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 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.

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.

Lessons learned from quantitative dynamical modeling in systems biology.

Due to the high complexity of biological data it is difficult to disentangle cellular processes relying only on intuitive interpretation of measurements. A Systems Biology approach that combines quantitative experimental data with dynamic mathematical modeling promises to yield deeper insights into these processes. Nevertheless, with growing complexity and increasing amount of quantitative experimental data, building realistic and reliable mathematical models can become a challenging task: the quality of experimental data has to be assessed objectively, unknown model parameters need to be estimated from the experimental data, and numerical calculations need to be precise and efficient.

Understanding the role of cross-arm binding efficiency in the activity of monoclonal and multispecific therapeutic antibodies.

Antibodies are essential components of the adaptive immune system that provide protection from extracellular pathogens and aberrant cells in the host. Immunoglobulins G, which have been adapted for therapeutic use due to their exquisite specificity of target recognition, are bivalent homodimers composed of two antigen binding Fab arms and an immune cell recruiting Fc module. In recent years significant progress has been made in optimizing properties of both Fab and Fc components to derive antibodies with improved affinity, stability, and effector function.

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.

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.

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.

Systems biologists seek fuller integration of systems biology approaches in new cancer research programs.

Systems biology takes an interdisciplinary approach to the systematic study of complex interactions in biological systems. This approach seeks to decipher the emergent behaviors of complex systems rather than focusing only on their constituent properties. As an increasing number of examples illustrate the value of systems biology approaches to understand the initiation, progression, and treatment of cancer, systems biologists from across Europe and the United States hope for changes in the way their field is currently perceived among cancer researchers.

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).

Directional persistence of EGF-induced cell migration is associated with stabilization of lamellipodial protrusions.

Migrating cells can sustain a relatively constant direction of lamellipodial protrusion and locomotion over timescales ranging from minutes to hours. However, individual waves of lamellipodial extension occur over much shorter characteristic times. Little understanding exists regarding how cells might integrate biophysical processes across these disparate timescales to control the directional persistence of locomotion.