Utilization of artificial circular RNAs as miRNA sponges and anti-PD-1 scFv expression platforms to suppress hepatocellular carcinoma progression

Abstract

Background: Hepatocellular carcinoma (HCC) is characterized by a complex interplay of genetic and epigenetic alterations that contribute to its aggressive nature and resistance to conventional therapies. The recent advent of immune checkpoint inhibitors has shown promise in enhancing the immune system's ability to target cancer cells. However, the efficacy of these therapies is often hindered by the tumor's immunosuppressive microenvironment. Circular RNAs (circRNAs), a class of non-coding RNAs, have emerged as promising candidates for the development of novel therapeutics due to their unique properties, including resistance to degradation and the ability to act as miRNA sponges.

Methods: In this study, we engineered artificial circRNAs to target oncogenic miRNAs and to express anti-PD-1 scFv antibodies, aiming to simultaneously disrupt oncogenic pathways and enhance the immune response against HCC.

Results: Our results demonstrate that the engineered circRNAs effectively sponge miR-25, leading to subsequent inhibition of HCC cell proliferation and angiogenesis. Moreover, the expression of anti-PD-1 scFv antibodies from the circRNAs significantly enhanced the cytotoxic T-cell response against HCC cells. In vivo studies revealed a significant reduction in tumor volume and prolonged survival in mice treated with the engineered circRNAs compared to controls.

Conclusions: Our findings highlight the potential of artificial circRNAs as a novel therapeutic strategy for HCC. By harnessing their ability to act as miRNA sponges and to express immunomodulatory proteins, these engineered circRNAs offer a promising approach to overcome the challenges associated with HCC therapy.

Keywords: anti-PD-1; circular RNA; hepatocellular carcinoma; immunotherapy; miRNA sponge; scFv antibody.

Figure 1

Synthesis and validation of circular RNA silencing miR-25 and expressing α-PD1 scFV. (A)Plasmid Sequence Design and Schematic Diagram of Engineered Circular RNA Synthesis. (B) Agarose gel confirmation of RNA circularization. (C) Sanger sequencing detection of circularization sites. (D) Western blot analysis showing the expression of α-PD1 in HEK293T and Hepa1–6 cells. (F, G) qPCR analysis demonstrating the effect of circRNA on miR-25 silencing. (H) Flow cytometry analysis of the blocking effect of circRNA on PD-1 expression in T cells. **, P < 0.01; ****, P < 0.0001.

Figure 2

Engineered circRNA as a miR-25 sponge inhibits invasion, migration, and proliferation in HCC. (A) Relative expression levels of miR-25 in normal tissues (n = 49) and HCC tumor tissues (n = 369) from the TCGA cohort. (B) Expression of miR-25 detected by RT-qPCR in 101 HCC patients with paired tumor and para-tumor tissues. (C) Representative results and quantitative analysis of transwell cell migration and invasion assays after silencing miR-25 in Hepa1–6 cells. (D) Wound healing assays validate the effects of silencing miR-25 in Hepa1–6 Cells. (E) Western blot detection of epithelial (E-cadherin), mesenchymal (Vimentin), and EMT related transcription factors (Slug and Snail) in Hepa1–6 Cells with Silencing of miR-25. (F) EdU assays detect cell proliferation after silencing miR-25 in Hepa1–6 cells. (G) Real-time cell analysis (RTCA) assays validate cell proliferation after silencing miR-25 in Hepa1–6 cells. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001.

Figure 3

Engineered circRNA affects angiogenesis in liver cancer cells. (A) Western Blot detection of exosomal markers. (B) qPCR test confirm the silencing efficiency of miRNA-25 in exosomes. (C) The effect of heap1–6 cells transfected with engineered circRNA on angiogenesis. (D) The effect of exosomes secreted by heap1–6 cells transfected with engineered circRNA on angiogenesis. (E) Western blotting detection of ZO-1, VEGFR in HUVEC cells with co-culture with transfected heap1–6 cells. *, P < 0.05; **, P < 0.01.

Figure 4

Anti-tumor efficacy of circRNAs in subcutaneous HCC model. (A) Treatment timeline of the experiment to evaluate the anti-tumor efficacy. (B) Body weight curves of mice during treatment. (C) Tumor growth curves of each group. (D) Average tumor growth curve of mice after treat with PBS, Ctrl, circSC25, circ-αPD1, circSC25-αPD1 (n = 5). (E) Tumor weight of each group. (F) Images of tumor size. (G) The silencing effect of miR-25 in tumor tissues. (H-J) Validation of PD-1, E-cadherin (E-Ca), and CD34 expression in tumor tissues by immunohistochemistry, Scale bars: 25 and 100 µm. (K) The representative immunofluorescence image of CD4⁺ and CD8⁺ T-cell infiltration in tumor tissues. Scale bars: 25 and 100 µm. *p < 0.05, **p < 0.01, ***p < 0.001.

Figure 5

Safety detection of artificial circular RNA. (A-H) Biochemical indicators of peripheral blood serum Triglyceride (TG), Glucose (Glu), Serum Creatinine (Crea), Urea, Alk aline phosphatase (AKP), Aspartateamino transferase (AST), Alanineamino transferase (ALT), Total bilirubin (TBil) after treatment with circRNAs; (B) Assessment of H&E staining of major organ pathology in HCC subcutaneous tumor-bearing mice after treatment with circRNAs. *p<0.05. (I) Indicate that the scale bar of the image is 50 µm.

Figure 6

Anti-tumor efficacy of circRNAs in orthotopic HCC model. (A) Treatment timeline of the experiment to evaluate the anti-tumor efficacy. (B) Kaplan–Meier survival curves of PBS, Ctrl, circSC25, circ-αPD1, circSC25-αPD1. (C) Tumor burden monitoring of PBS, Ctrl, circSC25, circ-αPD1, circSC25-αPD1 treated mice by bioluminescence imaging (n=5). (D, E) Serum cytokine interferon-γ and tumor necrosis factor-alpha (TNF-α) release after circRNAs administration via ELISA assays. (F) Flow cytometry analysis the percentage of matured dendritic cells (DCs) in lymph nodes after different treatment. (G) Flow cytometry analysis the percentage of central memory T cells in spleen after different treatment and the statistical analysis. (H) Flow cytometry analysis the percentage of CD8⁺ and CD4⁺ T cells in spleen after different treatment and the statistical analysis. (I) Flow cytometry analysis the PD1 expression level in CD8⁺ T cells in spleen after different treatment and the statistical analysis. *p < 0.05, **p < 0.01, ***p < 0.001.

Figure 7

Schematic diagram of the engineered circRNA serving as a molecular sponge for miR-25 and expressing anti-PD1 scFv to synergistically inhibit hepatocellular carcinoma.