Antje Walz

Targeting tumor-associated macrophages with anti-CSF-1R antibody reveals a strategy for cancer therapy

Macrophage infiltration has been identified as an independent poor prognostic factor in several cancer types. The major survival factor for these macrophages is macrophage colony-stimulating factor 1 (CSF-1). We generated a monoclonal antibody (RG7155) that inhibits CSF-1 receptor (CSF-1R) activation. In vitro RG7155 treatment results in cell death of CSF-1-differentiated macrophages. In animal models, CSF-1R inhibition strongly reduces F4/80(+) tumor-associated macrophages accompanied by an increase of the CD8(+)/CD4(+) T cell ratio. Administration of RG7155 to patients led to striking reductions of CSF-1R(+)CD163(+) macrophages in tumor tissues, which translated into clinical objective responses in diffuse-type giant cell tumor (Dt-GCT) patients.

Preclinical Optimization of MDM2 Antagonist Scheduling for Cancer Treatment by Using a Model-Based Approach

Purpose: Antitumor clinical activity has been demonstrated for the MDM2 antagonist RG7112, but patient tolerability for the necessary daily dosing was poor. Here, utilizing RG7388, a second-generation nutlin with superior selectivity and potency, we determine the feasibility of intermittent dosing to guide the selection of initial phase I scheduling regimens. Experimental Design: A pharmacokinetic–pharmacodynamic (PKPD) model was developed on the basis of preclinical data to determine alternative dosing schedule requirements for optimal RG7388-induced antitumor activity. This PKPD model was used to investigate the pharmacokinetics of RG7388 linked to the time-course of the antitumor effect in an osteosarcoma xenograft model in mice. These data were used to prospectively predict intermittent and continuous dosing regimens, resulting in tumor stasis in the same model system. Results: RG7388-induced apoptosis was delayed relative to drug exposure with continuous treatment not required. In initial efficacy testing, daily dosing at 30 mg/kg and twice a week dosing at 50 mg/kg of RG7388 were statistically equivalent in our tumor model. In addition, weekly dosing of 50 mg/kg was equivalent to 10 mg/kg given daily. The implementation of modeling and simulation on these data suggested several possible intermittent clinical dosing schedules. Further preclinical analyses confirmed these schedules as viable options. Conclusion: Besides chronic administration, antitumor activity can be achieved with intermittent schedules of RG7388, as predicted through modeling and simulation. These alternative regimens may potentially ameliorate tolerability issues seen with chronic administration of RG7112, while providing clinical benefit. Thus, both weekly (qw) and daily for five days (5 d on/23 off, qd) schedules were selected for RG7388 clinical testing. Clin Cancer Res; 20(14); 3742–52. ©2014 AACR.

Recent developments in using mechanistic cardiac modelling for drug safety evaluation

Highlights • Modelling and simulation can streamline decision making in drug safety testing.• Computational cardiac electrophysiology is a mature technology with a long heritage.• There are many challenges and opportunities in using in silico techniques in future.• We discuss how models can be used at different stages of drug discovery.• CiPA will combine screening platforms, human cell assays and in silico predictions.

First-in-human phase I clinical trial of RG7356, an anti-CD44 humanized antibody, in patients with advanced, CD44-expressing solid tumors

Transmembrane glycoprotein CD44 is overexpressed in various malignancies. Interactions between CD44 and hyaluronic acid are associated with poor prognosis, making CD44 an attractive therapeutic target. We report results from a first-in-human phase I trial of RG7356, a recombinant anti-CD44 immunoglobulin G1 humanized monoclonal antibody, in patients with advanced CD44-expressing solid malignancies. Sixty-five heavily pretreated patients not amenable to standard therapy were enrolled and received RG7356 intravenously biweekly (q2w) or weekly (qw) in escalating doses from 100 mg to 2,250 mg. RG7356 was well tolerated. Most frequent adverse events were fever, headache and fatigue. Dose-limiting toxicities included headache (1,500 mg q2w and 1,350 mg qw) and febrile neutropenia (2,250 mg q2w). The maximum tolerated dose with q2w dosing was 1,500 mg, but was not defined for qw dosing due to early study termination. Clinical efficacy was modest; 13/61 patients (21%) experienced disease stabilization lasting a median of 12 (range, 6–35) weeks. No apparent dose- or dose schedule-dependent changes in biological activity were reported from blood or tissue analyses. Tumor-targeting by positron emission tomography (PET) using 89Zr-labeled RG7356 was observed for doses ≥200 mg (q2w) warranting further investigation of this agent in combination regimens.

Influence of molecular size on tissue distribution of antibody fragments

Biodistribution coefficients (BC) allow estimation of the tissue concentrations of proteins based on the plasma pharmacokinetics. We have previously established the BC values for monoclonal antibodies. Here, this concept is extended by development of a relationship between protein size and BC values. The relationship was built by deriving the BC values for various antibody fragments of known molecular weight from published biodistribution studies. We found that there exists a simple exponential relationship between molecular weight and BC values that allows the prediction of tissue distribution of proteins based on molecular weight alone. The relationship was validated by a priori predicting BC values of 4 antibody fragments that were not used in building the relationship. The relationship was also used to derive BC50 values for all the tissues, which is the molecular weight increase that would result in 50% reduction in tissue uptake of a protein. The BC50 values for most tissues were found to be ~35 kDa. An ability to estimate tissue distribution of antibody fragments based on the BC vs. molecular size relationship established here may allow better understanding of the biologics concentrations in tissues responsible for efficacy or toxicity. This relationship can also be applied for rational development of new biotherapeutic modalities with optimal biodistribution properties to target (or avoid) specific tissues.

Translational PK/PD modeling to increase probability of success in drug discovery and early development

In this review we present ways in which translational PK/PD modeling can address opportunities to enhance probability of success in drug discovery and early development. This is achieved by impacting efficacy and safety-driven attrition rates, through increased focus on the quantitative understanding and modeling of translational PK/PD. Application of the proposed principles early in the discovery and development phases is anticipated to bolster confidence of successfully evaluating proof of mechanism in humans and ultimately improve Phase II success. The present review is centered on the application of predictive modeling and simulation approaches during drug discovery and early development, and more specifically of mechanism-based PK/PD modeling. Case studies are presented, focused on the relevance of M&S contributions to real-world questions and the impact on decision making.

Model-based assessment of erlotinib effect in vitro measured by real-time cell analysis

Real time cell analysis (RTCA) is an impedance-based technology which tracks various living cell characteristics over time, such as their number, morphology or adhesion to the extra cellular matrix. However, there is no consensus about how RTCA data should be used to quantitatively evaluate pharmacodynamic parameters which describe drug efficacy or toxicity. The purpose of this work was to determine how RTCA data can be analyzed with mathematical modeling to explore and quantify drug effect in vitro. The pharmacokinetic-pharmacodynamic erlotinib concentration profile predicted by the model and its effect on the human epidermoïd carcinoma cell line A431 in vitro was measured through RTCA output, designated as cell index. A population approach was used to estimate model parameter values, considering a plate well as the statistical unit. The model related the cell index to the number of cells by means of a proportionality factor. Cell growth was described by an exponential model. A delay between erlotinib pharmacokinetics and cell killing was described by a transit compartment model, and the effect potency, by an Emax function of erlotinib concentration. The modeling analysis performed on RTCA data distinguished drug effects in vitro on cell number from other effects likely to modify the relationship between cell index and cell number. It also revealed a time-dependent decrease of erlotinib concentration over time, described by a mono-exponential pharmacokinetic model with nonspecific binding.

Abstract PR04: Targeting tumor-asoociated macrophages with a novel anti-CSF1R antibody in cancer patients

Myeloid cells represent the most abundant immune cell type within the tumor microenvironment of certain tumor entities, including tumor associated macrophages (TAMs). Macrophage infiltration has been identified as an independent poor prognostic factor in several cancer types. The major survival factor for TAMs is macrophage colony stimulating factor 1 (CSF1). We generated a monoclonal antibody (RG7155) that binds to the secondary dimerization interface of CSF1 receptor (CSF1R) as a specific and potent allosteric inhibitor. In vitro, RG7155 treatment results in cell death of CSF1-differentiated macrophages. In animal models, CSF1R inhibition reduced the F4/80+ TAMs infiltrate by 90% and was accompanied by an increase of the CD8+/CD4+ T cell ratio. The ability of RG7155 to reduce TAMs is currently evaluated in a first-in-man phase I clinical study in patients suffering either from pigmented villonodular synovitis (PVNS), a neoplastic disorder characterized by CSF1 overexpression, or other tumor entities. The associated biomarker program involves mandatory paired pre- and on-treatment biopsies of tumor and surrogate skin tissue as well as pharmacodynamic marker assessment in circulating blood. In patients treated with RG7155 an increase of CSF1 associated with a sustained decrease of CD14+CD16+ alternatively activated monocytes in peripheral blood was detected. In PVNS patients administration of RG7155 led to striking reductions of CSF1R+ and CD163+ macrophages in tumor tissue resulting in objective clinical responses according to RECIST (Response Evaluation Criteria in Solid Tumors) in 5 out of 6 patients. All six evaluable PVNS patients showed partial metabolic response in FDG-PET imaging and significant symptomatic improvement as early as 4 weeks after treatment initiation. Furthermore, TAM reduction was also observed in paired tumor samples of patients with various advanced solid malignancies, suggesting broad applicability of this therapeutic approach. This abstract is also presented as Poster A50. Citation Format: Michael Cannarile, Sabine Hoves, Ann-Marie Broeske, Joerg Benz, Katharina Wartha, Valeria Runza, Flora Rey-Giraud, Leon P. Pradel, Friedrich Feuerhake, Irina Klaman, Tobin Jones, Ute Jucknischke, Stefan Scheiblich, Ingo H. Gorr, Antje Walz, Keelara Abiraj, Philippe Cassier, Antonio Sica, Carlos Gomez-Roca, Christophe Le Tourneau, Jean-Pierre Delord, Antoine Italiano, Hyam Levitsky, Jean-Yves Blay, Dominik Ruettinger, Carola H. Ries. Targeting tumor-asoociated macrophages with a novel anti-CSF1R antibody in cancer patients. [abstract]. In: Abstracts: AACR Special Conference on Cellular Heterogeneity in the Tumor Microenvironment; 2014 Feb 26-Mar 1; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(1 Suppl):Abstract nr PR04. doi:10.1158/1538-7445.CHTME14-PR04

Abstract B55: Antitumor activity of the MDM2 antagonist RG7388.

The p53 tumor suppressor is a transcription factor that inhibits tumor development by inducing cell cycle arrest or apoptosis in response to diverse stresses. In normal cells, p53 levels are tightly controlled by MDM2 which binds p53 and negatively regulates its activity and stability. MDM2 is overproduced in many human cancers, thereby impairing p53 function. Antagonists of p53-MDM2 interaction can reactivate p53 and offer a novel approach to cancer therapy. The first potent and selective small-molecule inhibitors of p53-MDM2 binding, the nutlins, provided preclinical proof-of-concept for MDM2 antagonists as therapeutics for patients with tumors expressing wild-type p53. Subsequently, a member of the nutlin family, RG7112, was the first small molecule inhibitor of MDM2 to be tested clinically. Here we describe, RG7388, a highly optimized agent with analogous mechanism of action representing an entirely new branch of the nutlin family of MDM2 antagonists. Like RG7112, RG7388 binds selectively to the p53 site on the surface of the MDM2 molecule, effectively displacing p53 from MDM2, and leading to p53 stabilization and activation of the p53 pathway. However, RG7388 is derived from a distinct chemical series that binds with higher potency and selectivity to the MDM2 protein. RG7388 has substantially improved pharmacological properties, resulting in superior preclinical efficacy at lower doses and exposures as compared with its predecessor, RG7112. RG7388 elicits growth arrest and apoptosis at approximately 10-fold lower concentrations in vitro and in vivo, has an improved CYP inhibition profile, and a 2.5- to 20-fold lower projected human efficacious dose as compared with RG7112. Tumors with functional p53 signaling and MDM2 over-expression or amplification are likely to be the most sensitive to RG7388, however preclinical studies indicate that tumors with normal MDM2 levels may also respond to this novel therapeutic strategy. Results from preclinical safety and toxicology studies support further exploration of this compound in cancer patients. RG7388 is a promising agent that may offer a new therapeutic option and is currently in clinical testing in both solid and hematologic malignancies. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):B55. Citation Format: Brian Higgins, Christian Tovar, Kelli Glenn, Antje Walz, Zoran Filipovic, Yu-E Zhang, Markus Dangl, Bradford Graves, Lyubomir Vassilev, Kathryn Packman. Antitumor activity of the MDM2 antagonist RG7388. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr B55.