Abstract A003: Identification of immunomodulatory compounds by high-throughput proteomics: Insights from quantification of 1000 proteins in a 20,000 sample screen

Abstract The identification of novel cancer immunotherapies and the characterization of their immunomodulatory effects is complicated by the plasticity of immune cells and the wide range of phenotypes they may adopt. However, the high cost of capturing this diversity at scale limits typical drug discovery efforts to simple readouts, such as cell killing, or the expression of individual cytokines. We previously described the Nomic platform, a proteomics tool capable of quantifying thousands of proteins at high-throughput and low cost. Here, we leverage the Nomic platform to screen a library of bioactive small molecules, characterize their immunomodulatory properties, and assess potential toxicities. We identified both expected and novel immune-regulating compounds, and captured in vitro signs of toxicity from therapies that failed clinical development due to dose-limiting toxicities, highlighting the power of our approach. To achieve this, we collected supernatants from hepatocytes, cardiomyocytes, and microglia treated with 510 compounds at three concentrations. We used Nomic’s Omni 1000 to measure 1,000 proteins across 20,000 samples, generating 20 million data points. Our dataset recapitulated the effects of control compounds such as corticosteroids, which reduced the expression of multiple cytokines while increasing the expression of SAA by hepatocytes, as well as TLR agonists, which dramatically increased the expression of TNFα, IL-12p40, IL-6, and several chemokines. Interestingly, 150 compounds (29%) displayed immunomodulatory properties, many of which were previously unreported. We simultaneously identified potential toxicities of the screened compounds, which was characterized by widespread decreases in protein levels in the supernatant, but increased levels of typically intracellular proteins such as CASP3, GAPDH, IRF3, TYMP, MAPK3, and eIF2a. We identified 68 cytotoxic compounds; of note, while most of these reduced cytokine expression, doxorubicin induced cytokine expression even at non-toxic doses, consistent with its reported pro-inflammatory properties. Other notable exceptions included the GSK-3 inhibitor LY2090314, and the BET inhibitor (+)-JQ1, which were toxic at higher doses, but induced the expression of distinct chemokines at lower doses. Based on the balance of toxicity and immunomodulation, we identified candidates for immunotherapy combinations. For example, the Met inhibitor PF-04217903 potently induced CXCL9-10 and IL-12 expression by hepatocytes, with no signs of toxicity. Considering that PF-04217903 was well tolerated in the clinic but was not pursued for strategic reasons, our results suggest potential for development in combination with checkpoint inhibitors for Met-driven tumors. Our results demonstrate the value of high-throughput proteomics to identify new immunomodulatory compounds and simultaneously characterize their safety profile. Citation Format: Nathaniel Robichaud, Alyssa Rosenbloom, Kiran Edwardson, Narges Rashidi, Milad Dagher. Identification of immunomodulatory compounds by high-throughput proteomics: Insights from quantification of 1000 proteins in a 20,000 sample screen abstract. In: Proceedings of the AACR Special Conference in Cancer Research: Mechanisms of Cancer Immunity and Cancer-related Autoimmunity; 2025 Sep 24-27; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(9 Suppl):Abstract nr A003.