Multi-pathway oxidative stress amplification via controllably targeted nanomaterials for photoimmunotherapy of tumors

Abstract

Photoimmunotherapy, which combines phototherapy with immunotherapy, exhibits significantly improved therapeutic effects compared with mono-treatment regimens. However, its use is associated with drawbacks, such as insufficient reactive oxygen species (ROS) production and uneven photosensitizer distribution. To address these issues, we developed a controllable, targeted nanosystem that enhances oxidative stress through multiple pathways, achieving synergistic photothermal, photodynamic, and immunotherapy effects for tumor treatment. These nanoparticles (D/I@HST NPs) accurately target overexpressed transferrin receptors (TfRs) on the surface of tumor cells through surface-modified transferrin (Tf). After endocytosis, D/I@HST NPs generate ROS under 808-nm laser irradiation, breaking the ROS-responsive crosslinking agent and increasing drug release and utilization. Tf also carries Fe³⁺, which is reduced to Fe²⁺ by iron reductase in the acidic tumor microenvironment (TME). Consequently, the endoperoxide bridge structure in dihydroartemisinin is cleaved, causing additional ROS generation. Furthermore, the released IR-780 exerts both photodynamic and photothermal effects, enhancing tumor cell death. This multi-pathway oxidative stress amplification and photothermal effect can trigger immunogenic cell death in tumors, promoting the release of relevant antigens and damage-associated molecular patterns, thereby increasing dendritic cell maturation and sensitivity of tumor cells to immunotherapy. Mature dendritic cells transmit signals to T cells, increasing T cells infiltration and activation, facilitating tumor growth inhibition and the suppression of lung metastasis. Furthermore, the myeloid-derived suppressor cells in the tumor decreases significantly after treatment. In summary, this multi-pathway oxidative stress-amplified targeted nanosystem effectively inhibits tumors, reverses the immunosuppressive tumor microenvironment, and provides new insights into tumor immunotherapy combined with phototherapy.

Keywords: Dihydroartemisinin; IR-780; Photoimmunotherapy; Reactive oxygen species; Transferrin.

Scheme 1

Schematic illustration of photoimmunotherapy of tumors using targeted nanomaterials causing multi-pathway oxidative stress amplification

Fig. 1

Preparation and characterization of D/I@HST NPs. (A) Schematic diagram of D/I@HST NPs synthesis and ROS response. (B) DLS analysis of the particle size distribution and representative TEM images of D/I@HST NPs with and without laser irradiation. Scale bar, 100 nm. (C) DLS analysis of the particle size distribution and representative TEM images of D/I@HGT NPs with and without laser irradiation. Scale bar, 100 nm. (D) Cumulative release rate of IR-780 in the presence or absence of H₂O₂, n = 3. (E) DPBF-based detection of ROS generation induction by IR-780 under laser irradiation. (F) DPBF-based detection of ROS production from the reaction between DHA and Fe²⁺ at pH 5.6. (G) Thermal infrared imaging of D/I@HST NPs at different concentrations after laser irradiation for different periods. (H) Temperature increase versus time plot under laser irradiation for different D/I@HST NPs concentrations. (I) Temperature increase versus time plot for D/I@HST NPs exposed to different laser irradiation powers

Fig. 2

ROS production and in vitro anti-tumor effects of D/I@HST NPs in 4T1 cells. (A) Representative CLSM images of ROS production in 4T1 cells treated with different NPs at an equal concentration of 1 µg/mL IR-780 (+ L, with laser irradiation). Scale bar, 50 μm. (B) Statistical analysis of (A) using ImageJ software; n = 3. (C) Intracellular ROS levels assessed using the DCFH-DA assay, n = 3. (D) CCK-8 assay analysis of 4T1 cell viability following laser irradiation, D@HST, D/I@HST, I@HST + L, D/I@HS + L, D/I@HST + L, or D/I@HGT + L (+ L, with laser irradiation), n = 3. (E) Fluorescent images of live/dead 4T1 cell staining following treatment with different nanomaterials; Scale bar, 200 μm. (F) Colony formation analysis of 4T1 cells one week after treatment with different nanomaterials. (G) Flow cytometry analysis of 4T1 cell apoptosis induced by different nanomaterials using Annexin V-FITC/PI staining. Data are presented as mean ± SD. Statistical analysis was performed using one-way ANOVA followed by Tukey’s test for (B) and (C). *P < 0.05, **P < 0.01, ***P < 0.001 and ****P < 0.0001

Fig. 3

D/I@HST NP-induced immunogenic cell death in 4T1 cells. (A) Schematic diagram of nanomaterial-induced immunogenic cell death of 4T1 cells and promoting the maturation of immature DCs under laser irradiation. (B) Representative CLSM images of CRT exposure on the surface of 4T1 cells and intracellular HMGB1 in 4T1 cells treated with culture medium, D@HST, I@HST + L, D/I@HS + L, D/I@HST + L, or D/I@HGT + L (+ L, with laser irradiation). Scale bar, 50 μm. (C) CRT levels in (B) obtained using ImageJ software, n = 4. (D) Intracellular HMGB1 levels in (B) determined using ImageJ software, n = 3. (E) Cellular ATP efflux levels in different treatment groups, n = 6. (F) Schematic diagram of BMDCs extraction and maturation. (G) Representative flow cytometry plot of BMDCs maturation after co-incubation with 4T1 cells and different treatments. Data are presented as the means ± SD. Statistical analysis was performed using one-way ANOVA followed by Tukey’s test for (B), (C), and (E). Significance is defined as ns, no significance, **P < 0.01, ***P < 0.001, and ****P < 0.0001

Fig. 4

In vivo targeting and distribution of D/I@HST NPs. (A) Experimental outline of fluorescence imaging in vivo. (B) In vivo whole-body fluorescence imaging of mice at various time points after the injection of the different nanomaterials. (C) Semi-quantitative analysis of fluorescence signals of the tumor area for 36 h after injection, n = 3. (D) Ex vivo fluorescence images of tumors and major organs 36 h after injection. (E) Quantitative biodistribution analysis of D/I@HST NPs in major organs of mice based on ex vivo fluorescence imaging in (D), n = 3. Data are presented as the mean ± SD. Statistical analysis was performed using two-way ANOVA followed by Tukey’s test for (C) and (E). *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001

Fig. 5

In vivo photothermal conversion effect and anti-tumor effect of D/I@HST NPs. (A) Schematic outline of in vivo anti-tumor experiments. (B) Representative thermographic images of tumor sites in mice irradiated with laser for different durations following injection with different nanomaterials. (C) Local temperature of tumors irradiated with an 808 nm laser for 5 min. (D) Tumor growth kinetics of average tumor volumes from mice treated with PBS, D@HST, I@HST + L, D/I@HS + L, D/I@HST + L, or D/I@HGT + L (+ L, with laser irradiation), n = 5. (E) Tumor inhibition rate across the different treatment groups. (F) Representative photomicrographs of tumor sections of the mice from the different treatment groups obtained after H&E staining. Scale bar, 100 μm. (G) TUNEL staining for apoptosis in tumors extracted from the mice subjected to the different treatments. Scale bar, 100 μm. (H) DHE immunofluorescence staining for the analysis of ROS accumulation in tumor sections of mice from the different treatment groups. Scale bar, 50 μm. (I) Statistical analysis of the mean fluorescence intensity of DHE in (H), n = 3. Data are presented as the mean ± SD. Statistical analysis was performed using two-way ANOVA followed by Tukey’s test for (C) and (D) and one-way ANOVA followed by Tukey’s test for (E) and (I). *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001

Fig. 6

Immune enhancement induced by different treatments in mice. (A-G) Representative flow cytometry plots and proportional statistics indicating the proportions of (A, B) mature DCs in tumors, (C, D) CD8⁺ T cells in CD3⁺ T cells, (E) CD4⁺ T cells in CD3⁺ T cells, and (F, G) MDSCs of 4T1 tumor-bearing mice following various treatments, n = 3. (H, I) Levels of serum (H) IL-12 and (I) TNF-α following various interventions, n = 3. Data are presented as the mean ± SD. Statistical analysis was performed using one-way ANOVA followed by Tukey’s test for (B), (D), (E), (G), (H), and (I). *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001

Fig. 7

Combined application of D/I@HST NPs and PD-LI inhibitors exerts potent tumor suppression and immune activation effects. (A) Schematic diagram of bilateral tumor construction and combined therapy. (B, C) Growth kinetics curves of (B) primary and (C) distant tumors in mice treated with PBS, BMS, D/I@HST(L), or BMS + D/I@HST(L) (“L”, with laser irradiation), n = 5. (D) Representative images of H&E-stained tumor sections on both sides of mice of different treatment groups. Scale bar, 100 μm. (E) Representative images of CD8⁺ T cell immunofluorescence staining on tumor sections from both sides of mice of different treatment groups. Scale bar, 20 μm. (F–H) The percentages of mDCs (F), CD8⁺ T (G) and CD4⁺ T (H) cell populations in tumors following various treatments, n = 3. (I) Representative images of lungs obtained from mice in different treatment groups, arrows indicate lung metastasis node. (J) Quantification of lung metastasis nodes in different groups, n = 5. (K) Volcanic map shows differentially expressed genes between the BMS + D/I@HST(L) and control groups. (L) GO functional enrichment analysis of genes significantly upregulated in the BMS + D/I@HST(L) vs. control groups. Data are presented as mean ± SD. Statistical analysis is performed using two-way ANOVA followed by Tukey’s test for (B) and (C) and one-way ANOVA followed by Tukey’s test for (F–H) and (J). Significance is defined as ns, no significance, *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001