Abstract P158: Phenotypic analysis of myeloid cells in a 3D image-based repolarization assay with tumor spheroids
Authors: Goverse Gera , Beztsinna Nataliia , Visser Benjamin , Veenendaal Tomas , van de Merbel Marjan , Spanjaard Emma , Weterings Ashgard , Yan Kuan , Price Leo , Daszkiewicz Lidia 
Published: December 2021

Abstract
Background The immunosuppressive tumor microenvironment (TME) involves multiple cell types and a better understanding of the interplay between these cells could potentially unleash the full potential of many different types of immunotherapies. Tumor infiltrating myeloid cells have both cancer-restraining and cancer-promoting functions. Therefore, to further increase the biological relevance of in vitro platform, we incorporated the myeloid cell compartment into 3D co-cultures of tumor cells and T cells to measure the effects of immune-modulators. Using our proprietary image analysis software and machine learning, a set of morphological features was identified that allowed discrimination between undifferentiated monocytes, M1 and M2 macrophages, and dendritic cells. In addition, the phenotypic profiles of the myeloid cells could be analyzed in the presence of the tumor supernatants or in co-cultures with tumor cells. This assay allows a better understanding of the suppressive tumor microenvironment including multiple cell types and is suitable to test different cancer immunotherapies. Materials and Methods Different myeloid cell populations were generated from healthy PBMCs. Polarized M1 and M2 macrophages, DCs, and undifferentiated monocytes were then co-cultured with tumor conditioned media, spheroids derived from different cancer cell lines, or colorectal cancer organoids (CRC), growing in protein hydrogel in 384 well-plates for 1-7 days. In addition, purified T cells were also incorporated in these cultures. The cellular interactions were visualized using high-content microscopy and OMiner® software, which was trained to identify phenotypic profiles of different myeloid cell populations in 3D, was used to quantify their similarity to the defined subsets upon treatment. Results Myeloid cell populations were classified according to their phenotypic features identified by 3D image analysis, which verified the repolarization of M2 macrophages by their shift into phenotypic space of the M1 type macrophages upon treatment with CSF1r inhibitor or STING agonist. Repolarization was confirmed with an increased similarity score towards M1 macrophages upon treatment. This approach was further used to reveal the different effects of tumor cells and their immunosuppressive TME on myeloid cell phenotypes, showing that each tumor differently influenced the repolarization of the myeloid cells. In addition, triple co-cultures with T cells revealed the suppressive effect of tumor associated myeloid cells on the proliferation and infiltration of T cells. Conclusions The phenotypic analysis of different myeloid cells in 3D co-cultures could be visualized and quantified elucidating the bi-directional interplay between tumor and immune cells, and the functional reprograming of the suppressive tumor associated population towards an M1 phenotype induced by drug candidates. This advanced platform for testing cancer immunotherapies combines the ability to examine the complexity of the TME with the robustness of a high-throughput screening platform.
Citation Format: Gera Goverse, Nataliia Beztsinna, Benjamin Visser, Tomas Veenendaal, Marjan van de Merbel, Emma Spanjaard, Ashgard Weterings, Kuan Yan, Leo Price, Lidia Daszkiewicz. Phenotypic analysis of myeloid cells in a 3D image-based repolarization assay with tumor spheroids [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P158.