ABSTRACT: Advanced-stage endometrial cancer patients typically receive a combination of platinum and paclitaxel chemotherapy. However, limited treatment options are available for those with recurrent disease, and there is a need to identify alternative treatment options for the advanced setting. Our goal was to evaluate the pre-clinical efficacy and mechanism of action of the anti-cancer drug Oklahoma Nitrone 007 (OKN-007) alone and in combination with carboplatin and paclitaxel in endometrial cancer. The effect of OKN-007 on the metabolic viability of endometrial cancer cells in both two- and three-dimensional (2D and 3D) cultures, as well as on clonogenic growth, in vitro was assessed. We also evaluated OKN-007 in vivo using an intraperitoneal xenograft model and targeted gene expression profiling to determine the molecular mechanism and gene expression programs altered by OKN-007. Our results showed that endometrial cancer cells were generally sensitive to OKN-007 in both 2D and 3D cultures. OKN-007 displayed a reduction in 3D spheroid and clonogenic growth. Subsequent targeted gene expression profiling revealed that OKN-007 significantly downregulated the immunosuppressive immunometabolic regulatory enzyme indolamine 2,3-dioxygenase 1 (IDO1) (-11.27-fold change) and modulated upstream inflammatory pathways that regulate IDO1 expression (interferon- (IFN-), Jak-STAT, TGF-β, and NF-kB), downstream IDO1 effector pathways (mTOR and aryl hydrocarbon receptor (AhR)) and altered T-cell co-signaling pathways. OKN-007 treatment reduced IDO1, SULF2, and TGF-β protein expression in vivo, and inhibited TGF-β, NF-kB, and AhR- receptor-mediated nuclear signaling in vitro. These findings indicate that OKN-007 surmounts pro-inflammatory, immunosuppressive, and pro-tumorigenic pathways and is a promising approach for the effective treat endometrial cancer. Targeted mRNA expression profiling was performed using the nCounter ® Tumor Signaling 360™ Panel (NanoString Technologies), which comprises 780 genes involved in cancer-related pathways and internal reference genes. Raw data were normalized and log2 transformed using the geNorm algorithm, differential expression (DE) was determined using the Generalized Linear Model (GLM), and Gene Set Analysis (GSA) was used to summarize the directed global significance score by calculating the change in regulation within each defined gene set relative to the baseline. Pathway enrichment was also calculated for gene sets as defined in multiple databases, including WikiPathways, REACTOME, MSigDB, and Gene Ontology, and FDR adjustment and p-Elim pruning scores were calculated when appropriate. DE, GSA, and other pathway enrichment were conducted using ROSALIND software (v. 3.38.5.1). Genes with >1.5-or <1.5-fold change at P < 0.05 were considered significantly differentially expressed.
