Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway, OncoImmunology (2021)
2021.12.02Journal Title : OncoImmunology (2021)
Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway.
Jeong Hun Kim [1], Won Suk Lee [2], Hye Jin Lee[3], Hannah Yang[4], Seung Joon Lee[5], so Jung Kong[6], Soyeon Je[7] , Hyun-Jin Yang[8] , Jongsun Jung[9] , Jaekyung Cheon[10], Beodeul Kang[11], Hong Jae Chon[12], and Chan Kim[13]
[1] [2] [3] [4] [5] [6] [10] [11] [12] [13] CHA Bundang Medical Center, Korea
[7] [8] [9] Syntekabio Inc, Korea
Abstract
Kynurenine (Kyn) is a key inducer of an immunosuppressive tumor microenvironment (TME). Although indoleamine 2,3-dioxygenase (IDO)-selective inhibitors have been developed to suppress the Kyn pathway, the results were not satisfactory due to the presence of various opposing mechanisms. Here, we employed an orally administered novel Kyn pathway regulator to overcome the limitation of anti-tumor immune response. We identified a novel core structure that inhibited both IDO and TDO. An orally available lead compound, STB-C017 (designated hereafter as STB), effectively inhibited the enzymatic and cellular activity of IDO and TDO in vitro. Moreover, it potently suppressed Kyn levels in both the plasma and tumor in vivo. STB monotherapy increased the infiltration of CD8+ T cells into TME. In addition, STB reprogrammed the TME with widespread changes in immune-mediated gene signatures. Notably, STB-based combination immunotherapy elicited the most potent anti-tumor efficacy through concurrent treatment with immune checkpoint inhibitors, leading to complete tumor regression and long-term overall survival. Our study demonstrated that a novel Kyn pathway regulator derived using deep learning technology can activate T cell immunity and potentiate immune checkpoint blockade by overcoming an immunosuppressive TME.
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