Assessment of circulating CD24, CD44, and CD45 stem cell markers as novel early diagnostic tools for hepatocellular carcinoma

Assessment of circulating CD24, CD44, and CD45 stem cell markers as novel early diagnostic tools for hepatocellular carcinoma | 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 Assessment of circulating CD24, CD44, and CD45 stem cell markers as novel early diagnostic tools for hepatocellular carcinoma Doaa Shoieb, Mohamed Abd-Elbaset, Mona S. Gouida, Ibrahim S. Kamel, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6886613/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: Early diagnosis of hepatocellular carcinoma (HCC) is one of the determinant factors for effective treatment with better prognosis. This study evaluated circulating stem cell markers CD24, CD44, and CD45 as potential early diagnostic biomarkers for HCC. Methods : In this study, male Wistar rats were used, grouped in four categories: Control, Olive Oil, Fibrosis (CCl 4 -induced), and HCC (DEN-induced). Serum levels of CD24, CD44, and CD45 were estimated and correlated with the levels of apoptotic markers (BCL2, BAX, P53); angiogenic markers (VEGF); oxidative stress markers (SOD); liver function tests (ALT, AST, ALP); and inflammatory cytokines (TNF-α). Histological examinations were done by H&E and Masson's Trichrome techniques. Results : Levels of CD24, CD44, and CD45 were significantly higher in the HCC group. The markers showed strong correlations with increased apoptotic activity, angiogenesis, oxidative stress, and altered liver function tests. Histological findings demonstrated severe fibrosis and damage to the liver tissue. High levels of inflammatory cytokines and AFP further confirm the diagnosis of HCC. Conclusion: The study demonstrates that CD24, CD44, and CD45 are viable early diagnostic markers for HCC. Their implementation in clinical settings could facilitate early diagnosis and improve the management and treatment outcomes of HCC patients. Hepatocellular Carcinoma CD24 CD44 CD45 Biomarkers Early Diagnosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Introduction The liver is constantly subjected to numerous external and internal elements, including viral infections, excessive alcohol consumption, pharmaceutical agents, toxic chemicals, dietary fats, and metabolic byproducts. These factors can inflict damage on liver tissue, triggering inflammatory responses and contributing to the progressive deterioration of liver function [ 1 ]. If the liver injury is persisted for a long time, it developed into chronic liver diseases starting with fibrosis then cirrhosis and ended by hepatocellular carcinoma [ 2 ]. Numerous chemicals can cause liver injury and reported to induce hepatotoxicity such as carbon tetrachloride (CCl 4 ), chloroform (CHCl 3 ) and iodoform (CHI 3 ), Bromobenzene, Ethionine and Diethylnitrosamine. CCl4 was approved to induce liver injury in many species. Its toxic effects depend on the dose and duration of exposure [ 3 ]. CCl 4 is metabolized in the liver to the trichloromethyl radical (CCl 3 *). Exposure to the CCl3* radical can disrupt critical biological processes. Its reactivity with lipids, proteins, and nucleic acids has been linked to disruptions in lipid metabolism, lowering in protein quantities, triggering mutations in DNA and progression into HCC [ 4 ]. Nitrosamines are carcinogens present in smoked pickled fish, nitrite-cured meats, agricultural chemicals, and alcoholic beverages or tobacco smoke. Diethylnitrosamine (DEN) is one of the most significant hepatotoxicants and hepatocarcinogens [ 5 ]. The biotransformation of DEN results in the accumulation of reactive oxygen species (ROS), a key factor in the oxidative damage observed in DNA and other cellular macromolecules. This compound also impairs the activity of various enzymes involved in DNA repair processes [ 6 ]. The liver possesses the capacity to regenerate the parenchymal tissue loss as a result of infection or injury. This is done through the increase in the population either of the hepatocytes or the liver progenitor cells when the extensive damage cannot enable the hepatocytes to feedback by participating in the proliferative response. Under normal conditions, stem cells remain in a dormant state within their niche. When activated, these stem cells divide, producing offspring that retain the ability to self-renew and others that can proliferate and differentiate into the specific cell types needed to repair the tissue [ 7 ]. Hepatic stem cells characterized by expression of CD133, CD44, CD45, CD90, epithelial cell adhesion molecule (EpCAM), CD47, CD34, C-kit, CD13, CD24, oval cell marker (OV6), DLK1, K19, and Lgr5 + on their surfaces [ 8 ]. Hence, in this study, we will assess some stem cell markers (CD24, CD44, and CD45) as a potential early diagnostic tools for hepatocellular carcinoma. Materials and Methods Animals Adult male albino Wistar rats, weighing between 130–150 g, were sourced from the Merck animal facility at the Faculty of Medicine, Mansoura University, Egypt. They were housed under standard laboratory conditions in clean, well-ventilated plastic cages, with free access to a standard commercial pellet diet and water. Chemicals The chemicals used in the study included: CCl 4 (Sigma Chemicals, St. Louis, MO), N-Nitrosodiethylamine (DEN) solution (Sigma Chemicals, St. Louis, MO), absolute ethanol and xylene (Supelco Inc., Sigma-Aldrich, USA), eosin yellow (Alpha Chemika, India), hematoxylin solution (Techno Pharmchem, India), and Masson's trichrome solution (Techno Pharmchem, India). Experimental Design The rats were divided into four groups, each consisting of 10 rats, and were administered olive oil and CCl4 for 7 weeks, followed by DEN for 10 weeks. Group 1 was the control and hence was not treated at all. In group 2, olive oil was injected intraperitoneally at a volume of 0.1 ml/100g twice a week at regular intervals [ 9 ]. Group 3: (CCl 4 ) receiving a 1:1 mixture of CCl 4 with olive oil, at the dose of 0.2 ml/100g, twice a week, at regular intervals [ 9 ]. Group 4: received in their drinking water 0.01% DEN for a period of 8 weeks. Subsequently, they were treated with normal denial-containing water [ 10 ]. Sample Collection and Preparation Blood samples were obtained by laparotomy and direct cardiac puncture. Following collection, blood samples were incubated at 37°C for 30 minutes to facilitate complete clot formation. Subsequently, serum was obtained by centrifugation at 3000 rpm for 15 minutes. The serum was used for the estimation of hepatic function parameters, fibrosis and HCC markers. Blood aliquots were then put into EDTA-containing tubes for immediate hematological assessment. A piece of the liver tissue from each rat was fixed in 10% buffered formalin for pathological examination. Biochemical Parameters Liver function was determined via measuring alanine aminotransferase (ALT) and aspartate aminotransferase (AST), and alkaline phosphatase (ALP) using COBAS INTEGRA systems. ALT was assessed with the ALTL kit, Test ID 0-495, by an IFCC kinetic method monitoring NADH oxidation [ 11 ]. AST was assessed using the ASTL kit, Test ID 0-494, based on the detection of oxaloacetate formation and its reaction with NADH [ 11 ]. ALP levels were assessed using the ALP2L kit (Test ID 0-550), employing a colorimetric assay that measures the cleavage of p-nitrophenyl phosphate to p-nitrophenol [ 12 ]. Additionally, alpha-fetoprotein (AFP), a marker associated with cancer-associated fibroblasts, was measured using the Rat AFP ELISA Kit (Catalog No. CSB-E08281r, Cusabio) via a quantitative sandwich enzyme immunoassay, with absorbance measured at 450 nm. Oxidative stress was gauged by measuring SOD1 levels using a NO ELISA kit (Catalog No. CSB-EL022397RA, Cusabio) through a sandwich ELISA method, with absorbance also determined at 450 nm. Western Blotting Proteins were isolated from blood samples using TriFast reagent, which facilitated the concurrent extraction of RNA, DNA, and proteins. The homogenized samples underwent phase separation, where RNA was retrieved from the aqueous phase, DNA from the interphase, and proteins from the phenol phase. Proteins were then precipitated, washed, and dissolved in SDS. For electrophoresis, various stock solutions, including acrylamide-bis-acrylamide, SDS, and Tris-HCl buffers, were prepared. The proteins were resolved on a 12% slab gel with a 4% stacking gel, stained with Coomassie blue, and analyzed using a GelDoc system equipped with TotalLab software. Transfer of proteins from SDS-PAGE gels to Hybond™ nylon membranes was performed using a TE62 Standard Transfer Tank. Following blocking with a nonfat dry milk solution, the membranes were incubated overnight with primary antibodies, washed, and then incubated with HRP-conjugated secondary antibodies for visualization of protein bands. Flow Cytometry Analysis Peripheral blood mononuclear cells were isolated by initially diluting the blood with an equal volume of PBS, followed by careful layering onto Ficol Hypaque and centrifugation at 400g for 30 minutes at 20°C. Cells were collected from the resulting interface, thoroughly washed, and then resuspended in PBS-BSA to achieve a final concentration of at least 1 x 10 7 cells/mL. For the staining procedure, 1 x 10 6 cells were incubated with 10 µL of conjugated antibodies for 30 minutes at 4°C in the dark. Following incubation, the cells were washed, resuspended in PBS, and fixed using 4% paraformaldehyde in PBS. The flow cytometric analysis was performed using an Accuri C6 flow cytometer (Becton Dickinson, USA). Estimation of hepatic stem cell markers Stem cell markers, such as CD45, CD24, and CD44 were assessed to identify specific cellular characteristics. The expression of CD45 was assessed using PE Rat Anti-Mouse CD45 antibody (BD Biosciences, Cat. No. 561087). CD24 was measured using PE Rat Anti-Mouse CD24 antibody (BD Biosciences, Cat. No. 553262). CD44 was quantified using PE Rat Anti-Mouse CD44 antibody (BD Biosciences, Cat. No. 561860). Apoptotic Markers Apoptotic markers including Bcl2, Bax, and P53 were measured to understand the apoptotic processes in the cells. Bcl2 : Measured using the Bcl-2 Monoclonal Antibody (10C4), FITC, Invitrogen kit (Cat. No. 11-6992-42) via flow cytometry (Accuri C6, Becton Dickinson, USA). Bax : Quantified using the Bax ELISA kit (Cat. No. MBS2512405) based on the Sandwich-ELISA principle, with absorbance measured at 450 nm. P53 : Analyzed using the Human/Mouse/Rat p53 Antibody kit (Cat. No. MAB1355) via western blotting. Angiogenic Marker To assess angiogenic activity, VEGF levels were measured using a VEGF ELISA kit (Catalog No. RRV00, R&D Systems) following a quantitative sandwich enzyme immunoassay technique, with absorbance recorded at 450 nm using a microplate reader (Stat Fax 4700, Awareness Technology, USA). Cytokines Cytokine analysis involved quantifying TNF-α levels using the Rat TNF alpha ELISA Kit (Catalog No. ab236712, Abcam), employing the sandwich ELISA technique, with data analyzed through a standard curve to determine cytokine concentrations. Histological Studies Preparation of Sections Liver samples were preserved in 10% buffered formalin for a duration of 48 hours. Following fixation, the tissues underwent a dehydration process using increasing concentrations of ethyl alcohol, were cleared with xylene, and then embedded in paraplast wax. Thin sections, measuring 5 µm in thickness, were sliced and subsequently stained for detailed observation under a light microscope. Haematoxylin and Eosin (H&E) Staining H&E staining was performed to observe the general histological structure. Sections were dewaxed, hydrated, and stained with hematoxylin for nuclear visualization, followed by eosin Y for cytoplasmic staining. This method provides a blue color for nuclei and a red color for cytoplasm, facilitating the differentiation of cellular components. Masson's Trichrome Staining Masson's Trichrome staining was used to differentiate cellular elements from connective tissue. The procedure involved staining nuclei with Weigert’s hematoxylin, followed by Biebrich scarlet-acid fuchsin for acidophilic components. Phosphomolybdic acid was used to differentiate the stain, and aniline blue was applied to stain collagen fibers blue, with a red background and black-stained nuclei. The sections were then dehydrated, cleared, and mounted for examination. Results Biochemical Analysis The liver enzyme levels exhibited notable changes across different treatment groups. As shown in Table 1 and Fig. 1 (A) and (B) , ALT and AST levels were significantly lower in the Olive Oil group, while significantly higher in the fibrosis (CCl 4 ) and HCC (DEN) groups compared to controls (p < 0.0001). ALP levels followed a similar pattern, with significant increases in the fibrosis and HCC groups and a decrease in the Olive Oil group compared to controls (p < 0.0001) (Table 1 and Fig. 1 (C)) . These results indicate distinct liver enzyme alterations due to the different treatments. Table 1 Biochemical parameters of liver function (ALT, AST, ALP) in different groups Groups ALT (U/L) AST (U/L) ALP (U/L) Control 37.5 ± 5.2 123 ± 6.976 110.3 ± 2.63 Olive Oil 20.2 ± 2.8 a 77 ± 8.515 a 58.40 ± 13.09 a Fibrosis 113.2 ± 40.2 ab 344.6 ± 176.0 ab 274.8 ± 98.99 ab HCC 105.4 ± 22.2 ab 260.4 ± 147.6 b 277.1 ± 117.2 ab The values are presented as mean ± standard error (SE). The differences between groups were analyzed using a one-way ANOVA test followed by Tukey HSD post hoc analysis. Letters (a, b, ab) indicate significant differences: a : Significantly different from the Control group (p < 0.0001); b : Significantly different from the Olive Oil group (p < 0.0001); ab : Significantly different from both Control and Olive Oil groups (p < 0.0001). Angiogenic and Oxidative Stress Markers The levels of superoxide dismutase 1 ( SOD1 ), a marker of oxidative stress, and vascular endothelial growth factor ( VEGF ), a key angiogenic factor, were measured in different rat groups (Control, Olive Oil, Fibrosis, HCC). As shown in Table 2 and Fig. 2 (A) and (B), s ignificant differences were observed in the levels of these markers across the groups, with VEGF and SOD1 levels indicating distinct alterations in oxidative stress and angiogenic activity due to different treatments (p < 0.0001). Table 2 Levels of VEGF and SOD in different groups Group VEGF (pg/ml) SOD (U/ml) Control 6.736 ± 2.112 159.3 ± 23.63 Olive Oil 7.246 ± 1.020 123.6 ± 16.23 a Fibrosis 1.832 ± 0.3469 ab 91.48 ± 13.53 ab HCC 1.350 ± 0.3371 ab 81.07 ± 8.985 abc The values are presented as mean ± standard error (SE). The differences between groups were analyzed using a one-way ANOVA test followed by Tukey HSD post hoc analysis. Letters (a, b, ab) indicate significant differences: a : Significantly different from the Control group (p < 0.0001); b : Significantly different from the Olive Oil group (p < 0.0001); ab : Significantly different from both Control and Olive Oil groups (p < 0.0001). Inflammatory Cytokines and Cancer-Associated Fibroblast Markers The VEGF and TNF-α levels were quantified to assess angiogenic and inflammatory responses. As shown in Table 3 and Fig. 3 (A) and (B) , both markers were significantly elevated in the Fibrosis and HCC groups, reflecting increased angiogenesis and inflammation (p < 0.0001). Table 3 Levels of TNF-α and AFP in different groups Group TNF-α (pg/ml) AFP (pg/ml) Control 290.0 ± 34.86 37.74 ± 2.756 Olive Oil 369.0 ± 36.55 a 147.0 ± 4.341 a Fibrosis 660.0 ± 42.92 ab 437.4 ± 29.82 ab HCC 758.6 ± 115.21 abc 621.9 ± 12.08 abc The values are presented as mean ± standard error (SE). The differences between groups were analyzed using a one-way ANOVA test followed by Tukey HSD post hoc analysis. Letters (a, b, ab) indicate significant differences: a : Significantly different from the Control group (p < 0.0001); b : Significantly different from the Olive Oil group (p < 0.0001); ab : Significantly different from both Control and Olive Oil groups (p < 0.0001). Apoptotic Markers The assessment of apoptotic markers Bcl2, Bax, and P53 indicated alterations in apoptosis regulation across the groups. As shown in Table 4 and Figs. 4 , 5 and 6 , elevated Bax levels (measured by ELISA) and P53 levels (measured by Western blot) coupled with reduced Bcl2 levels (measured by Flow Cytometry) were observed in the HCC group, suggesting increased apoptotic activity (Table 3 ). Table 4 Expression levels of apoptotic markers (BCL2, BAX, P53) in different groups Group BCL2 (%) BAX (pg/ml) P53 (%) Control 34.5 ± 2.3 2.27 ± 0.92 3.518 ± 0.5322 Olive Oil 43.3 ± 2.7 a 0.58 ± 0.23 a 8.280 ± 0.4764 a Fibrosis 67.9 ± 3.4 ab 0.8 ± 0.24 a 13.52 ± 0.7650 ab HCC 85.6 ± 3.1 abc 0.24 ± 0.07 abc 16.69 ± 0.4976 abc The values are presented as mean ± standard error (SE). The differences between groups were analyzed using a one-way ANOVA test followed by Tukey HSD post hoc analysis. Letters (a, b, ab) indicate significant differences: a : Significantly different from the Control group (p < 0.0001); b : Significantly different from the Olive Oil group (p < 0.0001); ab : Significantly different from both Control and Olive Oil groups (p < 0.0001). Stem Cell Markers: CD24, CD44, CD45 Flow cytometry was employed to determine the expression of stem cell markers CD24, CD44, and CD45 in control, olive oil, fibrosis, and HCC rat groups (Table 5 , Figs. 7 – 10 ). The percentage of positive cells varied significantly across the groups. CD45 + cells were present at 22.2% (control), 15.6% (olive oil), 55.1% (fibrosis), and 74.6% (HCC). Compared to the control, CD45 expression was significantly lower in the olive oil group and significantly higher in the fibrosis and HCC groups (p < 0.0001). CD44 + cells were detected at 12.6% (control), 24.2% (olive oil), 38.1% (fibrosis), and 84.6% (HCC), with all treatment groups exhibiting significantly increased expression (p < 0.0001). Similarly, CD24 + cells were found at 13.9% (control), 25.5% (olive oil), 40.7% (fibrosis), and 66.9% (HCC), with significant increases in all treatment groups (p < 0.0001). Table 5 Expression levels of CD24, CD44, and CD45 in different groups Group CD24 + (%) CD44 + (%) CD45 + (%) Control 14.2 ± 2.2 12.9 ± 1.6 22.4 ± 0.83 Olive Oil 26.5 ± 3.4 a 23.9 ± 2.6 a 15.4 ± 2.1 a Fibrosis 41.1 ± 5.2 ab 38.5 ± 2.1 ab 55.2 ± 1.1 ab HCC 67.9 ± 1.6 abc 84.9 ± 2.2 abc 74.7 ± 1 abc The values are presented as mean ± standard error (SE). The differences between groups were analyzed using a one-way ANOVA test followed by Tukey HSD post hoc analysis. Letters (a, b, ab) indicate significant differences: a : Significantly different from the Control group (p < 0.0001); b : Significantly different from the Olive Oil group (p < 0.0001); ab : Significantly different from both Control and Olive Oil groups (p < 0.0001). Correlation Analysis of Stem Cell Markers with Biochemical Parameters The correlation analysis of stem cell markers (CD24, CD44, CD45) with various biochemical parameters was conducted to assess their interrelationships. Significant correlations were observed for each marker, as detailed in Fig. 11 : CD24 (Fig. 11 A), CD44 (Fig. 11 B), and CD45 (Fig. 11 C). The correlation analysis of stem cell markers CD24, CD44, and CD45 revealed similar patterns. Positive correlations were observed with BCL2, P53, VEGF, SOD, ALT, AST, ALP, and AFP for all three markers. In contrast, negative correlations were identified with BAX and TNF-α. These findings suggest that higher expression of stem cell markers is associated with increased levels of angiogenic, oxidative stress, and liver function markers, while markers related to apoptosis and inflammation exhibit inverse relationships. Histological Studies Microscopic examination of Hematoxylin and Eosin (H&E) -stained liver tissue from the control group demonstrated normal hepatic architecture. Hepatocytes were observed to be organized in characteristic cords extending radially from the central veins towards the portal triads (Fig. 12 A & 12 B). The olive oil group showed almost normal liver architecture with congested interhepatic sinusoids (Fig. 12 C & 12 D). The CCl4 group exhibited hepatocyte stress, ballooning of the cytoplasm, pyknosis of the nuclei, inflammatory cell infiltration, and fibroblast and collagen fiber bands separating the hepatic lobules (Fig. 12 E & 12 F). The DEN-treated group showed abnormal hepatic architecture with hepatocytes arranged into solid nodules which were surrounded by pronounced neuro-inflammatory zones containing fibrous tissue, infiltrated with leukocytes and hemosiderin-laden macrophages (Fig. 12 G & 12 H). Masson's Trichrome staining further confirmed these observations. The control group displayed normal distribution of fibrous tissue surrounding the central vein (Fig. 13 A & 13 B). The olive oil group showed minimal expression of fibrous tissue bands (Fig. 13 C & 13 D). The CCl4 group exhibited extensive fibrous bands separating the hepatic lobules (Fig. 13 E & 13 F). The DEN-treated group showed abnormal hepatic architecture with hepatocytes arranged into solid nodules separated by thick fibrous septa (Fig. 13 G & 13 H). Discussion Hepatocellular carcinoma (HCC) and liver fibrosis are very serious health problems worldwide because of the late detection and extremely complex mechanisms of inflammation and oxidative stress underlying them [ 13 , 14 ]. In this study, we used CCl 4 to induce fibrosis and DEN to induce HCC in rats to study the potential of the markers CD24, CD44, and CD45 as an early diagnostic marker of HCC on top of the accumulated knowledge pertaining to these markers in relation to cancer biology. The results showed high levels of these markers in the HCC group, which were correlated with apoptotic activity, angiogenesis, oxidative stress, and alteration in liver function, thus supporting the diagnostic value. Our results indicated that there were marked changes in liver function indicators among the treated groups. In particular, the treated fibrosis CCl 4 and HCC DEN groups were respectively in higher levels of ALT, AST, and ALP, thus showing hepatic injury and cellular membrane instability, consistent with findings from previous studies [ 15 , 16 ]. Oxidative stress induction in the experimental animals was manifested from the significantly decreased levels of SOD in both the fibrosis and HCC groups. These data are consistent with previous reports of excessive ROS production induced by CCl4 and DEN in the initiation of lipid peroxidation and subsequent oxidative damage [ 17 , 18 ]. The observed markers of oxidative stress underline the pivotal role played by ROS in liver injury and carcinogenesis. Apoptotic marker analysis revealed increased Bax and P53 levels alongside decreased Bcl2 levels in the HCC group, suggesting heightened apoptotic activity. This pattern is indicative of the pro-apoptotic signaling pathways activated in response to severe hepatic injury and tumorigenesis, as supported by the literature [ 19 – 21 ]. Immunoblotting results showed further upregulation of the apoptotic markers Bax and P53 and downregulation of Bcl2 in HCC, indicating an increase in the apoptotic activity. The pattern is consistent with the available literature on the promotion of pro-apoptotic signaling in the liver under the state of severe injury and hepatocarcinogenesis conditions [ 19 – 21 ]. Moreover, the high expression levels of inflammatory cytokines, specifically TNF-α, in fibrosis and HCC groups highlight the inflammatory response associated with liver damage and cancer progression. TNF-α was reported to play a role in stimulating fibrogenesis and hepatocarcinogenesis by augmenting inflammatory and apoptotic pathways [ 22 , 23 ]. These findings are consistent with studies demonstrating increased TNF-α expression in CCl 4 and DEN-induced liver injury models [ 24 , 25 ]. The expression of stem cell markers CD24, CD44, and CD45 was very significantly elevated in the HCC group compared to the control and fibrosis groups. CD24 has been reported as playing an oncogenic role in progress, particularly in cell adhesion to other cells and in forming metastasis. The CD24 molecule is overexpressed in many cancers, among them being hepatocellular carcinoma [ 26 , 27 ]. This study confirms these observations through the high levels of CD24 in the HCC model, which agrees with [ 4 ], who revealed that CD24 participates in the development of liver disease into carcinoma. On the other hand, CD44 is a famous marker associated with cell-cell interactions, migration, and tumor progression [ 28 ]. Our results are in support of previous works indicating that CD44, particularly its standard isoform reported as CD44s, is actively involved in HCC's metastasis process. This is further evidenced by the study of [ 29 ], which found high expression of CD44 associated with advanced tumor states in liver cancer. CD45, also known as Protein Tyrosine Phosphatase Receptor Type C (PTPRC), primarily expressed on leukocytes, has been linked to immune evasion and tumor progression in HCC [ 30 , 31 ]. The findings of the present investigation are in concordance with previous observations by which showed that CD45 mediates tumor immunity within the microenvironment to foster HCC development. It is positively correlated to a high expression of CD24, CD44, and CD45 along with Bcl2, P53, VEGF, SOD, ALT, AST, ALP, and AFP, and is negatively correlated with Bax and TNF-α. This might suggest that their enhanced expression levels are associated with increased angiogenic markers, markers of oxidative stress and liver function markers, but are inversely related to apoptotic and inflammatory markers. As such, these correlations underline the potential role of CD24, CD44, and CD45 as early diagnostic biomarkers for HCC knockdowns because of their involvement in cancer stem cell properties and tumor progression [ 32 – 34 ] Histological analysis further supported these biochemical and molecular findings. The typical features of hepatocyte stress showed the following: ballooning, pyknosis, inflammatory infiltration, and fibrosis. The HCC group showed severe alterations, with solid nodules formation and wide extension of fibrous septa, characteristics of advanced liver cancer. These are in full accordance with previous histopathological descriptions of this model of CCl 4 and DEN-induced hepatic damage [ 32 – 34 ] In conclusion, this study is conducted to point out that CD24, CD44, and CD45 have the diagnostic potential for serving as early biomarkers in HCC due to comprehensive biochemical, apoptotic, angiogenic, oxidative stress, and histological data. These markers would provide great help to clinical application in terms of easy identification, thus helping in undertaking timely treatment among HCC patients. Further studies are highly needed in order to validate such findings in human subjects and have an exploration into the mechanisms associated with these stem cell markers' involvement in liver carcinogenesis. Abbreviations HCC Hepatocellular Carcinoma CCl₄ Carbon Tetrachloride DEN Diethylnitrosamine ALT Alanine Aminotransferase AST Aspartate Aminotransferase ALP Alkaline Phosphatase VEGF Vascular Endothelial Growth Factor SOD Superoxide Dismutase TNF α-Tumor Necrosis Factor-alpha AFP Alpha-Fetoprotein BCL2 B-cell Lymphoma 2 BAX BCL2-associated X protein P53 Tumor Protein P53 ROS Reactive Oxygen Species DLK1 Delta-like 1 Homolog K19 Keratin 19 Lgr5 Leucine-rich Repeat-containing G-protein Coupled Receptor 5 PTPRC Protein Tyrosine Phosphatase Receptor Type C (CD45) Declarations Ethics approval consent to participate Egyptian liver and institute liver hospital ELRIAH approved the experimental procedures with approval code number PHD2019/02. Funding Declaration This manuscript is self-funded, and the authors didn’t receive any external funds. Consent for publication None. Competing interests The authors declare that they have no competing interests Author Contribution Doaa Shoieb: Visualization, Validation, Software, Resources, Methodology, Investigation, Formal analysis, Data curation, Writing - original draft, Writing - review & editing. Mohamed Abd-Elbaset: Investigation, Methodology. Mona S. Gouida: Investigation, Methodology. Ibrahim S. Kamel: Methodology. Adel Abdel-Moneim: Supervision, Software, Resources, Project administration, Methodology, Investigation, Conceptualization. Ayman Hassan: Methodology. Reham Soliman: Investigation, Methodology. Gamal Shiha: Supervision, Project administration, Formal analysis, Data curation Writing - original draft, Writing - review & editing. Ahmed Nabil: Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Conceptualization, Writing - original draft, Writing - review & editing. 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Cellular and Molecular Life Sciences 69:3863–3879 Marotta LL, Almendro V, Marusyk A, Shipitsin M, Schemme J, Walker SR, others, Polyak K (2011) The JAK2/STAT3 signaling pathway is required for growth of CD44 + CD24–stem cell–like breast cancer cells in human tumors. J Clin Invest 121:2723–2735 Mima K, Okabe H, Ishimoto T, Hayashi H, Nakagawa S, others (2012) CD44s regulates the TGF-?-mediated mesenchymal phenotype and is associated with poor prognosis in patients with hepatocellular carcinoma. Cancer Res 72:3414–3423 Yamashita T, Honda M, Nakamoto Y, Baba M, Nio K, Hara Y, Kaneko S (2013) Discrete nature of EpCAM + and CD90 + cancer stem cells in human hepatocellular carcinoma. Hepatology 57:1484–1497 Rheinlander A, Schraven B, Bommhardt U (2018) CD45 in human physiology and clinical medicine. Immunol Lett 196:22–32 Hermiston ML, Xu Z, Weiss A (2003) CD45: A critical regulator of signaling thresholds in immune cells. Annu Rev Immunol 21:107–137 Haraguchi N, Ishii H, Mimori K, et al (2010) CD13 is a therapeutic target in human liver cancer stem cells. Journal of Clinical Investigation 120:3326–3339 Yang ZF, Ho DW, Ng MN, Lau CK, Yu WC, Ngai P, others, Fan ST (2008) Significance of CD90 + cancer stem cells in human liver cancer. Cancer Cell 13:153–166 Yamashita T, Ji J, Budhu A, et al (2009) EpCAM-Positive Hepatocellular Carcinoma Cells Are Tumor-Initiating Cells With Stem/Progenitor Cell Features. Gastroenterology 136:1012–1024 Additional Declarations No competing interests reported. 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. 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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-6886613","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":473023240,"identity":"e098e0e9-7201-4ee0-9784-ef84e6440c47","order_by":0,"name":"Doaa Shoieb","email":"","orcid":"","institution":"Biotechnology and Life Sciences Department, Faculty of Postgraduate Studies for Advanced Sciences (PSAS), Beni-Suef University, Salah Salem St, 62511.","correspondingAuthor":false,"prefix":"","firstName":"Doaa","middleName":"","lastName":"Shoieb","suffix":""},{"id":473023241,"identity":"5c359ff0-4868-461c-a166-880b352185df","order_by":1,"name":"Mohamed Abd-Elbaset","email":"","orcid":"","institution":"Department of pharmacology and toxicology, Faculty of pharmacy, El Saleheya El Gadida Univesity","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"","lastName":"Abd-Elbaset","suffix":""},{"id":473023242,"identity":"70d592a9-58ce-4c83-a869-f8f3b0e74dc8","order_by":2,"name":"Mona S. Gouida","email":"","orcid":"","institution":"Mansoura University children hospital (MUCH), Genetics unit, Faculty of Medicine, Mansoura University.","correspondingAuthor":false,"prefix":"","firstName":"Mona","middleName":"S.","lastName":"Gouida","suffix":""},{"id":473023243,"identity":"e585f6ff-5829-4ca7-bd10-07ef49a9808c","order_by":3,"name":"Ibrahim S. Kamel","email":"","orcid":"","institution":"Faculty of Applied Health Sciences Technology, East Port Said National University.","correspondingAuthor":false,"prefix":"","firstName":"Ibrahim","middleName":"S.","lastName":"Kamel","suffix":""},{"id":473023244,"identity":"028af0c6-45ff-4e09-8c60-7014cd9750df","order_by":4,"name":"Adel Abdel-Moneim","email":"","orcid":"","institution":"Molecular Physiology Division, Faculty of Science, Beni-Suef University.","correspondingAuthor":false,"prefix":"","firstName":"Adel","middleName":"","lastName":"Abdel-Moneim","suffix":""},{"id":473023245,"identity":"21cc18e5-b824-43b0-b8da-40aeb6265a92","order_by":5,"name":"Ayman Hassan","email":"","orcid":"","institution":"Egyptian Liver Research Institute and Hospital (ELRIAH), Sherbin.","correspondingAuthor":false,"prefix":"","firstName":"Ayman","middleName":"","lastName":"Hassan","suffix":""},{"id":473023246,"identity":"22bf6e18-58c1-4a47-8760-8aad98037fbc","order_by":6,"name":"Reham Soliman","email":"","orcid":"","institution":"Egyptian Liver Research Institute and Hospital (ELRIAH), Sherbin.","correspondingAuthor":false,"prefix":"","firstName":"Reham","middleName":"","lastName":"Soliman","suffix":""},{"id":473023248,"identity":"2ff8555e-4cc2-4ebc-8e31-ce3fff024a55","order_by":7,"name":"Gamal Shiha","email":"","orcid":"","institution":"Egyptian Liver Research Institute and Hospital (ELRIAH), Sherbin.","correspondingAuthor":false,"prefix":"","firstName":"Gamal","middleName":"","lastName":"Shiha","suffix":""},{"id":473023249,"identity":"808cd30f-d39f-4811-aebc-b0e3d27542f5","order_by":8,"name":"Ahmed Nabil","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYDCCAwwMzAwGFgxszIyNj8EizMwNxGiRYOBjbz5szMBgAOQyEqOFQYJBjudYmjRYCwMBLXy3zx78XFAgwcAmkWNWXVDxJ5q/HajlR8U2nFokz+UlS88wgGi5PeOMQe6Mw4wNjD1nbuPUYnCGx0CaB6aFt80gtwGohZmxDa8W498wLcUgLfOJ0GIGsQXofWaQlg2EtEgCtViD/QIMZGmeM8a5G4FaDuLzCx/QYbcL/tgwyDczNn7mqZDLnXf+8MEHPypwa4GB+gZk3gGC6kfBKBgFo2AU4AUATA9O1/HBqlAAAAAASUVORK5CYII=","orcid":"","institution":"Biotechnology and Life Sciences Department, Faculty of Postgraduate Studies for Advanced Sciences (PSAS), Beni-Suef University, Salah Salem St, 62511.","correspondingAuthor":true,"prefix":"","firstName":"Ahmed","middleName":"","lastName":"Nabil","suffix":""}],"badges":[],"createdAt":"2025-06-13 09:08:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6886613/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6886613/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85174461,"identity":"c9082713-6eb5-4f1f-93b7-1a5d9729db16","added_by":"auto","created_at":"2025-06-23 06:21:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":91537,"visible":true,"origin":"","legend":"\u003cp\u003eBiochemical analysis of liver function markers in different rat groups (Control, Olive Oil, Fibrosis, HCC). \u003cstrong\u003e(A)\u003c/strong\u003e ALT: Alanine aminotransferase levels\u003cstrong\u003e. (B)\u003c/strong\u003eAST: Aspartate aminotransferase levels.\u003cstrong\u003e (C)\u003c/strong\u003e ALP: Alkaline phosphatase levels. Values are presented as mean ± SE. Letters indicate significant differences: \u003cstrong\u003ea\u003c/strong\u003e: significantly different from Control; \u003cstrong\u003eb\u003c/strong\u003e: significantly different from Olive Oil; \u003cstrong\u003eab\u003c/strong\u003e: significantly different from both Control and Olive Oil groups (p \u0026lt; 0.0001). The differences between groups were analyzed using a one-way ANOVA test followed by Tukey HSD post hoc analysis.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6886613/v1/c4b2422003514fc0bb989191.png"},{"id":85174457,"identity":"6dabc90f-4ea8-43ee-801c-25f55ed98a28","added_by":"auto","created_at":"2025-06-23 06:21:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":109471,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of oxidative stress and angiogenic markers in different rat groups (Control, Olive Oil, Fibrosis, HCC). \u003cstrong\u003e(A)\u003c/strong\u003e SOD: Superoxide dismutase levels. \u003cstrong\u003e(B)\u003c/strong\u003eVEGF: Vascular endothelial growth factor levels. Values are presented as mean ± SE. Letters indicate significant differences: \u003cstrong\u003ea\u003c/strong\u003e: significantly different from Control; \u003cstrong\u003eb\u003c/strong\u003e: significantly different from Olive Oil; \u003cstrong\u003eab\u003c/strong\u003e: significantly different from both Control and Olive Oil groups (p \u0026lt; 0.0001). The differences between groups were analyzed using a one-way ANOVA test followed by Tukey HSD post hoc analysis.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6886613/v1/b96931f24babc71135be43c6.png"},{"id":85174476,"identity":"0e555b97-dc67-4a74-868f-97f1832d1bc1","added_by":"auto","created_at":"2025-06-23 06:21:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":137835,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of inflammatory and cancer-associated fibroblast markers in different rat groups (Control, Olive Oil, Fibrosis, HCC). \u003cstrong\u003e(A)\u003c/strong\u003e TNF-α: Tumor necrosis factor-alpha levels. \u003cstrong\u003e(B)\u003c/strong\u003e AFP: Alpha-fetoprotein levels. Values are presented as mean ± SE. Letters indicate significant differences: \u003cstrong\u003ea\u003c/strong\u003e: significantly different from Control; \u003cstrong\u003eb\u003c/strong\u003e: significantly different from Olive Oil; \u003cstrong\u003eab\u003c/strong\u003e: significantly different from both Control and Olive Oil groups (p \u0026lt; 0.0001). The differences between groups were analyzed using a one-way ANOVA test followed by Tukey HSD post hoc analysis.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6886613/v1/1e3d3daeb2011ecbed146466.png"},{"id":85174491,"identity":"9da6ea60-ec69-43c5-aac9-1de6f91023f1","added_by":"auto","created_at":"2025-06-23 06:21:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":322164,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe representative expression of BCl2 in the different rat groups (Control, olive oil, fibrosis, HCC) by Flow Cytometry.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6886613/v1/d96b6f39a88df2685cb69bc2.png"},{"id":85174460,"identity":"128fa541-455a-45d8-a649-ec72deaca272","added_by":"auto","created_at":"2025-06-23 06:21:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":165812,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe expression of P53 in the different rat groups (Control, olive oil, fibrosis, HCC) by Western blot. \u003c/strong\u003e(A) Representative Western blot images showing the expression of P53 and β-Actin (loading control). (B) Quantitative analysis of P53 expression in different rat groups, expressed as a percentage.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6886613/v1/b19e23fd1b3224bc7a6e5381.png"},{"id":85174465,"identity":"d99e22be-71cf-49c5-a830-cab97129cc86","added_by":"auto","created_at":"2025-06-23 06:21:21","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":105080,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of apoptotic markers in different rat groups (Control, Olive Oil, Fibrosis, HCC). \u003cstrong\u003e(A)\u003c/strong\u003e BCL2: B-cell lymphoma 2 levels. \u003cstrong\u003e(B)\u003c/strong\u003e BAX: BCL2-associated X protein levels.\u003cstrong\u003e (C)\u003c/strong\u003e P53: Tumor protein P53 levels. Values are presented as mean ± SE. Letters indicate significant differences: \u003cstrong\u003ea\u003c/strong\u003e: significantly different from Control; \u003cstrong\u003eb\u003c/strong\u003e: significantly different from Olive Oil; \u003cstrong\u003eab\u003c/strong\u003e: significantly different from both Control and Olive Oil groups (p \u0026lt; 0.0001). The differences between groups were analyzed using a one-way ANOVA test followed by Tukey HSD post hoc analysis.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6886613/v1/aa729f0b83aec92abb0e92fc.png"},{"id":85174458,"identity":"9a819c02-736d-4ca1-ba88-a736b5e3b0e9","added_by":"auto","created_at":"2025-06-23 06:21:21","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":262158,"visible":true,"origin":"","legend":"\u003cp\u003eThe representative expression of CD45 in the different rat groups (Control, olive oil, fibrosis, HCC).\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6886613/v1/2dc47ade80d424ae351dc6f1.png"},{"id":85175812,"identity":"ab75262e-bcf2-44ee-80d7-3dd6a7703727","added_by":"auto","created_at":"2025-06-23 06:29:21","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":245862,"visible":true,"origin":"","legend":"\u003cp\u003eThe representative expression of CD44 in the different rat groups (Control, olive oil, fibrosis, HCC).\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6886613/v1/5070504d1d79433145d466c7.png"},{"id":85174484,"identity":"0191538f-6d91-4c56-8a71-6144e76eebcd","added_by":"auto","created_at":"2025-06-23 06:21:22","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":245289,"visible":true,"origin":"","legend":"\u003cp\u003eThe representative expression of CD24 in the different rat groups (Control, olive oil, fibrosis, HCC).\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-6886613/v1/bfb52b00b5ad4b33a7f353d0.png"},{"id":85175818,"identity":"25b76ad7-412f-4d9a-9e26-d413dcf4d114","added_by":"auto","created_at":"2025-06-23 06:29:22","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":96716,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical representation of flow cytometry analysis of stem cell markers in different rat groups (Control, Olive Oil, Fibrosis, HCC).\u003cstrong\u003e(A) \u003c/strong\u003eCD45: Percentage of CD45+ cells. \u003cstrong\u003e(B) \u003c/strong\u003eCD44: Percentage of CD44+ cells.\u003cstrong\u003e (C) \u003c/strong\u003eCD24: Percentage of CD24+ cells. Values are presented as mean ± SE. Letters indicate significant differences: \u003cstrong\u003ea:\u003c/strong\u003e different from Control; \u003cstrong\u003eb:\u003c/strong\u003e different from Olive Oil; \u003cstrong\u003eab:\u003c/strong\u003e different from both Control and Olive Oil groups (p \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-6886613/v1/3d4fbc0c4fb3336b311e7386.png"},{"id":85174490,"identity":"511bf27b-2dd7-4b03-a926-241d15f6e5e4","added_by":"auto","created_at":"2025-06-23 06:21:23","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":62159,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation of stem cell markers with various biochemical parameters in different rat groups. (A) CD24, (B) CD44, and (C) CD45. Positive correlations were observed for BCL2, P53, VEGF, SOD, ALT, AST, ALP, and AFP; negative correlations were obtained in BAX and TNF-α. \u003cstrong\u003eBCL2\u003c/strong\u003e: B-cell lymphoma 2; \u003cstrong\u003eP53:\u003c/strong\u003e tumor protein p53; \u003cstrong\u003eVEGF:\u003c/strong\u003evascular endothelial growth factor; \u003cstrong\u003eSOD\u003c/strong\u003e: superoxide dismutase; \u003cstrong\u003eALT:\u003c/strong\u003ealanine aminotransferase; \u003cstrong\u003eAST:\u003c/strong\u003e aspartate aminotransferase; \u003cstrong\u003eALP:\u003c/strong\u003ealkaline phosphatase; and \u003cstrong\u003eAFP:\u003c/strong\u003e alpha-fetoprotein; \u003cstrong\u003eBAX:\u003c/strong\u003e Bcl-2-associated X protein and \u003cstrong\u003eTNF-α:\u003c/strong\u003e tumor necrosis factor-alpha.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-6886613/v1/10b75a2b6339c75c7d83d8ef.png"},{"id":85176379,"identity":"85136538-dd87-411e-8587-16dda7c55579","added_by":"auto","created_at":"2025-06-23 06:37:22","extension":"jpg","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":600265,"visible":true,"origin":"","legend":"\u003cp\u003ePhotomicrographs of rat liver sections stained with Hematoxylin and Eosin (H\u0026amp;E). \u003cstrong\u003eA \u0026amp; B:\u003c/strong\u003e Control group showing normal hepatic architecture with hepatocytes arranged in cords radiating from the central veins to the portal areas. \u003cstrong\u003eC \u0026amp; D:\u003c/strong\u003e Olive oil group exhibiting almost normal liver architecture with congested interhepatic sinusoids. \u003cstrong\u003eE \u0026amp; F:\u003c/strong\u003e CCl\u003csub\u003e4\u003c/sub\u003e group displaying hepatocyte stress, ballooning of the cytoplasm, pyknosis of the nuclei, inflammatory cell infiltration, and fibroblast and collagen fiber bands separating the hepatic lobules. \u003cstrong\u003eG \u0026amp; H:\u003c/strong\u003e DEN-treated group showing abnormal hepatic architecture with hepatocytes arranged into solid nodules without central veins, surrounded by thick neuro-inflammatory zones containing fibrous tissue infiltrated with leukocytes and hemosiderin-laden macrophages. (H\u0026amp;E, A, C, E \u0026amp; G X 100; B, D, F \u0026amp; H X 400)\u003c/p\u003e","description":"","filename":"12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6886613/v1/29f6e95c3768bed812e79948.jpg"},{"id":85174488,"identity":"03d477e8-dbde-4b7a-b8f9-7757fd5425db","added_by":"auto","created_at":"2025-06-23 06:21:23","extension":"jpg","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":527318,"visible":true,"origin":"","legend":"\u003cp\u003ePhotomicrographs of rat liver sections stained with Masson's Trichrome. \u003cstrong\u003eA \u0026amp; B: \u003c/strong\u003eControl group showing normal distribution of fibrous tissue surrounding the central vein. \u003cstrong\u003eC \u0026amp; D: \u003c/strong\u003eOlive oil group showing minimal expression of fibrous tissue bands. \u003cstrong\u003eE \u0026amp; F: \u003c/strong\u003eCCl4 group displaying extensive fibrous bands separating the hepatic lobules. \u003cstrong\u003eG \u0026amp; H:\u003c/strong\u003e DEN-treated group showing abnormal hepatic architecture with hepatocytes arranged into solid nodules separated by thick fibrous septa.\u003c/p\u003e","description":"","filename":"13.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6886613/v1/a429f6f70d57cd6a8b37dffc.jpg"},{"id":105717286,"identity":"1e7eabea-3b2d-48e2-a033-21ca47e43e19","added_by":"auto","created_at":"2026-03-30 08:59:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4233817,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6886613/v1/5b5286cd-fa2a-4d8c-897d-8b4f5f8f71d0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of circulating CD24, CD44, and CD45 stem cell markers as novel early diagnostic tools for hepatocellular carcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe liver is constantly subjected to numerous external and internal elements, including viral infections, excessive alcohol consumption, pharmaceutical agents, toxic chemicals, dietary fats, and metabolic byproducts. These factors can inflict damage on liver tissue, triggering inflammatory responses and contributing to the progressive deterioration of liver function [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. If the liver injury is persisted for a long time, it developed into chronic liver diseases starting with fibrosis then cirrhosis and ended by hepatocellular carcinoma [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNumerous chemicals can cause liver injury and reported to induce hepatotoxicity such as carbon tetrachloride (CCl\u003csub\u003e4\u003c/sub\u003e), chloroform (CHCl\u003csub\u003e3\u003c/sub\u003e) and iodoform (CHI\u003csub\u003e3\u003c/sub\u003e), Bromobenzene, Ethionine and Diethylnitrosamine. CCl4 was approved to induce liver injury in many species. Its toxic effects depend on the dose and duration of exposure [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. CCl\u003csub\u003e4\u003c/sub\u003e is metabolized in the liver to the trichloromethyl radical (CCl\u003csub\u003e3\u003c/sub\u003e*). Exposure to the CCl3* radical can disrupt critical biological processes. Its reactivity with lipids, proteins, and nucleic acids has been linked to disruptions in lipid metabolism, lowering in protein quantities, triggering mutations in DNA and progression into HCC [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNitrosamines are carcinogens present in smoked pickled fish, nitrite-cured meats, agricultural chemicals, and alcoholic beverages or tobacco smoke. Diethylnitrosamine (DEN) is one of the most significant hepatotoxicants and hepatocarcinogens [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The biotransformation of DEN results in the accumulation of reactive oxygen species (ROS), a key factor in the oxidative damage observed in DNA and other cellular macromolecules. This compound also impairs the activity of various enzymes involved in DNA repair processes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe liver possesses the capacity to regenerate the parenchymal tissue loss as a result of infection or injury. This is done through the increase in the population either of the hepatocytes or the liver progenitor cells when the extensive damage cannot enable the hepatocytes to feedback by participating in the proliferative response. Under normal conditions, stem cells remain in a dormant state within their niche. When activated, these stem cells divide, producing offspring that retain the ability to self-renew and others that can proliferate and differentiate into the specific cell types needed to repair the tissue [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Hepatic stem cells characterized by expression of CD133, CD44, CD45, CD90, epithelial cell adhesion molecule (EpCAM), CD47, CD34, C-kit, CD13, CD24, oval cell marker (OV6), DLK1, K19, and Lgr5\u0026thinsp;+\u0026thinsp;on their surfaces [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Hence, in this study, we will assess some stem cell markers (CD24, CD44, and CD45) as a potential early diagnostic tools for hepatocellular carcinoma.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnimals\u003c/h2\u003e \u003cp\u003eAdult male albino Wistar rats, weighing between 130\u0026ndash;150 g, were sourced from the Merck animal facility at the Faculty of Medicine, Mansoura University, Egypt. They were housed under standard laboratory conditions in clean, well-ventilated plastic cages, with free access to a standard commercial pellet diet and water.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eChemicals\u003c/h3\u003e\n\u003cp\u003eThe chemicals used in the study included: CCl\u003csub\u003e4\u003c/sub\u003e (Sigma Chemicals, St. Louis, MO), N-Nitrosodiethylamine (DEN) solution (Sigma Chemicals, St. Louis, MO), absolute ethanol and xylene (Supelco Inc., Sigma-Aldrich, USA), eosin yellow (Alpha Chemika, India), hematoxylin solution (Techno Pharmchem, India), and Masson's trichrome solution (Techno Pharmchem, India).\u003c/p\u003e\n\u003ch3\u003eExperimental Design\u003c/h3\u003e\n\u003cp\u003eThe rats were divided into four groups, each consisting of 10 rats, and were administered olive oil and CCl4 for 7 weeks, followed by DEN for 10 weeks. Group 1 was the control and hence was not treated at all. In group 2, olive oil was injected intraperitoneally at a volume of 0.1 ml/100g twice a week at regular intervals [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Group 3: (CCl\u003csub\u003e4\u003c/sub\u003e) receiving a 1:1 mixture of CCl\u003csub\u003e4\u003c/sub\u003e with olive oil, at the dose of 0.2 ml/100g, twice a week, at regular intervals [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Group 4: received in their drinking water 0.01% DEN for a period of 8 weeks. Subsequently, they were treated with normal denial-containing water [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eSample Collection and Preparation\u003c/h3\u003e\n\u003cp\u003eBlood samples were obtained by laparotomy and direct cardiac puncture. Following collection, blood samples were incubated at 37\u0026deg;C for 30 minutes to facilitate complete clot formation. Subsequently, serum was obtained by centrifugation at 3000 rpm for 15 minutes. The serum was used for the estimation of hepatic function parameters, fibrosis and HCC markers. Blood aliquots were then put into EDTA-containing tubes for immediate hematological assessment. A piece of the liver tissue from each rat was fixed in 10% buffered formalin for pathological examination.\u003c/p\u003e\n\u003ch3\u003eBiochemical Parameters\u003c/h3\u003e\n\u003cp\u003eLiver function was determined via measuring alanine aminotransferase (ALT) and aspartate aminotransferase (AST), and alkaline phosphatase (ALP) using COBAS INTEGRA systems. ALT was assessed with the ALTL kit, Test ID 0-495, by an IFCC kinetic method monitoring NADH oxidation [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. AST was assessed using the ASTL kit, Test ID 0-494, based on the detection of oxaloacetate formation and its reaction with NADH [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. ALP levels were assessed using the ALP2L kit (Test ID 0-550), employing a colorimetric assay that measures the cleavage of p-nitrophenyl phosphate to p-nitrophenol [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Additionally, alpha-fetoprotein (AFP), a marker associated with cancer-associated fibroblasts, was measured using the Rat AFP ELISA Kit (Catalog No. CSB-E08281r, Cusabio) via a quantitative sandwich enzyme immunoassay, with absorbance measured at 450 nm. Oxidative stress was gauged by measuring SOD1 levels using a NO ELISA kit (Catalog No. CSB-EL022397RA, Cusabio) through a sandwich ELISA method, with absorbance also determined at 450 nm.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eWestern Blotting\u003c/h2\u003e \u003cp\u003eProteins were isolated from blood samples using TriFast reagent, which facilitated the concurrent extraction of RNA, DNA, and proteins. The homogenized samples underwent phase separation, where RNA was retrieved from the aqueous phase, DNA from the interphase, and proteins from the phenol phase. Proteins were then precipitated, washed, and dissolved in SDS.\u003c/p\u003e \u003cp\u003eFor electrophoresis, various stock solutions, including acrylamide-bis-acrylamide, SDS, and Tris-HCl buffers, were prepared. The proteins were resolved on a 12% slab gel with a 4% stacking gel, stained with Coomassie blue, and analyzed using a GelDoc system equipped with TotalLab software.\u003c/p\u003e \u003cp\u003eTransfer of proteins from SDS-PAGE gels to Hybond\u0026trade; nylon membranes was performed using a TE62 Standard Transfer Tank. Following blocking with a nonfat dry milk solution, the membranes were incubated overnight with primary antibodies, washed, and then incubated with HRP-conjugated secondary antibodies for visualization of protein bands.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFlow Cytometry Analysis\u003c/h3\u003e\n\u003cp\u003ePeripheral blood mononuclear cells were isolated by initially diluting the blood with an equal volume of PBS, followed by careful layering onto Ficol Hypaque and centrifugation at 400g for 30 minutes at 20\u0026deg;C. Cells were collected from the resulting interface, thoroughly washed, and then resuspended in PBS-BSA to achieve a final concentration of at least 1 x 10\u003csup\u003e7\u003c/sup\u003e cells/mL. For the staining procedure, 1 x 10\u003csup\u003e6\u003c/sup\u003e cells were incubated with 10 \u0026micro;L of conjugated antibodies for 30 minutes at 4\u0026deg;C in the dark. Following incubation, the cells were washed, resuspended in PBS, and fixed using 4% paraformaldehyde in PBS. The flow cytometric analysis was performed using an Accuri C6 flow cytometer (Becton Dickinson, USA).\u003c/p\u003e\n\u003ch3\u003eEstimation of hepatic stem cell markers\u003c/h3\u003e\n\u003cp\u003eStem cell markers, such as CD45, CD24, and CD44 were assessed to identify specific cellular characteristics. The expression of \u003cb\u003eCD45\u003c/b\u003e was assessed using PE Rat Anti-Mouse CD45 antibody (BD Biosciences, Cat. No. 561087). \u003cb\u003eCD24\u003c/b\u003e was measured using PE Rat Anti-Mouse CD24 antibody (BD Biosciences, Cat. No. 553262). \u003cb\u003eCD44\u003c/b\u003e was quantified using PE Rat Anti-Mouse CD44 antibody (BD Biosciences, Cat. No. 561860).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eApoptotic Markers\u003c/h2\u003e \u003cp\u003eApoptotic markers including Bcl2, Bax, and P53 were measured to understand the apoptotic processes in the cells. \u003cb\u003eBcl2\u003c/b\u003e: Measured using the Bcl-2 Monoclonal Antibody (10C4), FITC, Invitrogen kit (Cat. No. 11-6992-42) via flow cytometry (Accuri C6, Becton Dickinson, USA). \u003cb\u003eBax\u003c/b\u003e: Quantified using the Bax ELISA kit (Cat. No. MBS2512405) based on the Sandwich-ELISA principle, with absorbance measured at 450 nm. \u003cb\u003eP53\u003c/b\u003e: Analyzed using the Human/Mouse/Rat p53 Antibody kit (Cat. No. MAB1355) via western blotting.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAngiogenic Marker\u003c/h2\u003e \u003cp\u003eTo assess angiogenic activity, VEGF levels were measured using a VEGF ELISA kit (Catalog No. RRV00, R\u0026amp;D Systems) following a quantitative sandwich enzyme immunoassay technique, with absorbance recorded at 450 nm using a microplate reader (Stat Fax 4700, Awareness Technology, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCytokines\u003c/h2\u003e \u003cp\u003eCytokine analysis involved quantifying TNF-α levels using the Rat TNF alpha ELISA Kit (Catalog No. ab236712, Abcam), employing the sandwich ELISA technique, with data analyzed through a standard curve to determine cytokine concentrations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eHistological Studies\u003c/h2\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003ePreparation of Sections\u003c/h2\u003e \u003cp\u003eLiver samples were preserved in 10% buffered formalin for a duration of 48 hours. Following fixation, the tissues underwent a dehydration process using increasing concentrations of ethyl alcohol, were cleared with xylene, and then embedded in paraplast wax. Thin sections, measuring 5 \u0026micro;m in thickness, were sliced and subsequently stained for detailed observation under a light microscope.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eHaematoxylin and Eosin (H\u0026amp;E) Staining\u003c/h2\u003e \u003cp\u003eH\u0026amp;E staining was performed to observe the general histological structure. Sections were dewaxed, hydrated, and stained with hematoxylin for nuclear visualization, followed by eosin Y for cytoplasmic staining. This method provides a blue color for nuclei and a red color for cytoplasm, facilitating the differentiation of cellular components.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eMasson's Trichrome Staining\u003c/h2\u003e \u003cp\u003eMasson's Trichrome staining was used to differentiate cellular elements from connective tissue. The procedure involved staining nuclei with Weigert\u0026rsquo;s hematoxylin, followed by Biebrich scarlet-acid fuchsin for acidophilic components. Phosphomolybdic acid was used to differentiate the stain, and aniline blue was applied to stain collagen fibers blue, with a red background and black-stained nuclei. The sections were then dehydrated, cleared, and mounted for examination.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eBiochemical Analysis\u003c/h2\u003e \u003cp\u003eThe liver enzyme levels exhibited notable changes across different treatment groups. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(A) and (B)\u003c/b\u003e, ALT and AST levels were significantly lower in the Olive Oil group, while significantly higher in the fibrosis (CCl\u003csub\u003e4\u003c/sub\u003e) and HCC (DEN) groups compared to controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). ALP levels followed a similar pattern, with significant increases in the fibrosis and HCC groups and a decrease in the Olive Oil group compared to controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(C))\u003c/b\u003e. These results indicate distinct liver enzyme alterations due to the different treatments.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBiochemical parameters of liver function (ALT, AST, ALP) in different groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eALT (U/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAST (U/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eALP (U/L)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123\u0026thinsp;\u0026plusmn;\u0026thinsp;6.976\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e110.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOlive Oil\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u0026thinsp;\u0026plusmn;\u0026thinsp;8.515\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58.40\u0026thinsp;\u0026plusmn;\u0026thinsp;13.09\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFibrosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113.2\u0026thinsp;\u0026plusmn;\u0026thinsp;40.2\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e344.6\u0026thinsp;\u0026plusmn;\u0026thinsp;176.0\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e274.8\u0026thinsp;\u0026plusmn;\u0026thinsp;98.99\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHCC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105.4\u0026thinsp;\u0026plusmn;\u0026thinsp;22.2\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e260.4\u0026thinsp;\u0026plusmn;\u0026thinsp;147.6\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e277.1\u0026thinsp;\u0026plusmn;\u0026thinsp;117.2\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe values are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error (SE). The differences between groups were analyzed using a one-way ANOVA test followed by Tukey HSD post hoc analysis. Letters (a, b, ab) indicate significant differences: \u003cb\u003ea\u003c/b\u003e: Significantly different from the Control group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); \u003cb\u003eb\u003c/b\u003e: Significantly different from the Olive Oil group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); \u003cb\u003eab\u003c/b\u003e: Significantly different from both Control and Olive Oil groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eAngiogenic and Oxidative Stress Markers\u003c/h2\u003e \u003cp\u003eThe levels of superoxide dismutase 1 (\u003cb\u003eSOD1\u003c/b\u003e), a marker of oxidative stress, and vascular endothelial growth factor (\u003cb\u003eVEGF\u003c/b\u003e), a key angiogenic factor, were measured in different rat groups (Control, Olive Oil, Fibrosis, HCC). As shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(A) and (B), s\u003c/b\u003eignificant differences were observed in the levels of these markers across the groups, with VEGF and SOD1 levels indicating distinct alterations in oxidative stress and angiogenic activity due to different treatments (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLevels of VEGF and SOD in different groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVEGF (pg/ml)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSOD (U/ml)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.736\u0026thinsp;\u0026plusmn;\u0026thinsp;2.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e159.3\u0026thinsp;\u0026plusmn;\u0026thinsp;23.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOlive Oil\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.246\u0026thinsp;\u0026plusmn;\u0026thinsp;1.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123.6\u0026thinsp;\u0026plusmn;\u0026thinsp;16.23\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFibrosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.832\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3469\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.48\u0026thinsp;\u0026plusmn;\u0026thinsp;13.53\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHCC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.350\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3371\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.07\u0026thinsp;\u0026plusmn;\u0026thinsp;8.985\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe values are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error (SE). The differences between groups were analyzed using a one-way ANOVA test followed by Tukey HSD post hoc analysis. Letters (a, b, ab) indicate significant differences: \u003cb\u003ea\u003c/b\u003e: Significantly different from the Control group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); \u003cb\u003eb\u003c/b\u003e: Significantly different from the Olive Oil group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); \u003cb\u003eab\u003c/b\u003e: Significantly different from both Control and Olive Oil groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eInflammatory Cytokines and Cancer-Associated Fibroblast Markers\u003c/h2\u003e \u003cp\u003eThe VEGF and TNF-α levels were quantified to assess angiogenic and inflammatory responses. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(A) and (B)\u003c/b\u003e, both markers were significantly elevated in the Fibrosis and HCC groups, reflecting increased angiogenesis and inflammation (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLevels of TNF-α and AFP in different groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTNF-α (pg/ml)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAFP (pg/ml)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e290.0\u0026thinsp;\u0026plusmn;\u0026thinsp;34.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.74\u0026thinsp;\u0026plusmn;\u0026thinsp;2.756\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOlive Oil\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e369.0\u0026thinsp;\u0026plusmn;\u0026thinsp;36.55\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e147.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.341\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFibrosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e660.0\u0026thinsp;\u0026plusmn;\u0026thinsp;42.92\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e437.4\u0026thinsp;\u0026plusmn;\u0026thinsp;29.82\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHCC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e758.6\u0026thinsp;\u0026plusmn;\u0026thinsp;115.21\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e621.9\u0026thinsp;\u0026plusmn;\u0026thinsp;12.08\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe values are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error (SE). The differences between groups were analyzed using a one-way ANOVA test followed by Tukey HSD post hoc analysis. Letters (a, b, ab) indicate significant differences: \u003cb\u003ea\u003c/b\u003e: Significantly different from the Control group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); \u003cb\u003eb\u003c/b\u003e: Significantly different from the Olive Oil group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); \u003cb\u003eab\u003c/b\u003e: Significantly different from both Control and Olive Oil groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eApoptotic Markers\u003c/h2\u003e \u003cp\u003eThe assessment of apoptotic markers Bcl2, Bax, and P53 indicated alterations in apoptosis regulation across the groups. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, elevated Bax levels (measured by ELISA) and P53 levels (measured by Western blot) coupled with reduced Bcl2 levels (measured by Flow Cytometry) were observed in the HCC group, suggesting increased apoptotic activity (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExpression levels of apoptotic markers (BCL2, BAX, P53) in different groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBCL2 (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBAX (pg/ml)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP53 (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.518\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5322\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOlive Oil\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.280\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4764\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFibrosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7650\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHCC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4976\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe values are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error (SE). The differences between groups were analyzed using a one-way ANOVA test followed by Tukey HSD post hoc analysis. Letters (a, b, ab) indicate significant differences: \u003cb\u003ea\u003c/b\u003e: Significantly different from the Control group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); \u003cb\u003eb\u003c/b\u003e: Significantly different from the Olive Oil group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); \u003cb\u003eab\u003c/b\u003e: Significantly different from both Control and Olive Oil groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eStem Cell Markers: CD24, CD44, CD45\u003c/h2\u003e \u003cp\u003eFlow cytometry was employed to determine the expression of stem cell markers CD24, CD44, and CD45 in control, olive oil, fibrosis, and HCC rat groups (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). The percentage of positive cells varied significantly across the groups. CD45\u0026thinsp;+\u0026thinsp;cells were present at 22.2% (control), 15.6% (olive oil), 55.1% (fibrosis), and 74.6% (HCC). Compared to the control, CD45 expression was significantly lower in the olive oil group and significantly higher in the fibrosis and HCC groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). CD44\u0026thinsp;+\u0026thinsp;cells were detected at 12.6% (control), 24.2% (olive oil), 38.1% (fibrosis), and 84.6% (HCC), with all treatment groups exhibiting significantly increased expression (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Similarly, CD24\u0026thinsp;+\u0026thinsp;cells were found at 13.9% (control), 25.5% (olive oil), 40.7% (fibrosis), and 66.9% (HCC), with significant increases in all treatment groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExpression levels of CD24, CD44, and CD45 in different groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCD24\u003csup\u003e+\u003c/sup\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCD44\u003csup\u003e+\u003c/sup\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCD45\u003csup\u003e+\u003c/sup\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOlive Oil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFibrosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe values are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error (SE). The differences between groups were analyzed using a one-way ANOVA test followed by Tukey HSD post hoc analysis. Letters (a, b, ab) indicate significant differences: \u003cb\u003ea\u003c/b\u003e: Significantly different from the Control group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); \u003cb\u003eb\u003c/b\u003e: Significantly different from the Olive Oil group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); \u003cb\u003eab\u003c/b\u003e: Significantly different from both Control and Olive Oil groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation Analysis of Stem Cell Markers with Biochemical Parameters\u003c/h2\u003e \u003cp\u003eThe correlation analysis of stem cell markers (CD24, CD44, CD45) with various biochemical parameters was conducted to assess their interrelationships. Significant correlations were observed for each marker, as detailed in Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e: CD24 (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eA), CD44 (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eB), and CD45 (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eC). The correlation analysis of stem cell markers CD24, CD44, and CD45 revealed similar patterns. Positive correlations were observed with BCL2, P53, VEGF, SOD, ALT, AST, ALP, and AFP for all three markers. In contrast, negative correlations were identified with BAX and TNF-α. These findings suggest that higher expression of stem cell markers is associated with increased levels of angiogenic, oxidative stress, and liver function markers, while markers related to apoptosis and inflammation exhibit inverse relationships.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eHistological Studies\u003c/h2\u003e \u003cp\u003eMicroscopic examination of \u003cb\u003eHematoxylin and Eosin (H\u0026amp;E)\u003c/b\u003e-stained liver tissue from the control group demonstrated normal hepatic architecture. Hepatocytes were observed to be organized in characteristic cords extending radially from the central veins towards the portal triads (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eA \u0026amp; \u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eB). The olive oil group showed almost normal liver architecture with congested interhepatic sinusoids (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eC \u0026amp; \u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eD). The CCl4 group exhibited hepatocyte stress, ballooning of the cytoplasm, pyknosis of the nuclei, inflammatory cell infiltration, and fibroblast and collagen fiber bands separating the hepatic lobules (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eE \u0026amp; \u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eF). The DEN-treated group showed abnormal hepatic architecture with hepatocytes arranged into solid nodules which were surrounded by pronounced neuro-inflammatory zones containing fibrous tissue, infiltrated with leukocytes and hemosiderin-laden macrophages (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eG \u0026amp; \u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003eMasson's Trichrome staining further confirmed these observations. The control group displayed normal distribution of fibrous tissue surrounding the central vein (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eA \u0026amp; \u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eB). The olive oil group showed minimal expression of fibrous tissue bands (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eC \u0026amp; \u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eD). The CCl4 group exhibited extensive fibrous bands separating the hepatic lobules (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eE \u0026amp; \u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eF). The DEN-treated group showed abnormal hepatic architecture with hepatocytes arranged into solid nodules separated by thick fibrous septa (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eG \u0026amp; \u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eHepatocellular carcinoma (HCC) and liver fibrosis are very serious health problems worldwide because of the late detection and extremely complex mechanisms of inflammation and oxidative stress underlying them [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In this study, we used CCl\u003csub\u003e4\u003c/sub\u003e to induce fibrosis and DEN to induce HCC in rats to study the potential of the markers CD24, CD44, and CD45 as an early diagnostic marker of HCC on top of the accumulated knowledge pertaining to these markers in relation to cancer biology. The results showed high levels of these markers in the HCC group, which were correlated with apoptotic activity, angiogenesis, oxidative stress, and alteration in liver function, thus supporting the diagnostic value.\u003c/p\u003e \u003cp\u003eOur results indicated that there were marked changes in liver function indicators among the treated groups. In particular, the treated fibrosis CCl\u003csub\u003e4\u003c/sub\u003e and HCC DEN groups were respectively in higher levels of ALT, AST, and ALP, thus showing hepatic injury and cellular membrane instability, consistent with findings from previous studies [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOxidative stress induction in the experimental animals was manifested from the significantly decreased levels of SOD in both the fibrosis and HCC groups. These data are consistent with previous reports of excessive ROS production induced by CCl4 and DEN in the initiation of lipid peroxidation and subsequent oxidative damage [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The observed markers of oxidative stress underline the pivotal role played by ROS in liver injury and carcinogenesis.\u003c/p\u003e \u003cp\u003eApoptotic marker analysis revealed increased Bax and P53 levels alongside decreased Bcl2 levels in the HCC group, suggesting heightened apoptotic activity. This pattern is indicative of the pro-apoptotic signaling pathways activated in response to severe hepatic injury and tumorigenesis, as supported by the literature [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eImmunoblotting results showed further upregulation of the apoptotic markers Bax and P53 and downregulation of Bcl2 in HCC, indicating an increase in the apoptotic activity. The pattern is consistent with the available literature on the promotion of pro-apoptotic signaling in the liver under the state of severe injury and hepatocarcinogenesis conditions [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMoreover, the high expression levels of inflammatory cytokines, specifically TNF-α, in fibrosis and HCC groups highlight the inflammatory response associated with liver damage and cancer progression. TNF-α was reported to play a role in stimulating fibrogenesis and hepatocarcinogenesis by augmenting inflammatory and apoptotic pathways [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These findings are consistent with studies demonstrating increased TNF-α expression in CCl\u003csub\u003e4\u003c/sub\u003e and DEN-induced liver injury models [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe expression of stem cell markers CD24, CD44, and CD45 was very significantly elevated in the HCC group compared to the control and fibrosis groups. CD24 has been reported as playing an oncogenic role in progress, particularly in cell adhesion to other cells and in forming metastasis. The CD24 molecule is overexpressed in many cancers, among them being hepatocellular carcinoma [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This study confirms these observations through the high levels of CD24 in the HCC model, which agrees with [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], who revealed that CD24 participates in the development of liver disease into carcinoma. On the other hand, CD44 is a famous marker associated with cell-cell interactions, migration, and tumor progression [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Our results are in support of previous works indicating that CD44, particularly its standard isoform reported as CD44s, is actively involved in HCC's metastasis process. This is further evidenced by the study of [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], which found high expression of CD44 associated with advanced tumor states in liver cancer. CD45, also known as Protein Tyrosine Phosphatase Receptor Type C (PTPRC), primarily expressed on leukocytes, has been linked to immune evasion and tumor progression in HCC [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The findings of the present investigation are in concordance with previous observations by which showed that CD45 mediates tumor immunity within the microenvironment to foster HCC development.\u003c/p\u003e \u003cp\u003eIt is positively correlated to a high expression of CD24, CD44, and CD45 along with Bcl2, P53, VEGF, SOD, ALT, AST, ALP, and AFP, and is negatively correlated with Bax and TNF-α. This might suggest that their enhanced expression levels are associated with increased angiogenic markers, markers of oxidative stress and liver function markers, but are inversely related to apoptotic and inflammatory markers. As such, these correlations underline the potential role of CD24, CD44, and CD45 as early diagnostic biomarkers for HCC knockdowns because of their involvement in cancer stem cell properties and tumor progression [\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eHistological analysis further supported these biochemical and molecular findings. The typical features of hepatocyte stress showed the following: ballooning, pyknosis, inflammatory infiltration, and fibrosis. The HCC group showed severe alterations, with solid nodules formation and wide extension of fibrous septa, characteristics of advanced liver cancer. These are in full accordance with previous histopathological descriptions of this model of CCl\u003csub\u003e4\u003c/sub\u003e and DEN-induced hepatic damage [\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eIn conclusion, this study is conducted to point out that CD24, CD44, and CD45 have the diagnostic potential for serving as early biomarkers in HCC due to comprehensive biochemical, apoptotic, angiogenic, oxidative stress, and histological data. These markers would provide great help to clinical application in terms of easy identification, thus helping in undertaking timely treatment among HCC patients. Further studies are highly needed in order to validate such findings in human subjects and have an exploration into the mechanisms associated with these stem cell markers' involvement in liver carcinogenesis.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHepatocellular Carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCl₄\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCarbon Tetrachloride\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDEN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDiethylnitrosamine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eALT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAlanine Aminotransferase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAST\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAspartate Aminotransferase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eALP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAlkaline Phosphatase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVEGF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVascular Endothelial Growth Factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSOD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSuperoxide Dismutase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTNF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eα-Tumor Necrosis Factor-alpha\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAFP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAlpha-Fetoprotein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBCL2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eB-cell Lymphoma 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBAX\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBCL2-associated X protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eP53\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTumor Protein P53\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReactive Oxygen Species\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDLK1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDelta-like 1 Homolog\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eK19\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKeratin 19\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLgr5\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeucine-rich Repeat-containing G-protein Coupled Receptor 5\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePTPRC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProtein Tyrosine Phosphatase Receptor Type C (CD45)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEgyptian liver and institute liver hospital ELRIAH approved the experimental procedures with approval code number PHD2019/02.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis manuscript is self-funded, and the authors didn’t receive any external funds.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\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\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eDoaa Shoieb: Visualization, Validation, Software, Resources, Methodology, Investigation, Formal analysis, Data curation, Writing - original draft, Writing - review \u0026amp; editing. Mohamed Abd-Elbaset: Investigation, Methodology. Mona S. Gouida: Investigation, Methodology. Ibrahim S. Kamel: Methodology. Adel Abdel-Moneim: Supervision, Software, Resources, Project administration, Methodology, Investigation, Conceptualization. Ayman Hassan: Methodology. Reham Soliman: Investigation, Methodology. Gamal Shiha: Supervision, Project administration, Formal analysis, Data curation Writing - original draft, Writing - review \u0026amp; editing. Ahmed Nabil: Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Conceptualization, Writing - original draft, Writing - review \u0026amp; editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ede Andrade KQ, Moura FA, dos Santos JM, de Ara\u0026uacute;jo ORP, Santos JC de F, Goulart MOF (2015) Oxidative stress and inflammation in hepatic diseases: Therapeutic possibilities of N-acetylcysteine. Int J Mol Sci 16:30269\u0026ndash;30308\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChatterjee R, Mitra A (2015) An overview of effective therapies and recent advances in biomarkers for chronic liver diseases and associated liver cancer. Int Immunopharmacol 24:335\u0026ndash;345\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeber LWD, Boll M, Stampfl A (2003) Hepatotoxicity and mechanism of action of haloalkanes: Carbon tetrachloride as a toxicological model. Crit Rev Toxicol 33:105\u0026ndash;136\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScholten D, Trebicka J, Liedtke C, Weiskirchen R (2015) The carbon tetrachloride model in mice. Lab Anim 49:4\u0026ndash;11\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMittal G, Brar APS, Soni G (2006) Impact of hypercholesterolemia on toxicity of N-nitrosodiethylamine: Biochemical and histopathological effects. Pharmacological Reports 58:413\u0026ndash;419\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQi Y, Chen X, Chan CY, Li D, Yuan C, Yu F, Lin MC, Yew DT, Kung HF, Lai L (2008) Two-dimensional differential gel electrophoresis/analysis of diethylnitrosamine induced rat hepatocellular carcinoma. Int J Cancer 122:2682\u0026ndash;2688\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChrist B, Pelz S (2013) Implication of hepatic stem cells in functional liver repopulation. Cytometry Part A 83 A:90\u0026ndash;102\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang JL, Gong L, Yan Q, Zhou NN, Lee VH, Guan X (2019) Advances in surface markers of liver cancer stem cell. Hepatoma Research\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConstandinou C, Henderson N, Iredale JP (2005) Modeling liver fibrosis in rodents. Methods Mol Med 117:237\u0026ndash;250\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFathy AH, Bashandy MA, Bashandy SAE, Mansour AM, Elsadek B (2017) Sequential analysis and staging of a diethylnitrosamine-induced hepatocellular carcinoma in male Wistar albino rat model. Can J Physiol Pharmacol 95:1462\u0026ndash;1472\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBergmeyer HU, Horder M, Rej R (1986) Approved recommendation (1985) on IFCC methods for the measurement of catalytic concentration of enzymes. Part 2. IFCC method for aspartate aminotransferase (L-aspartate: 2-oxoglutarate aminotransferase, EC 2.6.1.1). Journal of Clinical Chemistry and Clinical Biochemistry 24:497\u0026ndash;508\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchumann G, Klauke R, Canalias F, Bossert-Reuther S, F. H. Franck P, Gella FJ, others, Ceriotti F (2011) IFCC primary reference procedures for the measurement of catalytic activity concentrations of enzymes at 37\u0026deg; C. Part 9: Reference procedure for the measurement of catalytic concentration of alkaline phosphatase: International Federation of Clinical Chemis. Clin Chem Lab Med 49:1439\u0026ndash;1446\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReyes-Gordillo K, Shah R, Muriel P (2017) Oxidative stress and inflammation in hepatic diseases: current and future therapy. Oxidative medicine and cellular longevity\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePawlik TM (2024) Hepatocellular Carcinoma. Surg Oncol Clin N Am 33:xiii\u0026ndash;xiv\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRamaiah SK (2007) A toxicologist guide to the diagnostic interpretation of hepatic biochemical parameters. Food and chemical toxicology 45:1551\u0026ndash;1557\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang B, Tontonoz P (2018) Liver X receptors in lipid signalling and membrane homeostasis. Nat Rev Endocrinol 14:452\u0026ndash;463\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSinha K, Das J, Pal PB, Sil PC (2013) Oxidative stress: the mitochondria-dependent and mitochondria-independent pathways of apoptosis. Arch Toxicol 87:1157\u0026ndash;1180\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang G, Wang X, Chung TY, Ye W, Hodge L, Zhang L, Wang YJ (2020) Carbon tetrachloride (CCl4) accelerated development of non-alcoholic fatty liver disease (NAFLD)/steatohepatitis (NASH) in MS-NASH mice fed western diet supplemented with fructose (WDF). BMC Gastroenterol 20:1\u0026ndash;13\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePop C, Salvesen GS (2009) Human caspases: activation, specificity, and regulation. Journal of biological Chemistry 284:21777\u0026ndash;21781\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang B, Tan Y (2019) Hepatic stem cells: From biological characteristics to therapeutic applications. Cellular and Molecular Life Sciences 76:2253\u0026ndash;2273\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang B, Tan X (2019) Mechanisms of hepatic fibrosis and approaches for therapeutic interventions. Cells 8:714\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang YM, Seki E (2015) TNF? in liver fibrosis. Curr Pathobiol Rep 3:253\u0026ndash;261\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePradere JP, Kluwe J, De Minicis S, Jiao JJ, Gwak GY, Dapito DH, others, Schwabe RF (2013) Hepatic macrophages but not dendritic cells contribute to liver fibrosis by promoting the survival of activated hepatic stellate cells in mice. Hepatology 58:1461\u0026ndash;1473\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEltahir HM, Nazmy MH (2018) Esomeprazole ameliorates CCl4 induced liver fibrosis in rats via modulating oxidative stress, inflammatory, fibrogenic and apoptotic markers. Biomedicine and Pharmacotherapy 97:1356\u0026ndash;1365\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao X, Wang S, Li X, Liu H, Xu S (2021) Cadmium exposure induces TNF-?-mediated necroptosis via FPR2/TGF-?/NF-?B pathway in swine myocardium. Toxicology 453:152733\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBretz NP, Salnikov A V., Perne C, et al (2012) CD24 controls Src/STAT3 activity in human tumors. Cellular and Molecular Life Sciences 69:3863\u0026ndash;3879\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarotta LL, Almendro V, Marusyk A, Shipitsin M, Schemme J, Walker SR, others, Polyak K (2011) The JAK2/STAT3 signaling pathway is required for growth of CD44\u0026thinsp;+\u0026thinsp;CD24\u0026ndash;stem cell\u0026ndash;like breast cancer cells in human tumors. J Clin Invest 121:2723\u0026ndash;2735\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMima K, Okabe H, Ishimoto T, Hayashi H, Nakagawa S, others (2012) CD44s regulates the TGF-?-mediated mesenchymal phenotype and is associated with poor prognosis in patients with hepatocellular carcinoma. Cancer Res 72:3414\u0026ndash;3423\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYamashita T, Honda M, Nakamoto Y, Baba M, Nio K, Hara Y, Kaneko S (2013) Discrete nature of EpCAM\u0026thinsp;+\u0026thinsp;and CD90\u0026thinsp;+\u0026thinsp;cancer stem cells in human hepatocellular carcinoma. Hepatology 57:1484\u0026ndash;1497\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRheinlander A, Schraven B, Bommhardt U (2018) CD45 in human physiology and clinical medicine. Immunol Lett 196:22\u0026ndash;32\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHermiston ML, Xu Z, Weiss A (2003) CD45: A critical regulator of signaling thresholds in immune cells. Annu Rev Immunol 21:107\u0026ndash;137\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaraguchi N, Ishii H, Mimori K, et al (2010) CD13 is a therapeutic target in human liver cancer stem cells. Journal of Clinical Investigation 120:3326\u0026ndash;3339\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang ZF, Ho DW, Ng MN, Lau CK, Yu WC, Ngai P, others, Fan ST (2008) Significance of CD90\u0026thinsp;+\u0026thinsp;cancer stem cells in human liver cancer. Cancer Cell 13:153\u0026ndash;166\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYamashita T, Ji J, Budhu A, et al (2009) EpCAM-Positive Hepatocellular Carcinoma Cells Are Tumor-Initiating Cells With Stem/Progenitor Cell Features. Gastroenterology 136:1012\u0026ndash;1024\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Hepatocellular Carcinoma, CD24, CD44, CD45, Biomarkers, Early Diagnosis","lastPublishedDoi":"10.21203/rs.3.rs-6886613/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6886613/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Early diagnosis of hepatocellular carcinoma (HCC) is one of the determinant factors for effective treatment with better prognosis. This study evaluated circulating stem cell markers CD24, CD44, and CD45 as potential early diagnostic biomarkers for HCC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: In this study, male Wistar rats were used, grouped in four categories: Control, Olive Oil, Fibrosis (CCl\u003csub\u003e4\u003c/sub\u003e-induced), and HCC (DEN-induced). Serum levels of CD24, CD44, and CD45 were estimated and correlated with the levels of apoptotic markers (BCL2, BAX, P53); angiogenic markers (VEGF); oxidative stress markers (SOD); liver function tests (ALT, AST, ALP); and inflammatory cytokines (TNF-α). Histological examinations were done by H\u0026amp;E and Masson's Trichrome techniques.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Levels of CD24, CD44, and CD45 were significantly higher in the HCC group. The markers showed strong correlations with increased apoptotic activity, angiogenesis, oxidative stress, and altered liver function tests. Histological findings demonstrated severe fibrosis and damage to the liver tissue. High levels of inflammatory cytokines and AFP further confirm the diagnosis of HCC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The study demonstrates that CD24, CD44, and CD45 are viable early diagnostic markers for HCC. Their implementation in clinical settings could facilitate early diagnosis and improve the management and treatment outcomes of HCC patients.\u003c/p\u003e","manuscriptTitle":"Assessment of circulating CD24, CD44, and CD45 stem cell markers as novel early diagnostic tools for hepatocellular carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-23 06:21:16","doi":"10.21203/rs.3.rs-6886613/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":"0202a560-e531-4e36-89f8-6a898613295d","owner":[],"postedDate":"June 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T08:59:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-23 06:21:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6886613","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6886613","identity":"rs-6886613","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}