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. 2023 Jul 13;26(8):107367.
doi: 10.1016/j.isci.2023.107367. eCollection 2023 Aug 18.

Development of a DNA aptamer targeting IDO1 with anti-tumor effects

Zhenyu Zhu  1 , Zeliang Yang  1 , Chuanda Zhu  1 , Zixi Hu  1 , Zhongyu Jiang  1 , Jingjing Gong  1 , Yuyao Yuan  1 , Xi Chen  1 , Yan Jin  1 , Yuxin Yin  1   2   3
Affiliations

Development of a DNA aptamer targeting IDO1 with anti-tumor effects

Zhenyu Zhu et al. iScience. .

Abstract

Immune checkpoint blockade has become an effective approach to reverse the immune tolerance of tumor cells. Indoleamine 2,3-dioxygenase 1 (IDO1) is frequently upregulated in many types of cancers and contributes to the establishment of an immunosuppressive cancer microenvironment, which has been thought to be a potential target for cancer therapy. However, the development of IDO1 inhibitors for clinical application is still limited. Here, we isolated a DNA aptamer with a strong affinity and inhibitory activity against IDO1, designated as IDO-APT. By conjugating with nanoparticles, in situ injection of IDO-APT to CT26 tumor-bearing mice significantly suppresses the activity of regulatory T cells and promotes the function of CD8+ T cells, leading to tumor suppression and prolonged survival. Therefore, this functional IDO1-specific aptamer with potent anti-tumor effects may serve as a potential therapeutic strategy in cancer immunotherapy. Our data provide an alternative way to target IDO1 in addition to small molecule inhibitors.

Keywords: Cancer; Immunology; Pharmacology.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

None
Graphical abstract
Figure 1
Figure 1
Selection of IDO1-targeting aptamer (A) Schematic illustration of the protein-based SELEX process. (B) Flow cytometry analysis of the target binding capability of aptamer candidates. Bare beads or 1 μg IDO1 coated beads were incubated with 250 nM aptamer candidates or initial library for 1 h. The mean fluorescence intensity (MFI) of aptamers was used to reflect the binding capacity. MFI of blank was set as 1. Statistical significance between aptamer candidates and the initial library was assessed by two-tailed unpaired Student’s t test (n = 3, mean ± SEM, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001). (C) Kyn level was evaluated by in vitro IDO1 enzyme activity assay to determine the inhibitory effect of aptamer candidates. A mixture of 20 μg/mL IDO1 protein and 500 nM aptamer candidates or initial library in 100 μL reaction buffer was set as the reaction system. Statistical significance between aptamer candidates and the initial library was assessed by two-tailed unpaired Student’s t test (n = 3, mean ± SEM, ns means not significant, ∗p < 0.05, ∗∗p < 0.01). (D) The predicted secondary structure of IDO-APT. Data in (B and C) are representative of three independent experiments.
Figure 2
Figure 2
IDO-APT specifically binds with IDO1 (A) Dissociation constant (KD) of IDO-APT measured by flow cytometry. Serially diluted IDO-APT or scrambled APT was incubated with 1μg IDO1 coated beads for 1 h. The MFI of IDO-APT in different concentrations was used to calculate the value of KD. MFI of 640 nM IDO-APT was set as 100%. (B) IC50 of IDO-APT was determined by in vitro IDO1 enzyme activity assay. A mixture of 20 μg/mL IDO1 protein and different concentrations of IDO-APT or scrambled APT in 100 μL reaction buffer was set as the reaction system. Kyn level of the group without aptamers was set as 100%. (C) Mouse IDO1 protein retarded the migration of IDO-APT. A mixture of 100 nM IDO-APT and 1 mg/mL IDO1 protein was incubated at 4°C for 30 min, followed by native polyacrylamide gel electrophoresis. (D) Western blotting determined the expression of IDO1 induced by IFN-γ in CT26 cells. (E) Aptamer-mediated pull-down assay demonstrated specific binding between IDO-APT and IDO1 expressed in CT26 cells. 250 nM biotin-labeled IDO-APT or scrambled APT were used to capture IDO1 protein. IDO-APT without labeling (free IDO-APT) was added to compete with biotin-labeled IDO-APT. Data in (A–E) are representative of three independent experiments.
Figure 3
Figure 3
Characterization of mineralized nanoparticle conjugated IDO-APT (A) TEM image of NP-IDO-APT. Scale bars = 100 nm. (B) Size distribution of NP-IDO-APT determined by DLS. (C) Gel electrophoresis shows the stability of NP-IDO-APT at different times. RPMI 1640 containing 10% FBS was mixed with 100 nM FAM-labeled NP-IDO-APT or IDO-APT alone. The grayscale value of IDO-APT was calculated (right panel), and the grayscale value of IDO-APT that unincubated was set as 1 (n = 3, mean ± SEM, ∗∗∗∗p < 0.0001). (D) Cell-based IDO1 activity assay was performed to detect the Kyn level of the culture medium. CT26 cells were supplemented with 200 nM NP-IDO-APT or NP-Scr-APT and cultured for 24 h (n = 3, mean ± SEM, ∗∗∗p < 0.001). (E) Colocalization of IDO-APT and IDO1 protein was determined by immunofluorescence assay. IFN-γ treated CT26 cells were incubated with 200 nM NP-IDO-APT or NP-Scr-APT for 12 h. Statistical analysis of the fluorescence signal between aptamer (green) and IDO1 (red) was shown in the right panel. Scale bars = 5 μm. Statistical significance was assessed by two-way ANOVA (C) followed by Tukey’s multiple comparisons test or two-tailed unpaired Student’s t test (D). Data in (A–E) are representative of three independent experiments.
Figure 4
Figure 4
IDO-APT promotes T cell function in vitro Mouse spleen lymphocytes were cultured in vitro with 100 nM NPs, NP-Scr-APT, or NP-IDO-APT for 6 days, followed by flow cytometry analysis and RNA sequencing. (A) The percentage of CD25+ Foxp3+ cells was determined by flow cytometry (n = 4 cell cultures, mean ± SEM, ns means not significant, ∗∗p < 0.01). (B) Flow cytometric analysis of TNF-α expression in CD8+ T lymphocytes (n = 3 cell cultures, mean ± SEM, ns means not significant, ∗p < 0.05). (C) Flow cytometric analysis of IFN-γ expression in CD8+ T lymphocytes (n = 3 cell cultures, mean ± SEM, ns means not significant, ∗p < 0.05). (D) GO enrichment analysis identified pathways in lymphocytes treated with NP-IDO-APT. (E) Heatmap of the RNA-seq results related to T cell effector factors. The expression of each gene from the different groups was scaled by Z score. Statistical significance was assessed by one-way ANOVA (A, B, and C) followed by Tukey’s multiple comparisons test. Data in (A, B, and C) are representative of three independent experiments.
Figure 5
Figure 5
IDO-APT inhibits IDO1 activity in DCs to promote T cell activation DCs and CD3+ T cells at the ratio of 1:10 were cocultured in vitro with 100 nM NPs, NP-Scr-APT, or NP-IDO-APT for 6 days, followed by flow cytometry analysis. (A) Schematic illustration of DCs & T cells coculture assay. (B) BMDCs induced from BMs were analyzed by flow cytometry. CD45 and CD11b were used to indicate the proportion of DCs. (C) The mRNA and protein expression of IDO1 in DCs were determined after being treated with 50 ng/mL IFN-γ for 24 h, mRNA level of IFN-γ-untreated DCs was set as 1. (D) Flow cytometric analysis of TNF-α expression in CD8+ T cells (n = 3 cell cultures, mean ± SEM, ∗∗∗∗p < 0.0001). (E) Flow cytometric analysis of IFN-γ expression in CD8+ T cells (n = 3 cell cultures, ∗∗∗∗p < 0.0001). (F) The internalization of IDO-APT in DCs was determined by immunofluorescence assay. IFN-γ treated DCs were incubated with 200 nM NP-IDO-APT for 12 h. Scale bars = 5 μm. (G) Cell-based IDO1 activity assay was performed to detect the Kyn level of the culture medium. DCs were treated with 200 nM NPs, NP-Scr-APT, or NP-IDO-APT and cultured for 24 h (n = 3, ∗∗p < 0.01). Statistical significance was assessed by one (G) or two (D and E)-way ANOVA followed by Tukey’s multiple comparisons test. Data in (B–G) are representative of two independent experiments.
Figure 6
Figure 6
IDO-APT suppresses tumor growth in the CT26 tumor-bearing mouse model (A) Schematic illustration of the tumor model and treatment. Female BALB/c mice bearing CT26 tumors of ∼50 mm3 received 1.5 mg/kg NPs, NP-Scr-APT, or NP-IDO-APT at day 6, day 9, and day 12, by s.c. injection directly into the tumor. Tumor volumes were measured every 2 days. (B) IDO-APT inhibited tumor growth (n = 6 mice, mean ± SEM, ∗p < 0.05). (C) Volumes of final excised tumors for each treatment were recorded (n = 6 mice, mean ± SEM, ∗p < 0.05). (D) Representative images of final excised tumors (n = 5 mice). (E) Tumors were weighed after sacrifice (n = 6 mice, mean ± SEM, ∗p < 0.05). (F) Female BALB/c mice bearing CT26 tumor of ∼50 mm3 received three different dosages of NP-IDO-APT and were treated the same way as described above. Tumor volumes were recorded every 2 days (n = 6 mice, mean ± SEM, ns means not significant, ∗p < 0.05, ∗∗p < 0.01). (G) Volumes of final excised tumors for each treatment (n = 6 mice, mean ± SEM, ns means not significant, ∗∗p < 0.01). (H) Female NOD/SCID mice bearing CT26 tumors of ∼50 mm3 were treated the same way as described above. Tumor volumes were recorded every 2 days (n = 6 mice, mean ± SEM, ns means not significant). (I) Volumes of final excised tumors for each treatment in NOD/SCID mice were measured (n = 6 mice, mean ± SEM, ns means not significant). (J) Female BALB/c mice bearing IDO1-deficient CT26 tumors or IDO1-sufficient CT26 tumors of ∼50 mm3 were treated the same way as described above. Tumor volumes were recorded every 2 days (n = 4 mice, mean ± SEM, ns means not significant, ∗p < 0.05). (K) Volumes of final excised tumors for each treatment (n = 4 mice, mean ± SEM, ns means not significant, ∗p < 0.05). Statistical significance was assessed by one (C, E, G, and I) or two (B, F, H, J, and K)-way ANOVA followed by Tukey’s multiple comparisons test. Data in (B–K) are representative of two independent experiments.
Figure 7
Figure 7
IDO-APT inhibits IDO1 activity and promotes anti-tumor immune response in tumor-bearing mice Female BALB/c mice bearing CT26 tumors receiving the same treatment as Figure 6A were harvested tumor tissue and plasma two days after the last injection for further determination. (A) Ratios of Kyn (nM)/Trp (μM) in mouse plasma and tumor tissue were determined by LC−MS/MS (n = 6 mice, mean ± SEM, ∗∗p < 0.01). (B) Quantifying the counts of tumor-infiltrating CD45+ cells by flow cytometry (n = 6 mice, mean ± SEM, ∗∗p < 0.01, ∗∗∗∗p < 0.0001). (C) Quantifying the counts of tumor-infiltrating CD8+ T cells by flow cytometry (n = 6 mice, mean ± SEM, ∗∗∗p < 0.001). (D) Flow cytometric analysis of TNF-α expression in CD8+ T cells (n = 6 mice, mean ± SEM, ∗∗∗p < 0.001). (E) Flow cytometric analysis of IFN-γ expression in CD8+ T cells (n = 6 mice, mean ± SEM, ∗p < 0.05, ∗∗p < 0.01). (F) The percentage of CD25+ Foxp3+ cells gated in CD4+ lymphocytes was analyzed by flow cytometry (n = 6 mice, mean ± SEM, ∗∗p < 0.01). (G) The percentage of CD11b+ F4/80+ cells gated in CD45+ lymphocytes was analyzed by flow cytometry (n = 5 mice, mean ± SEM, ∗p < 0.05). (H) The percentage of CD11b+ Ly6C+ cells gated in CD45+ lymphocytes was analyzed by flow cytometry (n = 5 mice, mean ± SEM, ns means not significant). (I) The percentage of CD11b+ Ly6G+ cells gated in CD45+ lymphocytes was analyzed by flow cytometry (n = 5 mice, mean ± SEM, ∗∗p < 0.01). Statistical significance was assessed by one (B–I) or two (A)-way ANOVA followed by Tukey’s multiple comparisons test. Data in (A–I) are representative of two independent experiments.
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