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Donafenib is an improved version of sorafenib in which deuterium is substituted into the drug’s chemical structure, enhancing its stability and antitumor activity. Donafenib exhibits enhanced antitumor activity and better tolerance than sorafenib in preclinical and clinical studies. However, the specific mechanism of its effect on hepatocellular carcinoma has not been reported. Iron deposition is a cell death pattern caused by disturbances in iron metabolism. Apoptosis is a form of programmed cell death. They may interact with each other during cell death. This study mainly explores the potential mechanism of donafenib activating the p53 signaling pathway, inducing iron deposition, and enhancing cell apoptosis in hepatocellular carcinoma. Hepa1-6 and Huh7 cells were treated with various concentrations of donafenib. Scratch healing and pore migration tests were conducted. Analyze apoptosis through flow cytometry and TUNEL fluorescence labeling. RNA sequencing was conducted on both untreated and donafenib-treated Huh7 cells. The key proteins involved in ferroptosis (SLC7A11, GPX4) and apoptosis (caspase3, caspase8, Bax, Bcl-2, p53) were then evaluated using immunoblotting and immunohistochemical staining. Reactive oxygen species (ROS) levels in the cancer cells were measured. Donafenib treatment resulted in a dose-dependent decrease in the proliferation, migration, and invasion capabilities of cancer cells. There was an increase in apoptosis rates and ROS accumulation, and a reduction in tumor volume. The key proteins involved in ferroptosis and apoptosis underwent significant changes. Donafenib activates the p53 signaling pathway, induce ferroptosis, and enhance apoptosis, suggesting its potential as an effective therapeutic agent for HCC.
Introduction
Hepatocellular carcinoma (HCC), the predominant malignancy of the liver, ranks among the most common types of cancer worldwide, currently occupying the second spot in China in terms of mortality rates linked to primary liver cancer [1, 2]. Due to the insidious nature of HCC, as well as its high rates of late-stage metastasis and recurrence, diagnosis and treatment are challenging. At present, surgery is still the main treatment for liver cancer [3]. However, many patients diagnosed with liver cancer are already in the middle or late-stages and have thus exceeded the window for surgical intervention [4]. Liver cancer has a high recurrence rate and distant metastasis, while radiotherapy, chemotherapy, targeted therapy, and immunotherapy all have limited effects on this condition, resulting in a poor prognosis [5, 6–7].
Donafenib, a deuterated derivative of sorafenib, is an oral multi-receptor kinase small molecule inhibitor. Deuterium is a stable isotope with a larger mass than hydrogen, therefore it has higher metabolic stability. Introducing deuterium into drug molecules can prolong the half-life of the drug in the body, reduce metabolic rate, thereby reducing the clearance rate of the drug in the body and improving its bioavailability and efficacy. Specifically, donafenib replaces the methyl group on the sorafenib molecule with a triple methyl group. Compared with sorafenib, donafenib has a more stable metabolic process in the body, slower drug degradation and clearance, and longer lasting drug efficacy [8]. Donafenib has gained approval as the standard treatment for advanced HCC patients. This innovative compound exhibits promising results not only in combatting liver cancer but also in addressing conditions such as thyroid cancer and fatty liver disease [9]. Phase II–III clinical trial data show that donafenib has a better therapeutic effect than sorafenib because it is more stable [10]. At present, the mechanism through which donafenib treats cancer is not fully understood, and research on donafenib administration in liver cancer cases is relatively rare. Further research on this drug is therefore necessary.
Cell death, particularly apoptosis, holds significant importance in the suppression of tumors, with resistance to cell death being a defining feature of cancer. Due to the avoidance of apoptosis by tumor cells, which leads to treatment resistance and recurrence, much research has been dedicated to finding alternative processes to effectuate cancer cell death, such as necrosis, pyroptosis, iron deposition, and corrosion [11, 12]. Currently, many anticancer drugs in clinical practice promote or inhibit the activity of various apoptotic signaling pathways, thereby causing the death of cancer cells [13].
P53 plays an important role in preventing tumor development and is crucial in improving the efficacy of tumor treatment. After cellular stress occurs, p53 regulates the expression of key molecules related to exogenous death receptors and endogenous apoptosis-dependent pathways, thereby inhibiting cell survival [14].
In the nucleus, P53 has regulatory effects on multiple apoptosis-related proteins, such as PUMA. Following its expression in the cytoplasm, PUMA can interact with p53/Bcl-xL, causing p53 to detach and signaling the rupture of the mitochondrial membrane structure, exuding enzymes that induce cell apoptosis [15].
Iron death represents another powerful tumor suppression mechanism. It may have evolved to eliminate precancerous cells exposed to metabolic stress or nutrient deprivation. Iron apoptosis is a form of cell death regulated by oxidative stress and iron dependence, and it is mainly induced by the excessive production of ROS [16].
As SLC7A11 is one of the cysteine/glutamate reverse transporters, inhibiting its expression can inhibit glutathione synthesis. In addition, glutathione is a reducing cofactor of GPX4 (glutathione peroxidase). Therefore, inhibiting SLC7A11 not only affects glutathione but also impacts the expression of GPX4, thereby weakening cells’ antioxidant capacity. When this occurs, lipid peroxides are more likely to accumulate in the body, and cells become more prone to ferroptosis [17, 18–19].
SLC7A11 has been established as a central hub that connects ferroptosis with its proposed tumor-suppressive function. The expression of SLC7A11 can be inhibited through transcriptional regulation. SLC7A11 has been identified as a p53 transcriptional target inhibited by p53. Furthermore, it was demonstrated that the p53 component promotes iron apoptosis under various iron-induced conditions by inhibiting the expression of SLC7A11, while the upregulation of SLC7A11 due to by p53 deficiency promotes iron apoptosis resistance [20, 21]. In HCC, abnormal regulation of iron metabolism may lead to abnormal proliferation and drug resistance of tumor cells. Tumor cells may exhibit drug resistance by enhancing their antioxidant capacity to resist oxidative stress. Abnormal iron metabolism in tumor cells may also affect various signaling pathways, such as PI3K/ Akt/ mTOR, which play a key role in regulating cell growth, survival, and drug resistance [22]. By targeting iron homeostasis, regulating iron metabolism and oxidative stress levels, and intervening in related signaling pathways, new treatment strategies may be provided to address the issue of drug resistance in HCC.
Various studies have shown that donafenib has strong antitumor effects, but its role in HCC is still poorly studied. In this study, the impact of donafenib on the progression of liver cancer cells was explored, with a focus on activating the p53 signaling pathway, inducing ferroptosis, and enhancing cell apoptosis. These findings provide a theoretical basis for the use of donafenib in cancer treatment and addressing the issue of cancer cell resistance.
Methods
All experiments were conducted in biological replication, with each experiment repeated three times.
Cell culture
Hepa1-6 and Huh7 cell lines were procured from the Shanghai Cell Bank at the Chinese Academy of Sciences and the American Typical Culture Center, respectively. The Hepa1-6 cell line was specifically isolated from BW7756 liver cancer induced in C57/L mice. For the Huh7 cell culture, we used Dulbecco’s Modified Eagle’s medium (Thermo Fisher Scientific, C11995500BT) supplemented with 10% fetal bovine serum (GibcoLife Technologies, Carlsbad, CA) and 1% penicillin/streptomycin (P1400, Solarbio, China). The cells were maintained in an incubator at 37 °C with 5% CO2. Meanwhile, the Hepa1-6 cells were cultured in Roswell Park Memorial Institute 1640 medium (Thermo Fisher Scientific, C11875500BT) with the same supplements and incubator conditions as the Huh7 cells.
Reagents and antibodies
Donafenib and Dimethyl sulfoxide (DMSO) was purchased from MedChemExpress. Donafenib was dissolved in DMSO. Bcl-2 monoclonal antibody (#68,103–1-Ig), p53 polyclonal antibody (#10,442–1-AP), Caspase8 monoclonal antibody (#66,093–1-Ig), Beta Actin monoclonal antibody (#66,009–1-Ig), HIF-1 alpha monoclonal antibody (#66,730–1-Ig), GPX4 monoclonal antibody (#67,763–1-Ig), Caspase3 monoclonal antibody (#66,470–1-Ig), CD71 monoclonal antibody (#66,180–1-Ig), PD-L1 monoclonal antibody (#66,248–1-Ig), Bax polyclonal antibody (#50,599–2-Ig), SLC7A11 polyclonal antibody (#26,864–1-AP), HRP conjugated Effinipure goat antirabbit IgG (H + L) (#SA00001-2), and HRP conjugated Effinipure goat antimouse IgG (H + L) (#SA00001-1) were analyzed using a cell apoptosis analysis kit (#C1052) purchased from Protein Group and Beyotime Biotechnology.
Cell viability assay
A Cell Counting Kit-8 (Biosharp) was used to detect the degree of cytotoxicity of donafenib on Hepa1-6 and Huh7 cells, and each group was repeated three times. The cell density was adjusted to 5 × 104 cells/mL, 100 μL was added to a 96-well plate, cultured at 37 °C in a 5% CO2 incubator overnight for 24 h, and then treated with different concentrations of donafenib for intervention. 10 µL CCK8 was added at different detection time points and incubated for 2 h. The optical density (OD) was read with an absorbance value of 450 nm on the microplate reader. The semicirculated inhibitory concentration (IC50) of acetylides at lodges on each cell was calculated by Prism 9.0 software program, and the proliferation curve was made. Statistical analysis using Prsim 9.0.
Transwell migration/invasion assay
The matrix gel was diluted in serum-free medium at a ratio of 1:9 and placed on the upper surface of the Transwell chamber bottom membrane. It was incubated at 37 °C for 2 h. After 2 h, suck out the excess matrix gel. Cells were starved by serum for 12 h. When measuring cell migration, no matrix gel was added. When measuring cell invasion, matrix gel was added. Add 300 µL serum-free medium and 8 × 104 Huh7 or Hepa1-6 cells to each Transwell chamber. Add 800 µL of culture medium containing 10% FBS into the lower chamber of a 24 well plate. The experimental group was divided into a control group (add 1 µL DMSO to every 1 mL of culture medium), donafenib L group (5 µM/L), donafenib M group (10 µM/L), and donafenib H group (20 µM/L). The DMSO content in each group’s culture medium should not exceed one thousandth. After culturing with donafenib for 24 h, the cells were fixed and stained with 0.1% crystal violet for 60 min. The cells that crossed the membrane were observed and counted under a microscope. Quantitative analysis was performed using ImageJ software. Statistical analysis using Prsim 9.0.
Wound-healing invasion assay
Hepa1-6 and Huh7 cells were digested and seeded into 6-well plates. According to the calculated IC50, they were divided into a control group (add 1 µL DMSO to every 1 mL of culture medium), donafenib L group (5 µM/L), donafenib M group (10 µM/L), and donafenib H group (20 µM/L). When the cell density reaches 80%, use a 100 µL plastic pipette to draw a perpendicular line perpendicular to the well plate and the marked line, so that the scratch intersects with the marked line, forming several intersection points as fixed detection points and washed three times with phosphate buffered saline (PBS). After being washed, the cells were added to a 2% FBSDMEM medium containing different concentrations of donafenib, and pictures were taken at 0 and 24 h under an inverted microscope (Olympus). A transwell chamber (8 µm pore size, BD) was coated with 100 µL of Matrix (285 µg/mL, Corning) and placed in an incubator at 37 °C for 1 h to gelatinize.
We then added 600 µL of culture medium (containing 10% FBS) to each well of a 24-well plate. We placed a transwell culture chamber over the wells and added 200 µL of culture medium (excluding 10% FBS) containing 5 × 104 cells and the corresponding donafenib concentrations to each chamber. After a 48-h cultivation period, we rinsed the upper chamber with PBS, discarded the cells from the upper chamber, affixed the cells to the chamber’s base using methanol, and colored them with 0.1% crystal violet for 30 min at room temperature. Following washing and drying, the stained cells were deemed to have penetrated into the lower chamber. Photos were taken under an inverted microscope. Statistical analysis using Prsim 9.0.
Cell apoptosis analysis
Hepa1-6 and Huh7 cells were digested, and 2 mL of culture medium (2 × 105 cells/ml) were added to each well on a 6-well plate. The experimental group was divided into a control group (add 1 µL DMSO to every 1 mL of culture medium), donafenib L group (5 µM/L), donafenib M group (10 µM/L), and donafenib H group (20 µM/L). Following normal cultivation for 24 h, the different groups of cells were treated with the corresponding concentrations of donafenib for 24 h. The Beyotime cell apoptosis analysis kit was employed to detect apoptosis in the cells, while flow cytometry was used to assess the distribution pattern of apoptotic cells. Stain with Servicebio TUNEL fluorescence kit, take photos under fluorescence microscope, and calculate and analyze fluorescence intensity using ImageJ. Statistical analysis using Prsim 9.0.
RNA sequencing
The Huh7 cells were digested in a suspension, maintaining a cell concentration of 2 × 105 cells per milliliter. These cells were dispensed into a 6-well plate, with 2 ml added to each well. We next set up a blank control group and an experimental group (20 µM/L), repeating the process three times. After 24 h of normal culture, we collected the cells and extracted their RNA using the Trizol method. This step requires measuring the concentration and purity of the extracted RNA.
We enriched the mRNA with poly(a) tails using oligo (DT) microbeads and randomly fragmented it in fragment buffer. We employed a designated reverse transcriptase system to generate the initial cDNA strand, using mRNA fragments as templates and arbitrary oligonucleotides as initiators. We degraded the RNA strand with RNaseH and harnessed the double-stranded cDNA for the ligation of sequencing connectors. We filtered cDNA fragments ranging from 370 to 420 base pairs using Ampure XP beads for the purpose of PCR amplification. Subsequently, the purified PCR products were again refined with Ampure XP beads. Our constructed library was subjected to transcriptome sequencing via the illuminahiseq4000 platform. We performed a differential analysis of the obtained data, selecting genes with significant differences and identifying genes with P values of less than 0.05 as significant differential genes. We drew a volcano plot and performed an enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology.
Intracellular ROS determination
The Hepa1-6 and Huh7 cells were digested, and we distributed 1 mL of culture medium, which comprised 1 × 106 cells, into each well of a 6-well plate. The plate was maintained at 37 °C in 5% CO2 for 24 h. Subsequently, we introduced complete cell culture media containing varying concentrations of donafenib into the cell plate, dividing it into distinct groups, for an additional 24 h. The process was completed according to the instructions in the Reactive Oxygen Specifications Assay Kit (Beyotime). We observed the results, took photos under an inverted fluorescence microscope and analyzed them on a flow cytometer. We used ImageJ software to calculate and analyze the fluorescence intensity. Statistical analysis using Prsim 9.0.
Western blotting analysis
The Hepa1-6 and Huh7 cells, which were processed under different conditions, were treated separately, and protein lysis was performed on ice. Once the cultivation process was finalized, it was necessary to cool the centrifuge to a temperature of 4 °C. Subsequently, we discarded the culture medium and rinsed the cells thoroughly three times using PBS. The cells were exposed to RIPA lysis solution for 15 min. The treated sample was transferred to a cooled centrifuge and centrifuged at 4 °C for 10 min. The supernatant obtained following centrifugation contained the desired protein.
We collected the supernatant, measured the protein concentration using a BCA reagent kit, and added a loading buffer (about a quarter of the volume of the protein in the new EP tube). Electrophoresis was performed at 90 V for 10 min and then at 130 V for 70 min. The membrane transfer time was adjusted according to the target protein. After the membrane transfer was completed, 5% skim milk was sealed. After 30 min at 37 °C, the membrane was washed at room temperature for 30 min using TBST. After the sealing, the membrane was washed 3 times for 5 min each time. The primary antibodies (SLC7A11, BAX, Bcl-2, GPX4, CD71, Caspase3, Caspase8, HIF-1α, PD-L1, p53, and β-actin) were incubated overnight at 4 °C or at room temperature for 1 h. The membrane was then washed three times: the first time for 10 min, the second for 7 min, and the third for 5 min. The secondary antibodies were incubated at room temperature for 1 h. The film was washed 3 times for 5 min each. Following exposure, ImageJ software is used to quantitatively analyze the grayscale values of target protein bands and calculate the relative expression levels of target proteins. Statistical analysis using Prsim 9.0.
Xenotransplantation experiments and immunohistochemistry
Five-week-old BALB/c nude mice were acquired from Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China). All experimental surgical procedures and protocols undergone by these mice underwent stringent evaluation and received clearance from the Animal Care and Use Committee of Guangxi Medical University. The mice were housed in a pathogen-free environment with a controlled light–dark cycle of 12 h each. After the mice successfully acclimated to their new surroundings, 5 million Huh7 cells were administered via subcutaneous injection into the right side of each mouse, with 4 mice in each group, to establish liver cancer xenograft models.
Tumor sizes were measured and recorded once every 3 days, with 1/2 × (length × width 2) used as the formula to calculate tumor volumes. Taking as a starting point the average tumor volume, which was around 100 mm3, the mice were divided into four groups according to the different treatment methods [control group, donafenib L group (5 mg/kg), donafenib M group (10 mg/kg), and donafenib H group (20 mg/kg)], and the relevant drug, i.e., donafenib (100 μL) or an equal amount of physiological saline (100 μL), was intraperitoneally injected every 2 days. This procedure continued for 2–3 weeks. After the treatment, the mice were euthanized, and the tumors were removed for histological analysis. We performed IHC staining according to the manufacturer’s instructions (Zhongshan Jinqiao, Beijing, China). Quantify staining intensity and positive cell count using ImageJ analysis, and perform statistical analysis using Prsim 9.0.
HE staining
The tissue was soaked in 4% paraformaldehyde and fixed at 4 °C for more than 24 h. We used a paraffin-embedding machine to embed the tissue and cut it into 4-μm slices using a tissue-slicing machine. We let the specimen dry for 24 h at room temperature. After the wax was removed using xylene and ethanol, the paraffin-embedded tumor and normal tissue sections underwent rehydration. Subsequently, they were stained with eosin and hematoxylin. Finally, we examined and captured images of the slices under a microscope.
Statistical analysis
A statistical analysis was performed using the Prism 9.0 software program. The outcomes are expressed as mean values along with the standard deviation as derived from three or more observations. The statistical significance of the findings was determined by applying either Student’s t-test or a one-way analysis of variance. Statistical significance was set at a p-value < 0.05. All bioinformatic analyses were conducted using R software (4.1.2).
Results
Effect of donafenib on cell proliferation
The CCK8 experiment demonstrated that donafenib exerted a notable suppressive effect on the growth of Hepa1-6 and Huh7 cells compared to the control group. Furthermore, it revealed a direct proportional relationship between the inhibitory effect and the concentration of donafenib. Upon administering donafenib for 24 h, the IC50 values for the Hepa1-6 and Huh7 cells were determined to be 10.9 μM and 14.2 μM, respectively. After 48 h, the values were 9.1 μM and 5.0 μM, respectively (Fig. 1A, B). The Hepa1-6 and Huh7 cells were subjected to subsequent experimental treatment at 5, 10, and 20 μM (as L, M, and H concentrations), respectively.
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Fig. 1
Effect of donafenib on the proliferation capacity of Hepa1-6 and Huh7 cells. A Hepa1-6 cells were exposed to varying concentrations of donafenib for durations of 24 and 48 h, enabling the computation of the cell inhibition rate. The IC50 for 24 h was 10.9 μM, and for 48 h, it was 9.1 μM. B We calculated the rate of inhibition of Huh7 cells after 24 and 48 h of treatment with different concentrations of donafenib. The IC50 for 24 h was 14.2 μM, and for 48 h, it was 5.0 μM
Effect of donafenib on cell migration and invasion
The effects of donafenib on cell migration were evaluated using a scratch assay. We discovered a significant suppression of the migratory capabilities of the Hepa1-6 and Huh7 cells. Furthermore, it was observed that the migratory ability of these cells gradually diminished as the concentration of donafenib increased (Fig. 2A–D). The migration ability of the high concentration Donafenib group was significantly lower than that of the control group (P < 0.05). Based on the application of Matrigel in transwell experiments, we explored whether donafenib affects cell invasion ability. The results showed that as the concentration of donafenib increased, cell infiltration gradually decreased (Fig. 3A–H). The invasion ability of the high concentration Donafenib group was significantly lower than that of the control group (P < 0.05). This suggests that donafenib may inhibit the invasive capability of Hepa1-6 and Huh7 cells.
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Fig. 2
Effect of donafenib on the migration of Hepa1-6 and Huh7 cells. A and C represent the migration region of Huh7 treated with donafenib for 24 h. B and D represent the migration region of Hepa1-6 cells treated with donafenib for 24 h. As the concentration of donafenib increased, the migration ability of Hepa1-6 and Huh7 cells gradually decreased. Data are represented as the average of three trials ± standard deviation. ***, P < 0.001, ****, P < 0.0001
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Fig. 3
Effect of donafenib on the invasiveness of Hepa1-6 and Huh7 cells. We detected the number of invasive Huh7 (A, B, E, F) and Hepa1-6 (C, D, G, H) cells treated with donafenib for 24 h using a transwell assay and crystal violet staining. As the concentration of donafenib increased, the invasive ability of Huh7 and Hepa1-6 cells gradually decreased. Data are represented as the average of three trials ± standard deviation. *, P < 0.05, ***, P < 0.001, ****, P < 0.0001
Effect of donafenib on cell apoptosis
By comparing the NC group with the drug group, we found that donafenib can induce apoptosis in Hepa1-6 and Huh7 liver cancer cell lines. The proportion of late-stage apoptotic cells in the treatment group (20 µM/L) was higher than that in the NC group (0 μM) (P < 0.05). The proportion of late-stage apoptosis in Hepa1-6 cells increased from 4.96% to 13.34%, while the proportion in Huh7 cells increased from 4.02% to 8.40% (Fig. 4A–D). In order to further test the ability of donafenib to induce apoptosis in liver cancer cells, we also performed TUNEL fluorescence labeling and found that as the concentration of donafenib increased, TUNEL fluorescence gradually increased in liver cancer cells (P < 0.05) (Fig. 5A–D). Thus, there may be a dose-dependent relationship between the concentration of donafenib and the apoptosis rate of Hepa1-6 and Huh7 cells.
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Fig. 4
Effect of donafenib on apoptosis in Hepa1-6 and Huh7 cells. A, C Effect of donafenib on Hepa1-6 cells’ apoptosis. B, D Effect of donafenib on Huh7 cells’ apoptosis. As the concentration of donafenib increased, both apoptosis rates gradually increased. Data are represented as the average of three trials ± standard deviation. ns, P > 0.05, ****, P < 0.0001
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Fig. 5
Further investigate the effect of donafenib on apoptosis of Huh7 and Hepa1-6 cells through TUNEL labeling. TUNEL fluorescence of (A, B) Huh7 cells. TUNEL fluorescence of (C, D) Hepa1-6 cells. As the concentration of donafenib increases, TUNEL fluorescence gradually strengthens. The data is represented as the mean ± standard deviation of three experiments. ns, P > 0.05, *, P < 0.05, **, P < 0.01, ****, P < 0.0001
Screening differentially expressed genes in cells treated with donafenib, exploring gene function, and signal pathway enrichment analysis
To further investigate the potential mechanisms by which donafenib inhibits survival and metastasis in liver cancer cells, we sequenced Huh7 cells and found through RNA seq detection and analysis that the expression of multiple genes in HCC cells is regulated by donafenib, with significant upregulation and downregulation observed (Fig. 6A). Through in-depth analysis of the functions and signaling pathways of the differentially expressed genes, we discovered that these genes are predominantly concentrated in crucial biological processes, such as the p53 signaling pathway, cell apoptosis, ferroptosis, fatty acid metabolism, metabolic pathways, the cell cycle, the PPAR signaling pathway, and the MAPK signaling pathway (Fig. 6B, C).
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Fig. 6
Effect of donafenib on the transcriptome of Huh7 cells. A Differential gene volcano diagram. Red signifies a high level of expression in differentially expressed genes, while orange indicates a lower expression level. Gray represents genes that do not exhibit differential expression. B Analysis of functional enrichment to compare differentially expressed genes in the donafenib group and the control group. C Enrichment analysis of signaling pathways to further investigate the differentially expressed genes in the two groups. We selected iron death, cell apoptosis, and the p53 signaling pathway, which are mainly enriched in differentially expressed genes, for further analysis
Effects of donafenib on p53 signaling pathway, ferroptosis and cell apoptosis protein levels
To thoroughly investigate how donafenib inhibits the development and spread of cancer, we explored the expression levels of key proteins involved in the p53 signaling pathway, cell apoptosis, and iron death-related mechanisms through Western blot analysis. The results showed that as the concentration of donafenib increased, the key proteins GPX4 and SLC7A11 involved in iron deposition gradually decreased (P < 0.05). The anti-apoptotic protein Bcl-2, apoptosis-related proteins Caspase3 and Caspase8 also gradually decreased (P < 0.05), and the expression of cell proliferation related proteins CD71, HIF-1 α, and PD-L1 also gradually decreased (P < 0.05), while the tumor suppressor gene p53 and pro apoptotic protein Bax gradually increased (P < 0.05) (Fig. 7A–H). This may indicate that Donafenib can inhibit the proliferation of liver cancer cells, promote p53 expression, activate its downstream signaling pathways, induce iron deposition, and enhance cell apoptosis.
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Fig. 7
Exploring the effects of donafenib on the p53 signaling pathway, apoptosis, and expression of iron death-related proteins in Huh7 (A–D) and Hepa1-6 (E–H) cells through Western blotting. In the Huh7 and Hepa1-6 cell lines, as the concentration of donafenib increased, SLC7A11, GPX4, CD71, HIF-1α, Bcl-2, caspase3, caspase8, and PD-L1 protein were downregulated, while p53 and Bax protein were upregulated. Thus, donafenib can promote cell apoptosis and ferroptosis in Huh7 and Hepa1-6 cells and inhibit their proliferation. *, P < 0.05
Effect of donafenib on cellular ROS levels
To investigate whether donafenib affects ROS accumulation in liver cancer cells in vitro, we used the DCHF-DA method to detect ROS accumulation in Hepa1-6 and Huh7 liver cancer cells treated with different concentrations of donafenib. Both fluorescence microscopy and flow cytometry analysis showed that as the concentration of donafenib increased, the accumulation of ROS in cancer cells gradually increased (P < 0.05) (Fig. 8A–F). Donafenib increases the accumulation of ROS in liver cancer cells, while also inhibiting the expression of iron death key proteins SLC7A11 and GPX4, making liver cancer cells more prone to iron death.
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Fig. 8
D Determine whether donafenib affects the ROS levels of Huh7 (A, B, D, E) and Hepa1-6 (A, C, D, F) cells in vitro through fluorescence microscopy and flow cytometry analysis. As the concentration of donafenib increased, the accumulation of ROS in Huh7 and Hep1-6 cells gradually increased. Data are represented as the average of three trials ± standard deviation. ns, P > 0.05, ***, P < 0.001, ****, P < 0.0001
In vivo analysis of donafenib’s impact on liver cancer cells
To explore the potential impact of donafenib on the emergence and progression of liver cancer in a living organism, we implanted liver cancer cells beneath the skin of nude mice. Once tumors were established, the mice in the treatment group received intraperitoneal injections of varying dosages of donafenib. The findings revealed that as the amount of donafenib rose, the size of the tumor progressively diminished (P < 0.05) (Fig. 9A–C). HE staining analysis of the tumors indicated that all were solid in nature, and notably, the tumors treated with donafenib exhibited extensive necrosis, which became more prominent as the drug’s concentration increased (Fig. 9D). Immunohistochemical staining showed that the expression levels of proteins Ki-67, CD71, HIF-1α, and PD-L1, which are related to cell proliferation, gradually decreased with increasing donafenib concentrations (P < 0.05). Proteins SLC7A11 and GPX4, which are associated with ferroptosis (P < 0.05) (Fig. 10A–E), were increasingly downregulated with rising donafenib concentrations. Proteins Bcl-2, Caspase3, and Caspase8, which are associated with cell apoptosis (P < 0.05) (Fig. 11A–C), were increasingly downregulated with rising concentrations of donafenib, while p53 and Bax were increasingly upregulated with rising concentrations (P < 0.05) (Fig. 12A–F). Comparing the results of immunohistochemistry experiments with those of Western blot analysis, it was found that the expression of donafenib was similar in both, further indicating that donafenib can inhibit the proliferation of liver cancer cells, promote p53 expression, activate its downstream signaling pathways, induce iron deposition, and enhance cell apoptosis.
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Fig. 9
A Representative images of xenograft tumors in nude mice after different treatments. B Summary of the tumor growth curves in each group of mice. C Comparison of tumor weight in each group of mice. Donafenib has a strong inhibitory effect on tumor growth. D Tumor HE staining showed that all tumors were solid, and the tumors in the donafenib treatment group showed extensive necrosis and increased with rising concentrations. Data are represented as the average of three trials ± standard deviation. ns, P > 0.05, *, P < 0.05, **, P < 0.01
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Fig. 10
A–E Immunohistochemical staining showed that the expression levels of proteins Ki-67, CD71, HIF-1α, and PD-L1, which are related to cell proliferation, gradually decreased with increasing donafenib concentration. The proliferation ability of Huh7 and Hep1-6 cells decreased with increasing donafenib concentration. Data are represented as the average of three trials ± standard deviation. ns, P > 0.05, *, P < 0.05, **, P < 0.01, ***, P < 0.001
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Fig. 11
A–C Immunohistochemical staining showed that proteins SLC7A11 and GPX4, which are related to ferroptosis, were downregulated with increasing donafenib concentration. The key proteins that inhibit ferroptosis in Huh7 and Hep1-6 cells decreased with increasing donafenib concentration, which can promote ferroptosis in cells. Data are represented as the average of three trials ± standard deviation. ns, P > 0.05, *, P < 0.05, **, P < 0.01
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Fig. 12
A–F Immunohistochemical staining showed that the apoptotic proteins Bcl-2, caspase3, and caspase8, which promote the occurrence of liver cancer, can be inhibited by donafenib, while donafenib can promote an increase in the expression levels of p53 and Bax proteins, which induce cell apoptosis. Data are represented as the average of three trials ± standard deviation. ns, P > 0.05, *, P < 0.05, **, P < 0.01, ***, P < 0. 001
Discussion
At present, the efficacy of treatment for patients with advanced liver cancer remains unsatisfactory, ultimately making it one of the primary contributors to cancer-associated deaths globally [23]. It is estimated that from 2020 to 2040, the incidence of liver cancer will continue to increase significantly by as much as 55.0%. By 2040, there may be 1.4 million new cases and 1.3 million deaths due to liver cancer [24]. Saving liver cancer patients is a major challenge the world faces today. Therefore, we need to explore new targeted drugs for the treatment of liver cancer and study their potential molecular mechanisms.
Donafenib is a novel oral small molecule multi kinase inhibitor primarily used for the treatment of unresectable or metastatic hepatocellular carcinoma [25]. Its preclinical studies have shown good efficacy and safety, especially in phase II-III studies, where the efficacy and safety of donafenib in first-line treatment of unresectable or metastatic HCC patients with sorafenib were evaluated. In the Phase III clinical study (ZGDH3), a comparison was made between donafenib and sorafenib. The results showed that donafenib significantly prolonged the median overall survival of patients with advanced liver cancer, at 12.1 months and 10.3 months, respectively, with significant statistical differences. In addition, donafenib has shown better safety and good patient tolerance. Donafenib showed superior efficacy in the Phase III clinical trial (ZGDH3), significantly prolonging overall survival and reducing the risk of death by 17%. Since its approval for marketing, sorafenib has been the main drug for the treatment of advanced liver cancer, but its efficacy is not as good as that of donafenib in some aspects [10]. Lenvatinib is not inferior to sorafenib in terms of median survival, but significantly better than sorafenib in terms of progression free survival and objective response rate. Donafenib has also shown outstanding performance in these areas, further demonstrating its advantages in the treatment of advanced liver cancer. Compared with other liver cancer treatment drugs such as regorafenib, cabozantinib, and apatinib, donafenib has better median survival, median progression free survival, disease control rate, objective response rate, and overall response rate [26]. Donafenib has been approved for first-line treatment of advanced liver cancer patients due to its significant efficacy and good safety. Its clinical application prospects are broad, especially in patients who have poor response to existing treatments, and donafenib may become a more effective choice [10]. However, there is limited research on the effects of donafenib on liver cancer. Thus, it is necessary to investigate the potential mechanisms by which it inhibits the occurrence and metastasis of liver cancer. In this study, we demonstrated that donafenib can promote apoptosis in liver cancer cells in vitro and inhibit the proliferation, migration, and invasion of liver cancer cells. Furthermore, we preliminarily demonstrated its ability to kill cancer cells.
Apoptosis is one of the fundamental biological processes involved in the maintenance of a stable intracellular environment and the development of multiple systems. Dysregulation of cell apoptosis is one of the main causes of cancer development. As a programmed form of death, apoptosis exhibits significant differences from necrosis and autophagy, especially in terms of its morphology, biology, and genetics [27]. During the process of active cell death, apoptosis is governed by genes, and there remains a need for deeper exploration of its regulatory mechanism.
This study discovered that donafenib exhibits a notable capacity to enhance cell apoptosis, with a marked variation in the apoptosis rate in direct correlation to the escalation of the drug concentration. Our findings further suggest that donafenib exerts a robust inhibitory effect on the proliferation of HCC cells, effectively promoting the occurrence of cell apoptosis.
In recent years, to explore drug targets and mechanisms of action, many scientific and technological advancements have emerged, prominent among which is RNA-seq. It facilitates transcriptome analysis, enables deep sequencing from tissue samples, and yields qualitative and quantitative expression information [28]. We sequenced Huh7 cells and found through RNA-seq detection and analysis that donafenib significantly promoted or inhibited the expression of multiple genes in the HCC cells. After analyzing the functions of the differentially expressed genes and their associated signaling pathways, we discovered that these genes are predominantly involved in functions such as cell apoptosis, the p53 signaling pathway, ferroptosis, fatty acid metabolism, metabolic routes, and the cell cycle. The inhibition of liver cancer cell occurrence and progression holds utmost significance, with the p53 signaling pathway, cellular apoptosis, and iron death playing pivotal roles in this process. It is necessary to further explore the impact of donafenib on these pathways.
Reports have indicated that p53 can inhibit tumor growth and is one of the key proteins that inhibits tumor occurrence and development. P53 regulates the expression of many genes, most of which are related to cell proliferation, differentiation, aging, and apoptosis, playing a key role in response to genotoxicity or cellular stress [29]. The unconventional prefolding protein RPB5 interactor promotes the ubiquitination and degradation of p53 in a TRIM28-MDM2-dependent manner. Furthermore, when the promoter of stearoyl CoA desaturase 1 (SCD1) binds to p53, p53 transcription is inhibited. The combination of SCD1 inhibitors and donafenib has shown promising antitumor effects in organoid and xenograft tumors derived from p53 wild-type HCC patients [30]. The crucial function of p53 lies in regulating the Bcl-2 family members that are instrumental in fostering cell survival and apoptosis. Among these Bcl-2 family genes, Bax, Noxa, PUMA, and bid constitute a pivotal subset that is specifically targeted by p53 [31, 32–33]. Due to its crucial antitumor function, p53 often becomes a target for inactivation. In nearly half of all malignant tumor cases, p53 undergoes deleterious mutations or deletions [34].
The cytosine aspartic acid-specific protein family is mainly responsible for completing cell apoptosis. Cysteine plays a crucial role in cell apoptosis, with caspase-2, -8, -9, and -10 acting as promoters, and caspase-3, -6, and -7 acting as executors. This dual functionality establishes caspase as the central component underlying cellular programmed death [26]. In normal cells, the activation of caspase3 may significantly alter the stable state of the cell genome, leading to sustained DNA damage and promoting the transformation of normal cells into tumor cells [35]. In cancerous cells, the activation of caspase8 can potentially amplify the aggressive invasive and metastatic capabilities of malignant tumor cells [36].
The available research indicates that the expression of SLC7A11 protein is notably higher in liver cancer cells than in normal liver cells, and a trend has been observed in which increased expression correlates with a poorer prognosis [37, 38]. Therefore, controlling the expression of SLC7A11 protein may be beneficial for patient prognosis. Reports have indicated that GPX4 protein is present in both cytoplasm and mitochondria. GPX4 protein plays different functions in these two locations, including antioxidant defense and regulation of lipid metabolism. Inhibiting GPX4 activity triggers ferroptosis. Thus, GPX4 is a promising target for treating resistance to cancer cells through ferroptosis [39]. The principal factor that typically determines whether a cell undergoes apoptosis is the equilibrium established between the proteins that promote apoptosis and those that oppose it [40].
Using Western blot analysis, we found that SLC7A11, GPX4, CD71, HIF-1α, Bcl-2, caspase3, caspase8, and PD-L1 protein exhibited downregulation as the donafenib concentration escalated. Conversely, upregulation of p53 and Bax protein was observed. This discovery preliminarily confirms that donafenib can promote ferroptosis and apoptosis in HCC cells.
Increased ROS can promote the acquisition of oncogenic phenotypes and limit tumor development by stimulating sensitivity to cell death. Unsuppressed ROS accumulation is harmful to cancer cells [41]. In this study, the accumulation of ROS in liver cancer cells increased as the donafenib concentration rose, further confirming that donafenib can promote ferroptosis in HCC cells and inhibit the occurrence and development of liver cancer cells.
To explore whether donafenib affects the emergence and progression of liver cancer within a living organism, we administered liver cancer cells into nude mice through subcutaneous injection. Once tumors were established, the treatment group was intraperitoneally injected with varying dosages of donafenib. The results showed that, as the concentration of donafenib increased, the tumor volume and weight gradually decreased. Tumor HE staining revealed that all malignancies exhibited a solid morphology. Notably, the tumors in the donafenib-treated cohort exhibited extensive necrosis, which progressively increased as the concentration of donafenib was escalated. Immunohistochemical staining showed that, with Ki-67, Bcl-2, caspase3, caspase8, SLC7A11, and GPX4 downregulated with increasing donafenib concentrations, and p53 and Bax upregulated with increasing concentrations. This confirms that donafenib can promote p53 expression, ferroptosis, and cell apoptosis in HCC cells.
Donafenib activates oxidative stress response in cells by increasing intracellular ROS, leading to DNA damage. P53 is an intracellular stress sensor that can respond to oxidative stress signals such as ROS [42]. Donafenib can trigger iron deposition by inducing the production of ROS. Upregulation of p53 can inhibit the expression of SLC7A11, reduce the intake of cysteine, and lead to a decrease in glutathione synthesis, thereby reducing cellular antioxidant capacity. GPX4 can reduce oxidized polyunsaturated fatty acids in the cell membrane, preventing ferroptosis, while upregulation of p53 can inhibit the expression of GPX4 [42]. The increase in ROS induced by donafenib can lead to cell damage, while the activation of p53 can promote iron deposition. The synergistic effect of the two may result in more effective cancer cell death. P53 mediated ferroptosis increases the sensitivity of liver cancer cells to chemotherapy drugs such as donafenib, as the decrease in cellular antioxidant capacity and accumulation of lipid peroxides make cancer cells more susceptible to further oxidative stress damage. Iron deposition can not only cause cancer cell death, but also inhibit tumor angiogenesis (HIF-1α) and reduce metastatic potential (Ki-67) to suppress tumor growth and spread [42].
In summary, Donafenib enhances the therapeutic effect against hepatocellular carcinoma by inducing an increase in ROS in liver cancer cells, triggering iron deposition, and activating p53, forming a synergistic mechanism. These interactions not only promote the death of cancer cells, but may also inhibit the further growth and spread of tumors, providing new ideas and potential therapeutic targets for the treatment of HCC.
Author contributions
Contributions: (I) Conception and design: C Han, S Mo; (II) Administrative support: C Han, S Mo; (III) Provision of study materials: J Liang, M Chen, P Hoa, S Wei, H Huang, Q Xie, X Luo; (IV) Collection and assembly of data: J Liang, M Chen, G Yan, P Hoa, S Wei, H Huang, Q Xie, X Luo, C Han, S Mo; (V) Data analysis and interpretation: J Liang, C Han; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.
Funding
Medical Excellence Award Funded by the Creative Research Development Grant from the First Affiliated Hospital of Guangxi Medical University (grant No.2021006), first-class discipline innovation-driven talent program of Guangxi Medical University, Guangxi Medical and Health Appropriate Technology Development and Application Project (No. S2021100, S2022065), the National Natural Science Foundation of China (No. 81802874, 82260548), the Natural Science Foundation of the Guangxi Province of China (Grant No.2024GXNSFAA010347) and Guangxi Key Research and Development Program (GKEAB18221019) and Guangxi Key Laboratory of Enhanced Recovery After Surgery for Gastrointestinal Cancer.
Data availability
No datasets were generated or analyzed during the current study.
Declarations
Conflict of interests
The authors declare no competing interests.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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