A Novel B7-H6-Targeted IgG-Like T Cell-Engaging Antibody for the Treatment of Gastrointestinal Tumors.

PURPOSE: Advanced-stage gastrointestinal cancers represent a high unmet need requiring new effective therapies. We investigated the antitumor activity of a novel T cell-engaging antibody (B7-H6/CD3 ITE) targeting B7-H6, a tumor-associated antigen that is expressed in gastrointestinal tumors. EXPERIMENTAL DESIGN: Membrane proteomics and IHC analysis identified B7-H6 as a tumor-associated antigen in gastrointestinal tumor tissues with no to very little expression in normal tissues. The antitumor activity and mode of action of B7-H6/CD3 ITE was evaluated in in vitro coculture assays, in humanized mouse tumor models, and in colorectal cancer precision cut tumor slice cultures. RESULTS: B7-H6 expression was detected in 98% of colorectal cancer, 77% of gastric cancer, and 63% of pancreatic cancer tissue samples. B7-H6/CD3 ITE-mediated redirection of T cells toward B7-H6-positive tumor cells resulted in B7-H6-dependent lysis of tumor cells, activation and proliferation of T cells, and cytokine secretion in in vitro coculture assays, and infiltration of T cells into tumor tissues associated with tumor regression in in vivo colorectal cancer models. In primary patient-derived colorectal cancer precision-cut tumor slice cultures, treatment with B7-H6/CD3 ITE elicited cytokine secretion by endogenous tumor-infiltrating immune cells. Combination with anti-PD-1 further enhanced the activity of the B7-H6/CD3 ITE. CONCLUSION: These data highlight the potential of the B7-H6/CD3 ITE to induce T cell-redirected lysis of tumor cells and recruitment of T cells into noninflamed tumor tissues, leading to antitumor activity in in vitro, in vivo, and human tumor slice cultures, which supports further evaluation in a clinical study.

Discovery Strategies to Maximize the Clinical Potential of T-Cell Engaging Antibodies for the Treatment of Solid Tumors.

T-cell Engaging bispecific antibodies (TcEs) that can re-direct cytotoxic T-cells to kill cancer cells have been validated in clinical studies. To date, the clinical success with these agents has mainly been seen in hematologic tumor indications. However, an increasing number of TcEs are currently being developed to exploit the potent mode-of-action to treat solid tumor indications, which is more challenging in terms of tumor-cell accessibility and the complexity of the tumor microenvironment (TME). Of particular interest is the potential of TcEs as an immunotherapeutic approach for the treatment of non-immunogenic (often referred to as cold) tumors that do not respond to checkpoint inhibitors such as programmed cell death protein 1 (PD-1) and programmed death ligand 1 (PD-L1) antibodies. This has led to considerable discovery efforts for, firstly, the identification of tumor selective targeting approaches that can safely re-direct cytotoxic T-cells to cancer cells, and, secondly, bispecific antibodies and their derivatives with drug-like properties that promote a potent cytolytic synapse between T-cells and tumor cells, and in the most advanced TcEs, have IgG-like pharmacokinetics for dosing convenience. Based on encouraging pre-clinical data, a growing number of TcEs against a broad range of targets, and using an array of different molecular structures have entered clinical studies for solid tumor indications, and the first clinical data is beginning to emerge. This review outlines the different approaches that have been taken to date in addressing the challenges of exploiting the TcE mode-of-action for a broad range of solid indications, as well as opportunities for future discovery potential.

A Bispecific DLL3/CD3 IgG-Like T-Cell Engaging Antibody Induces Antitumor Responses in Small Cell Lung Cancer.

PURPOSE: Small cell lung cancer (SCLC) is the most lethal and aggressive subtype of lung carcinoma characterized by highly chemotherapy-resistant recurrence in the majority of patients. To effectively treat SCLC, we have developed a unique and novel IgG-like T-cell engaging bispecific antibody (ITE) that potently redirects T-cells to specifically lyse SCLC cells expressing Delta-like ligand 3 (DLL3), an antigen that is frequently expressed on the cell surface of SCLC cells, with no to very little detectable expression in normal tissues. EXPERIMENTAL DESIGN: The antitumor activity and mode of action of DLL3/CD3 ITE was evaluated in vitro using SCLC cell lines and primary human effector cells and in vivo in an SCLC xenograft model reconstituted with human CD3+ T-cells. RESULTS: Selective binding of DLL3/CD3 ITE to DLL3-positive tumor cells and T-cells induces formation of an immunological synapse resulting in tumor cell lysis and activation of T-cells. In a human T-cell engrafted xenograft model, the DLL3/CD3 ITE leads to an increase in infiltration of T-cells into the tumor tissue resulting in apoptosis of the tumor cells and tumor regression. Consistent with the mode of action, the DLL3/CD3 ITE treatment led to upregulation of PD-1, PD-L1, and LAG-3. CONCLUSIONS: This study highlights the ability of the DLL3/CD3 ITE to induce strictly DLL3-dependent T-cell redirected lysis of tumor cells and recruitment of T-cells into noninflamed tumor tissues leading to tumor regression in a preclinical in vivo model. These data support clinical testing of the DLL3/CD3 ITE in patients with SCLC.

A screening tool for therapeutic monoclonal antibodies: Identifying the most stable protein and its best formulation based on thioflavin T binding.

The lack of a fast selection method to identify the most stable protein is one of the major challenges for developing successful therapeutic protein formulations more rapidly. The swift and accurate detection of small amounts of aggregates is another problem since aggregates may trigger an immunological response and the aggregation decreases the biological activity of the antibody. Here we present an alternative method for initial screening of the aggregation propensity of proteins, using monoclonal antibodies (mAb) as an example and thioflavin T (ThT) binding. The major advantage of ThT binding is the short duration of testing compared with size-exclusion chromatography (SEC) measurements that can take 6 months or more even under accelerated conditions. The tendency to aggregate of each therapeutic human mAb probed with the ThT assay, together with SEC, is employed to formulate the ranking of mAb aggregation. ThT binding can determine the propensity of proteins to aggregate in a few days, illustrating that ThT binding would be a valuable screening tool.

Conformational stability and aggregation of therapeutic monoclonal antibodies studied with ANS and Thioflavin T binding.

Characterization of aggregation profiles of monoclonal antibodies (mAb) is gaining importance because an increasing number of mAb-based therapeutics are entering clinical studies and gaining marketing approval. To develop a successful formulation, it is imperative to identify the critical biochemical properties of each potential mAb drug candidate. We investigated the conformational change and aggregation of a human IgG1 using external dye-binding experiments with fluorescence spectroscopy and compared the aggregation profiles obtained to the results of size-exclusion chromatography. We show that using an appropriate dye at selected mAb concentration, unfolding or aggregation can be studied. In addition, dye-binding experiments may be used as conventional assays to study therapeutic mAb stability.

Prediction of protein binding regions.

Identifying protein binding sites provides important clues to the function of a protein. Experimental methods to identify the binding sites such as determining the crystal structures of protein complexes are extremely laborious and expensive. Here, we present a computational technique called spatial aggregation propensity (SAP) based on molecular simulations to predict protein binding sites. We apply this technique to two model proteins, an IgG1 antibody and epidermal growth factor receptor (EGFR) and demonstrate that SAP predicts protein binding regions with very good accuracy. In the case of the IgG1 antibody, SAP accurately predicts binding regions with the Fc-receptor, protein-A, and protein-G. For EGFR, SAP accurately predicts binding regions with EGF, TGFα, and with another EGFR. The resolution of SAP is varied to obtain a detailed picture of these binding sites. We also show that some of these binding sites overlap with protein self-aggregation prone regions. We demonstrate how SAP analysis can be used to engineer the protein to remove unfavorable aggregation prone regions without disturbing protein binding regions. The SAP technique could be also used to predict the yet unknown binding sites of numerous proteins, thereby providing clues to their function.

Evaluation of a non-Arrhenius model for therapeutic monoclonal antibody aggregation.

Understanding antibody aggregation is of great significance for the pharmaceutical industry. We studied the aggregation of five different therapeutic monoclonal antibodies (mAbs) with size-exclusion chromatography-high-performance liquid chromatography (SEC-HPLC), fluorescence spectroscopy, electron microscopy, and light scattering methods at various temperatures with the aim of gaining insight into the aggregation process and developing models of it. In particular, we find that the kinetics can be described by a second-order model and are non-Arrhenius. Thus, we develop a non-Arrhenius model to connect accelerated aggregation experiments at high temperature to long-term storage experiments at low temperature. We evaluate our model by predicting mAb aggregation and comparing it with long-term behavior. Our results suggest that the number of monomers and mAb conformations within aggregates vary with the size and age of the aggregates, and that only certain sizes of aggregates are populated in the solution. We also propose a kinetic model based on conformational changes of proteins and monomer peak loss kinetics from SEC-HPLC. This model could be employed for a detail analysis of mAb aggregation kinetics.

Tryptophan-tryptophan energy transfer and classification of tryptophan residues in proteins using a therapeutic monoclonal antibody as a model.

Intrinsic tryptophan (Trp) fluorescence is often used to determine conformational changes of proteins. The fluorescence of multi-Trp proteins is generally assumed to be additive. This assumption usually holds well if Trp residues are situated at long distances from each other in the absence of any excited state reactions involving these residues and therefore when energy transfer does not occur. Here, we experimentally demonstrate energy transfer among Trp residues and support it by a Master Equation kinetic model applied to a therapeutic monoclonal antibody (mAb). The mAbs are one of the most studied and important biologics for the pharmaceutical industry, and they contain many Trp residues in close proximity. Understanding mAb fluorescence is critical for interpreting fluorescence data and protein-structure relationships. We propose that Trp residues could be categorized into three types of emitters in the mAbs. Experimentally, we categorize them according to solvent accessibility based on dependence of their fluorescence lifetime on the external quencher concentration and their emission wavelength. Theoretically, we categorize with molecular dynamics simulations according to their solvent accessibility. This method of combinatorial mapping of fluorescence characteristics can be utilized to illuminate structural aspects as well as make comparisons of drug formulations for these pharmaceutical proteins.

Glycosylation influences on the aggregation propensity of therapeutic monoclonal antibodies.

Monoclonal antibodies are the fastest growing class of biologics in the pharmaceutical industry. The correlation between mAb glycosylation and aggregation has not been elucidated in detail, yet understanding the structure-stability relationship involving glycosylation is critical for developing successful drug formulations. We conducted studies of temperature-induced aggregation and compared the stability of both glycosylated and aglycosylated forms of a human IgG1. In parallel, we also performed molecular dynamics simulations of the glycosylated full antibody to gain an understanding of the polysaccharide surroundings at the molecular level. Aglycosylated mAbs are somewhat less stable and therefore aggregate more easily than the glycosylated form at the temperatures studied. Glycosylation seems to enhance solubility and stability of these therapeutics and thus might be important for long-term storage.

Prediction of aggregation prone regions of therapeutic proteins.

Therapeutic proteins such as antibodies are playing an increasingly prominent role in the treatment of numerous diseases including cancer and rheumatoid arthritis. However, these proteins tend to degrade due to aggregation during manufacture and storage. Aggregation decreases protein activity and raises concerns about an immunological response. We have recently developed a method based on full antibody atomistic simulations to predict antibody aggregation prone regions [Proc. Natl. Acac. Sci. 2009, 106, 11937]. This method is based on "spatial-aggregation-propensity (SAP)", a measure of the dynamic exposure of hydrophobic patches. In the present paper, we expand on this method to analyze the aggregation prone regions over a wide parameter range. We also explore the effect of different hydrophilic mutations on these predicted aggregation prone regions to engineer antibodies with enhanced stability. The mutation to lysine is more effective than serine but less effective than glutamic acid in enhancing antibody stability. Furthermore, we show that multiple simultaneous mutations on different SAP peaks can have a cumulative effect on enhancing protein stability. We also investigate the accuracy of various cheaper alternatives for SAP evaluation because the full antibody atomistic simulations are highly computationally expensive. These cheaper alternatives include antibody fragment (Fab, Fc) simulations, implicit solvent models, or direct computations from a static structure (i.e., a structure from X-ray or homology modeling). The SAP evaluation from the static structure is 200,000 times faster but less accurate compared to the SAP from explicit atom simulations. Nevertheless, the SAP from a static structure still predicts most of the major aggregation prone regions, making it a potential approach for use in high-throughput applications. Thus, the SAP technology described here could be employed either in high-throughput developability screening of therapeutic protein candidates or to improve their stability at later stages of manufacturing.

Design and application of antibody cysteine variants.

Antibodies are multidomain proteins that are extensively used as a research tool in molecular biology and as therapeutics in medicine. In many cases, antibodies are engineered to contain surface cysteines for the site-specific conjugation of payloads. These antibodies can serve as payload vehicles in targeting a diseased cell to which the conjugated molecules exercise their activity. Here, we design and analyze a set of fourteen new IgG1 cysteine variants, with at least one variant per immunoglobulin fold domain. The cross-linking propensity of these mutants correlates very well with a tool we have developed for measuring aggregation propensity in silico, called spatial aggregation propensity (SAP). Our results indicate the utility of the SAP technology in selecting antibody cysteine variants with desired properties. Moreover, the different oligomerization propensity of the variants suggests a variety of applications in molecular biology and medicine, such as payload delivery, structural analysis, electrophoresis, and chromatography.

Dynamic fluctuations of protein-carbohydrate interactions promote protein aggregation.

Protein-carbohydrate interactions are important for glycoprotein structure and function. Antibodies of the IgG class, with increasing significance as therapeutics, are glycosylated at a conserved site in the constant Fc region. We hypothesized that disruption of protein-carbohydrate interactions in the glycosylated domain of antibodies leads to the exposure of aggregation-prone motifs. Aggregation is one of the main problems in protein-based therapeutics because of immunogenicity concerns and decreased efficacy. To explore the significance of intramolecular interactions between aromatic amino acids and carbohydrates in the IgG glycosylated domain, we utilized computer simulations, fluorescence analysis, and site-directed mutagenesis. We find that the surface exposure of one aromatic amino acid increases due to dynamic fluctuations. Moreover, protein-carbohydrate interactions decrease upon stress, while protein-protein and carbohydrate-carbohydrate interactions increase. Substitution of the carbohydrate-interacting aromatic amino acids with non-aromatic residues leads to a significantly lower stability than wild type, and to compromised binding to Fc receptors. Our results support a mechanism for antibody aggregation via decreased protein-carbohydrate interactions, leading to the exposure of aggregation-prone regions, and to aggregation.

Design of therapeutic proteins with enhanced stability.

Therapeutic proteins such as antibodies constitute the most rapidly growing class of pharmaceuticals for use in diverse clinical settings including cancer, chronic inflammatory diseases, kidney transplantation, cardiovascular medicine, and infectious diseases. Unfortunately, they tend to aggregate when stored under the concentrated conditions required in their usage. Aggregation leads to a decrease in antibody activity and could elicit an immunological response. Using full antibody atomistic molecular dynamics simulations, we identify the antibody regions prone to aggregation by using a technology that we developed called spatial aggregation propensity (SAP). SAP identifies the location and size of these aggregation prone regions, and allows us to perform target mutations of those regions to engineer antibodies for stability. We apply this method to therapeutic antibodies and demonstrate the significantly enhanced stability of our mutants compared with the wild type. The technology described here could be used to incorporate developability in a rational way during the screening of antibodies in the discovery phase for several diseases.

Aggregation-prone motifs in human immunoglobulin G.

Therapeutic antibodies of many different IgG subclasses (IgG1, IgG2 and IgG4) are used in the treatment of various cancers, rheumatoid arthritis and other inflammatory and infectious diseases. These antibodies are stored for long durations under high concentrations as required in the disease treatment. Unfortunately, these antibodies aggregate under these storage conditions, leading to a decrease in antibody activity and raising concerns about causing an immunological response. Thus, there is a tremendous need to identify the aggregation-prone regions in different classes of antibodies. We use the SAP (spatial-aggregation-propensity) technology based on molecular simulations to determine the aggregation-prone motifs in the constant regions of IgG1 classes of antibodies. Mutations engineered on these aggregation-prone motif regions led to antibodies of enhanced stability. Fourteen aggregation-prone motifs are identified, with each motif containing one to seven residues. While some of these motifs contain residues that are neighbors in primary sequence, others contain residues that are far apart in primary sequence but are close together in the tertiary structure. Comparison of the IgG1 sequence with those of other subclasses (IgG2, IgG3 and IgG4) showed that these aggregation-prone motifs are largely preserved among all IgG subclasses. Other broader classes of antibodies (IgA1, IgD, IgE and IgM), however, differed in these motif regions. The aggregation-prone motifs identified were therefore common to all IgG subclasses, but differ from those of non-IgG classes. Moreover, since the motifs identified are in the constant regions, they are applicable for all antibodies within the IgG class irrespective of the variable region. Thus, the motif regions identified could be modified on all IgGs to yield antibodies of enhanced stability.

Predictive tools for stabilization of therapeutic proteins.

Monoclonal antibodies represent the fastest growing class of pharmaceuticals. A major problem, however, is that the proteins are susceptible to aggregation at the high concentration commonly used during manufacturing and storage. Our recent publication describes a technology based on molecular simulations to identify aggregation-prone regions of proteins in silico. The technology, called spatial aggregation propensity (SAP), identifies hot-spots for aggregation based on the dynamic exposure of spatially-adjacent hydrophobic amino acids. Monoclonal antibodies (mAbs) in which patches with high-SAP scores are changed to patches with significantly reduced SAP scores via a single mutation are more stable than wild type, thus validating the SAP method for mapping aggregation-prone regions on proteins. We propose that the SAP technology will be useful for protein stabilization, and as a screening tool to bridge discovery and development of protein-based therapeutics by a rational assessment of the developability of candidate protein drugs.

Genes with internal repeats require the THO complex for transcription.

The evolutionarily conserved multisubunit THO complex, which is recruited to actively transcribed genes, is required for the efficient expression of FLO11 and other yeast genes that have long internal tandem repeats. FLO11 transcription elongation in Tho- mutants is hindered in the region of the tandem repeats, resulting in a loss of function. Moreover, the repeats become genetically unstable in Tho- mutants. A FLO11 gene without the tandem repeats is transcribed equally well in Tho+ or Tho- strains. The Tho- defect in transcription is suppressed by overexpression of topoisomerase I, suggesting that the THO complex functions to rectify aberrant structures that arise during transcription.