mAbs最新文献

Nanobodies have emerged as promising tools for many biotechnological applications due to their small size, high stability and remarkable binding specificity. Next-Generation Sequencing (NGS) enables deep profiling of large nanobody libraries and panning campaigns; however, the scale and diversity of nanobody NGS datasets presents a significant bioinformatic challenge. To this end, we have developed alpseq, an optimized, open-source software pipeline designed specifically for the efficient and accurate processing of NGS data from nanobody libraries and panning campaigns. alpseq is also paired with a PCR-free sequencing library preparation protocol to allow researchers to easily generate their own data while avoiding biases. The alpseq software pipeline is composed of two parts: a pre-processing module written in Nextflow efficiently handles raw nanobody reads in a single line of code. These results are then fed into the analysis module, which contains a comprehensive suite of functions for quality control, diversity analysis, identification of enriched sequences and clustering. alpseq also creates a user-friendly interactive report which empowers scientists to explore their data without the need for extensive bioinformatic experience. Sophisticated panning campaign designs are supported, such as replicates and comparisons between different pans to find cross-binding leads. alpseq thus generates insights into the nanobody selection process and delivers a list of lead candidates for further experimental validation and downstream applications. alspeq is available at https://github.com/kzeglinski/alpseq.

Antibody-drug conjugates (ADCs) and other biopharmaceuticals require robust analytical methods to assess biotransformation in biological matrices. Current approaches often require off-line enrichment and extensive chromatographic separation, limiting throughput and complicating data processing. We developed a native affinity liquid chromatography-mass spectrometry (aLC-MS) method using POROS CaptureSelect FcXL columns combined with optimized solvents and MS parameters for direct analysis (1D aLC-MS) of ADCs and other antibody-derived formats in complex sample matrices, such as serum. The method was evaluated using stability studies and concentration series in mouse serum. Direct analysis enabled accurate determination of drug-antibody ratio (DAR), drug-load distribution (DLD) and relative drug abundance across samples without chromatographic peak integration. Stability studies revealed distinct ADC biotransformation profiles in serum versus PBS, including maleimide hydrolysis and disulfide exchange at under-conjugated cysteine sites. The aLC-MS method achieved excellent linearity (R² = 0.99) over 125-2000 µg/mL in serum and demonstrated sensitivity to 31.25 µg/mL. This rapid, selective aLC-MS method enables high-throughput monitoring of ADC quality attributes in complex matrices with minimal sample preparation, supporting biopharmaceutical product development and bioanalysis applications. The method is exclusively based on MS results, which makes data processing and reporting fast and easy to automate.

This study presents a systematic characterization of lysine glucuronidation that was revealed during the charge variant characterization of a bispecific antibody (bsAb). Site-specific quantitation by Glu-C/Asp-N peptide mapping suggested that glucuronidation occurred randomly across surface lysine residues. To understand the impact of glucuronidation on the structure and function of the bsAb, stressed samples with up to 84% total glucuronidation were generated and analyzed by a comprehensive panel of analytical methods. The results suggested that glucuronidation caused an acidic isoelectric point (pI) shift in the charge profile. However, it does not affect the higher-order structure or bioactivities of the bsAb, including antibody-dependent cell-mediated cytotoxicity, antigen binding, or Fc receptor interaction. To support routine process monitoring, a fit-for-purpose subunit mass method was developed and qualified for quantitation of glucuronidation, offering a higher-throughput alternative to peptide mapping for assessing process consistency and product comparability.

Chimeric antigen receptor (CAR)-modified T cells have garnered substantial attention due to their clinical success, culminating in six Food and Drug Administration-approved therapies for hematological malignancies. Notably, CD19-specific CAR T cell therapies have achieved remarkable clinical efficacy in treating B-cell malignancies, but these profound and durable responses are not observed in CAR T therapies targeting other indications, particularly solid tumors. Key design elements of CAR constructs - namely, antigen binding affinity and spacer length - play critical roles in determining T cell effector function and overall therapeutic effectiveness. Refining CAR designs may enhance T cell functionality, extend clinical application, and potentially apply CAR T cell therapies across a wider array of malignancies. In this study, affinity variant and spacer variant CARs targeting BCMA and DLL3 tumor antigens were evaluated using in vitro measurements of antigen-binding properties and effector function. Each panel of CARs spanned 2-3 logs of antigen binding affinity (BCMA: 181 pM KD to 74 nM KD, DLL3: 417 pM to 407 nM). Additionally, CAR T cells were challenged with tumor spheroids composed of BCMA⁺ H929 and DLL3⁺ SHP77 tumor cells. We show that for both tumor models, higher affinity CARs (KD stronger than approximately 100 nM) paired with an intermediate length spacer (IgG1 Fc, CH2-CH3, 230AA) elicited the strongest levels of tumor killing, CAR⁺ T cell expansion, and proinflammatory cytokine production. These CARs displayed the strongest cellular affinity when measured in a conjugation assay, suggesting a relationship between cellular affinity and T cell functional performance. This study highlights the critical role of CAR design in enhancing T cell functionality, demonstrating that high-affinity CARs combined with intermediate-length spacers yield superior performance in targeting BCMA and DLL3 antigens. This study provides a framework for rational CAR design, informing strategies to broaden the clinical utility of CAR T-cell therapies beyond hematologic cancers.

T-cell receptor mimic (TCRm) antibodies are an emerging class of tumor-targeting agents used in advanced immunotherapies such as bispecific T-cell engagers and CAR-T cells. Unlike conventional antibodies, TCRms are designed to recognize peptide - human leukocyte antigen (pHLA) complexes that present intracellular tumor-derived peptides on the cell surface. Due to the typically low surface abundance and high sequence similarity of pHLAs, TCRms require high affinity and exceptional specificity to avoid off-target toxicity. Conventional methods for off-target identification such as sequence similarity searches, motif-based screening, and structural modeling focus on the peptide and are limited in detecting cross-reactive peptides with little or no sequence homology to the target. To address this gap, we developed EpiPredict, a TCRm-specific machine learning framework trained on high-throughput kinetic off-target screening data. EpiPredict learns an antibody-specific mapping from peptide sequence to binding strength, enabling prediction of interactions with unmeasured pHLA sequences, including sequence-dissimilar peptides. We applied EpiPredict to two distinct TCRms targeting the cancer-testis antigen MAGE-A4. The model successfully predicted multiple off-targets with minimal sequence similarity to the intended epitope, many of which were experimentally validated via T2 cell binding assays. These findings establish EpiPredict as a valuable tool for lead optimization of TCRms, enabling the identification of antibody-specific off-targets beyond the scope of traditional peptide-centric methods and supporting the preclinical de-risking of TCRm-based therapies.

Over the past two decades, bi- and multispecific antibodies have emerged as a rapidly advancing class of therapeutic biologics, transforming oncology and immunotherapy. By simultaneously binding two or more distinct antigens or epitopes, these molecules achieve mechanisms of action beyond those of conventional monoclonal antibodies, including immune cell redirection, dual pathway modulation, and enhanced tissue selectivity. Bispecific and multispecific antibodies exhibit considerable structural diversity, encompassing a wide range of molecular architectures covering a steady growing 'zoo' of formats. The therapeutic success and diversity of molecules and formats is reflected in the 2021 revision of the international nonproprietary name system, which introduced the suffix - mig to denote multispecific immunoglobulins. In this review, we provide an overview of multispecific antibodies in clinical development, focusing on format, molecular design, and clinical status. In total, data for 501 multispecific antibodies were compiled and analyzed, identifying 112 different formats. Overall, this analysis highlights the rapid growth, enormous format diversity, and translational potential of multispecific antibodies. It underscores their emerging role as versatile therapeutics not only in oncology, but also in non-cancer indications, reflecting a field that continues to evolve rapidly in response to both scientific innovation and clinical needs.

The heavy-chain antibody variable domain (VHH) is the smallest antigen-binding domain of such antibodies, which are derived from camelids. In the past three decades, VHHs, which are also called single-domain antibodies, have been extensively used to target pathogens and/or toxins. Conventional screening methods, such as phage display, rely only on antibody-antigen binding as the sole criterion for selection. Despite being robust and high-throughput, such methods often require additional downstream experiments to identify VHH that neutralize their target. Here, we describe an innovative, high-throughput functional screening method, Rapid Antibody functional Screening by Pentavalent phage display (RASP), that incorporates purified antibody-displaying phages for virus neutralization assays, and thus can be used to directly identify neutralizing VHHs. As a proof-of-concept, we first displayed previously identified neutralizing VHHs specific for the spike proteins of SARS-CoV-2 and respiratory syncytial virus on phages and demonstrated a dose-dependent blockade of viral infection. We further improved our method by utilizing the pentavalent display feature of hyperphages. We showed that hyperphage-derived VHH phages were superior to helper phage-derived VHH phages in assaying viral neutralization potential. Thereafter, we applied RASP to identify multiple candidates by screening a semi-synthetic VHH library against recombinant vesicular stomatitis viruses pseudotyped with spike glycoproteins from SARS-CoV-2, Junin virus, and Ebola virus, featuring as case studies in antiviral antibody discovery. Further, we benchmarked RASP against established phage ELISA and next-generation sequencing methods. Overall, we successfully used RASP in the context of the discovery of antiviral VHHs, highlighting its broader applicability as a platform that can be used either in isolation or in conjunction with other functional screening methods to accelerate the discovery of antiviral VHHs.

Messenger RNA (mRNA) has emerged as a powerful tool for protein expression in clinical settings, yet its potential as a platform for biologics manufacturing remains underexplored. Here, we evaluate transient mRNA transfection in Chinese hamster ovary (CHO) cells as a rapid and versatile system for protein production. Using reporter mRNAs, we optimize transfection efficiency and benchmark performance against industry-standard plasmid transfection and stable cell line methods. We demonstrate that co-transfection of heavy and light chain mRNAs enables the efficient synthesis, assembly and secretion of the monoclonal antibody bevacizumab with high fidelity. Compared to conventional approaches, mRNA transfection drives rapid and predictable protein expression, reducing cell incubation times and enabling sequential or conditional expression. These features highlight mRNA as a flexible and efficient platform for transient expression, providing a foundation for accelerating the development and manufacturing of biologics.

Driven by the substantial limitations of first generation 4-1BB agonists urelumab and utomilumab, the field has shifted toward engineering next-generation molecules with improved therapeutic windows. This review provides a comprehensive analysis of this evolution, detailing how key molecular design strategies are used to restrict 4-1BB activation to the tumor microenvironment. We summarize available clinical data, highlighting that 4-1BB bispecific antibodies exhibit superior antitumor efficacy and more favorable safety profiles compared with their monospecific predecessors. Furthermore, we discuss strong rationale for combination strategies, emphasizing how 4-1BB signaling provides the crucial costimulatory signal necessary to sustain durable anti-tumor responses. In summary, this review elucidates the scientific basis of antibody engineering aimed at improving safety and tumor-selective activation of 4-1BB agonists and outlines future directions for optimizing their clinical application in cancer immunotherapy.

Immunogenicity prediction is widely used in the developability assessment of antibodies, and many marketed and clinical-stage therapeutics have a predicted T-cell epitope in the second complementary-determining region of their light chain (CDR2L). To investigate such CDR2Ls in more detail, we identified an antibody with a CDR2L for which a patient had developed treatment-emergent (TE) anti-drug antibodies (ADAs) in a clinical setting. With this, we establish the importance of predicted T-cell epitopes in CDR2L. In the course of deleting the T-cell epitope, we decided to aim for a solution that can be applied broadly to facilitate larger high-throughput discovery campaigns. For this purpose, we have developed a double-mutation scheme that targets AHo67 (Kabat51) and AHo68 (Kabat52) in the CDR2L. This 67G-68G mutation scheme was applied to all light chain sequences of a tri-specific single-chain diabody fused to a single-chain variable fragment (scMATCH3™) antibody for which TE ADAs had been observed. Analyses of patient sera showed that introduction of 67 G-68 G in CDR2L in combination with our previously described T101S-T146K (Kabat: T87S-T110K) framework mutations led to a scMATCH3 antibody with significantly reduced levels of both preexisting and TE ADA reactivities. For a diverse collection of single-chain variable fragments, application of the 67 G-68 G mutation scheme was experimentally seen to not substantially affect the functional or biophysical properties of the molecules, suggesting that this mutation scheme may be applicable to the improvement of therapeutic safety of antibodies of many types, with CDR2L-associated immunogenicity.