A 3D image-based quantification of immune cell-tumor spheroid interactions in the presence of checkpoint inhibition.

Abstract

82 Background: Delivering on the promises of cancer immunotherapy is hampered by a lack of in vitro testing platforms that enable the early selection of promising drugs candidates. While quantification of the number of cytotoxic T cells and IFNγ secretion can give an indication of the drug effect, it is often critical to assess the functional cytotoxicity and infiltration capacity. In addition, immunomodulatory effects of drug combinations need to be carefully assessed before these treatment modalities reach patients. However there are unlimited possibilities of new combinations, especially in the view of synergy effects observed with double checkpoint inhibition blockade and combination with standard of care drugs. To specifically address the needs of immunotherapy cancer drug developers, we developed robust assays that incorporate the human immune system into tumor spheroid cultures, with functional read-outs in a high throughput (384well plate) format. Methods: Breast cancer cells were grown in a hydrogel to form 3D tumoroids. HLA-matched PBMCs with and without pre-activation/exhaustion were added and the infiltration of T cells and subsequent tumoroid killing was quantified. The effect of immune checkpoint blockade was also assessed with the addition of pembrolizumab. Quantification of effects of stimulators and checkpoint inhibition was achieved with 3D imaging and morphometric analysis with OMiner software. Results: Automated 3D image and data analysis enabled discrimination of immune-tumour cell interactions depending on activation status of T cells. Activated T cells more efficiently infiltrated and killed tumoroids than non-activated ones. Cytotoxic activity of overactivated/exhausted T cells was supressed but this could be reversed by the presence of checkpoint inhibitor in the coculture. Conclusions: A 3D environment allows the different cell types to engage in a more realistic setting than when cells are grow in a monolayer. Using image-based analysis, immune-tumor interactions can be dissected. This represents a new, highly powerful tool for cancer immunotherapy drug developers to select the most promising compounds, allowing faster progression towards the clinic.