鲁索利替尼
癌症研究
生物
免疫检查点
骨髓纤维化
免疫疗法
免疫系统
免疫学
医学
骨髓
作者
Brett S. Marro,Jaroslav Žák,Isaraphorn Pratumchai,Luke L. Lairson,Michael B. A. Oldstone,John R. Teijaro
出处
期刊:Journal of Immunology
[American Association of Immunologists]
日期:2020-05-01
卷期号:204 (1_Supplement): 246.26-246.26
标识
DOI:10.4049/jimmunol.204.supp.246.26
摘要
Abstract Immune checkpoint blockade (ICB) therapy has emerged as viable first-line treatment for cancers such as melanoma. Despite the striking long-term clinical benefits that were previously unattainable, the effectiveness of ICB therapy remains limited in a majority of patients and cancer types. This is due in part to insufficient activation and/or restoration of anti-tumor T cell responses. Thus, understanding the signaling pathways that potentiate T cell exhaustion is essential for developing pharmacologic drugs that reactivate T cells and overcome the limitations of current ICB therapy. To this end, we developed a biologically relevant phenotypic screening system using the LCMV-CL13 infection model coupled with high-throughput flow cytometry to identify small-molecules that resurrect hypofunctional T cells. We discovered 19 hits following a screen of a manually curated collection of 12,000 repurposed drugs. Among the lead compounds identified were janus kinase (JAK) inhibitors including the anti-myelofibrosis drug ruxolitinib. Phenotypic rescue of exhausted T cells in vitro following ruxolitinib treatment resulted in a unique transcriptional signature that diverged from anti-PD-L1 treatment. Lineage-defining genes known to preserve precursor exhausted CD8+ T cells, including transcription factor 7 (Tcf7), were significantly upregulated following exposure to ruxolitinib. Mechanistically, ruxolitinib attenuated the cumulative pSTAT signaling signature within resurrected cells to enhance their survival. Collectively, these results demonstrate a disease-relevant framework for identifying small-molecule modulators of dysfunctional T cells and suggest that JAKs are viable targets for cancer immunotherapy.
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