Skip to main content
Download PDF

Nanomedicine-mediated induction of immunogenic cell death and prevention of PD-L1 overexpression for enhanced hepatocellular carcinoma therapy

Cancer Nanotechnology volume 11, Article number: 15 (2020) Cite this article

Abstract

Background

The present study aims to develop a nanoparticle encapsulating doxorubicin (DOX) and programmed death-ligand 1 (PD-L1) siRNA and evaluate its anti-tumor effects on hepatoma carcinoma (HCC).

Methods

Nanoparticle encapsulating DOX and PD-L1 siRNA (NPDOX/siPD-L1) was characterized by dynamic light scattering and transmission electron microscopy. Flow cytometry was applied to analyze cell populations, NPDOX/siPD-L1 internalization, and cell apoptosis. Real-Time (RT)-quantitative reverse transcription (qPCR) and western blotting were used to determine the mRNA and protein levels, respectively. Released ATP was determined using ATP determination kit and cytokines were determined using specific ELISAs. A tumor-bearing animal model was established to evaluate the anti-tumor effects of NPDOX/siPD-L1.

Results

Treatment of NPDOX/siPD-L1 induced immunogenic cell death (ICD) and PD-L1 overexpression in HCC. In vivo study demonstrated that intravenously injection of NPDOX/siPD-L1 significantly inhibited the tumor volume and PD-L1 expressions of tumor tissue in the H22 tumor-bearing animal model. Besides, the treatment of NPDOX/siPD-L1 also regulated the populations of matured dendritic cells and cytotoxic T cells and the productions of cytokines in the tumor tissues.

Conclusion

Taken together, NPDOX/siPD-L1 showed significant anti-tumor effects on HCC by the induction of ICD and inhibition of PD-L1 overexpression.

Background

Hepatoma, also called hepatocellular carcinoma (HCC), is one of the most frequent malignant cancers worldwide (Bosch et al. 2004). The morbidity and mortality of HCC are globally ranked as third and fifth, respectively. It is known that about 8% of people suffering from hepatitis, who are ease to develop into HCC (Bosch et al. 2004; Sia et al. 2017). Besides, nonalcoholic fatty liver diseases and cirrhosis are also reported to be associated with the occurrence and development of HCC (Murakami et al. 1998). It is difficult to diagnose HCC at the early stages. There are only 30–40% of patients at HCC early stages who were diagnosed. Once HCC develops into the advanced stages, surgical treatment such as transcatheter arterial chemoembolization becomes less effective, accompanied by poor prognosis and a high recurrence rate (Sia et al. 2017; Bruix et al. 2015). Additionally, surgical treatment is not recommended for patients who had extrahepatic metastases. Thus, chemotherapy is the only option for the treatment of HCC in those patients (Bruix et al. 2015; Li and Wang 2016).

Immunogenic cell death (ICD) is one type of cell death that causes an activation of the immune response (Galluzzi et al. 2017; Garg et al. 2015). When ICD occurs in the tumor microenvironment, calreticulin (CRT) is exposed on the surface of tumor cells, thereby stimulating dendritic cells (DCs) to engulf tumor cells (Galluzzi et al. 2017; Vandenabeele et al. 2016; Pitt et al. 2017). In addition, large amounts of adenosine triphosphate (ATP) are released in the tumor tissues, leading to the recruitment of immune cells including monocytes, macrophages, and DCs against tumor-associated antigens (Vandenabeele et al. 2016; Showalter et al. 2017). After that, activated cytotoxic T cells mediate the anti-cancer immune responses. Additionally, extracellular High mobility group box 1 protein (HMGB1) has also been implicated to be associated with ICD (Vandenabeele et al. 2016; Showalter et al. 2017). HMGB1 is released from the dead cells and is able to bind to toll-like receptor 4, thereby promoting matured DCs to present tumor-associated antigen to the T cells (Vandenabeele et al. 2016; Ladoire et al. 2016). These findings encourage us to discover drugs that are able to induce the ICD for cancer therapy.

Many studies have revealed that chemotherapeutic agents including platinum-based drug and doxorubicin (DOX) not only induce cell apoptosis, also trigger ICD (Wong et al. 2015; Fan et al. 2017; Jessup et al. 2019). However, we found that the treatment of DOX enhanced the expressions of programmed death-ligand 1 (PD-L1) in the tumor cells. We inferred that T cell-mediated anti-cancer immune responses were inhibited due to PD-L1 overexpression. To confirm our hypothesis, we evaluated the effects of DOX on the ICD in the PD-L1 knockdown tumor cells. Firstly, we designed a nanoparticle that can encapsulate DOX and PD-L1 siRNA (siPD-L1). Furthermore, to evaluate the anti-tumor effects of the nanoparticle encapsulating DOX and PD-L1 siRNA (NPDOX/siPD-L1) and its underlying mechanisms, we applied HCC cells and tumor-bearing animal models.

Materials and methods

Construction of nanoparticles encapsulating doxorubicin (DOX) and PD-L1 siRNA (NPDOX/siPD-L1) and its characterization

NPDOX/siPD-L1 was constructed according to a previously reported method. In brief, block copolymer PEG-PLA (Sigma-Aldrich, St. Louis, MO, USA), cationic lipid DOTAP (Avanti Polar Lipids, Alabaster, AL, USA), and DOX (Sigma-Aldrich) were combined at a ratio of 10:1:1 according to a single emulsion method (Sun et al. 2015). The formed NPDOX was further loaded with PD-L1 siRNA (siPD-L1, Suzhou Ribo Life Science Co., Ltd., Suzhou, China). After that, the gel retardation assay was used to determine the weight ratios of DOTAP to siPD-L1. Dynamic light scattering (DLS, Malvern Zetasizer Nano ZS90) was used to determine particle size and distribution. Transmission electron microscopy (TEM, JEOL JEM2010 200 kV) was used to observe the size and morphology of NPDOX/siPD-L1.

Cell lines and animals

HCC cell lines including murine H22 and human HepG2 were purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA) and cultured in the complete medium supplied with 10% fetal bovine serum, 100 μg/ml streptomycin, and 100 IU/ml penicillin at 37 °C in the presence of 5% CO2.

Mouse bone marrow-derived dendritic cells (BMDCs) and human peripheral blood dendritic cells (PBDCs) were isolated and cultured according to previously reported methods (Madaan et al. 2014; Grievink et al. 2016). For BMDCs isolation and culture, bone marrow progenitors were washed out from shin bone and thigh-bone of the mice, then cultured in the medium containing IL-4 (1 ng/ml) and granulocyte-macrophage colony-stimulating factor (10 ng/ml) (PeproTech, Rocky Hill, NJ). After culturing for 48 h, non-adherent cells were gently washed out. The remaining cell clusters were cultured. Medium was changed every other day. On day 7, the cells were collected for further experiments. For PBDCs isolation and culture, PBDCs were purified from non-adherent cells by an iso-osmotic Percoll density gradient, to yield low-density cells. Then, the low-density cells were plated to remove the monocytes. This treatment was repeated. The cells were cultured in the complete culture medium.

In the present study, H22 cells (1 × 106 cells) were co-cultured with BMDCs (1 × 106 cells) at a ratio of 1:1 in the 12-well plates. Similarly, human HepG2 cells (1 × 106 cells) were co-cultured with PBDCs (1 × 106 cells) at a ratio of 1:1 in the 12-well plates. After incubation for 24 h or 48 h, the cells and supernatant were collected for further assays.

H22-OVA cells were constructed by transfecting plasmid encoding OVA (VectorBuilder, USA) into H22 cells. OT-1 mice were purchased from the Cyagen Biosciences Inc (Suzhou, China).

Measurement of ATP

After the cells were treated with DOX or nanoparticles for 24 h, the release of ATP was determined using a chemiluminescent ATP determination kit (Life Technologies, Pleasanton, CA, USA), according to the document of the manufacturers.

Flow cytometry

The surface exposure of calreticulin (CRT) was determined using flow cytometry. H22 and HepG2 cells were treated with Doxorubicin (DOX, 0.25 μM) for 24 h and then labeled with anti-CRT-PerCP-Cy5.5 (antibody online. com. Catalog No. ABIN2486728). The percentage of CRT positive cells was quantified based on Propidium iodide (PI) negative cell populations.

To analyze cellular uptake of DOX and PD-L1 siRNA, H22 cells were incubated with indicated antibodies that were labeled with fluorescence Dye. siRNA was labeled with FITC. FITC signal and DOX signal were detected for determining cellular uptake of PD-L1 siRNA and DOX, respectively.

The populations of matured dendritic cells (DCs) and cytotoxic T cells in the tumor tissues were also detected using flow cytometry (BD FACSCalibur, San Jose, CA, USA) according to a previously reported method (Shang et al. 2018). APC-labeled CD80 (Clone: 16-10A1, BioLegend) and PE-labeled CD86 antibodies were applied to determine the population of DCs. APC-labeled CD4 (Clone: GK1.5, BioLegend) and FITC-labeled CD8 (Clone:53-6.7, BioLegend) were applied to determine the population of cytotoxic T cells. The results were analyzed using software FlowJo (LLC, Ashland, Oregon, USA).

Detection of cell apoptosis

In the present study, cell apoptosis was determined using flow cytometry. Annexin V/PI double staining was applied. H22-OVA cells were treated with nanoparticles for 24 h. Next, the treated H22-OVA cells were co-cultured with CD8 + T cells that were isolated from OT-1 mice in 9 mm petri-dish. Cells were then harvested and suspended in the binding buffer containing FITC-labeled Annexin-V and PI followed by incubation in the dark for 15 min. Then the population of apoptotic cells (Annexin-V+PI+) was measured by flow cytometry and data were analyzed using software FlowJo.

Quantitative Real-Time reverse transcription(qRT)-PCR

RNA extraction kit was used to isolate RNA from the cells, according to the manufacturer’s document. Reverse transcriptase was used in the RT reaction. The Melt curves were used to analyze the accuracy. The expressions of each gene were calculated using 2-△△Ct values. The mRNA expression values of PD-L1 were normalized to that of GAPDH.

ELISAs

The supernatant was collected from different treatment groups. The productions of the cytokines including high mobility group box 1 protein (HMGB1), transforming growth factor (TGF)-β, IL12p70, and interferon (IFN)-γ were determined using specifics ELISAs according to the manufacturers’ instruction (DAKEWE, Beijing, China).

Western blot

The protein was extracted according to the previous methods (Yang et al. 2017). In brief, a cold RIPA buffer containing protease inhibitor was used to lyse the cells or tumor tissues. After that, the extraction buffer was centrifuged at 13,000 g for 10 min to remove the cell debris and other insoluble materials. The BCA protein assay kits were applied to qualify the concentrations of extracted proteins.

An equal amount of proteins was loaded and separated using the 10% SDS gel. After that, the gel was transfer to a PVDF membrane, which was blocked with 5% non-fat milk at room temperature for 2 h. Next, a primary antibody against S-HMGB1 (ab18256, Abcam) or PD-L1 (ab205921, Abcam) was used to incubate with the membrane at 4 °C overnight. Appropriated secondary antibodies conjugated with HRP were used and the imaging system was applied to qualify the expressions of each target proteins. In the present study, bovine serum albumin (BSA) was used as an internal control for soluble HMGB1(S-HMGB1). β-actin was used as an internal control for PD-L1.

H22 tumor-bearing animal model

Murine H22 cells (1 × 107 cells/per mouse) were subcutaneous injected into the C57BL/6 mice. When tumor volumes reached between 50 and 100 mm3, the mice were intravenously injected (i.v.) with PBS, NPDOX, NPsiPD-L1, or NPDOX/siPD-L1 at every 3 days. The nanoparticles contained DOX at a dose of 2.5 mg/kg and siPD-L1 at a dose of 2 mg/kg. Tumor volumes were recorded every 3 days. Volumes were calculated using an equation [tumor volume (mm3) = (tumor length) × (tumor width)2 × 0.5]. At the end of the experimental period, the mice were sacrificed and tumor tissues were collected. The mRNA and protein levels of PD-L1 were measured using qRT-PCR and western blot, respectively. The experimental protocol was supported by the Ethic Commitment of Hangzhou First People’s Hospital.

Histopathological analysis

At the end of the experimental period, the mice were sacrificed and the tumor tissues were collected. After the tumor tissues were fixed in 10% formalin solution, the tissues were embedded in paraffin. Hematoxylin and eosin (H&E) staining was performed and the slides were observed under a microscope.

PCNA immunohistochemistry

To analyze the cell proliferation in the tumor tissues, PCNA immunohistochemistry was applied. Paraffin sections were incubated with mouse primary antibody against PCNA followed by incubation with secondary antibody. Avidin–biotin complex procedure was applied. Five randomly chosen sections PCNA immunostained for each group were viewed at a magnification of × 1000 using an image analyzer system.

Statistical analysis

SPSS 13.0 and GraphPad prism were used in this study. Data were shown as mean ± S.D. One- or two-way analysis of variance with multiple comparisons and Student–Newman–Keuls (SNK) test were performed. A p value that less than 0.05 was thought as a statistical significance between the two groups.

Results

Treatment of doxorubicin (DOX) induced immunogenic cell death (ICD) and overexpression of PD-L1 in HCC

We explored the effects of DOX on ICD and the expressions of PD-L1 in H22 and HepG2 cells. As shown in Fig. 1a, b, we investigated the effects of DOX on the expressions of CRT, which is responsible for triggering immune cells to kill cancer cells. The results demonstrated that the percentage of CRT positive cells were significantly increased after the cells were treated with DOX. In addition, the results showed that the treatment of DOX significantly increased the release of HMGB1 and ATP when compared with those in the control group (Fig. 1c–e). These results supported that the treatment of DOX induced ICD.

Fig. 1
figure 1

Treatment of doxorubicin induced immunogenic cell death (ICD) and overexpression of PD-L1 in HCC. HCC cells including cell H22 and human HCC cell HepG2 were treated with 0.25 μM Doxorubicin (DOX) for 24 h. After that, bio-assays were performed. a, b Flow cytometry was quantifying the percentage of calreticulin (CRT) positive cells from PI negative cell population. c, d Cell supernatant was collected and released supernatant HMGB1 (S-HMGB1) was determined using Western blot and ELISA, respectively. Besides, e released ATP was measured using ATP determination kit. As shown in f, DOX-treated HCC cells were co-incubated with DCs (BMDCs or PBDCs). After 48 h, g flow cytometry was used to determine matured BMDCs (CD45+ CD11c+ cells). Additionally, h–j the expressions of PD-L1 in HCC were determined using flow cytometry, RT-qPCR, and western blot, respectively. Data were represented as mean ± SD. *p < 0.05, **p < 0.01, ***p < 0.001. All the experiments were repeated three times with similar results

Full size image

In addition, we co-cultured DOX-treated HCC cells (H22 or HepG2 cells) with DCs (BMDCs or PBDCs). The results showed that the percentage of matured DCs were significantly increased when the cells were treated with DOX, indicating the treatment of DOX promoted the mature of DCs (Fig. 1f, g). Furthermore, the frequency of PD-L1 positive cells and the mRNA and protein levels of PD-L1 in HCC cells were significantly increased in the DOX-treated groups (Fig. 1h–j).

Construction and characterization of DOX and PD-L1 siRNA encapsulated nanoparticles (NPDOX/siPD-L1)

A single emulsion method was used to construct NPDOX/siPD-L1. As shown in Fig. 2a, nanoparticles that were encapsulated with DOX, polyethylene glycol-poly (d,l-lactide) (PEG5K-PLA8K), and cationic lipid DOTAP were mixed at a ratio of 10:1:1 using the emulsion method. Next, the formulated nanoparticles were loaded with PD-L1 siRNA. As shown in Fig. 2b, the gel retardation assay was applied to determine different weight ratios of DOTAP and siPD-L1. The NPDOX/siPD-L1 displayed a uniformed size distribution and a round morphology and its average diameter were equal to 120 nm (Fig. 2c). The zeta potentials of NPDOX and NPDOX/siRNA were about 5.0 and 35.0 mV, respectively (Fig. 2d). The selection of the ratio of PEG-PLA, cationic lipid DOTAP, and DOX was determined according to the encapsulation efficacy of DOX and the surface charge of the obtained nanoparticle. In this ratio, the encapsulation efficacy of DOX could reach 80% and the zeta potential of NPDOX was about 35.0 mV, making it possible to adsorb negative siRNA.

Fig. 2
figure 2

Construction and characterization of DOX and PD-L1 siRNA encapsulated nanoparticles (NPDOX/siPD-L1). a The diagram of the construction of NPDOX/siPD-L1. b The weight ratios of DOTAP to siPD-L1 were determined using gel retardation. Besides, c, d TEM image, size distribution, and surface potential of NPDOX/siPD-L1 were also determined. All the experiments were repeated three times with similar results

Full size image

NPDOX/siPD-L1 induced ICD of H22 cells and inhibited overexpression of PD-L1

We then determined the effects of NPDOX/siPD-L1 on the ICD and the expressions of PD-L1 in the H22 cells. First, we examined the internalization of NPDOX/siPD-L1 of the cells. The results demonstrated that both DOX and siPD-L1 were internalized into the cells, indicating the NPDOX/siPD-L1 were successfully delivered into the cells (Fig. 3a–c). Next, we determined the effects of NPDOX/siPD-L1 on the ICD by evaluation of the frequency of CRT positive cells, and the release of HMGB1 and ATP. The results demonstrated that treatment of NPDOX/siPD-L1 significantly increased the frequency of CRT positive cells and the release of HMGB1 and ATP when compared with those in the NPsiPD-L1-treated groups (Fig. 3d–f), indicating that the treatment of NPDOX/siPD-L1 significantly induced the ICD of H22 cells.

Fig. 3
figure 3

NPDOX/siPD-L1 induced ICD of H22 cells and inhibited overexpression of PD-L1. a, b FITC was used to label siRNA and DOX signal was used to label DOX. Flow cytometry was used to analyze internalization of NPDOX/siPD-L1 internalization. d CRT positive cells were analyzed using Flow cytometry. e, f Released HMGB1 and ATP were determined after the H22 cells were treated with NPDOX/siPD-L1. g The mRNA and protein levels of PD-L1 were determined using RT-qPCR and western blot, respectively. As shown in the h, treated H22-OVA cell were co-incubated with CD8+ T cells, and the apoptosis of H22 cells was determined. i Annexin V/PI double staining were applied and flow cytometry was used to determine cell apoptosis. Data were represented as mean ± SD. *p < 0.05, **p < 0.01, ***p < 0.001. All the experiments were repeated three times with similar results

Full size image

Moreover, to determine the efficiency of PD-L1 siRNA, we measured the mRNA and protein levels of PD-L1 in H22 cells. The results showed that NPsiPD-L1- and NPDOX/siPD-L1-treated group significantly decreased the mRNA and protein levels of PD-L1 (Fig. 3g), indicating that PD-L1 siRNA were successfully designed and encapsulated. As shown in Fig. 3h, H22-OVA cells were co-cultured with CD8+ T cells that were isolated from OT-1 mice. And then we determined the apoptosis of H22 cells. The results showed that treatment of NPDOX/siPD-L1 promoted the apoptotic cell population when compared with those in the NPsiPD-L1- or NPDOX/siNC-treated group (Fig. 3i).

NPDOX/siPD-L1 existed anti-tumor effects on a H22 tumor-bearing animal model

Before we applied NPDOX/siPD-L1 into in vivo study, we firstly determined the stability of NPDOX/siPD-L1 in serum. NPDOX/siPD-L1 was incubated with fetal bovine serum (10%, v/v)-containing PBS for 72 h and the size of nanoparticles was detected by DLS. As shown in Additional file 1: Fig. S1, a negligible change was observed within 72 h

To confirm the effects of NPDOX/siPD-L1 on in vitro study, an H22 tumor-bearing animal model was established to determine the in vivo anti-tumor effects of NPDOX/siPD-L1. Figure 4a displays the experimental schematic H22 tumor-bearing animal model and NPDOX/siPD-L1 administration. After subcutaneous injection of H22 cells for 1 week, the nanoparticles were intravenously administrated (i.v.) every 3 days. The results showed that tumor volumes in NPDOX/siPD-L1 treated groups were significant decreased when compared with those in the NPsiPD-L1- or NPDOX/siNC-treated groups (Fig. 4b). Next, we determined the mRNA and protein levels of PD-L1 in tumor tissues. The results showed that the mRNA and protein levels of PD-L1 were significantly decreased in the NPsiPD-L1- or NPDOX/siPD-L1 treated group (Fig. 4c, d). Furthermore, histology examination and PCNA were performed. The results showed that the treatment of NPDOX/siPD-L1 inhibited cell proliferation in the tumor tissues (Fig. 4e).

Fig. 4
figure 4

NPDOX/siPD-L1 existed anti-tumor effects on an H22 tumor-bearing animal model. a, b C57BL/6 mice were subcutaneously injected with H22 cells. After 1 week, tumor-bearing mice (n = 8) were intravenously injected with PBS, NPDOX, NPsiPD-L1 or NPDOX/siPD-L1, respectively. Tumor volumes were measured every 3 days (n = 8). At the end of the experiment, c, d the mRNA and protein levels of PD-L1 in tumor tissues were determined using RT-qPCR and western blot, respectively. e Histology examination of tumor tissue was performed using H&E staining. Besides, PCNA analyses were performed to determine the cell proliferation in tumor tissues. Scale bar was 10 μm

Full size image

Moreover, the present study also investigated the in vivo distribution of NPDOX/siPD-L1. H22 tumor-bearing mice were intravenously administrated with NPDOX/siPD-L1 (the injection dose of 2.5 mg/kg), mice were sacrificed 24 h later, main organs and tumor tissues were collected and examined using fluorescence in vivo imaging system (IVIS). We found that NPDOX/siPD-L1 efficiently accumulated in tumor tissues, and unavoidably, nanoparticles were also enriched in the spleen, liver, and kidney (Additional file 1: Fig. S2A, B).

NPDOX/siPD-L1 regulated the populations of matured dendritic cells and cytotoxic T cells and cytokine expression patterns in the tumor tissues

Finally, we investigated the underlying mechanisms of NPDOX/siPD-L1 on its anti-tumor effects. First, we analyzed the percentage of matured dendritic cells and cytotoxic T cells in tumor tissues. The results showed that treatment of NPDOX/siNC or NPDOX/siPD-L1 significantly increased the percentage of matured dendritic cells in tumor tissues. However, the treatment of NPsiPD-L1 did not significantly affect the percentage of matured dendritic cells (Fig. 5a, b). Additionally, NPsiPD-L1-treated groups demonstrated a significant increase of the percentage of cytotoxic T cells, and NPDOX/siPD-L1-treated groups displayed an even higher percentage of cytotoxic T cells in tumor tissues as compared to the NPDOX/siPD-L1-treated groups (Fig. 5c, d).

Fig. 5
figure 5

NPDOX/siPD-L1 regulated the populations of matured dendritic cells and cytotoxic T cells and cytokine expression patterns in the tumor tissues. a–d Flow cytometry was used to analyze CD45+CD11b+CD11c+ DCs and CD8+ cytotoxic T cells. e–g The expressions of TGF-β, IL12p70, and IFN-γ in tumor tissues were determined using ELISA. Data were represented as mean ± SD (n = 8). *p < 0.05, **p < 0.01, ***p < 0.001

Full size image

Moreover, we determined the productions of cytokines including TGF-β, IL12p70, and IFN-γ. The results demonstrated that the productions of TGF-β were significantly decreased in the NPDOX/siNC, NPsiPD-L1, or NPDOX/siPD-L1-treated groups in comparison to the control group (Fig. 5e). The NPDOX/siPD-L1-treated groups displayed strong inhibitory effects on the productions of TGF-β. Additionally, the treatment of NPDOX/siPD-L1 also showed significant promotion effects on the productions of IL12p70, and IFN-γ (Fig. 5f, g). Taken together, these results supported that the treatment of NPDOX/siPD-L1 regulated the populations of matured dendritic cells and cytotoxic T cells and the expressions of cytokines including TGF-β, IL12p70, and IFN-γ in the tumor tissues.

Discussion

In this study, we found that DOX induced ICD in the HCC cells including H22 and HepG2. ICD is characterized by the surface expose of CRT, the release of extracellular HMGB1 and ATP (Garg et al. 2015). Our results demonstrated that the treatment of DOX significantly increased the percentage of CRT positive cells, and the release of extracellular HMGB1 and ATP. Additionally, the release of HMGB1 is a late event of ICD, leading to matured DCs to present tumor-associated antigen to the T cells (Liu et al. 2018; Zhang et al. 2019). We then co-cultured DOX-treated HCC cells with DCs, and the results demonstrated that higher amount of matured DCs in the DOX-treated treated group as compared with those in the control group. These results supported that the treatment of DOX induced ICD in the HCC, which are consistent with a previous finding, in which DOX not only induces cell apoptosis, also triggers ICD (Kawano et al. 2016). However, the treatment of DOX enhanced the expressions of PD-L1 in the tumor cells. It is known that PD-L1 binds to programmed cell death protein 1 (PD-1), a co-inhibitor expressed on T cell surface that regulates T cell-mediated immune response (Zou et al. 2016; Roemer et al. 2016). Overexpression of PD-L1 is an obstacle for the treatment of DOX. Therefore, the present study aims to explore the effects of DOX on the ICD when it comes to that PD-L1 was inhibited.

Pegylated liposomal doxorubicin has been approved by the Food and Drug Administration (FDA) in 1995 (Hadjidemetriou et al. 2016). Since then, nanoparticle-based delivery systems for the DOX have drawn much attention in recent years (Jain et al. 2015; Malinovskaya et al. 2017). In the present study, we developed NPDOX/siPD-L1 in two steps. First, we mixed nanoparticles that were encapsulated with DOX, polyethylene glycol-poly (d,l-lactide) (PEG5K-PLA8K), and cationic lipid DOTAP at a ratio of 10: 1: 1 using the emulsion method. Second, we loaded siPD-L1 into the formulated nanoparticles. Our results demonstrated that the NPDOX/siPD-L1 displayed a uniformed size distribution and a round morphology. Additionally, both DOX and siPD-L1 were internalized into the cells, indicating NPDOX/siPD-L1 successfully being delivered the cells.

Overexpression of PD-L1 on the cancer cells promote cancer cell escape from T cell-mediated immune response (Tang et al. 2018). The previous study has demonstrated that the blockage of PD-L1 is an effectively adjunctive strategy to boost ICD (Tang et al. 2018). In this study, we observed that the knockdown of PD-L1 did not impact the ICD events including the expressions of CRT, the release of extracellular HMGB1 and ATP. Interestingly, when we combined DOX and siPD-L1, the results showed that treatment of NPDOX/siPD-L1 significantly increased the frequency of CRT positive cells and the release of HMGB1 and ATP when compared with those in the NPsiPD-L1-treated groups. These results supported the adjunctive role of blocking PD-L1 in the augment of ICD. Furthermore, we co-cultured treated H22-OVA cells with CD8+ T cells and evaluated the effects of NPsiPD-L1 and NPDOX/siPD-L1 on the cell apoptosis. CD8+ T cells are also known as cytotoxic T cells, which have been indicated to play a crucial role in cancer cell surveillance. In the present study, we found that the treatment of NPsiPD-L1 or NPDOX/siPD-L1 promoted HCC cell apoptosis.

To confirm the anti-tumor effects of NPDOX/siPD-L1 in vitro, an H22 tumor-bearing animal model was established. First, the results showed that the expressions of PD-L1 were significantly decreased in the NPsiPD-L1- or NPDOX/siPD-L1 treated group, indicating that the DOX and siPD-L1 were successfully delivered by nanoparticles. Surprisingly, the results showed a significant decrease in tumor volume in NPDOX/siPD-L1 treated groups. These results are consistent with PCNA analysis, in which showed that cell proliferation in tumor tissues was inhibited in the NPDOX/siPD-L1 treated group. We then explored whether the anti-tumor effects of NPDOX/siPD-L1 were associated with the regulation of the population of immune cells. Two types of cells including matured DCs and CD8+ T cells were analyzed in the tumor tissues. Matured DCs are known to present antigen to the T cells, whilst CD8+ T cells are known to kill cancer cells (Gardner and Ruffell 2016; Wang et al. 2019). Our results showed that NPDOX/siPD-L1 significantly increased the percentage of matured dendritic cells and CD8+ T cells in tumor tissues, indicating NPDOX/siPD-L1 regulated the populations of matured DCs and CD8+ T cells. Additionally, we also evaluated the productions of classic cytokines including TGF-β, IL12p70, and IFN-γ. It is known that CD8+ T cells secrete cytokines including IFN-γ which have anti-tumor functions (Wang et al. 2019; Gao et al. 2017). IL12p70, a cytokine produced by DCs, has been reported to trigger the activation of CD8+ T cells by the production of chemokines.(Lu 2017) It has been reported that TGF-β regulates T cell differentiation (Colak and Ten Dijke 2017). The results demonstrated that NPDOX/siPD-L1-treated groups inhibited the productions of TGF-β and promoted the productions of IL12p70 and IFN-γ. In summary, these results supported that the treatment of NPDOX/siPD-L1 existed anti-tumor effects by the regulation of the populations of matured DCs and CD8+ T cells and the expressions of cytokines including TGF-β, IL12p70, and IFN-γ.

Conclusion

In the present study, for the first time, we successfully developed a NPDOX/siPD-L1 that is able to simultaneously deliver DOX and PD-L1 siRNA into HCC cells and tumor tissues. Our results demonstrated that the treatment of NPDOX/siPD-L1 significantly induced ICD in the HCC cells. Additionally, in vivo study supported that treatment of NPDOX/siPD-L1 significantly inhibited tumor growth in part by the regulation the populations of matured DCs and cytotoxic T cells and the expressions of cytokines including TGF-β, IL12p70, and IFN-γ.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

DOX:

Doxorubicin

HCC:

Hepatoma carcinoma

ICD:

Immunogenic cell death

CRT:

Calreticulin

DCs:

Dendritic cells

PD-L1:

Programmed death-ligand 1

ATP:

Adenosine triphosphate

HMGB1:

High mobility group box 1 protein

S-HMGB1:

Soluble HMGB1

siPD-L1:

PD-L1 siRNA

NPDOX/siPD-L1 :

Nanoparticles encapsulating DOX and PD-L1 siRNA

FDA:

Food and Drug Administration

TGF:

Transforming growth factor

IFN:

Interferon

BMDCs:

Mouse bone marrow-derived dendritic cells

PBDCs:

Human peripheral blood dendritic cells

H&E:

Hematoxylin and eosin

PI:

Propidium iodide

References

  1. Bosch FX, Ribes J, Diaz M, Cleries R. Primary liver cancer: worldwide incidence and trends. Gastroenterology. 2004;127:S5–16. https://doi.org/10.1053/j.gastro.2004.09.011.

    Article  Google Scholar 

  2. Bruix J, Han KH, Gores G, Llovet JM, Mazzaferro V. Liver cancer: approaching a personalized care. J Hepatol. 2015;62:S144–56. https://doi.org/10.1016/j.jhep.2015.02.007.

    Article  Google Scholar 

  3. Colak S, Ten Dijke P. Targeting TGF-beta signaling in cancer. Trends Cancer. 2017;3:56–71. https://doi.org/10.1016/j.trecan.2016.11.008.

    CAS  Article  Google Scholar 

  4. Fan Y, Kuai R, Xu Y, Ochyl LJ, Irvine DJ, Moon JJ. Immunogenic cell death amplified by co-localized adjuvant delivery for cancer immunotherapy. Nano Lett. 2017;17:7387–93. https://doi.org/10.1021/acs.nanolett.7b03218.

    CAS  Article  Google Scholar 

  5. Galluzzi L, Buque A, Kepp O, Zitvogel L, Kroemer G. Immunogenic cell death in cancer and infectious disease. Nat Rev Immunol. 2017;17:97–111. https://doi.org/10.1038/nri.2016.107.

    CAS  Article  Google Scholar 

  6. Gao Z, Li Y, Wang F, Huang T, Fan K, Zhang Y, Zhong J, Cao Q, Chao T, Jia J, Yang S, Zhang L, Xiao Y, Zhou JY, Feng XH, Jin J. Mitochondrial dynamics controls anti-tumour innate immunity by regulating CHIP-IRF1 axis stability. Nat Commun. 2017;8:1805. https://doi.org/10.1038/s41467-017-01919-0.

    CAS  Article  Google Scholar 

  7. Gardner A, Ruffell B. Dendritic cells and cancer immunity. Trends Immunol. 2016;37:855–65. https://doi.org/10.1016/j.it.2016.09.006.

    CAS  Article  Google Scholar 

  8. Garg AD, Dudek-Peric AM, Romano E, Agostinis P. Immunogenic cell death. Int J Dev Biol. 2015;59:131–40. https://doi.org/10.1387/ijdb.150061pa.

    CAS  Article  Google Scholar 

  9. Grievink HW, Luisman T, Kluft C, Moerland M, Malone KE. Comparison of Three Isolation Techniques for Human Peripheral Blood Mononuclear Cells: cell Recovery and Viability, Population Composition, and Cell Functionality. Biopreserv Biobank. 2016;14:410–5. https://doi.org/10.1089/bio.2015.0104.

    CAS  Article  Google Scholar 

  10. Hadjidemetriou M, Al-Ahmady Z, Kostarelos K. Time-evolution of in vivo protein corona onto blood-circulating PEGylated liposomal doxorubicin (DOXIL) nanoparticles. Nanoscale. 2016;8:6948–57. https://doi.org/10.1039/c5nr09158f.

    CAS  Article  Google Scholar 

  11. Jain A, Kesharwani P, Garg NK, Jain A, Jain SA, Jain AK, Nirbhavane P, Ghanghoria R, Tyagi RK, Katare OP. Galactose engineered solid lipid nanoparticles for targeted delivery of doxorubicin. Colloids Surf B Biointerfaces. 2015;134:47–58. https://doi.org/10.1016/j.colsurfb.2015.06.027.

    CAS  Article  Google Scholar 

  12. Jessup JM, Kabbout M, Korokhov N, Joun A, Tollefson AE, Wold WSM, Mattoo AR. Adenovirus and Oxaliplatin cooperate as agnostic sensitizers for immunogenic cell death in colorectal carcinoma. Hum Vaccin Immunother. 2019. https://doi.org/10.1080/21645515.2019.1665960.

    Article  Google Scholar 

  13. Kawano M, Tanaka K, Itonaga I, Iwasaki T, Miyazaki M, Ikeda S, Tsumura H. Dendritic cells combined with doxorubicin induces immunogenic cell death and exhibits antitumor effects for osteosarcoma. Oncol Lett. 2016;11:2169–75. https://doi.org/10.3892/ol.2016.4175.

    CAS  Article  Google Scholar 

  14. Ladoire S, Enot D, Andre F, Zitvogel L, Kroemer G. Immunogenic cell death-related biomarkers: impact on the survival of breast cancer patients after adjuvant chemotherapy. Oncoimmunology. 2016;5:e1082706. https://doi.org/10.1080/2162402X.2015.1082706.

    CAS  Article  Google Scholar 

  15. Li L, Wang H. Heterogeneity of liver cancer and personalized therapy. Cancer Lett. 2016;379:191–7. https://doi.org/10.1016/j.canlet.2015.07.018.

    CAS  Article  Google Scholar 

  16. Liu P, Zhao L, Loos F, Iribarren K, Kepp O, Kroemer G. Epigenetic anticancer agents cause HMGB1 release in vivo. Oncoimmunology. 2018;7:e1431090. https://doi.org/10.1080/2162402X.2018.1431090.

    Article  Google Scholar 

  17. Lu X. Impact of IL-12 in cancer. Curr Cancer Drug Targets. 2017;17:682–97. https://doi.org/10.2174/1568009617666170427102729.

    CAS  Article  Google Scholar 

  18. Madaan A, Verma R, Singh AT, Jain SK, Jaggi M. A stepwise procedure for isolation of murine bone marrow and generation of dendritic cells. Journal of Biological Methods. 2014;1:e1.

    Article  Google Scholar 

  19. Malinovskaya Y, Melnikov P, Baklaushev V, Gabashvili A, Osipova N, Mantrov S, Ermolenko Y, Maksimenko O, Gorshkova M, Balabanyan V, Kreuter J, Gelperina S. Delivery of doxorubicin-loaded PLGA nanoparticles into U87 human glioblastoma cells. Int J Pharm. 2017;524:77–90. https://doi.org/10.1016/j.ijpharm.2017.03.049.

    CAS  Article  Google Scholar 

  20. Murakami T, Kim T, Nakamura H. Hepatitis, cirrhosis, and hepatoma. J Magn Reson Imaging. 1998;8:346–58. https://doi.org/10.1002/jmri.1880080214.

    CAS  Article  Google Scholar 

  21. Pitt JM, Kroemer G, Zitvogel L. Immunogenic and Non-immunogenic Cell Death in the Tumor Microenvironment. Adv Exp Med Biol. 2017;1036:65–79. https://doi.org/10.1007/978-3-319-67577-0_5.

    CAS  Article  Google Scholar 

  22. Roemer MG, Advani RH, Ligon AH, Natkunam Y, Redd RA, Homer H, Connelly CF, Sun HH, Daadi SE, Freeman GJ, Armand P, Chapuy B, de Jong D, Hoppe RT, Neuberg DS, Rodig SJ, Shipp MA. PD-L1 and PD-L2 genetic alterations define classical hodgkin lymphoma and predict outcome. J Clin Oncol. 2016;34:2690–7. https://doi.org/10.1200/JCO.2016.66.4482.

    CAS  Article  Google Scholar 

  23. Shang W, Jiang Y, Boettcher M, Ding K, Mollenauer M, Liu Z, Wen X, Liu C, Hao P, Zhao S. Genome-wide CRISPR screen identifies FAM49B as a key regulator of actin dynamics and T cell activation. Proc Natl Acad Sci. 2018;115:E4051–60.

    CAS  Article  Google Scholar 

  24. Showalter A, Limaye A, Oyer JL, Igarashi R, Kittipatarin C, Copik AJ, Khaled AR. Cytokines in immunogenic cell death: applications for cancer immunotherapy. Cytokine. 2017;97:123–32. https://doi.org/10.1016/j.cyto.2017.05.024.

    CAS  Article  Google Scholar 

  25. Sia D, Villanueva A, Friedman SL, Llovet JM. Liver cancer cell of origin, molecular class, and effects on patient prognosis. Gastroenterology. 2017;152:745–61. https://doi.org/10.1053/j.gastro.2016.11.048.

    CAS  Article  Google Scholar 

  26. Sun R, Liu Y, Li SY, Shen S, Du XJ, Xu CF, Wang J. Co-delivery of all-trans-retinoic acid and doxorubicin for cancer therapy with synergistic inhibition of cancer stem cells. J Control Release. 2015;213:e94. https://doi.org/10.1016/j.jconrel.2015.05.156.

    Article  Google Scholar 

  27. Tang H, Liang Y, Anders RA, Taube JM, Qiu X, Mulgaonkar A, Liu X, Harrington SM, Guo J, Xin Y. PD-L1 on host cells is essential for PD-L1 blockade–mediated tumor regression. J Clin Invest. 2018;128:580–8.

    Article  Google Scholar 

  28. Vandenabeele P, Vandecasteele K, Bachert C, Krysko O, Krysko DV. Immunogenic Apoptotic Cell Death and Anticancer Immunity. Adv Exp Med Biol. 2016;930:133–49. https://doi.org/10.1007/978-3-319-39406-0_6.

    CAS  Article  Google Scholar 

  29. Wang W, Green M, Choi JE, Gijon M, Kennedy PD, Johnson JK, Liao P, Lang X, Kryczek I, Sell A, Xia H, Zhou J, Li G, Li J, Li W, Wei S, Vatan L, Zhang H, Szeliga W, Gu W, Liu R, Lawrence TS, Lamb C, Tanno Y, Cieslik M, Stone E, Georgiou G, Chan TA, Chinnaiyan A, Zou W. CD8(+) T cells regulate tumour ferroptosis during cancer immunotherapy. Nature. 2019;569:270–4. https://doi.org/10.1038/s41586-019-1170-y.

    CAS  Article  Google Scholar 

  30. Wong DY, Ong WW, Ang WH. Induction of immunogenic cell death by chemotherapeutic platinum complexes. Angew Chem Int Ed Engl. 2015;54:6483–7. https://doi.org/10.1002/anie.201500934.

    CAS  Article  Google Scholar 

  31. Yang H, Wang J, Fan JH, Zhang YQ, Zhao JX, Dai XJ, Liu Q, Shen YJ, Liu C, Sun WD, Sun Y. Ilexgenin A exerts anti-inflammation and anti-angiogenesis effects through inhibition of STAT3 and PI3K pathways and exhibits synergistic effects with Sorafenib on hepatoma growth. Toxicol Appl Pharmacol. 2017;315:90–101. https://doi.org/10.1016/j.taap.2016.12.008.

    CAS  Article  Google Scholar 

  32. Zhang Y, Liu RB, Cao Q, Fan KQ, Huang LJ, Yu JS, Gao ZJ, Huang T, Zhong JY, Mao XT, Wang F, Xiao P, Zhao Y, Feng XH, Li YY, Jin J. USP16-mediated deubiquitination of calcineurin A controls peripheral T cell maintenance. J Clin Invest. 2019;129:2856–71. https://doi.org/10.1172/JCI123801.

    Article  Google Scholar 

  33. Zou W, Wolchok JD, Chen L. PD-L1 (B7-H1) and PD-1 pathway blockade for cancer therapy: mechanisms, response biomarkers, and combinations. Sci Transl Med. 2016;8:328rv324. https://doi.org/10.1126/scitranslmed.aad7118.

    CAS  Article  Google Scholar 

Download references

Acknowledgements

None.

Funding

This work was supported by grants from Medicine and Health Science and Technology Plan Projects of Zhejiang Province (grant No. 2021KY231) and Zhejiang Provincial Natural Science Foundation of China (grant No. LY21H160016).

Author information

Affiliations

  1. Department of Hepatopancreatobiliary Surgery, Hangzhou First People’s Hospital, The Affiliated Hospital of Medical School of Zhejiang University, Hangzhou, 310006, Zhejiang, China

    Hanzhang Zhu, Weijiang Zhou, Yafeng Wan, Ke Ge, Jun Lu & Changku Jia

Authors
  1. Hanzhang Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Weijiang Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yafeng Wan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ke Ge
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jun Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Changku Jia
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conception/design: HZ, WZ, YW, KG, JL and CJ. Collection and/or assembly of data: WZ, YW, KG and JL Manuscript writing: HZ and CJ. Final approval of manuscript: HZ, WZ, YW, KG, JL and CJ. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Changku Jia.

Ethics declarations

Ethics approval and consent to participate

The experimental protocol was supported by the Ethic Commitment of Hangzhou First People’s Hospital.

Consent for publication

Current study is available from the corresponding author on reasonable request.

Competing interests

All of the authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Additional file 1.

 Figure S1 and S2.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zhu, H., Zhou, W., Wan, Y. et al. Nanomedicine-mediated induction of immunogenic cell death and prevention of PD-L1 overexpression for enhanced hepatocellular carcinoma therapy. Cancer Nano 11, 15 (2020). https://doi.org/10.1186/s12645-020-00072-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12645-020-00072-6

Keywords

  • Hepatocellular carcinoma
  • Nanoparticle
  • Doxorubicin
  • Immunogenic cell death
  • PD-L1

Cancer Nanotechnology

ISSN: 1868-6966

Contact us