We describe evidence for a novel mechanism of monoclonal antibody (MAb)-directed nanoparticle (immunoliposome) targeting to solid tumors in vivo. Long-circulating immunoliposomes targeted to HER2 (ErbB2, Neu) were prepared by the conjugation of anti-HER2 MAb fragments (Fab ¶ or single chain Fv) to liposome-grafted polyethylene glycol chains. MAb fragment conjugation did not affect the biodistribution or long-circulating properties of i.v.-administered liposomes. However, antibody-directed targeting also did not increase the tumor localization of immunoliposomes, as both targeted and nontargeted liposomes achieved similarly high levels (7-8% injected dose/g tumor tissue) of tumor tissue accumulation in HER2-overexpressing breast cancer xenografts (BT-474). Studies using colloidal gold-labeled liposomes showed the accumulation of anti-HER2 immunoliposomes within cancer cells, whereas matched nontargeted liposomes were located predominantly in extracellular stroma or within macrophages. A similar pattern of stromal accumulation without cancer cell internalization was observed for anti-HER2 immunoliposomes in non-HER2-overexpressing breast cancer xenografts (MCF-7). Flow cytometry of disaggregated tumors posttreatment with either liposomes or immunoliposomes showed up to 6-fold greater intracellular uptake in cancer cells due to targeting. Thus, in contrast to nontargeted liposomes, anti-HER2 immunoliposomes achieved intracellular drug delivery via MAb-mediated endocytosis, and this, rather than increased uptake in tumor tissue, was correlated with superior antitumor activity. Immunoliposomes capable of selective internalization in cancer cells in vivo may provide new opportunities for drug delivery.

Combinatorial control of biological processes, in which redundancy and multifunctionality are the norm, fundamentally limits the therapeutic index that can be achieved by even the most potent and highly selective drugs. Thus, it will almost certainly be necessary to use new 'targeted' pharmaceuticals in combinations. Multicomponent drugs are standard in cytotoxic chemotherapy, but their development has required arduous empirical testing. However, experimentally validated numerical models should greatly aid in the formulation of new combination therapies, particularly those tailored to the needs of specific patients. This perspective focuses on opportunities and challenges inherent in the application of mathematical modeling and systems approaches to pharmacology, specifically with respect to the idea of achieving combinatorial selectivity through use of multicomponent drugs.

The ErbB signaling pathways, which regulate diverse physiological responses such as cell survival, proliferation and motility, have been subjected to extensive molecular analysis. Nonetheless, it remains poorly understood how different ligands induce different responses and how this is affected by oncogenic mutations. To quantify signal flow through ErbB-activated pathways we have constructed, trained and analyzed a mass action model of immediate-early signaling involving ErbB1-4 receptors (EGFR, HER2/Neu2, ErbB3 and ErbB4), and the MAPK and PI3K/Akt cascades. We find that parameter sensitivity is strongly dependent on the feature (e.g. ERK or Akt activation) or condition (e.g. EGF or heregulin stimulation) under examination and that this context dependence is informative with respect to mechanisms of signal propagation. Modeling predicts log-linear amplification so that significant ERK and Akt activation is observed at ligand concentrations far below the K d for receptor binding. However, MAPK and Akt modules isolated from the ErbB model continue to exhibit switch-like responses. Thus, key system-wide features of ErbB signaling arise from nonlinear interaction among signaling elements, the properties of which appear quite different in context and in isolation.

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.

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. Cancer Res; 70(6); 2485-94. ©2010 AACR.

Tumor necrosis factor (TNF) is a proinflammatory cytokine that induces conflicting pro- and antiapoptotic signals whose relative strengths determine the extent of cell death. TNF receptor (TNFR) has been studied in considerable detail, but it is not known how crosstalk among antagonistic pro- and antiapoptotic signals is achieved. Here we report an experimental and computational analysis of crosstalk between prodeath TNF and prosurvival growth factors in human epithelial cells. By applying classifier-based regression to a cytokine-signaling compendium of approximately 8000 intracellular protein measurements, we demonstrate that cells respond to TNF both directly, via activated TNF receptor, and indirectly, via the sequential release of transforming growth factor-alpha (TGF-alpha), interleukin-1alpha (IL-1alpha), and IL-1 receptor antagonist (IL-1ra). We refer to the contingent and time-varying series of extracellular signals induced by TNF as an "autocrine cascade." Time-dependent crosstalk of synergistic and antagonistic autocrine circuits may serve to link cellular responses to the local environment.

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. Mol Cancer Ther; 11(3); 582-93. Ó2012 AACR.

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