Development Of Therapeutic Antibodies Research Articles

Accurate prediction of antibody function and structure using bio-inspired antibody language model.

In recent decades, antibodies have emerged as indispensable therapeutics for combating diseases, particularly viral infections. However, their development has been hindered by limited structural information and labor-intensive engineering processes. Fortunately, significant advancements in deep learning methods have facilitated the precise prediction of protein structure and function by leveraging co-evolution information from homologous proteins. Despite these advances, predicting the conformation of antibodies remains challenging due to their unique evolution and the high flexibility of their antigen-binding regions. Here, to address this challenge, we present the Bio-inspired Antibody Language Model (BALM). This model is trained on a vast dataset comprising 336 million 40% nonredundant unlabeled antibody sequences, capturing both unique and conserved properties specific to antibodies. Notably, BALM showcases exceptional performance across four antigen-binding prediction tasks. Moreover, we introduce BALMFold, an end-to-end method derived from BALM, capable of swiftly predicting full atomic antibody structures from individual sequences. Remarkably, BALMFold outperforms those well-established methods like AlphaFold2, IgFold, ESMFold and OmegaFold in the antibody benchmark, demonstrating significant potential to advance innovative engineering and streamline therapeutic antibody development by reducing the need for unnecessary trials. The BALMFold structure prediction server is freely available at https://beamlab-sh.com/models/BALMFold.

DeepSP: Deep learning-based spatial properties to predict monoclonal antibody stability

Therapeutic antibody development faces challenges due to high viscosities and aggregation tendencies. The spatial charge map (SCM) and spatial aggregation propensity (SAP) are computational techniques that aid in predicting viscosity and aggregation, respectively. These methods rely on structural data derived from molecular dynamics (MD) simulations, which are computationally demanding. DeepSCM, a deep learning surrogate model based on sequence information to predict SCM, was recently developed to screen high-concentration antibody viscosity. This study further utilized a dataset of 20,530 antibody sequences to train a convolutional neural network deep learning surrogate model called Deep Spatial Properties (DeepSP). DeepSP directly predicts SAP and SCM scores in different domains of antibody variable regions based solely on their sequences without performing MD simulations. The linear correlation coefficient between DeepSP scores and MD-derived scores for 30 properties achieved values between 0.76 and 0.96 with an average of 0.87. DeepSP descriptors were employed as features to build machine learning models to predict the aggregation rate of 21 antibodies, and the performance is similar to the results obtained from the previous study using MD simulations. This result demonstrates that the DeepSP approach significantly reduces the computational time required compared to MD simulations. The DeepSP model enables the rapid generation of 30 structural properties that can also be used as features in other research to train machine learning models for predicting various antibody stability using sequences only. DeepSP is freely available as an online tool via https://deepspwebapp.onrender.com and the codes and parameters are freely available at https://github.com/Lailabcode/DeepSP.

Prediction of polyspecificity from antibody sequence data by machine learning.

Antibodies are generated with great diversity in nature resulting in a set of molecules, each optimized to bind a specific target. Taking advantage of their diversity and specificity, antibodies make up for a large part of recently developed biologic drugs. For therapeutic use antibodies need to fulfill several criteria to be safe and efficient. Polyspecific antibodies can bind structurally unrelated molecules in addition to their main target, which can lead to side effects and decreased efficacy in a therapeutic setting, for example via reduction of effective drug levels. Therefore, we created a neural-network-based model to predict polyspecificity of antibodies using the heavy chain variable region sequence as input. We devised a strategy for enriching antibodies from an immunization campaign either for antigen-specific or polyspecific binding properties, followed by generation of a large sequencing data set for training and cross-validation of the model. We identified important physico-chemical features influencing polyspecificity by investigating the behaviour of this model. This work is a machine-learning-based approach to polyspecificity prediction and, besides increasing our understanding of polyspecificity, it might contribute to therapeutic antibody development.

Rapid development of double-hit mRNA antibody cocktail against orthopoxviruses

The Orthopoxvirus genus, especially variola virus (VARV), monkeypox virus (MPXV), remains a significant public health threat worldwide. The development of therapeutic antibodies against orthopoxviruses is largely hampered by the high cost of antibody engineering and manufacturing processes. mRNA-encoded antibodies have emerged as a powerful and universal platform for rapid antibody production. Herein, by using the established lipid nanoparticle (LNP)-encapsulated mRNA platform, we constructed four mRNA combinations that encode monoclonal antibodies with broad neutralization activities against orthopoxviruses. In vivo characterization demonstrated that a single intravenous injection of each LNP-encapsulated mRNA antibody in mice resulted in the rapid production of neutralizing antibodies. More importantly, mRNA antibody treatments showed significant protection from weight loss and mortality in the vaccinia virus (VACV) lethal challenge mouse model, and a unique mRNA antibody cocktail, Mix2a, exhibited superior in vivo protection by targeting both intracellular mature virus (IMV)-form and extracellular enveloped virus (EEV)-form viruses. In summary, our results demonstrate the proof-of-concept production of orthopoxvirus antibodies via the LNP-mRNA platform, highlighting the great potential of tailored mRNA antibody combinations as a universal strategy to combat orthopoxvirus as well as other emerging viruses.

DOTAD: A Database of Therapeutic Antibody Developability.

The development of therapeutic antibodies is an important aspect of new drug discovery pipelines. The assessment of an antibody's developability-its suitability for large-scale production and therapeutic use-is a particularly important step in this process. Given that experimental assays to assess antibody developability in large scale are expensive and time-consuming, computational methods have been a more efficient alternative. However, the antibody research community faces significant challenges due to the scarcity of readily accessible data on antibody developability, which is essential for training and validating computational models. To address this gap, DOTAD (Database Of Therapeutic Antibody Developability) has been built as the first database dedicated exclusively to the curation of therapeutic antibody developability information. DOTAD aggregates all available therapeutic antibody sequence data along with various developability metrics from the scientific literature, offering researchers a robust platform for data storage, retrieval, exploration, and downloading. In addition to serving as a comprehensive repository, DOTAD enhances its utility by integrating a web-based interface that features state-of-the-art tools for the assessment of antibody developability. This ensures that users not only have access to critical data but also have the convenience of analyzing and interpreting this information. The DOTAD database represents a valuable resource for the scientific community, facilitating the advancement of therapeutic antibody research. It is freely accessible at http://i.uestc.edu.cn/DOTAD/ , providing an open data platform that supports the continuous growth and evolution of computational methods in the field of antibody development.

Abstract 2821: Development of therapeutic monoclonal antibodies against DKK1 peptide-HLA-A2 complex to treat human cancers

Abstract Immunotherapy is a promising option for cancer treatment. Targeted immunotherapy with monoclonal antibodies (mAbs) is an effective and safe method for the treatment of malignancies. In recent years, efforts have been made to identify potential therapeutic mAbs by defining alternative or novel target antigens. We reported that Dickkopf-1 (DKK1) is a good target for immunotherapy of human cancers based on its wide expression in different cancers but not in normal tissues. As DKK1 is a secreted protein, mAbs directly binding to DKK1 may have limited effects on cancer cells in vivo. Our previous studies demonstrated that DKK1 peptide (such as P20 and P66v, which bind with HLA-A*0201 (HLA-A2) molecule) specific cytotoxic T cells specifically kill myeloma and other cancer cells that express DKK1 and HLA-A2, but not HLA-A2+ normal cells, indicating that DKK1+ tumor cells naturally express these peptides, in the context of HLA-A2 molecules, on their surface. To develop cancer therapeutic antibodies, DKK1 peptide P20-HLA-A2 monomer was synthesized and used to immunize mice. Hybridomas secreting mAbs recognizing cell surface-expressed DKKl P20-HLA-A2 complex (DKK1-A2) were obtained and analyzed. In this study, we generated novel (DKK1-A2) mAbs recognizing DKK1 (P20) peptide in the context of human HLA-A*0201 (HLA-A2) molecules (DKK1-A2 complexes) that are naturally expressed by HLA-A2+DKK1+ cancer cells. These mAbs bound to HLA-A2+DKK1+ hematologic (myeloma, lymphoma, and leukemia) and solid (breast, pancreatic, and prostate) cancer cells and directly induced apoptosis in the cancer cells by activating the caspase-9 cascade. DKK1-A2 mAbs also effectively lysed cancer cells in vitro by mediating CDC and ADCC activities. Furthermore, DKK1-A2 mAbs were therapeutic against established hematologic and solid cancers in their xenograft mouse models. To enhance the therapeutic efficacy of DKK1-A2 mAbs, we investigated the effect of combination treatment of DKK1-A2 mAbs with lenalidomide. Our results showed that there is an additive therapeutic effect between DKK1-A2 mAbs and lenalidomide in vivo, underscoring a potential clinical development strategy for combining DKK1-A2 mAb with lenalidomide to treat cancer patients. As DKK1 is not detected in most human tissues, DKK1-A2 mAbs did not bind to or kill HLA-A2+ blood cells in vitro nor caused tissue damage in vivo in tumor-free or tumor-bearing HLA-A2-transgenic mice. Thus, our study suggests that DKK1-A2 mAbs may be a promising therapeutic agent to treat human cancers and warrants further preclinic studies to determine their translatability to clinic. Citation Format: Jianfei Qian, Wang Qiang, Liuling Xiao, Wei Xiong, Miao Xian, Chuanchao Zhang, Yabo Li, Qing Yi. Development of therapeutic monoclonal antibodies against DKK1 peptide-HLA-A2 complex to treat human cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2821.

Abstract 89: Comprehensive cell based bioassay approaches for characterization, and clinical development of therapeutic agonistic antibodies for cancer immunotherapy and autoimmune diseases

Abstract Agonistic antibodies are emerging as promising therapeutics for targeting immune checkpoints, particularly those within the TNF Receptor Superfamily, as they play a crucial role in regulating immune cell function, especially in the context of cancer treatment. In addition, there is also a growing focus on the potential of agonistic antibodies to selectively activate co-inhibitory checkpoint receptors. This offers a promising avenue for suppressing inflammation in autoimmune diseases and restoring tolerance in graft-vs-host disease (GvHD) while avoiding the complications of global immunosuppression. While a substantial number of clinical trials are currently underway for oncology and autoimmune indications, there is a notable scarcity of commercially available assays to support the clinical development of this class of therapeutics, impacting their time-to-clinic. Existing assays frequently fail to accurately assess the agonistic activity of antibodies as they are unable to replicate the necessary physiologically relevant conditions. In this context, we present several case studies that highlight the pivotal role of cell-based bioassay approaches developed by Eurofins DiscoverX in driving the characterization and clinical development of agonistic antibody therapeutics targeting various checkpoint receptors. Additionally, we discuss our data demonstrating the indispensable role of FcyR-mediated antibody clustering in establishing the otherwise elusive agonistic activity of antibodies. Citation Format: Venkatesh Chari, Jennifer Lin-Jones, Luhan Yang, Jane E. Lamerdin, Gaurav Agrawal. Comprehensive cell based bioassay approaches for characterization, and clinical development of therapeutic agonistic antibodies for cancer immunotherapy and autoimmune diseases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 89.

Abstract 7174: Pharmacokinetics and immunogenicity of anti-PD-1 antibody in humanized FcRn mouse models compared to immunocompetent mouse models

Abstract Introduction: The development and use of therapeutic antibodies in cancer therapy has increased significantly in recent years, led by the success of approved immune checkpoint blockade antibodies targeting PD-1 and PD-L1 axis. However, obtaining more clinically relevant pharmacokinetics (PK), safety and efficacy data for antibodies is still challenging in preclinical phase. Humanized FcRn (hFcRn) transgenic mouse model has a more faithful catabolism compared to WT mice, providing more accurate and predictable PK data of innovative antibody-based therapeutics at discovery stage[1]. In this study, we sought to investigate pharmacokinetics and immunogenicity characteristics of anti-PD-1 antibody in hFcRn transgenic mice and provide guidance for its differentiation of prediction value for drug PK and safety by comparing to WT mice. Methods: Non-tumor bearing hFcRn mice and wild type C57BL/6 mice were divided into 2 groups, 5 mice were enrolled into each group. Mice were administered anti-PD-1(Nivolumab) at 10 mg/kg single dose after grouping by intravenous (IV) injection. Blood samples at 12 timepoints (15min, 6h, 1, 2, 4, 7, 10, 14, 21, 28, 35, 42 days) post-dosing were collected for PK and Anti-Drug Antibody (ADA) analysis by MSD and ELISA. Results: Nivolumab clearance in hFcRn mice followed a typical linear profile with rapid distribution phase and slow elimination phase (t1/2 = 350 to 400 h). While the PK profile in C57BL/6 mice displayed non-linear clearance and very short elimination phase (t1/2 = 45 to 50 h). This data demonstrated that hFcRn mice have better correlated half-life with human (Nivolumab single dose by IV with 10mg/kg, t1/2 = 595 h) [2]. ADA analysis revealed that it was produced starting from Day 10 in wild type C57BL/6 mice and the frequency of ADA induced by Nivolumab in wild type mice (2/5) was higher than hFcRn mice (0/5). The variation of Nivolumab level was correlated with ADA production in wild type mice. This suggested hFcRn shows lower immunogenicity than wild type mice for human IgG drug and can potentially improve negative effect of ADA interference on PK evaluation. Conclusion: The result of this study demonstrated that the PK data in hFcRn mouse model was more predictive of human PK profile compared to wild type C57BL/6 mice. This advances innovation in antibody-based therapeutics and translational applications, with improved PK, safety and efficacy evaluation for preclinical human IgG drug development in cancer therapy.

Abstract 1876: Development of therapeutic antibodies targeting the GLUT-1 transporter to restrict cancer cell growth

Abstract Background: Upregulated glucose metabolism is one of the strategies cancer cells use to fuel their abnormal cell growth and division. Targeting the cancer-specific glucose transporter GLUT-1 is a promising approach to restrict glucose uptake and challenge the metabolic needs of tumor cells. Antibodies, as opposed to small molecule inhibitors, are an attractive modality to therapeutically target complex muti-pass membrane transporters. Here we report the development of antibodies that very specifically block the function of only GLUT-1. Methods: Monoclonal antibodies against GLUT-1 were generated using virus-like particles. For immunization, chickens were used as they are evolutionarily distant from mammals and can produce antibodies with prolonged CDR3-s in VH, which could facilitate their binding to the limited extracellular region of GLUT-1. Antibody discovery was performed with HybriFree B cell cloning technology followed by functional screens with 2-deoxyglucose uptake interference or cell proliferation measurements. Results: The discovered antibodies specifically bind to GLUT-1 with low nanomolar EC50 values and do not target other glucose transporters. The lead candidate, ICO-33, inhibits glucose uptake and rewires the metabolism of GLUT-1-dependent cancer cells to rely on oxidative phosphorylation. This results in a significantly synergistic cancer proliferation inhibition with ICO-33 and OXPHOS inhibitor combinations in doses that do not inhibit proliferation as single agents. ICO-33 and OXPHOS inhibitor treatment is well-tolerated and demonstrates a drastic tumor growth inhibition in in vivo colorectal and pancreatic cancer models. Conclusions: We describe the discovery of highly specific monoclonal antibodies targeting GLUT-1. We further demonstrate that the restriction of the much-needed glucose uptake by ICO-33 makes cancer cells highly susceptible to OXPHOS inhibitor co-therapy both in vitro and in vivo, validating the antibody as a promising candidate for clinical development. Citation Format: Siret Tahk, Kai Virumae, Korneelia Anton, Paule Hermet, Robin Pau, Mario Plaas, Maiken Abel, Denis Belitškin, Luciano Galdieri, Steven Garner, Jillian Krings, Kaleb Collver, Emily Schultz, Kaitlyne Powers, Alastair King, Francisca Neethling, Anu Planken, Mart Ustav, Joan Terya, Andres Mannik, Mart Ustav. Development of therapeutic antibodies targeting the GLUT-1 transporter to restrict cancer cell growth [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1876.

Abstract 6344: Engineering of ICAM-1 refractory antibodies for the development of therapeutic antibodies and antibody drug conjugates (ADCs) in ICAM-1 over-expressing cancers

Abstract Human cancers employ a number of mechanisms to evade host immune responses against novel antigens generated from aberrant over-expression, mutations and/or epigenetic alterations. Humoral immunity utilizes antibodies and immune-effector cells as well as molecular immune complexes involving the complement system to mediate the killing of dysregulated cancer cells. We refer to these anti-cancer mechanisms as Humoral Immuno-Oncology (HIO). HIO suppression is mediated by tumor-produced proteins called HIO factors. One such factor is CA125, which was previously shown to bind IgG-type antibodies and inhibit their immune-effector activities, including antibody dependent (ADCC) and complement dependent (CDC) cellular cytotoxicity. Using a combination of experimental screening and literature searches, a second protein produced by tumors and associated with a variety of cancer indications was discovered and found to be soluble ICAM-1 (sICAM-1). Through various functional studies we reported that sICAM-1 and membrane ICAM-1 (mICAM-1) are capable of binding IgG1-type antibodies that in turn inhibits their immune-effector activity. Through a combination of truncation and substitution mutagenesis, we identified a four amino acid motif within the CH3 domain of IgG1 essential for ICAM-1 binding, resulting in the inhibition of ADCC activity. While traditional glycine and alanine substitutions in this region abrogated ICAM-1 binding, these modifications caused tertiary structural changes in the Fc domain that resulted in loss of ADCC activity. Through a combinatorial amino acid substitution approach, we identified a four amino acid combination within the 407YSKL410 to 407FARV410 motif that resulted in antibodies refractory to sICAM-1 binding with robust ADCC activity. Additionally, isogenic wildtype and ICAM-1 knockdown target cell lines showed mICAM-1 inhibited target cell killing of a saporin antibody drug conjugate (ADC) and this was the direct result of mICAM-1 reducing antibody internalization, a requisite for maximal ADC target cell killing. The inhibitory activity of mICAM-1 could be overcome employing antibodies containing the 407FARV410 substitution. These findings highlight yet another mechanism by which tumors can suppress the host’s immune system for survival and offer new concepts for developing antibody-based therapies that can aid in the treatment of various cancer indications, especially those over-expressing ICAM-1. Moreover, the findings here offer diagnostic and therapeutic clinical design opportunities to improve upon existing approved immune-mediated therapies for which this factor is present. Citation Format: Brad Kline, Luigi Grasso, Nicolas Nicolaides. Engineering of ICAM-1 refractory antibodies for the development of therapeutic antibodies and antibody drug conjugates (ADCs) in ICAM-1 over-expressing cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6344.

Abstract 5333: NeoMab: A novel platform for fully human therapeutic antibody development

Abstract Antibodies and antibody containing therapeutics, such as multivalent antibodies, chimeric antigen receptors (CARs), and antibody directed conjugates (ADCs), have been proven to be highly prominent in cancer treatment. However, challenges such as immunogenicity stemming from non-human or unnatural sequences and limitations in preclinical animal study systems still impede the rapid development of antibody drugs. To overcome these hurdles, GemPharmatech has created a novel antibody gene humanized model, the NeoMab mouse, to develop fully human antibodies. The NeoMab model was established via large genomic fragment knock-in technology, retaining native mouse constant region encoding genes and regulatory elements, while incorporating human variable gene repertoires into the endogenous loci. Developed in the BALB/c background, the NeoMab mouse carries fully functional MHC molecules, potentially enhancing antigen presentation. These mice sustain a competent immune system with a B cell development and maturation pattern, immune cell profile, and serum immunoglobulin levels comparable to those of BALB/c mice. NeoMab mice exhibit a robust humoral immune response, with a rapid increase in antigen-specific serum titers upon immunization using different antigens, such as recombined protein, plasmids, and overexpressing cell lines. Utilizing human V(D)J genes to encode immunoglobulins at a human-like frequency and diversity, antibodies derived from NeoMab mice demonstrate affinity and functional activity comparable to, or even surpassing, FDA-approved drugs. In conclusion, the NeoMab mouse model in the BALB/c background has been rigorously validated to elicit a robust response to specific antigen immunization, producing antibodies with high affinity, diversity, and functional activity. GemPharmatech's extensive drug-target gene humanized mouse library (comprising over 800 targets) and diverse disease models in oncology and other fields facilitate a seamless connection between in vitro antibody screening and in vivo animal studies. The integration of NeoMab, target humanization animals, and disease models enables GemPharmatech to provide an integrated solution, reducing time and costs while elevating the quality of antibody discovery in the field. Citation Format: Mingkun Zhang, Cunxiang Ju, Song Li, Junchao Peng, Jing Zhao, Xiang Gao. NeoMab: A novel platform for fully human therapeutic antibody development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5333.

Abstract 3107: SMASH: Single molecule antibody screening with high-throughput imaging system

Abstract Larger, more diverse antibody libraries are being screened in recent years. Despite enabling the high-throughput screening of extensive libraries, the process for identification and characterization of antibodies remains laborious and time-intensive. Here we report a platform that not only compiles hit finding and validation processes, but also provides high-resolution binding affinity as well as rank order among the library being screened. We streamlined the library construction and affinity screening via microscale transient expression in HEK293T cells with designed antibody sequence and direct quantification of antibody-antigen binding affinity which reduced the timeline from multiple weeks to a single week. We constructed the single-chain fragment antigen binding (scFab) libraries by replacing the duplex DNA fragment in CDR of interest while preserving the human framework of Fab. We have demonstrated that the SPID technique allows to detect antibody-antigen interactions from just dozens of pg of scFabs in total. This allowed us to bypass the conventional DNA cloning or even PCR amplification to achieve the minimum amount of DNA plasmids for expressing scFabs to be analyzed such as BLI and SPR. Therefore, we assembled the DNA plasmids through in vitro ligation with high efficiency and directly introduced it to HEK293T in 96-well microplate with microscale (200 ul) for transient transfection, which only takes three days for library generation. Next, we utilized SPID to quantify the number of single molecules between free and antigen-bound fractions of scFab, resulting in occupancy at the antibody-antigen binding equilibrium. This technique facilitated the determination of binding affinity (KD) for 200 antibody-antigen pairs within a 6-hour TAT encompassing both measurement and analysis. In total, we utilized 4,000 times less antibody for characterization while achieving enhanced sensitivity compared to both BLI and SPR methods. As a proof-of-concept, we generated a library consisting of 720 variants of Trastuzumab in scFab format to probe the landscape of CDRs affecting affinities against HER2 showing nM to low uM dynamic range of KD. Out of 720 analyzed variants, 5% were deleterious, 38% provided substantial changes, 40% showed little/no change, 17% enhanced affinity to HER2. To validate the robustness of the platform, we extensively expanded the library screening, assessing over 2,000 antibody variants for their affinity against more than three different therapeutic targets. To conclude, we demonstrated an efficient approach for monitoring changes in affinity resulting from single mutations in scFab. This rapid screening of site-saturated libraries would lead to a combinational variant library that our platform can screen. Ultimately, our platform aims to identify potential candidates for therapeutic antibody development throughput the phases of antibody discovery, maturation, and engineering. Citation Format: Jihye Jo, Changju Chun, Byeong-Kwon Sohn, Booyoung Yu, Jiyu Lee. SMASH: Single molecule antibody screening with high-throughput imaging system [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3107.

Structural insights reveal interplay between LAG-3 homodimerization, ligand binding, and function

Lymphocyte activation gene-3 (LAG-3) is an inhibitory receptor expressed on activated T cells and an emerging immunotherapy target. Domain 1 (D1) of LAG-3, which has been purported to directly interact with major histocompatibility complex class II (MHCII) and fibrinogen-like protein 1 (FGL1), has been the major focus for the development of therapeutic antibodies that inhibit LAG-3 receptor-ligand interactions and restore T cell function. Here, we present a high-resolution structure of glycosylated mouse LAG-3 ectodomain, identifying that cis-homodimerization, mediated through a network of hydrophobic residues within domain 2 (D2), is critically required for LAG-3 function. Additionally, we found a previously unidentified key protein-glycan interaction in the dimer interface that affects the spatial orientation of the neighboring D1 domain. Mutation of LAG-3 D2 residues reduced dimer formation, dramatically abolished LAG-3 binding to both MHCII and FGL1 ligands, and consequentially inhibited the role of LAG-3 in suppressing T cell responses. Intriguingly, we showed that antibodies directed against D1, D2, and D3 domains are all capable of blocking LAG-3 dimer formation and MHCII and FGL-1 ligand binding, suggesting a potential allosteric model of LAG-3 function tightly regulated by dimerization. Furthermore, our work reveals unique epitopes, in addition to D1, that can be targeted for immunotherapy of cancer and other human diseases.

Rapid isolation of pan-neutralizing antibodies against Omicron variants from convalescent individuals infected with SARS-CoV-2.

The emergence of SARS-CoV-2 Omicron subvariants haspresented a significant challenge to global health, as these variants show resistance to most antibodies developed early in the pandemic. Therapeutic antibodies with potent efficacy to the Omicron variants are urgently demanded. Utilizing the rapid antibody discovery platform, Berkeley Lights Beacon, we isolated two monoclonal neutralizing antibodies, 2173-A6 and 3462-A4. These antibodies were isolated from individuals who recently recovered from Omicron infections. Both antibodies, 2173-A6 and 3462-A4, demonstrated high affinity for the RBD and effectively neutralized pseudoviruses from various Omicron lineages, including BA.4/5, XBB.1.16, XBB.1.5, and EG.5.1. This neutralization was achieved through binding to identical or overlapping epitopes. The use of the Beacon platform enabled the rapid isolation and identification of effective neutralizing antibodies within less than 10 days. This process significantly accelerates the development of novel therapeutic antibodies, potentially reducing the time required to respond to unknown infectious diseases in the future.

AbImmPred: An immunogenicity prediction method for therapeutic antibodies using AntiBERTy-based sequence features.

Due to the unnecessary immune responses induced by therapeutic antibodies in clinical applications, immunogenicity is an important factor to be considered in the development of antibody therapeutics. To a certain extent, there is a lag in using wet-lab experiments to test the immunogenicity in the development process of antibody therapeutics. Developing a computational method to predict the immunogenicity at once the antibody sequence is designed, is of great significance for the screening in the early stage and reducing the risk of antibody therapeutics development. In this study, a computational immunogenicity prediction method was proposed on the basis of AntiBERTy-based features of amino sequences in the antibody variable region. The AntiBERTy-based sequence features were first calculated using the AntiBERTy pre-trained model. Principal component analysis (PCA) was then applied to reduce the extracted feature to two dimensions to obtain the final features. AutoGluon was then used to train multiple machine learning models and the best one, the weighted ensemble model, was obtained through 5-fold cross-validation on the collected data. The data contains 199 commercial therapeutic antibodies, of which 177 samples were used for model training and 5-fold cross-validation, and the remaining 22 samples were used as an independent test dataset to evaluate the performance of the constructed model and compare it with other prediction methods. Test results show that the proposed method outperforms the comparison method with 0.7273 accuracy on the independent test dataset, which is 9.09% higher than the comparison method. The corresponding web server is available through the official website of GenScript Co., Ltd., https://www.genscript.com/tools/antibody-immunogenicity.

Fast-Track Discovery of SARS-CoV-2-Neutralizing Antibodies from Human B Cells by Direct Functional Screening.

As the COVID-19 pandemic revealed, rapid development of vaccines and therapeutic antibodies are crucial to guarantee a quick return to the status quo of society. In early 2020, we deployed our droplet microfluidic single-cell-based platform DROPZYLLA® for the generation of cognate antibody repertoires of convalescent COVID-19 donors. Discovery of SARS-CoV-2-specific antibodies was performed upon display of antibodies on the surface of HEK293T cells by antigen-specific sorting using binding to the SARS-CoV-2 spike and absence of binding to huACE2 as the sort criteria. This efficiently yielded antibodies within 3-6 weeks, of which up to 100% were neutralizing. One of these, MTX-COVAB, displaying low picomolar neutralization IC50 of SARS-CoV-2 and with a neutralization potency on par with the Regeneron antibodies, was selected for GMP manufacturing and clinical development in June 2020. MTX-COVAB showed strong efficacy in vivo and neutralized all identified clinically relevant variants of SARS-CoV-2 at the time of its selection. MTX-COVAB completed GMP manufacturing by the end of 2020, but clinical development was stopped when the Omicron variant emerged, a variant that proved to be detrimental to all monoclonal antibodies already approved. The present study describes the capabilities of the DROPZYLLA® platform to identify antibodies of high virus-neutralizing capacity rapidly and directly.

Epidemiology of and Genetic Factors Associated with Acanthamoeba Keratitis.

Acanthamoeba keratitis (AK) is a severe, rare protozoal infection of the cornea. Acanthamoeba can survive in diverse habitats and at extreme temperatures. AK is mostly seen in contact lens wearers whose lenses have become contaminated or who have a history of water exposure, and in those without contact lens wear who have experienced recent eye trauma involving contaminated soil or water. Infection usually results in severe eye pain, photophobia, inflammation, and corneal epithelial defects. The pathophysiology of this infection is multifactorial, including the production of cytotoxic proteases by Acanthamoeba that degrades the corneal epithelial basement membrane and induces the death of ocular surface cells, resulting in degradation of the collagen-rich corneal stroma. AK can be prevented by avoiding risk factors, which includes avoiding water contact, such as swimming or showering in contact lenses, and wearing protective goggles when working on the land. AK is mostly treated with an antimicrobial therapy of biguanides alone or in combination with diaminidines, although the commercial availability of these medicines is variable. Other than anti-amoeba therapies, targeting host immune pathways in Acanthamoeba disease may lead to the development of vaccines or antibody therapeutics which could transform the management of AK.

Development of therapeutic monoclonal antibodies against DKK1 peptide-HLA-A2 complex to treat human cancers

BackgroundTargeted immunotherapy with monoclonal antibodies (mAbs) is an effective and safe method for the treatment of malignancies. Development of mAbs with improved cytotoxicity, targeting new and known tumor-associated antigens, therefore...

Evaluating mAbs binding abilities to Omicron subvariant RBDs: implications for selecting effective mAb therapies.

The ongoing evolution of the Omicron lineage of SARS-CoV-2 has led to the emergence of subvariants that pose challenges to antibody neutralization. Understanding the binding dynamics between the receptor-binding domains (RBD) of these subvariants spike and monoclonal antibodies (mAbs) is pivotal for elucidating the mechanisms of immune escape and for advancing the development of therapeutic antibodies. This study focused on the RBD regions of Omicron subvariants BA.2, BA.5, BF.7, and XBB.1.5, employing molecular dynamics simulations to unravel their binding mechanisms with a panel of six mAbs, and subsequently analyzing the origins of immune escape from energetic and structural perspectives. Our results indicated that the antibody LY-COV1404 maintained binding affinities across all studied systems, suggesting the resilience of certain antibodies against variant-induced immune escape, as seen with the mAb 1D1-Fab. The newly identified mAb 002-S21F2 showed a similar efficacy profile to LY-COV1404, though with a slightly reduced binding to BF.7. In parallel, mAb REGN-10933 emerged as a potential therapeutic candidate against BF.7 and XBB.1.5, reflecting the importance of identifying variant-specific antibody interactions, akin to the binding optimization observed in BA.4/5 and XBB.1.5. And key residues that facilitate RBD-mAb binding were identified (T345, L441, K444, V445, and T500), alongside residues that hinder protein-protein interactions (D420, L455, K440, and S446). Particularly noteworthy was the inhibited binding of V445 and R509 with mAbs in the presence of mAb 002-S21F2, suggesting a mechanism for immune escape, especially through the reduction of V445 hydrophobicity. These findings enhance our comprehension of the binding interactions between mAbs and RBDs, contributing to the understanding of immune escape mechanisms. They also lay the groundwork for the design and optimization of antiviral drugs and have significant implications for the development of treatments against current and future coronaviruses.

Therapeutic antibody targeting natriuretic peptide receptor 1 inhibits gastric cancer growth via BCL-2-mediated intrinsic apoptosis.

Despite recent advances in the development of therapeutic antibodies, the prognosis of unresectable or metastatic gastric cancer (GC) remains poor. Here, we searched for genes involved in the malignant phenotype of GC and investigated the potential of one candidate gene to serve as a novel therapeutic target. Analysis of transcriptome datasets of GC identified natriuretic peptide receptor 1 (NPR1), a plasma membrane protein, as a potential target. We employed a panel of human GC cell lines and gene-specific small interfering RNA-mediated NPR1 silencing to investigate the roles of NPR1 in malignancy-associated functions and intracellular signaling pathways. We generated an anti-NPR1 polyclonal antibody and examined its efficacy in a mouse xenograft model of GC peritoneal dissemination. Associations between NPR1 expression in GC tissue and clinicopathological factors were also evaluated. NPR1 mRNA was significantly upregulated in several GC cell lines compared with normal epithelial cells. NPR1 silencing attenuated GC cell proliferation, invasion, and migration, and additionally induced the intrinsic apoptosis pathway associated with mitochondrial dysfunction and caspase activation via downregulation of BCL-2. Administration of anti-NPR1 antibody significantly reduced the number and volume of GC peritoneal tumors in xenografted mice. High expression of NPR1 mRNA in clinical GC specimens was associated with a significantly higher rate of postoperative recurrence and poorer prognosis. NPR1 regulates the intrinsic apoptosis pathway and plays an important role in promoting the GC malignant phenotype. Inhibition of NPR1 with antibodies may have potential as a novel therapeutic modality for unresectable or metastatic GC.