Abstract Purpose: Although there are many well-defined signaling pathways in tumor cells that provide druggable targets, emergence of growth factor-mediated resistance and parallel pathway compensation frequently occurs, limiting the effectiveness of these treatment strategies. The purpose of this study was to model cancer cell responses to combinations of growth factors (ligands) and targeted investigational therapies in order to identify which signaling pathways are mechanistically related. The results presented here demonstrate the use of network biology-based phenotypic screening and modeling to reveal unexpected behaviors, identify positive and negative biomarkers, and guide novel treatment strategies. Methods: To assess the effect of ligands and RTK-directed antibodies in combination with targeted investigational therapies in cancer cells, we conducted a high throughput viability screen in 3D cultures. A library of 87 small molecules targeting different components of signaling and metabolic pathways was used in combination with growth factors and therapeutic antibodies. The therapeutic antibodies included in the screen were MM-121 (anti-ErbB3), MM-131 (anti-Met/EpCAM), MM-141 (anti-IGF-1R/ErbB3), and MM-151 (anti-EGFR). Using these data, we inferred a pathway connectivity model to identify pathway crosstalk and novel and effective combination strategies, which were then further evaluated in vitro and in mouse xenograft models. Results: Overall, we found that ligand-mediated resistance varies depending on the cancer type. For example, HGF and EGF play particularly strong roles in gastric and colorectal cancer cells, respectively. Interestingly, a few cases were found in which a ligand reduced cell viability compared to control, but this had no effect on drug response. In most cases where a ligand rendered cells insensitive to a certain drug treatment, a combination with the appropriately matched therapeutic antibody re-sensitized cells to the drug, suggesting that a combination strategy could potentially be used to overcome ligand-mediated resistance. Among the findings that were observed in multiple cell lines, MM-131 combined well with EGFR-directed agents in HGF responsive tumor cells, and MM-141 combined well with metformin in colorectal and lung cancer cell lines. These findings were further validated in vivo. Conclusions: Growth factors for EGFR, Met, ErbB3, and IGF-1R decrease sensitivity to a wide range of targeted investigational agents in cancer cell lines. These effects, however, are not general, but instead are dependent on the type of cancer cell being treated. Insights from this screen may help guide the future clinical development of MM-121, MM-131, MM-141 and MM-151. Citation Format: Kristina Masson, Andreas Raue, Gavin MacBeath. A network biology screen reveals ligand-receptor pathway connections and resistance mechanisms to RTK-directed therapies in cancer cells. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1199.
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