Abstract

   Hepatocellular carcinoma (HCC) is a major complication of chronic
   hepatitis B (CHB), with macrophage M2 polarization playing a critical
   role in shaping the tumor-promoting hepatic immune microenvironment.
   Sirtuin 1 (SIRT1) has been implicated in immune modulation and liver
   carcinogenesis. This study investigates the potential of Mimetic
   Nanoparticles (MNPs) for delivering SIRT1 inhibitors to regulate
   macrophage polarization and remodel the hepatic immune
   microenvironment, aiming to prevent HCC development post-CHB. A
   transgenic mouse model of CHB was established, and RNA sequencing
   (RNA-seq) and proteomics analyses revealed significant dysregulation of
   genes associated with M2 macrophage polarization, particularly SIRT1.
   Functional enrichment analysis highlighted key pathways, including
   PI3K-Akt and NF-κB, that contribute to CHB-driven immune alterations.
   Synthesized and characterized MNPs successfully delivered SIRT1
   inhibitors, effectively inhibiting M2 macrophage polarization in vitro.
   In vivo administration of MNPs-SIRT1-FN significantly reduced M2
   macrophage infiltration and suppressed tumor growth. These findings
   suggest that nanoparticle-mediated SIRT1 inhibition is a promising
   strategy for immunomodulation and HCC prevention in CHB patients. This
   study provides novel insights into nanoparticle-based immunotherapy for
   CHB-related HCC and highlights a potential therapeutic avenue for liver
   cancer prevention.

Supplementary Information

   The online version contains supplementary material available at
   10.1186/s12951-025-03447-2.

   Keywords: Nanoparticles, SIRT1 Inhibition, Macrophage polarization,
   Chronic hepatitis B, Hepatocellular carcinoma

Graphical Abstract

   [42]graphic file with name 12951_2025_3447_Fig7_HTML.jpg

Supplementary Information

   The online version contains supplementary material available at
   10.1186/s12951-025-03447-2.

Introduction

   Hepatocellular carcinoma (HCC) is one of the leading causes of
   cancer-related deaths worldwide, with high incidence and mortality
   rates [[43]1–[44]3]. This is particularly evident in developing
   countries, where the prevalence of chronic hepatitis B (CHB)
   significantly increases HCC incidence [[45]4, [46]5]. Although
   antiviral treatments have made considerable progress in controlling
   hepatitis B virus (HBV) infections and reducing the incidence of acute
   hepatitis, CHB patients remain at high risk for cirrhosis and HCC
   [[47]6–[48]8]. Notably, the chronic inflammatory response and
   persistent viral replication in CHB are key factors driving the
   progression to HCC [[49]9–[50]11]. Therefore, exploring new therapeutic
   strategies to prevent CHB from progressing to HCC is of significant
   clinical importance, as it can improve patient survival rates and
   reduce the healthcare burden associated with HCC [[51]12, [52]13].

   Currently, the primary treatment options for HCC include surgical
   resection, radiation therapy, chemotherapy, and targeted therapy
   [[53]14, [54]15]. However, these conventional treatments often come
   with significant side effects, and their efficacy varies among
   individuals [[55]16–[56]18]. In particular, for advanced-stage HCC,
   high tumor recurrence rates and drug resistance severely limit
   treatment effectiveness [[57]19–[58]21]. Although surgical resection is
   the preferred treatment for early-stage HCC, many patients are
   diagnosed at intermediate or advanced stages, missing the optimal
   window for surgery [[59]22–[60]24]. Radiation and chemotherapy can
   damage normal liver tissue, increasing patient discomfort [[61]14,
   [62]25, [63]26]. While targeted therapy has improved treatment outcomes
   to some extent, issues with target specificity and patient tolerance
   remain significant challenges. Consequently, the search for new methods
   to effectively regulate the hepatic immune microenvironment has become
   a focal point in HCC treatment research.

   In recent years, the advent of immunotherapy has brought new hope for
   HCC patients. In particular, the combination of immune checkpoint
   inhibitors (ICIs) with macromolecular anti-angiogenesis drugs has made
   milestone progress [[64]27]. The global multicenter phase III clinical
   trial IMBrave-150 has shown that compared to sorafenib, the combination
   of atezolizumab and bevacizumab significantly improves the median
   overall survival (MoS) of advanced hepatocellular carcinoma (HCC)
   patients. Specifically, the MoS for the “T + A” regimen was 19.2
   months, while sorafenib was 13.4 months, showing a statistically
   significant difference (P < 0.001) [[65]28, [66]29]. In the
   perioperative period, immunotherapy has also demonstrated its unique
   advantages. The IMbrave050 study, as the first global trial exploring
   the use of anti-angiogenesis combined with immunotherapy for adjuvant
   treatment in HCC, provides the most compelling evidence available
   [[67]30].

   Macrophages play a crucial role in the hepatic immune microenvironment
   and can be categorized into M1 and M2 types based on their functional
   states [[68]31, [69]32]. M1 macrophages exhibit pro-inflammatory
   properties by secreting large amounts of inflammatory cytokines such as
   TNF-α and IL-1β, which are involved in pathogen clearance and tissue
   repair [[70]33–[71]35]. Conversely, M2 macrophages possess
   anti-inflammatory and tissue repair functions, primarily by secreting
   anti-inflammatory cytokines such as IL-10 and TGF-β, thereby promoting
   tissue regeneration and repair [[72]36–[73]38]. In the context of CHB
   and HCC, excessive polarization of M2 macrophages is closely associated
   with HCC development. Their immunosuppressive role within the tumor
   microenvironment enables tumor cells to evade immune surveillance
   [[74]39–[75]41]. Therefore, regulating macrophage polarization,
   particularly inhibiting M2 polarization, may offer new strategies for
   the prevention and treatment of HCC.

   In recent years, mimetic nanoparticles (MNPs) have shown immense
   potential in drug delivery [[76]42, [77]43]. MNPs exhibit excellent
   biocompatibility and targeting capabilities, enabling efficient drug
   delivery to specific cells or tissues, thereby enhancing therapeutic
   efficacy and reducing side effects [[78]44]. This study aims to use
   MNPs to deliver Sirtuin 1 (SIRT1) inhibitors, modulating macrophage M2
   polarization to remodel the hepatic immune microenvironment, thereby
   preventing the progression of HCC following CHB. SIRT1, a deacetylase,
   plays a critical role in various biological processes (BP), including
   inflammation, metabolic regulation, and apoptosis. Inhibiting SIRT1 can
   effectively suppress macrophage M2 polarization, reduce immune
   suppression in the tumor microenvironment, and consequently inhibit
   tumor growth and metastasis.

   The aim of this study is to investigate the mechanisms by which MNPs
   delivering SIRT1 inhibitors regulate macrophage M2 polarization and
   remodel the hepatic immune microenvironment. Using a CHB mouse model,
   we systematically evaluated the efficacy and molecular mechanisms of
   MNPs-SIRT1-FN in preventing the progression of HCC. Initially,
   high-throughput RNA Sequencing (RNA-seq) and proteomics analyses were
   conducted to identify Differentially Expressed Genes (DEGs) and
   proteins in CHB mice and their roles in hepatic pathology.
   Subsequently, bioinformatics tools were employed to screen and perform
   functional enrichment analysis of these DEGs and proteins, revealing
   key signaling pathways and BP. Finally, in vivo and in vitro
   experiments validated the inhibitory effects of MNPs-SIRT1-FN on
   macrophage M2 polarization and their preventive and therapeutic
   efficacy against HCC in the context of CHB. This study not only offers
   new strategies and approaches for the prevention and treatment of HCC
   but also highlights the potential of biomimetic nanotechnology in tumor
   immunotherapy, providing robust scientific evidence for clinical
   application. This research strategy could serve as a reference for
   treating other chronic inflammation-related cancers, possessing broad
   scientific and clinical significance.

Materials and methods

Ethics statement

   All animal experiments conducted in this study strictly adhered to the
   “Guidelines for the Scientific Use of Animals” issued by the Ministry
   of Science and Technology. Prior to the experiments, approval was
   obtained from the Institutional Animal Care and Use Committee (approval
   number: BUA812403010). All procedures were designed to minimize animal
   suffering and to ensure that the number of animals used was the minimum
   required to achieve scientific validity.

Construction of a CHB-Induced HCC mouse model

   Six- to eight-week-old transgenic C57BL/6 mice, specifically expressing
   the HBV gene, were obtained from Charles River Laboratories. The mice
   were housed under specific pathogen-free (SPF) conditions, with a
   12-hour light/dark cycle and ad libitum access to food and water.
   Initially, liver damage was induced by intraperitoneal injection of
   diethylnitrosamine (DEN, 25 mg/kg). Subsequently, the HBV transgenic
   mice continued expressing the HBV gene to simulate the pathological
   state of chronic hepatitis B. To enhance the inflammatory response and
   promote model development, the immune microenvironment was modulated
   using immunoregulators (PD-1/PD-L1 antibodies). During this period,
   mice were regularly monitored for changes in body weight, liver
   function indicators (ALT, AST), and external symptoms (reduced activity
   or changes in fur sheen). The mice were randomly divided into two
   groups: the treatment group (receiving injections of SIRT1
   inhibitor-loaded MNPs) and the control group, with 10 mice in each
   group. The treatment group mice received tail vein injections of the
   MNPs, and their body weight and behavior were monitored for 24 h
   post-injection, and after 4 weeks of treatment, the mice were
   euthanized, and liver tissues were harvested for further experiments.
   The in vivo experimental procedure is detailed in Figure [79]S1.

Liver function and histological analysis

   Every two weeks, blood samples were collected from the tail vein, and
   levels of ALT and AST were measured using a Beckman Coulter automated
   biochemical analyzer. At the end of the experiment, all mice were
   euthanized with an overdose of carbon dioxide. Liver tissues were
   collected for Hematoxylin and Eosin (H&E) staining and
   immunohistochemical analysis. Immunohistochemistry was performed using
   antibodies against SIRT1 and CD206 (Abcam, UK), and images were
   captured and analyzed using a Nikon Eclipse Ti microscope (Nikon,
   Japan). Concurrently, antibodies targeting F4/80 were used in
   conjunction with antibodies against CD206 and CD80 (Abcam, UK) for
   immunofluorescence co-localization staining. The co-localization of the
   staining was observed using a confocal laser scanning microscope (CLSM,
   Leica TCS SP8).

RNA-seq

   Total RNA was extracted from the liver tissues of both control and CHB
   groups using Trizol reagent (15596026, Invitrogen, USA). The integrity
   and purity of the extracted RNA were assessed with an Agilent 2100
   Bioanalyzer (G2939B, Agilent, USA), ensuring an RNA integrity number
   (RIN) of no less than 7.0. High-throughput sequencing was performed on
   the Illumina HiSeq platform (Illumina, USA). The sequencing data
   underwent quality control and were aligned to the mouse reference
   genome using HISAT2 software. Gene expression levels were quantified
   with HTSeq-count. DEGs were identified using DESeq2 with criteria of
   |logFC| > 1 and p < 0.05. The DEGs between the control and disease
   groups were visualized using volcano plots generated by the “ggplot2”
   package. All analyses were conducted in R version 4.3.1 (R Foundation
   for Statistical Computing).

Immune infiltration

   Based on our expression profile, we used the R software packages
   “e1071” and “preprocessCore” in combination with the CIBERSORT
   algorithm to score 22 types of immune infiltrating cells. Statistical
   analysis and visualization were conducted using R version 4.2.1, with
   the “ggplot2” package employed for visualization.

Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG)
enrichment analysis

   For gene set functional enrichment analysis, we utilized the R package
   org.Hs.eg.db (version 3.1.0) to obtain GO annotations for the genes,
   which served as the background for mapping the genes to the background
   set. The R package clusterProfiler (version 3.14.3) was used to perform
   the enrichment analysis and generate the gene set enrichment results.
   For KEGG pathway enrichment analysis, we retrieved the latest KEGG
   pathway gene annotations using the KEGG REST API, which also served as
   the background for mapping genes to the background set. The R package
   clusterProfiler (version 3.14.3) was again employed to conduct the
   enrichment analysis and obtain the results. The parameters were set
   with a minimum gene set size of 5, a maximum gene set size of 5000, a
   p-value of < 0.05, and an FDR of < 0.25. Data visualization was
   performed using the ggplot2 package.

Proteomics analysis

   Total proteins were extracted from liver tissues of both the CHB and
   control groups using RIPA buffer (with protease inhibitors, Thermo
   Fisher Scientific, USA). Protein quantification was performed using the
   BCA Protein Assay Kit (23227, Thermo Fisher Scientific, USA). After
   enzymatic digestion, protein samples were analyzed using LC-MS/MS on a
   Q Exactive HF mass spectrometer (Thermo Fisher Scientific, USA). The
   proteomics data were processed with Proteome Discoverer software
   (Thermo Fisher Scientific, USA) to identify protein expression changes
   associated with HCC development and immune regulation.

   Proteins with a |logFC| > 1 and a p-value < 0.05 in the Student’s
   t-test were considered significantly differentially expressed proteins
   (DEPs).

Materials and reagents

   The materials and reagents used in this study include mesoporous silica
   (MCM-41) nanoparticles (Sigma-Aldrich, Product No. 691306); SIRT1
   inhibitor EX-527 (Sigma-Aldrich, Product No. SML0546);
   3-aminopropyltriethoxysilane (APTES) (Sigma-Aldrich, Product No.
   440140); 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride
   (EDC) (Sigma-Aldrich, Product No. E6383); N-hydroxysuccinimide (NHS)
   (Sigma-Aldrich, Product No. 130672); and fibronectin (FN)
   (Sigma-Aldrich, Product No. F2006). Other necessary chemical reagents
   and solvents, such as ethanol, dimethyl sulfoxide (DMSO), and
   phosphate-buffered saline (PBS), were also used.

Preparation of nanoparticles

   Mesoporous silica was selected for this study due to its high surface
   area, excellent biocompatibility, tunable pore size, and ability to
   provide controlled drug release [[80]45]. Additionally, its mature
   surface functionalization strategies allow for efficient loading and
   targeted delivery of SIRT1 inhibitors [[81]46]. At room temperature,
   MCM-41 nanoparticles were dispersed in anhydrous ethanol, followed by
   the addition of APTES (5% v/v). The mixture was stirred for 12 h to
   achieve amination. The aminated nanoparticles were then collected by
   centrifugation (10,000 rpm, 10 min) and washed multiple times with
   anhydrous ethanol. Finally, the nanoparticles were vacuum-dried at
   60 °C.

SIRT1 inhibitor loading

   Aminated nanoparticles were dispersed in PBS, followed by the addition
   of EDC and NHS (molar ratio 1:1, final concentration 10 mM) and stirred
   for 30 min to activate the carboxyl groups. Given that EX527 shows high
   specificity for SIRT1 [[82]47], and has been a commonly used inhibitor
   in SIRT1 research in recent years [[83]48], we chose EX-527 as the
   SIRT1 inhibitor. The SIRT1 inhibitor EX-527 (final concentration 5 mM)
   was then added, and the reaction proceeded at room temperature for 12 h
   to form a covalent bond, loading the inhibitor onto the nanoparticle
   surface. The nanoparticles were collected by centrifugation and washed
   multiple times with PBS. The loaded nanoparticles were stored at 4 °C.

Fibronectin modification

   Nanoparticles loaded with SIRT1 inhibitors were dispersed in PBS,
   followed by the addition of EDC and NHS (molar ratio 1:1, final
   concentration 10 mM). The mixture was stirred for 30 min to activate
   the carboxyl groups. Fibronectin (final concentration 2 mg/mL) was then
   added, and the reaction was allowed to proceed at room temperature for
   12 h to covalently attach the fibronectin to the nanoparticle surface.
   The resulting fibronectin-modified MNPs (MNPs-SIRT1-FN) were obtained
   through multiple rounds of centrifugation and washing with PBS. The
   modified nanoparticles were stored at 4 °C.

Characterization

   The morphology and size of the nanoparticles were observed using
   Transmission Electron Microscopy (TEM, JEOL JEM-2100 F). The particle
   size distribution and surface charge of the nanoparticles were measured
   using Dynamic Light Scattering (DLS, Malvern Zetasizer Nano ZS). The
   chemical modifications on the surface of the nanoparticles were
   analyzed by Fourier Transform Infrared Spectroscopy (FTIR, Thermo
   Nicolet iS50). The thermal stability of the nanoparticles was assessed
   using Thermogravimetric Analysis (TGA, TA Instruments Q500).

Encapsulation efficiency determination

   The determination of encapsulation efficiency is conducted using
   high-performance liquid chromatography (HPLC, HPLC 1260, Agilent).
   Initially, a series of EX-527 standard solutions at different
   concentrations are prepared and analyzed via HPLC to establish a
   standard curve between concentration and peak area. Subsequently, the
   nanoparticles are treated with an appropriate solvent to release the
   encapsulated EX-527, and its concentration is determined using HPLC.
   Encapsulation efficiency (EE%) and drug loading (DL%) are calculated
   using formulas (1) and (2), respectively, by comparing the total amount
   of EX-527 added with the amount detected by HPLC, providing
   quantitative information about the drug encapsulation performance. Each
   value is measured three times.

   Formula (1): Inline graphic

   Formula (2): Inline graphic

Cell culture

   Mouse macrophage cell line RAW 264.7 (ATCC TIB-71) was obtained for the
   study. The cells were cultured in DMEM medium supplemented with 10%
   fetal bovine serum (FBS, Gibco, USA) and 1% penicillin-streptomycin
   (Gibco, USA). Cultures were maintained at 37 °C in a humidified
   atmosphere of 5% CO[2]. Normal human liver cells, L-O2 cells
   (iCell-h054, Cellverse Co., Ltd., Shanghai, China), are cultured in
   RPMI 1640 medium supplemented with 10% FBS and 1%
   penicillin-streptomycin at 37 °C under 5% CO[2] conditions.

In Vitro Cellular Uptake Experiment

   L-O2 and RAW 264.7 cells were seeded into a 6-well plate at a density
   of 1 × 10^6 cells per well and incubated for 24 h. Fluorescently
   labeled MNPs-SIRT1-FN (FITC-labeled, Thermo Fisher Scientific, Product
   No.: F1303) were then added at a concentration of 50 µg/mL. The cells
   were further incubated for 2, 4, 8, and 24 h. Subsequently, the cells
   were collected and washed three times with PBS.

   Prepared MNPs were added to the culture medium of RAW 264.7
   macrophages, with different concentration groups set up: low
   concentration (10 µg/mL), medium concentration (50 µg/mL), and high
   concentration (100 µg/mL), along with a control group (untreated).
   After 24 h of incubation, subsequent analyses were performed.

In Vitro Biocompatibility Evaluation

   Cell viability was determined using a live/dead cell staining kit
   (PF00007, Proteintech, USA). Specifically, L-O2 and RAW 264.7 cells
   were seeded at a density of 1.5 × 10^4 cells/cm² in 24-well plates and
   cultured with medium containing nanoparticles for 1, 3, and 7 days.
   After culturing, the cells were thoroughly washed with PBS and
   co-incubated with 200 µL of live/dead staining solution at room
   temperature for 30 min, followed by observation under a fluorescence
   microscope. To ensure the reproducibility of the results, experiments
   under each set of conditions were performed in triplicate.

Lysosomal escape capability assay

   1 × 10^6 RAW 264.7 cells were seeded in 6-well plates and cultured
   overnight at 37 °C. Subsequently, nanoparticles labeled with Rhodamine
   B-PEG-NH[2] (abbreviated as RhB, R164232, Aladdin, Shanghai, China,
   [84]https://www.aladdin-e.com/zh_cn/) were co-cultured with RAW 264.7
   cells for 2 h and 6 hours. After co-culturing, the cells were washed
   and stained with Hoechst 33,342 (C0031, 1:100, Solarbio, Beijing,
   China) and Lyso-Tracker Green fluorescent probe (C1047S, Beyotime,
   Shanghai, China). All samples were observed by CLSM.

Observation with confocal laser scanning microscopy (CLSM)

   RAW 264.7 cells that had taken up fluorescently labeled nanoparticles
   were fixed on coverslips using 4% paraformaldehyde for 15 min, followed
   by three washes with PBS. The coverslips were mounted with a mounting
   medium containing DAPI (Sigma-Aldrich, product number: D9542). The
   cellular uptake of nanoparticles was observed using a confocal laser
   scanning microscope (CLSM, Leica TCS SP8). Each experiment was repeated
   three times, and representative images were presented.

Cell polarization detection

   Cells were collected and washed twice with PBS (Gibco, USA). The cells
   were then fixed with 4% paraformaldehyde (Sigma-Aldrich, USA) for
   15 min. Specific antibodies (anti-CD206 and anti-Arg1, purchased from
   BioLegend) were used for staining. The stained cells were suspended in
   a flow cytometry buffer and analyzed using a flow cytometer (BD
   FACSAria™ III, BD Biosciences) to detect the expression of M2
   macrophage markers, CD206 and Arg1.

   The cell culture supernatant was collected, and the levels of cytokines
   IL-10 and TGF-β were measured using an Enzyme-Linked Immunosorbent
   Assay (ELISA) kit (R&D Systems) according to the manufacturer’s
   instructions. Absorbance was read at 450 nm using a microplate reader
   (Bio-Rad, USA). The final measurements were reported as cytokine
   concentrations in picograms per milliliter (pg/mL).

RT-qPCR

RNA extraction and reverse transcription

   Under sterile conditions, total RNA was extracted from treated
   macrophages using Trizol reagent (Invitrogen, USA) according to the
   manufacturer’s instructions. The purified RNA (at least 1 µg per
   experiment) served as the template for cDNA synthesis, which was
   performed using the PrimeScript RT reagent Kit (Takara Bio, Japan).

Real-Time Quantitative PCR

   RT-qPCR was conducted using the SYBR Green Master Mix (Thermo Fisher
   Scientific, USA) on the ABI 7500 Real-Time PCR system (Applied
   Biosystems, USA). The expression levels of the SIRT1 mRNA and M2
   macrophage-related genes, such as Mrc1 and Arg1, were quantified, with
   GAPDH used as the reference gene. The PCR conditions were set as
   follows: initial denaturation at 95 °C for 5 min, followed by 40 cycles
   of 95 °C for 15 s and 60 °C for 30 s. Each sample was tested in at
   least triplicate to ensure the reliability of the data.

Western blot

   Total protein was extracted from cells using RIPA buffer containing
   protease inhibitors (Beyotime, China). Protein concentration was
   determined with a BCA protein assay kit (Pierce, USA). Equal amounts of
   protein (at least 20 µg per sample) were separated by Sodium Dodecyl
   Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE) and transferred
   to PVDF membranes (Millipore, USA). The membranes were blocked with 5%
   non-fat milk to prevent nonspecific binding and then incubated
   overnight at 4 °C with the following primary antibodies: anti-SIRT1,
   p-PI3K (ab191606, Abcam, UK), PI3K (ab154598, Abcam, UK), p-AKT
   (ab38449, Abcam, UK), AKT (ab8805, Abcam, UK), and the internal control
   β-actin (Abcam, UK). The next day, the membranes were incubated for 1 h
   with HRP-conjugated secondary antibodies (Jackson ImmunoResearch, USA).
   Signals were detected using a chemiluminescence detection system
   (Bio-Rad, USA), and images were captured and analyzed with ImageJ
   software (NIH, USA).

Immunofluorescence staining

   The treated RAW 264.7 or mouse liver tissue was fixed with 4%
   paraformaldehyde (Sigma-Aldrich, USA) and permeabilized using 0.1%
   Triton X-100 (Sigma-Aldrich, USA). The cells were then incubated with
   the primary antibody against SIRT1 (Cell Signaling Technology, USA);
   CD206 (Cell Signaling Technology, USA); CD80 (Cell Signaling
   Technology, USA) or F4/80 (Cell Signaling Technology, USA), followed by
   incubation with the secondary antibody Alexa Fluor 488 (Invitrogen,
   USA) or Alexa Fluor 549 (Invitrogen, USA). Observations were made using
   a confocal microscope (Leica TCS SP8, Germany), and image analysis was
   performed with LAS X software (Leica, Germany).

Analysis of immune microenvironment components

   The distribution of immune cell subsets in the liver of both the
   treatment and control groups was analyzed using a flow cytometer (BD
   Biosciences, USA). Sample preparation involved treating liver tissue
   with collagenase and DNase, followed by staining with specific
   antibodies (e.g., F4/80, CD11b, CD86, CD206) for surface and
   intracellular markers. Flow cytometry data were analyzed using FlowJo
   software.

Statistical analysis methods

   Statistical analyses in this study were performed using SPSS 25.0 and
   GraphPad Prism 8.0. All experimental data are presented as
   mean ± standard deviation (Mean ± SD). Group comparisons for cell and
   animal experiments were conducted using one-way analysis of variance
   (ANOVA), with statistical significance defined as p < 0.05. For
   multiple comparisons, Tukey’s honestly significant difference (HSD)
   post hoc test was applied. If the assumptions of normality and
   homogeneity of variance were met, Student’s t-test (for two groups) or
   one-way ANOVA (for three or more groups) was used. If these assumptions
   were not met, non-parametric tests such as the Mann–Whitney U test or
   Kruskal–Wallis test were employed. For time-dependent in vivo
   experiments, repeated measures ANOVA was used to evaluate the effect of
   time. All statistical tests were two-tailed, with p < 0.05 considered
   statistically significant.

Results

SIRT1 promotes M2 macrophage polarization inducing HCC Post-CHB

   We used 6-8-week-old C57BL/6 transgenic mice that specifically express
   HBV genes. RNA-seq was performed on liver tissues from two groups of
   mice. Differential expression analysis identified 496 DEGs, with 199
   significantly downregulated and 297 significantly upregulated. The most
   notable gene was SIRT1 (Fig. [85]1A).

Fig. 1.

   [86]Fig. 1
   [87]Open in a new tab

   Transcriptional Profiling Analysis of CHB Mouse Liver Tissue. Note: (A)
   Volcano plot of differential analysis of transcriptome sequencing,
   where red indicates significantly upregulated genes, blue indicates
   significantly downregulated genes, and gray represents genes with no
   significant difference; (B) Infiltration status of two immune cell
   groups; (C) Heatmap of marker genes for M1 and M2 macrophages; (D) KEGG
   enrichment analysis of DEGs; (E-G) GO enrichment analysis of DEGs,
   including BP (E), CC (F), and MF (G). Control: n = 3; CHB: n = 3

   In the CHB group, impaired function of various immune regulatory cells
   was detected. Using the “CIBERSORT” method, we assessed immune cell
   infiltration in both groups. The results indicated a significant
   decrease in M1 macrophages and a significant increase in M2 macrophages
   in the CHB group (Fig. [88]1B).

   A heatmap was used to show the expression of genes related to M2
   polarization, including ARG1, MRC1 (CD206), CCL22, and IL10, all of
   which were highly expressed in the CHB group. In contrast, M1
   macrophage-related genes such as NOS2, IL-1β, TNF-α, IL-6, CXCL10, and
   IFN-γ were downregulated in the CHB group (Fig. [89]1C).

   Functional enrichment analysis of 486 DEGs revealed significant
   enrichment in the PI3K-Akt signaling pathway, FoxO signaling pathway,
   IL-17 signaling pathway, and NF-kappa B signaling pathway according to
   KEGG results (Fig. [90]1D). GO analysis showed significant associations
   in BP with organic hydroxy compound metabolic process, regulation of
   lipid metabolic process, and organic hydroxy compound biosynthetic
   process (Fig. [91]1E); in cellular component (CC) with plasma membrane
   part, cell surface, and side of the membrane (Fig. [92]1F); and in
   molecular function (MF) with signaling receptor binding, cytokine
   receptor binding, and CCR chemokine receptor binding (Fig. [93]1G).

   The proteomic differential analysis identified 22 DEPs, with 6
   significantly downregulated and 16 significantly upregulated. SIRT1 was
   the most significantly altered, with ARG1 and IL10 significantly
   downregulated and TNF and IL-6 significantly upregulated
   (Fig. [94]2A-B).

Fig. 2.

   [95]Fig. 2
   [96]Open in a new tab

   Proteomic Analysis of Mouse Liver Tissue in CHB Mice. Note: (A) Volcano
   plot of proteomic differential analysis, where red indicates
   significantly upregulated proteins, green indicates significantly
   downregulated proteins, and grey represents proteins with no
   significant difference; (B) Heat map of DEPs; (C) KEGG enrichment
   analysis of DEPs; (D-F) GO analysis of DEPs, BP (D), CC (E), MF (F).
   Control group: n = 3; CHB group: n = 3

   Functional enrichment analysis of DEPs revealed significant enrichment
   in the PI3K-Akt signaling pathway, FoxO signaling pathway, IL-17
   signaling pathway, and AGE-RAGE signaling pathway in diabetic
   complications according to KEGG results (Fig. [97]2C). GO analysis
   showed significant associations in BP with response to
   oxygen-containing compounds, cellular response to oxygen-containing
   compounds, and response to hormones (Fig. [98]2D); in CC with
   transferase complex, phosphatidylinositol 3-kinase complex, class I,
   and interleukin-6 receptor complex (Fig. [99]2E); and in MF with
   molecular function (MF) regulator, cytokine receptor binding, and
   receptor-ligand activity (Fig. [100]2F).

   Overall, SIRT1 was the most significantly altered gene in both the
   transcriptome and proteome. Previous studies have reported that SIRT1
   plays a role in regulating inflammation [[101]49] and can promote the
   progression of various cancers [[102]50, [103]51]. SIRT1 downregulates
   M1 macrophage markers and upregulates M2 macrophage markers [[104]52].
   In summary, we hypothesize that SIRT1 may induce HCC post-CHB by
   inhibiting M1 macrophage polarization and promoting M2 polarization.

Mesoporous silica nanoparticles exhibit excellent stability and drug release
properties

   By integrating the results from transcriptomics and proteomics
   sequencing analyses, we hypothesize that SIRT1 may induce the
   occurrence of liver cancer following chronic hepatitis B (CHB) by
   inhibiting M1 macrophage polarization and promoting M2 polarization. To
   further investigate the impact of SIRT1 on the development of liver
   cancer, we employed the SIRT1 inhibitor EX-527 for liver cancer
   treatment. To overcome issues such as the short half-life and lack of
   target specificity of the drug, we designed a mesoporous silica
   nanoparticle-based targeted delivery system. This system utilizes
   mesoporous silica as the core, loading the inhibitor through covalent
   bonds into the drug, and targets specific receptors expressed in the
   liver, such as integrin αvβ3, through modifications with
   fibrinogen(PMID: 28340512和PMID: 15661807). This study aims to develop a
   new type of nanoparticle drug that has liver targeting, controlled
   release, and extended drug half-life capabilities (Fig. [105]3A).

Fig. 3.

   [106]Fig. 3
   [107]Open in a new tab

   Preparation and Characterization of MNPs. Note: (A) Schematic
   illustration of the preparation process of MNPs-SIRT1-FN (starting from
   the base MCM-41 nanoparticles, through amination modification, SIRT1
   inhibitor loading, to fibronectin modification). (B) TEM image
   displaying the uniform spherical morphology of MCM-41 nanoparticles,
   with an average particle size of approximately 100 nanometers. (C) DLS
   results showcase the particle size distribution of modified
   nanoparticles, confirming a slight increase in size after surface
   modification. (D) FTIR spectra demonstrating characteristic absorption
   peaks of nanoparticles before and after amination modification,
   validating the success of chemical modification. (E) XPS analysis
   confirms the successful introduction of amines onto the nanoparticle
   surface. (F) TGA results show the thermal stability of nanoparticles
   after SIRT1 inhibitor loading. (G) FTIR further confirms the successful
   loading of the SIRT1 inhibitor onto the nanoparticles. (H) DLS results
   indicate changes in particle size before and after fibronectin
   modification. (I) TEM images show the uniform spherical morphology of
   MNPs-SIRT1 and MNPs-SIRT1-FN. (J) A fluorescence microscopy image
   displays the fluorescence signal of FITC-labeled nanoparticles,
   confirming successful labeling. (K) FACS results reveal the cellular
   uptake of fluorescently labeled nanoparticles. All data are expressed
   as mean ± standard error, with each experiment repeated three times.
   Statistical analysis was conducted using ANOVA and Tukey’s post-hoc
   test, where * indicates p < 0.05, ** indicates p < 0.01, and ***
   indicates p < 0.001

   The MCM-41 nanoparticles, prepared via the sol-gel method, exhibited a
   uniform spherical morphology under TEM with an average particle size of
   approximately 100 nm (Fig. [108]3B). DLS results demonstrated a narrow
   size distribution, indicating good uniformity and dispersion
   (Fig. [109]3C). The MCM-41 nanoparticles were aminated using
   3-aminopropyltriethoxysilane (APTES). FTIR showed a prominent N-H
   stretching vibration peak at 3400 cm^-1, confirming the introduction of
   amino groups (Fig. [110]3D). X-ray Photoelectron Spectroscopy (XPS)
   further verified the successful amination (Fig. [111]3E).

   Using EDC/NHS coupling, the SIRT1 inhibitor EX-527 was successfully
   loaded onto the aminated nanoparticles. Thermogravimetric Analysis
   (TGA) indicated significant weight loss between 200 and 300 °C,
   suggesting a high loading of the SIRT1 inhibitor, with the modified
   nanoparticles maintaining good thermal stability below 300 °C
   (Fig. [112]3F). FTIR analysis also confirmed the successful binding of
   the SIRT1 inhibitor, as evidenced by the appearance of characteristic
   absorption peaks of the inhibitor (Fig. [113]3G). Furthermore,
   fibronectin (FN) was covalently attached to the nanoparticles loaded
   with the SIRT1 inhibitor via EDC/NHS coupling. FTIR and XPS analysis
   confirmed the presence of fibronectin’s characteristic absorption peaks
   and elemental signals on the modified nanoparticles. DLS results showed
   an increase in particle size, indicating successful fibronectin
   modification (Fig. [114]3H).

Fig. 4.

   [115]Fig. 4
   [116]Open in a new tab

   Characterization of Multifunctional Biomimetic Nanoparticles. Note:
   (A-B) Confocal microscopy analysis of RAW 264.7 and L-O2 cells after
   24 h of culture with MNPs-SIRT1 and MNPs-SIRT1-FN nanoparticles,
   showing nanoparticle uptake (scale bar = 10 μm). (C-D) Live/dead cell
   staining to assess the toxicity of MNPs-SIRT1-FN nanoparticles to RAW
   264.7 and L-O2 cells, ‘ns’ indicates no significant difference compared
   to the PBS group (scale bar = 100 μm). (E) Lysosomal escape of
   nanoparticles assessed by CLSM after 2 h and 6 h of incubation, with
   blue fluorescence representing Hoechst 33,342 nuclear staining, green
   fluorescence representing Lyso-Tracker lysosomal staining, and red
   fluorescence representing RhB-labeled nanoparticles (scale bar
   = 50 μm). (F) Chemical stability testing results indicate that within
   the pH range of 5.0 to 8.0, the nanoparticles demonstrate excellent
   chemical stability. (G) Analysis of drug release properties reveals
   that nanoparticles loaded with SIRT1 inhibitors rapidly release
   approximately 40% of the drug under simulated physiological conditions
   in vitro within 24 h, followed by a gradual release over 72 h,
   demonstrating favorable sustained release characteristics that align
   with the requirements of long-term therapy. All data are expressed as
   mean ± standard error, with experiments repeated three times.
   Statistical analysis was conducted using ANOVA and Tukey post hoc
   tests, with * indicating p < 0.05, ** indicating p < 0.01, and ***
   indicating p < 0.001

   TEM observations indicate that the modified nanoparticles maintain a
   spherical shape and uniform size distribution (Fig. [117]3I). DLS
   results demonstrate that the nanoparticles exhibit good dispersion in
   aqueous solution and possess a positive surface charge, indicating
   stability under physiological conditions. The nanoparticles were
   labeled with fluorescein isothiocyanate (FITC) and verified using
   fluorescence microscopy and flow cytometry. The results show that the
   labeled nanoparticles exhibit strong fluorescence signals under
   fluorescence microscopy (Fig. [118]3J). Flow cytometry results indicate
   significant cellular uptake of the fluorescently labeled nanoparticles,
   confirming successful labeling and good biocompatibility
   (Fig. [119]3K).

   In addition, we performed immunofluorescence staining to examine the
   uptake of MNPs-SIRT1 and MNPs-SIRT1-FN nanoparticles by RAW 264.7 and
   L-O2 cells. Green fluorescence was observed in both cell types after
   co-incubation with MNPs-SIRT1 and MNPs-SIRT1-FN, indicating that both
   types of nanoparticles were successfully internalized by the cells.
   Notably, under equivalent dosages, MNPs-SIRT1-FN exhibited
   significantly higher cellular uptake than MNPs-SIRT1 (Fig. [120]4A-B),
   further confirming that fibronectin modification enhances nanoparticle
   uptake.

   We further evaluated the biosafety of MNPs-SIRT1-FN nanoparticles.
   Live/dead cell staining showed that, compared to the PBS group, the
   nanoparticles exhibited negligible cytotoxicity to both L-O2 and
   macrophage cells (Fig. [121]4C-D). To investigate the lysosomal escape
   capability of the nanoparticles, RhB-labeled nanoparticles were
   co-incubated with RAW 264.7 cells and observed via CLSM. As shown in
   Fig. [122]4E, after 2 h of incubation, the red fluorescence from
   RhB-labeled MNPs-SIRT1 and MNPs-SIRT1-FN co-localized with green
   lysosomal fluorescence, forming yellow puncta. However, after 6 h, most
   of the red fluorescence in the MNPs-SIRT1-FN group was separated from
   the green signal, suggesting a successful escape from lysosomes. In
   contrast, the MNPs-SIRT1 group remained co-localized with lysosomes.
   These results indicate that immunoprotein modification promotes
   lysosomal escape, thereby enabling more nanoparticles to target SIRT1
   (Fig. [123]4E).

   Further chemical stability tests show that the nanoparticles maintain
   stability within a physiological pH range (pH 5.0–8.0), indicating
   their suitability for biomedical applications (Fig. [124]4F). The
   encapsulation efficiency (EE%) of the SIRT1 inhibitor in the
   nanoparticles was 67.56 ± 5.67%, and the drug loading (DL%) was
   6.67 ± 0.83%. Both the encapsulation rate and drug loading of these
   nanoparticles are considered to be good. Under simulated physiological
   conditions, the drug release profile of SIRT1 inhibitor-loaded
   nanoparticles was tested in vitro (Fig. [125]4G). The results reveal
   that approximately 40% of the drug is released within the first 24 h,
   followed by a gradual release over the next 72 h, demonstrating good
   sustained-release properties. The release curve indicates that the
   nanoparticles can stably release the drug, meeting the requirements for
   long-term therapy.

MNPs delivering SIRT1 inhibitors significantly inhibit M2 macrophage
polarization

   The workflow for in vitro cell experiments is shown in Fig. [126]5A. In
   RAW 264.7, after 24 h of treatment with MNPs, the numbers of M1 and M2
   macrophages were analyzed using flow cytometry at different
   nanoparticle concentrations(Fig. [127]5B). The results showed that the
   number of M1 macrophages in the nanoparticle-treated groups was
   significantly higher than in the control group (p < 0.05), while the
   number of M2 macrophages was significantly lower than in the control
   group (p < 0.05). Furthermore, as the concentration of nanoparticles
   increased, the number of M1 macrophages gradually increased, whereas
   the number of M2 macrophages gradually decreased, resulting in a
   progressively higher ratio of M1 to M2 macrophages (Fig. [128]5C-F).

Fig. 5.

   [129]Fig. 5
   [130]Open in a new tab

   MNPs Delivery of SIRT1 Inhibitor Inhibits Macrophage M2 Polarization by
   Regulating the SIRT1/PI3K-AKT Signaling Pathway. Note: (A) Schematic of
   in vitro cell experiment process. (B) Flow cytometry gating strategy
   for M1 and M2 macrophages. (C) Flow cytometry analysis of the ratio of
   M1 to M2 macrophages after treatment with different concentrations of
   nanoparticles. (D) Statistical chart of the M1 macrophage ratio. (E)
   Statistical chart of the M1 macrophage ratio. (F) The ratio of M1
   macrophages to M2 macrophages. (G) Expression levels of M2 polarization
   markers CD206 and Arg1 in macrophages after treatment with different
   concentrations of nanoparticles. (H) Impact of different nanoparticle
   concentrations on the secretion of Anti-inflammatory Cytokines IL-10
   and TGF-β in RAW 264.7 cells. (I) Influence of different nanoparticle
   concentrations on the gene expression of SIRT1 in RAW 264.7 cells. (J)
   Effects of different nanoparticle concentrations on the protein
   expression of SIRT1, p-PI3K/PI3K, and p-AKT/AKT in RAW 264.7 cells
   using Western Blot analysis. (K) Quantitative analysis of SIRT1,
   p-PI3K/PI3K, and p-AKT/AKT protein expression in RAW 264.7 cells. (L)
   Immunofluorescence staining results showed reduced nuclear localization
   of SIRT1 (green) in different nanoparticle treatment groups (scale bar:
   25 μm). All data are presented as mean ± standard error, the
   experiments were repeated three times, and statistical analysis was
   performed using ANOVA and Tukey post hoc test; * indicates p < 0.05, **
   indicates p < 0.01, *** indicates p < 0.001, **** indicates p < 0.0001

   Flow cytometry analysis revealed that the expression of M2 macrophage
   markers CD206 and Arg1 was significantly lower in the
   nanoparticle-treated groups compared to the control group (p < 0.05).
   In the low concentration group (10 µg/mL), the proportion of
   CD206-positive cells decreased by approximately 30%, and Arg1-positive
   cells decreased by about 27%. In the medium concentration group
   (50 µg/mL), CD206-positive cells decreased by approximately 41%, and
   Arg1-positive cells decreased by about 34%. In the high concentration
   group (100 µg/mL), CD206-positive cells decreased by approximately 67%,
   and Arg1-positive cells significantly decreased by about 57%
   (Fig. [131]5G). Previous studies have shown that SIRT1 may be
   negatively correlated with IL-10/TGF-β levels through the NF-κB pathway
   [[132]53, [133]54]. ELISA results showed that the secretion levels of
   anti-inflammatory cytokines IL-10 and TGF-β in the treated groups
   significantly increased with the concentration of nanoparticles
   (p < 0.05). In the low concentration group (10 µg/mL), IL-10 secretion
   increased by approximately 1.5 times, and TGF-β secretion increased by
   about 1.4 times. In the medium concentration group (50 µg/mL), IL-10
   secretion increased by approximately 2 times, and TGF-β secretion
   increased by about 1.8 times. In the high concentration group
   (100 µg/mL), IL-10 secretion increased by approximately 3 times, and
   TGF-β secretion significantly increased by about 2.5 times
   (Fig. [134]5H).

   RT-qPCR results showed significant changes in the expression levels of
   the SIRT1 gene in different nanoparticle treatment groups relative to
   the housekeeping gene GAPDH (p < 0.05). Specifically, the relative
   expression of the SIRT1 gene decreased by approximately 30% in the low
   concentration (10 µg/mL) treatment group, by about 45% in the medium
   concentration (50 µg/mL) treatment group, and by roughly 75% in the
   high concentration (100 µg/mL) treatment group (Fig. [135]5I). These
   changes were further validated by Western Blot analysis, which
   demonstrated significant alterations in the expression levels of SIRT1,
   p-PI3K, and p-AKT/AKT proteins across different nanoparticle
   concentrations (p < 0.05). Specifically, SIRT1 protein levels decreased
   by about 30% in the low concentration (10 µg/mL) group, by
   approximately 50% in the medium concentration (50 µg/mL) group, and by
   around 70% in the high concentration (100 µg/mL) group. Conversely,
   p-PI3K/PI3K and p-AKT/AKT protein levels decreased by approximately 30%
   and 20%, respectively, in the low-concentration group, by about 40% and
   30% in the medium-concentration group and increased by roughly 50% and
   42% in the high concentration group (Fig. [136]5J-K). The expression of
   the housekeeping protein β-actin remained stable across all treatment
   groups, indicating consistent protein loading. These findings suggest
   that nanoparticle treatments significantly regulate SIRT1 protein
   expression in RAW 264.7 in a concentration-dependent manner.
   Immunofluorescence staining revealed reduced nuclear localization of
   SIRT1 in the different nanoparticle treatment groups (Fig. [137]5L).
   These results indicate a significant change in SIRT1 localization
   within the cell following nanoparticle treatment, implying alterations
   in the activation state of the SIRT1/PI3K-AKT signaling pathway,
   thereby promoting M2 macrophage polarization.

Fig. 6.

   [138]Fig. 6
   [139]Open in a new tab

   Distribution Dynamics and Metabolic Process of MNPs in Mice. Note: (A)
   Fluorescence imaging: Fluorescence imaging results of MNPs in the
   livers of mice at different time points (3 h, 24 h, and 72 h) after
   injection. (B) Time course of fluorescence intensity in the liver. (C)
   Ex vivo imaging of the major organs (heart, liver, spleen, lungs,
   kidneys, and brain) in mice 24 h after injection of the multifunctional
   biomimetic nanoparticles. (D) Statistical chart of the quantitative
   fluorescence intensity in the liver

Distribution and clearance dynamics of MNPs in mice

   The distribution of MNPs in mice was tracked using fluorescent
   labeling. Results indicated that within 3 h post-injection, the MNPs
   rapidly accumulated in the liver (Fig. [140]6A), reaching their peak
   concentration at 24 h. The targeting of nanoparticles to the liver was
   significantly improved with fibronectin modification compared to
   nanoparticles without fibronectin modification, especially at 24 h
   post-injection. Subsequently, the fluorescent signal gradually
   diminished, and by 72 h, a significantly reduced level of fluorescence
   was observed in the liver (Fig. [141]6B).

   Additionally, 24 h after the injection of the nanoparticles, the mice
   were euthanized and their major organs (heart, liver, spleen, lungs,
   kidneys, and brain) were collected for ex vivo imaging analysis. The
   results indicated a significant increase in the distribution of the
   fibrinogen-modified multifunctional biomimetic nanoparticles in the
   mouse liver (Fig. [142]6C-D). This finding suggests that the
   modification with fibrinogen effectively enhances the liver-targeting
   ability of the nanoparticles.

MNPs delivering SIRT1 inhibitors significantly inhibit macrophage M2
polarization in mice

   Flow cytometry analysis (Fig. [143]7A-B) demonstrated a significant
   increase in the expression of M1 macrophage markers (CD80 and CD86) in
   the treatment group compared to the control group (p < 0.05).
   Conversely, the expression of the M2 macrophage marker (CD206) was
   significantly decreased in the treatment group, showing a statistically
   significant difference from the control group (p < 0.05). Flow
   cytometry assay showed a significant increase in the number of M1
   macrophages and a significant decrease in the number of M2 macrophages
   compared to the control group, demonstrating the potential
   immunomodulatory effect of SIRT1 inhibitor (Fig. [144]7C-D). These
   findings indicate that SIRT1 inhibitors delivered through a
   nanoparticle system can effectively modulate macrophage polarization,
   promoting a shift in the immune microenvironment from an
   anti-inflammatory to a pro-inflammatory state.

Fig. 7.

   [145]Fig. 7
   [146]Open in a new tab

   Regulation of Macrophage Polarization in Mice by Delivery of SIRT1
   Inhibitor Using MNPs. Notes: (A-B) Expression levels of M1 macrophage
   markers CD80 and CD86 and M2 macrophage marker CD206 in the treatment
   and control groups; (C) Flow cytometry gating strategy for M1 and M2
   macrophages; (D) Ratio of M1 to M2 macrophages. All data are presented
   as mean ± standard error, the experiments were repeated three times,
   and statistical analysis was performed using Student’s t test; **
   indicates p < 0.01, **** indicates p < 0.0001

MNPs delivering SIRT1 inhibitors significantly improve liver pathology and
function in mice

   Histological examination using H&E staining (Fig. [147]8A) revealed
   that the liver tissues in the treatment group displayed clear
   hepatocyte boundaries, significantly reduced infiltration of
   inflammatory cells, and marked improvement in liver fibrosis.
   Immunohistochemical analysis (Fig. [148]8B) further demonstrated a
   significant reduction in SIRT1 expression in the liver tissues of the
   treatment group compared to the control group. In addition,
   immunofluorescence staining showed that compared with the Control
   group, the expression of CD206 protein in the liver tissues of mice in
   the Treatment group was significantly reduced, whereas the expression
   of F4/80 and CD80 proteins was significantly increased, which indicated
   that the number of macrophages in the liver tissues of mice was
   significantly increased by the action of the nanoparticles, and that
   the nanoparticles promoted the M1 polarisation of the macrophages and
   suppressed the macrophage M2 polarisation (Fig. [149]8C-D). These
   changes are closely associated with improvements in liver pathology,
   indicating that MNPs delivering SIRT1 inhibitors exert a significant
   therapeutic effect.

Fig. 8.

   [150]Fig. 8
   [151]Open in a new tab

   Impact of MNPs Delivery of SIRT1 Inhibitor on the Hepatic Pathological
   Structure in Mice. Note: (A) H&E staining of mouse liver tissue. (B)
   Immunohistochemical staining images of liver tissue sections for SIRT1.
   (C-D) Immunofluorescence staining images of liver tissue sections for
   F4/80, CD206 and CD80. (E) Changes in serum ALT and AST levels before
   and after treatment. All data are presented as mean ± standard error,
   the experiments were repeated three times, and statistical analysis was
   performed using Student’s t test; * indicates p < 0.05, ** indicates
   p < 0.01, *** indicates p < 0.001, **** indicates p < 0.0001

   Post-treatment, as shown in Fig. [152]8E, the levels of serum ALT and
   AST in the treatment group were significantly lower than those in the
   control group, with ALT levels reduced by 45% and AST levels by 38%,
   both changes being statistically significant (p < 0.01). The
   substantial improvement in these biochemical markers suggests that
   SIRT1 inhibitors can effectively alleviate liver inflammation and
   cellular damage, thereby protecting liver function.

   Finally, we conducted an in vivo biosafety assessment of the
   multifunctional biomimetic nanoparticles. The results showed that no
   significant damage was observed in the heart, brain, spleen, lung, and
   kidney tissues of the mice across all groups, as evidenced by H&E
   staining (Figure [153]S2). This indicates that the nanoparticles
   possess good biosafety.

Discussion

   This study aims to investigate the delivery of SIRT1 inhibitors using
   MNPs to modulate Macrophage M2 Polarization, thereby reshaping the
   liver immune microenvironment and preventing the progression of HCC
   following CHB. Compared to previous studies, this research demonstrates
   significant innovations in both techniques and methodology. Traditional
   studies often focus on the mechanisms of single molecules. In contrast,
   this study employs nanoparticle delivery to enhance the efficacy of
   SIRT1 inhibitors in reaching target cells and modulates macrophage
   polarization to comprehensively reshape the liver immune
   microenvironment. This strategy not only improves the targeting and
   stability of the drug but also reduces its side effects, highlighting
   its potential for clinical applications.

   For the experimental design, we utilized 6-8-week-old C57BL/6
   transgenic mice specifically expressing HBV genes to establish an
   animal model of CHB. This approach more accurately simulates the
   pathological process of human CHB than previous methods. Through RNA
   and proteomic analyses of liver tissues from both control and CHB
   groups, we identified various DEGs and DEPs associated with the
   development of HCC. High-throughput RNA-seq and proteomic analysis not
   only enhanced the comprehensiveness and accuracy of the data but also
   deepened our understanding of the role of SIRT1 in HCC post-CHB,
   providing a solid foundation for future research.

   One of the primary findings of this study is the significant
   upregulation of SIRT1 expression in the liver tissues of CHB mice.
   Immunohistochemical analysis revealed a notable decrease in M1
   macrophages and a corresponding increase in M2 macrophages in the CHB
   group. This observation aligns with previous studies and further
   substantiates the critical role of SIRT1 in regulating immune cell
   polarization. Genes associated with M2 polarization, such as ARG1,
   MRC1, CCL22, and IL10, were upregulated in the HBV group, whereas genes
   linked to M1 polarization, including NOS2, IL-1β, and TNF-α, were
   downregulated [[154]55]. These results suggest that SIRT1 influences
   the hepatic immune microenvironment in CHB by modulating macrophage
   polarization, which may play a pivotal role in the development of HCC.

   Additionally, this study identified several key signaling pathways
   related to liver pathology, such as PI3K-Akt, FoxO, IL-17, and NF-kappa
   B, through the screening of DEGs and DEPs. Functional enrichment
   analysis further confirmed the potential involvement of these pathways
   in liver lesions induced by HBV infection. Proteomics analysis also
   indicated a strong association between SIRT1 activity and the PI3K-Akt
   signaling pathway, suggesting that SIRT1 may impact immune cell
   polarization by regulating this pathway, thereby contributing to the
   development of HCC post-CHB. These findings not only enhance our
   understanding of the mechanisms underlying HCC development post-CHB but
   also provide new perspectives for future therapeutic strategies.

   The preparation and characterization of MNPs is a significant highlight
   of this study. We successfully synthesized MNPs loaded with a SIRT1
   inhibitor and confirmed their structure and function through
   comprehensive characterization. Compared to traditional delivery
   systems, these MNPs exhibit enhanced stability and biocompatibility,
   allowing for more efficient delivery of the SIRT1 inhibitor. This study
   is the first to demonstrate that MNPs-SIRT1-FN can significantly
   inhibit macrophage M2 polarization. This finding not only confirms the
   advantages of nanoparticles in drug delivery but also offers new
   possibilities for the prevention and treatment of HCC.

   In animal experiments, we found that the proportion of M2-type
   macrophages in the liver of mice in the treatment group was
   significantly reduced compared to the control group. Immune
   microenvironment analysis revealed an increased proportion of
   pro-inflammatory immune cells and a decreased proportion of
   immunosuppressive cells in the liver tissues of the treated mice,
   indicating an effective remodeling of the immune microenvironment.
   These results provide clearer evidence of the potential of SIRT1
   inhibitors in HCC prevention compared to previous studies. This
   discovery not only enhances our understanding of the role of the immune
   microenvironment in HCC development but also offers new directions for
   future clinical applications.

   In conclusion, our study demonstrates that MNPs delivering SIRT1
   inhibitors can effectively regulate macrophage M2 polarization and
   remodel the liver immune microenvironment, thereby inhibiting the
   development and progression of HCC following CHB. This strategy holds
   significant value in scientific research and has promising clinical
   applications, providing new methods and insights for the prevention and
   treatment of HCC. However, this study has some limitations, such as
   being conducted only in a mouse model; further validation is needed to
   determine applicability to humans. Additionally, the long-term safety
   and biocompatibility of MNPs require further investigation. Future
   research should explore the application of SIRT1 inhibitors in other
   types of HCC and their combined use with other treatments. By
   continually optimizing nanoparticle delivery systems, we hope to
   provide more effective solutions for the comprehensive treatment of
   HCC.

Electronic supplementary material

   Below is the link to the electronic supplementary material.
   [155]12951_2025_3447_MOESM1_ESM.jpg^ (804.5KB, jpg)

   Supplementary Material 1: Figure S1. Schematic Illustration of In Vivo
   Animal Experiment Procedure
   [156]12951_2025_3447_MOESM2_ESM.jpg^ (1.8MB, jpg)

   Supplementary Material 2: Figure S2. In Vivo Biosafety Assessment of
   Multifunctional Biomimetic Nanoparticles

Acknowledgements