Abstract LB-196: Image-based analysis of the interplay between myeloid cells and tumor cells in a 3D co-culture assay
Authors: Goverse Gera , Beztsinna Nataliia , Yan Kuan , Guelen Lars , Vink Paul , Price Leo , Daszkiewicz Lidia 
Published: August 2019

Abstract
BACKGROUND The myeloid cell compartment plays an important role in anti-tumor immune responses and represents a heterogeneous population with both cancer-promoting and cancer-restraining actions. Unleashing the full potential of cancer immunotherapies requires an understanding of the cellular mechanisms that govern these opposite actions. To date, high throughput relevant preclinical models for dissecting the interactions between different cellular players in the tumor microenvironment are lacking. Previously we have shown that a 3D image-based co-culture system allows assessing the efficacy of immune modulators that aim to enhance PBMC infiltration and tumoroid killing. Here, further improvements to the model are depicted. More specifically, we incorporated different myeloid cell populations to have a better representation of the human immune system in the tumor microenvironment (TME). In house developed software was trained on a set of features that enabled discrimination between undifferentiated monocytes, M1 and M2 macrophages and dendritic cells in 3D. Subsequently, these different myeloid subsets were co-cultured with tumoroids to analyze the complex cellular interactions that occur in the TME. This assay therefore offers the possibility to test cancer immunotherapies that target multiple cell types involved in anti-tumor immune responses and general modulation of suppressive tumor environment.
MATERIAL and METHODS Different myeloid populations were generated in 3D from monocytes derived from healthy donor PBMCs. Polarized M1 and M2 macrophages, DCs and undifferentiated monocytes were then co-cultured with spheroids derived from the SUM-149 breast cancer cell line, growing in protein hydrogel. The cellular interactions were visualized using high-content microscopy and quantified with multiparametric morphometric analysis with OMinerTM software.
RESULTS Using 3D image analysis different myeloid cells were distinguished from each other based on phenotypic measurements. In addition, our analysis enabled the discrimination of immune-tumor cell interactions and revealed the different effects of myeloid cells on tumor growth in co-culture. On the other hand, this approach also analyzes the tumor-driven mechanisms that can regulate myeloid cell differentiation and contribute to the immunosuppressive microenvironment, and can be used to study drug candidates targeting myeloid cells to promote tumor killing.
CONCLUSIONS The 3D assay presented here enables visualization and quantification of effects of immunotherapies on myeloid cells using morphological measurements. This co-culture system provides means to elucidate the bi-directional interplay between tumor and immune cells, allowing for analysis of functional reprograming of the suppressive population towards a M1 phenotype induced by drug candidates. This advanced platform for testing cancer immunotherapies also combines the complexity of the TME with the robustness of a high throughput screening platform.
Citation Format: Gera Goverse, Nataliia Beztsinna, Kuan Yan, Lars Guelen, Paul Vink, Leo Price, Lidia Daszkiewicz. Image-based analysis of the interplay between myeloid cells and tumor cells in a 3D co-culture assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-196.