Raghida Bukhalid

Therapeutically Targeting ErbB3: A Key Node in Ligand-Induced Activation of the ErbB Receptor–PI3K Axis

Computational modeling of the ErbB signaling network affirms ErbB3 as a therapeutic target. Zooming In on ErbB3 Aberrant signaling involving the ErbB family of receptors, which can signal as homo- or heterodimers to activate the phosphatidylinositol 3-kinase (PI3K) signaling pathway, has been implicated as contributing to various cancers. Using a systems approach, Schoeberl et al. implicated ErbB3—a member of the ErbB family that is catalytically inactive—as critical to signaling stimulated by ligands that bind either ErbB1 or ErbB3. Computational analysis suggested that inhibiting ligand binding to ErbB3 might represent a more successful approach to treating cancers associated with ligand-induced stimulation of ErbB-PI3K signaling mediated by combinatorial receptor activation than do current therapies that target overexpressed or mutationally activated ErbB-family receptors. Moreover, experimental analysis revealed that a monoclonal antibody developed on the basis of this strategy could stop the growth of tumors grafted into immunodeficient mice. The signaling network downstream of the ErbB family of receptors has been extensively targeted by cancer therapeutics; however, understanding the relative importance of the different components of the ErbB network is nontrivial. To explore the optimal way to therapeutically inhibit combinatorial, ligand-induced activation of the ErbB–phosphatidylinositol 3-kinase (PI3K) axis, we built a computational model of the ErbB signaling network that describes the most effective ErbB ligands, as well as known and previously unidentified ErbB inhibitors. Sensitivity analysis identified ErbB3 as the key node in response to ligands that can bind either ErbB3 or EGFR (epidermal growth factor receptor). We describe MM-121, a human monoclonal antibody that halts the growth of tumor xenografts in mice and, consistent with model-simulated inhibitor data, potently inhibits ErbB3 phosphorylation in a manner distinct from that of other ErbB-targeted therapies. MM-121, a previously unidentified anticancer therapeutic designed using a systems approach, promises to benefit patients with combinatorial, ligand-induced activation of the ErbB signaling network that are not effectively treated by current therapies targeting overexpressed or mutated oncogenes.

A systematic, family-wide investigation reveals that ~30% of mammalian PDZ domains engage in PDZ-PDZ interactions

PDZ domains are independently folded modules that typically mediate protein-protein interactions by binding to the C termini of their target proteins. However, in a few instances, PDZ domains have been reported to dimerize with other PDZ domains. To investigate this noncanonical-binding mode further, we used protein microarrays comprising virtually every mouse PDZ domain to systematically query all possible PDZ-PDZ pairs. We then used fluorescence polarization to retest and quantify interactions and coaffinity purification to test biophysically validated interactions in the context of their full-length proteins. Overall, we discovered 37 PDZ-PDZ interactions involving 46 PDZ domains (~30% of all PDZ domains tested), revealing that dimerization is a more frequently used binding mode than was previously appreciated. This suggests that many PDZ domains evolved to form multiprotein complexes by simultaneously interacting with more than one ligand.

Enhanced Targeting of the EGFR Network with MM-151, an Oligoclonal Anti-EGFR Antibody Therapeutic

Although EGFR is a validated therapeutic target across multiple cancer indications, the often modest clinical responses to current anti-EGFR agents suggest the need for improved therapeutics. Here, we demonstrate that signal amplification driven by high-affinity EGFR ligands limits the capacity of monoclonal anti-EGFR antibodies to block pathway signaling and cell proliferation and that these ligands are commonly coexpressed with low-affinity EGFR ligands in epithelial tumors. To develop an improved antibody therapeutic capable of overcoming high-affinity ligand-mediated signal amplification, we used a network biology approach comprised of signaling studies and computational modeling of receptor–antagonist interactions. Model simulations suggested that an oligoclonal antibody combination may overcome signal amplification within the EGFR:ERK pathway driven by all EGFR ligands. Based on this, we designed MM-151, a combination of three fully human IgG1 monoclonal antibodies that can simultaneously engage distinct, nonoverlapping epitopes on EGFR with subnanomolar affinities. In signaling studies, MM-151 antagonized high-affinity EGFR ligands more effectively than cetuximab, leading to an approximately 65-fold greater decrease in signal amplification to ERK. In cell viability studies, MM-151 demonstrated antiproliferative activity against high-affinity EGFR ligands, either singly or in combination, while cetuximab activity was largely abrogated under these conditions. We confirmed this finding both in vitro and in vivo in a cell line model of autocrine high-affinity ligand expression. Together, these preclinical studies provide rationale for the clinical study of MM-151 and suggest that high-affinity EGFR ligand expression may be a predictive response marker that distinguishes MM-151 from other anti-EGFR therapeutics. Mol Cancer Ther; 14(7); 1625–36. ©2015 AACR.

Abstract A210: Mechanism of action of MM-151, a potent mixture of three human antibody antagonists targeting EGFR.

Epidermal growth factor receptor (EGFR) is a key regulator of cancer cell proliferation, apoptosis, invasion, and metastasis. However, the clinical benefits of EGFR targeted agents such as erlotinib and cetuximab have been modest. Using Merrimack9s Network Biology platform, a computational systems analysis was performed to identify how best to inhibit signaling through the EGFR-ERK network. These simulations predicted that enhanced inhibition is required to overcome the robust signal amplification inherent to this network and is best achieved through treatment with a combination of at least two noncompetitive ligand antagonists. The MM-151 therapeutic was developed to achieve the simulated design criteria and consists of a mixture of three fully human monoclonal antibodies directed against distinct non-overlapping epitopes in EGFR. Detailed in vitro and on-cell binding experiments, supported by computational simulations, with single component antibodies and their monovalent Fab variants, display a rich complexity of antibody affinity and avidity. All three antibodies are shown to have subnanomolar monovalent affinity to EGFR but to vary in the degree to which they functionally crosslink receptor (two antibodies display high avidity while the third has weak avidity). Ligand competition experiments with saturating antibody concentrations (EC90 of on-cell binding) demonstrate that two of the antibodies are each complete ligand antagonists while the third antibody is a partial (approx. 25%) antagonist. When combined into the MM-151 mixture, these antibodies simultaneously engage and robustly crosslink receptor to form a highly antagonistic therapeutic. Treatment of human tumor-derived cell lines with MM-151 elicits complete inhibition of ligand-mediated ERK signaling over a wide range of both EGF receptor density (as high as 2×10∘6 receptors per cell in the A431 cell line) and ligand burden (8 and 80nM EGF). In contrast, monoclonal EGFR targeted therapeutics, such as cetuximab and panitumumab, as well as oligoclonal inhibitors similar to MM-151, show weaker or even no effect on ERK signaling under similar conditions. Furthermore, the potency of monovalent MM-151 (Fab variants) is diminished in EGF mediated EGFR and ERK signaling, highlighting the importance of receptor crosslinking through antibody avidity as a determinant of efficacy. Together, these data demonstrate that MM-151 is a potent inhibitor of the EGFR-ERK signaling axis with the potential of improved efficacy over current EGFR targeted therapies. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr A210.

Abstract A144: Therapeutically targeting high-affinity ligand activation of EGFR with MM-151, an oligoclonal therapeutic.

The Epidermal Growth Factor Receptor (EGFR/ErbB1) is a receptor tyrosine kinase whose activation has been shown to play a key role in tumor growth and development. The EGFR ligand family is comprised of seven transmembrane precursor proteins whose expression and processing is highly regulated. These ligands can be classified based upon their affinity to EGFR; epidermal growth factor (EGF), betacellulin (BTC), heparin-binding epidermal growth factor (HB-EGF), and transforming growth factor alpha (TGFα) are considered high-affinity ligands, whereas amphiregulin (AREG), epiregulin (EREG), and epigen (EPI) are considered low-affinity ligands. EGFR overexpression in tumors is associated with higher risk of recurrence, metastasis, poorer survival and resistance to chemotherapy. Therefore, this pathway is a compelling target for the development of anti-EGFR therapeutics. Using Merrimack9s Network Biology approach, we performed a computational systems analysis to identify an optimal strategy to inhibit the EGFR-ERK signaling network, which is characterized by robust signal amplification from the receptor to downstream effectors. As a result, we developed MM-151, an oligoclonal therapeutic composed of three fully human monoclonal antibodies targeted to distinct EGFR epitopes. MM-151 inhibits EGFR pathway activation by the dual mechanism of EGFR ligand-blocking and enhancement of receptor downregulation. Our preclinical in vitro studies revealed greater potency for MM-151 versus existing monoclonal antibodies (e.g. cetuximab, panitumumab and nimotuzumab). Importantly, MM-151 was shown to inhibit in vitro ERK signaling and cell proliferation induced by both high- and low-affinity EGFR ligands, unlike existing monoclonal therapeutics, which only block low-affinity ligand-induced signaling and cell proliferation. In in vitro cell proliferation assays, several cell line models that were responsive to anti-EGFR monoclonals in the presence of the low-affinity ligand AREG became increasingly unresponsive to treatment upon titrating in increasing amounts of the high-affinity ligand EGF. Conversely, cells remained responsive to MM-151 even in the presence of high-affinity EGF ligand burden. In preclinical non-small cell lung cancer (NSCLC) and head and neck squamous cell carcinoma (HNSCC) EGFR-wildtype cell line models, overexpression of autocrine AREG is positively correlated with increased sensitivity to the anti-EGFR monoclonal cetuximab or tyrosine kinase inhibitor gefitinib (K. Yonesaka et al. , Clin. Cancer Res., 2008, 14: 6963–6973). In the clinic, metastatic colon cancer patients with wild type K-ras tumors highly expressing the low-affinity ligands AREG and EREG are more likely to exhibit disease control on cetuximab treatment (J. B. Baker et al. , Br. J. Cancer, 2011, 104: 488–495). Our preclinical data suggest that elevated high-affinity ligand expression would likely correlate with decreased patient response to anti-EGFR monoclonals, and that patients whose tumors are driven by high-affinity EGFR ligands might instead benefit from MM-151 treatment. Together, these data suggest that MM-151, capable of blocking both high and low affinity ligand-driven EGFR signaling, may have the potential to more broadly benefit lung and colon cancer patients as compared to existing EGFR-directed therapies. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr A144.

Abstract PR9: Investigating combinatorial ligand addiction provides insights into rational drug combinations in cancer therapy

Cancer, the second most common cause of death in the United States, is a collection of diseases caused by uncontrolled cell growth and metastasis. The main treatment for cancer is chemotherapy, which generally kills fast growing cells nonspecifically and has many side effects. A different type of cancer treatment, called targeted therapy, aims to avoid general toxicity by using drugs that block the activity of specific gene products, usually encoded by oncogenes, which have been shown to drive tumor growth. To date, targeted therapies, alone or in combination with chemotherapies, have mainly been successful in rare subsets of patients with tumors addicted to single oncogenes. This has created a rationale to mainly treat patients with an oncogene-addiction (such as those carrying mutated or overexpressed kinases) with targeted therapies like erlotinib and trastuzumab, which inhibit human epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 2 (HER2/ErbB2), respectively. Here, evidence is provided that targeted therapies are also effective in tumors that are dependent on multiple growth factors – a phenomenon that is called combinatorial ligand addiction. Specifically, it is shown that ligands that bind the EGFR family and the hepatocyte growth factor receptor (HGFR/MET) can activate protein kinase B (PKB/AKT) across a broad set of cancer cell lines, suggesting that ligand signaling is redundant and widespread. It is also shown that ErbB ligands have distinct signaling dynamics and strengths, which provides a rationale for investigating each component of the ErbB signaling network. Using a systematic approach, we found that ErbB3 is an important therapeutic target even though it is not overexpressed and lacks kinase activity. Furthermore, it is shown that cell lines with and without known oncogene-addiction express autocrine ligands and have improved growth inhibition with drug combinations that include autocrine ligand-blocking antibodies. This research demonstrates that combinatorial ligand addiction creates a new rationale for therapeutic combinations to improve efficacy and prevent resistance in cancer cells that are treated with current targeted drugs. This proffered talk is also presented as Poster A22. Citation Format: Emily A. Pace, Ulrik B. Nielsen, Birgit Schoeberl, Diana H. Chai, Anand Parikh, Ashish Kalra, Shinji Oyama, Bryan Johnson, Gege Tan, Aaron Fulgham, Raghida Bukhalid. Investigating combinatorial ligand addiction provides insights into rational drug combinations in cancer therapy [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr PR9.

Abstract 3756: Prediction of xenograft response to MM-121, an anti-ErbB3 inhibitor, using computational modeling and measurements of five biomarkers

Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC One of the challenges faced by targeted therapeutics currently in the clinic is the relatively small population of patients who derive significant benefit from their use. We report the development of a preclinical classifier which can correctly predict xenograft response to MM-121, an anti-ErbB3 antibody, based on the measurement of a few key biomarkers in cell lysates. Deregulation of the ErbB family receptors is common in many cancers. Using a combination of computational modeling and quantitative experiments we identified ErbB3 as a key mediator of mitogenic signaling downstream of the ErbB receptors. Based on these results, we developed MM-121, a first in class anti-ErbB3 monoclonal antibody that blocks heregulin-induced signaling and inhibits tumor growth in multiple xenograft models of human cancer. Here we present our efforts to derive a predictive biomarker signature that identifies tumors that are responsive to MM-121. Using our computational model of the ErbB signaling pathway we identified the five most critical proteins for predicting activation of phospho-AKT - a key mediator of cell survival and apoptosis. These proteins include MM-121s target, ErbB3, and its ligand, heregulin. We profiled these biomarkers in a large panel of cancer cell lines, and using the measured effect of MM-121 on inhibiting tumor growth in eight xenograft tumor models, we determined a classification rule for predicting xenograft response. We subsequently used this classification rule to correctly predict a priori MM-121 response in 11 xenograft models. These results suggest that our computationally-derived biomarker signature is sufficient for predicting response to MM-121 in xenografts, and could offer significant clinical benefit by helping select patients for MM-121 treatment. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3756.