Identification and high-throughput genotyping of single nucleotide polymorphism markers in a non-model conifer (Abies nordmanniana (Steven) Spach).

Single nucleotide polymorphism (SNP) markers are powerful tools for investigating population structures, linkage analysis, and genome-wide association studies, as well as for breeding and population management. The availability of SNP markers has been limited to the most commercially important timber species, primarily due to the cost of genome sequencing required for SNP discovery. In this study, a combination of reference-based and reference-free approaches were used to identify SNPs in Nordmann fir (Abies nordmanniana), a species previously lacking genomic sequence information. Using a combination of a genome assembly of the closely related Silver fir (Abies alba) species and a de novo assembly of low-copy regions of the Nordmann fir genome, we identified a high density of reliable SNPs. Reference-based approaches identified two million SNPs in common between the Silver fir genome and low-copy regions of Nordmann fir. A combination of one reference-free and two reference-based approaches identified 250 shared SNPs. A subset of 200 SNPs were used to genotype 342 individuals and thereby tested and validated in the context of identity analysis and/or clone identification. The tested SNPs successfully identified all ramets per clone and five mislabeled individuals via identity and genomic relatedness analysis. The identified SNPs will be used in ad hoc breeding of Nordmann fir in Denmark.

MM-131, a bispecific anti-Met/EpCAM mAb, inhibits HGF-dependent and HGF-independent Met signaling through concurrent binding to EpCAM.

Activation of the Met receptor tyrosine kinase, either by its ligand, hepatocyte growth factor (HGF), or via ligand-independent mechanisms, such as MET amplification or receptor overexpression, has been implicated in driving tumor proliferation, metastasis, and resistance to therapy. Clinical development of Met-targeted antibodies has been challenging, however, as bivalent antibodies exhibit agonistic properties, whereas monovalent antibodies lack potency and the capacity to down-regulate Met. Through computational modeling, we found that the potency of a monovalent antibody targeting Met could be dramatically improved by introducing a second binding site that recognizes an unrelated, highly expressed antigen on the tumor cell surface. Guided by this prediction, we engineered MM-131, a bispecific antibody that is monovalent for both Met and epithelial cell adhesion molecule (EpCAM). MM-131 is a purely antagonistic antibody that blocks ligand-dependent and ligand-independent Met signaling by inhibiting HGF binding to Met and inducing receptor down-regulation. Together, these mechanisms lead to inhibition of proliferation in Met-driven cancer cells, inhibition of HGF-mediated cancer cell migration, and inhibition of tumor growth in HGF-dependent and -independent mouse xenograft models. Consistent with its design, MM-131 is more potent in EpCAM-high cells than in EpCAM-low cells, and its potency decreases when EpCAM levels are reduced by RNAi. Evaluation of Met, EpCAM, and HGF levels in human tumor samples reveals that EpCAM is expressed at high levels in a wide range of Met-positive tumor types, suggesting a broad opportunity for clinical development of MM-131.

Dual Inhibition of IGF-1R and ErbB3 Enhances the Activity of Gemcitabine and Nab-Paclitaxel in Preclinical Models of Pancreatic Cancer.

Purpose: Insulin-like growth factor receptor 1 (IGF-1R) is critically involved in pancreatic cancer pathophysiology, promoting cancer cell survival and therapeutic resistance. Assessment of IGF-1R inhibitors in combination with standard-of-care chemotherapy, however, failed to demonstrate significant clinical benefit. The aim of this work is to unravel mechanisms of resistance to IGF-1R inhibition in pancreatic cancer and develop novel strategies to improve the activity of standard-of-care therapies.Experimental Design: Growth factor screening in pancreatic cancer cell lines was performed to identify activators of prosurvival PI3K/AKT signaling. The prevalence of activating growth factors and their receptors was assessed in pancreatic cancer patient samples. Effects of a bispecific IGF-1R and ErbB3 targeting antibody on receptor expression, signaling, cancer cell viability and apoptosis, spheroid growth, and in vivo chemotherapy activity in pancreatic cancer xenograft models were determined.Results: Growth factor screening in pancreatic cancer cells revealed insulin-like growth factor 1 (IGF-1) and heregulin (HRG) as the most potent AKT activators. Both growth factors reduced pancreatic cancer cell sensitivity to gemcitabine or paclitaxel in spheroid growth assays. Istiratumab (MM-141), a novel bispecific antibody that blocks IGF-1R and ErbB3, restored the activity of paclitaxel and gemcitabine in the presence of IGF-1 and HRG in vitro Dual IGF-1R/ErbB3 blocking enhanced chemosensitivity through inhibition of AKT phosphorylation and promotion of IGF-1R and ErbB3 degradation. Addition of istiratumab to gemcitabine and nab-paclitaxel improved chemotherapy activity in vivoConclusions: Our findings suggest a critical role for the HRG/ErbB3 axis and support the clinical exploration of dual IGF-1R/ErbB3 blocking in pancreatic cancer. Clin Cancer Res; 24(12); 2873-85. ©2018 AACR.

Systems biology driving drug development: from design to the clinical testing of the anti-ErbB3 antibody seribantumab (MM-121).

The ErbB family of receptor tyrosine kinases comprises four members: epidermal growth factor receptor (EGFR/ErbB1), human EGFR 2 (HER2/ErbB2), ErbB3/HER3, and ErbB4/HER4. The first two members of this family, EGFR and HER2, have been implicated in tumorigenesis and cancer progression for several decades, and numerous drugs have now been approved that target these two proteins. Less attention, however, has been paid to the role of this family in mediating cancer cell survival and drug tolerance. To better understand the complex signal transduction network triggered by the ErbB receptor family, we built a computational model that quantitatively captures the dynamics of ErbB signaling. Sensitivity analysis identified ErbB3 as the most critical activator of phosphoinositide 3-kinase (PI3K) and Akt signaling, a key pro-survival pathway in cancer cells. Based on this insight, we designed a fully human monoclonal antibody, seribantumab (MM-121), that binds to ErbB3 and blocks signaling induced by the extracellular growth factors heregulin (HRG) and betacellulin (BTC). In this article, we present some of the key preclinical simulations and experimental data that formed the scientific foundation for three Phase 2 clinical trials in metastatic cancer. These trials were designed to determine if patients with advanced malignancies would derive benefit from the addition of seribantumab to standard-of-care drugs in platinum-resistant/refractory ovarian cancer, hormone receptor-positive HER2-negative breast cancer, and EGFR wild-type non-small cell lung cancer (NSCLC). From preclinical studies we learned that basal levels of ErbB3 phosphorylation correlate with response to seribantumab monotherapy in mouse xenograft models. As ErbB3 is rapidly dephosphorylated and hence difficult to measure clinically, we used the computational model to identify a set of five surrogate biomarkers that most directly affect the levels of p-ErbB3: HRG, BTC, EGFR, HER2, and ErbB3. Preclinically, the combined information from these five markers was sufficient to accurately predict which xenograft models would respond to seribantumab, and the single-most accurate predictor was HRG. When tested clinically in ovarian, breast and lung cancer, HRG mRNA expression was found to be both potentially prognostic of insensitivity to standard therapy and potentially predictive of benefit from the addition of seribantumab to standard of care therapy in all three indications. In addition, it was found that seribantumab was most active in cancers with low levels of HER2, consistent with preclinical predictions. Overall, our clinical studies and studies of others suggest that HRG expression defines a drug-tolerant cancer cell phenotype that persists in most solid tumor indications and may contribute to rapid clinical progression. To our knowledge, this is the first example of a drug designed and clinically tested using the principles of Systems Biology.

HER2+ Cancer Cell Dependence on PI3K vs. MAPK Signaling Axes Is Determined by Expression of EGFR, ERBB3 and CDKN1B.

Understanding the molecular pathways by which oncogenes drive cancerous cell growth, and how dependence on such pathways varies between tumors could be highly valuable for the design of anti-cancer treatment strategies. In this work we study how dependence upon the canonical PI3K and MAPK cascades varies across HER2+ cancers, and define biomarkers predictive of pathway dependencies. A panel of 18 HER2+ (ERBB2-amplified) cell lines representing a variety of indications was used to characterize the functional and molecular diversity within this oncogene-defined cancer. PI3K and MAPK-pathway dependencies were quantified by measuring in vitro cell growth responses to combinations of AKT (MK2206) and MEK (GSK1120212; trametinib) inhibitors, in the presence and absence of the ERBB3 ligand heregulin (NRG1). A combination of three protein measurements comprising the receptors EGFR, ERBB3 (HER3), and the cyclin-dependent kinase inhibitor p27 (CDKN1B) was found to accurately predict dependence on PI3K/AKT vs. MAPK/ERK signaling axes. Notably, this multivariate classifier outperformed the more intuitive and clinically employed metrics, such as expression of phospho-AKT and phospho-ERK, and PI3K pathway mutations (PIK3CA, PTEN, and PIK3R1). In both cell lines and primary patient samples, we observed consistent expression patterns of these biomarkers varies by cancer indication, such that ERBB3 and CDKN1B expression are relatively high in breast tumors while EGFR expression is relatively high in other indications. The predictability of the three protein biomarkers for differentiating PI3K/AKT vs. MAPK dependence in HER2+ cancers was confirmed using external datasets (Project Achilles and GDSC), again out-performing clinically used genetic markers. Measurement of this minimal set of three protein biomarkers could thus inform treatment, and predict mechanisms of drug resistance in HER2+ cancers. More generally, our results show a single oncogenic transformation can have differing effects on cell signaling and growth, contingent upon the molecular and cellular context.

Cyclophosphamide-Mediated Tumor Priming for Enhanced Delivery and Antitumor Activity of HER2-Targeted Liposomal Doxorubicin (MM-302).

Given the bulky nature of nanotherapeutics relative to small molecules, it is hypothesized that effective tumor delivery and penetration are critical barriers to their clinical activity. HER2-targeted PEGylated liposomal doxorubicin (MM-302, HER2-tPLD) is an antibody-liposomal drug conjugate designed to deliver doxorubicin to HER2-overexpressing cancer cells while limiting uptake into nontarget cells. In this work, we demonstrate that the administration and appropriate dose sequencing of cyclophosphamide can improve subsequent MM-302 delivery and enhance antitumor activity in preclinical models without negatively affecting nontarget tissues, such as the heart and skin. We demonstrate that this effect is critically dependent on the timing of cyclophosphamide administration. Furthermore, the effect was found to be unique to cyclophosphamide and related analogues, and not shared by other agents, such as taxanes or eribulin, under the conditions examined. Analysis of the cyclophosphamide-treated tumors suggests that the mechanism for improved MM-302 delivery involves the induction of tumor cell apoptosis, reduction of overall tumor cell density, substantial lowering of interstitial fluid pressure, and increasing vascular perfusion. The novel dosing strategy for cyclophosphamide described herein is readily translatable to standard clinical regimens, represents a potentially significant advance in addressing the drug delivery challenge, and may have broad applicability for nanomedicines. This work formed the basis for clinical evaluation of cyclophosphamide for improving liposome deposition as part of an ongoing phase I clinical trial of MM-302 in HER2-positive metastatic breast cancer.

Heregulin-ErbB3-Driven Tumor Growth Persists in PI3 Kinase Mutant Cancer Cells.

PI3K is frequently mutated in cancer and plays an important role in cell growth and survival. Heregulin (HRG)-mediated autocrine or paracrine signaling through the receptor tyrosine kinase ErbB3 potently activates the PI3K/AKT pathway and has been shown to mediate resistance to a wide variety of anticancer agents. Although PI3K functions downstream of HRG-ErbB3, it is unknown whether activating mutations in PI3K render HRG ineffective. If so, patients with PI3K mutations would not be expected to benefit from ErbB3-directed therapies. Here, we find that a subset of cell lines harboring activating PI3K mutations can be further growth-stimulated by HRG, and this effect is blocked by incubation with seribantumab (MM-121), a monoclonal anti-ErbB3 antibody. Although expression of mutant PI3K in wild-type PI3K cells frequently results in loss of HRG-stimulated growth, some cell lines continue to respond to HRG. In cell lines where HRG-stimulated growth is lost, this loss is invariably accompanied by a reduction in ErbB3 levels, a corresponding increase in basal phosphorylation levels of FOXO-family transcription factors, and a reduction in HRG-induced downstream signaling. Importantly, HRG-stimulated growth is partially rescued by re-expressing ErbB3. This response is blocked by seribantumab, indicating that ErbB3 levels rather than downstream signaling proteins limit HRG-stimulated growth in PI3K mutant cells. Overall, these results suggest that activating mutations in PI3K do not preclude potential benefit from ErbB3-directed therapy, but that it may be important to measure ErbB3 levels in patients with PI3K mutant cancers to determine if they would benefit.

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.

Comprehensive optimization of a single-chain variable domain antibody fragment as a targeting ligand for a cytotoxic nanoparticle.

Antibody-targeted nanoparticles have the potential to significantly increase the therapeutic index of cytotoxic anti-cancer therapies by directing them to tumor cells. Using antibodies or their fragments requires careful engineering because multiple parameters, including affinity, internalization rate and stability, all need to be optimized. Here, we present a case study of the iterative engineering of a single chain variable fragment (scFv) for use as a targeting arm of a liposomal cytotoxic nanoparticle. We describe the effect of the orientation of variable domains, the length and composition of the interdomain protein linker that connects VH and VL, and stabilizing mutations in both the framework and complementarity-determining regions (CDRs) on the molecular properties of the scFv. We show that variable domain orientation can alter cross-reactivity to murine antigen while maintaining affinity to the human antigen. We demonstrate that tyrosine residues in the CDRs make diverse contributions to the binding affinity and biophysical properties, and that replacement of non-essential tyrosines can improve the stability and bioactivity of the scFv. Our studies demonstrate that a comprehensive engineering strategy may be required to identify a scFv with optimal characteristics for nanoparticle targeting.

Preclinical activity of nanoliposomal irinotecan is governed by tumor deposition and intratumor prodrug conversion.

A major challenge in the clinical use of cytotoxic chemotherapeutics is maximizing efficacy in tumors while sparing normal tissue. Irinotecan is used for colorectal cancer treatment but the extent of its use is limited by toxic side effects. Liposomal delivery systems offer tools to modify pharmacokinetic and safety profiles of cytotoxic drugs. In this study, we defined parameters that maximize the antitumor activity of a nanoliposomal formulation of irinotecan (nal-IRI). In a mouse xenograft model of human colon carcinoma, nal-IRI dosing could achieve higher intratumoral levels of the prodrug irinotecan and its active metabolite SN-38 compared with free irinotecan. For example, nal-IRI administered at doses 5-fold lower than free irinotecan achieved similar intratumoral exposure of SN-38 but with superior antitumor activity. Tumor response and pharmacokinetic modeling identified the duration for which concentrations of SN-38 persisted above a critical intratumoral threshold of 120 nmol/L as determinant for antitumor activity. We identified tumor permeability and carboxylesterase activity needed for prodrug activation as critical factors in achieving longer duration of SN-38 in tumors. Simulations varying tumor permeability and carboxylesterase activity predicted a concave increase in tumor SN-38 duration, which was confirmed experimentally in 13 tumor xenograft models. Tumors in which higher SN-38 duration was achieved displayed more robust growth inhibition compared with tumors with lower SN-38 duration, confirming the importance of this factor in drug response. Overall, our work shows how liposomal encapsulation of irinotecan can safely improve its antitumor activity in preclinical models by enhancing accumulation of its active metabolite within the tumor microenvironment.

Insulin-like growth factor promotes cardiac lineage induction in vitro by selective expansion of early mesoderm.

A thorough understanding of the developmental signals that direct pluripotent stem cells (PSCs) toward a cardiac fate is essential for translational applications in disease modeling and therapy. We screened a panel of 44 cytokines/signaling molecules for their ability to enhance Nkx2.5(+) cardiac progenitor cell (CPC) formation during in vitro embryonic stem cell (ESC) differentiation. Treatment of murine ESCs with insulin or insulin-like growth factors (IGF1/2) during early differentiation increased mesodermal cell proliferation and, consequently, CPC formation. Furthermore, we show that downstream mediators of IGF signaling (e.g., phospho-Akt and mTOR) are required for this effect. These data support a novel role for IGF family ligands to expand the developing mesoderm and promote cardiac differentiation. Insulin or IGF treatment could provide an effective strategy to increase the PSC-based generation of CPCs and cardiomyocytes for applications in regenerative medicine.

MM-141, an IGF-IR- and ErbB3-directed bispecific antibody, overcomes network adaptations that limit activity of IGF-IR inhibitors.

Although inhibition of the insulin-like growth factor (IGF) signaling pathway was expected to eliminate a key resistance mechanism for EGF receptor (EGFR)-driven cancers, the effectiveness of IGF-I receptor (IGF-IR) inhibitors in clinical trials has been limited. A multiplicity of survival mechanisms are available to cancer cells. Both IGF-IR and the ErbB3 receptor activate the PI3K/AKT/mTOR axis, but ErbB3 has only recently been pursued as a therapeutic target. We show that coactivation of the ErbB3 pathway is prevalent in a majority of cell lines responsive to IGF ligands and antagonizes IGF-IR-mediated growth inhibition. Blockade of the redundant IGF-IR and ErbB3 survival pathways and downstream resistance mechanisms was achieved with MM-141, a tetravalent bispecific antibody antagonist of IGF-IR and ErbB3. MM-141 potency was superior to monospecific and combination antibody therapies and was insensitive to variation in the ratio of IGF-IR and ErbB3 receptors. MM-141 enhanced the biologic impact of receptor inhibition in vivo as a monotherapy and in combination with the mTOR inhibitor everolimus, gemcitabine, or docetaxel, through blockade of IGF-IR and ErbB3 signaling and prevention of PI3K/AKT/mTOR network adaptation.

Computational modeling of ERBB2-amplified breast cancer identifies combined ErbB2/3 blockade as superior to the combination of MEK and AKT inhibitors.

Crosstalk and compensatory circuits within cancer signaling networks limit the activity of most targeted therapies. For example, altered signaling in the networks activated by the ErbB family of receptors, particularly in ERBB2-amplified cancers, contributes to drug resistance. We developed a multiscale systems model of signaling networks in ERBB2-amplified breast cancer to quantitatively investigate relationships between biomarkers (markers of network activity) and combination drug efficacy. This model linked ErbB receptor family signaling to breast tumor growth through two kinase cascades: the PI3K/AKT survival pathway and the Ras/MEK/ERK growth and proliferation pathway. The model predicted molecular mechanisms of resistance to individual therapeutics. In particular, ERBB2-amplified breast cancer cells stimulated with the ErbB3 ligand heregulin were resistant to growth arrest induced by inhibitors of AKT and MEK or coapplication of two inhibitors of the receptor ErbB2 [Herceptin (trastuzumab) and Tykerb (lapatinib)]. We used model simulations to predict the response of ErbB2-positive breast cancer xenografts to combination therapies and verified these predictions in mice. Treatment with trastuzumab, lapatinib, and the ErbB3 inhibitor MM-111 was more effective in inhibiting tumor growth than the combination of AKT and MEK inhibitors and even induced tumor regression, indicating that targeting both ErbB3 and ErbB2 may be an improved therapeutic approach for ErbB2-positive breast cancer patients.

HER2-targeted liposomal doxorubicin displays enhanced anti-tumorigenic effects without associated cardiotoxicity.

Anthracycline-based regimens are a mainstay of early breast cancer therapy, however their use is limited by cardiac toxicity. The potential for cardiotoxicity is a major consideration in the design and development of combinatorial therapies incorporating anthracyclines and agents that target the HER2-mediated signaling pathway, such as trastuzumab. In this regard, HER2-targeted liposomal doxorubicin was developed to provide clinical benefit by both reducing the cardiotoxicity observed with anthracyclines and enhancing the therapeutic potential of HER2-based therapies that are currently available for HER2-overexpressing cancers. While documenting the enhanced therapeutic potential of HER2-targeted liposomal doxorubicin can be done with existing models, there has been no validated human cardiac cell-based assay system to rigorously assess the cardiotoxicity of anthracyclines. To understand if HER2-targeting of liposomal doxorubicin is possible with a favorable cardiac safety profile, we applied a human stem cell-derived cardiomyocyte platform to evaluate the doxorubicin exposure of human cardiac cells to HER2-targeted liposomal doxorubicin. To the best of our knowledge, this is the first known application of a stem cell-derived system for evaluating preclinical cardiotoxicity of an investigational agent. We demonstrate that HER2-targeted liposomal doxorubicin has little or no uptake into human cardiomyocytes, does not inhibit HER2-mediated signaling, results in little or no evidence of cardiomyocyte cell death or dysfunction, and retains the low penetration into heart tissue of liposomal doxorubicin. Taken together, this data ultimately led to the clinical decision to advance this drug to Phase I clinical testing, which is now ongoing as a single agent in HER2-expressing cancers.

Impact of intrinsic affinity on functional binding and biological activity of EGFR antibodies.

Aberrant expression and activation of EGF receptor (EGFR) has been implicated in the development and progression of many human cancers. As such, targeted therapeutic inhibition of EGFR, for example by antibodies, is a promising anticancer strategy. The overall efficacy of antibody therapies results from the complex interplay between affinity, valence, tumor penetration and retention, and signaling inhibition. To gain better insight into this relationship, we studied a panel of EGFR single-chain Fv (scFv) antibodies that recognize an identical epitope on EGFR but bind with intrinsic monovalent affinities varying by 280-fold. The scFv were converted to Fab and IgG formats, and investigated for their ability to bind EGFR, compete with EGF binding, and inhibit EGF-mediated downstream signaling and proliferation. We observed that the apparent EGFR-binding affinity for bivalent IgG plateaus at intermediate values of intrinsic affinity of the cognate Fab, leading to a biphasic curve describing the ratio of IgG to Fab affinity. Mathematical modeling of antibody-receptor binding indicated that the biphasic effect results from nonequilibrium assay limitations. This was confirmed by further observation that the potency of EGF competition for antibody binding to EGFR improved with both intrinsic affinity and antibody valence. Similarly, both higher intrinsic affinity and bivalent binding improved the potency of antibodies in blocking cellular signaling and proliferation. Overall, our work indicates that higher intrinsic affinity combined with bivalent binding can achieve avidity that leads to greater in vitro potency of antibodies, which may translate into greater therapeutic efficacy.

Antitumor activity of a novel bispecific antibody that targets the ErbB2/ErbB3 oncogenic unit and inhibits heregulin-induced activation of ErbB3.

The prevalence of ErbB2 amplification in breast cancer has resulted in the heavy pursuit of ErbB2 as a therapeutic target. Although both the ErbB2 monoclonal antibody trastuzumab and ErbB1/ErbB2 dual kinase inhibitor lapatinib have met with success in the clinic, many patients fail to benefit. In addition, the majority of patients who initially respond will unfortunately ultimately progress on these therapies. Activation of ErbB3, the preferred dimerization partner of ErbB2, plays a key role in driving ErbB2-amplified tumor growth, but we have found that current ErbB2-directed therapies are poor inhibitors of ligand-induced activation. By simulating ErbB3 inhibition in a computational model of ErbB2/ErbB3 receptor signaling, we predicted that a bispecific antibody that docks onto ErbB2 and subsequently binds to ErbB3 and blocks ligand-induced receptor activation would be highly effective in ErbB2-amplified tumors, with superior activity to a monospecific ErbB3 inhibitor. We have developed a bispecific antibody suitable for both large scale production and systemic therapy by generating a single polypeptide fusion protein of two human scFv antibodies linked to modified human serum albumin. The resulting molecule, MM-111, forms a trimeric complex with ErbB2 and ErbB3, effectively inhibiting ErbB3 signaling and showing antitumor activity in preclinical models that is dependent on ErbB2 overexpression. MM-111 can be rationally combined with trastuzumab or lapatinib for increased antitumor activity and may in the future complement existing ErbB2-directed therapies to treat resistant tumors or deter relapse.

Optimizing properties of antireceptor antibodies using kinetic computational models and experiments.

Monoclonal antibodies are valuable as anticancer therapeutics because of their ability to selectively bind tumor-associated target proteins like receptor tyrosine kinases. Kinetic computational models that capture protein-protein interactions using mass action kinetics are a valuable tool for understanding the binding properties of monoclonal antibodies to their targets. Insights from the models can be used to explore different formats, to set antibody design specifications such as affinity and valence, and to predict potency. Antibody binding to target is driven by both intrinsic monovalent affinity and bivalent avidity. In this chapter, we describe a combined experimental and computational method of assessing the relative importance of these effects on observed drug potency. The method, which we call virtual flow cytometry (VFC), merges experimental measurements of monovalent antibody binding kinetics and affinity curves of antibody-antigen binding into a kinetic computational model of antibody-antigen interaction. The VFC method introduces a parameter χ, the avidity factor, which characterizes the ability of an antibody to cross-link its target through bivalent binding. This simple parameterization of antibody cross-linking allows the model to successfully describe and predict antibody binding curves across a wide variety of experimental conditions, including variations in target expression level and incubation time of antibody with target. We further demonstrate how computational models of antibody binding to cells can be used to predict target inhibition potency. Importantly, we demonstrate computationally that antibodies with high ability to cross-link antigen have significant potency advantages. We also present data suggesting that the parameter χ is a physical, epitope-dependent property of an antibody, and as a result propose that determination of antibody cross-linking and avidity should be incorporated into the screening of antibody panels for therapeutic development. Overall, our results suggest that antibody cross-linking, in addition to monovalent binding affinity, is a key design parameter of antibody performance.

Building and characterizing antibody-targeted lipidic nanotherapeutics.

Immunoliposomes provide a complementary, and in many instances advantageous, drug delivery strategy to antibody-drug conjugates. Their high carrying capacity of 20,000-150,000 drug molecules/liposome, allows for the use of a significantly broader range of moderate-to-high potency small molecule drugs when compared to the comparably few subnanomolar potency maytansinoid- and auristatin-based immunoconjugates. The multivalent display of 5-100 antibody fragments/liposome results in an avidity effect that can make use of even moderate affinity antibodies, as well as a cross-linking of cell surface receptors to induce the internalization required for intracellular drug release and subsequent activity. The underlying liposomal drug must be effectively engineered for long circulating pharmacokinetics and stable in vivo drug retention in order to allow for the drug to be efficiently delivered to the target tissue and take advantage of the site-specific bioavailability provided for by the targeting arm. In this chapter, we describe the rationale for engineering stable immunoliposome-based therapeutics, methods required for preparation of immunoliposomes, as well as for their physicochemical and in vivo characterization.

An ErbB3 antibody, MM-121, is active in cancers with ligand-dependent activation.

ErbB3 is a critical activator of phosphoinositide 3-kinase (PI3K) signaling in epidermal growth factor receptor (EGFR; ErbB1), ErbB2 [human epidermal growth factor receptor 2 (HER2)], and [hepatocyte growth factor receptor (MET)] addicted cancers, and reactivation of ErbB3 is a prominent method for cancers to become resistant to ErbB inhibitors. In this study, we evaluated the in vivo efficacy of a therapeutic anti-ErbB3 antibody, MM-121. We found that MM-121 effectively blocked ligand-dependent activation of ErbB3 induced by either EGFR, HER2, or MET. Assessment of several cancer cell lines revealed that MM-121 reduced basal ErbB3 phosphorylation most effectively in cancers possessing ligand-dependent activation of ErbB3. In those cancers, MM-121 treatment led to decreased ErbB3 phosphorylation and, in some instances, decreased ErbB3 expression. The efficacy of single-agent MM-121 was also examined in xenograft models. A machine learning algorithm found that MM-121 was most effective against xenografts with evidence of ligand-dependent activation of ErbB3. We subsequently investigated whether MM-121 treatment could abrogate resistance to anti-EGFR therapies by preventing reactivation of ErbB3. We observed that an EGFR mutant lung cancer cell line (HCC827), made resistant to gefitinib by exogenous heregulin, was resensitized by MM-121. In addition, we found that a de novo lung cancer mouse model induced by EGFR T790M-L858R rapidly became resistant to cetuximab. Resistance was associated with an increase in heregulin expression and ErbB3 activation. However, concomitant cetuximab treatment with MM-121 blocked reactivation of ErbB3 and resulted in a sustained and durable response. Thus, these results suggest that targeting ErbB3 with MM-121 can be an effective therapeutic strategy for cancers with ligand-dependent activation of ErbB3.

Therapeutically targeting ErbB3: a key node in ligand-induced activation of the ErbB receptor-PI3K axis.

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.