Comparative Proteomic Analysis of Drug Shikonin Addition to Liver

Comparative Proteomic Analysis of Drug Shikonin Addition to Liver | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparative Proteomic Analysis of Drug Shikonin Addition to Liver Ze-ning Wang, Cun-yu Li, Weimin Zheng, Yan Jiang, Ting Yu, Yang Liu, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8322459/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: HCC (Hepatocellular Carcinoma) accounts for 85–90% of primary liver cancers and ranks as the third deadliest malignancy worldwide. While targeted therapies have improved outcomes, advanced HCC remains challenging to treat. TCM (Traditional Chinese Medicine), particularly SK (Shikonin) from Lithospermum erythrorhizon , shows promise by targeting multiple cancer hallmarks like apoptosis resistance and angiogenesis. Methods: Using DIA (Data-Independent Acquisition) proteomics, we analyzed SK-treated HCC cell lines. GO (Gene Ontology) enrichment identified key pathways, while molecular docking validated protein interactions. Immunohistochemistry confirmed differential protein expression. Results: SK treatment significantly altered mitochondrial function-related proteins. Nine DEPs (Differentially Expressed Proteins) were consistently regulated across all cell lines, forming a network linked to TP53 and PRKN. Molecular docking supported these interactions, and immunohistochemistry verified DEP expression patterns. Conclusions: SK exerts anti-HCC effects by modulating mitochondrial proteins and key regulators like TP53/PRKN. These findings highlight SK's multi-target potential and support further investigation of TCM compounds for HCC combination therapies. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 INTRODUCTION Cancer ranks as the second leading cause of death worldwide, surpassed only by cardiovascular diseases¹. HCC (Hepatocellular carcinoma), accounting for 85–90% of primary liver cancers, is a major global health burden: it was among the top three cancer-related causes of death in 46 countries and top five in 90 countries in 2020¹. Projections estimate that liver cancer mortality will reach 1.3 million by 2040¹. Current therapeutic options for advanced HCC, including kinase inhibitors, yield limited clinical benefit². In East Asia and China, TCM (Traditional Chinese Medicine)—including herbal medicine and acupuncture—is frequently integrated with Western medicine to improve outcomes for cancer patients. TCM not only alleviates symptoms such as fatigue, chronic pain, anorexia-cachexia, and insomnia but also mitigates adverse effects of chemotherapy, radiotherapy, or targeted therapies. Notably, TCM demonstrates efficacy in mid-to-late-stage cancers (e.g., gastric, cervical, colorectal, and liver cancers)³. Its advantages include low toxicity, multi-target effects, and potential reversal of MDR (Multi-Drug Resistance)⁴. For example, TCM interventions have been validated in PLGC (Precancerous Lesions of Gastric Cancer)⁵ and CACC (Colitis-Associated Colorectal Cancer)⁶. Previous studies have identified bioactive components from TCM with anti-cancer properties. For instance, our group characterized the anti-tumor effects of trichosanthin, a ribosome-inactivating protein, revealing dysregulation of ribosome- and spliceosome-related proteins in cancer cells⁷. Here, we investigate the molecular mechanism of SK (Shikonin), a naphthoquinone compound isolated from Lithospermum erythrorhizon ( Figure 1 ). SK potently induces apoptosis and inhibits proliferation in three HCC cell lines (GQY-7701, Bel-7402, HepG2). Using DIA (Data-Independent Acquisition) proteomics, we identified nine core DEPs (Differentially Expressed Proteins) shared across cell lines. IPA (Ingenuity Pathway Analysis) and molecular docking experiments revealed a regulatory network centered on TP53 and PRKN, suggesting SK exerts dual effects on PRKN-mediated mitophagy (ubiquitin-proteasome system) and TP53-dependent cell cycle arrest⁸. These findings provide novel insights into SK’s multitargeted anti-cancer activity, positioning it as a promising candidate for HCC therapy. METHODS Comparative Proteomic Analysis of Drug Shikonin Addition to Liver Ze-ning Wang 1* , Cun-yu Li 2* , Weimin Zheng 3 , Yan Jiang 1 , Ting Yu 4 , Yang Liu 1 , Yang Zhang 1# , Hong Jin 1# Shanghai Stomatological Hospital & Institutes of Biomedical Sciences, Fudan University, Shanghai, China College of Life and Health Sciences, Northeastern University, Shenyang, China School of Pharmacy, Nanjing Medical University, Nanjing, 211166, China Polessky State University, Pinsk, Republic of Belarus * These authors contributed equally. # Correspondence to: Hong Jin: [email protected] Yang Zhang: [email protected] Email: Ze-ning Wang: [email protected] Cun-yu Li: [email protected] Weimin Zheng: [email protected] Yan Jiang: [email protected] Yang Liu: [email protected] Keywords: Shikonin; Proteome; Markers; IPA; Liver Cell Line ABSTRACT Background: HCC (Hepatocellular Carcinoma) accounts for 85–90% of primary liver cancers and ranks as the third deadliest malignancy worldwide. While targeted therapies have improved outcomes, advanced HCC remains challenging to treat. TCM (Traditional Chinese Medicine), particularly SK (Shikonin) from Lithospermum erythrorhizon , shows promise by targeting multiple cancer hallmarks like apoptosis resistance and angiogenesis. Methods: Using DIA (Data-Independent Acquisition) proteomics, we analyzed SK-treated HCC cell lines. GO (Gene Ontology) enrichment identified key pathways, while molecular docking validated protein interactions. Immunohistochemistry confirmed differential protein expression. Results: SK treatment significantly altered mitochondrial function-related proteins. Nine DEPs (Differentially Expressed Proteins) were consistently regulated across all cell lines, forming a network linked to TP53 and PRKN. Molecular docking supported these interactions, and immunohistochemistry verified DEP expression patterns. Conclusions: SK exerts anti-HCC effects by modulating mitochondrial proteins and key regulators like TP53/PRKN. These findings highlight SK's multi-target potential and support further investigation of TCM compounds for HCC combination therapies. INTRODUCTION Cancer ranks as the second leading cause of death worldwide, surpassed only by cardiovascular diseases¹. HCC (Hepatocellular carcinoma), accounting for 85–90% of primary liver cancers, is a major global health burden: it was among the top three cancer-related causes of death in 46 countries and top five in 90 countries in 2020¹. Projections estimate that liver cancer mortality will reach 1.3 million by 2040¹. Current therapeutic options for advanced HCC, including kinase inhibitors, yield limited clinical benefit². In East Asia and China, TCM (Traditional Chinese Medicine)—including herbal medicine and acupuncture—is frequently integrated with Western medicine to improve outcomes for cancer patients. TCM not only alleviates symptoms such as fatigue, chronic pain, anorexia-cachexia, and insomnia but also mitigates adverse effects of chemotherapy, radiotherapy, or targeted therapies. Notably, TCM demonstrates efficacy in mid-to-late-stage cancers (e.g., gastric, cervical, colorectal, and liver cancers)³. Its advantages include low toxicity, multi-target effects, and potential reversal of MDR (Multi-Drug Resistance)⁴. For example, TCM interventions have been validated in PLGC (Precancerous Lesions of Gastric Cancer)⁵ and CACC (Colitis-Associated Colorectal Cancer)⁶. Previous studies have identified bioactive components from TCM with anti-cancer properties. For instance, our group characterized the anti-tumor effects of trichosanthin, a ribosome-inactivating protein, revealing dysregulation of ribosome- and spliceosome-related proteins in cancer cells⁷. Here, we investigate the molecular mechanism of SK (Shikonin), a naphthoquinone compound isolated from Lithospermum erythrorhizon ( Figure 1 ). SK potently induces apoptosis and inhibits proliferation in three HCC cell lines (GQY-7701, Bel-7402, HepG2). Using DIA (Data-Independent Acquisition) proteomics, we identified nine core DEPs (Differentially Expressed Proteins) shared across cell lines. IPA (Ingenuity Pathway Analysis) and molecular docking experiments revealed a regulatory network centered on TP53 and PRKN, suggesting SK exerts dual effects on PRKN-mediated mitophagy (ubiquitin-proteasome system) and TP53-dependent cell cycle arrest⁸. These findings provide novel insights into SK’s multitargeted anti-cancer activity, positioning it as a promising candidate for HCC therapy. Figure 1. Workflow for proteomics investigation and validation of anti-cancer mechanism of SK. The study involved three cancer cell lines (QGY-7701, Bel-7402, and HepG2), each with three biological replicates and three technical replicates. Both in vitro and in vivo experiments demonstrated that different doses of SK exert varying degrees of inhibition on liver cancer cell lines. Specifically, the DIA (Data-Independent Acquisition) proteomics technology identified over 9,300 mouse proteins. DEPs (Differentially Expressed Proteins) were systematically screened using an integrated analytical approach combining volcano plot analysis, PLS-DA, and WGCNA. Notably, three DEPs showing differential expression across all three cell lines were validated via IHC (Immunohistochemistry). METHODS Drug Shikonin was purchased from Meilunbio ® . The molecular formula of shikonin is C₁₆H₁₆O₅, and its molecular weight is 288.30 ( Supplementary Figure 1 ). It met the quality standard of HPLC purity ≥ 98% as a reference standard. Cell Culture A 1% Penicillin-Streptomycin solution (Thermo Fisher Scientific, Cat. No. 15140148) was used. When cells reached 50% confluence, fresh medium containing the vehicle (dimethyl sulfoxide, DMSO) was added, and cells were incubated in a humidified atmosphere of either 95% air or 5% CO₂. All experiments were performed independently at least three times and in triplicate. Conditioned media and cells were collected and stored at -80°C until use. MTT assay HCC cells were seeded into 96-well plates at a density of 1×10⁴ cells per well. The cells were then treated with varying concentrations of SK (1 μM, 5 μM, 8 μM, 10 μM, 20 μM, and 50 μM). Each concentration group included four replicate wells. After 24 hours of incubation with SK, MTT solution (Beyotime, C0009) was added to each well, and the plates were further incubated in the dark for 4 hours. Subsequently, the formazan crystals formed were dissolved by adding DMSO and gently shaking the plates at low speed for approximately 10 minutes. The absorbance was measured at wavelengths of 570 nm and 690 nm using a SpectraMax M5 microplate reader (MD, USA). Cell morphology Cells were seeded in 6-well plates at a density of 5×10⁵ cells per well and cultured in Dulbecco's Modified Eagle Medium (DMEM, Gibco) supplemented with 10% fetal bovine serum (FBS, Gibco) and 1% penicillin/streptomycin. When the cells reached 70% confluence, they were treated with SK and incubated for 24 hours. Following the treatment, cell morphology was observed and images were captured using a microscope. The images were acquired and analyzed using Leica software (Leica Microsystems). Apoptosis Analysis HCC cells were seeded in 6-well plates at a density of 1×10⁶ cells per well and treated with or without SK for 24 hours. After treatment, the cells were collected and stained using an Annexin V-FITC/PI apoptosis detection kit (Yeasen, 40302) following the manufacturer's protocol. Briefly, the cells were washed twice with phosphate-buffered saline (PBS) and then stained with Annexin V-FITC and propidium iodide (PI) in the dark at room temperature for 15 minutes. Apoptosis was assessed using a flow cytometer (BD Biosciences, USA), and the data were analyzed using FlowJo software (version 10, USA). Tumor Model To evaluate the effect of SK on HCC growth in vivo, a xenograft tumor model was established in nude mice. The mice were randomly divided into four groups, with five distinctly marked mice in each group. HMGB1 stable knockdown cell lines (shHMGB1-1 and shHMGB1-2) and control cell lines (shNC1 and shNC2) were subcutaneously injected into the mice. Briefly, 5×10⁶ HCCLM3 cells suspended in 200 μL of PBS (Phosphate-Buffered Saline) were injected into the right flank of each mouse using a 1-mL syringe. After palpable tumors formed, tumor sizes were measured every 5 days. Tumor volume was calculated using the formula: Volume = (L×W²)/2, where L represents the length (longest diameter) and W represents the width (shortest perpendicular diameter) of the tumor, and the results were plotted in mm³. On day 35, the mice were euthanized, and tumor weights were recorded. The tumor growth curve was plotted based on the volume measurements. Additionally, the expression level of HMGB1 in the subcutaneous tumors was analyzed by Western blot. All animal experiments were performed in accordance with protocols approved by the IACUC (Institutional Animal Care and Use Committee) of Fudan University. Sample preparation and Protein extraction QGY-7701, Bel-7402, and Hep G2 cells (5×10⁶ cells each) were harvested, washed with PBS, and centrifuged at 1,000×g for 10 minutes. The supernatant was carefully removed, and the cell pellet was resuspended in lysis buffer containing 7 M urea, 2 M thiourea, 4% CHAPS, 100 mM DTT (Dithiothreitol), 0.5 mM PMSF (PhenylMethylSulfonyl Fluoride), and 1 mM protease inhibitor cocktail. The cells were disrupted by sonication on ice using an ultrasonic instrument, with each pulse lasting 5 seconds and a 10-second interval between pulses. This process was repeated five times. The lysate was then kept on ice for 40 minutes to ensure complete lysis. Cellular debris was removed by centrifugation at 15,000×g for 45 minutes at 4°C. The resulting protein samples were either used immediately or stored at -80°C for subsequent analysis. Protein concentration was determined using the modified Bradford method. Protein Digestion and Desalting Two hundred micrograms of protein dissolved in lysate were reduced with 10 mM DTT at 37°C for 1 hour, followed by alkylation with 20 mM iodoacetamide in the dark at room temperature for 30 minutes. Proteins were then precipitated by adding four volumes of ice-cold acetone and incubating overnight at -80°C. After centrifugation at 12,000×g for 15 minutes, the supernatant was removed, and the protein pellet was resuspended in 200 μL of 50 mM ammonium bicarbonate. Trypsin was added at a 1:50 (w/w) enzyme-to-protein ratio for overnight digestion at 37°C. The digestion was terminated by adding formic acid to a final concentration of 5%. The resulting peptide mixture was desalted using a Sepak desalting column (Waters, USA) and prepared for MS (Mass Spectrometry) analysis. LC (Liquid Chromatography) Separation For high-pH two-dimensional (2D) separation, 100 μg of protein extract was loaded onto a chromatographic column (BEH C18, 300 Å, 1.7 μm, 2.1 mm×150 mm; Waters, USA). The separation was performed using mobile phase A (water with 5 mM ammonium formate, pH 10.3) and mobile phase B (acetonitrile). The gradient was set to increase mobile phase B linearly from 5% to 45% over 20 minutes. The eluted fractions were concatenated into 20 fractions, which were further combined into 4 final fractions. These fractions were lyophilized and redissolved in an aqueous solution containing 1‰ formic acid for subsequent analysis. The second-dimensional separation was performed using a nanoElute LC system (Bruker Daltonics). A capillary column (250 mm×75 μm, Inopticks) was employed, with mobile phase A (water containing 1‰ formic acid) and mobile phase B (acetonitrile containing 1‰ formic acid). Peptide separation was carried out at a flow rate of 300 nL/min over a 90-minute gradient. The mobile phase B concentration was increased from 2% to 22% in the first 45 minutes, followed by a rapid increase to 37% within 5 minutes and then to 80% within another 5 minutes. The column was rinsed and equilibrated for the final 5 minutes. A total of 200 ng of peptide fragments was injected for LC-MS analysis. MS (Mass Spectrometry) Analysis All fractions were analyzed using a hybrid trapped ion mobility spectrometry (TIMS) coupled with a quadrupole time-of-flight mass spectrometer (TIMS-TOF Pro, Bruker Daltonics). The instrument was equipped with a nano-electrospray ion source, and data were acquired in a scanning range of 100-1,700 m/z with a mobility range of 0.7-1.3 Vs/cm². Each acquisition cycle lasted 1.16 seconds, consisting of 1 full MS scan and 10 parallel accumulation serial fragmentation (PASEF) MS/MS scans. The intensity threshold was set to 5,000, with an accumulation and release time of 100 ms. The ion source voltage was maintained at 1,500 V, with an auxiliary gas flow rate of 3 L/min and an ion source temperature of 180°C. Data analysis The raw MS data were processed using Peaks Online software (Bioinformatics Solutions, Inc.). A mouse protein database downloaded from SwissProt (17,046 proteins, version 2022-10) was used for protein identification. The mass tolerance was set to 15 ppm for MS 1 and 0.05 Da for MS 2 . Trypsin was specified as the digestion enzyme, allowing for up to one missed cleavage. Carbamidomethylation of cysteine residues was set as a fixed modification, while acetylation (protein N-terminus), oxidation (methionine), and deamidation (asparagine and glutamine) were set as variable modifications. The peak area of identified proteins was extracted and used for subsequent statistical analysis. Bioinformatics analysis Inter-group statistical analyses were performed using MATLAB. DEPs were screened using VIP (Variable Importance in Projection) scores from OPLS-DA (Orthogonal Partial Least Squares-Discriminant Analysis) and volcano plots. Hierarchical clustering and GO enrichment analysis were conducted using MATLAB (version R2020b). Biological networks were constructed using IPA (Ingenuity Pathway Analysis). Heatmaps were generated using the R package ComplexHeatmap (version 2.12.1). Transcriptomic data from The Cancer Genome Atlas (TCGA) were obtained from the GEPIA2 database (http://gepia2.cancer-pku.cn). Weighted gene co-expression network analysis (WGCNA) was performed using the R package WGCNA (version 1.72-1). Molecular Docking Receptor Preparation. The PDB file of the target protein was downloaded from the PDB (Protein Data Bank). Subsequently, PyMol software was utilized to eliminate redundant ions and water molecules from the protein structure. To facilitate subsequent docking simulations, AutoDockTools was employed to add hydrogen atoms and assign charges to the target protein. The processed protein was then saved in the PDBQT format, which is compatible with docking programs. Ligand Preparation. The structure of SK was drawn using ChemDraw. This structure was then imported into Chem3D and saved as a PDB file. In AutoDockTools, the conformation of SK was optimized and set according to the principles of molecular conformation. After the conformational adjustment, SK was saved in the PDBQT format, rendering it suitable for docking with the target protein. Docking Process. Within AutoDockTools, the PDBQT files of both the target protein and SK were opened. A docking box was precisely defined to specify the region of interest within the target protein where the binding interaction with SK was anticipated. Docking calculations were made by AutoDock Vina and viewed by PyMol. The affinity between the target protein and SK was evaluated based on the docking scores obtained from AutoDock Vina, providing insights into the strength of their binding interaction. RESULTS Toxicology and systemic safety assessment of SK To evaluate the potential toxicity and systemic safety of SK, mice were administered low, medium, and high concentrations of SK. The results demonstrated that SK had no significant impact on the growth or body weight of the mice (Figure 2A). Histopathological analysis of liver tissue paraffin sections using H&E (Hematoxylin and Eosin) staining revealed that the liver tissue structure and hepatocyte morphology in SK-treated mice were comparable to those in the control group. These findings suggest that SK does not exhibit significant hepatotoxicity in mice under the tested conditions. To further assess the systemic toxicity of SK, histopathological analysis was performed on kidney, heart, and liver tissues using H&E staining. As shown in Supplementary Figure 2, no significant toxic alterations, such as cell necrosis or structural damage, were observed in any of the tested tissues across the control and SK-treated groups. These results collectively indicate that SK does not exhibit apparent toxicity to the kidney, heart, or liver under the experimental conditions. Antitumor Efficacy of SK in a Subcutaneous Tumor Model SK exhibited a pronounced inhibitory effect on the growth of HCC subcutaneous tumors. Following the subcutaneous inoculation of liver cancer cells, tumor volume and weight were significantly reduced in mice treated with SK compared to the control group (Figure 2B-F). This inhibitory effect was dose-dependent, with the high-concentration SK group showing the most substantial reduction in tumor volume and weight. in vitro experiments of SK Cell Viability . The effect of SK on cell viability was assessed using the Cell Counting Kit-8 (CCK-8, Dojindo, CK04-3000T) in three hepatocellular carcinoma (HCC) cell lines: HepG2, Bel-7402, and QGY-7701. Cells were treated with increasing concentrations of SK (ranging from 0 to 50 μM). SK significantly inhibited the proliferation of all three cell lines in a dose-dependent manner (Figure 3A). However, the sensitivity to SK varied among the cell lines. HepG2 cells were the most sensitive, while QGY-7701 cells exhibited the highest tolerance. These results indicate that SK exerts a potent inhibitory effect on HCC cell proliferation, with the optimal inhibitory concentration varying depending on the cell type. Morphological Changes . SK treatment induced significant morphological alterations in HCC cell lines. Following exposure to SK, cells exhibited shrinkage, reduced cell size, rounding, and the appearance of cytoplasmic vacuoles (Figure 3B). These changes are consistent with cellular stress and apoptosis, suggesting that SK disrupts cellular homeostasis and induces cytotoxic effects. Apoptosis . The pro-apoptotic effect of SK was evaluated using flow cytometry with Annexin V-FITC and propidium iodide (PI) double staining (Beyotime, C1062L). Treatment with 10 μM SK significantly increased the proportion of early and late apoptotic cells in all three HCC cell lines compared to the control groups (Figure 3C-D). Notably, Bel-7402 cells exhibited the highest proportion of early apoptotic cells, while HepG2 and QGY-7701 cells showed higher proportions of late apoptotic and dead cells. These findings align with the cell viability results, further confirming that SK induces apoptosis in HCC cells. The differential sensitivity of the cell lines to SK underscores the importance of considering cell type-specific resistance when determining optimal dosages for future clinical applications. Proteome for three cancer cell lines DEPs Screening We performed proteomic DIA (Data Independent Acquisition) technology on three liver cancer cell lines (GQY-7701, Bel-7402, and HepG2). A total of 48 samples were included, with biological and technical replicates. Hierarchy Clustering and Boxplot were constructed for observing the reproducibility of the three liver cancer cell lines and biological and technical reproducibility ( Supplementary Figure 3&4 ). Samples treated with drugs were separated from the control group. QGY-7701 and Bel-7402 showed the best performance, with three technical replicates clustering together under each biological replicate, while HepG2 showed a slightly poorer performance, but still able to distinguish between the control and drug treatment groups. From the OPLS-DA (Orthogonal Partial Least Squares Discriminant Analysis) plot ( Figure 4A ), there was a clear difference between the control and drug treatment groups, indicating that the VIP (Variable Importance in Projection) index can be used to screen DEPs between groups of samples. 9178, 8701 and 9196 proteins were identified in the control group, and 9217, 9060 and 9227 proteins were identified in the drug treatment group (Supplementary2, Table 1). In the control group, the overlap of three biological repetitions of three cell lines was 81%, 82% and 87%, respectively. However, in the drug treatment group, the overlap of three biological repeats was 86%, 92% and 89% respectively (Figure 4B). This result shows that the scale of proteome and biological repetition are close to saturation. A total of 9359 proteins were identified in the three liver cancer cell lines, and 9171 proteins were the same, accounting for 97.99%, indicating that there were very few proteins specifically expressed in each cell line (Figure 4C). We combined OPLS-DA and volcano plot to screen DEPs. In the volcano plot, the cutoff of fold change between groups was set 2, and the p value of t-test is 0.01. In GQY-7701 cell line, 3260 proteins with the VIP index greater than 1 accounted for 35% (Supplementary Figure 5A), in which 547 proteins were up-regulated and 370 proteins were down-regulated in volcano plot (Supplementary Figure 5B). In Bel-7402 cell line, 3,843 (41%) proteins had VIP index greater than 1, in which 641 proteins were up-regulated and 229 proteins were down-regulated in volcano plot. In HepG2 cell line, 3430 (37%) proteins had VIP index greater than 1, in which 133 proteins were up-regulated and 104 proteins were down-regulated. There are 607 proteins that show significant differences in drug treatment group versus control group across three liver cancer cell lines, and only 9 of them were common differences (Figure 4DF). WGCNA（Weighted Gene Co-expression Network Analysis）is a commonly used bioinformatics analysis method for expression profile data, which can cluster and modularize gene expression profiles. WGCNA can group genes with similar expression patterns into the same module and calculate the similarity between modules and between modules and samples to reveal the interrelationships and regulatory networks between genes. WGCNA can obtain gene modules most related to phenotypes. The most related modules (including positive and negative correlations) were obtained for GQY-7701, Bel-7402, and HepG2 cell lines using WGCNA, which contained 1733, 2323, and 1180 proteins, respectively. The correlation coefficients between the first module and phenotypes were all greater than 0. Interestingly, all nine DEPs described above appeared in the first module of WGCNA (Figure 4E), with five proteins appearing in the first module of all cell lines. The enrichment of biological process of top module for each cell line was described in Supplementary Figure 6-8. Mitochondrial related proteins were significant enriched in the intersected list of top modules from each cell line and DEPs for three cell lines (Supplementary Figure 9). Functional Analysis To elucidate the functional impact of SK on HCC cell lines, we conducted GO enrichment analysis. The results revealed significant differences in protein distribution across various GO terms between the drug-treated and control groups. Subcellular Localization . In the subcellular localization category, the most pronounced differences were observed in the Nucleolus (GO:0005730) and Mitochondrial Inner Membrane (GO:0005743) ( Figure 5A ). The number of proteins localized to these compartments significantly increased in the drug-treated group. The nucleolus, a key organelle involved in ribosome biogenesis and RNA synthesis, plays a critical role in regulating cell cycle, DNA repair, and transcription. The mitochondrial inner membrane, essential for oxidative phosphorylation and energy production, is often dysfunctional in cancer cells. Dysregulation of this compartment, such as reduced membrane potential, defects in the respiratory chain, and reactive oxygen species (ROS) accumulation, can promote tumorigenesis and cancer progression. Biological Processes . In the biological process category, the most differentially regulated terms included Positive Regulation of Translation by RNA Polymerase II (GO:0045944), Neutrophil Degranulation (GO:0043312), Positive Regulation of Translation, DNA-templated (GO:0045893), and Positive Regulation of Cell Population Proliferation (GO:0008284) ( Figure 5B ). Neutrophil degranulation, a critical immune response, involves the release of pro-inflammatory factors such as IL-1β and TNF-α, which can exert anti-tumor effects at high levels of activation. The other three terms, related to gene transcription and translation, highlight the nucleus as a key target for anti-cancer therapies, including DNA-damaging and microtubule-targeting agents. Pathway Enrichment Analysis . We mapped the DEPs obtained from each cell line into the IPA pathway. The enrichment of DEPs is calculated by Fisher exact test in IPA ( Figure 5D ), while z-score predicts the likelihood of pathway activation or inhibition based on the number and fold change of DEPs in the location of pathway. That is, target pathway is predicted to be activated when z-score greater than 0, while predicted to be inhibited when z-score less than 0 ( Figure 5C ). The results showed that OXPHOS (Oxidative Phosphorylation) and NER Pathway (Nucleotide Excision Repair Pathway) were enriched and predicted to be activated, while the Sirtuin pathway was inhibited 9 . OXPHOS are often inhibited in tumor cells (Warburg effect). However, both activation and inhibition of OXPHOS may have anti-cancer effects, and the research on this aspect has not been clear. Sirtuin is a class of NAD-dependent deacetylase. Sirtuin pathway can inhibit the expression of P16 and the activity of AMPK, thus promoting the growth and metastasis of cancer. In the drug treatment group, Sirtuin pathway was inhibited, reflecting the anti-cancer pathway of SK. NER Pathway is mainly responsible for repairing DNA damage. In the drug treatment group, NER Pathway was activated and enriched, which slowed down the deterioration of tumor. GO categories and KEGG pathways related to cell death and oxidative phosphorylation were significantly enriched in the proteomic analysis ( Figure 5E-F & Supplementary Figure 10 ). Notably, apoptosis-related terms were predominantly enriched in the Bel-7402 cell line, suggesting that SK exerts a pronounced pro-apoptotic effect in this cell type. GO terms screening . To identify key GO terms associated with SK treatment, we compared the overall protein expression levels between the control and drug-treated groups across 9,375 GO terms. Differential expression (t-test, p < 0.01) was observed in 104 terms for QGY-7701, 328 terms for Bel-7402, and 28 terms for HepG2 ( Figure 6A ). Among these, four mitochondrial-related GO terms: Mitochondrial Electron Transport (GO:0006120), Mitochondrial Respiratory Chain Complex I Assembly (GO:0032981), Mitochondrial Translational Elongation (GO:0070125), and Mitochondrial Translational Termination (GO:0070126) showed significant differences between the treatment and control groups in two cell lines ( Figure 6B-E ). Notably, proteins associated with these terms were upregulated in the SK-treated groups. Mitochondria play a central role in ATP production, and their function is frequently suppressed in tumor cells. Restoring mitochondrial function has been linked to anti-cancer effects, as demonstrated by studies showing that certain drugs and natural products can inhibit tumor growth and metastasis by enhancing mitochondrial activity. In this study, SK significantly enhanced mitochondrial electron transport, respiratory chain function, and translation processes, suggesting its potential to restore mitochondrial homeostasis and exert anti-tumor effects. Furthermore, analysis using the MitoCarta database revealed significant upregulation of mitochondrial-related DEPs in the Bel-7402 cell line following SK treatment compared to the control group (Supplementary Figure 11). This upregulation was observed across all mitochondrial functional categories, further supporting the role of SK in enhancing mitochondrial function and its potential as a therapeutic agent for hepatocellular carcinoma. Nine DEPs and validation The nine DEPs identified across all three HCC cell lines were categorized into three clusters based on their expression patterns (Figure 7A). In the first two clusters, which include S2512, YIF1A, TR112, GP180, CENPV, and NDUS7, all proteins were upregulated in the SK-treated groups. In contrast, the three proteins in the third cluster (UB2V1, ACTS, and MIA40) were downregulated. NDUS7, TR112, and MIA40 are enzymes; S2512, MIA40, and NDUS7 are localized to the mitochondria; CENPV, TR112, and UB2V1 are nuclear proteins; and GP180 and YIF1A are membrane-associated proteins. Across all cell lines, the nine DEPs exhibited significant differences in protein expression between the SK-treated and control groups (Figure 7B). To validate these findings, we selected three DEPs (512, ACTS, and UB2V1) for immunohistochemical analysis. The immunohistochemical results confirmed the proteomic data, showing complete consistency in protein expression patterns ( Figure 7D ). Specifically, the IOD (Integral Optical Density) values of ACTS and UB2V1 significantly decreased with increasing SK concentration, while the IOD value of S2512 increased significantly ( Figure 7E ). To further investigate the relevance of these DEPs in other cancer types, we analyzed their transcriptomic expression profiles across 31 tumors using the GEPIA2 database. The data revealed that ACTS was downregulated in all tumor types, while the other eight DEPs were upregulated. The upregulation of these DEPs was most prominent in Diffuse Large B-cell Lymphoma (DLBC), Pancreatic Adenocarcinoma (PAAD), and Thymoma (THYM) ( Figure 7C ). Additionally, data from the Human Protein Atlas (HPA) indicated that, except for CENPV and ACTS, the remaining seven DEPs were associated with cancer prognosis ( Supplementary2, Table 2 ). Network analysis and molecular docking Using IPA network analysis, we constructed a network of these 9 DEPs and found that the differential expression of these DEPs was directly or indirectly related to TP53 and PRKN ( Figure 8A ). The systematic docking screening against all network hubs (degree ≥3) revealed selective binding of SK to PRKN and TP53 proteins, with binding affinities significantly stronger than other nodal molecules (-ΔG >6 kcal/mol). This target specificity aligns with their topological dominance in the IPA network, where both molecules exhibited as highest betweenness centrality and degree of connectivity. By the way, the observed dual targeting suggests SK may exert therapeutic effects through coordinated modulation of PRKN-mediated mitophagy (Ubiquitin-proteasome system) coupled with TP53-dependent cell cycle arrest (Genomic stability control). DISCUSSION In vivo and in vitro experiments demonstrated that SK affected the size, volume, weight, metastasis, and apoptosis of liver tumors, with the effect intensifying as the dosage increased. We employed the proteomics DIA method to profile the proteomes of three liver cancer cell lines. Enrichment analysis revealed significant alterations in Neutrophil Degranulation, Mitochondrial Inner Membrane, Oxidative Phosphorylation, NER Pathway, and Sirtuin Signaling Pathway post - drug treatment. A total of 9 DEPs were identified across all three cell lines, with subcellular localizations as follows: SLC25A12 (S2512), CHCHD4 (MIA40), and NDUFS7 (NDUS7) in the mitochondria; CENPV (CENPV), TRMT112 (TR112), and UBE2V1 (UB2V1) in the nucleus; GPR180 (GP180) and YIF1A (YIF1A) on the membrane; and ACTA1 (ACTS) on the cytoskeleton. IPA regulatory network construction indicated that these 9 DEPs were directly or indirectly related to TP53 and PRKN. Mitochondrial DEPs SLC25A12 is mitochondrial membrane transporter mediating aspartate-glutamate exchange. Low SLC25A12 expression correlates with poor prognosis in multiple cancers, and its knockdown promotes lung metastasis and reduces survival in mice¹⁰. CHCHD4 is critical for mitochondrial respiratory chain assembly. Overexpression in tumors correlates with enhanced OXPHOS, EMT phenotypes, and poor patient outcomes via mTORC1 activation¹¹. NDUFS7 is a subunit of complex I in OXPHOS. Downregulated in clear cell renal carcinoma and modulated by natural compounds to inhibit oncogenesis¹². Nuclear DEPs CENPV is a centromere-associated protein. In oral squamous cell carcinoma, DNA methylation of CENPV is part of a prognostic signature¹⁴. TRMT112 is a methyltransferase cofactor enhancing WBSCR22 stability. Co-overexpression with WBSCR22 suppresses pancreatic cancer progression¹⁵. UBE2V1 is an E2 ubiquitin ligase promoting colorectal cancer metastasis via SIRT1 degradation and autophagy inhibition¹⁶. Membrane DEPs GPR180 is a GPCR linked to vascular smooth muscle proliferation. Hypermethylation of GPR180 predicts poor HCC prognosis¹⁷. YIF1A is involved in ER-Golgi trafficking. Its homolog YIPF2 enhances apoptosis in non-small cell lung cancer via TNFRSF10B recycling¹⁸. Cytoskeletal DEP ACTA1 is an actin isoform regulating cell motility. Overexpression correlates with early tongue cancer metastasis and EMT progression¹⁹. CONCLUSION SK, a naphthoquinone compound derived from traditional Chinese medicine, exhibits significant potential for cancer prevention and treatment. Toxicological studies demonstrated that SK has moderate hepatotoxicity in mice. Notably, as the concentration of SK increased, a dose-dependent inhibition of tumor volume and weight was observed in mice, highlighting its potent anti-tumor efficacy in vivo. In vitro experiments further revealed that SK reduces cell viability, inhibits migration, and promotes apoptosis in three HCC cell lines: QGY-7701, Bel-7402, and HepG2. In this study, the optimal dose of SK for the three HCC cell lines was determined using the MTT assay. Subsequently, DIA proteomic technology was employed to investigate the molecular mechanisms underlying SK's anti-cancer effects. Proteomic analysis was performed on both control and SK-treated groups for each cell line, with repeated sampling to ensure robustness. DEPs were identified through OPLS-DA, volcano plots, and WGCNA. A high proportion of cell line-specific DEPs were observed, indicating that even within the same organ, different cell types may adopt distinct anti-cancer pathways in response to SK. Among the DEPs, nine were consistently differentially expressed across all three cell lines. Three of these were further validated using immunohistochemistry. Importantly, the regulatory network constructed from these nine DEPs revealed that their differential expression is directly or indirectly linked to TP53 and PRKN, a finding further supported by molecular docking studies. This dual targeting suggests that SK may exert its therapeutic effects through the coordinated modulation of PRKN-mediated mitophagy (involving the ubiquitin-proteasome system) and TP53-dependent cell cycle arrest (critical for genomic stability control). These mechanisms collectively highlight SK's potential to disrupt cancer cell survival and proliferation through synergistic pathways. ABBREVIATION Abbreviation Full Name CACC Colitis-Associated Colorectal Cancer DEPs Differential Expressed Proteins DIA Data Independent Acquisition EMT Epithelial-Mesenchymal Transition HCC Hepatocellular Carcinoma IL InterLeukin MDR MultiDrug Resistance NER Pathway Nucleotide Excision Repair Pathway NP Nucleolar Protein OPLS-DA Orthogonal Partial Least Squares Discriminant Analysis OXPHOS Mitochondrial Oxidative Phosphorylation PLGC Precancerous Lesions of Gastric Cancer SIRT1 NAD-dependent protein deacetylase sirtuin-1 TCM Traditional Chinese Medic TNF Tumor Necrosis Factor TNFRSF10B Tumor Necrosis Factor Receptor SuperFamily Member 10B VIP Variable Importance in Projection WGCNA Weighted Gene Co-expression Network Analysis YIP1 YPT1-interacting protein Declarations ACKNOWLEDGEMENT We are so grateful to the selfless help from the Shanghai Huisen Science & Technology Company for biological validation. FUNDING This research was supported by the National Nature Science Foundation of China (32070605 & 32371334). CONSENT FOR PUBLICATION Not applicable. Ethical Approval All animal experiments were conducted under the protocols approved by the institutional animal care and use committee at Fudan university. DATA AVAILABILITY The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the iProX partner repository with the identifier IPX0003967001. COMPETING INTERESTS The authors declare that they have no competing interests. AUTHOR CONTRIBUTIONS Conception and design: Hong Jin Administrative support: Hong Jin Collection and assembly of data: Yang Zhang and Zening Wang Data analysis and interpretation: Yang Zhang and Zening Wang Manuscript writing: All authors； Final approval of manuscript: All authors. References Rumgay, H. et al. Global burden of primary liver cancer in 2020 and predictions to 2040. J Hepatol 77 , 1598-1606, doi:10.1016/j.jhep.2022.08.021 (2022). Crunkhorn, S. Kinase inhibitor combination combats liver cancer. Nat Rev Drug Discov 20 , 668, doi:10.1038/d41573-021-00132-5 (2021). Zhang, X., Qiu, H., Li, C., Cai, P. & Qi, F. The positive role of traditional Chinese medicine as an adjunctive therapy for cancer. Biosci Trends 15 , 283-298, doi:10.5582/bst.2021.01318 (2021). Wei, J. et al. Traditional Chinese medicine reverses cancer multidrug resistance and its mechanism. Clin Transl Oncol 24 , 471-482, doi:10.1007/s12094-021-02716-4 (2022). Xu, W., Li, B., Xu, M., Yang, T. & Hao, X. Traditional Chinese medicine for precancerous lesions of gastric cancer: A review. Biomed Pharmacother 146 , 112542, doi:10.1016/j.biopha.2021.112542 (2022). Wei, X. et al. Advances in research on the effectiveness and mechanism of Traditional Chinese Medicine formulas for colitis-associated colorectal cancer. Front Pharmacol 14 , 1120672, doi:10.3389/fphar.2023.1120672 (2023). Bradford, M. M. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72 , 248-254, doi:10.1006/abio.1976.9999 (1976). Charles Jacob, H. K. et al. Modulation of Early Neutrophil Granulation: The Circulating Tumor Cell-Extravesicular Connection in Pancreatic Ductal Adenocarcinoma. Cancers (Basel) 13 , doi:10.3390/cancers13112727 (2021). Busatto, F. F., Viero, V. P., Schaefer, B. T. & Saffi, J. Cell growth analysis and nucleotide excision repair modulation in breast cancer cells submitted to a protocol using doxorubicin and paclitaxel. Life Sci 268 , 118990, doi:10.1016/j.lfs.2020.118990 (2021). Alkan, H. F. et al. Deficiency of malate-aspartate shuttle component SLC25A12 induces pulmonary metastasis. Cancer Metab 8 , 26, doi:10.1186/s40170-020-00232-7 (2020). Thomas, L. W. et al. CHCHD4 regulates tumour proliferation and EMT-related phenotypes, through respiratory chain-mediated metabolism. Cancer Metab 7 , 7, doi:10.1186/s40170-019-0200-4 (2019). Stein, J., Tenbrock, J., Kristiansen, G., Muller, S. C. & Ellinger, J. Systematic expression analysis of the mitochondrial respiratory chain protein subunits identifies COX5B as a prognostic marker in clear cell renal cell carcinoma. Int J Urol 26 , 910-916, doi:10.1111/iju.14040 (2019). Branco, C. S. et al. Modulation of Mitochondrial and Epigenetic Targets by Polyphenols-rich Extract from Araucaria angustifolia in Larynx Carcinoma. Anticancer Agents Med Chem 19 , 130-139, doi:10.2174/1871520618666180816142821 (2019). Zhu, Q., Tian, G. & Gao, J. Construction of prognostic risk prediction model of oral squamous cell carcinoma based on co-methylated genes. Int J Mol Med 44 , 787-796, doi:10.3892/ijmm.2019.4243 (2019). Khan, A. A. et al. WBSCR22 and TRMT112 synergistically suppress cell proliferation, invasion and tumorigenesis in pancreatic cancer via transcriptional regulation of ISG15. Int J Oncol 60 , doi:10.3892/ijo.2022.5314 (2022). Shen, T. et al. Ube2v1-mediated ubiquitination and degradation of Sirt1 promotes metastasis of colorectal cancer by epigenetically suppressing autophagy. J Hematol Oncol 11 , 95, doi:10.1186/s13045-018-0638-9 (2018). Honda, S. et al. Clinical prognostic value of DNA methylation in hepatoblastoma: Four novel tumor suppressor candidates. Cancer Sci 107 , 812-819, doi:10.1111/cas.12928 (2016). Wang, Y. et al. YIPF2 promotes chemotherapeutic agent-mediated apoptosis via enhancing TNFRSF10B recycling to plasma membrane in non-small cell lung cancer cells. Cell Death Dis 11 , 242, doi:10.1038/s41419-020-2436-x (2020). Lee, D. Y. et al. Actin-Associated Gene Expression is Associated with Early Regional Metastasis of Tongue Cancer. Laryngoscope 131 , 813-819, doi:10.1002/lary.29025 (2021). Additional Declarations No competing interests reported. Supplementary Files Supplementary.docx Supplementary 1. (Word) All supplementary figures. ST.xlsx Supplementary 2. (Excel) l Proteome: All Identified proteins in three liver cancer cells. l 9 DEPs: Nine DEPs across all three cancer cells. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8322459","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":559782416,"identity":"03b22a4d-8e86-4dd0-8f0e-be03d8bd4798","order_by":0,"name":"Ze-ning Wang","email":"","orcid":"","institution":"Shanghai Stomatological Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ze-ning","middleName":"","lastName":"Wang","suffix":""},{"id":559782417,"identity":"a120c129-cabb-46d4-be29-f2e10b273b55","order_by":1,"name":"Cun-yu Li","email":"","orcid":"","institution":"Northeastern University","correspondingAuthor":false,"prefix":"","firstName":"Cun-yu","middleName":"","lastName":"Li","suffix":""},{"id":559782418,"identity":"e28f5a77-139b-4568-9859-bd4ca8048aa1","order_by":2,"name":"Weimin Zheng","email":"","orcid":"","institution":"Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Weimin","middleName":"","lastName":"Zheng","suffix":""},{"id":559782419,"identity":"a9de0ab5-c6bb-4252-8136-80c8afb39e45","order_by":3,"name":"Yan Jiang","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Jiang","suffix":""},{"id":559782420,"identity":"fb7680ff-5d83-43e4-a056-a49f29d7e4e4","order_by":4,"name":"Ting Yu","email":"","orcid":"","institution":"Polessky State University","correspondingAuthor":false,"prefix":"","firstName":"Ting","middleName":"","lastName":"Yu","suffix":""},{"id":559782421,"identity":"fb101be0-938c-4e6f-88c8-1c2218830468","order_by":5,"name":"Yang Liu","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Liu","suffix":""},{"id":559782422,"identity":"efe25c0d-4664-491e-9a13-41b13142eba2","order_by":6,"name":"Yang Zhang","email":"","orcid":"","institution":"Shanghai Stomatological Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Zhang","suffix":""},{"id":559782423,"identity":"d635c43f-51bf-484f-bd70-cb59d03fc05e","order_by":7,"name":"Hong Jin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYBACxmYGNhAtx97AYAAWaCBWizHPAWK1AAFYS2IP0VqY23mPPfi4oza9RyJ54+cCBhvZDQeYnz3A7zC+dMOZZ47n9kikFUvPYEgz3nCAzdwAvxYeM2netmO5+yVyDKR5GA4nbjjAwyZBjJZ0Hokc4988DP+J1lKTANRiBrTlAHFaJGe2HTDs4XlWZs1jkGw88zCbGV4thv1nzCQ+ttXJ87Anb77NU2En23e8+Rl+LQ1g6jCUCwoqZnzqgUAeQtURUDYKRsEoGAUjGgAAElZCRgNtpBsAAAAASUVORK5CYII=","orcid":"","institution":"Shanghai Stomatological Hospital","correspondingAuthor":true,"prefix":"","firstName":"Hong","middleName":"","lastName":"Jin","suffix":""}],"badges":[],"createdAt":"2025-12-10 03:08:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8322459/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8322459/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98276554,"identity":"75fa50a5-1b41-4d36-97a1-9d1c74d3c630","added_by":"auto","created_at":"2025-12-16 03:50:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1971374,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWorkflow for proteomics investigation and validation of anti-cancer mechanism of SK. \u003c/strong\u003eThe study involved three cancer cell lines (QGY-7701, Bel-7402, and HepG2), each with three biological replicates and three technical replicates. Both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e experiments demonstrated that different doses of SK exert varying degrees of inhibition on liver cancer cell lines. Specifically, the DIA (Data-Independent Acquisition) proteomics technology identified over 9,300 mouse proteins. DEPs (Differentially Expressed Proteins) were systematically screened using an integrated analytical approach combining volcano plot analysis, PLS-DA, and WGCNA. Notably, three DEPs showing differential expression across all three cell lines were validated via IHC (Immunohistochemistry).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-8322459/v1/7c01504f361020f8f8f8f885.png"},{"id":98276558,"identity":"1a443259-c2c1-4222-8b7e-3ae28bcb74b1","added_by":"auto","created_at":"2025-12-16 03:50:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":11105318,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIn vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e studies of the effects of SK in mice. \u003c/strong\u003eMouse tumorigenicity assay and pharmacological reactions to SK. \u003cstrong\u003eA)\u003c/strong\u003e H\u0026amp;E staining of liver tissues from mice treated with control, low, middle, and high SK concentrations, visualized under a microscope (scale bar: 50 μm) \u003cstrong\u003eB) \u003c/strong\u003eTemporal changes in mouse body weight (measured on Day 1, 4, 7, 10, and 14) across control, low, middle, and high SK treatment groups, with statistical annotations indicating significant differences. \u003cstrong\u003eC)\u003c/strong\u003e Photographs of mice in control, low-SK, and high-SK groups, providing a visual overview of their physical states. \u003cstrong\u003eD)\u003c/strong\u003e Tumor volume growth curves (from Day 8 to Day 22) after subcutaneous liver cancer cell inoculation. The high-SK group exhibited a significantly smaller tumor volume (p\u0026lt;0.05). \u003cstrong\u003eE)\u003c/strong\u003e Excised tumor images from control, low-SK, and high-SK groups on Day 22, highlighting size variations among groups.\u003cstrong\u003e F) \u003c/strong\u003eTumor weight measurements on Day 22. The high-SK group showed a notable reduction in tumor weight compared to the control group (p\u0026lt;0.05), demonstrating SK’s tumor-inhibiting efficacy.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8322459/v1/8c3701f7c47ae39c080fdd46.png"},{"id":98276556,"identity":"fbc513f4-946d-4ec4-ba95-e293b19c9dec","added_by":"auto","created_at":"2025-12-16 03:50:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":4094502,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIn vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e studies of the effects of SK in hepatocellular carcinoma cell lines.\u003c/strong\u003e \u003cstrong\u003eA) \u003c/strong\u003eCell viability assay of three hepatocellular carcinoma cell lines treated with varying concentrations of SK. SK significantly inhibited hepatocellular carcinoma cell proliferation in a concentration-dependent manner. Notably, the inhibitory effect strengthened with increasing SK concentrations. Based on these results, 10 μM SK was selected for subsequent experiments.\u003cstrong\u003e B)\u003c/strong\u003e Morphological changes in hepatocellular carcinoma cell lines upon SK treatment. Images (at 5× and 20× magnifications) illustrate distinct morphological differences between control (C1-C3) and SK-treated groups (T1-T3). \u003cstrong\u003eC)\u003c/strong\u003e Flow cytometry analysis of the three hepatocellular carcinoma cell lines after SK treatment. The percentage of apoptotic cells (located in the I and IV quadrants) was notably higher in the SK-treated groups compared to the control groups, further confirming that SK markedly suppressed hepatocellular carcinoma cell proliferation. \u003cstrong\u003eD) \u003c/strong\u003eBar charts quantifying the percentages of live cells (black bars) and apoptotic cells (gray bars) in control and 10 μM SK-treated groups. Statistical symbols (*, **, *** vs. control; #, ##, ### for specific comparisons) highlight significant differences: 10 μM SK reduces live cell percentages and increases apoptosis rates in the cell lines, further validating SK’s pro-apoptotic and anti-proliferative effects.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-8322459/v1/d3f7790552d8b9fcbad3341f.png"},{"id":98276560,"identity":"db58c66b-de8f-40be-83d1-b04b6f91d96d","added_by":"auto","created_at":"2025-12-16 03:50:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4178063,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGlobal view for proteome of three hepatocellular carcinoma cell lines treated with SK. A)\u003c/strong\u003e OPLS-DA of the three liver cancer cell line. Biological replicates within the control and treatment groups clustered respectively, demonstrating robust proteomic reproducibility for screening reliable DEPs. \u003cstrong\u003eB) \u003c/strong\u003eVenn diagrams comparing the number of identified proteins across biological and technical replicates in each cell line. All three replicates showed over 90% coverage overlap, reflecting consistent protein identification outcomes. \u003cstrong\u003eC)\u003c/strong\u003e Venn comparisons of identified proteins in each cell line. \u003cstrong\u003eD)\u003c/strong\u003e Venn comparisons of DEPs in each cell line. Notably, 9 DEPs were differentially expressed across all three cell lines.\u003cstrong\u003e E) \u003c/strong\u003eComparison of the number of top positive and negative modules identified by WGCNA in each cell line with 9 DEPs. \u003cstrong\u003eF) \u003c/strong\u003eRelationship network of DEPs in each cell line. The red dots at the center denote the 9 DEPs shared among the three cell lines.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-8322459/v1/2a88f3f74bb4f0b5154bbb82.png"},{"id":98276553,"identity":"9e333c57-ba21-42e3-b7c9-72cfcd611e10","added_by":"auto","created_at":"2025-12-16 03:50:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2009281,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEnrichment analysis for proteomics data of three hepatocellular carcinoma cell lines. A)\u003c/strong\u003e Comparison of protein numbers under subcellular location among the three cell lines. All displayed GO terms had the p-value less than 0.05, showcasing significant subcellular distribution patterns of proteins. \u003cstrong\u003eB)\u003c/strong\u003e Comparison of protein numbers under biological process among the three cell lines, identifying key biological processes associated with DEPs. \u003cstrong\u003eC)\u003c/strong\u003e Pathway activation/inhibition predictions for DEPs in three cell lines using z-scores via IPA (Ingenuity Pathway Analysis), visualizing functional pathway activity trends. \u003cstrong\u003eD)\u003c/strong\u003e IPA pathway enrichment analysis of DEPs in the three cell lines using the Fisher Exact Test. \u003cstrong\u003eE)\u003c/strong\u003e Enrichment of cell death-related GO categories in the three cell lines, with “*” annotations highlighting notable significance. \u003cstrong\u003eF) \u003c/strong\u003eKEGG pathway enrichment analysis integrating cell death-related GO categories and oxidative phosphorylation across the three cell lines.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-8322459/v1/b82bec403a4e0e14e53c8b82.png"},{"id":98435939,"identity":"22eae9cf-9a22-4015-9d4f-7fcbf389ac28","added_by":"auto","created_at":"2025-12-17 16:54:40","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1166950,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe protein expression of mitochondrial proteins based on the proteomics data of three hepatocellular carcinoma cell lines.\u003c/strong\u003e \u003cstrong\u003eA) \u003c/strong\u003eStatistical differences in protein quantification for each GO term across groups. The red line serves as the cutoff (indicating a t-test p-value \u0026lt; 0.01). Specifically, the numbers of GO terms surpassing this cutoff in the GQY-7701, Bel-7402, and HepG2 cell lines are 104, 328, and 28, respectively. \u003cstrong\u003eB-E)\u003c/strong\u003e Highlight four mitochondria-related GO terms that displayed differences in both the GQY-7701 and Bel-7402 cell lines.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-8322459/v1/370096dd3f065a775dafb890.png"},{"id":98276559,"identity":"439556e4-f231-48c2-839a-533db488ff44","added_by":"auto","created_at":"2025-12-16 03:50:50","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":4028971,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression analysis and validation of the nine DEPs commonly identified across three hepatocellular carcinoma cell lines, with immunohistochemical validation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e Heatmap depicting the expression patterns of the nine DEPs. These DEPs are clustered into three groups according to expression levels. Notably, DEPs in the third cluster show downregulation in the drug treatment group. \u003cstrong\u003eB) \u003c/strong\u003eProtein quantification of the nine DEPs in the three cell lines, presenting statistical differences (marked with corresponding statistical symbols). \u003cstrong\u003eC)\u003c/strong\u003e Multi-dimensional profiling of the nine DEPs across various tumor types, including mRNA expression in TCGA, protein expression status, subcellular localization (mitochondrion, nucleus, membrane, cytoskeleton), and their roles as prognostic markers in liver hepatocellular carcinoma. \u003cstrong\u003eD)\u003c/strong\u003e Immunohistochemical images (20 μm scale) showing the expression of ACTA1, SLC25A12, and UBE2V1 in control, low, and high treatment groups. \u003cstrong\u003eE)\u003c/strong\u003e T-test statistical results for ACTA1, SLC25A12, and UBE2V1 across control, low, and high groups. Significant differences are indicated (p\u0026lt;0.05, **p\u0026lt;0.001), validating the differential expression patterns of these proteins.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-8322459/v1/704686938ef4e9bfe7a03eb7.png"},{"id":98435207,"identity":"4140962d-69de-4f20-8ccc-6dd57f448c75","added_by":"auto","created_at":"2025-12-17 16:53:18","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":2290454,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTCGA and IPA network analysis of the nine DEPs commonly identified among the three hepatocellular carcinoma cell lines.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e IPA network analysis of the 9 DEPs. Yellow and blue lines represent deduced pathways obtained from IPA's MAP (Molecule Activity Predictor) functions. Red font marked on the nodes represents proteins associated with TP53. The 9 DEPs have a direct or indirect relationship with TP53. \u003cstrong\u003eB) \u003c/strong\u003eMolecular docking interaction between the PRKN and SK. \u003cstrong\u003eC) \u003c/strong\u003eMolecular docking interaction between TP53 and SK.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-8322459/v1/1c9c8d4354bbe63d795d864e.png"},{"id":98622592,"identity":"b4fe6608-0b95-4861-8374-9bb1fb4c7bb2","added_by":"auto","created_at":"2025-12-19 16:58:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":33510161,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8322459/v1/b8bb0414-da44-4e9d-a141-2ae412df82ac.pdf"},{"id":98276562,"identity":"116d3ef2-6a10-48a1-80ed-915cb34c73ef","added_by":"auto","created_at":"2025-12-16 03:50:51","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16970326,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e1)\u003c/strong\u003e \u003cstrong\u003eSupplementary 1. \u003c/strong\u003e(Word)\u003c/p\u003e\n\u003cp\u003eAll supplementary figures.\u003c/p\u003e","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-8322459/v1/b349678f7b1d40c5eda4e057.docx"},{"id":98276561,"identity":"445c738d-c4bd-4956-9f1f-3c85da712823","added_by":"auto","created_at":"2025-12-16 03:50:50","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":4596173,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e1)\u003c/strong\u003e \u003cstrong\u003eSupplementary 2. \u003c/strong\u003e(Excel)\u003c/p\u003e\n\u003cp\u003el Proteome: All Identified proteins in three liver cancer cells.\u003c/p\u003e\n\u003cp\u003el 9 DEPs: Nine DEPs across all three cancer cells.\u003c/p\u003e","description":"","filename":"ST.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8322459/v1/e2e2ab426aecfd7c72f77412.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Proteomic Analysis of Drug Shikonin Addition to Liver","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCancer ranks as the second leading cause of death worldwide, surpassed only by cardiovascular diseases¹. HCC (Hepatocellular carcinoma), accounting for 85–90% of primary liver cancers, is a major global health burden: it was among the top three cancer-related causes of death in 46 countries and top five in 90 countries in 2020¹. Projections estimate that liver cancer mortality will reach 1.3 million by 2040¹. Current therapeutic options for advanced HCC, including kinase inhibitors, yield limited clinical benefit².\u003c/p\u003e\n\u003cp\u003eIn East Asia and China, TCM (Traditional Chinese Medicine)—including herbal medicine and acupuncture—is frequently integrated with Western medicine to improve outcomes for cancer patients. TCM not only alleviates symptoms such as fatigue, chronic pain, anorexia-cachexia, and insomnia but also mitigates adverse effects of chemotherapy, radiotherapy, or targeted therapies. Notably, TCM demonstrates efficacy in mid-to-late-stage cancers (e.g., gastric, cervical, colorectal, and liver cancers)³. Its advantages include low toxicity, multi-target effects, and potential reversal of MDR (Multi-Drug Resistance)⁴. For example, TCM interventions have been validated in PLGC (Precancerous Lesions of Gastric Cancer)⁵ and CACC \u0026nbsp;(Colitis-Associated Colorectal Cancer)⁶.\u003c/p\u003e\n\u003cp\u003ePrevious studies have identified bioactive components from TCM with anti-cancer properties. For instance, our group characterized the anti-tumor effects of trichosanthin, a ribosome-inactivating protein, revealing dysregulation of ribosome- and spliceosome-related proteins in cancer cells⁷.\u003c/p\u003e\n\u003cp\u003eHere, we investigate the molecular mechanism of SK (Shikonin), a naphthoquinone compound isolated from \u003cem\u003eLithospermum erythrorhizon\u003c/em\u003e (\u003cstrong\u003eFigure 1\u003c/strong\u003e). SK potently induces apoptosis and inhibits proliferation in three HCC cell lines (GQY-7701, Bel-7402, HepG2). Using DIA (Data-Independent Acquisition) proteomics, we identified nine core DEPs (Differentially Expressed Proteins) shared across cell lines. IPA (Ingenuity Pathway Analysis) and molecular docking experiments revealed a regulatory network centered on TP53 and PRKN, suggesting SK exerts dual effects on PRKN-mediated mitophagy (ubiquitin-proteasome system) and TP53-dependent cell cycle arrest⁸. These findings provide novel insights into SK’s multitargeted anti-cancer activity, positioning it as a promising candidate for HCC therapy.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003eComparative Proteomic Analysis of Drug Shikonin Addition to Liver\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZe-ning Wang\u003cstrong\u003e\u003csup\u003e1*\u003c/sup\u003e\u003c/strong\u003e,\u0026nbsp;Cun-yu Li\u003cstrong\u003e\u003csup\u003e2*\u003c/sup\u003e\u003c/strong\u003e, Weimin Zheng\u003cstrong\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/strong\u003e, Yan Jiang\u003cstrong\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e, Ting Yu\u003cstrong\u003e\u003csup\u003e4\u003c/sup\u003e\u003c/strong\u003e, Yang Liu\u003cstrong\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e, Yang Zhang\u003cstrong\u003e\u003csup\u003e1#\u003c/sup\u003e\u003c/strong\u003e, Hong Jin\u003cstrong\u003e\u003csup\u003e1#\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eShanghai Stomatological Hospital \u0026amp; Institutes of Biomedical Sciences, Fudan University, Shanghai, China\u003c/li\u003e\n \u003cli\u003eCollege of Life and Health Sciences, Northeastern University, Shenyang, China\u003c/li\u003e\n \u003cli\u003eSchool of Pharmacy, Nanjing Medical University, Nanjing, 211166, China\u003c/li\u003e\n \u003cli\u003ePolessky State University, Pinsk, Republic of Belarus\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e* These authors contributed equally.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e# Correspondence to:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eHong Jin:\u0026nbsp;[email protected]\u003c/li\u003e\n \u003cli\u003eYang Zhang: [email protected]\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eEmail:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eZe-ning Wang:\u0026nbsp;[email protected]\u003c/li\u003e\n \u003cli\u003eCun-yu Li: [email protected]\u003c/li\u003e\n \u003cli\u003eWeimin Zheng: [email protected]\u003c/li\u003e\n \u003cli\u003eYan Jiang: [email protected]\u003c/li\u003e\n \u003cli\u003eYang Liu: [email protected]\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eKeywords:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShikonin; Proteome; Markers; IPA; Liver Cell Line\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eABSTRACT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e HCC (Hepatocellular Carcinoma) accounts for 85–90% of primary liver cancers and ranks as the third deadliest malignancy worldwide. While targeted therapies have improved outcomes, advanced HCC remains challenging to treat. TCM (Traditional Chinese Medicine), particularly SK (Shikonin) from \u003cem\u003eLithospermum erythrorhizon\u003c/em\u003e, shows promise by targeting multiple cancer hallmarks like apoptosis resistance and angiogenesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Using DIA (Data-Independent Acquisition) proteomics, we analyzed SK-treated HCC cell lines. GO (Gene Ontology) enrichment identified key pathways, while molecular docking validated protein interactions. Immunohistochemistry confirmed differential protein expression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e SK treatment significantly altered mitochondrial function-related proteins. Nine DEPs (Differentially Expressed Proteins) were consistently regulated across all cell lines, forming a network linked to TP53 and PRKN. Molecular docking supported these interactions, and immunohistochemistry verified DEP expression patterns.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e SK exerts anti-HCC effects by modulating mitochondrial proteins and key regulators like TP53/PRKN. These findings highlight SK's multi-target potential and support further investigation of TCM compounds for HCC combination therapies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eINTRODUCTION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCancer ranks as the second leading cause of death worldwide, surpassed only by cardiovascular diseases¹. HCC (Hepatocellular carcinoma), accounting for 85–90% of primary liver cancers, is a major global health burden: it was among the top three cancer-related causes of death in 46 countries and top five in 90 countries in 2020¹. Projections estimate that liver cancer mortality will reach 1.3 million by 2040¹. Current therapeutic options for advanced HCC, including kinase inhibitors, yield limited clinical benefit².\u003c/p\u003e\n\u003cp\u003eIn East Asia and China, TCM (Traditional Chinese Medicine)—including herbal medicine and acupuncture—is frequently integrated with Western medicine to improve outcomes for cancer patients. TCM not only alleviates symptoms such as fatigue, chronic pain, anorexia-cachexia, and insomnia but also mitigates adverse effects of chemotherapy, radiotherapy, or targeted therapies. Notably, TCM demonstrates efficacy in mid-to-late-stage cancers (e.g., gastric, cervical, colorectal, and liver cancers)³. Its advantages include low toxicity, multi-target effects, and potential reversal of MDR (Multi-Drug Resistance)⁴. For example, TCM interventions have been validated in PLGC (Precancerous Lesions of Gastric Cancer)⁵ and CACC \u0026nbsp;(Colitis-Associated Colorectal Cancer)⁶.\u003c/p\u003e\n\u003cp\u003ePrevious studies have identified bioactive components from TCM with anti-cancer properties. For instance, our group characterized the anti-tumor effects of trichosanthin, a ribosome-inactivating protein, revealing dysregulation of ribosome- and spliceosome-related proteins in cancer cells⁷.\u003c/p\u003e\n\u003cp\u003eHere, we investigate the molecular mechanism of SK (Shikonin), a naphthoquinone compound isolated from \u003cem\u003eLithospermum erythrorhizon\u003c/em\u003e (\u003cstrong\u003eFigure 1\u003c/strong\u003e). SK potently induces apoptosis and inhibits proliferation in three HCC cell lines (GQY-7701, Bel-7402, HepG2). Using DIA (Data-Independent Acquisition) proteomics, we identified nine core DEPs (Differentially Expressed Proteins) shared across cell lines. IPA (Ingenuity Pathway Analysis) and molecular docking experiments revealed a regulatory network centered on TP53 and PRKN, suggesting SK exerts dual effects on PRKN-mediated mitophagy (ubiquitin-proteasome system) and TP53-dependent cell cycle arrest⁸. These findings provide novel insights into SK’s multitargeted anti-cancer activity, positioning it as a promising candidate for HCC therapy.\u003c/p\u003e\n\u003cp\u003e\u003cimg width=\"553\" height=\"494\" 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alt=\"image\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1. Workflow for proteomics investigation and validation of anti-cancer mechanism of SK.\u0026nbsp;\u003c/strong\u003eThe study involved three cancer cell lines (QGY-7701, Bel-7402, and HepG2), each with three biological replicates and three technical replicates. Both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e experiments demonstrated that different doses of SK exert varying degrees of inhibition on liver cancer cell lines. Specifically, the DIA (Data-Independent Acquisition) proteomics technology identified over 9,300 mouse proteins. DEPs (Differentially Expressed Proteins) were systematically screened using an integrated analytical approach combining volcano plot analysis, PLS-DA, and WGCNA. Notably, three DEPs showing differential expression across all three cell lines were validated via IHC (Immunohistochemistry).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMETHODS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDrug\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShikonin was purchased from Meilunbio\u003csup\u003e®\u003c/sup\u003e. The molecular formula of shikonin is C₁₆H₁₆O₅, and its molecular weight is 288.30 (\u003cstrong\u003eSupplementary Figure 1\u003c/strong\u003e). It met the quality standard of HPLC purity ≥ 98% as a reference standard.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell Culture\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA 1% Penicillin-Streptomycin solution (Thermo Fisher Scientific, Cat. No. 15140148) was used. When cells reached 50% confluence, fresh medium containing the vehicle (dimethyl sulfoxide, DMSO) was added, and cells were incubated in a humidified atmosphere of either 95% air or 5% CO₂. All experiments were performed independently at least three times and in triplicate. Conditioned media and cells were collected and stored at -80°C until use.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMTT assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHCC cells were seeded into 96-well plates at a density of 1×10⁴ cells per well. The cells were then treated with varying concentrations of SK (1 μM, 5 μM, 8 μM, 10 μM, 20 μM, and 50 μM). Each concentration group included four replicate wells. After 24 hours of incubation with SK, MTT solution (Beyotime, C0009) was added to each well, and the plates were further incubated in the dark for 4 hours. Subsequently, the formazan crystals formed were dissolved by adding DMSO and gently shaking the plates at low speed for approximately 10 minutes. The absorbance was measured at wavelengths of 570 nm and 690 nm using a SpectraMax M5 microplate reader (MD, USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell morphology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells were seeded in 6-well plates at a density of 5×10⁵ cells per well and cultured in Dulbecco's Modified Eagle Medium (DMEM, Gibco) supplemented with 10% fetal bovine serum (FBS, Gibco) and 1% penicillin/streptomycin. When the cells reached 70% confluence, they were treated with SK and incubated for 24 hours. Following the treatment, cell morphology was observed and images were captured using a microscope. The images were acquired and analyzed using Leica software (Leica Microsystems).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eApoptosis Analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHCC cells were seeded in 6-well plates at a density of 1×10⁶ cells per well and treated with or without SK for 24 hours. After treatment, the cells were collected and stained using an Annexin V-FITC/PI apoptosis detection kit (Yeasen, 40302) following the manufacturer's protocol. Briefly, the cells were washed twice with phosphate-buffered saline (PBS) and then stained with Annexin V-FITC and propidium iodide (PI) in the dark at room temperature for 15 minutes. Apoptosis was assessed using a flow cytometer (BD Biosciences, USA), and the data were analyzed using FlowJo software (version 10, USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTumor Model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate the effect of SK on HCC growth in vivo, a xenograft tumor model was established in nude mice. The mice were randomly divided into four groups, with five distinctly marked mice in each group. HMGB1 stable knockdown cell lines (shHMGB1-1 and shHMGB1-2) and control cell lines (shNC1 and shNC2) were subcutaneously injected into the mice. Briefly, 5×10⁶ HCCLM3 cells suspended in 200 μL of PBS (Phosphate-Buffered Saline) were injected into the right flank of each mouse using a 1-mL syringe. After palpable tumors formed, tumor sizes were measured every 5 days. Tumor volume was calculated using the formula: Volume = (L×W²)/2, where L represents the length (longest diameter) and W represents the width (shortest perpendicular diameter) of the tumor, and the results were plotted in mm³. On day 35, the mice were euthanized, and tumor weights were recorded. The tumor growth curve was plotted based on the volume measurements. Additionally, the expression level of HMGB1 in the subcutaneous tumors was analyzed by Western blot. All animal experiments were performed in accordance with protocols approved by the IACUC (Institutional Animal Care and Use Committee) of Fudan University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample preparation and Protein extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQGY-7701, Bel-7402, and Hep G2 cells (5×10⁶ cells each) were harvested, washed with PBS, and centrifuged at 1,000×g for 10 minutes. The supernatant was carefully removed, and the cell pellet was resuspended in lysis buffer containing 7 M urea, 2 M thiourea, 4% CHAPS, 100 mM DTT (Dithiothreitol), 0.5 mM PMSF (PhenylMethylSulfonyl Fluoride), and 1 mM protease inhibitor cocktail. The cells were disrupted by sonication on ice using an ultrasonic instrument, with each pulse lasting 5 seconds and a 10-second interval between pulses. This process was repeated five times. The lysate was then kept on ice for 40 minutes to ensure complete lysis. Cellular debris was removed by centrifugation at 15,000×g for 45 minutes at 4°C. The resulting protein samples were either used immediately or stored at -80°C for subsequent analysis. Protein concentration was determined using the modified Bradford method.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein Digestion and Desalting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo hundred micrograms of protein dissolved in lysate were reduced with 10 mM DTT at 37°C for 1 hour, followed by alkylation with 20 mM iodoacetamide in the dark at room temperature for 30 minutes. Proteins were then precipitated by adding four volumes of ice-cold acetone and incubating overnight at -80°C. After centrifugation at 12,000×g for 15 minutes, the supernatant was removed, and the protein pellet was resuspended in 200 μL of 50 mM ammonium bicarbonate. Trypsin was added at a 1:50 (w/w) enzyme-to-protein ratio for overnight digestion at 37°C. The digestion was terminated by adding formic acid to a final concentration of 5%. The resulting peptide mixture was desalted using a Sepak desalting column (Waters, USA) and prepared for MS (Mass Spectrometry) analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLC (Liquid Chromatography) Separation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor high-pH two-dimensional (2D) separation, 100 μg of protein extract was loaded onto a chromatographic column (BEH C18, 300 Å, 1.7 μm, 2.1 mm×150 mm; Waters, USA). The separation was performed using mobile phase A (water with 5 mM ammonium formate, pH 10.3) and mobile phase B (acetonitrile). The gradient was set to increase mobile phase B linearly from 5% to 45% over 20 minutes. The eluted fractions were concatenated into 20 fractions, which were further combined into 4 final fractions. These fractions were lyophilized and redissolved in an aqueous solution containing 1‰ formic acid for subsequent analysis. The second-dimensional separation was performed using a nanoElute LC system (Bruker Daltonics). A capillary column (250 mm×75 μm, Inopticks) was employed, with mobile phase A (water containing 1‰ formic acid) and mobile phase B (acetonitrile containing 1‰ formic acid). Peptide separation was carried out at a flow rate of 300 nL/min over a 90-minute gradient. The mobile phase B concentration was increased from 2% to 22% in the first 45 minutes, followed by a rapid increase to 37% within 5 minutes and then to 80% within another 5 minutes. The column was rinsed and equilibrated for the final 5 minutes. A total of 200 ng of peptide fragments was injected for LC-MS analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMS (Mass Spectrometry) Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll fractions were analyzed using a hybrid trapped ion mobility spectrometry (TIMS) coupled with a quadrupole time-of-flight mass spectrometer (TIMS-TOF Pro, Bruker Daltonics). The instrument was equipped with a nano-electrospray ion source, and data were acquired in a scanning range of 100-1,700 m/z with a mobility range of 0.7-1.3 Vs/cm². Each acquisition cycle lasted 1.16 seconds, consisting of 1 full MS scan and 10 parallel accumulation serial fragmentation (PASEF) MS/MS scans. The intensity threshold was set to 5,000, with an accumulation and release time of 100 ms. The ion source voltage was maintained at 1,500 V, with an auxiliary gas flow rate of 3 L/min and an ion source temperature of 180°C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw MS data were processed using Peaks Online software (Bioinformatics Solutions, Inc.). A mouse protein database downloaded from SwissProt (17,046 proteins, version 2022-10) was used for protein identification. The mass tolerance was set to 15 ppm for MS\u003csup\u003e1\u003c/sup\u003e and 0.05 Da for MS\u003csup\u003e2\u003c/sup\u003e. Trypsin was specified as the digestion enzyme, allowing for up to one missed cleavage. Carbamidomethylation of cysteine residues was set as a fixed modification, while acetylation (protein N-terminus), oxidation (methionine), and deamidation (asparagine and glutamine) were set as variable modifications. The peak area of identified proteins was extracted and used for subsequent statistical analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBioinformatics analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInter-group statistical analyses were performed using MATLAB. DEPs were screened using VIP (Variable Importance in Projection) scores from OPLS-DA (Orthogonal Partial Least Squares-Discriminant Analysis) and volcano plots. Hierarchical clustering and GO enrichment analysis were conducted using MATLAB (version R2020b). Biological networks were constructed using IPA (Ingenuity Pathway Analysis). Heatmaps were generated using the R package \u003cstrong\u003eComplexHeatmap\u003c/strong\u003e (version 2.12.1). Transcriptomic data from The Cancer Genome Atlas (TCGA) were obtained from the GEPIA2 database (http://gepia2.cancer-pku.cn). Weighted gene co-expression network analysis (WGCNA) was performed using the R package \u003cstrong\u003eWGCNA\u003c/strong\u003e (version 1.72-1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular Docking\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eReceptor Preparation.\u003c/em\u003e\u003c/strong\u003e The PDB file of the target protein was downloaded from the PDB (Protein Data Bank). Subsequently, PyMol software was utilized to eliminate redundant ions and water molecules from the protein structure. To facilitate subsequent docking simulations, AutoDockTools was employed to add hydrogen atoms and assign charges to the target protein. The processed protein was then saved in the PDBQT format, which is compatible with docking programs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eLigand Preparation.\u003c/em\u003e\u003c/strong\u003e The structure of SK was drawn using ChemDraw. This structure was then imported into Chem3D and saved as a PDB file. In AutoDockTools, the conformation of SK was optimized and set according to the principles of molecular conformation. After the conformational adjustment, SK was saved in the PDBQT format, rendering it suitable for docking with the target protein.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDocking Process.\u003c/em\u003e\u003c/strong\u003e Within AutoDockTools, the PDBQT files of both the target protein and SK were opened. A docking box was precisely defined to specify the region of interest within the target protein where the binding interaction with SK was anticipated. Docking calculations were made by AutoDock Vina and viewed by PyMol. The affinity between the target protein and SK was evaluated based on the docking scores obtained from AutoDock Vina, providing insights into the strength of their binding interaction.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eToxicology and systemic safety assessment of SK\u003c/p\u003e\n\u003cp\u003eTo evaluate the potential toxicity and systemic safety of SK, mice were administered low, medium, and high concentrations of SK. The results demonstrated that SK had no significant impact on the growth or body weight of the mice (Figure 2A). Histopathological analysis of liver tissue paraffin sections using H\u0026amp;E (Hematoxylin and Eosin) staining revealed that the liver tissue structure and hepatocyte morphology in SK-treated mice were comparable to those in the control group. These findings suggest that SK does not exhibit significant hepatotoxicity in mice under the tested conditions.\u003c/p\u003e\n\u003cp\u003eTo further assess the systemic toxicity of SK, histopathological analysis was performed on kidney, heart, and liver tissues using H\u0026amp;E staining. As shown in\u0026nbsp;Supplementary Figure 2, no significant toxic alterations, such as cell necrosis or structural damage, were observed in any of the tested tissues across the control and SK-treated groups. These results collectively indicate that SK does not exhibit apparent toxicity to the kidney, heart, or liver under the experimental conditions.\u003c/p\u003e\n\u003cp\u003eAntitumor Efficacy of SK in a Subcutaneous Tumor Model\u003c/p\u003e\n\u003cp\u003eSK exhibited a pronounced inhibitory effect on the growth of HCC subcutaneous tumors. Following the subcutaneous inoculation of liver cancer cells, tumor volume and weight were significantly reduced in mice treated with SK compared to the control group (Figure 2B-F). This inhibitory effect was dose-dependent, with the high-concentration SK group showing the most substantial reduction in tumor volume and weight.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ein vitro\u003c/em\u003e experiments of SK\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCell Viability\u003c/em\u003e. The effect of SK on cell viability was assessed using the Cell Counting Kit-8 (CCK-8, Dojindo, CK04-3000T) in three hepatocellular carcinoma (HCC) cell lines: HepG2, Bel-7402, and QGY-7701. Cells were treated with increasing concentrations of SK (ranging from 0 to 50 \u0026mu;M). SK significantly inhibited the proliferation of all three cell lines in a dose-dependent manner (Figure 3A). However, the sensitivity to SK varied among the cell lines. HepG2 cells were the most sensitive, while QGY-7701 cells exhibited the highest tolerance. These results indicate that SK exerts a potent inhibitory effect on HCC cell proliferation, with the optimal inhibitory concentration varying depending on the cell type.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMorphological Changes\u003c/em\u003e. SK treatment induced significant morphological alterations in HCC cell lines. Following exposure to SK, cells exhibited shrinkage, reduced cell size, rounding, and the appearance of cytoplasmic vacuoles (Figure 3B). These changes are consistent with cellular stress and apoptosis, suggesting that SK disrupts cellular homeostasis and induces cytotoxic effects.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eApoptosis\u003c/em\u003e. The pro-apoptotic effect of SK was evaluated using flow cytometry with Annexin V-FITC and propidium iodide (PI) double staining (Beyotime, C1062L). Treatment with 10 \u0026mu;M SK significantly increased the proportion of early and late apoptotic cells in all three HCC cell lines compared to the control groups (Figure 3C-D). Notably, Bel-7402 cells exhibited the highest proportion of early apoptotic cells, while HepG2 and QGY-7701 cells showed higher proportions of late apoptotic and dead cells. These findings align with the cell viability results, further confirming that SK induces apoptosis in HCC cells. The differential sensitivity of the cell lines to SK underscores the importance of considering cell type-specific resistance when determining optimal dosages for future clinical applications.\u003c/p\u003e\n\u003cp\u003eProteome for three cancer cell lines\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDEPs Screening\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe performed proteomic DIA (Data Independent Acquisition) technology on three liver cancer cell lines (GQY-7701, Bel-7402, and HepG2). A total of 48 samples were included, with biological and technical replicates. Hierarchy Clustering and Boxplot were constructed for observing the reproducibility of the three liver cancer cell lines and biological and technical reproducibility (\u003cstrong\u003eSupplementary\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Figure 3\u0026amp;4\u003c/strong\u003e). Samples treated with drugs were separated from the control group. QGY-7701 and Bel-7402 showed the best performance, with three technical replicates clustering together under each biological replicate, while HepG2 showed a slightly poorer performance, but still able to distinguish between the control and drug treatment groups. From the OPLS-DA (Orthogonal Partial Least Squares Discriminant Analysis) plot (\u003cstrong\u003eFigure 4A\u003c/strong\u003e), there was a clear difference between the control and drug treatment groups, indicating that the VIP (Variable Importance in Projection) index can be used to screen DEPs between groups of samples.\u003c/p\u003e\n\u003cp\u003e9178, 8701 and 9196 proteins were identified in the control group, and 9217, 9060 and 9227 proteins were identified in the drug treatment group (Supplementary2, Table 1). In the control group, the overlap of three biological repetitions of three cell lines was 81%, 82% and 87%, respectively. However, in the drug treatment group, the overlap of three biological repeats was 86%, 92% and 89% respectively (Figure 4B). This result shows that the scale of proteome and biological repetition are close to saturation. A total of 9359 proteins were identified in the three liver cancer cell lines, and 9171 proteins were the same, accounting for 97.99%, indicating that there were very few proteins specifically expressed in each cell line (Figure 4C).\u003c/p\u003e\n\u003cp\u003eWe combined OPLS-DA and volcano plot to screen DEPs. In the volcano plot, the cutoff of fold change between groups was set 2, and the p value of t-test is 0.01. In GQY-7701 cell line, 3260 proteins with the VIP index greater than 1 accounted for 35% (Supplementary Figure 5A), in which 547 proteins were up-regulated and 370 proteins were down-regulated in volcano plot (Supplementary Figure 5B). In Bel-7402 cell line, 3,843 (41%) proteins had VIP index greater than 1, in which 641 proteins were up-regulated and 229 proteins were down-regulated in volcano plot. In HepG2 cell line, 3430 (37%) proteins had VIP index greater than 1, in which 133 proteins were up-regulated and 104 proteins were down-regulated. There are 607 proteins that show significant differences in drug treatment group versus control group across three liver cancer cell lines, and only 9 of them were common differences (Figure 4DF).\u003c/p\u003e\n\u003cp\u003eWGCNA（Weighted Gene Co-expression Network Analysis）is a commonly used bioinformatics analysis method for expression profile data, which can cluster and modularize gene expression profiles. WGCNA can group genes with similar expression patterns into the same module and calculate the similarity between modules and between modules and samples to reveal the interrelationships and regulatory networks between genes. WGCNA can obtain gene modules most related to phenotypes. The most related modules (including positive and negative correlations) were obtained for GQY-7701, Bel-7402, and HepG2 cell lines using WGCNA, which contained 1733, 2323, and 1180 proteins, respectively. The correlation coefficients between the first module and phenotypes were all greater than 0. Interestingly, all nine DEPs described above appeared in the first module of WGCNA (Figure 4E), with five proteins appearing in the first module of all cell lines. The enrichment of biological process of top module for each cell line was described in Supplementary Figure 6-8. Mitochondrial related proteins were significant enriched in the intersected list of top modules from each cell line and DEPs for three cell lines (Supplementary Figure 9).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunctional Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo elucidate the functional impact of SK on HCC cell lines, we conducted GO enrichment analysis. The results revealed significant differences in protein distribution across various GO terms between the drug-treated and control groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSubcellular Localization\u003c/em\u003e\u003c/strong\u003e. In the subcellular localization category, the most pronounced differences were observed in the Nucleolus (GO:0005730) and Mitochondrial Inner Membrane (GO:0005743) (\u003cstrong\u003eFigure 5A\u003c/strong\u003e). The number of proteins localized to these compartments significantly increased in the drug-treated group. The nucleolus, a key organelle involved in ribosome biogenesis and RNA synthesis, plays a critical role in regulating cell cycle, DNA repair, and transcription. The mitochondrial inner membrane, essential for oxidative phosphorylation and energy production, is often dysfunctional in cancer cells. Dysregulation of this compartment, such as reduced membrane potential, defects in the respiratory chain, and reactive oxygen species (ROS) accumulation, can promote tumorigenesis and cancer progression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBiological Processes\u003c/em\u003e\u003c/strong\u003e. In the biological process category, the most differentially regulated terms included Positive Regulation of Translation by RNA Polymerase II (GO:0045944), Neutrophil Degranulation (GO:0043312), Positive Regulation of Translation, DNA-templated (GO:0045893), and Positive Regulation of Cell Population Proliferation (GO:0008284) (\u003cstrong\u003eFigure 5B\u003c/strong\u003e). Neutrophil degranulation, a critical immune response, involves the release of pro-inflammatory factors such as IL-1\u0026beta; and TNF-\u0026alpha;, which can exert anti-tumor effects at high levels of activation. The other three terms, related to gene transcription and translation, highlight the nucleus as a key target for anti-cancer therapies, including DNA-damaging and microtubule-targeting agents.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePathway Enrichment Analysis\u003c/em\u003e\u003c/strong\u003e. We mapped the DEPs obtained from each cell line into the IPA pathway. The enrichment of DEPs is calculated by Fisher exact test in IPA (\u003cstrong\u003eFigure 5D\u003c/strong\u003e), while z-score predicts the likelihood of pathway activation or inhibition based on the number and fold change of DEPs in the location of pathway. That is, target pathway is predicted to be activated when z-score greater than 0, while predicted to be inhibited when z-score less than 0 (\u003cstrong\u003eFigure 5C\u003c/strong\u003e). The results showed that OXPHOS (Oxidative Phosphorylation) and NER Pathway (Nucleotide Excision Repair Pathway) were enriched and predicted to be activated, while the Sirtuin pathway was inhibited\u003csup\u003e9\u003c/sup\u003e. OXPHOS are often inhibited in tumor cells (Warburg effect). However, both activation and inhibition of OXPHOS may have anti-cancer effects, and the research on this aspect has not been clear. Sirtuin is a class of NAD-dependent deacetylase. Sirtuin pathway can inhibit the expression of P16 and the activity of AMPK, thus promoting the growth and metastasis of cancer. In the drug treatment group, Sirtuin pathway was inhibited, reflecting the anti-cancer pathway of SK. NER Pathway is mainly responsible for repairing DNA damage. In the drug treatment group, NER Pathway was activated and enriched, which slowed down the deterioration of tumor. GO categories and KEGG pathways related to\u0026nbsp;cell death\u0026nbsp;and\u0026nbsp;oxidative phosphorylation\u0026nbsp;were significantly enriched in the proteomic analysis (\u003cstrong\u003eFigure 5E-F \u0026amp; Supplementary Figure 10\u003c/strong\u003e). Notably, apoptosis-related terms were predominantly enriched in the Bel-7402 cell line, suggesting that SK exerts a pronounced pro-apoptotic effect in this cell type.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGO terms screening\u003c/em\u003e\u003c/strong\u003e. To identify key GO terms associated with SK treatment, we compared the overall protein expression levels between the control and drug-treated groups across 9,375 GO terms. Differential expression (t-test, p \u0026lt; 0.01) was observed in 104 terms for QGY-7701, 328 terms for Bel-7402, and 28 terms for HepG2 (\u003cstrong\u003eFigure 6A\u003c/strong\u003e). Among these, four mitochondrial-related GO terms: Mitochondrial Electron Transport (GO:0006120), Mitochondrial Respiratory Chain Complex I Assembly (GO:0032981), Mitochondrial Translational Elongation (GO:0070125), and Mitochondrial Translational Termination (GO:0070126) showed significant differences between the treatment and control groups in two cell lines (\u003cstrong\u003eFigure 6B-E\u003c/strong\u003e). Notably, proteins associated with these terms were upregulated in the SK-treated groups. Mitochondria play a central role in ATP production, and their function is frequently suppressed in tumor cells. Restoring mitochondrial function has been linked to anti-cancer effects, as demonstrated by studies showing that certain drugs and natural products can inhibit tumor growth and metastasis by enhancing mitochondrial activity. In this study, SK significantly enhanced mitochondrial electron transport, respiratory chain function, and translation processes, suggesting its potential to restore mitochondrial homeostasis and exert anti-tumor effects. Furthermore, analysis using the MitoCarta database revealed significant upregulation of mitochondrial-related DEPs in the Bel-7402 cell line following SK treatment compared to the control group (Supplementary Figure 11). This upregulation was observed across all mitochondrial functional categories, further supporting the role of SK in enhancing mitochondrial function and its potential as a therapeutic agent for hepatocellular carcinoma.\u003c/p\u003e\n\u003cp\u003eNine DEPs and validation\u003c/p\u003e\n\u003cp\u003eThe nine DEPs identified across all three HCC cell lines were categorized into three clusters based on their expression patterns (Figure 7A). In the first two clusters, which include S2512, YIF1A, TR112, GP180, CENPV, and NDUS7, all proteins were upregulated in the SK-treated groups. In contrast, the three proteins in the third cluster (UB2V1, ACTS, and MIA40) were downregulated. NDUS7, TR112, and MIA40 are enzymes; S2512, MIA40, and NDUS7 are localized to the mitochondria; CENPV, TR112, and UB2V1 are nuclear proteins; and GP180 and YIF1A are membrane-associated proteins. Across all cell lines, the nine DEPs exhibited significant differences in protein expression between the SK-treated and control groups (Figure 7B).\u003c/p\u003e\n\u003cp\u003eTo validate these findings, we selected three DEPs (512, ACTS, and UB2V1) for immunohistochemical analysis. The immunohistochemical results confirmed the proteomic data, showing complete consistency in protein expression patterns (\u003cstrong\u003eFigure 7D\u003c/strong\u003e). Specifically, the IOD (Integral Optical Density) values of ACTS and UB2V1 significantly decreased with increasing SK concentration, while the IOD value of S2512 increased significantly (\u003cstrong\u003eFigure 7E\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eTo further investigate the relevance of these DEPs in other cancer types, we analyzed their transcriptomic expression profiles across 31 tumors using the GEPIA2 database. The data revealed that ACTS was downregulated in all tumor types, while the other eight DEPs were upregulated. The upregulation of these DEPs was most prominent in Diffuse Large B-cell Lymphoma (DLBC), Pancreatic Adenocarcinoma (PAAD), and Thymoma (THYM) (\u003cstrong\u003eFigure 7C\u003c/strong\u003e). Additionally, data from the Human Protein Atlas (HPA) indicated that, except for CENPV and ACTS, the remaining seven DEPs were associated with cancer prognosis (\u003cstrong\u003eSupplementary2, Table 2\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eNetwork analysis and molecular docking\u003c/p\u003e\n\u003cp\u003eUsing IPA network analysis, we constructed a network of these 9 DEPs and found that the differential expression of these DEPs was directly or indirectly related to TP53 and PRKN (\u003cstrong\u003eFigure 8A\u003c/strong\u003e). The systematic docking screening against all network hubs (degree \u0026ge;3) revealed selective binding of SK to PRKN and TP53 proteins, with binding affinities significantly stronger than other nodal molecules (-\u0026Delta;G \u0026gt;6 kcal/mol). This target specificity aligns with their topological dominance in the IPA network, where both molecules exhibited as highest betweenness centrality and degree of connectivity. By the way, the observed dual targeting suggests SK may exert therapeutic effects through coordinated modulation of PRKN-mediated mitophagy (Ubiquitin-proteasome system) coupled with TP53-dependent cell cycle arrest (Genomic stability control).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn vivo and in vitro experiments demonstrated that SK affected the size, volume, weight, metastasis, and apoptosis of liver tumors, with the effect intensifying as the dosage increased. We employed the proteomics DIA method to profile the proteomes of three liver cancer cell lines. Enrichment analysis revealed significant alterations in Neutrophil Degranulation, Mitochondrial Inner Membrane, Oxidative Phosphorylation, NER Pathway, and Sirtuin Signaling Pathway post - drug treatment. A total of 9 DEPs were identified across all three cell lines, with subcellular localizations as follows: SLC25A12 (S2512), CHCHD4 (MIA40), and NDUFS7 (NDUS7) in the mitochondria; CENPV (CENPV), TRMT112 (TR112), and UBE2V1 (UB2V1) in the nucleus; GPR180 (GP180) and YIF1A (YIF1A) on the membrane; and ACTA1 (ACTS) on the cytoskeleton. IPA regulatory network construction indicated that these 9 DEPs were directly or indirectly related to TP53 and PRKN.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMitochondrial DEPs\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSLC25A12 is mitochondrial membrane transporter mediating aspartate-glutamate exchange. Low SLC25A12 expression correlates with poor prognosis in multiple cancers, and its knockdown promotes lung metastasis and reduces survival in mice¹⁰. CHCHD4 is critical for mitochondrial respiratory chain assembly. Overexpression in tumors correlates with enhanced OXPHOS, EMT phenotypes, and poor patient outcomes via mTORC1 activation¹¹. NDUFS7 is a subunit of complex I in OXPHOS. Downregulated in clear cell renal carcinoma and modulated by natural compounds to inhibit oncogenesis¹².\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNuclear DEPs\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCENPV is a centromere-associated protein. In oral squamous cell carcinoma, DNA methylation of \u003cem\u003eCENPV\u003c/em\u003e is part of a prognostic signature¹⁴. TRMT112 is a methyltransferase cofactor enhancing WBSCR22 stability. Co-overexpression with WBSCR22 suppresses pancreatic cancer progression¹⁵. UBE2V1 is an E2 ubiquitin ligase promoting colorectal cancer metastasis via SIRT1 degradation and autophagy inhibition¹⁶.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMembrane DEPs\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGPR180 is a GPCR linked to vascular smooth muscle proliferation. Hypermethylation of \u003cem\u003eGPR180\u003c/em\u003e predicts poor HCC prognosis¹⁷. YIF1A is involved in ER-Golgi trafficking. Its homolog YIPF2 enhances apoptosis in non-small cell lung cancer via TNFRSF10B recycling¹⁸.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCytoskeletal DEP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eACTA1 is an actin isoform regulating cell motility. Overexpression correlates with early tongue cancer metastasis and EMT progression¹⁹.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eSK, a naphthoquinone compound derived from traditional Chinese medicine, exhibits significant potential for cancer prevention and treatment. Toxicological studies demonstrated that SK has moderate hepatotoxicity in mice. Notably, as the concentration of SK increased, a dose-dependent inhibition of tumor volume and weight was observed in mice, highlighting its potent anti-tumor efficacy in vivo. In vitro experiments further revealed that SK reduces cell viability, inhibits migration, and promotes apoptosis in three HCC cell lines: QGY-7701, Bel-7402, and HepG2.\u003c/p\u003e\n\u003cp\u003eIn this study, the optimal dose of SK for the three HCC cell lines was determined using the MTT assay. Subsequently, DIA proteomic technology was employed to investigate the molecular mechanisms underlying SK's anti-cancer effects. Proteomic analysis was performed on both control and SK-treated groups for each cell line, with repeated sampling to ensure robustness. DEPs were identified through OPLS-DA, volcano plots, and WGCNA. A high proportion of cell line-specific DEPs were observed, indicating that even within the same organ, different cell types may adopt distinct anti-cancer pathways in response to SK. Among the DEPs, nine were consistently differentially expressed across all three cell lines. Three of these were further validated using immunohistochemistry.\u003c/p\u003e\n\u003cp\u003eImportantly, the regulatory network constructed from these nine DEPs revealed that their differential expression is directly or indirectly linked to TP53 and PRKN, a finding further supported by molecular docking studies. This dual targeting suggests that SK may exert its therapeutic effects through the coordinated modulation of PRKN-mediated mitophagy (involving the ubiquitin-proteasome system) and TP53-dependent cell cycle arrest (critical for genomic stability control). These mechanisms collectively highlight SK's potential to disrupt cancer cell survival and proliferation through synergistic pathways.\u003c/p\u003e"},{"header":"ABBREVIATION","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFull Name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eColitis-Associated Colorectal Cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDEPs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDifferential Expressed Proteins\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eData Independent Acquisition\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEpithelial-Mesenchymal Transition\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHepatocellular Carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eIL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInterLeukin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMDR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMultiDrug Resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNER Pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNucleotide Excision Repair Pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNucleolar Protein\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOPLS-DA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOrthogonal Partial Least Squares Discriminant Analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOXPHOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMitochondrial Oxidative Phosphorylation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePLGC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePrecancerous Lesions of Gastric Cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSIRT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNAD-dependent protein deacetylase sirtuin-1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTCM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTraditional Chinese Medic\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTNF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTumor Necrosis Factor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTNFRSF10B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTumor Necrosis Factor Receptor SuperFamily Member 10B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eVIP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eVariable Importance in Projection\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWGCNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eWeighted Gene Co-expression Network Analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYIP1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eYPT1-interacting protein\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are so grateful to the selfless help from the Shanghai Huisen Science \u0026amp; Technology Company for biological validation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the National Nature Science Foundation of China (32070605 \u0026amp; 32371334).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONSENT FOR PUBLICATION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animal experiments were conducted under the protocols approved by the institutional animal care and use committee at Fudan university.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the iProX partner repository with the identifier IPX0003967001.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCOMPETING INTERESTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eConception and design: Hong Jin\u003c/li\u003e\n \u003cli\u003eAdministrative support: Hong Jin\u003c/li\u003e\n \u003cli\u003eCollection and assembly of data: Yang Zhang and Zening Wang\u003c/li\u003e\n \u003cli\u003eData analysis and interpretation: Yang Zhang and Zening Wang\u003c/li\u003e\n \u003cli\u003eManuscript writing: All authors；\u003c/li\u003e\n \u003cli\u003eFinal approval of manuscript: All authors.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRumgay, H.\u003cem\u003e et al.\u003c/em\u003e Global burden of primary liver cancer in 2020 and predictions to 2040. \u003cem\u003eJ Hepatol\u003c/em\u003e\u003cstrong\u003e77\u003c/strong\u003e, 1598-1606, doi:10.1016/j.jhep.2022.08.021 (2022).\u003c/li\u003e\n\u003cli\u003eCrunkhorn, S. 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Y.\u003cem\u003e et al.\u003c/em\u003e Actin-Associated Gene Expression is Associated with Early Regional Metastasis of Tongue Cancer. \u003cem\u003eLaryngoscope\u003c/em\u003e\u003cstrong\u003e131\u003c/strong\u003e, 813-819, doi:10.1002/lary.29025 (2021).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8322459/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8322459/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e HCC (Hepatocellular Carcinoma) accounts for 85–90% of primary liver cancers and ranks as the third deadliest malignancy worldwide. While targeted therapies have improved outcomes, advanced HCC remains challenging to treat. TCM (Traditional Chinese Medicine), particularly SK (Shikonin) from \u003cem\u003eLithospermum erythrorhizon\u003c/em\u003e, shows promise by targeting multiple cancer hallmarks like apoptosis resistance and angiogenesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Using DIA (Data-Independent Acquisition) proteomics, we analyzed SK-treated HCC cell lines. GO (Gene Ontology) enrichment identified key pathways, while molecular docking validated protein interactions. Immunohistochemistry confirmed differential protein expression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e SK treatment significantly altered mitochondrial function-related proteins. Nine DEPs (Differentially Expressed Proteins) were consistently regulated across all cell lines, forming a network linked to TP53 and PRKN. Molecular docking supported these interactions, and immunohistochemistry verified DEP expression patterns.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e SK exerts anti-HCC effects by modulating mitochondrial proteins and key regulators like TP53/PRKN. These findings highlight SK's multi-target potential and support further investigation of TCM compounds for HCC combination therapies.\u003c/p\u003e","manuscriptTitle":"Comparative Proteomic Analysis of Drug Shikonin Addition to Liver","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-16 03:50:45","doi":"10.21203/rs.3.rs-8322459/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4dc65741-e039-4e70-9f26-f442288eb14f","owner":[],"postedDate":"December 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-16T15:39:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-16 03:50:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8322459","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8322459","identity":"rs-8322459","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}