Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway

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 empl...

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Autores principales: Jeong Hun Kim, Won Suk Lee, Hye Jin Lee, Hannah Yang, Seung Joon Lee, so Jung Kong, Soyeon Je, Hyun-Jin Yang, Jongsun Jung, Jaekyung Cheon, Beodeul Kang, Hong Jae Chon, Chan Kim
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Publicado: Taylor & Francis Group 2021
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Acceso en línea:https://doaj.org/article/b79d3c54e4ff44589373a0cee089c2d6
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spelling oai:doaj.org-article:b79d3c54e4ff44589373a0cee089c2d62021-12-01T14:40:59ZDeep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway2162-402X10.1080/2162402X.2021.2005280https://doaj.org/article/b79d3c54e4ff44589373a0cee089c2d62021-01-01T00:00:00Zhttp://dx.doi.org/10.1080/2162402X.2021.2005280https://doaj.org/toc/2162-402XKynurenine (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.Jeong Hun KimWon Suk LeeHye Jin LeeHannah YangSeung Joon Leeso Jung KongSoyeon JeHyun-Jin YangJongsun JungJaekyung CheonBeodeul KangHong Jae ChonChan KimTaylor & Francis Grouparticlekynurenine pathwaytumor microenvironmentindoleamine 23-dioxygenasedeep learning technologyImmunologic diseases. AllergyRC581-607Neoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENOncoImmunology, Vol 10, Iss 1 (2021)
institution DOAJ
collection DOAJ
language EN
topic kynurenine pathway
tumor microenvironment
indoleamine 2
3-dioxygenase
deep learning technology
Immunologic diseases. Allergy
RC581-607
Neoplasms. Tumors. Oncology. Including cancer and carcinogens
RC254-282
spellingShingle kynurenine pathway
tumor microenvironment
indoleamine 2
3-dioxygenase
deep learning technology
Immunologic diseases. Allergy
RC581-607
Neoplasms. Tumors. Oncology. Including cancer and carcinogens
RC254-282
Jeong Hun Kim
Won Suk Lee
Hye Jin Lee
Hannah Yang
Seung Joon Lee
so Jung Kong
Soyeon Je
Hyun-Jin Yang
Jongsun Jung
Jaekyung Cheon
Beodeul Kang
Hong Jae Chon
Chan Kim
Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway
description 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.
format article
author Jeong Hun Kim
Won Suk Lee
Hye Jin Lee
Hannah Yang
Seung Joon Lee
so Jung Kong
Soyeon Je
Hyun-Jin Yang
Jongsun Jung
Jaekyung Cheon
Beodeul Kang
Hong Jae Chon
Chan Kim
author_facet Jeong Hun Kim
Won Suk Lee
Hye Jin Lee
Hannah Yang
Seung Joon Lee
so Jung Kong
Soyeon Je
Hyun-Jin Yang
Jongsun Jung
Jaekyung Cheon
Beodeul Kang
Hong Jae Chon
Chan Kim
author_sort Jeong Hun Kim
title Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway
title_short Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway
title_full Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway
title_fullStr Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway
title_full_unstemmed Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway
title_sort deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway
publisher Taylor & Francis Group
publishDate 2021
url https://doaj.org/article/b79d3c54e4ff44589373a0cee089c2d6
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