ioAVATAR

Immune checkpoint inhibitors (ICI) have revolutionized the treatment of cancer, but unfortunately ovarian cancer (OC) represents an entity in which the success of T cell-based ICI have so far remained limited. However, the innate immune system, in particular tumor-associated macrophages (TAMs) and dendritic cells (DCs), represents a novel and encouraging therapeutic target to be explored in the context of OC. TAMs build up the majority of cells in the tumor microenvironment (TME) and have the advantage over T cells of being quickly recruited into the tissue, not requiring antigen presentation for activation and having high plasticity.
Our preliminary research data shows that i) particularly immunosuppressive (M2-like) macrophages and DCs are found in the OC tissue and ascites of the patients, and ii) targeting of different myeloid checkpoints significantly affects anti-OC phagocytosis, cytotoxicity and T cell activation. However, adequate models that reflect the complex network of cellular interactions in the TME of OC patients and that are suitable for validating combined immunotherapeutic approaches are currently lacking. Therefore, our primary aim is to develop patient AVATARs, complex ex vivo models that twins the pathophysiological escape mechanisms in OC patients. We will use two different approaches: fluidic organ-on-chip models and tissue slice cultures. The secondary aim will be to test novel immune oncology (IO) drug combinations on TAMs and DCs in this model based on existing and own preliminary data, and also in combination with established T cell immunotherapies (IT). Additionally, assessment of baseline and post-treatment immune profiles based on flow cytometry, single cell/bulk RNAseq, in situ multi-immunofluorescence and spatial transcriptomics will be performed on selected samples and IO drug combinations. Using these OMICs data and bioinformatics, the third aim of the study is to comprehensively investigate the effects of combined myeloid T cell IO drug strategies on the tumor-immune cell interactions in our ioAVATARs.
The overall goal of ioAVATAR is to establish a reliable ex vivo model to identify and validate, in a complex network, multi-specific combination therapies that synergistically generate effective and sustained immunity against OC carcinogenesis, with a particular focus on TAMs and DCs. Long term goals are to translate the most promising IO drug combinations into the clinic and to develop a patient avatar model that can be used in the clinical setting for personalized response prediction to IO drugs. By using antibodies that are already implemented in clinical trials, we expect that translation into the clinic is feasible.
The ioAVATAR multidisciplinary consortium's strengths in clinical oncology, immunology and bioinformatics offer a clear perspective for the implementation of new fast line ioAVATAR models to test multi-specific IT strategies with a clinical application as the ultimate goal of our mission.