在功能基因组学和化合物筛选中对1000种分泌蛋白进行分析，揭示细胞毒性和免疫调节靶点

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. The Nomic platform is a novel proteomics tool capable of quantifying thousands of proteins at high-throughput and low cost, leveraged here in functional genomics and compound screens, simultaneously characterizing immunomodulatory and cytotoxic effects. We collected supernatants for secretome analysis from the CPJUMP1 dataset, in which U2OS osteosarcoma cells were perturbed with matched ORF, CRISPR KO, and compound libraries targeting 161 genes, and quantified 191 cytokines using a Nomic Flex panel. Overexpression of upstream kinases induced an inflammatory phenotype, consistent with established oncogene-induced inflammation. Furthermore, as seen in morphological analyses, CRISPR KO phenotypes were poorly matched with the phenotypes of compounds targeting corresponding genes due to poor specificity of compounds for individual targets. To further characterize on-target and off-target immunomodulatory effects of compounds, we quantified 1000 proteins in supernatants from hepatocytes treated with 510 compounds at three concentrations for 48h, using the Omni 1000. Cytotoxic compounds such as staurosporine resulted in intracellular proteins leaking out of cells and being detected in the supernatant, whereas resiquimod, a TLR7/8 agonist, induced the expression of a variety of cytokines. Clinically-relevant immunotoxicity was captured: thus, methylprednisolone was generally anti-inflammatory, but with paradoxical increases in SAA and IL-6, consistent with paradoxically inflammed livers seen in patients. Actinomycin D was cytotoxic while inducing IL-1b and TNFa, consistent with the immune contribution to this compound's anti-cancer properties. Finally, we demonstrated the capacity of secretome analysis to probe pathways regulating cytokine expression. For example, comparison of a set of 11 mTOR inhibitors identified on-target immune modulation and off target effects at increasing doses, enabling characterization of compound potency and specificity. Our results demonstrate the value of high-throughput proteomics to identify new immunomodulatory targets and compounds, evaluate potential toxicities, and characterize potency and specificity.