Antibody Therapeutics

Human epidermal growth factor receptor 2 (HER2) is an oncogenic receptor tyrosine kinase in breast cancer and other malignancies. A subset of HER2-positive tumours expresses 611-CTF-p95HER2, a tumour-specific, hyperactive truncated isoform associated with metastasis and treatment resistance that lacks most of the extracellular domain targeted by conventional HER2-directed antibodies. We previously developed NAZ-mAb (formerly known as Oslo-2), a monoclonal antibody against 611-CTF-p95HER2. Here, we describe a computational antibody-engineering workflow for designing variants of NAZ-mAb. Starting from the sequence alone, we modeled the NAZ-mAb-611-CTF-p95HER2 complex, generated a combinatorial mutational landscape using FoldX 5.0, and prioritized candidate variants using predicted interaction energy and developability criteria. Two variants representing distinct design strategies were selected for validation: an aromatic double mutant, NAZ-mAb v1 (L:S31W/L:H107W), and a conservative single mutant, NAZ-mAb v2 (L:S31M). Both variants were successfully expressed as recombinant IgGs; NAZ-mAb v2 achieved a five-fold higher recombinant expression yield than parental NAZ-mAb, while both variants retained antigen binding with a higher apparent signal than the parental antibody in indirect ELISA. However, Biacore two-state kinetic analysis revealed weaker affinities than the parental antibody (KD NAZ-mAb v1: 32.6 nM, NAZ-mAb v2: 9.45 nM vs. parental NAZ-mAb: 5.33 nM). These findings show that the computational workflow can generate experimentally tractable, antigen-engaging NAZ-mAb variants, while also highlighting the limitations of fixed-backbone interaction-energy ranking as a predictor of binding affinity and yield. This study provides a practical framework for computationally driven, developability-aware antibody optimization in the absence of experimental structural data.

Pancreatic cancer remains a highly lethal malignancy with limited therapeutic options. Chimeric antigen receptor (CAR) therapy has revolutionized the treatment of hematological cancers but still faces major limitations in solid tumors, particularly due to the scarcity of tumor-specific targets. Cutaneous lymphocyte antigen (CLA) recently emerged as a promising PDAC target due to its high tumor expression and limited presence in healthy tissues. However, previously reported CLA-directed CAR constructs lacked antitumor functionality. Here, we investigated multiple strategies to generate functional CLA-targeting CAR approaches. We first hypothesized that impaired activity resulted from fratricide caused by CLA expression on activated T cells. CLA knockout was successfully achieved through deletion of fucosyltransferase-7, but not by knockout of the major CLA carrier backbones CD162, CD44 or CD43, suggesting additional CLA carriers or compensatory regulation. As CLA knockout alone did not restore CAR-mediated killing, we explored whether insufficient binding affinity limited CAR activity. Affinity maturation was performed in silico and in vitro using yeast surface display, identifying 39 candidate mutations, although none restored cytotoxicity. We finally switched to an AdCAR strategy using anti-biotin CAR T cells combined with biotinylated anti-CLA scFv-Fc adapters. This approach enabled efficient, concentration-dependent cytotoxicity with both CLA-targeting binders. Additionally, we identified a dynamic, cell density-dependent regulation of CLA expression. Finally, glycan profiling of CLA binders further revealed broader-than-expected glycan interactions, suggesting a potentially wider definition of the CLA family. Overall, our findings establish CLA as a functional PDAC immunotherapy target while revealing unexpected complexity in its regulation and molecular presentation.

Fc receptor-like protein 5 (FCRL5) is a low-affinity IgG receptor expressed on B cells, with emerging therapeutic relevance due to its expression on multiple myeloma cells, and a potential role in regulating B cell responses. Previous reports on the FCRL5-IgG interaction vary widely in reported affinities, binding differences across IgG subclasses, and molecular requirements for maximal binding. Furthermore, the impact of Fc-engineering strategies, as used in (therapeutic) monoclonal antibodies, remains poorly understood. Here, we provide a comprehensive biochemical analysis of the FCRL5-IgG interaction. We demonstrate that FCRL5 is a true IgG Fc-receptor, binding with very low affinity (60-80 M). FCRL5 binds IgG in a manner involving primarily the two N-terminal domains of FCRL5, and the third domain for maximal binding, but with distinct essential residues in the IgG Fc-tail. Surface plasmon resonance analysis of the binding of FCRL5 to the various IgG subclasses revealed a preference for IgG1 and IgG4. Interestingly, various Fc-engineered IgG variants commonly used for silencing or enhancing of Fc receptor binding do not impact FCRL5 binding. Screening the binding of a set of IgG antibodies carrying defined sets of Fc-mutations to FCRL5 revealed E293 as a key binding determinant and led to the discovery of E293R as a mutation that selectively abrogates FCRL5 binding while preserving binding to other classical Fc{gamma}Rs. Lastly, we show that FCRL5 has considerable preference for binding afucosylated IgG. Together, our results define the essential characteristics of the IgG-FCRL5 interaction and demonstrate the potential of both naturally occurring IgG variants as well as therapeutically explored bioengineered IgG formats to differentially engage FCRL5.

BackgroundLate-stage attrition in therapeutic antibody discovery is dominated by developability liabilities: aggregation, polyspecificity, charge-driven non-specific binding, and chain-mispairing artefacts. Bispecific antibodies amplify these risks because each additional binding arm adds a new biophysical envelope that must be jointly satisfied. The existing in-silico ecosystem addresses individual axes of this problem (humanization, structure prediction, single-metric developability scoring) but few platforms integrate them end-to-end. PTIm-mAb (SANSHI Bio Solutions Pvt Ltd) is a multi-objective, AI/ML-driven antibody design platform that jointly optimizes sequence liabilities, surface aggregation, charge balance, humanness, and predicted binding affinity, and recommends a bispecific architecture in a single workflow. MethodsWe applied PTIm-mAb to the published sequences of eleven FDA-approved bispecific antibodies using the platforms default-parameter Pareto-acceptance optimization loop, run to convergence or to the internal iteration ceiling, with no human curation between the platform run and the external profiler. Both wild-type and platform-optimized sequences were profiled independently with three publicly available developability tools: Aggrescan, CamSol, and the Therapeutic Antibody Profiler (TAP). Paired-sample tests (Wilcoxon signed-rank, exact binomial sign test, McNemar exact test) evaluated the direction and significance of changes. ResultsAcross the 17 evaluable paired arms profiled by TAP, PTIm-mAb cleared four wild-type CDR-vicinity Positive Charge Patch (PPC) flags Blinatumomab-Arm1 (1.9952 [->] 0.6885), Mosunetuzumab-Arm1 (1.3391 [->] 0.0568), Linvoseltamab-Arm2 (0.8060 [->] 0.0), and the headline Elranatamab-Arm1 case (1.7981 [->] 0.5799) achieved without trading off any other in-range metric and corroborated by Aggrescan and CamSol on the same arm. Total CDR length was significantly shortened across the cohort (Wilcoxon two-sided p = 0.0075, one-sided p = 0.0037, effect size r = 0.65): significant improvement on the metric most directly under the optimizers control. The directional shift on Aggrescan integrated aggregation propensity was also significant by sign test (24 of 36 chains improved, 2 unchanged, 10 worsened; p = 0.021). On the already-clean Zenocutuzumab profile the optimizer identified residual headroom (PPC 0.1191 [->] 0.0; SFvCSP 12.5 [->] 6.0), demonstrating that the platforms value extends to candidates that pass all flags. Three results: Teclistamab Arm-1, Emicizumab, and Talquetamab Arm-2 did not clear all flags and are presented as candidates for iterative re-invocation of the platform pipeline on the optimized output (planned follow-up; Section 5). The remaining TAP metrics (PSH, PPC magnitude, PNC, |SFvCSP|) trended in the improvement direction without reaching significance in this cohort, a pattern consistent with the expected statistical signature of a multi-objective optimizer applied to molecules already within the clinical-stage envelope. The platform reported a mean of 12.8 months and USD 723,889 of computational front-loading per project across the nine-project cohort (range 9.0-16.0 months; USD 510,000-960,000); the underlying cost assumptions are tabulated in Supplementary Table S3. ConclusionPTIm-mAb produces externally verifiable, literature-aligned improvements on the metrics most directly under its control, clears CDR-vicinity charge-patch flags on a meaningful fraction of flagged candidates, and front-loads substantial design-iteration work. The cohort-level pattern is consistent with a calibrated multi-objective optimizer operating at the edge of detectable headroom on a deliberately hard benchmark. We position the platform as an early-stage triage and lead-optimization layer in bispecific antibody discovery. For molecules whose first-pass result does not clear all flags, iterative re-invocation of the pipeline on the optimized output is a natural follow-up direction.

Integrin v{beta}8 is a major activator of latent transforming growth factor-{beta} (TGF-{beta}) and an emerging therapeutic target in cancer and immune regulation. However, functional assays that directly measure v{beta}8-mediated activation of latent TGF-{beta} in a physiologically relevant context remain limited. Here, we report a co-culture cell-based reporter assay for quantitative measurement of v{beta}8-mediated activation of latent TGF-{beta}1. NIH/3T3 reporter cells were engineered to express a SMAD-responsive NanoLuc reporter, constitutive firefly luciferase for internal normalization, and cell-surface GARP-latent TGF-{beta}1. When co-cultured with v{beta}8-expressing LN-229 cells, reporter cells produced a robust signal that directly reflected localized latent TGF-{beta}1 activation. The assay demonstrated stable expression of the required biological components, reproducible signal-to-background performance, and sensitivity to benchmark v{beta}8-blocking antibodies. Inhibition studies showed potent dose-dependent blockade by an anti-v{beta}8 antibody. In contrast, pan-TGF-{beta} neutralizing antibody displayed markedly weaker apparent potency, suggesting that targeting localized v{beta}8-mediated activation is more effective than neutralizing released TGF-{beta} in this assay context. The assay also enabled screening and ranking of anti-v{beta}8 antibodies, identifying several high-potency clones, and detected v{beta}8-mediated activation of a non-cleavable latent TGF-{beta}1 mutant. This platform provides a sensitive, internally normalized, and scalable approach for mechanistic studies and therapeutic discovery targeting the v{beta}8-TGF-{beta} axis.

Colorectal cancer (CRC) remains a significant contributor to cancer-associated deaths worldwide, indicating the need for new therapeutic targets and modalities. Antibody-drug conjugates (ADCs) have demonstrated remarkable potential for the treatment of various cancer types, although their efficacy as monotherapies is often limited by insufficient targeting of tumor heterogeneity, dose-limiting toxicities, and drug resistance. Accordingly, multi-targeting therapeutic strategies, such as bispecific ADCs (bsADCs), which simultaneously target two cancer-associated antigens or non-overlapping epitopes on the same antigen, may prove more effective at overcoming resistance and eliminating tumors compared to monospecific ADCs. In this work, we describe the development of EGFR:LGR5 bispecific antibodies (bsAbs) and bsADCs. EGFR:LGR5 bsAbs were shown to internalize to the lysosome to a greater extent than EGFR- and LGR5-targeting monoclonal antibodies (mAbs) and drive EGFR lysosomal degradation in an LGR5-mediated fashion. However, EGFR:LGR5 bsAbs exerted suboptimal cytotoxicity in CRC cell lines. We therefore engineered an EGFR:LGR5 bsADC that demonstrated 100- to 1000-fold enhanced efficacy over a previously developed LGR5-targeting monospecific ADC (8E11-CPT2) with an identical linker-payload in CRC cell lines of various genetic backgrounds and EGFR and LGR5 expression levels. EGFR:LGR5 bsADC potency was strongly correlated with cell line sensitivity to the CPT2 payload. EGFR:LGR5 bsADC induced tumor regression in select RASMUT CRC xenograft models and demonstrated superior antitumor activity and prolonged survival benefit in all evaluated models versus EGFR mAb cetuximab (CTX), bsAb, and 8E11-CPT2. These findings strongly support the further development of EGFR and LGR5 dual-targeting approaches for CRC and other EGFR- and LGR5-expressing malignancies. One Sentence SummaryEGFR:LGR5 bsADCs exert robust antitumor activity and outperform EGFR:LGR5 bsAb and LGR5 monospecific ADC in RASWT and RASMUT colorectal cancer models.

The role of antigen-specific T cells responding to antigen is a topic of intense studies, and critical for mechanistic insight of diseases and development of therapeutic strategies. Methods for broad-scale detection of antigen-specific CD4 T cells are lacking, while such methods have demonstrated great value in exploring CD8 T cell response in health and disease. Furthermore, major histocompatibility complex II (MHCII) assays are technically challenging due to high HLA diversity, lower binding affinities, low frequencies of ex vivo antigen-specific CD4 T cells and several bottlenecks in production and peptide exchange of MHCII monomers. Here we use peptide-loaded MHCII (pMHCII) proteins multimerized on a barcode- and fluorophore-labelled dextran backbone to provide a method for the detection of peptide-specific CD4 T cells by using a large display of MHCII-associated peptides. We have established a protocol for MHCII production and peptide-exchange suitable for the generation of large libraries of peptide-MHCII complexes. We validate the use of such pMHCII complexes in the form of barcode-labelled MHCII multimers to detect antigen-specific CD4 T cells. We demonstrate that we can identify antigen specific CD4 T cells, using these DNA barcoded peptide-MHCII multimer. The multimer bound CD4 T cells were selected based on the fluorochrome signal, and the co-attached DNA barcodes were hereafter amplified and used to identify the peptide-MHCII response/binding. In cases where the peptide-specific CD4 T cells frequencies are very low, we expanded the cell population with peptide-pools and in the presence of IL2. The given CD4 T cell populations hereby reach a cell number allowing for the DNA-barcoded pMHCII multimers to detect responses otherwise missed out. Applying this technology, we utilized a panel of 150 peptides derived from human cytomegalo virus (CMV), Epstein barr virus (EBV), Influenza (Flu), SARS CoV 2 and SARS CoV1, Hepatitis B virus (HBV), and Hepatitis C virus (HCV) loaded onto HLA-DRB1*01:01 and DRB1*04:01 to screen peripheral blood mononuclear cells (PBMC). We assessed ex vivo responses in 16 participants with HCV infection, and successfully detected naturally occurring viral-specific CD4 T cells at frequencies as low as 0.004% of total CD4 T cells. The low-frequency responses, identified via the barcode screen, were rigorously validated using individual fluorophore-labelled tetramer staining after a peptide-driven expansion in 15 participants. Furthermore, we assessed the recognition of novel HCV epitopes in 11 additional participants. Through this, we identified a total of 12 distinct HCV epitopes, including 9 that have not been previously utilized in assays to detect CD4 T cells. Overall, this barcoded-multimer platform provides a powerful tool for the large-scale discovery of class II epitopes and the broad profiling of CD4 T cell specificities. This method will allow for in-depth analyses of immune interactions, provide a better understanding of the antigen-driven associations between CD4 and CD8 T cell responses, and help dissect the complexities of CD4 T cell protection in HCV infection.

The rapid emergence of SARS-CoV-2 variants that evade neutralizing antibodies underscores the need for next-generation antiviral biologics that combine molecular precision with scalable, cost-effective manufacturing. Computationally designed miniproteins targeting the receptor-binding domain (RBD) of the spike protein offer a compelling alternative to monoclonal antibodies due to their small size, high thermal stability, and compatibility with microbial expression systems. Here we report the end-to-end development and cGMP production of IPD-52520, a de novo antiviral miniprotein, using an optimized E. coli platform. Two miniprotein candidates, a homotrimeric construct (Trimer is referred to as IPD-52520, 17 kDa) and a tandem fusion (Daisy is referred to as IPD-52521, 25 kDa), were evaluated in parallel through systematic optimization of strain selection, media composition, fed-batch fermentation, inclusion-body solubilization, refolding, and chromatographic purification. The Trimer was downselected as the lead molecule based on superior preclinical efficacy, favorable pharmacokinetic properties, and higher volumetric manufacturing yields. The optimized process delivers approximately 2 g/L of purified protein at greater than 90% purity. Scale-up from 5 L to 50 L under cGMP conditions demonstrated excellent batch-to-batch reproducibility across six independent batches, supporting nonclinical and Phase 1 clinical supply. Comprehensive biophysical characterization confirmed a well-folded, predominantly alpha-helical trimer (Tm = 73.4 {degrees}C; polydispersity = 1.005) with an intact primary structure and strong target-binding affinity (KD < 1 pM). Real-time stability studies indicate that the drug substance is stable at 2-8 {degrees}C for at least 12 months, with ongoing stability studies. These results demonstrate the feasibility of translating computationally designed antiviral miniproteins into manufacturable biologics and provide a platform applicable to rapid-response therapeutics against current and future pandemic threats.

Background: Medulloblastoma (MB) is the most common malignant brain tumour in children, and aggressive subgroups are frequently driven by the oncoproteins MYC or MYCN. Direct therapeutic targeting of MYC/MYCN has been challenging because of their intrinsically disordered protein structures. The aim of this study was to determine whether novel SE486-11 analogues (UNSW-SCs) can therapeutically target MYC/MYCN-driven MB. Methods: The anticancer activity of UNSW-SCs was assessed in MB cell lines with differential MYC/MYCN expression. Target engagement was evaluated using surface plasmon resonance and drug affinity responsive target stability assays. Blood-brain barrier penetration, MYC/MYCN protein degradation, cell cycle effects, apoptosis, DNA damage, and synergy with histone deacetylase (HDAC) inhibitors were examined. Therapeutic efficacy was evaluated in murine models of MYC- and MYCN-driven human MB. Results: UNSW-SCs showed potent anticancer activity, with preferential selectivity toward MB cells expressing high MYC/MYCN levels and IC50 values ranging from 0.22 to 1.18 M. The lead molecule, UNSW-SC-22, directly bound MYC, crossed the blood-brain barrier, and achieved a brain-to-plasma ratio of 1.44 at peak concentrations. UNSW-SC-22 induced MYC/MYCN-dependent cytotoxicity associated with enhanced proteasomal degradation, cell cycle arrest, apoptosis, and DNA damage. Combined treatment with HDAC inhibitors further reduced MYC/MYCN protein levels, increased DNA damage, and enhanced apoptosis. In vivo, UNSW-SC-22, either alone or with entinostat, significantly suppressed intracranial tumour growth and prolonged survival. Conclusions: UNSW-SC-22 is a brain-penetrant MYC/MYCN-targeting molecule with potent preclinical activity in MYC/MYCN-driven MB, supporting its development as a monotherapy or combination strategy with HDAC inhibition.

Immune cell engagers (ICE) such as bispecific antibodies (bsAbs), within an immunological synapse, bind and link CD3 on a T cell to a target antigen (TAA) on a cancer cell, forming a trimer (CD3:bsAb:TAA complex). With sufficient trimer numbers within the synapse, the T cell can become activated and promote cancer cell killing. Elranatamab, a CD3-bispecific antibody for multiple myeloma, has received FDA and EMA filing acceptance (August 2023 and December 2023, respectively) adding to a growing list of bsAbs that are treating patients. In the drug development stages of ICE bsAbs, mechanistic modeling approaches are often used to attain a greater quantitative understanding of the modality, preclinically, and provide human pharmacokinetic and efficacious dose predictions to aide in Phase 1 trial design. To date, the majority of ordinary differential equation (ODE) trimer models treat the tumor compartment as well-mixed and trimer formation is governed by a bulk population reaction not accounting for individual synapses. This lack of discrimination can lead to imprecise analysis when analyzing results across E:T ratios using metrics like trimers per T cell or trimers per target cell. To this end we developed an ODE trimer model based on single-synapse complexes (one target cell/one immune cell) with 2D cross-linking trimer formation. We show computationally that the number of trimers per synapse is invariant to the value of the E:T ratio for a given free bsAb concentration, a property that cannot be captured by non-synapse models. A simple demonstration of this discrepancy using the well-known Betts trimer model is presented. We then apply the Betts trimer model coupled to a tumor growth inhibition (TGI) module to show that our synapse-based trimer model is easy to substitute in to model TGI, including the addition of a trimer-per-synapse activation threshold function for cell killing. Overall, our model attempts to balance mechanistic fidelity while limiting the complexity of the model.

Human Immunodeficiency Virus (HIV)-1 broadly neutralizing antibodies (bNAbs) have demonstrated clinical efficacy, but face manufacturing challenges associated with recombinant protein production and purification. Here, we present a ribonucleic acid (RNA)-encoded bNAb (RibobNAb) platform that enables in vivo antibody production of the clinically validated bNAb PGT121 via lipid nanoparticle (LNP) delivery, supporting rapid evaluation of Fc variants (LS, del294, LS-del294) in vitro and in vivo. We confirmed expression, sub-nanomolar HIV-1 Env binding, and potent neutralization across all RibobNAb variants in vitro. In mice, single RNA-LNP administrations yielded in vivo expression of all RibobNAb variants, with PGT121-LS exhibiting a prolonged half-life compared with PGT121. In non-human primates (NHPs), a single intravenous administration of PGT121-LS RNA-LNP was well tolerated without anti-drug antibody (ADA) formation over 180 days and resulted in PGT121-LS half-lives comparable to the reference protein. Single intramuscular administration showed RibobNAb expression but resulted in ADA development from Day 14 onwards and lower bioavailability. In vivo-expressed PGT121-LS RibobNAb retained identical antiviral functionality to PGT121-LS reference protein. An NHP pharmacokinetics model integrating RNA transfection and translation dynamics enabled allometric scaling and first-in-human dose prediction. We highlight RibobNAbs as an alternative to conventional purified protein antibodies for rapid development of bNAb-based therapeutic strategies.

Influenza A viruses H3N2 and H10N5 represent, respectively, a persistently dominant seasonal pathogen and a newly documented zoonotic threat with the latter strain variants responsible for the first confirmed human fatality in January 2024, yet no vaccine platform currently addresses co-protection against both subtypes within a unified immunogen. We report here the immunoinformatics based vaccine design and multi-layered computational validation of a 419-amino-acid multi-epitope subunit vaccine construct targeting conserved hemagglutinin (HA) and neuraminidase (NA) antigens identified through multiple sequence alignment of the avian H10N5 (A/swine/Hubei/10/2008) and H3N2 human reference strain sequences to identify viral agents undergoing mammalian adaptations. Linear B-cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes were predicted using ABCpred, BCEpred, BepiPred 2.0, NetMHCpan 2.1, and NetMHCpan 4.0, then filtered through VaxiJen 3.0, AllerTOP v2.1, and ToxinPred to retain only antigenic, non-allergenic, non-toxic candidates. The final construct, incorporating an avian {beta}-defensin N-terminal adjuvant with GPGPG, AAY, and EAAAK linkers, exhibited a molecular weight of 43.9 kDa, instability index of 31.15, and SOLPro solubility probability of 0.763. Tertiary structure modeling via I-TASSER and GalaxyRefine achieved 84.4% Ramachandran-favored residues. Molecular docking against TLR3 and TLR7 yielded binding free energies of -16.1 and -16.8 kcal/mol with picomolar dissociation constants. Molecular dynamics simulations confirmed complex stability over extended trajectories. Furthermore, codon optimization produced a Codon Adaptation Index of 1.0 for E. coli K12 expression. In silico immune simulation demonstrated robust activation of humoral and cellular immunity including elevated IgG1, IgM, IFN-{gamma}, IL-2, rapid NK cell expansion, and broad B-cell clonal diversity. These findings establish a computationally validated candidate capable of providing protection against influenza in multiple host organisms, warranting experimental advancement.

Tuberculosis (TB) remains a leading global cause of infectious mortality due, in part, to the limited efficacy of the Mycobacterium bovis BCG vaccine against pulmonary TB. Previous studies in mice have shown that stimulating type I interferon (IFN) signaling during BCG vaccination can bolster protection against Mycobacterium tuberculosis, yet clinically feasible delivery strategies for this approach are lacking. Adenoviral vectors, which induce potent type I IFN responses and are utilized in approved vaccine platforms, represent a promising adjuvant strategy. To evaluate the host immune response to this combination, bone marrow-derived murine macrophages were co-infected with replication-deficient adenovirus and BCG. Adenovirus-infected macrophages elicited a robust type I IFN response via the cGAS/STING pathway. Compared to BCG infection alone, co-infected macrophages exhibited additive expression of genes with known host-protective roles against M. tuberculosis. Conversely, co-infection with BCG suppressed adenovirus-induced type I IFN signaling and diminished the production of IFN-stimulated genes compared to adenovirus infection alone. Together, these findings reveal a complex regulatory interplay during adenovirus and BCG co-infection. While BCG partially restricts adenoviral IFN induction, the co-infection still drives an enhanced host-protective gene profile, suggesting that adenoviral vectors could serve as a viable platform to modulate innate immunity and improve BCG vaccine efficacy. IMPORTANCETuberculosis (TB) remains the leading cause of death by a single infectious organism with approximately 1.25 million deaths annually. M. bovis BCG remains the only approved vaccine for TB; however, its efficacy against the contagious and most common pulmonary form of the disease is limited. There have been numerous attempts to improve BCG efficacy, but these approaches have not resulted in any clinically approved vaccine. We propose that BCG combined with a replication-deficient adenovirus presents a way to bolster vaccine-conferred protection as the combination may elicit a robust innate immune response and drive a more protective T cell response. Moreover, BCG and replication-deficient adenoviruses have well-assessed safety profiles and decades of studies regarding their use in patients. The significance of our work is in leveraging their complementary immunology to function as a combined vaccine platform. This approach presents a novel and clinically feasible approach to improve the BCG vaccine.

Predicting linear B-cell epitopes is a basic immunoinformatics task that has a direct impact on vaccine design and antibody engineering. Recent advances in machine learning have improved predictive performance, but most existing approaches are trained on aggregated datasets and assume that antigenic patterns are conserved across host organisms. This assumption ignores the immunological variability depending on the host and prevents generalizing the model across species. This is the first systematic host-wise evaluation where we present a systematic machine learning-based analysis of host-aware linear B-cell epitope prediction using curated datasets from the Immune Epitope Database (IEDB). We build separate datasets for human, mouse, and non-human primate hosts and assess several classification models, including Random Forest, Support Vector Machine (SVM), Gradient Boosting, XGBoost, and K-Nearest Neighbors (KNN). The models exploit feature representations derived from sequences, such as AAIndex descriptors, biochemical properties from ExPASy, and dipeptide composition. Our results show that predictive performance differs substantially across hosts. Models achieve up to 86.07% accuracy and 0.93 ROC-AUC on human datasets but lower performance on mouse and non-human primate datasets. This gap underlies dataset bias and sequence distribution differences, as well as the inability of existing features to capture host-specific immunological context. These results indicate that the prediction of linear B-cell epitopes is intrinsically host-specific, and a single global model does not generalize well across species. We propose to incorporate host-aware modeling strategies and organism-specific features for enhanced predictive reliability and biological relevance.

Current SARS-CoV-2 vaccines provide limited breadth of protection, underscoring the need for vaccine strategies that optimize immune responses. Virosomesoffer a modular vaccine platform that enables multivalent antigen display and incorporation of adjuvants which can steer immune responses. We evaluated the immune response in BALB/c mice with virosomes displaying SARS-CoV-2 Wuhan or Delta spike antigens and coupled with various distinct adjuvants. Adjuvant selection differentially influenced both humoral and cellular immune outcomes. The TLR7/8 agonist 3M -052 induced a strong Th1-biased response, characterized by elevated IgG2a/IgG1 ratios and robust type 1 cytokine induction with suppression of Th2-associated cytokines. In contrast, the saponin QS-21 enhanced antibody functional quality, illustrated by improved virus neutralization potency and breadth. Furthermore, the combined incorporation of both 3M-052 and QS-21 induced an elevated Th1-biased response without improving neutralization capacity. In conclusion, different adjuvants added onto our virosome-basedvaccine led to distinct antibody responses and splenic T-cell profiles, reflective of differences in immune programming. This information guides the selection of adjuvants for respiratory virus vaccines.

Determining the structural basis of antigen recognition by antibodies and T cell receptors (TCRs) provides critical insights into effective immune targeting and can inform design of biotherapeutics and vaccines. Accurate computational modeling of antibodies and TCRs in complex with their targets poses a major challenge for predictive methods, including AlphaFold, which is generally accurate for modeling protein complexes but has shown limited success for immune recognition. In this study we assessed the performance of AlphaFold2, AlphaFold3, increased sampling protocols, and related deep learning methods for modeling antibody-protein, antibody-peptide, and TCR-peptide-major histocompatibility complex (pMHC) recognition. We show that increased sampling and AlphaFold3 generally improve performance relative to default sampling and AlphaFold2, however predictive accuracy and improvement levels varied considerably among interface classes, with antibody-peptide complexes representing a challenge despite their small antigen size. Comparing per-case success across methods showed some complementarity, indicating opportunities for increased success through model pooling approaches, for instance increasing antibody-peptide near-native success from 41% to 59%. Analysis of AlphaFold confidence scores and modeling of a noncanonical complex provided further insights into predictive performance. These results highlight considerations for predictive antibody and TCR complex modeling efforts, while revealing key distinctions among protocols, scoring, and immune complex classes.

Lipoarabinomannan (LAM) is a useful biomarker for detection of M. tuberculosis infection and disease. Related antigens can be detected in urine samples of TB patients by combinations of monoclonal antibodies (mAbs) directed against specific epitopes expressed in LAM. While sensitive for samples from patients with active TB disease who have HIV-1 co-infections, these assays are less effective for other populations, and there is therefore a need for more sensitive antibodies that can improve the sensitivity of these assays. Here we characterize the antigen and epitope specificities, sequence diversity and isotype dependencies of eight LAM-specific human mAbs that target five distinct arabinose- and mannose-dependent epitopes present in LAM and lipoarabinomannan (LM). Whereas all of the mAbs recognized ManLAM, only a few, including A194-01, consistently detected antigens in TB+ urine samples. Converting A194-01 from the IgG1 to the IgM isotype resulted in broader recognition of poly-Ara glycan epitopes, and increased sensitivity for clinical antigens when combined with several capture reagents, including RU95-C1, a novel antibody targeting the mannan domain of LAM. These results define novel epitopes that are differentially expressed in bacterial and urinary forms of LAM, and identify novel antibody combinations which possess enhanced diagnostic utility for clinical forms of LAM.

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy with limited therapeutic options, underscoring the need for innovative treatments. Chimeric antigen receptor (CAR) therapy has transformed hematologic malignancies but faces key challenges in solid tumors, particularly on-target/off-tumor toxicity and antigen heterogeneity. Adapter CAR (AdCAR) platforms offer enhanced control by decoupling antigen recognition from CAR activation, enabling controllable, reversible, and multi-antigen targeting. Recent studies suggest AdCARs can function as an AND-gate using combinations of adapter molecules at controlled surface densities. This defines activation thresholds, termed the Surface Activation Matrix, that restricts full activation to tumor cells overexpressing the target antigen combination, thereby reducing off-tumor toxicity. In this study, we evaluated its applicability to PDAC using adapters targeting CD318, TSPAN8 and CD66c. We systematically evaluated single and combinatorial adapter dosing in co-culture assays with AsPC1 cells, in a donor-dependent manner. Low concentrations of individual adapters were non-cytotoxic, whereas combining them at identical sub-threshold doses restored potent tumor killing, demonstrating that AdCAR activation depends on cumulative adapter density rather than total amount. However, the activation threshold required for AND-gate cytotoxicity varied between donors, highlighting the need for patient-specific titration to achieve selective tumor killing. These findings validate that AdCAR T cell activity in PDAC can be finely tuned through adapter concentration and combinatorial targeting, enabling selective tumor recognition while minimizing on-target/off-tumor toxicity. This flexible, safety-oriented strategy supports targeting heterogeneous PDAC tumors, though donor-dependent variability remains a critical consideration for clinical implementation.

Adoptive T-cell therapies rely on the identification and expansion of rare tumor-reactive T cells, yet current enrichment strategies are limited by the low abundance of these cells and complexity of their functional enrichment. Here, we present a microfluidic platform that exploits hydrodynamic shear as a controllable parameter for enriching antigen-specific T cells through peptide-major histocompatibility complex (pMHC)-mediated capture. An eight-channel microfluidic device was engineered to simultaneously interrogate a range of wall shear stresses while maintaining uniform cell delivery, enabling systematic identification of shear conditions that maximize antigen-specific enrichment. Using engineered MART-1-specific Jurkat cells, we demonstrate that T-cell capture is jointly regulated by wall shear stress and pMHC density, with intermediate shear preferentially enriching antigen-specific cells over nonspecific binders. Translation of the optimal operating condition to a high-throughput single-shear device enabled approximately 35-fold enrichment of antigen-specific T cells from peripheral blood mononuclear cells containing only 0.05% target cells. We further show that peptide-MHC complexes isolated directly from melanoma whole-cell lysates support shear-dependent enrichment comparable to recombinant pMHCs. Finally, primary MART-1-specific CD8 T cells enriched using tumor-derived pMHCs retained the ability to recognize melanoma cells and upregulated the activation marker CD137 following antigen-specific stimulation. Together, these findings establish hydrodynamic shear as an orthogonal parameter for antigen-specific T-cell enrichment and provide a framework for integrating force-based selection with tumor-derived pMHCs to isolate functional antigen-specific T cells using tumor-derived pMHCs.

Mycobacterium tuberculosis (Mtb) infection kills more people worldwide than any other pathogen. While the Bacille Calmette-Guerin (BCG) vaccine for Mtb has been widely used for over a century, it provides insufficient protection to eradicate this disease. One of our labs has recently established that a protein antigen (H1) can be combined with a STING pathway agonist to achieve strong protection against Mtb in mice, with performance that exceeds that of the BCG vaccine. However, its reliance on a synthetic cyclic dinucleotide (CDN) with relatively poor cell uptake requires higher dosing levels, thus increasing costs. To increase the efficiency of this vaccine and provide a delivery strategy that could also be used in humans, the H1 Mtb antigen and CDN adjuvant were conjugated to genome-free MS2 viral capsids that included cationic mutations to increase cell uptake. Specifically, the H1 antigen was conjugated to the external surface of MS2 using a tyrosinase-mediated oxidative coupling reaction, and the native STING agonist cGAMP was coupled to internal cysteine residues through a reductively cleavable disulfide linker. The resulting MS2-H1 and MS2-cGAMP conjugates were then co-delivered for three doses of vaccination in mice before exposure to Mtb. The MS2-based vaccine platform was observed to have comparable efficacy to the original H1/CDN formulation, but its enhanced uptake properties enabled 57-fold less CDN and 3-fold less H1 antigen. Additionally, this vaccine elicited immune responses that have been previously demonstrated to correlate with protection. The ability of the capsid shells to protect the CDN cargo during transport allowed enzymatically produced, and thus readily accessible, cGAMP to be used instead of more costly CDNs that require many synthetic steps. This, combined with the reduced overall amount of CDN and H1 that was required, could lower the production costs of future vaccines substantially. Finally, the ability of the capsid-based carriers to bypass the membrane transporters for CDNs suggests that this enhanced vaccination platform is likely to exhibit improved human efficacy in future studies.