Antibody Therapeutics

Single-chain variable fragments (scFvs) are widely used in diagnostic and therapeutic applications. These antibody fragments comprise two antibody variable domains connected by a flexible peptide linker whose properties critically influence folding, stability, oligomeric state, and antigen-binding. Therefore, careful linker selection represents a key step in scFv design. Guanylyl Cyclase C (GUCY2C) is a tumor-associated cell surface receptor expressed in gastrointestinal malignancies, including more than 90% of colorectal cancer (CRC) cases across all disease stages. Its restricted physiological expression pattern makes GUCY2C an attractive target for immunotherapy and precision oncology therapies. Here, we investigated the structural and functional consequences of incorporating alternative linker designs into an anti-GUCY2C scFv. Using molecular modeling, protein-protein docking, and molecular dynamics (MD) simulations, we evaluated the conformational stability, interdomain organization, and antigen-binding interactions of each construct. Our results provide a dynamic, structure-based assessment of how linker composition influences GUCY2C recognition and scFv structural behavior. Furthermore, this work establishes a computational framework for the rational optimization of GUCY2C-targeted antibody fragments.

For millions of immunocompromised individuals, vaccines may not elicit adequate protection from infections, so alternative strategies for pre-exposure prophylaxis are essential. There is only one non-vaccine product authorized in the U.S. as pre-exposure prophylaxis against COVID-19: the monoclonal antibody pemivibart. We previously showed that pemivibart had lower neutralizing activity in vitro against many recent dominant SARS-CoV-2 variants, such as KP.3.1.1, NB.1.8.1, and LP.8.1.1, than it had against JN.1, which was dominant when the antibody was first authorized. The manufacturer of pemivibart (Invivyd) recently initated clinical testing of a new monoclonal antibody derived from pemivibart, VYD2311, but there are no available studies of the activity of VYD2311 against dominant and emerging SARS-CoV-2 variants. Here, using pseudovirus neutralization assays, we measured the neutralizing activity of laboratory-synthesized VYD2311 and pemivibart against dominant and emerging SARS-CoV-2 variants, including XFG, NB.1.8.1, and the genetically distant BA.3.2.2. We found that VYD2311 potently neutralized all tested variants in vitro, dramatically more so than pemivibart. Combined with interpretation of earlier clinical trials of a parental antibody product, we conclude that VYD2311 is a promising candidate for passive immunoprophylaxis against COVID-19, particularly for those who do not respond well to vaccination.

In germinal centers, activated B cells modify their antigen receptors through somatic hypermutation (SHM), followed by antigenic selection that favors expansion of high affinity B cells. The affinity maturation process is critical for development of broadly neutralizing antibodies (bnAbs) against the human immunodeficiency virus-1 (HIV-1). BnAbs have been isolated from some people living with HIV-1. Because these antibodies target conserved epitopes of the HIV-1 Envelope (Env) protein, they inhibit a broad spectrum of viruses. Eliciting bnAbs by vaccination is a top priority for HIV-1 prevention, but reproducing the lengthy maturation of bnAbs is a major challenge. The problem is typified by VRC01 class antibodies, which recognize the CD4 binding site of HIV-1 Env protein. To reach the CD4 binding site, antibodies need to navigate through adjacent glycans. Accommodating the glycans requires multiple SHMs in germinal center (GC) B cells, including infrequent events. For this reason, VRC01 vaccine development often stalls at this point. We have generated a mouse model aimed at providing a potential solution for navigating this vaccine design impediment. To this end, we made a mouse model that expresses a stalled VRC01 intermediate conditionally in GC B cells. This system has three advantages: 1) direct expression of the intermediate obviates prior immunization steps, thereby shortening the immunization scheme; 2) the conditional expression system bypasses tolerance control checkpoints that sometimes delete B cells expressing bnAbs; 3) the intermediate responds to immunization in GCs, the physiological site of affinity maturation. With this model, we established an immunization method to mature the VRC01 intermediate into heterologous neutralizing antibodies against viruses with a native glycan shield. Since high mutation load is common among bnAbs, the germinal center conditional expression system could provide a general tool for boost immunogen design to overcome roadblocks in the maturation pathway. Author summaryIn response to antigenic stimulation, cognate B cells become activated and form germinal centers in lymphoid tissues. Germinal center B cells modify their antigen receptors through somatic hypermutation (SHM) of immunoglobulin variable region gene exons, with antigen selecting for high affinity B cells by providing survival advantage. This mechanism accounts for antibody affinity maturaton over the gradual course of an immune response. Affinity maturation is critical for generating potent, neutralizing antibodies against diverse strains of the human immunodeficiency virus-1 (HIV-1). These broadly neutralizing antibodies (bnAbs) are heavily mutated, reflecting lengthy affinity maturation over years of chronic infection. Recapitulating the affinity maturation process is a major challenge for bnAb induction by vaccination. In immunization experiments, bnAb development often stalls at rate limiting steps that involve infrequent, but functionally important, mutational events. Overcoming such obstacles requires boost immunogens that can stimulate the stalled B cells to acquire the requisite mutations. To this end, we recapitulated the maturation arrest of a bnAb lineage by expressing a stalled antibody in mouse germinal center B cells. Using this mouse model, we developed boost immunization conditions that advanced the antibody maturation beyond a roadblock to attain neutralizing activities against heterogenous viruses.

Circulating tumor cells (CTCs), and especially CTC-clusters, are linked to poor prognosis and may reveal mechanisms of metastasis and treatment resistance. Therefore, developing unbiased methods for the functional characterization of CTCs in liquid biopsies is an urgent need. Here, we present an evaluation of multiplex imaging mass cytometry (IMC) to analyze CTCs in mice with human xenograft tumors. In a single-step process, IMC uses metal-labeled antibodies to simultaneously detect a large number of proteins/modifications within minimally manipulated small volumes of blood from the tail vein or heart. We used breast cancer cell lines and a patient-derived xenograft (PDX) to assess antibodies for cross-species interpretation. Along with manual verification, HALO-AI-based cell segmentation was used to identify CTCs and quantify markers. Despite some limitations regarding human-specificity, this technology can be used to investigate the effect of genetic and pharmacological interventions on the properties of single and cluster CTCs in tumor-bearing mice.

Accurately modeling antibody-antigen interactions requires distinguishing intrinsic binding affinity ("protein-interaction") from protein biophysical properties ("protein-quality"), including folding, stability, and expression. However, high-throughput mutational measurements commonly used to train and benchmark computational models often conflate these effects, obscuring the true determinants of molecular recognition. Here, we present an experimental and analytical framework to disentangle protein-interaction effects from protein-quality effects in single-domain antibody (VHH)-antigen binding. Using a large-scale deep mutational scanning (DMS) dataset spanning four VHH-antigen complexes, with single and double mutations in both partners, we introduce control binders to quantify protein-quality changes independently of protein-interaction. This enables decomposition of experimentally measured affinity into protein-interaction and protein-quality components at scale. Leveraging the disentangled dataset, we evaluated state-of-the-art structure- and sequence-based models for protein-quality and protein-interaction prediction and show that their performance largely reflects protein-quality rather than protein-interaction effects. Our results highlight a major confounder in current datasets and suggest that accounting for protein-quality will be essential for training next-generation affinity-prediction models. Nomenclature Antibody related termsO_LIPrimary VHH: The VHH of a VHH-antigen complex for which the paratope and the epitope weremutated. C_LIO_LIControl VHH: A second VHH that binds to the same antigen as the primary VHH but has non-overlapping epitope positions and therefore does not bind to any of the mutated antigen positions. C_LI Affinity-related termsO_LIReal Affinity: "The strength of the interaction between two [...] molecules that bind reversibly (interact)" 1. In the context of antibody-antigen binding, it quantifies interactions between active proteins (which are expressed and correctly folded 2 and are therefore functionally and biologically active (see below). It is commonly quantified by the equilibrium dissociation constant, KD. C_LIO_LIObserved affinity ({degrees}KD): The interaction strength experimentally measured between two molecules. Unlike real affinity, this value is confounded by the biophysical properties of the individual binding partners, specifically their folding, stability, and expression levels. Consequently, the observed affinity often differs from the real/intrinsic affinity if a significant fraction of the protein population is inactive 3. NOTE: Unless otherwise specified, {degrees}KD is reported in - log10 space. For example, a {degrees}KD of -9 corresponds to 10-9M or 1nM. C_LIO_LIChange in observed affinity ({Delta}{degrees}KD): The shift in the observed affinity between two proteins upon mutation, reported as the log10-transformed fold change. A value of 1 reflects a 10-fold difference, a value of 2 a 100-fold difference, etc. This aggregate change resolves into two distinct biophysical components 2, 4: O_LIProtein-interaction change: The change in the intrinsic thermodynamic affinity between the two binding partners, each in its active state (i.e., the specific change in interface Gibbs free energy because both enthalpy and entropy are considered). C_LIO_LIProtein-quality change: The change in the fraction of the mutated protein population that is biologically active - meaning it is expressed, correctly folded, and stable 2, 5. O_LIFolding: The process that guides the polypeptide chain toward its native conformation, which is a prerequisite for forming a functional binding site. C_LIO_LIStability: The thermodynamic capacity to maintain the folded structure over time and under physiological conditions. Stability (decrease in Gibbs free energy from the unfolded to the folded state) ensures the binding interface remains intact and prevents competing processes such as aggregation 6. C_LIO_LIExpression: The steady-state abundance of the protein. This is largely dependent on proper folding and stability, as cellular quality control mechanisms degrade proteins that fail to fold or remain stable at functional concentrations. C_LI C_LI C_LIO_LIChange in relative affinity ({Delta}{Delta}{degrees}KD): the difference between the {Delta}{degrees}KD of the primary VHH compared to the control VHH for a given epitope mutation. C_LI Model-related termsO_LIESM-IF1 sc: Single-chain (sc) structure-conditioned inverse folding model (ESM-IF1), using the isolated monomer structure of the mutated protein: either the VHH or the antigen 7. C_LIO_LIESM-IF1 mc: Multi-chain (mc) structure-conditioned model (ESM-IF1), using the full complex structure (both antibody and antigen) 7. C_LIO_LIStability prediction score: Score that represents the predicted change in stability based on a single mutation, normally represented as {Delta}{Delta}G. C_LI

Engineering macrophages with chimeric antigen receptors is emerging as a promising cancer therapeutic. Chimeric antigen receptor-expressing macrophages (CAR-Ms) engineered to recognize tumor-specific antigens have been shown to inhibit tumor growth and activate adaptive immune responses, leading to robust tumor control in animal studies. Based on this work, clinical trials have been initiated. While the trials have shown promise, challenges remain. The dynamic interactions between CAR-Ms and cancer cells and the exact mechanisms driving anti-tumor effects remain poorly defined. Defining the dynamic interactions between CAR-Ms and cancer cells will provide critical insights for optimizing future CAR-M design and improving therapeutic efficacy. We sought to directly visualize CAR-M interactions with glioblastoma cells at high-resolution and in real-time using CAR-Ms engineered to recognize Neural-Glial Antigen 2 (NG2), an antigen expressed on glioblastoma cells. Using patient-derived glioblastoma cells, we formed glioblastoma spheroids and embedded them in a 3D matrix together with CAR-Ms. Using time-lapse microscopy, as expected, we found that NG2-targeting CAR-Ms engulfed glioblastoma cells. However, excitingly, we found that NG2-targeting CAR-Ms blocked >85% of glioblastoma cell invasion in 3D. This inhibition of glioblastoma invasion was not due to a significant change in CAR-M polarization states. Together, these data suggest that NG2-targeting CAR-Ms both engulf glioblastoma cells and block glioblastoma invasive behavior.

Cancer remains a major therapeutic challenge despite substantial advances in diagnosis and treatment, including immune checkpoint blockade. Among emerging immunotherapeutic approaches, adoptive cell transfer (ACT) has attracted growing interest. Human peripheral V{gamma}9V{delta}2 T cells are promising candidates for ACT because they combine rapid and potent antitumor functions with major histocompatibility complex (MHC)-independent tumor recognition, enabling allogeneic use with limited risk of graft-versus-host disease. This raises the possibility of generating standardized V{gamma}9V{delta}2 T-cell banks from healthy donors for off-the-shelf immunotherapy. Here, we provide preclinical evidence supporting the suitability of allogeneic human V{gamma}9V{delta}2 T cells for ACT. We characterized peripheral blood V{gamma}9V{delta}2 T cells from healthy donors after successive antigen-specific and non-specific amplification steps, assessing their phenotype, effector functions, and metabolic state. Amplified cells maintained a strong pro-inflammatory Th1-like profile, preserved cytotoxic activity, and did not produce immunoregulatory cytokines. They also displayed high purity, a predominant effector memory phenotype, reduced expression of several inhibitory immune checkpoints, and sustained antitumor reactivity. Altogether, these findings support the development of allogeneic V{gamma}9V{delta}2 T-cell products as a scalable platform for next-generation cancer immunotherapies.

The variable regions of antibody heavy chains (HCs) and light chains (LCs) are assembled by V(D)J recombination in progenitor B cells to generate an immense repertoire of primary B cell receptors (BCRs), the precursors of affinity-matured antibodies secreted in response to antigen stimulation. The complementarity determining region (CDR) 1, 2 and 3 of antibodies are the principal antigen contact sites, with CDR3 being highly diverse due to V(D)J junctional diversification by terminal deoxynucleotidyl transferase (TdT). The HC CDR3 (CDR H3) plays a prominent role in broadly neutralizing antibodies (bnAbs) against the human immunodeficiency virus-1 (HIV-1). BnAbs overcome the genetic heterogeneity of HIV-1 by recognizing conserved epitopes on the HIV-1 Envelope (Env) protein. Reaching these targets requires long CDR H3s that penetrate through the glycan shield or other structural hindrances on the Env protein. The shortage of human antibodies with such long CDR H3s poses a challenge for bnAb elicitation by vaccination. To aid immunogen design, we generated six mouse models for inducing bnAbs against particular HIV-1 Env epitopes. In each mouse model, we integrated the human HC VH, D, JH segments and LC VL, JL segments of a bnAb lineage into the mouse HC and LC loci, with each set engineered to undergo V(D)J recombination and to generate diverse human HC and LC variable regions. Combined action of V(D)J recombination and TdT- mediated junctional diversification in developing B cells generated a range of human variable region exons for a given bnAb lineage that contained highly diverse CDR3s in each mouse model. Moreover, these repertoires contained humanized antibodies that had bnAb-like long CDR H3s that could potentially serve as bnAb precursors. Therefore, these mouse models can be used to test whether immunogens can induce bnAbs from rare and diverse precursors in a complex antibody repertoire. Author summaryThe human immunodeficiency virus-1 (HIV-1) is the causative agent of acquired immunodeficiency syndrome (AIDS). An efficacious HIV-1 vaccine is needed to control the AIDS pandemic. However, in multiple clinical trials, vaccine candidates failed to confer protection against HIV-1 infection. The lack of efficacy is mainly due to the enormous heterogeneity of HIV-1 strains in human circulation. A breakthrough in the field has been the identification of broadly neutralizing antibodies (bnAbs) in a small fraction of HIV-1 infected patients. Because these antibodies recognize conserved targets on different HIV-1 strains, they can inhibit a wide spectrum of viruses. Eliciting HIV-1 bnAbs is a top priority for vaccine development. For this endeavor, a major difficulty is that most bnAbs have unusual properties. To induce bnAbs, vaccines must be highly selective for rare human antibodies that can develop into bnAbs. To facilitate this effort, we have generated a panel of mouse models that can produce potential precursors for major types of HIV-1 bnAbs. We engineered mouse models to produce diverse precursors in complex antibody repertoires, which mimic the challenging condition in human vaccination. These mouse models can be used to assess and optimize vaccine candidates at the preclinical stage.

BackgroundCompanion canines need advances in therapeutic options for solid tumor malignancies. Prior studies established feasibility of autologous natural killer (NK) cell infusions in canines with solid tumors; however, autologous products are limited by dysfunctional immunity and a manufacturing process that delays care. Allogeneic NK cells offer the possibility of "off-the-shelf" therapy to be administered from healthy donors. MethodsPeripheral blood mononuclear cells (PBMCs) were isolated from healthy canine donors via density gradient separation. NK cells were expanded with recombinant human IL-2 and canine IL-21 with the addition of K562 feeder cells transfected with CD137 ligand and membrane bound human IL-15. Additional experiments included IL-12 in the expansions. In vitro potency was assessed via co-culture with the D17-mKate2 canine osteosarcoma cell line. Three canines were enrolled in a phase 1 trial infusing ex vivo expanded allogeneic NK cells after lymphodepletion. ResultsFlow cytometric analysis confirmed successful expansion of canine NK cells with up to 50% of cells demonstrating NKp46+ after 14 days of expansion. Residual T cell numbers varied based on donor. The addition of IL-12 led to increased NK cell expansion. Incucyte demonstrated potency with increasing osteosarcoma cell death at higher effector to target ratios. Three canines with metastatic/refractory solid tumors were successfully lymphodepleted and infused with allogeneic NK cell products. The canines tolerated the infusions well. ConclusionsCanine allogeneic NK cells were successfully expanded and activated ex vivo, demonstrated potency in vitro, and safety in vivo. Further studies will optimize the NK cell product and escalate dosing to reach the maximal tolerable dose.

Preclinical antibody discovery relies on progressive screening and down-selection of candidate antibodies from large immune repertoires, yet this critical process is poorly represented in existing public databases. Here we introduce KyDab (Kymouse Antibody Database), a well-curated database of antibody discovery selection data generated using standardized workflows on the Kymouse humanized mouse platform. The current release includes 11 Kymouse platform mice immunisation studies covering 51 immunogens, more than 120,000 paired heavy-light chain sequences, and binding measurements for a selected subset of experimentally characterized clones. By capturing full-funnel selection data with consistent metadata and both positive and negative experimental outcomes, KyDab provides a valuable data resource for the development and evaluation of artificial intelligence models for antibody discovery. KyDab is accessible https://kydab.naturalantibody.com, and the database will be continuously updated as new datasets become available.

Metastasis is the leading cause of death in breast cancer patients, yet there are no drugs specifically designed to block cancer cell intravasation, an early step of the metastatic cascade that originates circulating tumour cells (CTCs). A major challenge in developing anti-intravasation drugs is the scarcity of relevant in vitro platforms suitable for predictable drug discovery. Intravasation is a fundamental step of metastasis and involves the crossing of cancer cells through an endothelial barrier to enter the blood circulation. Here we developed an intravasation-on-a-chip model with controlled extracellular matrix composition, fluid flow and shear stress, which mimics the dynamic tumour-endothelium interface. The systems allows real-time imaging of intravasation and the isolation and quantification of intravasated cancer cells. As a proof-of-concept for drug testing, we show that perfusion with the PI3K/mTOR inhibitor Dactolisib, significantly reduced intravasation without compromising endothelial cell viability. The system also provides the capability to evaluate inhibitor on-target activity via imaging analysis. This intravasation-on-a-chip model offers a powerful, scalable, and imaging-compatible platform for discovering and evaluating anti-intravasation compounds.

Purpose/ObjectiveThis study aimed to design and computationally evaluate a synthetic GluN1-mimetic peptide as a decoy to bind and neutralize pathogenic autoantibodies in anti-NMDA receptor (NMDAR) encephalitis, a severe autoimmune neurological disorder affecting approximately 1.5 per million individuals annually. MethodsKey GluN1 epitope residues (351-390 of the amino-terminal domain) were identified from crystallographic evidence and patient-derived antibody binding studies. Multiple peptide variants were rationally designed to mimic the antibody-binding interface. AlphaFold2 was used to predict peptide structures. Rigid-body docking simulations were conducted with HADDOCK 2.4 to model peptide-antibody complexes, and binding affinities were quantified using PRODIGY. A scrambled peptide control was included to establish docking specificity. ResultsThe top-performing peptide demonstrated favorable predicted binding ({Delta}G = -21.5 kcal/mol, Kd = 1.7 x 10-{superscript 1} M) with an average pLDDT score of 90%, a buried surface area of 3,255.5 [A]{superscript 2}, and 18 intermolecular hydrogen bonds. Relative to the scrambled control ({Delta}G = -8.3 kcal/mol), the designed peptide showed substantially stronger predicted binding. Conclusion/ImplicationsThese results support the validity of an epitope-mimicry design strategy and establish a scalable computational framework for prioritizing peptide decoy candidates applicable to other antibody-mediated autoimmune disorders. Experimental validation remains necessary to confirm real-world efficacy.

Despite >50 years of methods development, specific antibodies are still generated at low throughput and remain in high demand across biotechnology. Most biologics and immunoprobes are monoclonal antibodies, developed using a combination of inoculating animals with a target antigen, engineered candidate libraries, and multiple rounds of selection using phage or yeast display. Here we introduce a synthetic biology scheme to eliminate the need for nearly all of these steps, by combining Surface display on E. coli and Phage display with the microvirus {Phi}X174, Assisting Continuous Evolution (SurPhACE). Instead of building libraries for screening, SurPhACE runs a closed evolutionary program. A typical experiment can have 1011 mutant candidates under active selection, with complete turnover of the mutant population every 30min, or >5x1012 unique mutants per day, using less than 100mL of bacterial culture media. We demonstrate SurPhACE for optimizing a nanobody to a related epitope, and develop novel nanobodies for an arbitrary target using a minimal starting library to establish a proof of concept and identify best practices for this scalable method for generating protein binders.

Affinity purification is a essential technique for isolating highly purified proteins; however, generating affinity ligands require significant time and financial investment. To address these limitations, this study proposes a novel affinity chromatography method utilizing in silico-designed cyclic peptides as ligands. Targeting Complement C1q (C1q), a plasma protein that plays crucial roles in classical complement pathway, we employed the biomolecular structure prediction model, AlphaFold2, to design specific binding cyclic peptides. Based on these designs, we synthesized lariat-type cyclic peptides characterized by disulfide cyclization and biotinylation, which were subsequently immobilized on streptavidin carriers. Performance tests confirmed that the resulting column specifically captured C1q, allowing for elution via a standard NaCl concentration gradient. Notably, high selectivity was preserved even in the presence of plasma, underscoring the ligands practical robustness. By overcoming traditional constraints through (1) rapid and simple design, (2) high specificity, and (3) universal versatility without genetic modification, this de novo design strategy represents a potential breakthrough in protein purification technologies. HighlightsO_LIAI-driven de novo design generated a specific cyclic peptide ligand for Complement C1q C_LIO_LIThe synthetic ligand enabled one-step purification of Complement C1q directly from human plasma C_LIO_LIMild elution conditions preserved the targets oligomeric structure and native interactome C_LIO_LIThis label-free strategy offers a rapid, low-cost alternative to antibody-based chromatography C_LI

Glioma is the most common primary malignant tumor of the brain, and accumulating evidence indicates that neuronal activity plays a pivotal role in tumor progression. In this study, neuronal activity is modulated in vitro using potassium chloride (KCl)-induced depolarization and midazolam (MDZ)-mediated suppression. MDZ is a neuronal activity modulation medication, commonly used for sedation, anxiolysis, and amnesia in clinics. After treatment, conditioned media derived from these neuronal cultures are subsequently co-cultured with glioma cells. EdU incorporation assays demonstrate that MDZ significantly inhibits glioma cell proliferation in vitro. Furthermore, an orthotopic xenograft glioma model is established to assess the anti-tumor efficacy of MDZ in vivo, as evaluated by tumor volume and Ki-67 immunostaining. Mechanistically, insulin-like growth factor 1 (IGF1) is identified as the neuronal-activity-regulated factor that promotes glioma growth through activation of the PI3K/AKT signaling pathway. Moreover, transcriptomic profiling of brain tissues reveals that MDZ attenuates neuronal activity and downregulates neuron-derived growth factors in both glioma and non-tumor regions, thereby exerting anti-tumor effects in vivo. Collectively, these findings demonstrate that MDZ suppresses glioma progression by suppressing neuronal activity and inhibiting neuron-derived trophic factors, providing new insights into the development of therapeutic strategies for glioma.

Diffuse large B-cell lymphoma (DLBCL), the most common aggressive lymphoma, encompasses histologically similar but genetically distinct cancers. Recent genetic studies have defined at least six molecular subtypes, yet none account for Epstein-Barr virus (EBV), despite 5-15% of DLBCLs being EBV-associated. By reanalyzing published whole-exome and RNA-sequencing data from 481 tumors, we identified 19 EBV-positive cases. These were significantly enriched in the BN2 subtype (6/19), while most (11/19) remained unclassified. In BN2 tumors, several subtype-defining mutations were reduced in frequency among EBV-positive cases, supporting the hypothesis that EBV oncogenes substitute for specific cellular alterations and may confound DLBCL classification algorithms. Extending our analysis to cell lines, we found that the widely used Val cell line harbors the B95-8 laboratory EBV strain; other EBV-positive lines appeared authentic but modeled only non-BN2 subtypes and expressed an atypical viral latency III program, whereas some DLBCL tumors expressed the atypical latency III program and others latency I or II. Together, these findings demonstrate that EBV-positive DLBCL, like DLBCL itself, is not a single disease, and that current in vitro models only partially capture its biological heterogeneity. Key pointsO_LIEBV-positive DLBCL is not a single disease and EBV status can impact genetic-based classifications. C_LIO_LICurrent EBV-positive DLBCL cell lines do not adequately capture tumor complexity; we determined that Val is a problematic cell line. C_LI

CD4+ T helper cells are required for CD8+ killer T cells to suppress tumor growth. An orally-available small molecule surrogate of alpha-1 antitrypsin, Alphataxin, was previously demonstrated to elevate the numbers of circulating and tumor-infiltrating CD4+ T cells and to suppress kidney tumor growth in mice. To determine whether Alphataxin might be effective in other T cell-responsive cancers, mice orthotopically implanted with colon tumors were treated using Alphataxin and anti-PD-1 as monotherapies or in combination. Combination therapy significantly suppressed tumor growth (ORR = 37.5%) and increased tumor-infiltrating CD4+ T cells, CD8+ T cells, NK cells, M2 macrophages, and DC2 dendritic cells. Release of IFN-{gamma} by helper T cells in the tumor microenvironment appeared to contribute to the effectiveness of killer T cells in suppressing tumor growth. Toxicology studies in rats revealed no untoward effects. Alphataxin, to our knowledge the first and only drug developed to rapidly and sustainably increase the number of circulating and tumor-infiltrating CD4+ helper T cells, is a powerful therapeutic that provides long-term remission in T cell-responsive cancers in combination with anti-PD-1.

Affinity chromatography is a powerful and therefore popular method for the purification of proteins for structural studies. The success of the technique relies on the specificity of the interaction between the target protein and the affinity resin. Here, we present the identification of two protein contaminants isolated from HEK293 cell lysate following affinity purification of twin Strep-tagged or FLAG-tagged proteins. The contaminants were identified as human propionyl-coenzyme A carboxylase (hPCC) and protein arginine methyltransferase 5 in complex with methylosome protein 50 (PRMT5:MEP50) via a combination of cryo-EM data processing and proteomic analyses. This report serves to illustrate how these contaminants may appear in cryo-EM datasets and to highlight the paramount importance of affinity chromatography resin specificity for efficient protein purification.

IntroductionMalaria is a leading health problem with high disease burden and mortality rates worldwide. Currently approved vaccines target the sporozoite form of Plasmodium falciparum that initially infects the liver, but only provide modest protection against malaria in young children. There is an urgent need to develop next-generation malaria vaccines that target multiple parasite developmental stages for greater efficacy. Antibodies to merozoites, which are involved in blood-stage replication, and are associated with clinical illness, have multiple functional activities and can protect against malaria. A promising merozoite vaccine candidate is Merozoite Surface Protein 2 (PfMSP2). Antibodies to PfMSP2 can promote multiple antibody Fc-mediated functional activities to clear merozoites. MethodsWe developed and evaluated monovalent and bivalent (3D7 and FC27 variants) PfMSP2-based mRNA vaccines. We designed and codon-optimised mRNA, which was validated for in vitro expression in mammalian cells, and subsequently formulated as lipid nanoparticles for vaccination of mice in a 3-dose regimen. Vaccination with recombinant PfMSP2 protein with adjuvant was performed for comparison. We evaluated the induction of antibodies and functional activities relevant to protective immunity. ResultsmRNA vaccines induced prominent IgG responses using monovalent (3D7 allele) and bivalent (3D7 and FC27 alleles) vaccines encoding near full-length PfMSP2, and antibodies recognised the surface of whole merozoites. Vaccine responses were equivalent to, or superior than, a recombinant protein-based PfMSP2 vaccine. The bivalent vaccine induced equivalent antibodies to the two PfMSP2 alleles. Vaccination induced cytophilic IgG subclasses with multiple functional activities, including complement fixation, binding of human Fc{gamma}-receptors I and IIa, and opsonic phagocytosis. ConclusionsPfMSP2 is highly immunogenic using the mRNA vaccine platform and induces antibodies with multiple functional activities associated with protective immunity in humans. Combining PfMSP2 with other merozoite and sporozoite antigens is a promising strategy to develop highly efficacious vaccines to achieve malaria control and elimination goals.

Targeting protein-protein interactions (PPIs) with small molecules is historically challenging due to shallow, solvent-exposed interfaces that lack classical binding pockets. Furthermore, employing traditional structure-based virtual screening (SBVS) across ultra-large chemical spaces to find novel chemotypes imposes prohibitive computational bottlenecks. Here, we report the first prospective, real-world application of the PyRMD2Dock platform, an AI-enforced SBVS workflow that integrates machine learning and standard docking available within the PyRMD Studio suite. To target the structurally demanding immune receptor CD28, a chemically diverse subset of 2.4 million molecules from the Enamine REAL Diversity Space was docked into a cleft adjacent to the canonical ligand interface. These data were used to train 672 classification models, and the optimized model rapidly screened the remaining [~]46 million compounds. Following interaction filtering and clustering, 232 highly prioritized ligands were identified. Experimental validation of 150 purchased candidates yielded a remarkable hit rate, identifying multiple direct CD28 binders. Lead compounds 100 and 104 exhibited submicromolar affinity (Kd = 343.8 nM and 407.1 nM, respectively), potent CD28-CD80 disruption, and functional blockade in cellular reporter assays. Furthermore, these compounds successfully reduced cytokine secretion in primary human tumor-PBMC and epithelial tissue co-culture models. This study validates PyRMD2Dock as a highly scalable, effective protocol for mining massive chemical libraries to discover small-molecule modulators of challenging immune receptor interfaces.