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 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.

Overexpression and Selective Anticancer Efficacy of ENO3 in STK11 Mutant Lung Cancers.

Oncogenic gain-of-function mutations are clinical biomarkers for most targeted therapies, as well as represent direct targets for drug treatment. Although loss-of-function mutations involving the tumor suppressor gene, STK11 (LKB1) are important in lung cancer progression, STK11 is not the direct target for anticancer agents. We attempted to identify cancer transcriptome signatures associated with STK11 loss-offunction mutations. Several new sensitive and specific gene expression markers (ENO3, TTC39C, LGALS3, and MAML2) were identified using two orthogonal measures, i.e., fold change and odds ratio analyses of transcriptome data from cell lines and tissue samples. Among the markers identified, the ENO3 gene over-expression was found to be the direct consequence of STK11 loss-of-function. Furthermore, the knockdown of ENO3 expression exhibited selective anticancer effect in STK11 mutant cells compared with STK11 wild type (or recovered) cells. These findings suggest that ENO3 -based targeted therapy might be promising for patients with lung cancer harboring STK11 mutations.