Fig 1: Lesinurad, an SLC22 inhibitor suppressed IFN signaling and EMT in Mes cells and in combination with gemcitabine restrained tumor growth, and metastasis in mouse models of PDAC(A) Transport of [glycine-2-3H]-glutathione measured in the presence of SLC22 inhibitors (20 µM each) in Mes cells. Error bars, mean ± SD. n = 3 biological replicates for each condition was examined and three independent experiments were performed.(B) Structure of lesinurad.(C) Representative phase contrast images of the Mes cells treated with vehicle or lesinurad (20 µM) for 48 h. Scale bar, 50 µm n = 5 random fields from each condition was photographed and analyzed and data represent three independent experiments.(D) Western blots showing the protein expression of players in the IFN-STAT3-ROR1 signaling axis in Mes clones treated with indicated concentrations of lesinurad for 48 h ß-Actin was used as a loading control.(E) Western blots illustrating the protein expression of epithelial and mesenchymal markers in Mes clones treated with indicated concentrations of lesinurad for 48 h ß-Actin was used as a loading control. Data presented in (D and E) represent three independent experiments.(F) Design of an orthotopic mouse pancreatic tumor xenograft study conducted to evaluate the anti-tumor and antimetastatic abilities of gemcitabine and lesinurad alone and the combination of both drugs at the indicated doses detailed in the STAR Method section.(G) Quantification of weights of the primary tumors dissected from above groups of animals. Error bars, mean ± SEM. n = 5 mice per group; each point represents one animal.(H) Quantification of metastatic foci in the viscera and cavities from the above groups of animals. Tumor associated metastatic foci and lesions >1 mm3 were scored and included in the analysis. Error bars, mean ± SEM. n = 5 mice per group; each point represents total number of metastatic nodules quantified from one animal.(I) Design showing KPC mice study conducted to assess the efficacy of gemcitabine alone and in combination with lesinurad on survival, tumor growth, and metastasis.(J) Changes in individual tumor volumes at 6 (T1) and 12 weeks of age (T2) as determined by micro-CT imaging analyses. Animals that received gemcitabine alone (n = 5 tumors) versus the combination of gemcitabine + lesinurad (n = 7 tumors) are compared. Each line represents one tumor and the average change in the collective tumor volume is presented in lines with open circles. n = 3 KPC mice per group were monitored by micro-CT imaging for tumor burden.(K) Kaplan–Meier survival analysis showing the elapsed survival time of groups of KPC mice treated with saline (n = 12 mice), gemcitabine (n = 14 mice), or gemcitabine + lesinurad (n = 14 mice) at the indicated doses (detailed in STAR Method section) twice a week.(L) The incidence of metastasis in KPC mice enrolled in the saline (n = 12 mice), gemcitabine monotherapy (n = 14 mice), and gemcitabine + lesinurad groups (n = 14 mice), as determined by post-survival necropsy examination.(M) Model of the proposed mechanism of action of SLC22A10 and SLC22A15 in promoting EMT and pancreatic cancer progression.Data in (A) were analyzed by one-way ANOVA with Dunnett’s multiple comparisons test. Data in (G and H) were analyzed by one-way ANOVA with Tukey’s multiple comparisons test. Data in (J) were analyzed by two-way ANOVA with Sidak’s multiple comparisons test. For the data presented in (K), the differences in median overall survival times of KPC mice in different groups were analyzed using log rank (Mantel–Cox) test. Data presented in (L) were analyzed by Fisher’s exact test. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001; ns, not significant.
Fig 2: SLC22A10 and SLC22A15 transport glutathione that stimulates IFN-STAT3-ROR1 signaling and EMT(A) Heat maps depicting metabolites that are significantly altered in SLC22A10-OE (left panel) and SLC22A15-OE (right panel) clones compared with the vector-transduced clone, as determined by untargeted metabolomics utilizing LC-MS/MS in ESI + mode. Metabolites in bold are related and significantly increased in both SLC22A10- and SLC22A15-OE clones compared with the vector-transduced clone. n = 5 biological replicates and n = 3 technical replicates of each sample (pLV-Control, pLV-SLC22A10, and pLV-SLC22A15) were analyzed.(B–D) Levels of total cellular glutathione (GSH + GSSG), reduced glutathione (GSH), and oxidized glutathione (GSSG) in primary tumor tissues dissected from mice described in Figure 2 G. Error bars, mean ± SD. Tissues from n = 3 tumors for each condition was processed and assayed.(E) Transport of radiolabeled [glycine-2-3H]-glutathione was determined in PANC-1 cells transduced with control, SLC22A10, and SLC22A15 lentiviruses. Error bars, mean ± SD.(F) Transport of [glycine-2-3H]-glutathione in Mes cells transduced with scramble, shSLC22A10, and shSLC22A15 lentiviruses. Error bars, mean ± SD.(G) Transport of [glycine-2-3H]-glutathione in PANC-1 cells transduced with control, SLC22A10, and SLC22A15 lentiviruses or co-transduced with SLC22A10 and SLC22A15 lentiviruses. Cells were pretreated with BSO (100 µM) for 24 h before the transport study. GSSG (20 mM) was added to the transport buffer for the duration of transport period. Error bars, mean ± SD.(H) Transport of [glycine-2-3H]-glutathione in the presence of Na+-containing buffer at pH 7.4 or N-methyl-D-glucamine chloride (NMDG) buffer or HEPES buffered saline (HBS) or Na+-containing buffer at pH 5.5 in PANC-1 cells transduced with control, SLC22A10, and SLC22A15 lentiviruses. Error bars, mean ± SD.(I) Transport of [glycine-2-3H]-glutathione in PANC-1 cells transduced with control, SLC22A10, and SLC22A15 lentiviruses in the presence of 100 µM each of top differentially altered metabolites (identified from the metabolomic analysis of pLV-Control, pLV-SLC22A10, and pLV-SLC22A15 clones). For the data presented in (E-I), three biological replicates for each condition were tested and n = 3 independent experiments were performed.(J) Representative phase contrast images of PANC-1 cells treated with indicated concentrations of GSH for 48 h. Scale bar, 50 µm. Three random fields from each condition were photographed and analyzed. n = 3 independent experiments performed.(K) Western blots depicting the protein expression of epithelial and mesenchymal markers in PANC-1 cells treated with indicated concentrations of GSH for 6 h ß-Actin were used as a loading control. Western blots shown represent three independent experiments.(L) Western blots illustrating the protein expression of the markers of IFN-STAT3-ROR1 signaling axis in PANC-1 cells treated with increasing concentrations of GSH for 6 h ß-Actin were used as a loading control. Western blots shown represent three independent experiments.(M) Western blots assessing the protein expression of markers of the IFN-STAT3-ROR1 signaling axis in vector-transduced and SLC22A10- and SLC22A15-OE clones treated with the indicated concentrations of BSO and GSH. Cells were treated with BSO or vehicle for 24 h and followed by GSH or vehicle for 6 h ß-Actin was used as a loading control. Western blots represent at least three independent experiments.Data presented in (B–G) were analyzed by one-way ANOVA with Dunnett’s multiple comparisons test and data presented in (H and I) were analyzed by two-way ANOVA with Dunnett’s multiple comparisons test. *p < 0.05; **p < 0.01; ***p < 0.001; ns, not significant.
Fig 3: SLC22A10 and SLC22A15 induce ROR1 activation and EMT via IFN/STAT3 signaling pathway(A) Volcano plots demonstrating global transcriptional changes in SLC22A10- and SLC22A15-OE clones versus vector-transduced clone as determined by RNA-seq analysis. Each circular dot indicates one gene. X axis: log2 fold change; Y axis: logP-values. Highlighted genes inside rectangles are the most significantly differentially expressed genes in cells expressing SLC22A10 (left) and SLC22A15 (right).(B) Venn diagram showing the most significantly differentially expressed genes common to both SLC22A10- and SLC22A15-OE clones as unveiled by RNA-seq analysis.(C) mRNA levels of top genes most significantly differentially expressed in both SLC22A10- and SLC22A15-OE clones compared with the control clone. For the data presented in (A-C), n = 3 independent biological replicates of each sample were used for the RNA-seq.(D) Western blots showing protein expression of pROR1 (Tyr786), and ROR1 in control, SLC22A10-OE, and SLC22A15-OE clones in PANC-1 and HPAF-II cells. ß-Actin was used as a loading control. Western blots shown represent three independent experiments.(E) Representative phase contrast images of PANC-1 cells captured 72 h post-transduction with lentiviral particles of vector or pHAGE-ROR1. Scale bars, 50 µm n = 3 random fields photographed and analyzed from each condition.(F) Western blots showing the protein expression of total and phosphorylated ROR1 and epithelial and mesenchymal markers in PANC-1 cells transduced with lentiviral particles of vector or pHAGE-ROR1. ß-Actin was used as a loading control. Results represent three independent experiments.(G) Western blots assessing the protein expression of SLC22A10, SLC22A15, pROR1 (Tyr786), ROR1, and epithelial, and mesenchymal markers in SLC22A10-OE, SLC22A15-OE, shRNA-ROR1, SLC22A10-OE + shROR1, and SLC22A15-OE + shROR1 transduced clones. ß-Actin was used as a loading control. Results represent at least three independent experiments performed.(H) GSEA enrichment plot displaying the enrichment of hallmark IFN-a and IFN-? pathway genes in SLC22A10- and SLC22A15-OE clones. NES: enrichment score normalized to mean enrichment of random samples of the same size. n = 3 independent biological replicates of each RNA sample (pLV-Control, pLV-SLC22A10, and pLV-SLC22A15) were sequenced and analyzed.(I) Western blots assessing the protein expression of key players of the IFN-a and IFN-? signaling pathway in vector-transduced and SLC22A10- and SLC22A15-OE clones. ß-Actin was used as a loading control. Data represent three independent experiments.(J) Quantification of IFN-a and IFN-? in the conditioned medium (CM) collected from vector-control, SLC22A10- and SLC22A15-OE clones. Error bars: mean ± SD.(K) Western blots displaying the protein expression of key players of the IFN-a and IFN-? signaling pathway including pROR1 (Tyr786), and ROR1 in stable clones of shRNA-Control (scramble), shSLC22A10, and shSLC22A15 developed in Mes and mKPC cells. ß-Actin was used as a loading control. Western blots shown represent three independent experiments.(L) Western blots depicting the protein expression of markers of the IFN-STAT3-ROR1 signaling axis in PANC-1 cells treated with the indicated concentrations of IFN-a and IFN-? for 48 h ß-Actin was used as a loading control. Western blots shown represent three independent experiments.(M) Western blots assessing the protein expression of pSTAT3 (Tyr705), STAT3, pROR1 (Tyr786), and ROR1 in vector-transduced and SLC22A10- and SLC22A15-OE clones treated with WP1066 (2.5 µM) for 24 h ß-Actin was used as a loading control. Western blots shown represent at least three independent experiments.(N) Western blots assessing the protein expression of IFNAR1, IFNGR1, pROR1 (Tyr786), and ROR1 in vector-transduced and SLC22A10- and SLC22A15-OE clones treated with IFN-a-IFNa-R-I (10 µM) for 24 h ß-Actin was used a loading control. Western blots shown represent three independent experiments.Data in (J) were analyzed by one-way ANOVA with Dunnett’s multiple comparisons test. **p < 0.01; ***p < 0.001; ns, not significant. Results represent three independent experiments.
Fig 4: Single-cell transcriptomics of PBMCs identifying CD169+ classical monocytes associated with GO progression(A) Workflow chart of the overall experimental design.(B) Left, UMAP plot showing the distribution of different cell types in the peripheral blood from 5 GO patients and 4 GD patients. Right, UMAP plots showing expression of representative marker genes for the major cell types in PBMCs.(C) Heatmap showing the distribution of upregulation DEGs in each cell type. Each column represents one cell type, and each row represents upregulated genes (LogFC >0.5, adjusted p value <0.05).(D) Combined volcano plot showing up- and downregulated genes across the most effectively changed cell types in GOs (an adjusted p value <0.01 is indicated in red; an adjusted p value ≥0.01 is indicated in black; genes within IFN pathways and inflammation are labeled). Bar plot depicting enriched pathways of the significantly upregulated genes in combined volcano plot.(E) UMAP visualization of monocytes from the transcriptomic atlas of PBMCs, colored by the identified monocyte subtypes. Boxplots comparing the differences in cell proportions between GOs (orange) and GDs (green) in the selected monocytes. The data are summarized as the mean ± SD. Statistical analysis was performed using Wilcoxon test. ns, not significant; ∗p < 0.05.(F) Mass cytometry plot (Top) and bar plot (Bottom) showing the proportions of CD169+ classical monocytes in peripheral monocytes from GOs (n = 22) and GDs (n = 20). The data are summarized as the mean ± SD. Statistical analysis was performed using independent-sample t test. ∗∗p < 0.01.
Fig 5: CD169+ clas_mono expansion is related to high levels of interferons in GO(A) Network visualization of upregulated TFs and their target genes. The internal nodes annotate TFs; the circular edge denotes the downstream target upregulated DEGs of these TFs; bar plots showing the pathway enrichment of these DEGs. The node sizes are positively correlated to the number of associated DEGs.(B) Representative histograms and quantitative analysis of phosphorylated STAT1 levels (normalized MFI values) in CD169+ clas_mono from the GO and GD groups (n = 6 per group). The data are summarized as the mean ± SD. Statistical analysis was performed using independent-sample t test. ∗∗p < 0.01.(C) Monocytes were stimulated with IFN-γ, IFN-α and IFN-β for 6 h, and relative mRNA expression (CD169 genes) was measured using qRT-PCR (n = 6). The data are summarized as the mean ± SD. Statistical analysis was performed using one-way ANOVA. ns, not significant; ∗p < 0.05; ∗∗∗p < 0.001.(D) Representative histograms and quantitative of the mass cytometry analysis results showing the proportions of CD169+ clas_mono after 24 h of IFN-γ, IFN-α and IFN-β stimulation (n = 6). Statistical analysis was performed using one-way ANOVA. All data with error bars are presented as mean ± SD. ns, not significant; ∗∗∗p < 0.001.
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