HepG2 cells stimulated by THP-1-conditioned medium: a potential in vitro model of systemic inflammation–induced hepatic alterations

Abstract

Background

Chronic inflammatory diseases are associated with qualitative and quantitative changes in lipid and lipoprotein metabolism, including high density lipoproteins (HDLs), increasing patients´ susceptibility to atherosclerosis and cardiovascular mortality. Given the liver’s central role in lipoprotein metabolism and systemic inflammation, we aimed to develop and investigate an in vitro model of inflammation-induced hepatic metabolic changes.

Methods and Results

To better approximate in vivo conditions, where systemic inflammation exposes the liver to a complex environment rich in cytokines and inflammatory mediators, we exposed human hepatocarcinoma HepG2 cells to conditioned media (CM) from THP-1-derived macrophages using phorbol-12-myristate-13-acetate (PMA) and lipopolysaccharide (LPS). The effect of CM on mRNA expression in HepG2 was tested by quantitative real-time PCR or protein expression by Western blot analysis. Even short-term exposure to CM (2–4 h) led to a significant change in the mRNA expression of inflammatory genes and several transcription factors (e.g., TNF-α, NF-κB, PPARα, and LRH-1). This change was accompanied by alternations in the expression of lipoprotein-associated genes at different time points (e.g. SAA, LDLr, ApoA1, ABCA1, PON1, and PCSK9). After 24 h of exposure, no effect on HepG2 viability was observed.

Conclusion

In our model, we observed several significant inflammation-induced changes in hepatic lipoprotein metabolism, making it a valuable in vitro system for further mechanistic studies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11033-026-11641-0.

Introduction

Chronic inflammation has emerged as a significant health concern in recent years. Systemic inflammation can increase susceptibility to atherosclerosis and contribute to cardiovascular morbidity and mortality [1, 2]. Given the close interconnection between metabolic pathways and the immune system, the chronic presence of inflammatory molecules and mediators in systemic circulation can disrupt metabolic processes and impair their normal functions. For example, the remodelling of the high-density lipoprotein (HDL) proteome into pro-inflammatory HDL (piHDL) has been observed. During inflammation, HDL particles usually become depleted of key components such as apolipoprotein A1 (ApoA1), lecithin–cholesterol acyltransferase (LCAT), and the antioxidant enzyme paraoxonase 1 (PON1), and are concomitantly associated with acute-phase proteins, notably serum amyloid A (SAA), which can displace ApoA1 in certain HDL subpopulations [3]. Additional changes associated with chronic inflammatory diseases (CIDs) include: (i) impaired reverse cholesterol transport (RCT) [4], with ATP-binding cassette transporter A1 (ABCA1) playing a prominent role; (ii) elevated plasma triacylglycerol (TAG) levels [5]; (iii) reduced low-density lipoprotein (LDL) levels correlating inversely with increased cardiovascular risk - a phenomenon known as the lipid paradox [6]; (iv) higher prevalence of proatherogenic small dense LDL (sdLDL) particles [7]; and (v) disruption of the LDL receptor (LDLr) pathway, reflected by altered LDLr and proprotein convertase subtilisin/kexin type 9 (PCSK9) protein and/or mRNA expression [8]. Further investigations in this area are crucial to elucidate the mechanisms underlying inflammation-driven alterations in lipid metabolism and to identify therapeutic strategies for improving cardiovascular health in patients with chronic inflammation.

In this study, we aimed to develop and analyse an in vitro model of inflammation-induced changes in lipid metabolism using HepG2 liver cells exposed to THP-1-derived conditioned media (CM). Although hepatic cell lines such as HepG2 have certain limitations, they remain valuable and practical models for studying liver-specific processes and assessing the impact of compounds in vitro [9]. THP-1 is a human monocytic leukemia cell line widely used as a model to study monocyte and macrophage functions and signalling pathways. THP-1 cells are capable of producing substantial amounts of pro-inflammatory molecules upon stimulation [10]. The combination of pro-inflammatory mediators secreted by activated macrophages with HepG2 cells may better simulate the complex inflammatory hepatic environment present in the organism during chronic inflammation.

Materials and methods

Cell lines and culture conditions

The final protocol (illustrated schematically in Fig. 1) for CM preparation was established on the basis of our previous optimisation experiments, in which different stimulation strategies for THP-1 cells (1 µg/mL lipopolysaccharide (LPS) for 8 h; 100 ng/mL phorbol 12-myristate 13-acetate (PMA) for 24 h; or a combination of 10 ng/mL PMA for 24 h followed by 1 µg/mL LPS for 4 h) (PMA + LPS), as well as various CM dilutions (1:1, 1:3, and 1:5.6) in HepG2 cells were tested (Supplementary material: Fig. S1, Fig. S2, Fig. S3).

Fig. 1.

Schematic diagram of the CM preparation procedure (generated by Adobe Illustrator)

HepG2 (ATCC, USA) cells were cultured in RPMI 1640 medium (R1639, Biosera, France) supplemented with 10% fetal bovine serum (Biosera, France), 100 U/mL penicillin/streptomycin (Biosera, France), and 1 mM sodium pyruvate (S8636, Sigma-Aldrich, USA). For the experiments, HepG2 cells were seeded into 12-well plates (Costar Corning, USA) at a density of 0.2 × 10⁶ cells/well, 24 h prior to CM exposure.

The growth medium for the THP-1 (CLS, Germany) cells was the same as that for the HepG2 cells, with the addition of 10 mM HEPES (Bioconcept, Switzerland). For CM collection, THP-1 monocytes were seeded into T25 culture flasks (NEST, China) at a concentration of 0.9 × 10⁶ cells/mL, pretreated with 10 ng/mL PMA (P8139, Sigma-Aldrich, USA) for 24 h, and subsequently stimulated with 1 µg/mL lipopolysaccharide (LPS) (L2630, Sigma-Aldrich, USA) for 4 h. After the pretreatment period, the medium was replaced with serum- and supplement-free RPMI, in which the cells were incubated for an additional 24 h. The collected CM was, in the case of LPS-only or non-stimulated THP-1 cells, centrifuged or/and filtered through a 0.22 μm PVDF syringe filter (NEST, China), then diluted with serum-free RPMI at a 1:3 ratio and applied to HepG2 cells. At specified time points, HepG2 cells were harvested for RNA isolation and subsequent quantitative real-time PCR (qRT-PCR) analysis.

RNA isolation, cDNA synthesis and quantitative real-time PCR (qRT-PCR) analysis

Total RNA was isolated from THP-1 and HepG2 cells using RNAzol^® RT (RN190, MRC, USA). A total of 450 ng of RNA was reverse-transcribed into cDNA using the TaKaRa PrimeScript™ RT reagent kit (TaKaRa, Japan). The cDNA was diluted 1:20 with Tris-EDTA (TE) buffer and used for qRT-PCR. The reactions were performed using HOT FIREPol^® EvaGreen^® qPCR Mix Plus (Solis BioDyne, Tartu, Estonia) on a QuantStudio™ 3 real-time PCR system (Applied Biosystems, Thermo Fisher Scientific, Foster City, CA, USA) with gene-specific oligonucleotide primers (Supplementary material: Table S1). The thermal cycling program consisted of an initial activation step at 95 °C for 15 min, followed by 40 cycles of 95 °C for 15 s, 60 °C for 30 s, and 72 °C for 30 s. Relative mRNA expression was analysed using the Pfaffl method, with GAPDH serving as the endogenous control. Primer specificity was confirmed by melt curve analysis and agarose gel electrophoresis. Each qPCR reaction was performed in two technical replicates (duplicate wells). Relative mRNA expression was analyzed using the Pfaffl method, with normalization using a geometric mean–based normalization factor derived from four housekeeping genes: GAPDH, TBP, MDH1, and β-actin. PCR efficiencies were determined using LinRegPCR (LinRegPCR version 2021.2, Netherlands) software. Primer specificity was confirmed by melt curve analysis and agarose gel electrophoresis.

Enzyme-linked immunosorbent assay (ELISA)

The protein composition of the CM was evaluated by ELISA. CM samples from four independent experiments were collected after filtration, frozen at − 80 °C, and analysed using the Elabscience^® Human IL-1β ELISA Kit (E-EL-H0149, Elabscience, USA) and the Human TNF-α ELISA Kit (BSKH60077, Bioss Antibodies, China), according to the manufacturers’ instructions. For TNF-α measurements, the CM was diluted 1:10. The absorbance was measured using a Synergy H1 plate reader (BioTek, USA).

Cell viability analysis (MTT assay)

The viability of HepG2 cells exposed to CM was assessed using the MTT assay. This colourimetric assay is based on the reduction of the yellow tetrazolium salt 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT, M5655, Sigma-Aldrich, USA) to purple formazan by metabolically active cells. HepG2 cells were seeded into 96-well plates at a density of 0.028 × 10⁶ cells/well. After 24 h, the cells were treated with freshly prepared CM for an additional 24 h. The cells were subsequently incubated with 100 µL of serum-free RPMI and 50 µL of MTT solution (1 mg/mL in PBS) for 4 h. The formazan crystals were solubilised in 150 µL of DMSO for 30 min, and the absorbance was measured at 570 nm using a Synergy H1 plate reader (BioTek, USA).

Cell cycle analysis

Cell cycle assay was performed with DAPI staining (D9542, Sigma-Aldrich, USA) using a fluorescence image cytometer NucleoCounter NC-3000 (Chemometec, Allerød, Denmark) and the Cell Cycle-DAPI assay protocol.

HepG2 cells were seeded in 60 mm culture dishes (NEST, China) at a density of 1.5 × 10⁶ cells/dish. 24 h after attachment, the cells were exposed to CM. After a further 24 h of cultivation, the cells were harvested by trypsinization, combined with floating cells, and centrifuged (500 g, 5 min). Following resuspension in PBS, the cells were fixed in 70% cold ethanol at 4 °C for 2 h. The ethanol was removed, and the cells were washed with PBS and centrifuged again. A mixture of DAPI (1 µg/mL) and Triton X-100 (0.1%) was added to the cell pellet, which was subsequently incubated for 5 min at 37 °C. The stained cells were then analysed by manual gating using NucleoView NC-3000 software.

Western blot

For Western blot analysis, the cells were seeded into a 6-well plate at a concentration of 0.5 × 10⁶ cells/well. After treatment with CM for 24 h, the cells were harvested using RIPA buffer supplemented with protease and phosphatase inhibitors (PMSF, NaF, Na₃VO₄, β-mercaptoethanol). The protein concentration was assessed using the Pierce BCA Protein Assay Kit (Thermo Fisher Scientific). Western blot was performed using standard protocol with primary antibodies against β-actin (Abcam, Cambridge, UK, EPR21241), ApoA1 (Abcam, Cambridge, UK, EP1368Y) and PCSK9 (Cell Signalling Technology, Netherlands, 85813T), and secondary antibodies conjugated to horseradish peroxidase. A chemiluminescent reaction using the Immobilon Crescendo Western HRP substrate (Millipore) was employed for signal detection with the UVITEC Imaging System (Nine Alliance). For the quantification of band densities, Uviband Nine Alliance software (Uvitec, Cambridge, UK) was used.

Statistical analysis

Statistical analysis was performed using GraphPad Prism software (GraphPad, Boston, USA). Comparisons between control and CM-treated cells were made using multiple t-tests with false discovery rate correction by the two-stage Benjamini, Krieger, and Yekutieli method. In cases with more than two experimental groups, one-way ANOVA followed by Tukey’s multiple comparisons test was used. The presented data were compiled from two to four independent experiments.The exact number of biological replicates for each experimental condition is indicated in the corresponding figures.

Results

Effect of PMA + LPS inflammatory stimulation on gene and protein expression in THP-1 cells

Based on the preliminary results from experiments conducted on THP-1 and HepG2 cells (Fig. S1, Fig. S2), the stimulation protocol chosen for the THP-1 cells in the experimental model was PMA at 10 ng/mL for 24 h followed by LPS at 1 µg/mL for 4 h (PMA + LPS).

The combination of PMA + LPS significantly up-regulated the mRNA expression of all analysed inflammatory genes, nuclear factor kappa-light-chain-enhancer of activated B cells p50/p105 (NF-κB p50/p105), tumour necrosis factor alpha (TNF-α), and interleukin 1β (IL-1β), confirming the successful induction of inflammation in THP-1 cells (Fig. 2a). ELISA performed on frozen CM from PMA + LPS-stimulated THP-1 cells, collected across several independent experiments, confirmed the presence of TNF-α and IL-1β proteins in the CM. The concentrations of both cytokines were significantly elevated compared to those in medium from unstimulated THP-1 cells (Fig. 2b).

Fig. 2.

Gene expression of inflammatory markers NF-κB p50/p105, TNF-α, and IL-1β in THP-1 cells. The experiment was performed in two independent experimental runs, each including three biological replicates. (a) Protein concentration (TNF-α and IL-1β) in CM from THP-1 (b) stimulated by PMA (10 ng/mL) for 24 h and subsequently stimulated by LPS (1 µg/mL) for 4 h. ELISA assays were performed on samples collected from four (IL-1β) and five (TNF-α) independent biological experiments, which were analyzed simultaneously in a single assay run. Each biological replicate was measured once (single technical replicate). N.D. = not detected, ** p < 0,01 *** p < 0,001 **** p < 0,0001

Effects of CM on the viability, morphology and cell cycle of HepG2 cells

HepG2 cells were exposed to CM derived from PMA + LPS-treated THP-1 cells diluted with serum-free RPMI at a ratio of 1:3. This dilution represents the best compromise between nutrition and inflammatory signalling (Fig. S3). To assess whether CM had some toxic effects on HepG2 cells, we evaluated cell viability using the MTT assay, the effect of CM on the cell cycle by DAPI staining and the morphology of control and CM-exposed HepG2 cells by light microscopy at 200x magnification.

After 24 h of CM exposure, no significant reduction in cell viability (Fig. 3a) or alterations in the cell cycle of HepG2 cells (Fig. 3b) were observed. The cells retained a normal morphology (Fig. 3c). Thus, no signs of the cytotoxicity of CM on HepG2 cells were observed.

Fig. 3.

Comparison of HepG2 viability by MTT assay (a), the cell cycle by DAPI staining followed by cytometry (b), and morphology by light microscopy at 200x magnification (c) of control (CTRL) HepG2 cells and HepG2 stimulated with CM (CM) 24 h after treatment. MTT assays were performed in two independent experiments using 96-well plates. Half of the wells were assigned to the control group and the other half to the CM-treated group. M1: G0/G1 phase; M2: S phase; M3: G2 phase of the cell cycle

Gene and protein expression changes in HepG2 cells following CM exposure from PMA + LPS-stimulated THP-1 cells

The effects of CM stimulation on the mRNA expression of inflammatory genes, transcription factors, and lipoprotein metabolism–related genes in HepG2 cells were evaluated by qRT-PCR at multiple time points.

The exposure of HepG2 cells to CM resulted in rapid, short-term (within 2–4 h) increases in the expression of pro-inflammatory genes, such as NF-κB p50/p105, TNF-α, haptoglobin (data not shown), and the negative regulator of inflammation A20, also known as tumor necrosis factor alpha–induced protein 3 (TNFAIP3). Serum amyloid A (SAA), the piHDL component, was rapidly up-regulated, and its expression remained high throughout the entire 28-hour experimental period (Fig. 4a). Concurrently, we observed downregulation of the transcription factors peroxisome proliferator–activated receptor α (PPARα) and liver receptor homolog-1 (LRH-1), along with the up-regulation of the LDL receptor (LDLr) (Fig. 4b and c). A notable decrease in PON1 expression began approximately 4 h and persisted for 28 h. At later time points (20–24 h), CM stimulation led to significant downregulation of lipoprotein metabolism–related genes including PCSK9, ApoA1, ABCA1, and ApoC3, compared with those in control cells (Fig. 4c). Although a decreasing trend was also observed throughout the entire time course also for LCAT, particularly at the 4-hour mark, this trend did not reach statistical significance (data not shown). In line with the changes in mRNA expression, CM stimulation for 24 h led to decreased protein expression of apolipoprotein ApoA1 and PCSK9 in HepG2 cells (Fig. 4d).

Fig. 4.

Time-dependent changes in the relative mRNA expression of the inflammatory markers NF-κB p50/p105, TNF-α, A20, and SAA (a), transcription factors PPARα and LRH-1 (b), and lipid metabolism–associated genes LDLr, PON1, PCSK9, ApoA1, ABCA1, and ApoC3 (c) in HepG2 cells stimulated with CM (diluted 1:3) derived from THP-1 cells activated with PMA + LPS. Time-course experiments were performed in three independent biological experiments with duplicates for most time points. For selected key time points (4 h and 24 h), which were identified as the most relevant based on previous experiments, an additional experiment with biological quadruplets was conducted to increase precision. Protein expression of ApoA1 and PCSK9 (d) in HepG2 cells 24 h after stimulation with CM. Data represent nine biological replicates from three independent experiments. * p < 0,05 ** p < 0,01 *** p < 0,001 **** p < 0,0001

Gene expression changes in HepG2 cells following CM exposure from non-stimulated (NS) THP-1 cells

To determine whether inflammatory activation of THP-1 cells is essential for effective CM-mediated modulation of HepG2 gene expression, we compared the response of HepG2 cells to CM from stimulated versus NS THP-1 cells. The medium from NS THP-1 cells, unlike the medium from PMA + LPS-stimulated THP-1 cells, induced no significant changes in gene expression after 4 h (NF-κB p50/105, TNF-α, A20, SAA, PPARα, and LRH-1) (Fig. 5a) or 24 h (PON1, PCSK9, ApoA1, ABCA1, and ApoC3) (Fig. 5b) except for a mild increase in LDLr expression in HepG2 cells.

Fig. 5.

Relative mRNA expression of inflammatory markers, transcription factors and lipid metabolism–associated genes in HepG2 cells after stimulation with CM derived from THP-1 cells treated with PMA + LPS (CM) or from THP-1 cells that were left non-stimulated (NS). mRNA was isolated at suitable time points based on previous experiments: 4 h for NF-κB p50/p105, TNF-α, A20, SAA, PPARα, LRH-1, and LDLr (a) and 24 h for PON1, PCSK9, ApoA1, ABCA1, and ApoC3 (b). qPCR analyses represent the average of three independent biological experiments. In the first experiment, three biological replicates were analysed. The second and third experiments each involved four biological replicates.* p < 0,05 ** p < 0,01 *** p < 0,001 **** p < 0,0001

The effect of PMA + LPS-stimulated THP-1 CM was also compared with that of CM from LPS-stimulated RAW 264.7 mouse macrophages (Fig. S4). Both types of macrophages induced a pro-inflammatory HepG2 phenotype, with THP-1 cells eliciting a more consistent HDL-related response.

Discussion

Lipid metabolism, a central process in maintaining systemic homeostasis, is predominantly orchestrated by the liver, which regulates the synthesis, uptake, processing, and export of TAG, very-low-density lipoproteins (VLDLs), LDL, free fatty acids (FFAs), and HDL. The liver’s pivotal functions are profoundly sensitive to inflammatory signals, undergoing significant metabolic shifts during both acute and chronic inflammation. Chronic inflammatory states disturb hepatic lipid metabolism contributing to deleterious changes in circulating lipoproteins, including the alteration of anti-inflammatory HDL to the pro-inflammatory piHDL and promoting the development of cardiovascular complications through proatherogenic mechanisms [3, 11]. Recently, many experimental models for studying liver inflammation have employed single-cytokine or LPS stimulation of liver cells. However, since systemic inflammation is typically characterised by the orchestrated effects of multiple circulating cytokines and mediators, such models may lack the necessary complexity of the human body, including potential synergistic activities of these mediators. Development of a complex in vitro liver model is essential for understanding inflammation-induced alterations in lipid metabolism and for evaluating the mechanisms and therapeutic potential of anti-inflammatory agents in a physiologically relevant context. One approach to developing such an in vitro model is to expose hepatocytes (HepG2) to a complex mixture of pro-inflammatory mediators released by activated immune cells (THP-1) [10]. To define the optimal experimental conditions, numerous preliminary experiments were conducted using different types of media and supplements to optimise the maintenance of both cell cultures (THP-1 and HepG2), several types of THP-1 inflammatory stimuli, and others. In this work, the most relevant experimental setting is presented. The most frequently used LPS concentrations for activating PMA-differentiated THP-1 cells are 100 ng/ml and 1 µg/ml. We employed a concentration of 1 µg/ml of LPS to elicit higher production of proinflammatory cytokines. LPS concentrations in the range of 100 ng/ml − 1 µg/ml may be subject to protocol optimisation for customised inflammatory responses [12–15].

In the CM, we estimated the concentrations of the two most important and extensively studied primary pro-inflammatory mediators in in vitro and in clinical studies, TNF-α and IL-1β, to confirm that the THP-1 cells had been successfully activated to secrete cytokines into the medium [16]. The strong up-regulation of inflammatory genes in PMA + LPS-stimulated THP-1 cells (Fig. S1) and the increased cytokine concentration in CM observed in our experiments (Fig. 2) are consistent with the literature [14, 15, 17, 18], where a stronger activating effect of the combination of PMA and LPS, compared with that of PMA [18] or LPS [19] alone, has also been reported. This finding also correlates well with the changes observed in HepG2 cells stimulated with CM from differently activated THP-1 cells (Fig. S2), where the combination of PMA and LPS produces the most potent CM in terms of its effect on ApoA1, SAA and PON1 expression. The mean final IL-1β concentration added to HepG2 cells (23 pg/ml), as determined by ELISA, exceeds plasma levels in patients with chronic inflammation [20] but aligns closely with the pooled mean across 24 studies in a sepsis meta-analysis [16]. The mean final TNF-α concentration added to HepG2 cells (6.4 ng/ml) substantially exceeds plasma levels in chronic [21] (meta-analysis) or acute [16] inflammation. HepG2 is a widely used human cell line exhibiting remarkable resistance to inflammatory stimuli, requiring significantly higher concentrations of proinflammatory mediators like TNF-α, IL-1β, or LPS to induce meaningful responses compared to primary hepatocytes or other hepatic models. HepG2 cells downregulate key inflammatory pathways, therefore requiring unphysiologic mediator levels (10–100 ng/ml TNF-α) to elicit responses to proinflammatory stimuli [22]. Future investigations will more comprehensively characterise the macrophage-derived factors driving the observed HepG2 responses.

Whilst in our experiments remodelling CM from stimulated THP-1 cells did not influence the viability, cell cycle or morphology of HepG2 cells (Fig. 3), several laboratories encountered challenges in creating this in vitro model because of the significantly decreased viability of HepG2 cells (personal communication) or changes in cell morphology [23]. One potential cause of this detrimental effect might be the use of Dulbecco’s Modified Eagle´s medium high glucose (DMEM HG) instead of RPMI medium. DMEM HG, which is more commonly used than RPMI 1640 for culturing HepG2 cells, can cause additional oxidative stress and inflammation, as we discussed in more detail previously [24].

The time-course experiments in HepG2 cells with CM provided a more detailed characterisation of the model. The increased expression of mRNAs encoding the pro-inflammatory cytokine TNF-α and the transcription factor NF-κB indicates that pro-inflammatory pathways have been successfully induced in our model. The time-course results, where NF-κB, TNF-α, and the member of negative feedback loop A20 are up-regulated only in the first 2–4 h and resolving naturally in HepG2 cells, correspond to the well-known transient up-regulation of NF-κB and pro-inflammatory cytokines [25]. This self-limiting response mirrors physiological hepatic inflammation (e.g. acute phase response) to avoid chronic damage and to enable the repair of the liver tissue. Unlike the aforementioned inflammatory markers in this model, the expression of SAA, a key acute-phase protein, remained elevated throughout the entire 28-hour experimental timeframe. Administering single doses of TNF-α, IL-1β or IL-6 to HepG2 cells results in different transcriptional time profiles, but combining these cytokines can further enhance and prolong SAA mRNA induction [26, 27]. The liver, being the main site of SAA production, is strongly stimulated by TNF-α, IL-1β, and IL-6 to synthesise SAA, which subsequently becomes a major component of piHDL [28]. The same cytokines downregulate the hepatic transcription of PON1, a negative acute-phase protein, leading to the diminished antioxidant capacity of HDL in preventing the oxidative modification of lipoproteins [3, 11].

Together with decreased ApoA1, decreased PON1 and increased SAA are typical features of HDL to piHDL remodelling, correlating with changes observed in patients with CID [3]. Reduced expression of the surface transporter ABCA1, which is important for HDL biogenesis, may lead to impaired RCT. The observed changes in ABCA1 mRNA expression, alongside increased LDLr mRNA expression and decreased PPARα expression, are consistent with the findings of the study by Ma et al. [29], in which the impact of inflammation on HepG2 cells and the livers of ApoE knockout mice was investigated. Decreased ABCA1-mediated cholesterol efflux and increased LDLr-mediated influx may account for increased cholesterol accumulation in hepatocytes. Increased LDL uptake by HepG2 cells upon stimulation with CM from LPS-treated THP-1 cells was also observed in the study of Grove et al. [30]. Up-regulated hepatic LDL uptake might contribute to the decreased plasma concentration of LDL, a feature typically observed in patients with CID [2]. Similarly, Liu et al. reported reduced PCSK9 protein expression along with increased LDLr mRNA and protein levels in inflammation-stimulated HepG2 cells and in casein-treated ApoE KO mice. These changes were suggested to be mediated by the mTOR pathway [31].

Many of the aforementioned changes can be attributed to the downregulation of the transcription factors PPARα and LRH-1 or the up-regulation of NF-κB, which, in addition to our model, has also been observed in inflammatory models in the literature [29, 32, 33]. PPARα and NF-κB, which have opposite and mutually inhibiting effects, may be involved in regulating the mRNA expression of ApoA1, SAA, ABCA1, and PON1 [34]. Additionally, the decrease in LRH-1 mRNA expression, considered a negative regulator of the liver acute phase response, may contribute to increased SAA expression [35] and decreased ApoA1 expression [36]. Similarly, inflammatory conditions downregulate hepatocyte nuclear factor 4α (HNF4α) expression and its direct regulatory effects on acute-phase gene expression, including SAA, as well as on the repression of the pro-inflammatory IL-6/STAT3 pathway and the production of apolipoproteins, such as ApoA1 and ApoC3 [37–39].

The reproducibility of the experimental model was verified by repeating the procedure in an independent laboratory using different cell batches and laboratory equipment (Fig. S4). The results obtained were consistent with those generated in the original laboratory setting, confirming the robustness of the model.

Despite the consistency of previous results with our model, there are also studies from inflammatory models with contradictory observations. For example, Cui et al. observed increased PCSK9 mRNA expression in CRP -treated HepG2 cells [40], and Xie et al. observed increased ABCA1 mRNA expression in rats with adjuvant arthritis [41]. A study by Bohan et al. revealed increased LRH-1 mRNA expression in HepG2 cells after inflammatory cytokine stimulation [42]. However, the designs of the studies differed in terms of the experimental models and stimulation approaches used.

ApoA1 and PCSK9, selected as representative proteins that play key roles in lipoprotein metabolism, were quantified in HepG2 lysates rather than in the medium. Although secretion analysis provides physiological relevance, intracellular quantification captures changes in production [43–45].

THP-1 cells in an undifferentiated state generally produce very low to undetectable levels of classic pro-inflammatory cytokines (as confirmed in our work, Fig. 2b). However, they may still secrete other bioactive molecules capable of influencing the HepG2 transcriptome. Since the CM from NS THP-1 cells induced no significant changes in gene expression (except for a mild increase in LDLr expression), gene expression analysis confirmed that the observed significant short-term and long-term effects in HepG2 cells are the result of pro-inflammatory cytokines and mediators produced following the stimulation of THP-1 cells with PMA + LPS (Fig. 5).

Both THP-1 and RAW 264.7 cell lines are widely used in macrophage-related studies [46, 47]. Comparative proteomic analyses indicate that stimulated THP-1-derived macrophages and RAW 264.7 cells share broadly similar, although not identical, inflammatory and polarisation profiles, reflecting species- and cell-line–specific differences [46]. Since CM from stimulated mouse RAW 264.7 macrophages elicited effects in HepG2 cells comparable to those from stimulated THP-1-derived macrophages (Fig. S4), the lipid-metabolism–modifying activity appears to be a common property of pro-inflammatory stimulated macrophages.

Conclusion

In the optimised HepG2 model stimulated with CM from PMA + LPS-exposed THP-1 cells, we observed changes in mRNA or protein expression consistent with the data from CID patients, animal models and in vitro inflammatory models. These changes included decreased ApoA1, PON1 and PPARα mRNA expression, and decreased ApoA1 and PCSK9 protein expression, as well as increased LDLr and SAA mRNA expression. These effects were not associated with any detrimental effects on cell viability, the cell cycle or morphology. Based on these findings, we recommend our model as a promising tool for studying inflammation-driven changes in liver metabolism in future research. The model could be used to study the pathways and mechanisms involved in inflammatory lipid remodelling, or to test drugs for its normalisation.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

All authors contributed to the study conception and design. The majority of data production was carried out by VV under supervision of ĽP, with assistance from MB for qRT-PCR, PV and JK for Western blot analyses, GG and JH for ELISA, MTT and the cell cycle. The original draft of the manuscript was written by VV and ĽP. Proofreading and editing were performed by ĽP. DK contributed to the discussion and refinement of the manuscript, provided suggestions for the experiments and supervised the reproducibility testing of the model. All authors reviewed and approved the final manuscript.

Funding

Open access funding provided by The Ministry of Education, Science, Research and Sport of the Slovak Republic in cooperation with Centre for Scientific and Technical Information of the Slovak Republic. This work was supported by a grant from the European Union’s Next Generation EU through the Recovery and Resilience Plan for Slovakia under project No. 09I03-03-V05-00012 (part of experimental costs), and by a grant from the COST Action AtheroNET, CA21153, as part of a short-term scientific mission (STSM),supported by COST (European Cooperation in Science and Technology) (travel costs).

Data availability

All data supporting the findings of this study are available within the paper and its Supplementary Information.

Declarations

Competing interests

The authors declare no competing interests.