Targets for MAbs: innovative approaches for their discovery & validation, LabEx MAbImprove 6th antibody industrial symposium, June 25-26, 2018, Montpellier, France

Enhanced Tumor Targeting of Radiolabeled Mouse/Human Chimeric Anti-Tn Antibody in Losartan-Treated Mice Bearing Tn-Expressing Lung Tumors

Aim: ChiTn, a mouse/human chimeric anti-Tn monoclonal antibody, was radiolabeled with iodine-131 (131I) and technetium-99m (99mTc) to assess its biodistribution and internalization in Tn-expressing (Tn+) and wild-type (Tn-) LL/2 lung cancer cells. Results: Selective accumulation and gradual internalization of ChiTn were observed in Tn+ cells. Biodistribution in mice with both Tn+ or Tn- lung tumors indicated that the uptake of radiolabeled ChiTn within tumors increased over time. Dual-labeling experiments with 99mTc and 131I showed different biodistribution patterns, with 99mTc exhibiting higher values in the liver, spleen, and kidneys, while 131I showed higher uptake in the thyroid and stomach. However, tumor uptake did not significantly differ between Tn+ and Tn- tumors. To improve tumor targeting, Losartan, an antihypertensive drug known to enhance tumor perfusion and drug delivery, was investigated. Biodistribution studies in Losartan-treated mice revealed significantly higher radiolabeled ChiTn uptake in Tn+ tumors. No significant changes were observed in the uptake of the control molecule IgG-HYNIC™99mTc. Conclusions: These findings demonstrate the enhanced tumor targeting of radiolabeled ChiTn in Losartan-treated mice with Tn-expressing lung tumors. They highlight the potential of ChiTn as a theranostic agent for cancer treatment and emphasize the importance of Losartan as an adjunctive treatment to improve tumor perfusion and drug delivery.

Application of quantitative protein mass spectrometric data in the early predictive analysis of membrane-bound target engagement by monoclonal antibodies

Model-informed drug discovery advocates the use of mathematical modeling and simulation for improved efficacy in drug discovery. In the case of monoclonal antibodies (mAbs) against cell membrane antigens, this requires quantitative insight into the target tissue concentration levels. Protein mass spectrometry data are often available but the values are expressed in relative, rather than in molar concentration units that are easier to incorporate into pharmacokinetic models. Here, we present an empirical correlation that converts the parts per million (ppm) concentrations in the PaxDb database to their molar equivalents that are more suitable for pharmacokinetic modeling. We evaluate the insight afforded to target tissue distribution by analyzing the likely tumor-targeting accuracy of mAbs recognizing either epidermal growth factor receptor or its homolog HER2. Surprisingly, the predicted tissue concentrations of both these targets exceed the Kd values of their respective therapeutic mAbs. Physiologically based pharmacokinetic (PBPK) modeling indicates that in these conditions only about 0.05% of the dosed mAb is likely to reach the solid tumor target cells. The rest of the dose is eliminated in healthy tissues via both nonspecific and target-mediated processes. The presented approach allows evaluation of the interplay between the target expression level in different tissues that determines the overall pharmacokinetic properties of the drug and the fraction that reaches the cells of interest. This methodology can help to evaluate the efficacy and safety properties of novel drugs, especially if the off-target cell degradation has cytotoxic outcomes, as in the case of antibody-drug conjugates.

The Dawn of a New Era: Targeting the "Undruggables" with Antibody-Based Therapeutics

The high selectivity and affinity of antibodies toward their antigens have made them a highly valuable tool in disease therapy, diagnosis, and basic research. A plethora of chemical and genetic approaches have been devised to make antibodies accessible to more "undruggable" targets and equipped with new functions of illustrating or regulating biological processes more precisely. In this Review, in addition to introducing how naked antibodies and various antibody conjugates (such as antibody-drug conjugates, antibody-oligonucleotide conjugates, antibody-enzyme conjugates, etc.) work in therapeutic applications, special attention has been paid to how chemistry tools have helped to optimize the therapeutic outcome (i.e., with enhanced efficacy and reduced side effects) or facilitate the multifunctionalization of antibodies, with a focus on emerging fields such as targeted protein degradation, real-time live-cell imaging, catalytic labeling or decaging with spatiotemporal control as well as the engagement of antibodies inside cells. With advances in modern chemistry and biotechnology, well-designed antibodies and their derivatives via size miniaturization or multifunctionalization together with efficient delivery systems have emerged, which have gradually improved our understanding of important biological processes and paved the way to pursue novel targets for potential treatments of various diseases.

Deep Mining of Complex Antibody Phage Pools

An important, and rapidly growing class of drugs are antibodies which can be discovered through phage display technology. In this technique, antibodies are typically first enriched through consecutive rounds of selection on a target antigen with amplification in bacteria between each selection round. Thereafter, a subset of random individual clones is analyzed for binding in a screening procedure. This results in discovery of the most abundant antibodies in the pool. However, there are multiple factors affecting the enrichment of antibodies during the selection resulting in a very complex output pool of antibodies. A few antibodies are present in many copies and others only in a few copies, where the most abundant antibodies are not necessarily the functionally best ones. In order to utilize the full potential of the output from a phage display selection, and enable discovery of low abundant, potentially functionally important clones, deep mining technologies are needed. In this chapter, two methods for deep mining of an antibody pool are described, protein depletion and antibody blocking. The methods can be applied both when the target is a single antigen and on complex antigen mixtures such as whole cells and tissues.

Viro-antibody therapy: engineering oncolytic viruses for genetic delivery of diverse antibody-based biotherapeutics

Cancer therapeutics approved for clinical application include oncolytic viruses and antibodies, which evolved by nature, but were improved by molecular engineering. Both facilitate outstanding tumor selectivity and pleiotropic activities, but also face challenges, such as tumor heterogeneity and limited tumor penetration. An innovative strategy to address these challenges combines both agents in a single, multitasking therapeutic, i.e., an oncolytic virus engineered to express therapeutic antibodies. Such viro-antibody therapies genetically deliver antibodies to tumors from amplified virus genomes, thereby complementing viral oncolysis with antibody-defined therapeutic action. Here, we review the strategies of viro-antibody therapy that have been pursued exploiting diverse virus platforms, antibody formats, and antibody-mediated modes of action. We provide a comprehensive overview of reported antibody-encoding oncolytic viruses and highlight the achievements of 13 years of viro-antibody research. It has been shown that functional therapeutic antibodies of different formats can be expressed in and released from cancer cells infected with different oncolytic viruses. Virus-encoded antibodies have implemented direct tumor cell killing, anti-angiogenesis, or activation of adaptive immune responses to kill tumor cells, tumor stroma cells or inhibitory immune cells. Importantly, numerous reports have shown therapeutic activity complementary to viral oncolysis for these modalities. Also, challenges for future research have been revealed. Established engineering technologies for both oncolytic viruses and antibodies will enable researchers to address these challenges, facilitating the development of effective viro-antibody therapeutics.

Accelerating target deconvolution for therapeutic antibody candidates using highly parallelized genome editing

Therapeutic antibodies are transforming the treatment of cancer and autoimmune diseases. Today, a key challenge is finding antibodies against new targets. Phenotypic discovery promises to achieve this by enabling discovery of antibodies with therapeutic potential without specifying the molecular target a priori. Yet, deconvoluting the targets of phenotypically discovered antibodies remains a bottleneck; efficient deconvolution methods are needed for phenotypic discovery to reach its full potential. Here, we report a comprehensive investigation of a target deconvolution approach based on pooled CRISPR/Cas9. Applying this approach within three real-world phenotypic discovery programs, we rapidly deconvolute the targets of 38 of 39 test antibodies (97%), a success rate far higher than with existing approaches. Moreover, the approach scales well, requires much less work, and robustly identifies antibodies against the major histocompatibility complex. Our data establish CRISPR/Cas9 as a highly efficient target deconvolution approach, with immediate implications for the development of antibody-based drugs.

Efficient deconvolution of antibody targets is needed for phenotype-based discovery. Here, the authors investigate a deconvolution approach based on pooled CRISPR Cas9 to achieve 97% deconvolution success rate.