English

• As the third leading cause of cancer related deaths, hepatocellular carcinoma (HCC) presents significant challenges due to limited effective therapeutic options and rapid disease progression [1, 2]. Curative options including surgery and liver transplantation are only viable for select patients [3]. Although tyrosine kinase inhibitors have been a breakthrough for advanced HCC, they offer only modest improvements in progression-free survival. Chemotherapy agents like oxaliplatin (OXA) have been found to decrease the population of mature dendritic cells and CD8⁺ T cells in HCC [4]. However, the heterogeneity of HCC poses substantial challenges to therapeutic interventions [5, 6]. Cancer metabolism focusing on alterations in metabolic processes in cancer cells compared to normal cells, offers new therapeutic perspectives [7].

  Recent studies have illuminated the interaction between metabolic and immunologic process [8]. Cancer cells are characterized by increased glucose uptake and aerobic glycolysis, leading to lactate production [9-12]. Lactate, associated with tumor recurrence and metastasis, influences various immune cell types, contributing to a tumor-suppressive microenvironment through mechanisms such as lactic acidosis, lactate-mediated intracellular signal transduction and histone modification [13-17]. Lactate dehydrogenase A (LDHA), which catalyzes the conversion of pyruvate to lactate, plays a crucial role in cancer cell proliferation and is implicated in tumorigenesis, metastasis, invasion, and immune evasion [18-20]. LDHA inhibitors are being widely investigated as promising therapeutic targets, which shows potential in reducing inflammation-induced effects, metastasis, and proliferation of cancer cells [16, 21]. LDHA inhibition may enhance the sensitivity of glioblastoma cells to chemotherapy, suggesting potential synergistic effects with agents such as OXA in HCC [22].

  The clinical application of LDHA inhibitors may be limited by non-selective toxicity and complex interaction. Delivery through gels could enhance targeting and facilitate controlled drug release [23-25]. While hydrogels and organogels are commonly used in cancer therapy, their capacity to encapsulate hydrophobic drugs is limited [26, 27]. Emulsion gels, which containing both oil and water phase, can encapsulate hydrophobic drugs effectively and have been developed to improve drug delivery [28].

  Here, we adopt the attractive Pickering emulsion gel (APEG) which is water-in-oil emulsion gel [29, 30] to encapsulate OXA and LDHA inhibitor, GSK2837808A (GSK) for drug-delivery to HCC model as shown in Fig. 1. Hydrophobic GSK is dissolved in the oil phase, and hydrophilic OXA is dissolved in the dispersed water droplets. The OXA + GSK@gel shows excellent lipase-triggered release and subsequent sustained release of OXA + GSK. Under the combined treatment, the OXA + GSK@gel activates potent T cell-mediated antitumor immune response to transform the "cold" tumor microenvironment (TME) to "hot" TME, suggesting that APEGs loaded with OXA + GSK are good drug delivery system to enhance anti-tumor therapy.

  Figure 1

  

  Figure 1.  Schematic of using APEGs to co-deliver OXA and GSK into HCC TME.

  DownLoad: Full-Size Img PowerPoint

  In this study, APEGs are designed and prepared by emulsifying the water phase into droplets in the continuous oil phase, as shown in Fig. 2A. Hydrophobic therapeutics can be dissolved in the oil phase while hydrophilic ones can be dissolved in the water phase, enabling encapsulation and delivery.

  Figure 2

  

  Figure 2.  Preparation and characterization of APEGs. (A) Preparation of APEGs by emulsifying the water phase and the oil phase. (B–D) Size distribution of APEGs at oil to water ratio of 1:2, 1:3, and 1:4. Inset is the optical microscope image of water droplets in the oil phase. (E) Fluorescent confocal microscope images of APEGs loaded with FITC dextran in the water phase and Nile red in oil phase. Scale bar: 50 µm. (F) 3D reconstruction showing the microstructure of APEGs from z-scans of fluorescent confocal microscope images. (G) Release profiles of FITC dextran-loaded droplets of APEGs in the presence of saline (blue upper triangle) and lipase (green lower triangle). (H) Release profiles of Nile red-loaded in the oil phase of APEGs in the presence of saline (blue upper triangle) and lipase (green lower triangle). (I) Phase diagram of APEGs prepared at oil to water ratio of 1:3, with different concentrations of shellac NPs in water phase and NH₂-PS-NH₂ telechelic polymers in oil phase. (J) Stability of OXA + GSK@gels stored at different temperatures.

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  APEGs with different ratio of oil to water are prepared, such as 1:2, 1:3, and 1:4. The droplets and size distribution of APEGs prepared at different oil to water ratio are shown in the Figs. 2B–D. As the volume of water phase increased from 67% to 80%, the diameter of droplet decreases from 40 µm to 23 µm.

  Fluorescein isothiocyanate (FITC) dextran and Nile red serve as the indicators of hydrophilic and hydrophobic therapeutics. Fluorescent confocal microscopy imaging indicates successfully loading of hydrophilic and hydrophobic therapeutics as shown in Fig. 2E, and the APEGs are water-in-oil type. To observe the microstructure of APEGs more directly, 3D reconstruction showing the APEGs from z-scans of fluorescent confocal microscope images in Fig. 2F, from which dispersed spherical droplets can be seen.

  The APEGs contained FITC dextran and Nile red can be released at the trigger of lipase at a linearly increasing and finish the release on the 12^th day, and almost no release in phosphate buffered saline (PBS) solution as shown in Figs. 2G and H, which show the APEG systems can realize the control and slow release. In addition, similar release profile can be found in a weak acid environment (PBS, pH 6.8) as shown in Fig. S1 (Supporting information), which can simulate the environment of tumor.

  To successful prepare APEGs, a minimum concentration of shellac NPs (0.0065 mg/g) and a minimum concentration of NH₂-PS-NH₂ telechelic polymers (4 mg/mL) are required to ensure gelation as shown in Fig. 2I.

  The stability of OXA + GSK@gel is investigated. OXA + GSK@gels are stable above freezing point, for example, from 4 ℃ to 50 ℃. Below freezing point, for example, at −20 ℃, APEGs are destroyed due to the crystallization of water. However, stable APEGs can be retrieved at room temperature simply by vortexing as shown in Fig. 2J. The OXA + GSK@gels are also stable against centrifugation speed less than 1500 rpm, though a small amount of oil is released out by compressing the water droplets under centrifugation above 1500 rpm as shown in Fig. S2 (Supporting information). The OXA + GSK@gels are stable in the solutions of PBS (pH 6.4), PBS (pH 7.0), and 10% fetal bovine serum (FBS) as shown in Fig. S3 (Supporting information), for no observable changes are observed in 48 h.

  The strain sweeps of APEGs prepared at different oil to water ratios are shown in Fig. 3A. The elastic modulus G′ is larger than the viscous modulus G″, showing the APEG systems of a non-flowable characteristics. As the strain gradually increased, the elastic modulus G′ decline while the viscous modulus G″ increase eventually. At the yield strain values as shown in Fig. 3B, the viscous modulus G″ became larger than the elastic modulus G′ and the APEG systems became flowable, which is a characteristic shear-thinning behavior. The loss factor (tanδ), the value of G″/G′, define gel's strength. As G″/G′ < 1, it would be accepted as gel. The loss factor (tanδ) further demonstrates the gel state and its transformation in a qualitative manner as shown in Fig. S4A (Supporting information).

  Figure 3

  

  Figure 3.  Viscoelastic properties and 3D printing of APEGs. (A) Strain sweeps of elastic modulus G′ and viscous modulus G″ at oil to water ratio of 1:2, 1:3, and 1:4, showing characteristic shear-thinning behaviors. The frequency is held constant at 1 rad/s. (B) Yield strain values extracted from strain sweep. (C) Frequency sweeps of elastic modulus G′ and viscous modulus G″ at oil to water ratio of 1:2, 1:3, and 1:4, showing characteristic shear-thinning behaviors. The strain was held constant at 1%. (D) G′ and G″ values at 10 rad/s. (E) Time sweeps of elastic modulus G′ and viscous modulus G″ at oil to water ratio of 1:3. (F) Temperature sweeps of elastic modulus G′ and viscous modulus G″ at oil to water ratio of 1:3 from 20 ℃ to 50 ℃. (G) The viscosity of APEGs at shear rate of 0.1–1000 s⁻¹. (H) Dependance of apparent viscosity on temperature from 20 ℃ to 50 ℃. (I–K) 3D printing of APEGs in air. (L) 3D printing of APEGs directly in water. Scale bar: 1 cm.

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  The elastic modulus G′ and the viscous modulus G″ of APEGs with angular frequency at different oil to water ratios are shown in Fig. 3C. The APEGs exhibit a degree of frequency dependence at different oil to water ratios, as G′ and G″ decreased with decreasing frequency. The elastic modulus G′ of APEGs at different oil to water ratios are greater than viscous modulus G″, showing a solid-like characteristics. The data confirm these hypotheses and suggest that increasing water phase leads to more stiff gels with constant solid-like properties as shown in Fig. 3D. The loss factor (tanδ) further demonstrates the gel state in a qualitative manner as shown in Fig. S4B (Supporting information).

  Based on the strain sweeps and frequency sweeps of APEGs at different oil to water ratios, as well as considering convenience for injection during subsequent administration, a finally ratio of 1:3 for oil to water is chosen. The elastic modulus G′ and the viscous modulus G″ of APEGs, prepared at oil to water ratio of 1:3, are also determined with the change of time and temperature. The viscosity with shear rate and temperature is determined when the ratio of oil to water is 1:3.

  In addition, the viscoelastic performance of APEGs is hardly compromised over time as shown in Fig. 3E. In temperature sweeps, the elastic modulus G′ shows little dependence on temperature. Additionally, the elastic modulus G′ remain greater than the viscous modulus G″, suggesting the stability of the APEG systems as shown in Fig. 3F. The viscosity curves of APEGs prepared under oil to water ratio of 1:3 have the characteristics of shear thinning as shown in Fig. 3G. When the shear rate is kept at 100 s⁻¹, the viscosity decreased with increasing temperature as shown in Fig. 3H.

  The shear-thinning viscoelastic properties and excellent stability make the APEGs is an ideal ink for 3D printing, which can directly print patterns in air, as shown in Figs. 3I–K. As the APEG system consist of water droplets in the oil phase, the APEGs can print in water directly, as shown in Fig. 3L.

  To validate the enhanced anti-tumor effects of OXA + GSK@gels in vivo, we establish the mouse model of HCC which is low-immunogenic by injecting Hep1–6 cells. The procedure and protocol of animal experiments are approved by the Institutional Animal Care and Use Committee, ZJCLA (No. ZJCLA-IACUC-20, 010, 245). When the tumor volume reaches about 30 mm³, tumor-bearing mice are divided into 6 groups, which receive peritumoral injection of 100 µL of PBS, gel, GSK@gel, OXA@gel, OXA + GSK or OXA + GSK@gel every 3 days for a total of 3 times as shown in Fig. 4A. Treatment with GSK@gel, OXA@gel, OXA + GSK or OXA + GSK@gel result in tumor growth inhibition in different degrees compared with PBS group and gel group according to the tumor growth curve. In addition, OXA + GSK@gel group shows the highest tumor inhibition in all these groups in Hep1–6 mice model as shown in Figs. 4B–D. Besides, the weights of dissected tumors further validate that treatment with GSK@gel, OXA@gel, OXA + GSK or OXA + GSK@gel can cause the tumor reduction, especially the OXA + GSK@gel group shows the most obvious effect as shown in Fig. 4E. Additionally, the body weight of HCC mice shows no significant variation during different treatment groups as shown in Fig. 4F. Taken together, these results suggest that APEGs loaded with OXA and GSK can significantly enhance the anti-tumor effect for HCC.

  Figure 4

  

  Figure 4.  APEG-mediated combination therapy for HCC in vivo. (A) Models showing the therapeutic schedule for the inoculation of tumors in mice and various treatments (PBS, gel, GSK@gel, OXA@gel, OXA + GSK and OXA + GSK@gel). (B) Photographs of tumors dissected from mice under different treatments after 10 days. (C) Tumor volume of tumor-bearing mice under different treatments over time. (D) Volume and (E) weight of tumors dissected from mice of different groups. (F) Weight of tumor-bearing mice under different treatments over time. Data are presented as mean ± SEM (n = 5). ^*P < 0.05, ^***P < 0.001. ns denotes not significant.

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  To elucidate the OXA and GSK loaded APEG-mediated therapeutic mechanism on HCC, we collect the tumors from Hep1–6 mouse model with different treatments and analyze the expression level of Ki67 which indicated for proliferation via immunohistochemical (IHC) staining. The results suggest that OXA + GSK@gel cause the least proliferation of tumor cells in the TME of HCC as shown in Fig. 5A. In addition, terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) staining on dissected tumors which indicated for apoptosis suggest that OXA + GSK@gel can enhance apoptosis of tumor cells as shown in Fig. 5B. This can further prove the combination treatment effects of OXA and GSK loaded with APEG.

  Figure 5

  

  Figure 5.  In vivo immune activation of GSK + Oxa@gel. (A) Histological examinations of dissected tumors using Ki67 staining. Scale bar: 200 µm. (B) Histological examinations of dissected tumors using TUNEL assay. Scale bar: 100 µm. (C) Gating strategy for detecting the ratio of TAMs by flow cytometry. Ratios of (D) TAMs, (E) M1-like TAMs, and (F) M2-like TAMs within the TME. Data are presented as mean ± SEM (n = 5). ^*P < 0.05, ^**P < 0.01, ^***P < 0.001.

  DownLoad: Full-Size Img PowerPoint

  Both OXA and GSK are shown to have an effect on the TME, while HCC is characterized by low immunogenicity [31-33]. To investigate the immune response activated by the co-delivery of OXA + GSK@gel in HCC TME, we apply flow cytometry to detect the immune cells, including lymphocytes, tumor-associated macrophages (TAMs), CD4⁺ T cells, CD8⁺ T cells and cytotoxic T lymphocytes (CTLs), in the TME of dissected tumors from each group. The gating strategies of TAMs are shown in Fig. 5C. The ratios of TAMs (CD11b⁺F4/80⁺ in CD45⁺) show no significant variation during each group as shown in Fig. 5D. The ratios of M1-like TAMs (dead dye⁻CD45⁺CD11b⁺F4/80⁺CD86⁺CD206⁻) in OXA + GSK@gel group show the highest ratio as shown in Fig. 5E. Meanwhile, the ratios of M2-like TAMs (dead dye⁻CD45⁺CD11b⁺F4/80⁺CD86⁻CD206⁺) in OXA + GSK@gel decrease significantly compared with PBS groups as shown in Fig. 5F. These results suggest that OXA + GSK@gel can polarize macrophages from M2 to M1 to some extent in the tumor immune microenvironment.

  Besides, we investigate the T cell mediated anti-tumor effects in TME. The gating strategies of detecting the ratio of CTLs by flow cytometry are shown in Fig. 6A. The ratios of CD45⁺ lymphocytes in drug treated groups is higher than PBS or gel treated groups. Among all the drug treated groups, the OXA + GSK@gel group has the highest proportion of CD45⁺ lymphocytes as shown in Fig. 6B. The ratios of CD3⁺ T cells (CD45⁺CD3⁺) and CD4⁺ T cells in different groups show no significant difference as shown in Figs. 6C and D. The OXA + GSK@gel can increase CD8⁺ T cells compared with the PBS or gel treated groups as shown in Fig. 6E. Meanwhile, OXA + GSK@gel can significantly increase the infiltration of CTLs in HCC TME as shown in Fig. 6F. These results illustrate that OXA + GSK@gel can increase the CTLs to activate the immune response in HCC TME, thus enhance the anti-tumor activity.

  Figure 6

  

  Figure 6.  In vivo immune activation of GSK + Oxa@gel. (A) Gating strategy for detecting the ratio of cytotoxic T lymphocytes (CTLs) by flow cytometry. Ratios of (B) CD45⁺ lymphocytes, (C) CD3⁺ T cells, (D) CD4⁺ T cells, (E) CD8⁺ T cells, and (F) CTLs within the TME. Data are presented as mean ± SEM (n = 5). ^*P < 0.05, ^**P < 0.01.

  DownLoad: Full-Size Img PowerPoint

  To investigate the safety of OXA + GSK@gel in vivo, we perform hematoxylin-eosin (H & E) staining on major organs, including the heart, liver, spleen, lung and kidney, from mice treated with PBS, gel, GSK@gel, OXA@gel, OXA + GSK and OXA + GSK@gel. As shown in Fig. 7, compared with PBS group, there is no distinguishable damage observed in HCC model mice with different treatments. This indicate that the APEGs loaded with OXA and GSK possess good biocompatibility, which provides a new possibility for the treatment of HCC.

  Figure 7

  

  Figure 7.  Safety evaluation of various treatments. H & E-stained images of heart, liver, spleen, lung and kidney of mice treated with PBS, gel, GSK@gel, OXA@gel, OXA + GSK and OXA + GSK@gel. Scale bar: 200 µm.

  DownLoad: Full-Size Img PowerPoint

  Gels have been widely studied for their role in tumor treatment, capable of carry different types of drugs, such as chemotherapy drugs, small molecule inhibitors, and immunosuppressive drugs. However, traditional gels face limitations in drug control and release. Therefore, it is necessary to construct different structures of gels to improve their drug delivery ability. Here, we construct water-in-oil APEGs, which can carry both hydrophilic and hydrophobic drugs. The experimental results show that the APEG has good stability, enable slow drug release, and exhibit good biocompatibility. Moreover, co-loaded of OXA and the LDHA inhibitor GSK in the APEG system shows a stronger anti-tumor effect in mice, which could effectively inhibit tumor cell proliferation and promote apoptosis.

  OXA combined with 5-fluorouracil and leucovorin can be used as the first-line treatment for advanced HCC, but the drug resistance limits the therapeutic effect of platinum in HCC [34-36]. LDHA serves as a biomarker for poor prognosis in various types of solid tumor and plays an important role in regulating immune function [37]. Here we adopt OXA and GSK, to investigate the combined effect of chemotherapy and LDHA inhibitors in HCC [4, 38]. OXA and GSK loaded in APEGs significantly enhance the anti-tumor effect, resulting in increased apoptosis and decreased proliferation of tumor cells.

  Some studies have shown that the use of OXA can increase the ratios of M1 macrophages and reduce the M2 macrophages [39-41]. LDHA is found to alter the cancerous microenvironment and impede the antitumor effect of immune cells by increasing the level of lactate [37]. Detailly, LDHA enhances immune-suppressive cells while inhibiting cytolytic cells such as natural killer cells and cytotoxic T lymphocytes, thereby contributing to chemotherapy resistance [37, 42, 43]. LDHA inhibition also prevents M2-like polarization of TAM by decreasing the level of lactate. GSK which is delivered into tumors by hyaluronic acid (HA)-modified metal-phenolic nanomedicine (HPP-Ca@GSK) can inhibit aerobic glycolysis of cancer cells and produce high glucose and low lactate conditions with increased activation and infiltration of CD8⁺ T cells [44]. In this context, a potential combination of LDHA inhibitors and chemotherapy is suggested to generate a combined effect to inhibit tumor progression and proliferation. Our flow analysis reveals a regulatory effect of OXA + GSK@gel on the HCC TME, which M1 increased, M2 decreased, and the infiltration of CD8⁺ T cells increased, thereby providing better anti-tumor effect. The enhanced cell-killing ability of combining LDHA inhibition with chemotherapy, including paclitaxel and OXA, has been demonstrated in breast cancer and colorectal cancer [45, 46]. Microenvironmental factors including M2-like polarization and the ratio of the lymphocytes are shown to regulate the response to OXA [4, 46]. Silencing LDHA has been proved to enhance the chemotherapeutic effect of OXA in colorectal cancer by amplifying the autophagy induced by OXA and inhibit the M2-like polarization of TAM [46]. These verify the combined impact of OXA and LDHA inhibitors on immune microenvironment [37, 42].

  In our study, we use the clinical commonly used iodized oil to prepare the water-in-oil mode of APEGs, which increase the biocompatibility. The study is important because this APEG effectively deliver two drugs simultaneously, solving the dissolution problem of hydrophobic drug GSK. Besides, by detecting the TME of HCC after OXA + GSK@gel treatment, we confirm that the combination of OXA and GSK can reverse the polarization of M2-like macrophages, up-regulate the infiltration of T cells, increase the activated CTL, and inhibit the acidic TME caused by lactate, thereby achieving a better tumor treatment effect.

  While this study has demonstrated the therapeutic effect of OXA + GSK@gel, it is essential to acknowledge our limitations and outline potential directions for future research. Firstly, the synergistic effects of OXA and GSK can be investigated to elucidate their mutual mechanisms of action further. Understanding whether these drugs interact synergistically can pave the way for more targeted and effective treatment strategies. Secondly, we can add additional research on memory T cells in the TME of HCC mouse models to explore the impact of OXA + GSK@gel on tumor recurrence in mice. By exploring these further researches, we can not only address the current study's limitations but also expand our understanding of the intricate mechanisms underlying oncological treatments and potentially enhance therapeutic outcomes in the future.

  Declaration of competing interest

  The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

  CRediT authorship contribution statement

  Chanqi Ye: Writing – original draft, Software, Methodology, Formal analysis. Jia Zhang: Writing – original draft, Software, Methodology, Investigation. Jie Shen: Writing – review & editing, Methodology, Data curation. Ruyin Chen: Writing – original draft, Methodology. Qiong Li: Formal analysis, Data curation. Peng Zhao: Writing – review & editing, Funding acquisition, Conceptualization. Dong Chen: Writing – review & editing, Supervision, Funding acquisition, Conceptualization. Jian Ruan: Writing – review & editing, Supervision, Project administration, Funding acquisition, Conceptualization.

  Acknowledgments

  This work was supported by Natural Science Foundation of Zhejiang Province (Nos. LY20H160033, LY22H160019), National Key Research and Development Program of China (No. YS2021YFC3000089), Zhejiang Province Science and Technology Plan Project (No. 2024C03175), National Natural Science Foundation of China (Nos. 82074208, 22278352, 82473004).

  Supplementary materials

  Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.cclet.2024.110519.

  
  
• 1. [1]

     H. Sung, J. Ferlay, R.L. Siegel, et al., CA Cancer J. Clin. 71 (2021) 209–249. doi: 10.3322/caac.21660

  2. [2]

     D. Tang, S. Dong, N. Ma, et al., Hepatology. 51 (2010) 1255–1263. doi: 10.1002/hep.23451

  3. [3]

     A. Benson, M. D'Angelica, D. Abbott, et al., J. Natl. Compr. Canc. Netw. 19 (2021) 541–565. doi: 10.6004/jnccn.2021.0022

  4. [4]

     H. Zhu, Y. Shan, K. Ge, et al., Cell. Oncol. 43 (2020) 1203–1214. doi: 10.1007/s13402-020-00552-2

  5. [5]

     R. Dhanasekaran, Semin. Liver Dis. 41 (2021) 9–18.

  6. [6]

     J. Sheng, J. Wu, X. Yin, et al., Chin. Chem. Lett. 34 (2023) 107738.

  7. [7]

     S.Y. Kim, Arch. Pharm. Res. 38 (2015) 299–301.

  8. [8]

     E.L. Pearce, E.J. Pearce, Immunity 38 (2013) 633–643.

  9. [9]

     S. Ganapathy-Kanniappan, J.F. Geschwind, et al., Mol. Cancer 12 (2013) 152. doi: 10.1186/1476-4598-12-152

  10. [10]

      V.L. Payen, E. Mina, V.F. Van Hée, et al., Mol. Metab. 33 (2020) 48–66.

  11. [11]

      M.J. Watson, P.D.A. Vignali, S.J. Mullett, et al., Nature 591 (2021) 645–651. doi: 10.1038/s41586-020-03045-2

  12. [12]

      M.M.G. Kes, J. Van den Bossche, A.W. Griffioen, et al., Biochim. Biophys. Acta Rev. Cancer 1874 (2020) 188427.

  13. [13]

      P. Sonveaux, F. Végran, T. Schroeder, et al., J. Clin. Invest. 118 (2008) 3930–3942.

  14. [14]

      I. San-Millán, G.A. Brooks, Carcinogenesis 38 (2017) 119–133.

  15. [15]

      S. Walenta, M. Wetterling, M. Lehrke, et al., Cancer Res. 60 (2000) 916–921.

  16. [16]

      G. Bononi, S. Masoni, V. Di Bussolo, et al., Semin. Cancer Biol. 86 (2022) 325–333.

  17. [17]

      Z.H. Wang, W.B. Peng, P. Zhang, et al., EBioMedicine 73 (2021) 103627.

  18. [18]

      F. Khan, Y. Lin, H. Ali, et al., Nat. Commun. 15 (2024) 1987.

  19. [19]

      P. Miao, S. Sheng, X. Sun, et al., IUBMB life 65 (2013) 904–910. doi: 10.1002/iub.1216

  20. [20]

      V. Jurisic, S. Radenkovic, G. Konjevic, et al., Adv. Exp. Med. Biol. 867 (2015) 115–124. doi: 10.1007/978-94-017-7215-0_8

  21. [21]

      V.R. Fantin, J. St-Pierre, P. Leder, Cancer Cell 9 (2006) 425–434.

  22. [22]

      M. Koukourakis, A. Tsolou, S. Pouliliou, et al., Biochem. Biophys. Res. Commun. 491 (2017) 932–938.

  23. [23]

      S Kim, H Lee, B Jeong, Carbohydr. Polym. 291 (2022) 119559.

  24. [24]

      L. Zhai, Y. Shi, Y. Yan, et al., Chin. Chem. Lett. 34 (2023) 108104.

  25. [25]

      H. Sun, H. Zhao, R. Yin, et al., Chin. Chem. Lett. 36 (2025) 110067. doi: 10.1016/j.cclet.2024.110067

  26. [26]

      S.A. Mortazavi, R. Aboofazeli, Iran. J. Pharm. Res. 2 (2003) 135–140.

  27. [27]

      A. Joseph, J. Pharm. Sci. 79 (1990) 1044.

  28. [28]

      M. Talat, M. Zaman, R. Khan, et al., Drug Dev. Ind. Pharm. 47 (2021) 1193–1199. doi: 10.1080/03639045.2021.1993889

  29. [29]

      X. Dai, J. Zhang, X. Bao, et al., Adv. Mater. 35 (2023) e2303542.

  30. [30]

      B. Wu, C. Yang, Q. Xin, et al., Adv. Mater. 33 (2021) e2102362.

  31. [31]

      R. Donne, A. Lujambio, Hepatology 77 (2023) 1773–1796. doi: 10.1002/hep.32740

  32. [32]

      Y.X. Zhang, Y.Y. Zhao, J. Shen, et al., Nano Lett. 19 (2019) 2774–2783. doi: 10.1021/acs.nanolett.8b04296

  33. [33]

      Y. Ma, C. Guo, X. Wang, et al., J. Exp. Clin. Cancer Res. 42 (2023) 237. doi: 10.2186/jpr.jpr_d_23_00098

  34. [34]

      S. Qin, Y. Bai, H.Y. Lim, et al., J. Clin. Oncol. 31 (2013) 3501–3508.

  35. [35]

      X. Yin, B. Tang, J.H. Li, et al., J. Exp. Clin. Cancer Res. 36 (2017) 166.

  36. [36]

      L. Goyal, H. Zheng, T.A. Abrams, et al., Clin. Cancer Res. 25 (2019) 80–89. doi: 10.1158/1078-0432.ccr-18-0847

  37. [37]

      J. Ding, J.E. Karp, A. Emadi, Cancer Biomark. 19 (2017) 353–363.

  38. [38]

      A.X. Zhu, L.S. Blaszkowsky, D.P. Ryan, et al., J. Clin. Oncol. 24 (2006) 1898–1903.

  39. [39]

      F. Li, X. Zheng, X. Wang, et al., Transl. Oncol. 14 (2021) 101202.

  40. [40]

      S.J. Park, S. Kweon, M.K. Moyo, et al., Biomaterials 310 (2024) 122625.

  41. [41]

      E. Limagne, M. Thibaudin, L. Nuttin, et al., Cancer Immunol. Res. 7 (2019) 1958–1969. doi: 10.1158/2326-6066.cir-19-0228

  42. [42]

      K. Singer, M. Kastenberger, E. Gottfried, et al., Int. J. Cancer 128 (2011) 2085–2095. doi: 10.1002/ijc.25543

  43. [43]

      Z. Husain, Y. Huang, P. Seth, et al., J. Immunol. 191 (2013) 1486–1495. doi: 10.4049/jimmunol.1202702

  44. [44]

      J. Yan, W. Li, H. Tian, et al., ACS Nano 17 (2023) 14667–14677. doi: 10.1021/acsnano.3c02428

  45. [45]

      M. Zhou, Y. Zhao, Y. Ding, et al., Mol. Cancer 9 (2010) 33.

  46. [46]

      L. Hu, S. Huang, G. Chen, et al., ACS Appl. Mater. Interfaces 14 (2022) 31625–31633. doi: 10.1021/acsami.2c05841

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  Figure 1  Schematic of using APEGs to co-deliver OXA and GSK into HCC TME.

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  Figure 2  Preparation and characterization of APEGs. (A) Preparation of APEGs by emulsifying the water phase and the oil phase. (B–D) Size distribution of APEGs at oil to water ratio of 1:2, 1:3, and 1:4. Inset is the optical microscope image of water droplets in the oil phase. (E) Fluorescent confocal microscope images of APEGs loaded with FITC dextran in the water phase and Nile red in oil phase. Scale bar: 50 µm. (F) 3D reconstruction showing the microstructure of APEGs from z-scans of fluorescent confocal microscope images. (G) Release profiles of FITC dextran-loaded droplets of APEGs in the presence of saline (blue upper triangle) and lipase (green lower triangle). (H) Release profiles of Nile red-loaded in the oil phase of APEGs in the presence of saline (blue upper triangle) and lipase (green lower triangle). (I) Phase diagram of APEGs prepared at oil to water ratio of 1:3, with different concentrations of shellac NPs in water phase and NH₂-PS-NH₂ telechelic polymers in oil phase. (J) Stability of OXA + GSK@gels stored at different temperatures.

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  Figure 3  Viscoelastic properties and 3D printing of APEGs. (A) Strain sweeps of elastic modulus G′ and viscous modulus G″ at oil to water ratio of 1:2, 1:3, and 1:4, showing characteristic shear-thinning behaviors. The frequency is held constant at 1 rad/s. (B) Yield strain values extracted from strain sweep. (C) Frequency sweeps of elastic modulus G′ and viscous modulus G″ at oil to water ratio of 1:2, 1:3, and 1:4, showing characteristic shear-thinning behaviors. The strain was held constant at 1%. (D) G′ and G″ values at 10 rad/s. (E) Time sweeps of elastic modulus G′ and viscous modulus G″ at oil to water ratio of 1:3. (F) Temperature sweeps of elastic modulus G′ and viscous modulus G″ at oil to water ratio of 1:3 from 20 ℃ to 50 ℃. (G) The viscosity of APEGs at shear rate of 0.1–1000 s⁻¹. (H) Dependance of apparent viscosity on temperature from 20 ℃ to 50 ℃. (I–K) 3D printing of APEGs in air. (L) 3D printing of APEGs directly in water. Scale bar: 1 cm.

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  Figure 4  APEG-mediated combination therapy for HCC in vivo. (A) Models showing the therapeutic schedule for the inoculation of tumors in mice and various treatments (PBS, gel, GSK@gel, OXA@gel, OXA + GSK and OXA + GSK@gel). (B) Photographs of tumors dissected from mice under different treatments after 10 days. (C) Tumor volume of tumor-bearing mice under different treatments over time. (D) Volume and (E) weight of tumors dissected from mice of different groups. (F) Weight of tumor-bearing mice under different treatments over time. Data are presented as mean ± SEM (n = 5). ^*P < 0.05, ^***P < 0.001. ns denotes not significant.

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  Figure 5  In vivo immune activation of GSK + Oxa@gel. (A) Histological examinations of dissected tumors using Ki67 staining. Scale bar: 200 µm. (B) Histological examinations of dissected tumors using TUNEL assay. Scale bar: 100 µm. (C) Gating strategy for detecting the ratio of TAMs by flow cytometry. Ratios of (D) TAMs, (E) M1-like TAMs, and (F) M2-like TAMs within the TME. Data are presented as mean ± SEM (n = 5). ^*P < 0.05, ^**P < 0.01, ^***P < 0.001.

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  Figure 6  In vivo immune activation of GSK + Oxa@gel. (A) Gating strategy for detecting the ratio of cytotoxic T lymphocytes (CTLs) by flow cytometry. Ratios of (B) CD45⁺ lymphocytes, (C) CD3⁺ T cells, (D) CD4⁺ T cells, (E) CD8⁺ T cells, and (F) CTLs within the TME. Data are presented as mean ± SEM (n = 5). ^*P < 0.05, ^**P < 0.01.

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  Figure 7  Safety evaluation of various treatments. H & E-stained images of heart, liver, spleen, lung and kidney of mice treated with PBS, gel, GSK@gel, OXA@gel, OXA + GSK and OXA + GSK@gel. Scale bar: 200 µm.

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