Abstract A30: Predictive and pharmacodynamic biomarkers of vantictumab (OMP-18R5; anti-Frizzled) in non-small cell lung cancer (2015)

Abstract Background: Vantictumab is a monoclonal antibody that blocks canonical WNT/β-catenin signaling through binding of five FZD receptors (1, 2, 5, 7, 8). This antibody inhibits the growth of several tumor types, reduces tumor-initiating cell frequency (TIC) and exhibits synergistic activity with standard-of-care (SOC) chemotherapeutic agents (Gurney et al., 2012). To target responsive patients and understand the mechanism of action of the drug, we set out to identify predictive and pharmacodynamic (PD) biomarkers of vantictumab in non-small cell lung cancer (NSCLC). Materials and methods: The response to vanticutmab was established from in vivo efficacy experiments including different treatment groups: control, vantictumab, paclitaxel and vantictumab in combination with paclitaxel. For combination treatment, same day dosing and sequential dosing (paclitaxel dosed 2 days after the antibody) were compared. Samples were collected for PD biomarker analysis. To identify a predictive biomarker for the response to vantictumab in NSCLC patients, gene expression data from 7 NSCLC patient derived xenograft (PDX) models was analyzed. We utilized support vector machine-recursive feature elimination (SVM-RFE, Guyon et al., 2002) to select genes and support vector machine (SVM) for classification. Results: Vantictumab showed significant tumor growth inhibition as a single agent as well as in combination with paclitaxel. The reduction of TIC and the antitumor efficacy of vantictumab were significantly enhanced with sequential dosing compared with same day dosing. These findings suggested that optimal synergy occurs using sequential dosing, likely due to enhanced blockade of cell cycle progression at mitosis. PD biomarker analysis confirmed inhibition of genes in Wnt, Notch, and stem cell pathways by vantictumab both as a single agent and also in combination with paclitaxel. Wnt pathway targets including AXIN2 and LEF1 were down-regulated significantly by vantictumab in both sequential dosing and same day dosing confirming the mechanism of action. From a series of 7 in vivo efficacy PDX experiments, LEF1 was identified as a predictive biomarker of vantictumab response and achieved the best performance with cross-validated positive predictive value (PPV) = negative predictive value (NPV) = sensitivity = specificity = 100%. Strong correlation was also observed between LEF1 gene expression and the ratio of tumor volume. Furthermore, LEF1 was able to successfully predict the response to vantictumab in 2 independent NSCLC PDX models. Prevalence estimation for LEF1 ranged from 35% to 50% based on public microarray datasets. LEF1 was also found to be significantly correlated with the response to vantictumab in combination with paclitaxel in 12 NSCLC PDX models (p = 0.0162), indicating LEF1 as a potential predictive biomarker of the response vantictumab as a single agent and in combination with SOC in NSCLC. Conclusions: A biomarker study for the pharmacodynamics and response to vantictumab was performed using a series of PDX NSCLC models. PD biomarkers were identified which confirmed the mechanism of action of vantictumab. LEF1 was identified as a predictive biomarker and is being evaluated in the Phase 1b study of vantictumab in combination with SOC in previously treated NSCLC: NCT01957007. Comprehensive PD and predictive biomarker data will be presented. Citation Format: CHUN ZHANG, Fiore Cattaruzza, Pete Yeung, Wan-Ching Yen, Marcus Fischer, Alayne Brunner, Min Wang, Belinda Cancilla, Rainer Brachmann, Tim Hoey, John Lewicki, Ann M. Kapoun. Predictive and pharmacodynamic biomarkers of vantictumab (OMP-18R5; anti-Frizzled) in non-small cell lung cancer. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr A30.