM concentration also matched the measured concentration by LC–MS/MS.

Conclusions and Implications

Our results successfully demonstrated that BSI measurements of physiologically relevant K_D values can be used to establish IVIVC, for PF‐00547659 to MAdCAM despite the lack of correlation when using Biacore measured K_D and accurately estimates endogenous target concentrations. The application of BSI would greatly enhance successful basic pharmacological research and drug development.

Pharmacological considerations for predicting PK/PD at the site of action for therapeutic proteins

For therapeutic proteins whose sites of action are distal to the systemic circulation, both drug and target concentrations at the tissue sites are not necessarily proportional to those in systemic circulation, highlighting the importance of understanding pharmacokinetic/pharmacodynamic (PK/PD) relationship at the sites of action. This review summarizes the pharmacological considerations for predicting local PK/PD and the importance of measuring PK and PD at site of action. Three case examples are presented to show how mechanistic and physiologically based PK/PD (PBPK/PD) models which incorporated the PK and PD at the tissue site can be used to facilitate understanding the exposure-response relationship for therapeutic proteins.

Assessing the Impact of Tissue Target Concentration Data on Uncertainty in In Vivo Target Coverage Predictions

Understanding pharmacological target coverage is fundamental in drug discovery and development as it helps establish a sequence of research activities, from laboratory objectives to clinical doses. To this end, we evaluated the impact of tissue target concentration data on the level of confidence in tissue coverage predictions using a site of action (SoA) model for antibodies. By fitting the model to increasing amounts of synthetic tissue data and comparing the uncertainty in SoA coverage predictions, we confirmed that, in general, uncertainty decreases with longitudinal tissue data. Furthermore, a global sensitivity analysis showed that coverage is sensitive to experimentally identifiable parameters, such as baseline target concentration in plasma and target turnover half‐life and fixing them reduces uncertainty in coverage predictions. Overall, our computational analysis indicates that measurement of baseline tissue target concentration reduces the uncertainty in coverage predictions and identifies target‐related parameters that greatly impact the confidence in coverage predictions.

Deciphering the In Vivo Performance of a Monoclonal Antibody to Neutralize Its Soluble Target at the Site of Action in a Mouse Collagen-Induced Arthritis Model

PURPOSE

Study the disposition and target-neutralization capability of an anti-interleukin-6 (IL-6) monoclonal antibody (mAb) at the joint in a mouse collagen-induced arthritis (CIA) model.

METHODS

A mechanistic pharmacokinetic/pharmacodynamic study was conducted in a mouse CIA model using CNTO 345, a rat anti-mouse IL-6 mAb, as model compound. The drug, total/free IL-6 concentrations in both serum and joint lavage fluid were quantitatively assessed and compared to those in the normal control mice.

RESULTS

CNTO 345 exhibited higher clearance and significantly higher joint lavage/serum ratio in the CIA mice than in the normal control mice. The mAb concentrations in the joint lavage are approximately proportional to the serum concentrations at all the time points being examined. Dosing of CNTO 345 led to sustained free IL-6 suppression in both serum and joint lavage in a dose-dependent manner. A dose-dependent increase in total IL-6 was observed in serum, but not in the joint lavage fluid. Though no change in disease activity was observed following a single dose of anti-IL-6 mAb at peak of the disease, a dose-dependent decrease in serum amyloid A, a downstream biomarker of IL-6, was observed.

CONCLUSIONS

This study provided quantitative assessments of the distribution and target-neutralization capability of an anti-IL-6 mAb at the site of action in an animal disease model.

Utility of free and total target measurements as target engagement and efficacy biomarkers in biotherapeutic development--opportunities and challenges

For biotherapeutics directed against soluble targets, most often monoclonal antibodies (mAbs), their therapeutic efficacy theoretically is driven by the magnitude and duration of free target suppression. However, for soluble targets of rapid turnover and low abundance, it can be technically challenging to directly measure the lowering of free target following treatment with biologics. The opportunities, challenges, and practical approaches to assess free and bound soluble targets and the utility of free and bound target measurements as biomarkers for target engagement and efficacy are covered in this review. In particular, case examples are presented to illustrate the interplay between drug and free/bound target, and how an integrated bioanalytical and pharmacokinetic/target engagement/pharmacodynamic (PK/TE/PD) modeling approach can be used to assess the target engagement for biologics directed against soluble targets with rapid turnover. Important caveats of the modeling approach in the absence of free target measurements are also discussed.

Mathematical modeling of receptor occupancy data: A valuable technology for biotherapeutic drug development

BACKGROUND

In drug development, in vivo assessment of target engagement provides confidence when testing the drug's mechanism of action and improves the likelihood of clinical success. For biologics, receptor occupancy (RO) determined from circulating cells can provide evidence of target engagement. Integrating this information with mathematical modeling can further enhance the understanding of drug-target interactions and the biological factors that are critical to the successful modulation of the target and ultimately the disease state.

METHODS

This mini-review presents two specific types of mathematical models used to describe antibody-receptor systems and highlights how experimental data can inform the model parameters. Simulations are used to illustrate how various mechanisms influence RO, PK and total cellular receptor profiles.

RESULTS

The simulations demonstrate the effect antibody-receptor internalization, affinity and receptor turnover have on commonly acquired data in drug development.

CONCLUSIONS

Integrating RO data with mathematical models such as the two presented here (target-mediated drug disposition and site-of-action models) can provide a more comprehensive view of the biological system, which can be used to test hypotheses, extrapolate preclinical findings to humans and impact clinical study designs and risk assessments for the successful development of biotherapeutics.

Follicular helper T-cells: expanding roles in T-cell lymphoma and targets for treatment

Follicular helper T-cells (Tfh cells) are a subset of CD4(+) T-cells that are essential for normal production of high affinity antibodies. Tfh cells characteristically produce IL21 and IL4 and show high expression of surface markers CXCR5, ICOS, PDCD1 (PD-1) and the chemokine CXCL13. In this review we will focus on the emerging links between Tfh cells and subtypes of T-cell non-Hodgkin lymphoma: angioimmunoblastic T-cell lymphoma (AITL) and ~20% of peripheral T-cell lymphoma not otherwise specified (PTCL-NOS) have surface marker features of Tfh cells and share a spectrum of genetic abnormalities. The recurrent genetic abnormalities associated with AITL include mutations in epigenetic modifiers such as TET2 and DNMT3A and the motility and adhesion gene, RHOA, is mutated in up to 70% of cases. ~20% of PTCL-NOS demonstrate RHOA mutations and have other characteristics suggesting an origin in Tfh cells. The recognition that specific genetic and surface markers are associated with malignant Tfh cells suggests that the next few years will bring major changes in diagnostic and treatment possibilities. For example, antibodies against IL21, PDCD1 and ICOS are already in clinical trials for autoimmune disease or other malignancies and antibodies against CXCL13 are in pre-clinical development.