Antibody Therapeutics最新文献

[This corrects the article DOI: 10.1093/abt/tbae013.].

Background: Single domain antibodies (sdAbs) possess unique characteristics that make them highly effective for developing complex therapeutics.

Methods: Our process uses a fully synthetic phage display library to generate single domain antibodies that can bind to disease relevant antigen conformations. A human IGHV3 family scaffold makes up the phage display libraries, and these VHO libraries are applied to diverse phage biopannings against target antigens. After NGS processing, unique VHOs undergo automated cloning into expression constructs followed by transfections and purifications. Binding assays were used to determine VHO binding behaviors to the target proteins. Additional VHO interactions are measured against endogenous targets on cells by way of flow cytometry, cell internalization, and activation assays.

Results: We show that a fully synthetic phage display library can generate VHOs that bind to disease relevant antigen conformations. The diverse biopanning methods and processing of next-generation sequencing generated many VHO paratopes. These different VHO sequences can be expressed as Fc fusion proteins. Various screening assays resulted in VHOs representing different epitopes or activities. During the hit evaluation, we demonstrate how screening can identify distinct VHO activities that have been used to generate differentiated drug molecules in various bispecific and multispecific antibody formats.

Conclusion: We demonstrate how screening can identify distinct VHO activities that have been used to generate differentiated drug molecules in various bispecific and multispecific antibody formats.

Despite their triumph in treating human diseases, antibody therapies for animals have gained momentum more slowly. However, the first approvals of animal antibodies for osteoarthritic pain in cats and dogs may herald the dawn of a new era. For example, goats are vital to economies around the world for their milk, meat, and hide products. It is therefore imperative to develop therapies to safeguard goats-with antibodies at the forefront. Goat antibodies will be crucial in the development of therapeutic antibodies, for example, as tracers to study antibody distribution in vivo, reagents to develop other therapeutic antibodies, and therapeutic agents themselves (e.g., antibody-drug conjugates). Hamstringing this effort is a still-burgeoning understanding of goat antibodies and their derivatization. Historically, goat antibody conjugates were generated through stochastic chemical modifications, producing numerous attachment sites and modification ratios, thereby deleteriously impacting antigen binding. Site-specific methods exist but often require substantial engineering and have not been demonstrated with goat antibodies. Nevertheless, we present herein a novel method to site-specifically conjugate native goat antibodies: chemo-enzymatic remodeling of the native Fc N-glycan introduces a reactive azide handle, after which click chemistry with strained alkyne partners affords homogeneous conjugates labeled only on the Fc domain. This process is robust, and resulting conjugates retain their antigen binding and specificity. To our knowledge, our report is the first for site-specific conjugation of native goat antibodies. Furthermore, our approach should be applicable to other animal antibodies-even with limited structural information-with similar success.

Background: Several HER2-targeting antibody-drug conjugates (ADC) have gained market approval for the treatment of HER2-expressing metastasis. Promising responses have been reported with the new generation of ADCs in patients who do not respond well to other HER2-targeting therapeutics. However, these ADCs still face challenges of resistance and/or severe adverse effects associated with their particular payload toxins. Eribulin, a therapeutic agent for the treatment of metastatic breast cancer and liposarcoma, is a new choice of ADC payload with a distinct mechanism of action and safety profile.

Methods: We've generated a novel HER2-tageting eribulin-containing ADC, BB-1701. The potency of BB-1701 was tested in vitro and in vivo against cancer cells where HER2-expressing levels vary in a large range. Bystander killing effect and toxin-induced immunogenic cell death (ICD) of BB-1701 were also tested.

Results: In comparison with HER2-targeting ADCs with DM1 and Dxd payload, eribulin-containing ADC demonstrated higher in vitro cytotoxicity in HER2-low cancer cell lines. BB-1701 also effectively suppressed tumors in models resistant to DM1 or Dxd containing ADCs. Mode of action studies showed that BB-1701 had a significant bystander effect on HER2-null cells adjacent to HER2-high cells. In addition, BB-1701 treatment induced ICD. Repeated doses of BB-1701 in nonhuman primates showed favorable pharmacokinetics and safety profiles at the intended clinical dosage, route of administration, and schedule.

Conclusions: The preclinical data support the test of BB-1701 in patients with various HER2-expressing cancers, including those resistant to other HER2-targeting ADCs. A phase I clinical trial of BB-1701 (NCT04257110) in patients is currently underway.

Fc optimization can significantly enhance therapeutic efficacy of monoclonal antibodies. However, existing Fc engineering approaches are sub-optimal with noted limitations, such as inappropriate glycosylation, polyclonal libraries, and utilizing fragment but not full-length IgG display. Applying cell cycle arrested recombinase-mediated cassette exchange, this study constructed high-quality monoclonal Fc libraries in CHO cells, displayed full-length IgG on cell surface, and preformed ratiometric fluorescence activated cell sorting (FACS) with the antigen and individual FcγRs. Identified Fc variants were quantitatively evaluated by flow cytometry, ELISA, kinetic and steady-state binding affinity measurements, and cytotoxicity assays. An error-prone Fc library focusing on the hinge-C_H2 region was constructed in CHO cells with a functional diversity of 7.5 × 10⁶. Panels of novel Fc variants with enhanced affinity and selectivity for FcγRs were isolated. Particularly, clone 2a-10 (G236E/K288R/K290W/K320M) showed increased binding strength towards FcγRIIa-131R and 131H allotypes with kinetic dissociation constants (K_D-K) of 140 nM and 220 nM, respectively, while reduced binding strength towards FcγRIIb compared to WT Fc; clone 2b-1 (K222I/V302E/L328F/K334E) had K_D-K of 180 nM towards FcγRIIb; clone 3a-2 (P247L/K248E/K334I) exhibited K_D-K of 190 nM and 100 nM towards FcγRIIIa-176F and 176 V allotypes, respectively, and improved potency of 2.0 ng/ml in ADCC assays. Key mutation hotspots were identified, including P247 for FcγRIIIa, K290 for FcγRIIa, and K334 for FcγRIIb bindings. Discovery of Fc variants with enhanced affinity and selectivity towards individual FcγR and the identification of novel mutation hotspots provide valuable insights for further Fc optimization and serve as a foundation for advancing antibody therapeutics development.

[This corrects the article DOI: 10.1093/abt/tbae005.].

Cancer immunotherapy represents a paradigm shift in oncology, offering a superior anti-tumor efficacy and the potential for durable remission. The success of personalized vaccines and cell therapies hinges on the identification of immunogenic epitopes capable of eliciting an effective immune response. Current limitations in the availability of immunogenic epitopes restrict the broader application of such therapies. A critical criterion for serving as potential cancer antigens is their ability to stably bind to the major histocompatibility complex (MHC) for presentation on the surface of tumor cells. To address this, we have developed a comprehensive database of MHC epitopes, experimentally validated for their MHC binding and cell surface presentation. Our database catalogs 451 065 MHC peptide epitopes, each with experimental evidence for MHC binding, along with detailed information on human leukocyte antigen allele specificity, source peptides, and references to original studies. We also provide the grand average of hydropathy scores and predicted immunogenicity for the epitopes. The database (MHCepitopes) has been made available on the web and can be accessed at https://github.com/jcm1201/MHCepitopes.git. By consolidating empirical data from various sources coupled with calculated immunogenicity and hydropathy values, our database offers a robust resource for selecting actionable tumor antigens and advancing the design of antigen-specific cancer immunotherapies. It streamlines the process of identifying promising immunotherapeutic targets, potentially expediting the development of effective antigen-based cancer immunotherapies.

Background: Early assessment of antibody off-target binding is essential for mitigating developability risks such as fast clearance, reduced efficacy, toxicity, and immunogenicity. The baculovirus particle (BVP) binding assay has been widely utilized to evaluate polyreactivity of antibodies. As a complementary approach, computational prediction of polyreactivity is desirable for counter-screening antibodies from in silico discovery campaigns. However, there is a lack of such models.

Methods: Herein, we present the development of an ensemble of three deep learning models based on two pan-protein foundational protein language models (ESM2 and ProtT5) and an antibody-specific protein language model (PLM) (Antiberty). These models were trained in a transfer learning network to predict the outcomes in the BVP assay and the bovine serum albumin binding assay, which was developed as a complement to the BVP assay. The training was conducted on a large dataset of antibody sequences augmented with experimental conditions, which were collected through a highly efficient application system.

Results: The resulting models demonstrated robust performance on canonical mAbs (monospecific with heavy and light chain), bispecific Abs, and single-domain Fc (VHH-Fc). PLMs outperformed a model built using molecular descriptors calculated from AlphaFold 2 predicted structures. Embeddings from the antibody-specific and foundational PLMs resulted in similar performance.

Conclusion: To our knowledge, this represents the first application of PLMs to predict assay data on bispecifics and VHH-Fcs.