mAbs最新文献

{"title":"Targeted dual selection to optimize transposon stable pool generation of multispecifics.","authors":"Julie Johnston, Sonja Tierson, Yuyan Xu, Kalie Mix, Yj Jane Guo, Serhan Zenger, David Reczek, Dietmar Hoffmann, Brian Hall, Virginia Brophy","doi":"10.1080/19420862.2025.2600728","DOIUrl":"10.1080/19420862.2025.2600728","url":null,"abstract":"<p><p>Growing knowledge around disease states has led to opportunities within research to make designer molecules with improved specificity and broader efficacy. These next-generation molecules frequently take advantage of multispecific targeting and controlled mechanisms of action by utilizing four unique peptide chains as seen in many bispecific or trispecific antibodies. However, with all the opportunities these multispecifics offer, their increased biological complexities come with increased challenges during expression and purification to produce high-quality material. Lower yields accompanied with a high degree of mispairing after the initial capture purification step are often limiting factors. Developing new methods for stable pool expression can offer a strong advantage for progressing these molecules through research toward development. Here, we implemented optimized stable cell pools using targeted dual selection (TDS), a novel approach that combines specified selective pressure with transposon-guided semi-targeted gene integration. By utilizing key analytical data obtained during early-stage high-throughput transient productions, we can predict improved vector configurations for the generation of optimized TDS stable pools. We demonstrate that this design can improve molecule quality at the initial capture purification step in two Y-shaped bispecific molecules and two cross-over dual variable trispecific molecules by achieving up to four-fold increase in protein of interest yields while maintaining product quality. Use of this strategy in research can enable simplified purification strategies as well as increased production yields required for successful and timely project progression.</p>","PeriodicalId":18206,"journal":{"name":"mAbs","volume":"18 1","pages":"2600728"},"PeriodicalIF":7.3,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12710902/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145756800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Systematic review and data-driven insights into CHO cell engineering for next-generation antibody production.","authors":"Alexandra Schulz, Trent Munro, Anja Puklowski, Emma Slack, Anne B Tolstrup, Kerstin Otte","doi":"10.1080/19420862.2026.2615475","DOIUrl":"10.1080/19420862.2026.2615475","url":null,"abstract":"<p><p>Chinese hamster ovary (CHO) cells remain the dominant platform for therapeutic antibody and biopharmaceutical production, yet productivity bottlenecks persist, particularly for complex molecules. To identify overarching trends in host cell optimization, a systematic review and quantitative cross-study analysis of 164 publications (2011-2024) reporting CHO cell engineering strategies with effects on titer or specific productivity was conducted. Data from 466 engineered targets were extracted and analyzed by strategy, pathway, and production context. The field - driven largely by antibody production - has evolved from simple overexpression toward CRISPR-mediated knockouts, while combinatorial approaches, and engineering of nuclear, epigenetic, and apoptotic/proliferative targets achieved the greatest gains. Despite technological advances, reported improvement folds remained stable, highlighting the need for pathway-informed, multi-target engineering. Future progress in predictive modeling of engineering strategies will depend on standardized models and structured datasets. This review provides a data-driven framework for rational CHO design to support next-generation biotherapeutic production.</p>","PeriodicalId":18206,"journal":{"name":"mAbs","volume":"18 1","pages":"2615475"},"PeriodicalIF":7.3,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12818826/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145994292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biparatopic targeting of IL-23 enables dual-epitope engagement and enhanced neutralization potency.","authors":"Ross Gauntlett, James Lodge, Joe Watson, James Yates, Joanna Cordy, Helen Sinfield, Richard Caruana, Zahra Rattray","doi":"10.1080/19420862.2026.2689777","DOIUrl":"https://doi.org/10.1080/19420862.2026.2689777","url":null,"abstract":"<p><p>Biparatopic antibodies (bpAbs) have two non-overlapping epitopes on a single antigen, offering a distinct therapeutic potential, yet their application to soluble cytokines remains underexplored. Herewithin, we engineered and characterized biparatopic antibodies targeting human interleukin-23 (IL-23) by combining the clinically validated variable regions of ustekinumab and guselkumab into 1 + 1 IgG-like and 2 + 2 Fab-IgG extended biparatopic formats. Constructs were generated using heterodimer promoting C_H3 mutations and redox repair assembly of half‑antibodies, expressed in HEK-2936E cells, and benchmarked against parental monospecific antibodies. An orthogonal analytical workflow, comprising sodium dodecyl sulfate polyacrylamide gel electrophoresis, liquid chromatography-mass spectrometry, analytical size-exclusion chromatography, surface plasmon resonance (SPR), and mass photometry was used to define critical quality attributes and characterize biparatopic target engagement. SPR kinetic analysis demonstrated picomolar affinities across constructs and revealed avidity‑driven enhancements in apparent affinity. A bespoke SPR dual‑engagement bridging assay confirmed simultaneous IL-23A and IL-12B binding, validating obligate biparatopic engagement. Mass photometry independently corroborated <i>in trans</i> immune complex formation and revealed stoichiometry-dependent multimerisation across the bpAb formats explored. Functional neutralization was measured using an IL-23 luciferase reporter assay and supported by a bespoke, two-parameter mechanistic model, which accurately predicted observed EC₅₀ shifts. Biparatopic formats exhibited equivalent potency relative to equimolar antibody mixtures, establishing a generalizable framework for engineering and modeling soluble cytokine‑targeting biparatopic therapeutics.</p>","PeriodicalId":18206,"journal":{"name":"mAbs","volume":"18 1","pages":"2689777"},"PeriodicalIF":7.9,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148265272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Local electrostatics governs tryptophan oxidation and enables rational stability engineering in antibodies.","authors":"Sunidhi Lenka, Shrenik Mehta, Nicole Stephens, Franziska Seeger, Wei-Ching Liang, Andrew Watkins, Jonathan Zarzar, Negar Jafari, Rhyan Puno, Caleigh Azumaya, Ryan Kelly, Shuang Wu, Cecilia Chiu, Meredith Hazen, Yan Wu, Flaviyan Jerome Irudayanathan, Sreedhara Alavattam, Robert Kelley, Saeed Izadi","doi":"10.1080/19420862.2026.2713231","DOIUrl":"10.1080/19420862.2026.2713231","url":null,"abstract":"<p><p>Oxidation of tryptophan (Trp) residues in therapeutic antibody complementarity-determining regions (CDRs) can impair binding affinity, stability, and developability, yet the molecular determinants of site-specific susceptibility remain incompletely understood. Here, we present a structure-informed machine learning framework trained on Trp oxidation profiles from 187 monoclonal antibodies to identify the physicochemical drivers of oxidation risk. Beyond solvent accessibility, the dominant known predictor, we identify local residue-level electrostatic potential (Epot) as a strong independent modulator: negatively charged microenvironments markedly increase oxidation susceptibility. A two-parameter model combining only solvent accessibility and Epot achieves 79% classification accuracy, approaching the 84% performance of full-feature ensemble models, and correctly classifies all 10 CDR Trp sites in a blind validation panel of eight clinical-stage IgG1 antibodies. Leveraging the long-range nature of electrostatic effects, we show that targeted distal charge-altering mutations, without direct modification of the oxidation-prone Trp, reduce oxidation rates by approximately 50% in four of five re-engineered antibodies, with binding affinity preserved in two. In a clinically relevant anti-CD33 antibody where the critical CDR Trp oxidizes at 97% and Trp-to-Phe substitution abolishes binding, iterative electrostatic optimization yielded variants with up to ~50% oxidation reduction, including one single-point-mutation variant achieving 27% oxidation reduction at only 1.4-fold affinity cost, substantially outperforming direct Trp substitution. Redox replica-exchange molecular dynamics simulations provide mechanistic support, revealing an 88 mV increase in Trp reduction potential upon distal charge-reversing mutations. Together, these results establish local electrostatics as a predictive, tunable, and mechanistically grounded handle for rational antibody engineering, and provide a practical framework for simultaneously optimizing oxidation stability and antigen-binding function.</p>","PeriodicalId":18206,"journal":{"name":"mAbs","volume":"18 1","pages":"2713231"},"PeriodicalIF":7.9,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13475319/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148725995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient inference of non-polyreactive antibody variants dependent on local fine-tuning.","authors":"Matthew Saunders, Sophie Comyn, Borka Medjo, Zahra Anderson, Chase LaCombe, Jake Ripley, Kyra Chapman, Tim Ma, Abigail Ventura, Alyssa Ruelos, Alec Jaeger, Chase Poindexter, Ophelia Rebanal, Nemanja Vuvic, Sean M West, David Eavarone, John M Sutton, Douglas Ganini da Silva, David A Spencer","doi":"10.1080/19420862.2026.2692763","DOIUrl":"10.1080/19420862.2026.2692763","url":null,"abstract":"<p><p>Antibody polyreactivity, which is characterized by broad, low-affinity off-target binding, is an undesirable drug property associated with rapid clearance. Existing <i>in vitro</i> screening methods often suffer from interassay variability, while current <i>in silico</i> models lack the generalizability needed to efficiently identify non-polyreactive variants within the localized sequence spaces typical of drug‑optimization campaigns. Here, we address both challenges through refining low‑ and high‑throughput assays suitable for generating standardized datasets and quantifying the impact of localized protein language model (PLM) tuning in a specific drug‑optimization context. We demonstrate that range‑normalized summation scores derived from multi-concentration monoclonal antibody ELISA provide highly reproducible ground-truth measurements with inter-experiment Pearson <i>r</i> ≥ 0.99. We verified a previously developed yeast-display high-throughput approach for polyreactivity data generation and screened a library of 240,000 single-chain variable fragment heavy‑chain complementarity-determining region variants, then used this data to fine-tune two PLMs. As expected, local fine-tuning dramatically improved model performance on a test set in the relevant sequence space, while performance on an out-of-distribution set of 80 clinical antibodies was largely unchanged. The top‑performing base and tuned models were tasked with inferring 18 low or non-polyreactive variants. The observed inference success rates were 0% and 66.6%, respectively, demonstrating the practical utility of local tuning in a drug development context. Together, this work provides a reproducible, integrated framework combining robust <i>in vitro</i> assay methodology with locally tuned <i>in silico</i> models to efficiently resolve polyreactivity during antibody optimization.</p>","PeriodicalId":18206,"journal":{"name":"mAbs","volume":"18 1","pages":"2692763"},"PeriodicalIF":7.9,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13313185/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148317949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preclinical development of ABL206, a novel bispecific antibody-drug conjugate targeting B7-H3 and ROR1.","authors":"Jung A Kwon, Suyoun Lee, Juhee Kim, Byeong Min Yoo, Hyeon Ji Park, Ilhwan Ryu, Junyoung Kim, JaeHyun Eom, Yong-Gyu Son, Donghoon Yeom, Byungje Sung, Myeonghan Yoo, Arim Seo, Jiseon Yoo, Jin Young Park, Jinwon Jung, Jinhyung Ahn, Weon-Kyoo You, Sang Hoon Lee, Min Ji Ko","doi":"10.1080/19420862.2026.2731283","DOIUrl":"10.1080/19420862.2026.2731283","url":null,"abstract":"<p><p>Bispecific antibody-drug conjugates (BsADCs) represent a promising strategy to enhance tumor selectivity and overcome the limitations of monospecific ADCs. Here, we report the preclinical development of ABL206 (NEOK001), a novel BsADC targeting B7-H3 and ROR1, which are frequently co-expressed in various solid tumors. ABL206 was engineered in a 2 + 2 format and site-specifically conjugated with tavatecan, an exatecan-based linker-payload, utilizing GlycoConnect® technology to yield a highly homogeneous molecule with a drug-to-antibody ratio (DAR) of 4. <i>In vitro</i>, ABL206 demonstrated specific dual antigen binding, internalization, potent target-dependent cytotoxicity and a bystander killing effect. <i>In vivo</i>, ABL206 induced superior tumor regression, outperforming exact-matched monospecific ADCs at equimolar doses. Across 38 patient-derived xenograft (PDX) models spanning nine tumor types, ABL206 demonstrated broad translational potential with strong tumor regression. ABL206 consistently outperformed clinical-stage benchmark monospecific ADCs, ifinatamab deruxtecan (I-DXd) and zilovertamab vedotin, and effectively induced regression in I-DXd-pretreated regrowing tumors. Furthermore, ABL206 exhibited excellent <i>in vitro</i> plasma stability, a robust pharmacokinetic profile in rodents and non-human primates, and a favorable safety profile with the highest non-severely toxic dose (HNSTD) of 60 mg/kg in cynomolgus monkeys. Collectively, these data provide a comprehensive preclinical proof-of-concept for ABL206, supporting its advancement into a Phase 1 clinical trial for patients with advanced solid tumors (NCT07612176).</p>","PeriodicalId":18206,"journal":{"name":"mAbs","volume":"18 1","pages":"2731283"},"PeriodicalIF":7.9,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13577293/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148956194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conformation-aware structure prediction of antigen-recognizing immune proteins.","authors":"Frédéric A Dreyer, Jan Ludwiczak, Karolis Martinkus, Brennan Abanades, Robert G Alberstein, Pan Kessel, Pranav Rao, Jae Hyeon Lee, Richard Bonneau, Andrew M Watkins, Franziska Seeger","doi":"10.1080/19420862.2025.2602217","DOIUrl":"10.1080/19420862.2025.2602217","url":null,"abstract":"<p><p>We introduce Ibex, a pan-immunoglobulin structure prediction model for antibodies, nanobodies, and T-cell receptors. Unlike previous approaches, Ibex explicitly distinguishes between bound and unbound protein conformations by training on labeled <i>apo</i> and <i>holo</i> structural pairs, enabling accurate prediction of both states at inference time. Ibex achieves state-of-the-art accuracy, demonstrating superior out-of-distribution performance on a comprehensive benchmark of high-resolution antibody structures with a mean CDR H3 RMSD of 2.28 Å. Ibex combines this accuracy with significantly reduced computational requirements, providing a robust foundation for accelerating large molecule design and therapeutic development.</p>","PeriodicalId":18206,"journal":{"name":"mAbs","volume":"18 1","pages":"2602217"},"PeriodicalIF":7.9,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12710905/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145723805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multidimensional maturation of antibody variable domains with machine-learning assistance.","authors":"Tomoyuki Ito, Sakiya Kawada, Hikaru Nakazawa, Akikazu Murakami, Mitsuo Umetsu","doi":"10.1080/19420862.2025.2611472","DOIUrl":"10.1080/19420862.2025.2611472","url":null,"abstract":"<p><p>In antibody development, a mutagenesis approach has been widely used to improve affinity, but such mutations often compromise biophysical properties. Here, we combined molecular evolution with machine learning to simultaneously improve affinity and expression level of camelid heavy-chain antibody variable domains (VHHs). Using phage display and deep sequencing, we selected five residues in an anti-SARS-CoV-2 VHH for affinity maturation. We constructed training data using experimentally measured expression levels and target affinities of 117 variants with randomized residues. Machine-learning-predicted top-rank variants showed improved expression level and affinity compared to variants in the training data. Several variants achieved 50-70-fold stronger affinities in the pico-molar range and 4-5-fold higher expression level than wild-type. Furthermore, one variant showed 9.5°C improvement in thermal stability. These results highlight the utility of machine learning-assisted molecular evolution as a strategy for multidimensional optimization of antibody properties.</p>","PeriodicalId":18206,"journal":{"name":"mAbs","volume":"18 1","pages":"2611472"},"PeriodicalIF":7.9,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12785217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145912156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of knockdown approaches for the generation of stable cell populations expressing afucosylated antibodies.","authors":"Maria Tsachaki, Andrew Samy, Mégane Peltret, Timothee Brunstein Laplace, Emilie Vaxelaire-Hily, Farid Mosbaoui, Anna Galea, Francesca Contarin, Lionel Duarte, Roberto Giovannini, Martin Bertschinger","doi":"10.1080/19420862.2026.2684393","DOIUrl":"10.1080/19420862.2026.2684393","url":null,"abstract":"<p><p>Targeted silencing of cellular genes in cell lines stably expressing a secreted recombinant protein offers a flexible and convenient strategy for modulating product quality attributes. However, unlike genetic knockout of a cellular gene or the use of potent inhibitors to eliminate cellular enzyme activity, gene knockdown approaches using microRNAs (miRNA) or short hairpin RNAs (shRNA) may result in only partial reduction of enzyme activity and only partial change of the desired product quality attribute. Moreover, through saturation of the Dicer pathway, shRNA may introduce cytotoxic effects that affect product yield. In this study, we demonstrate that miRNAs are a more suitable tool than shRNAs for α1,6-fucosyltransferase (FUT8) knockdown in Chinese hamster ovary (CHO) cells, when expressed under the control of an RNA-Polymerase II promoter. In the presence of miRNAs targeted to the FUT8 mRNA, the fucosylation levels of the N-glycan linked to Asn297 (EU numbering) of a recombinant monoclonal antibody (mAb) were considerably reduced (>90% afucosylation by hydrophilic interaction liquid chromatography - high‑performance liquid chromatography; no detectable fucosylated product by intact mass spectrometry), without a relevant impact on mAb expression. By comparison, overexpression of shRNAs targeted to the FUT8 mRNA resulted in higher levels of residual fucosylation of the mAb and a larger reduction in mAb titers. miRNAs overcame a limitation of the knockdown approach with shRNAs, making this approach a valuable tool for biopharmaceutical manufacturing.</p>","PeriodicalId":18206,"journal":{"name":"mAbs","volume":"18 1","pages":"2684393"},"PeriodicalIF":7.9,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13274123/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148239723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and preclinical characterization of an affinity-tuned BCMA×CD3 bispecific T-cell engager for broad B-cell depletion.","authors":"Jamie Thomas, Gang Xu, Hannah Lock, Qin Song, Yumei Yin, Wanying Luo, Kyu Hong, Liguang Lou, Changyu Wang, Leslie Chinn, Neelufar Mozaffarian, Jaideep Dudani, Paul Bessette, Charlie Zhou, Ruth Lan, Bo Chen, Nishant Mehta","doi":"10.1080/19420862.2026.2718587","DOIUrl":"10.1080/19420862.2026.2718587","url":null,"abstract":"<p><p>B cell maturation antigen (BCMA) is a validated target for plasma cell depletion; however, T cell-redirecting approaches must balance potent cytotoxicity with controlled T cell activation. Here, we describe the design and preclinical characterization of gamgertamig, an affinity-tuned BCMA×CD3 bispecific T-cell engager engineered to promote target-dependent activity. Gamgertamig is a humanized IgG4-based 1 + 1 bispecific antibody incorporating Fc-silencing mutations and a reduced-affinity CD3-binding arm, resulting in a >50-fold affinity bias toward BCMA relative to CD3. Gamgertamig exhibited high-affinity binding to BCMA and mediated potent, antigen-dependent cytotoxicity across B cell and myeloma cell lines spanning a wide range of target densities, with sub-nanomolar EC₅₀ values. In primary human peripheral blood mononuclear cells (PBMCs), gamgertamig induced robust depletion across B cell subsets, including naïve, memory, and transitional populations. Consistent activity was observed across samples from healthy donors and patients with autoimmune diseases and multiple myeloma. In vivo, gamgertamig produced dose-dependent tumor inhibition in human PBMC-reconstituted xenograft models and sustained depletion of circulating B cells and bone marrow plasma cells in rhesus monkeys, with a serum half-life exceeding five days. Together, these data demonstrate that gamgertamig mediates potent, target-dependent cytotoxicity and broad depletion of disease-relevant B-cell populations, supporting its development as a BCMA×CD3 T-cell engager for autoimmune diseases and B-cell malignancies.</p>","PeriodicalId":18206,"journal":{"name":"mAbs","volume":"18 1","pages":"2718587"},"PeriodicalIF":7.9,"publicationDate":"2026-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13501987/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148794942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}