Maureen O’Connor-McCourt

Differential tumor-targeting abilities of three single-domain antibody formats

The large molecular size of antibody drugs is considered one major factor preventing them from becoming more efficient therapeutics. Variable regions of heavy chain antibodies (HCAbs), or single-domain antibodies (sdAbs), are ideal building blocks for smaller antibodies due to their molecular size and enhanced stability. In the search for better antibody formats for in vivo imaging and/or therapy of cancer, three types of sdAb-based molecules directed against epidermal growth factor receptor (EGFR) were constructed, characterized and tested. Eleven sdAbs were isolated from a phage display library constructed from the sdAb repertoire of a llama immunized with a variant of EGFR. A pentameric sdAb, or pentabody, V2C-EG2 was constructed by fusing one of the sdAbs, EG2, to a pentamerization protein domain. A chimeric HCAb (cHCAb), EG2-hFc, was constructed by fusing EG2 to the fragment crystallizable (Fc) of human IgG1. Whereas EG2 and V2C-EG2 localized mainly in the kidneys after i.v. injection, EG2-hFc exhibited excellent tumor accumulation, and this was largely attributed to its long serum half life, which is comparable to that of IgGs. The moderate size (approximately 80 kDa) and intact human Fc make HCAbs a unique antibody format which may outperform whole IgGs as imaging and therapeutic reagents.

Identification of Vascular Breast Tumor Markers by Laser Capture Microdissection and Label-Free LC−MS

Blood vessels in tumors frequently show abnormal characteristics, such as tortuous morphology or leakiness, but very little is known about protein expression in tumor vessels. In this study, we have used laser capture microdissection (LCM) to isolate microvessels from clinical samples of invasive ductal carcinoma (IDC), the most common form of malignant breast cancer, and from patient-matched adjacent nonmalignant tissue. This approach eliminates many of the problems associated with the heterogeneity of clinical tumor tissues by controlling for differences in protein expression between both individual patients and different cell types. Proteins from the microvessels were trypsinized and the resulting peptides were quantified by a label-free nanoLC-MS method. A total of 86 proteins were identified that are overexpressed in tumor vessels relative to vessels isolated from the adjacent nonmalignant tissue. These proteins include well-known breast tumor markers such as Periostin and Tenascin C but also proteins with lesser-known or emerging roles in breast cancer and tumor angiogenesis (i.e., Serpin H1, Clic-1, and Transgelin 2). We also identified 40 proteins that were relatively under-expressed in IDC tumor vessels, including several components of the basement membrane whose lower expression could be responsible for weakening tumor vessels. Lastly, we show that a subset of 29 proteins, derived from our list of differentially expressed proteins, is able to predict survival in three publicly available clinical breast cancer microarray data sets, which suggests that this subset of proteins likely plays a functional role in cancer progression and outcome.

Binding Properties of the Transforming Growth Factor-β Coreceptor Betaglycan: Proposed Mechanism for Potentiation of Receptor Complex Assembly and Signaling

Transforming growth factor (TGF) β1, β2, and β3 (TGF-β1–TGF-β3, respectively) are small secreted signaling proteins that each signal through the TGF-β type I and type II receptors (TβRI and TβRII, respectively). However, TGF-β2, which is well-known to bind TβRII several hundred-fold more weakly than TGF-β1 and TGF-β3, has an additional requirement for betaglycan, a membrane-anchored nonsignaling receptor. Betaglycan has two domains that bind TGF-β2 at independent sites, but how it binds TGF-β2 to potentiate TβRII binding and how the complex with TGF-β, TβRII, and betaglycan undergoes the transition to the signaling complex with TGF-β, TβRII, and TβRI are not understood. To investigate the mechanism, the binding of the TGF-βs to the betaglycan extracellular domain, as well as its two independent binding domains, either directly or in combination with the TβRI and TβRII ectodomains, was studied using surface plasmon resonance, isothermal titration calorimetry, and size-exclusion chromatography. These studies show that betaglycan binds TGF-β homodimers with a 1:1 stoichiometry in a manner that allows one molecule of TβRII to bind. These studies further show that betaglycan modestly potentiates the binding of TβRII and must be displaced to allow TβRI to bind. These findings suggest that betaglycan functions to bind and concentrate TGF-β2 on the cell surface and thus promote the binding of TβRII by both membrane-localization effects and allostery. These studies further suggest that the transition to the signaling complex is mediated by the recruitment of TβRI, which simultaneously displaces betaglycan and stabilizes the bound TβRII by direct receptor–receptor contact.

Computational selection of antibody-drug conjugate targets for breast cancer

The selection of therapeutic targets is a critical aspect of antibody-drug conjugate research and development. In this study, we applied computational methods to select candidate targets overexpressed in three major breast cancer subtypes as compared with a range of vital organs and tissues. Microarray data corresponding to over 8,000 tissue samples were collected from the public domain. Breast cancer samples were classified into molecular subtypes using an iterative ensemble approach combining six classification algorithms and three feature selection techniques, including a novel kernel density-based method. This feature selection method was used in conjunction with differential expression and subcellular localization information to assemble a primary list of targets. A total of 50 cell membrane targets were identified, including one target for which an antibody-drug conjugate is in clinical use, and six targets for which antibody-drug conjugates are in clinical trials for the treatment of breast cancer and other solid tumors. In addition, 50 extracellular proteins were identified as potential targets for non-internalizing strategies and alternative modalities. Candidate targets linked with the epithelial-to-mesenchymal transition were identified by analyzing differential gene expression in epithelial and mesenchymal tumor-derived cell lines. Overall, these results show that mining human gene expression data has the power to select and prioritize breast cancer antibody-drug conjugate targets, and the potential to lead to new and more effective cancer therapeutics.

Glycoproteomic Comparison of Clinical Triple-Negative and Luminal Breast Tumors

Triple-negative (TN) breast cancer accounts for ∼ 15% of breast cancers and is characterized by a high likelihood of relapse and a lack of targeted therapies. In contrast, luminal-type tumors that express the estrogen and progesterone receptors (ER+/PR+) and lack expression of human epidermal growth factor receptor 2 (Her2-) are treated with targeted hormonal therapy and carry a better prognosis. To identify potential targets for the development of future therapeutics aimed specifically at TN breast cancers, we have used a hydrazide-based glycoproteomic workflow to compare protein expression in clinical tumors from nine TN (Her2-/ER-/PR-) and nine luminal (Her2-/ER+/PR+) patients. Using a label-free LC-MS based approach, we identified and quantified 2264 proteins. Of these, 90 proteins were more highly expressed and 86 proteins were underexpressed in the TN tumors relative to the luminal tumors. The expression level of four of these potential targets was verified in the original set of tumors by Western blot and correlated well with our mass-spectrometry-based quantification. Furthermore, 30% of the proteins differentially expressed between luminal and TN tumors were validated in a larger cohort of 406 TN and 469 luminal tumors through corresponding differences in their mRNA expression in publically available microarray data. A group of 29 of these differentially expressed proteins was shown to correctly classify 88% of TN and luminal tumors using microarray data of their associated mRNA levels. Interestingly, even within a group of TN breast cancer patients, the expression levels of these same mRNAs were able to significantly predict patient survival, suggesting that these proteins play a role in the aggressiveness seen in TN tumors. This study provides a comprehensive list of potential targets for the development of diagnostic and therapeutic agents specifically aimed at treating TN breast cancer and demonstrates the utility of using publicly available microarray data to further prioritize potential targets.

Assisted Design of Antibody and Protein Therapeutics (ADAPT)

Effective biologic therapeutics require binding affinities that are fine-tuned to their disease-related molecular target. The ADAPT (Assisted Design of Antibody and Protein Therapeutics) platform aids in the selection of mutants that improve/modulate the affinity of antibodies and other biologics. It uses a consensus z-score from three scoring functions and interleaves computational predictions with experimental validation, significantly enhancing the robustness of the design and selection of mutants. The platform was tested on three antibody Fab-antigen systems that spanned a wide range of initial binding affinities: bH1-VEGF-A (44 nM), bH1-HER2 (3.6 nM) and Herceptin-HER2 (0.058 nM). Novel triple mutants were obtained that exhibited 104-, 46- and 32-fold improvements in binding affinity for each system, respectively. Moreover, for all three antibody-antigen systems over 90% of all the intermediate single and double mutants that were designed and tested showed higher affinities than the parent sequence. The contributions of the individual mutants to the change in binding affinity appear to be roughly additive when combined to form double and triple mutants. The new interactions introduced by the affinity-enhancing mutants included long-range electrostatics as well as short-range nonpolar interactions. This diversity in the types of new interactions formed by the mutants was reflected in SPR kinetics that showed that the enhancements in affinities arose from increasing on-rates, decreasing off-rates or a combination of the two effects, depending on the mutation. ADAPT is a very focused search of sequence space and required only 20–30 mutants for each system to be made and tested to achieve the affinity enhancements mentioned above.

Engineering TGF-β Traps: Artificially Dimerized Receptor Ectodomains as High-affinity Blockers of TGF-β Action

Receptor ectodomain-based ligand traps are a new class of candidate therapeutics that can be optimized using protein engineering approaches that are built on an understanding of the interactions between natural receptors and their ligands. We present here a summary of our characterization of TGF-β ligand-receptor interactions using primarily surface plasmon resonance (SPR)-based biosensor analyses. The results of those studies lead us to hypothesize that artificial dimerization of TGF-β receptor ectodomains may provide a bridged-binding avidity effect that promotes stable binding and increased ligand trapping potency. We confirmed this by utilizing a de novo designed heterodimerizing coiled-coil peptide system to generate, and compare in a systematic manner, monomeric and dimeric versions of soluble TGF-β receptor ectodomains. Finally, we discuss how the potency and specificity of artificially dimerized receptor ectodomain-based traps may compare favorably with other classes of TGF-β pathway inhibitors.

Abstract 560: Development of a novel class of traps that potently block transforming growth factor-beta (TGF-beta) thereby counteracting TGF-beta mediated immunosuppression and promoting T-cell infiltration into tumors

Introduction: Elevated TGF-β ligand markedly augments cancer progression primarily by suppressing the immune system in the tumor microenvironment, in particular by suppressing T-cell recruitment and/or activation. We developed a novel class of decoy receptor traps to potently block TGF- β and induce T-cell infiltration into tumors. This promotes the “T-cell-inflamed” tumor state, which is expected to render tumors sensitive to immune checkpoint inhibitors and other immunotherapeutics. Experimental Procedures: We have computationally designed a class of avidity-enhanced receptor-ectodomain-based traps which bind and neutralize TGF-β. Several trap formats have been produced and tested, with each format exhibiting varying characteristics, including differing circulating half-lives and in vitro blocking potencies (from nM to pM). Representative therapeutic candidates from the different trap formats were evaluated for efficacy in in vivo studies using the syngeneic 4T1 triple negative breast cancer (TNBC) tumor model. Additionally, ex vivo studies were performed on CD4+ and CD8+ T-cells harvested from the draining lymph nodes of treated animals. Results: In efficacy studies using the syngeneic 4T1 TNBC model, novel TGF-β traps were shown to promote significant T-cell infiltration into tumors. This infiltration resulted in reduced primary tumor growth as well as significant reductions in metastatic lesions. Additionally, ex vivo studies revealed that trap treatment decreased T-cell apoptosis, promoted T-cell proliferation in response to tumor cell lysates in the presence of dendritic cells, as well as increased the capacity of T-cells to specifically lyse 4T1 tumor cells. Conclusion: Novel computationally-designed TGF-β traps are capable of promoting the “T-cell-inflamed” tumor state. Combination studies in which this novel class of anti-TGF-β immunotherapy is combined with immune checkpoint inhibitors are ongoing. Citation Format: Maureen D. O’Connor-McCourt, Anne E.G. Lenferink, John Zwaagstra, Traian Sulea, Jason Baardsnes, Catherine Collins, Christiane Cantin, Yves Durocher, Renu Singh, James Koropatnick. Development of a novel class of traps that potently block transforming growth factor-beta (TGF-beta) thereby counteracting TGF-beta mediated immunosuppression and promoting T-cell infiltration into tumors. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 560.