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Elimination of the binding of immunoglobulin Fc to Fc gamma receptors is highly desirable for the avoidance of unwanted inflammatory responses to therapeutic antibodies and fusion proteins. Many different approaches have been used in the clinic, but they have not been systematically compared. We have now produced a matched set of anti-CD20 antibodies with different Fc subclasses and variants and compared their activity for binding to C1q, Fc-gamma receptors and in cell-based assays. Most of the variants still have significant levels of activity in one or more of these assays and many of them have impaired temperature stability compared with the corresponding wild-type antibody.

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Myasthenia gravis (MG) is a chronic and severe disease of the skeletal neuromuscular junction (NMJ) in which the effects of neurotransmitters are attenuated, leading to muscle weakness. In the most common forms of autoimmune MG, antibodies attack components of the postsynaptic membrane, including the acetylcholine receptor (AChR) or muscle-specific kinase (MuSK). MuSK, a master regulator of NMJ development, associates with the low-density lipoprotein-related receptor 4 (Lrp4) to form the signaling receptor for neuronal Agrin, a nerve-derived synaptic organizer. Pathogenic antibodies to MuSK interfere with binding between MuSK and Lrp4, inhibiting the differentiation and maintenance of the NMJ. MuSK MG can be debilitating and refractory to treatments that are effective for AChR MG. We show here that recombinant antibodies, derived from MuSK MG patients, cause severe neuromuscular disease in mice. The disease can be prevented by a MuSK agonist antibody, presented either prophylactically or after disease onset. These findings suggest a therapeutic alternative to generalized immunosuppression for treating MuSK MG by selectively and directly targeting the disease mechanism.

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Therapeutic antibodies (Abs) have been anticipated as promising alternatives to conventional treatments such as topical minoxidil and oral finasteride for androgenetic alopecia (AGA). Due to the high molecular weight of typical Abs, the half-life of subcutaneous Abs exceeds 2 weeks, allowing an administration intervals of once a month or longer. Direct injection into the areas of hair loss is also feasible, potentially enhancing treatment efficacy while minimizing systemic side effects. However, therapeutic Abs are rarely developed for AGA therapy due to the requirement to be responsiveness to androgens and to exist in the extracellular fluid or cell surface surrounding the hair follicle. In this review, we introduce recent progress of antibody therapeutics in AGA targeting the prolactin receptor, Interleukin-6 receptor, C-X-C motif chemokine ligand 12, and dickkopf 1. As therapeutic Abs for AGA are still in the early stages, targets need further validation and optimization for clinical application.

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Therapeutics for eradicating hepatitis B virus (HBV) infection are still limited and current nucleos(t)ide analogs (NAs) and interferon are effective in controlling viral replication and improving liver health, but they cannot completely eradicate the hepatitis B virus and only a very small number of patients are cured of it. The TCR-like antibodies recognizing viral peptides presented on human leukocyte antigens (HLA) provide possible tools for targeting and eliminating HBV-infected hepatocytes. Here, we generated three TCR-like antibodies targeting three different HLA-A2.1-presented peptides derived from HBV core and surface proteins. Bispecific antibodies (BsAbs) were developed by fuzing variable fragments of these TCR-like mAbs with an anti-CD3ϵ antibody. Our data demonstrate that the BsAbs could act as T cell engagers, effectively redirecting and activating T cells to target HBV-infected hepatocytes in vitro and in vivo. In HBV-persistent mice expressing human HLA-A2.1, two infusions of BsAbs induced marked and sustained suppression in serum HBsAg levels and also reduced the numbers of HBV-positive hepatocytes. These findings highlighted the therapeutic potential of TCR-like BsAbs as a new strategy to cure hepatitis B.

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The Fc region of antibodies is vital for most of their physiological functions, many of which are engaged through binding to a range of Fc receptors. However, these same interactions are not always helpful or wanted when therapeutic antibodies are directed against self-antigens, and can sometimes cause catastrophic adverse reactions. Over the past 40 years, there have been intensive efforts to "silence" unwanted binding to Fc-gamma receptors, resulting in at least 45 different variants which have entered clinical trials. One of the best known is "LALA" (L234A/L235A). However, neither this, nor most of the other variants in clinical use are completely silenced, and in addition, the biophysical properties of many of them are compromised. I review the development of different variants to see what we can learn from their biological properties and use in the clinic. With the rise of powerful new uses of antibody therapy such as bispecific T-cell engagers, antibody-drug conjugates, and checkpoint inhibitors, it is increasingly important to optimize the Fc region as well as the antibody binding site in order to achieve the best combination of safety and efficacy.

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The emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and onset of the coronavirus disease-19 (COVID-19) pandemic led to an immediate need for therapeutic treatment options. Therapeutic antibodies were developed to fill a gap when traditional antivirals were not available. In late 2020, the United States Government undertook an effort to compare candidate therapeutic antibodies in virus neutralization assays and in the hamster model of SARS-CoV-2 infection. With the emergence of SARS-CoV-2 variants, the effort expanded to evaluate the efficacy of nearly 50 products against major variants. A subset of products was further evaluated for therapeutic efficacy in hamsters. Here we report results of the hamster studies, including pathogenicity with multiple variants, neutralization capacity of products, and efficacy testing of products against Delta and Omicron variants. These studies demonstrate the loss of efficacy of early products with variant emergence and support the use of the hamster model for evaluating therapeutics.

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Recombinant SARS-CoV-2 S protein expression was examined in Vero cells by imaging using the human monoclonal antibody panel (PD4, PD5, sc23, and sc29). The PD4 and sc29 antibodies recognised conformational specific epitopes in the S2 protein subunit at the Endoplasmic reticulum and Golgi complex. While PD5 and sc23 detected conformationally specific epitopes in the S1 protein subunit at the Golgi complex, only PD5 recognised the receptor binding domain (RBD). A comparison of the staining patterns of PD5 with non-conformationally specific antibodies that recognises the S1 subunit and RBD suggested the PD5 recognised a conformational structure within the S1 protein subunit. Our data suggests the antibody binding epitopes recognised by the human monoclonal antibodies formed at different locations in the secretory pathway during S protein transport, but a conformational change in the S1 protein subunit at the Golgi complex formed antibody binding epitopes that are recognised by virus neutralising antibodies.

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Tissue cross-reactivity (TCR) studies for the development of therapeutic antibodies are conducted to estimate any possible binding sites within the human body that can be affected by the antibody when assessing safety in humans. Any possible binding sites include specific binding sites of the antibody to its target antigen and nonspecific or off-target binding sites. In TCR studies the therapeutic antibodies and immunohistochemistry (IHC) of frozen tissues must be applied in assays. However, there are technical issues with applying a therapeutic antibody or test article to IHC, such as human-on-human staining, difficulty in applying the test article to IHC, and retention of the target antigen in frozen sections. In the current review, we introduce three case studies in which these technical issues were addressed, and propose a practical scheme for points to consider when conducting a TCR study. Information on the target antigen distribution obtained through robust assays and case-by-case strategies were found to be useful for understanding and assessing the relevance of toxic effects between animals and humans. Thus, we anticipate that by considering the points discussed in the current review and combining the data with information on the biological features of the target antigens and therapeutic antibodies, it will be possible to predict safety risks in humans with higher accuracy.

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The optimization of therapeutic antibodies through traditional techniques, such as candidate screening via hybridoma or phage display, is resource-intensive and time-consuming. In recent years, computational and artificial intelligence-based methods have been actively developed to accelerate and improve the development of therapeutic antibodies. In this study, we developed an end-to-end sequence-based deep learning model, termed AttABseq, for the predictions of the antigen-antibody binding affinity changes connected with antibody mutations. AttABseq is a highly efficient and generic attention-based model by utilizing diverse antigen-antibody complex sequences as the input to predict the binding affinity changes of residue mutations. The assessment on the three benchmark datasets illustrates that AttABseq is 120% more accurate than other sequence-based models in terms of the Pearson correlation coefficient between the predicted and experimental binding affinity changes. Moreover, AttABseq also either outperforms or competes favorably with the structure-based approaches. Furthermore, AttABseq consistently demonstrates robust predictive capabilities across a diverse array of conditions, underscoring its remarkable capacity for generalization across a wide spectrum of antigen-antibody complexes. It imposes no constraints on the quantity of altered residues, rendering it particularly applicable in scenarios where crystallographic structures remain unavailable. The attention-based interpretability analysis indicates that the causal effects of point mutations on antibody-antigen binding affinity changes can be visualized at the residue level, which might assist automated antibody sequence optimization. We believe that AttABseq provides a fiercely competitive answer to therapeutic antibody optimization.

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The multiattribute method (MAM) has emerged as a powerful tool for simultaneously screening multiple product quality attributes of therapeutic antibodies. One such potential critical quality attribute (CQA) is glycation, a common modification that can impact the heterogeneity, functional activity, and immunogenicity of therapeutic antibodies. However, current methods for monitoring glycation levels in MAM are rare and not sufficiently rapid and accurate. In this study, an improved mass spectrometry (MS)-based MAM was developed to simultaneously monitor glycation and other quality attributes including afucosylation. The method was evaluated using two therapeutic antibodies with different glycosylation site numbers. Treatment with IdeS, Endo F2, and dithiothreitol generated three distinct subunits, and the glycation results obtained were similar to those treated with PNGase F, which is routinely used to release glycans; the sample processing time was greatly reduced while providing additional quality attribute information. The MS-based MAM was also employed to assess the glycation progression following forced glycation in various buffer solutions. A significant increase in oxidation was observed when forced glycation was conducted in an ammonium bicarbonate buffer solution, and a total of 23 potential glycation sites and 4 significantly oxidized sites were identified. Notably, we found that ammonium bicarbonate was found to specifically stimulate oxidation, while glycation had a synergistic effect on oxidation. These findings establish this study as a novel methodology for achieving a technologically advanced platform and concept that enhances the efficacy of product development and quality control, characterized by its broad-spectrum, rapid, and accurate nature.

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Therapeutic antibodies are an important class of biopharmaceuticals. With the rapid development of deep learning methods and the increasing amount of antibody data, antibody generative models have made great progress recently. They aim to solve the antibody space searching problems and are widely incorporated into the antibody development process. Therefore, a comprehensive introduction to the development methods in this field is imperative. Here, we collected 34 representative antibody generative models published recently and all generative models can be divided into three categories: sequence-generating models, structure-generating models, and hybrid models, based on their principles and algorithms. We further studied their performance and contributions to antibody sequence prediction, structure optimization, and affinity enhancement. Our manuscript will provide a comprehensive overview of the status of antibody generative models and also offer guidance for selecting different approaches.

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Drug product development of therapeutic antibody formulations is still dictated by the risk of protein particle formation during processing or storage, which can lead to loss of potency and potential immunogenic reactions. Since structural perturbations are the main driver for irreversible protein aggregation, the conformational integrity of antibodies should be closely monitored. The present study evaluated the applicability of a plate reader-based high throughput method for Intrinsic Tryptophan Fluorescence Emission (ITFE) spectroscopy to detect protein aggregation due to protein unfolding in high-concentrated therapeutic antibody samples. The impact of fluorophore concentration on the ITFE signal in microplate readers was investigated by analysis of dilution series of two therapeutic antibodies and pure tryptophan. At low antibody concentrations (< 5 mg/mL, equivalent to 0.8 mM tryptophan), the low inner filter effect suggests a quasi-linear relationship between antibody concentration and ITFE intensity. In contrast, the constant ITFE intensity at high protein concentrations (> 40 mg/mL, equivalent to 6.1 mM tryptophan) indicate that ITFE spectroscopy measurements of IgG1 antibodies are feasible in therapeutically relevant concentrations (up to 223 mg/mL). Furthermore, the capability of the method to detect low levels of unfolding (around 1 %) was confirmed by limit of detection (LOD) determination with temperature-stressed antibody samples as degradation standards. Change of fluorescence intensity at the maximum (ΔIaM) was identified as sensitive descriptor for protein degradation, providing the lowest LOD values. The results demonstrate that ITFE spectroscopy performed in a microplate reader is a valuable tool for high-throughput monitoring of protein degradation in therapeutic antibody formulations.

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Precise measurement of the binding activity changes of therapeutic antibodies is important to determine the potential critical quality attributes (CQAs) in developability assessment at the early stage of antibody development. Here, we report a surface plasmon resonance (SPR)-based relative binding activity method, which incorporates both binding affinity and binding response and allows us to determine relative binding activity of antibodies with high accuracy and precision. We applied the SPR-based relative binding activity method in multiple forced degradation studies of antibody developability assessment. The current developability assessment strategy provided comprehensive, precise characterization of antibody binding activity in the stability studies, enabling us to perform correlation analysis and establish the structure-function relationship between relative binding activity and quality attributes. The impact of a given quality attribute on binding activity could be confidently determined without isolating antibody variants. We identified several potential CQAs, including Asp isomerization, Asn deamidation, and fragmentation. Some potential CQAs affected binding affinity of antibody and resulted in a reduction of binding activity. Certain potential CQAs impaired antibody binding to antigen and led to a loss of binding activity. A few potential CQAs could influence both binding affinity and binding response and cause a substantial decrease in antibody binding activity. Specifically, we identified low abundance Asn33 deamidation in the light chain complementarity-determining region as a potential CQA, in which all the stressed antibody samples showed Asn33 deamidation abundances ranging from 4.2% to 27.5% and a mild binding affinity change from 1.76 nM to 2.16 nM.

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Through machine learning, identifying correlations between amino acid sequences of antibodies and their observed characteristics, we developed an internal viscosity prediction model to empower the rapid engineering of therapeutic antibody candidates. For a highly viscous anti-IL-13 monoclonal antibody, we used a structure-based rational design strategy to generate a list of variants that were hypothesized to mitigate viscosity. Our viscosity prediction tool was then used as a screen to cull virtually engineered variants with a probability of high viscosity while advancing those with a probability of low viscosity to production and testing. By combining the rational design engineering strategy with the in silico viscosity prediction screening step, we were able to efficiently improve the highly viscous anti-IL-13 candidate, successfully decreasing the viscosity at 150 mg/mL from 34 cP to 13 cP in a panel of 16 variants.

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The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) heavily burdens human health. Multiple neutralizing antibodies (nAbs) have been issued for emergency use or tested for treating infected patients in the clinic. However, SARS-CoV-2 variants of concern (VOC) carrying mutations reduce the effectiveness of nAbs by preventing neutralization. Uncoding the mutation profile and immune evasion mechanism of SARS-CoV-2 can improve the outcome of Ab-mediated therapies. In this review, we first outline the development status of anti-SARS-CoV-2 Ab drugs and provide an overview of SARS-CoV-2 variants and their prevalence. We next focus on the failure causes of anti-SARS-CoV-2 Ab drugs and rethink the design strategy for developing new Ab drugs against COVID-19. This review provides updated information for the development of therapeutic Ab drugs against SARS-CoV-2 variants.

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BACKGROUND: Therapeutic drug monitoring of treatment with therapeutic antibodies is hampered by the application of a wide range of different methods in the quantification of serum levels. LC-MS based methods could significantly improve comparability of results from different laboratories, but such methods are often considered complicated and costly. We developed a method for LC-MS/MS based quantification of 11 therapeutic antibodies concomitantly measured in a single run, with emphasis on simplicity in sample preparation and low cost. RESULTS: After a single-step sample purification using caprylic acid precipitation to remove interfering proteins, the sample underwent proteolysis followed by LC-MS/MS analysis. Infliximab is used as internal standard for sample preparation while isotope-labeled signature peptides identified for each analyte are internal standards for the LC-MS/MS normalization. The method was validated according to recognized guidelines, and pipetting steps can be performed by automated liquid handling systems. The total precision of the method ranged between 2.7 and 7.3 % (5.1 % average) across the quantification range of 4-256 µg/ml for all 11 drugs, with an average accuracy of 96.3 %. Matrix effects were xamined in 55 individual patient samples instead of the recommended 6, and 147 individual patient samples were screened for interfering compounds. SIGNIFICANCE AND NOVELTY: Our method for simultaneous quantification of 11 t-mAb in human serum allows an unprecedented integration of robustness, speed and reduced complexity, which could pave the way for uniform use in research projects and clinical settings alike. In addition, the first LC-MS protocol for signature peptide-based quantification of durvalumab is described. This high throughput method can be readily adapted to a drug panel of choice.

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BACKGROUND: The use of single-chain variable fragments (scFvs) for treating human diseases, such as cancer and immune system disorders, has attracted significant attention. However, a critical drawback of scFv is its extremely short serum half-life, which limits its therapeutic potential. Thus, there is a critical need to prolong the serum half-life of the scFv for clinical applications. One promising serum half-life extender for therapeutic proteins is human serum albumin (HSA), which is the most abundant protein in human serum, known to have an exceptionally long serum half-life. However, conjugating a macromolecular half-life extender to a small protein, such as scFv, often results in a significant loss of its critical properties. RESULTS: In this study, we conjugated the HSA to a permissive site of scFv to improve pharmacokinetic profiles. To ensure minimal damage to the antigen-binding capacity of scFv upon HSA conjugation, we employed a site-specific conjugation approach using a heterobifunctional crosslinker that facilitates thiol-maleimide reaction and inverse electron-demand Diels-Alder reaction (IEDDA). As a model protein, we selected 4D5scFv, derived from trastuzumab, a therapeutic antibody used in human epithermal growth factor 2 (HER2)-positive breast cancer treatment. We introduced a phenylalanine analog containing a very reactive tetrazine group (frTet) at conjugation site candidates predicted by computational methods. Using the linker TCO-PEG4-MAL, a single HSA molecule was site-specifically conjugated to the 4D5scFv (4D5scFv-HSA). The 4D5scFv-HSA conjugate exhibited HER2 binding affinity comparable to that of unmodified 4D5scFv. Furthermore, in pharmacokinetic profile in mice, the serum half-life of 4D5scFv-HSA was approximately 12 h, which is 85 times longer than that of 4D5scFv. CONCLUSIONS: The antigen binding results and pharmacokinetic profile of 4D5scFv-HSA demonstrate that the site-specifically albumin-conjugated scFv retained its binding affinity with a prolonged serum half-life. In conclusion, we developed an effective strategy to prepare site-specifically albumin-conjugated 4D5scFv, which can have versatile clinical applications with improved efficacy.

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Advanced biopharmaceutical manufacturing requires novel process analytical technologies for the rapid and sensitive assessment of the higher-order structures of therapeutic proteins. However, conventional physicochemical analyses of denatured proteins have limitations in terms of sensitivity, throughput, analytical resolution, and real-time monitoring capacity. Although probe-based sensing can overcome these limitations, typical non-specific probes lack analytical resolution and provide little to no information regarding which parts of the protein structure have been collapsed. To meet these analytical demands, we generated biosensing probes derived from artificial proteins that could specifically recognize the higher-order structural changes in antibodies at the protein domain level. Biopanning of phage-displayed protein libraries generated artificial proteins that bound to a denatured antibody domain, but not its natively folded structure, with nanomolar affinity. The protein probes not only recognized the higher-order structural changes in intact IgGs but also distinguished between the denatured antibody domains. These domain-specific probes were used to generate response contour plots to visualize the antibody denaturation caused by various process parameters, such as pH, temperature, and holding time for acid elution and virus inactivation. These protein probes can be combined with established analytical techniques, such as surface plasmon resonance for real-time monitoring or plate-based assays for high-throughput analysis, to aid in the development of new analytical technologies for the process optimization and monitoring of antibody manufacturing.

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Therapeutic antibodies (Abs) improve the clinical outcome of cancer patients. However, on-target off-tumor toxicity limits Ab-based therapeutics. Cluster of differentiation 147 (CD147) is a tumor-associated membrane antigen overexpressed in cancer cells. Ab-based drugs targeting CD147 have achieved inadequate clinical benefits for liver cancer due to side effects. Here, by using glycoengineering and hypoxia-activation strategies, we developed a conditional Ab-dependent cellular cytotoxicity (ADCC)-enhanced humanized anti-CD147 Ab, HcHAb18-azo-PEG5000 (HAP18). Afucosylated ADCC-enhanced HcHAb18 Ab was produced by a fed-batch cell culture system. Azobenzene (Azo)-linked PEG5000 conjugation endowed HAP18 Ab with features of hypoxia-responsive delivery and selective targeting. HAP18 Ab potently inhibits the migration, invasion, and matrix metalloproteinase secretion, triggers the cytotoxicity and apoptosis of cancer cells, and induces ADCC, complement-dependent cytotoxicity, and Ab-dependent cellular phagocytosis under hypoxia. In xenograft mouse models, HAP18 Ab selectively targets hypoxic liver cancer tissues but not normal organs or tissues, and has potent tumor-inhibiting effects. HAP18 Ab caused negligible side effects and exhibited superior pharmacokinetics compared to those of parent HcHAb18 Ab. The hypoxia-activated ADCC-enhanced humanized HAP18 Ab safely confers therapeutic efficacy against liver cancer with improved selectivity. This study highlights that hypoxia activation is a promising strategy for improving the tumor targeting potential of anti-CD147 Ab drugs.

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Resistance to therapeutic antibodies caused by on-target point mutations is a major obstacle in anticancer therapy, creating an "unmet clinical need." To tackle this problem, researchers are developing new generations of antibody drugs that can overcome the resistance mechanisms of existing agents. We have previously reported a structure-guided and phage-assisted evolution (SGAPAE) approach to evolve cetuximab, a therapeutic antibody, to effectively reverse the resistance driven by EGFRS492R or EGFRG465R mutations, without changing the binding epitope or compromising the antibody efficacy. In this protocol, we provide detailed instructions on how to use the SGAPAE approach to evolve cetuximab, which can also be applied to other therapeutic antibodies for reversing on-target point mutation-mediated resistance. The protocol consists of four steps: structure preparation, computational prediction, phage display library construction, and antibody candidate selection.

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