Targeting of Suppressive Myeloid Cells via Small Molecule Immunomodulators Erin M Kischuk 10.25394/PGS.9778562.v1 https://hammer.purdue.edu/articles/thesis/Targeting_of_Suppressive_Myeloid_Cells_via_Small_Molecule_Immunomodulators/9778562 Suppressive myeloid cells including myeloid-derived suppressor cells (MDSC) and tumor-associated macrophages (TAM), are a significant barrier to cancer immunotherapy. These cells enhance tumor growth and metastasis and promote immune escape by suppressing the anti-tumor T cell response. One of the key mechanisms of suppression is the production of nitric oxide (NO) via iNOS which leads to the modification and inactivation of various proteins involved in T cell effector function. Previous efforts to control suppressive myeloid cells have included direct elimination, blockade of accumulation or function at the tumor site, and conversion to an anti-tumor phenotype. Unfortunately, though several strategies have been tested in preclinical models and in clinical trials, there are currently no approved and effective therapies that are selective for these cells. The discovery of new drugs for these cells is hampered by the limited availability of primary cells for screening. The studies herein describe efforts to develop effective immunotherapies that target suppressive myeloid cells more specifically. Using a specific receptor, FRĪ², combined with photodynamic therapy we were able to deplete MDSC and TAM from solid tumors. This strategy limits the cytotoxic effects to the target cells within the tumor site. We also pursued a strategy of targeting accumulation and/or suppressive function via testing of GCL.2, a compound expected to reduce the accumulation of MDSC at the tumor site. Finally, we targeted the NO production pathway using synthetic small molecules. Importantly, we did not target iNOS directly but utilized a computer-based model that analyzed the interactions of compounds with a large set of putatively overexpressed targets in suppressive MDSC. Experimental data was integrated into the model to refine additional selections. With this approach, we were able to identify several hit compounds and verified the immunomodulatory activity of one compound <i>in vivo</i>. These studies demonstrate that targeting the suppressive phenotype is a viable approach to cancer immunotherapy, and we have also validated a novel approach to drug discovery for suppressive myeloid cells. 2019-10-16 19:09:17 MDSC machine Learning Predictions immunomodulatory Cellular Immunology