Alcohol induces sorafenib resistance in hepatocellular carcinoma: A Translational Study

Alcohol induces sorafenib resistance in hepatocellular carcinoma: A Translational Study | 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 Alcohol induces sorafenib resistance in hepatocellular carcinoma: A Translational Study Anoïsia Courtois, Constance Marie, Gregory Fouquet, Momar Diouf, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6837338/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Jan, 2026 Read the published version in Journal of Molecular Medicine → Version 1 posted 5 You are reading this latest preprint version Abstract Background: Alcohol is a major cause of hepatocellular carcinoma (HCC), accounting for 30% of cases worldwide. Sorafenib, a tyrosine kinase inhibitor (TKI), was the standard first-line treatment for advanced HCC until 2021, but sorafenib resistance is common. We explored the impact of chronic alcohol exposure (CAE) on sorafenib response and sought to identify associated resistance mechanisms. Methods: Huh-7 HCC cells were chronically exposed to alcohol for 6 months. Sorafenib resistance was assessed by measuring cell viability (IC50) and evaluating the protein expression of signaling pathways involved in resistance using immunoblotting. RNA sequencing was performed to identify mechanisms of resistance. Sorafenib response was assessed with RECIST 1.1 criteria in HCC patients. A retrospective study of 86 CHIEF cohort HCC patients (alcohol-related vs. non-alcohol-related etiologies) evaluated overall survial (OS) and progression-free survival (PFS) using the log-rank test. Results: CAE significantly decreased cell sensitivity to sorafenib ( p=0.006 ), indicating increased resistance. The ERK pathway was involved. RNA sequencing of our cells identified a total of 80 differencially expressed genes associated with drug resistance and aggressiveness. Clinically, alcohol-related HCC patients were less responsive to sorafenib (35% responders vs. 65%, p=0.014 ) and had significantly different OS ( p=0.0234 ). Median OS was 10 months (95% CI=[6.1; 15.7]) for alcohol-related HCC and 12.1 months (95% CI=[7.7; 64.9]) for other etiologies. PFS was lower in the alcohol group (5.72 months (95% CI=[4.63 ;12.8]) vs. 9.66 months (95% CI=[4.40 ; 39.9], p=0.0298 )). Conclusion: Sorafenib resistance due to chronic alcohol consumption is consistent in both in vitro models and clinical settings. Hepatocellular carcinoma Alcohol Sorafenib Resistance Figures Figure 1 Figure 2 Figure 3 Figure 4 Key messages Chronic alcohol exposure reduces the effectiveness of sorafenib in hepatocellular carcinoma (HCC), as demonstrated in both in vitro and clinical settings. In vitro, alcohol-exposed HCC cells showed increased sorafenib resistance, associated with activation of the ERK signaling pathway and differential expression of 80 genes linked to drug resistance and tumor aggressiveness. Clinically, patients with alcohol-related HCC had poorer responses to sorafenib and shorter overall and progression-free survival compared to patients with non-alcohol-related HCC. These findings suggest that alcohol-related HCC may require alternative or personalized therapeutic strategies beyond standard TKI treatments. Introduction Excessive and chronic alcohol consumption is responsible for approximately 30% of HCC cases worldwide 1 . Chronic alcohol consumption can induce the development of alcohol-related liver disease (ALD) defined by a large clinical spectrum of liver diseases, such as hepatocellular carcinoma (HCC) which is one of the most severe forms 2 . HCC, the most common form of liver cancer, is the third-leading cause of cancer-related mortality. This cancer is ranked as the sixth most prevalent cancer worldwide 3 . The majority of HCC cases are diagnosed at an advanced stage of the disease, which limits curative therapeutic strategies. Additionally, patients with alcohol-related HCC are diagnosed at a later stage of the disease, resulting in lower survival 1,4 . Patients should be stratified by the Barcelona Clinic Liver Cancer (BCLC) staging to determine the indicated treatment 5 . For advanced HCC patients, therefore not eligible for curative strategies, the indicated treatments are immunotherapies and targeted therapies, such as sorafenib 6 . Sorafenib, a tyrosine kinase inhibitor (TKI), was the first therapy approved for the treatment of advanced HCC. This first-line treatment showed an improvement in overall survival (OS) of only 3 months (10.7 months versus 7.9 months for placebo) 7 . It inhibits tumor proliferation and angiogenesis by targeting tyrosine kinases associated with Vascular Endothelial Growth Factor Receptor (VEGFR) and Platelet-Derived Growth Factor Receptor (PDGFR) 7,8 . Subsequently, other targeted therapies were approved for patients with advanced HCC, such as lenvatinib, another first-line treatment, as well as regorafenib and cabozantinib, second-line treatments 9 . Approximately 50% of HCC patients are receiving systemic therapies during their health care pathway 10 . However, sorafenib remains a fundamental treatment for HCC, administered as a first-line therapy to patients not eligible for immunotherapy, or as second-line therapy to patients for whom immunotherapy was ineffective 11 . Unfortunately, only 30% of patients can benefit from it and these patients usually develop a drug resistance within 6 months 12 . Various mechanisms have been shown to be responsible for the acquisition of resistance to sorafenib. The emergence of this resistance leads to therapeutic failure of these anti-cancer treatments in many patients with HCC. A hypoxic tumour microenvironment, epithelial-mesenchymal transition, the presence of cancer stem cells and increased efflux transporter activity all contribute to the development of this resistance 13 . The ATP-Binding Cassette (ABC) efflux transporters have been shown to play a crucial role in sorafenib resistance by promoting drug efflux. Inhibiting these transporters increases the response of HCC cells to this molecule 14 . Cancer cells are known to develop drug resistance by activating various signaling pathways through receptor tyrosine kinases (RTKs). Additionally, resistance in HCC cells is acquired via RTK activation, resulting in the reactivation of the RAS/MEK/ERK and AKT pathways 15 . Besides, alcohol exposure induces activation of the MAPK pathway and thus ERK1/2 phosphorylation 16 . The efficacy of treatments could be affected by different underlying etiologies of HCC. Studies have shown that metabolic dysfunction-associated steatohepatitis (MASH) related HCC is less responsive to immunotherapy 17,18 , but this remains controversial, as post hoc analyses have not shown any difference in response to immunotherapy depending on the etiology 19,20 . In a previous study, we demonstrated in a cellular model of HCC that chronic alcohol exposure promotes the progression and aggressiveness of HCC. Alcohol exposure induced an increase in migration and invasion capacities, as well as an increase in the expression of cancerous stem cell markers such as CD133. The latter was also significantly highly expressed in alcohol-related HCC, as observed in biopsies from patients with HCC 16 . Currently, the etiology of HCC is not considered in the choice of treatment. Here, we explored the consequences of chronic alcohol exposure (CAE) on the response to sorafenib in both in vitro model and in patients. First, we determined the effects of CAE on the response to sorafenib in a cellular model to identify potential cellular mechanisms of the resistance. Secondly, we conducted a retrospective study on a cohort of patients with HCC treated with sorafenib to evaluate the impact of alcohol on their survival. Materials and methods Cell line and culture conditions Early grade HCC cell line Huh-7 was obtained from the virology department (AGIR laboratory EA 4294, CURS, CHU Sud, Amiens). Cells were maintained in Dulbecco’s Modified Eagle’s Medium supplemented with 10% foetal calf serum, 2 mM L-glutamine, 100 U/mL penicillin and 100 µg/mL streptomycin (Dutscher, Issy-les-Moulineaux, France). Huh-7 cells were grown in a humidified incubator with 5% CO 2 at 37°C and routinely tested for mycoplasma contamination. Chronic alcohol exposure (CAE) Huh-7 cells were exposed to ethanol using the CAE protocol as described in our previous study 16 . The Huh-7 HCC cell line was grown in media containing ethanol for 6 months at different concentrations, 80 mM, 160 mM, and 270 mM. The CAE protocol is represented in Supplementary methods. Cell viability assays and inhibitory concentration 50 (IC50) The MethylThiazole Tetrazolium (MTT) salt assay was used to evaluate the response to sorafenib. 24 hours after seeding 1500 cells/well in a 96-well plate, huh-7 cells were treated for 72 hours with the following range of sorafenib: 1, 2, 4, 6, 8, 10, 15, 20, 25, 30 and 50 µM. We used dimethyl sulfoxide (DMSO) as a control and replicated each condition in triplicate on a 96-well plate. They were then rinsed and exposed for 75 min to a 0.5 mg/mL MTT solution resuspended in the culture medium. Reduced purple formazan crystals were dissolved with a solution of DMSO:isopropanol (50:50) and measured at 570 nm using Tecan Infinite M200 Pro. Cellular viability was also measured using Promega’s CellTiter-Glo Luminescent Cell Viability Assay (Ref G7571), which generates a luminescent signal proportional to the amount of ATP. 96 well were seeded with 5,000 cells/well 24 h prior to treatment. Huh-7 cells were treated for 72 hours with the following range of sorafenib : 1, 2, 4, 6, 8, 10, 15, 20, 25, 30 and 50 µM. DMSO was used as a control, and each condition was replicated in triplicate. The assay was performed according to the manufacturer’s protocol. The luminescent signal was measured using Tecan Infinite M200 Pro. The IC50 values of sorafenib were calculated using GraphPad Prism software (version 9.3.1,GraphPad Software, Inc.,La Jolla,CA,USA). Western Blot analysis Western Blot analysis To extract total protein, cells were lysed with Radioimmunoprecipitation assay (RIPA) buffer containing protease and phosphatase inhibitors (Roche, Meylan, France) and Triton-X100 at finally concentration of 0.1%. After protein quantitation (Bradford), equal amounts of each protein sample were separated by electrophoresis and transferred on PVDF membranes (Bio-Rad, Munich, Germany). The used primary antibodies are listed in Supplementary table 3. Revelation was performed using Enhanced ChemiLuminescence (ECL) system (Bio-Rad, Munich, Germany). Results were analysed using ImageLab software (Bio-Rad). Study design This was a retrospective, monocentric study carried out at Amiens University Hospital. Patients are part of the CHIEF cohort (French national cohort of HCC patients, NCT04348838). Recruitment was performed between 2019 and 2022. Eligible patients were aged ≥ 18 years, with HCC diagnosed on liver histology or radiological evidence. Key exclusion criteria included the presence of another serious life-threatening disease, cholangiocarcinoma or hepatocholangiocarcinoma, pregnancy, and minors patients. All patients included provided a signed and informed consent form for the anonymous use of clinical and biological data. The study is classified as MR01 issued by «la Commission Nationale de l'Informatique et des Libertés (CNIL)». For the purpose of this study, only patients with HCC treated with sorafenib were included. Patients received oral sorafenib 400 mg twice daily. We categorized patients into two groups, HCC of alcohol-related etiology (N = 54) and HCC of other etiologies (N = 32) (Hepatitis B Virus (HBV), Hepatitis C Virus (HCV), MASH and others). For patients with multiple etiologies, we prioritized alcoholic etiology and included them in the HCC alcoholic group. The response rate of sorafenib was assessed at 3 months of treatment according to Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 21 . Overall survival (OS) was defined as the time from the start of sorafenib treatment until death. Progression Free Survival (PFS) was defined as the time from the start of sorafenib treatment until progression or deaths events. RNA Sequencing Total RNA of Ctl and 270 mM Huh-7 cells was extracted using ReliaPrep™ RNA Miniprep Systems (Promega, Charbonnières-les-bains, France). We performed RNA sequencing using Illumina’s stranded total RNA Prep ligation with ribo-zero plus kit following the manufacturer’s instructions (Illumina, San Diego, USA). RNA and cDNA concentrations were recorded (Qubit 3 Fluorometer, Thermo Fisher Scientific, Waltham, USA) before the library preparation, while RNA quality was assessed using a bioanalyzer 2100 (Agilent). cDNA was quantified once again before pooling the libraries., cDNA were then sequenced with an Illumina NextSeq 550 device using a paired-end read length of 2x75 bases (NextSeq 500/550 High Output Kit v2.5). RNAseq analysis and figures were obtained using Dr TOM software (BGI). Bowtie2 was used to map the clean reads to the gene sequence reference (transcriptome), and RSEM was then used to calculate the gene expression levels. The differential gene expression detection was achieved through DESeq2 R package 22 . RNA sequencing was performed on two separate samples, each replicated four times. Statistical Analyses The propensity score was estimated by the probability of having an alcohol etiology as a function of the following variables of interest: Age, Sex, AST, ALT, Bilirubin, Child Pugh, and BCLC score. In order to calculate the propensity score for all patients, the multiple imputation technique (10 repetitions) was used for each variable containing missing data. For each of the 10 imputated datasets, weights were then calculated according to the IPTW (Inverse probability of treatment weighting) method using the ATE (average treatment effect) estimator through the ‘Matchtem’ R package. After weighting the overall sample, the comparability of the variables between the two groups was assessed using the standardised mean difference (SMD) and represented graphically by the 'loveplot'. An SMD of less than 0.15 was considered a criterion for the comparability of a variable between the two groups. After weighting by the propensity score, all seven variables were well balanced between the two groups (alcohol vs . other) as the standardised differences were in the range [-0.15;0.15]. Using the mean stabilized weights across the 10 datasets, the weighted survival curves were displayed for each group and compared using a pooled Logrank test for weigthed data (‘svrlogrank’ and ‘micombine.chisquare’ R functions). The χ2 test or Fisher’s exact test were used to compare nominal data. The patients analysis was performed using R software version 4.2.3 via the RStudio interface version ©2023.06.2. All cells data are presented as Mean ± SEM (standard error of the mean). All statistical tests are two-tailed and p-values less than 0.05 were considered statistically significant, with * for p < 0.05. ** for p < 0.01 and *** for p < 0.001. The Kruskal-Wallis test and the Dunn’s post hoc test was used for the MTT assay. The Student t test was employed for the cell titer assay. Cellular experiments statistical analyses were performed using GraphPad Prism software (version 9.3.1)(GraphPad Software, Inc., La Jolla, CA, USA). Results Chronic alcohol exposure (CAE) induces resistance to sorafenib in HCC cells First, in order to determine the effect of CAE on sorafenib sensitivity, we determined the IC50 of sorafenib in Huh-7 cells. Cells were cultured following the CAE protocol, with a 6-month alcohol exposure at different concentrations: 80 mM, 160 mM, and 270 mM. The results show a alcohol dose-dependent shift to the right of the cell viability curve. Compared to the control (Ctl) cells, 270 mM CAE cells exposed to sorafenib had more viability (Fig. 1 A). Then, for the Ctl condition, the IC50 was 4.4 ± 0.09µM. There was a non-significant increase in the IC50 of sorafenib for the 80 and 160 mM conditions. There was a significant increase in IC50 with CAE at 270 mM, reaching a value of 10.3 ± 1.4µM ( p = 0.006 , Dunn’s test)(Fig. 1 B). An increase of 134.1% compared with Ctl cells. These results highlight a decrease in the sensitivity to sorafenib, reflecting the acquisition of CAE cell resistance. With regard to the results of the cell titer assay, for the control condition, the IC50 was 5.75µM. An increase in IC50 was observed with alcohol exposure, reaching a value of 9.05µM for the 270mM condition (Fig. 1 D). However, this increase was not significant ( p = 0.135 , Student t test). We also studied the effect of CAE on the response to lenvatinib, another first-line tyrosine kinase inhibitor treatment for advanced HCC. We observed an increase in the IC50 of lenvatinib at the 160 mM condition compared with the control condition ( p = 0.019 ), but not at 270 mM ( p = 0.768 ) (Suppl Fig. 1A and 1B). Secondly, we looked at second-line TKI treatments for patients with advanced HCC, regorafenib and cabozantinib. The results showed a dose-dependent shift to the right of the cell viability (Suppl Fig. 1C and 1E). We observed an increase in the IC50 of regorafenib and cabozantinib with CAE at 270 mM (Suppl Fig. 1D and 1F). It was significant for cabozantinib ( p = 0.033 ) but not for regorafenib ( p = 0.152 ). These results highlight a decrease in the sensitivity to regorafenib and cabozantinib with CAE, reflecting the acquisition of cell resistance. Our results demonstrate the acquisition of resistance to different targeted therapies following exposure to alcohol. CAE activates ERK signaling pathways in Huh-7 cells treated by sorafenib We investigated the impact of CAE on the signaling pathways involve in sorafenib resistance with Western Blot experiments. In Ctl cells non exposed to ethanol, we observed a significant decrease in mTOR phosphorylation with sorafenib at 5 µM (0.434-fold, p = 0.004 ) and 10 µM (0.526-fold, p = 0.013 ) compared to non-sorafenib treated Ctl cells. Our experiments demonstrated also a significant decrease of ERK 1/2 phosphorylation in Ctl cells with sorafenib at 10 µM (0.41-fold, p = 0.025 ) compared to non-sorafenib treated Ctl cells. Sorafenib at 5 µM and 10 µM in CAE 270 mM had no effect on mTOR and ERK1/2 phosphorylation. Sorafenib treatment did not modify the expression of Ras protein in Ctl and CAE 270 mM cells (Fig. 2 A and 2 B). These results are schematically summarized in Fig. 2 C. Efflux transporters are not involved in the acquisition of sorafenib resistance induced by CAE Several studies have demonstrated the involvement of efflux transporters in treatment resistance in HCC. Therefore, we wanted to study the impact of CAE on efflux transporter activity. To do this, we studied the effect of CAE on the accumulation of rhodamine123 (R123) in Huh-7 cells. After cell recovery and fluorescence analysis by flow cytometry, we observed a slightly lower retention of R123 in alcohol-treated Huh-7 cells (Suppl Fig. 2A). These results would suggest a higher efflux transporter activity with 160mM and 270mM alcohol in Huh-7 cells compared with the 80mM condition ( p = 0.004 and p = 0.003 respectively) . However, there was no significant difference with the control condition. To confirm this result, we assessed the expression of various efflux transporters of the ABC family, known to be involved in this mechanism of resistance. Our results show a significant increase in the expression of ABBC1 (MRP1) transcripts in 270mM CAE cell ( p = 0.049 ). No difference in ABCB1 (MDR1) transcript expression was induced by CAE ( p = 0.99 ). Surprisingly, CAE caused a significant decrease in the expression of ABCG2 transcripts ( p = 0.006 , Suppl Fig. 2B). We then studied the protein expression of the MRP1 and MDR1 transporters by flow cytometry and CAE does not modulate their protein expression (Suppl Fig. 2C). Subsequently, we used the EFFLUX-ID Gold kit (Enzo Life Sciences) to specifically determine the activity of the MRP1/MRP2/MRP3, MDR1 and ABCG2 transporters, using inhibitors, following the manufacturer’s instructions. We did not observe a significant difference with alcohol exposure in the activity of the efflux transporters MRP, MDR1 and ABCG2 ( p = 0.12 , p = 0.81 , p = 0.11 respectively, ANOVA, Suppl Fig. 2D). Identification by RNAseq of differentially expressed and drug resistance-related genes induced by alcohol In order to determine the mechanisms of resistance to treatments induced by alcohol exposure, we conducted RNA Sequencing on our Huh-7 control and 270 mM CAE cells (Fig. 3 ). Based on the Venn diagrams, we identified 16,261 common genes between our two conditions (Fig. 3 A). Additionally, 408 genes are specific to the Ctrl condition, while 786 genes are specific to the 270 mM condition. Among the 16,261 genes, we further extracted 1,405 differentially expressed genes and visualized them in the volcano map (Fig. 3 B), including 815 up-regulated and 590 down-regulated genes. The results of the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis showed 20 differentially expressed pathways in Ctrl and 270 mM cells (Fig. 3 C). We obtained a list of drug resistance and aggressiveness genes from the KEGG pathway. A total of 80 genes were retrieved for drug resistance and are depicted in the heat map such as genes involved in angiogenesis (VEGF, PDFGA/B/D). We also find the MRAS (log2 270mM/Ctl = 3.09), PROM1 (CD133) (log2 270mM/Ctl = 3.15) and CD36 genes (log2 270mM/Ctl = 3.07) (Fig. 3 D). These genes showed a significant differential expression between Ctrl and 270 mM cells. These results show significant differences in the transcriptomic profiles of HCC cells chronically exposed or not to alcohol. Alcohol-related HCC patients are less responsive to sorafenib A total of 86 patients with HCC were enrolled in this study, including 54 patients in the alcohol-related HCC group and 32 patients in the non–alcohol-related HCC group. The baseline characteristics of the patients are shown in ​Table 1 . Table 1 Baseline characteristics of HCC patients according to alcohol consumption. Values are expressed in number (percentage) for categorical variables, or median (interquartile range) for numerical variables. Fisher tests were used for categorical variables; Wilcoxon rank sum test was used for continuous variables. p-values < 0.05 are bolded and statistically significant. Abbreviations: AFP, Alpha fetoprotein; ASAT, transaminases; ALAT, Alanine aminotransferase; PTH, Prothrombin Time; BCLC, Barcelona clinic liver cancer. Characteristic Alcohol HCC, N = 54 Non-Alcohol HCC, N = 32 p-value Sexe 0.004 F 1 (1.9%) 7 (22%) M 53 (98%) 25 (78%) Age 70 (65, 75) 69 (61, 80) 0.9 missing 0 1 AFP ( ng/mL ) 14 (4, 242) 24 (4, 250) > 0.9 missing 12 5 AST ( UI/L ) 56 (42, 86) 57 (38, 87) 0.8 missing 16 9 ALT ( UI/L ) 43 (32, 70) 42 (28, 61) 0.6 missing 16 9 Total bilirubin ( µmol/L ) 17 (12, 23) 16 (13, 32) 0.6 missing 16 7 PT ( % ) 76 (60, 88) 68 (63, 88) 0.5 missing 15 6 Albumin ( G/L ) 36.7 (34.0, 39.9) 36.0 (32.0, 39.6) 0.3 missing 20 11 Creatinine ( µmol/L ) 71 (54, 94) 72 (57, 88) 0.9 missing 15 8 BCLC 0.4 B 14 (37%) 5 (26%) C 24 (63%) 14 (74%) missing 16 13 Child Pugh 0.013 A 39 (91%) 17 (65%) B 4 (9.3%) 9 (35%) missing 11 6 Sorafenib Response 0.014 Responders Non-Responders 19 (35%) 35 (65%) 20(63%) 12 (37%) The gender distribution is significantly different between our two groups ( p = 0.004 ). There were 53 (98%) men and 1 (1.9%) woman in the alcohol HCC group and 25 (78%) men and 7 (22%) women in the non-alcohol HCC group. No clinically relevant differences were observed between the groups in terms of median age at the time of inclusion or biochemical characteristics (AST, ALT, alpha-fetoprotein, bilirubin, creatinine, albumin, and prothrombin) at the time of sorafenib treatment. The BCLC stage was assessed in 57 (66.3%) patients (information was missing for 29 (33.7%) patients). The distribution of BCLC stages between alcohol and non-alcohol groups did not significantly differ ( p = 0.4 ). However, the Child–Pugh liver function class differs between the two groups ( p = 0.013 ). In the HCC alcohol group, 39 (91%) patients had a Child A score and 4 (9.3%) a B score. In the non-alcohol HCC group, 17 (65%) patients had a Child A score and 9 (35%) a B score. We subsequently evaluated the response to sorafenib, taking into account the etiology of HCC, whether alcohol or non-alcohol. Patients with alcohol-related HCC had a significantly lower response rate to sorafenib compared to patients with non-alcohol-related HCC (35% (n = 19) versus 63% (n = 20) respectively, p = 0.014 ). Alcohol reduces overall survival (OS) and increases HCC progression in HCC patients treated with sorafenib Before conducting the multivariate analysis, variables were balanced using the method of SMD (Suppl Fig. 3). The median OS was 10 months (95% CI=[6.1;15.7]) and 12.1 months (95% CI=[7.7;64.9]) in the "Alcohol" and "Other aetiology" groups, respectively (Fig. 4 A). Alcohol-related HCC significantly shortened the lifespan of patients ( p = 0.0234 ). The proportions of patients at risk of death at 36 months were 4% and 30% in the respective groups. The median progression-free survival PFS was 5.72 months (95% CI=[4.63;12.8]) in the alcohol-related HCC group versus 9.66 months (95% CI=[4.40;39.9] in non–alcohol-related HCC group (Fig. 4 B). Alcohol-related HCC patients had significantly shorter PFS ( p = 0.0298 ). The proportions of patients without progression or at risk of death at 18 months were 11% and 41% in the respective groups. Both OS and PFS were better in the non-alcohol-related HCC group. Discussion In our previous work, we reported that chronic alcohol exposure induces an aggressive phenotype, characterized by altered cell migration and invasion, as well as changes in the expression of cancer stem cell markers (CD133, CD44, CD90) 16 . Several systemic treatments are currently recommended for patients with advanced HCC. Sorafenib was the standard first-line treatment until 2021, but it remains a second-line option for advanced HCC 11 . It has significantly improved the overall survival of patients with advanced HCC. Unfortunately, clinical evidence confirms that many patients develop resistance to sorafenib over time 15 . Several studies have reported the acquisition of sorafenib resistance in vitro following prolonged exposure to the drug 23–25 . Since alcohol is a major etiological factor in HCC and etiology is not considered when choosing treatments for advanced HCC, it seemed important to investigate the effect of chronic alcohol exposure on the efficacy of sorafenib. Our results indicate that CAE in HCC cells leads to resistance to sorafenib. Several mechanisms of resistance to sorafenib have been documented in the literature. The MAP kinase pathway, including Ras/Raf/MEK/ERK signaling, has been shown to be closely associated with treatment resistance 26 . This pathway regulates various cellular processes, including proliferation, growth, differentiation, and survival. Hyperactivation of the Ras/Raf/MAPK pathway is observed in more than 50% of HCC cases 27 and alcohol exposure has been reported to trigger the activation of ERK1/2 phosphorylation 16 . Previous studies have demonstrated increased ERK1/2 phosphorylation in sorafenib-resistant HCC cells after 10 months of prolonged drug exposure 25 . In HCC cells not exposed to ethanol, we observed a significant reduction in mTOR and ERK1/2 phosphorylation following sorafenib treatment. However, this decrease was not observed in cells that had been chronically exposed to ethanol. RNA Sequencing has provided valuable insights into the aggressiveness and treatment resistance induced by CAE. Several differentially expressed genes were identified between the control and CAE conditions, including PROM1 and CD36. We previously demonstrated that CD133, encoded by the PROM1 gene, is overexpressed in response to CAE 16 . CD133 is involved in multiple biological processes, including tumorigenicity, differentiation, cellular regeneration, and treatment resistance 28 . Moreover, CD133 + CD44 + cells exhibit a strong capability for treatment resistance, which is mediated by an increased expression of ABC efflux transporters 29 . The CD36 receptor has been shown to promote HCC progression through the PI3K/AKT/mTOR signaling pathway 30 . Based on the results obtained in RNA sequencing, it would be interesting to study CD36 in our CAE cellular model. Moreover, CD36 has been investigated as a potential therapeutic target able to suppress HCC proliferation and metastasis. Its role in metabolic reprogramming and the enhancement of fatty acid uptake through the Src/PI3K/AKT signaling pathway further underscores its importance in HCC progression 31 . RNA Sequencing also highlighted the upregulation of angiogenesis-related genes such as VEGF and PDGF in response to alcohol exposure. These investigations could provide new insights into overcoming resistance in alcohol-related HCC patients. Our clinical study evaluated the response to sorafenib in 86 patients. The results indicate that patients with alcohol-related HCC are less responsive to sorafenib compared to those with HCC of other etiologies. These findings are consistent with our in vitro results. Furthermore, Costentin et al . demonstrated that patients with alcohol-related HCC have a shorter median survival compared to those with non-alcohol-related HCC 4 . In our cohort of HCC patients treated with sorafenib, those with alcohol-related HCC also had a shorter overall survival and progression-free survival. The induction of sorafenib resistance by alcohol suggests that sorafenib may not be effective in treating patients with alcohol-related HCC. Immunotherapy is also a therapeutic approach used in the treatment of advanced HCC. The IMBrave150 study compared the efficacy of the atezolizumab-bevacizumab combination to that of sorafenib 32 . Atezolizumab is an antibody targeting PD-L1 (Programm Death Ligand 1) and bevacizumab is an antibody targeting VEGF, helping to prevent the inhibition of immune checkpoints. The study showed that patients treated with the atezolizumab-bevacizumab combination had a longer survival (19.2 months) compared to those treated with sorafenib (13.4 months). Due to these promising results, this combination has become the new first-line treatment for advanced HCC 32,33 . Therefore, it would be valuable to investigate the response to this combination in both alcohol-related and non-alcohol-related HCC. Given the differences between these etiologies, personalized treatment may be necessary to optimize outcomes. Furthermore, the importance of addiction management in the treatment of alcohol-related cancers has been well established. Alcohol rehabilitation or a history of abstinence has been associated with a lower risk of alcohol-associated cancers 34 . The study by Costentin et al . demonstrated that alcohol withdrawal increases survival in alcohol-related HCC patients, aligning their survival rates closer to those with non-alcohol-related HCC 4 . While alcohol cessation reduces HCC risk by 6 to 7% per year, the harmful effects can persist for decades, requiring a 23-year withdrawal period to match HCC incidence in abstinent patients 35 . To study alcohol withdrawal effects, our lab's chronic alcohol exposure protocol includes a one-month withdrawal period after six months of exposure. This protocol has shown that withdrawal reverses some of the aggressiveness capabilities associated with alcohol-induced HCC, such as decreased cancerous stem cell (CSC) marker expression and reduced cellular migration and invasion 16 . These findings underscore the importance of alcohol withdrawal in the management of HCC. Despite the importance of abstinence, addiction follow-up is not routinely implemented, only 0.9% of cancer patients are aware of resources to manage alcohol consumption 36 . Addiction follow-up during treatment is often lacking, making it difficult to stratify patients into abstinent and non-abstinent groups. Given this, it would be important to investigate whether alcohol withdrawal improves treatment response in HCC patients. Currently, the therapeutic strategy for HCC is primarily based on tumor grade. Our team has clearly demonstrated that HCC with an alcohol etiology is less responsive to sorafenib and exhibits increased aggressiveness, with shorter OS and PFS. Our in vitro models are consistent with the clinical results, underlining the relevance and robustness of our conclusions. Moreover, the resistance induced by alcohol appears to be a class effect impacting all TKI molecules. However, the pathophysiological mechanisms underlying sorafenib resistance induced by alcohol in HCC remain poorly understood. Further research is needed to identify all the molecular factors involved and to better understand the full scope of alcohol's impact on treatment resistance. Strengthening these areas of understanding will be crucial in developing more effective, personalized therapeutic approaches for HCC patients with an alcoholic etiology. Abbreviations ABC : ATP-Binding Cassette AFP : Alpha fetoprotein ALD : Alcohol-related liver disease ALT : Alanine transaminase ANOVA : Analysis of variance AST : Aspartate transaminase ATE : Average treatment effect BCLC : Barcelona Clinic Liver Cancer CAE : Chronic alcohol exposure CNIL : Commission nationale de l'informatique et des libertés CSC : Cancerous stem cell ECL : Enhanced ChemiLuminescence HBV : Hepatitis B virus HCC : Hepatocellular carcinoma HCV : Hepatitis C virus IPTW : Inverse probability of treatment weighting MASH : Metabolic dysfunction-associated steatohepatitis MTT : MethylThiazole Tetrazolium NP40 : Nonidet P40 OS : Overall survival PDGFR : Platelet-Derived Growth Factor Receptor PD-L1 : Programm Death Ligand 1 PFS : Progression free survival PTH : Prothrombin Time R123 : Rhodamine123 RECIST : Response evaluation criteria in solid tumors RTKs : Receptor tyrosine kinases SMD : Standardized mean difference TKI : Tyrosine kinase inhibitor VEGFR : Vascular Endothelial Growth Factor Receptor WD : Withdrawal Declarations Clinical trial number : The clinical trial number ofthe CHIEF cohort is NCT04348838, registered with the number 19.04.15.41412 by the “Comité deProtection des Personnes Sud-Est IV” (RCB ID: 2019-A00679-48). Availability of data and material : Not applicable Ethics approval and consent to participate : Patients are part of the CHIEF cohort (French national cohort of HCC patients, NCT04348838). All patients included provided a signed and informed consent form for the anonymous use of clinical and biological data. The study was approved by local ethics committees: “Comité de Protection des Personnes Sud-Est IV” (Agence Régionale de santé d’Auvergne-Rhône-Alpes). The study is classified as MR01 issued by «la Commission Nationale de l'Informatique et des Libertés (CNIL)». Financial support statement: Anoïsia Courtois is the recipient of a doctoral grant attributed by the “Ministère de l’Enseignement Supérieur, de la Recherche et de l’Innovation“(MESRI). The present work and Dr Grégory Fouquet were funded by The “Institut National du Cancer” (INCa) and “Institut pour la Recherche en Santé Publique” (IReSP) call to research projects to reduce and fight against psychoactive substances consumption and addictions grant of 2021. Damien Esparteiro was funded by the “Region Hauts-de-France” and the Amiens-Picardie University Hospital (CHU Amiens-Picardie). Conflict of interest statement: No conflict of interest. Authors contributions: CA: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Writing. MC: Investigation, Methodology, Resources. FG: Investigation, Methodology, Resources. DM: Investigation. ED: Writing. DG: Investigation. ML: Investigation. NM: Funding acquisition, Validation, Writing—review. NKE: Funding acquisition, Project administration, Clinical data provinding, Supervision, Writing. MI : Conceptualization, Data curation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing, Writing—review & editing. Acknowledgements : We thank Pr Loïc Garçon and his research team HEMATIM EA4666 for the flow cytometry technique. We also acknowledge the contribution of the Genetics department of the Amiens University Hospital for their expertise in sequencing. References Ganne-Carrié N, Nahon P. Hepatocellular carcinoma in the setting of alcohol-related liver disease. J Hepatol . 2019;70(2):284-293. doi:10.1016/j.jhep.2018.10.008 Ceni E, Mello T, Galli A. Pathogenesis of alcoholic liver disease: Role of oxidative metabolism. World J Gastroenterol . 2014;20(47):17756-17772. doi:10.3748/wjg.v20.i47.17756 Cancer Today. Accessed September 11, 2024. https://gco.iarc.who.int/today/ Costentin CE, Mourad A, Lahmek P, et al. Hepatocellular carcinoma is diagnosed at a later stage in alcoholic patients: Results of a prospective, nationwide study: Delayed Diagnosis of Alcohol-Related HCC. Cancer . 2018;124(9):1964-1972. doi:10.1002/cncr.31215 Mak LY, Cruz-Ramón V, Chinchilla-López P, et al. Global Epidemiology, Prevention, and Management of Hepatocellular Carcinoma. Am Soc Clin Oncol Educ Book . 2018;(38):262-279. doi:10.1200/EDBK_200939 Vogel A, Meyer T, Sapisochin G, Salem R, Saborowski A. Hepatocellular carcinoma. The Lancet . 2022;400(10360):1345-1362. doi:10.1016/S0140-6736(22)01200-4 Llovet JM, Ricci S, Mazzaferro V, et al. Sorafenib in Advanced Hepatocellular Carcinoma. N Engl J Med . 2008;359(4):378-390. doi:10.1056/NEJMoa0708857 Wilhelm SM, Carter C, Tang L, et al. BAY 43-9006 Exhibits Broad Spectrum Oral Antitumor Activity and Targets the RAF/MEK/ERK Pathway and Receptor Tyrosine Kinases Involved in Tumor Progression and Angiogenesis. Cancer Res . 2004;64(19):7099-7109. doi:10.1158/0008-5472.CAN-04-1443 Yang JD, Hainaut P, Gores GJ, Amadou A, Plymoth A, Roberts LR. A global view of hepatocellular carcinoma: trends, risk, prevention and management. Nat Rev Gastroenterol Hepatol . 2019;16(10):589-604. doi:10.1038/s41575-019-0186-y Llovet JM, Castet F, Heikenwalder M, et al. Immunotherapies for hepatocellular carcinoma. Nat Rev Clin Oncol . 2022;19(3):151-172. doi:10.1038/s41571-021-00573-2 Reig M, Forner A, Rimola J, et al. BCLC strategy for prognosis prediction and treatment recommendation: The 2022 update. J Hepatol . 2022;76(3):681-693. doi:10.1016/j.jhep.2021.11.018 Tang W, Chen Z, Zhang W, et al. The mechanisms of sorafenib resistance in hepatocellular carcinoma: theoretical basis and therapeutic aspects. Signal Transduct Target Ther . 2020;5(1):87. doi:10.1038/s41392-020-0187-x Niu L, Liu L, Yang S, Ren J, Lai PBS, Chen GG. New insights into sorafenib resistance in hepatocellular carcinoma: Responsible mechanisms and promising strategies. Biochim Biophys Acta BBA - Rev Cancer . 2017;1868(2):564-570. doi:10.1016/j.bbcan.2017.10.002 Di Giacomo S, Briz O, Monte MJ, et al. Chemosensitization of hepatocellular carcinoma cells to sorafenib by β-caryophyllene oxide-induced inhibition of ABC export pumps. Arch Toxicol . 2019;93(3):623-634. doi:10.1007/s00204-019-02395-9 Leung CON, Tong M, Chung KPS, et al. Overriding Adaptive Resistance to Sorafenib Through Combination Therapy With Src Homology 2 Domain–Containing Phosphatase 2 Blockade in Hepatocellular Carcinoma. Hepatology . 2020;72(1):155-168. doi:10.1002/hep.30989 Marié C, Fouquet G, Courtois A, et al. Mechanisms of chronic alcohol exposure-induced aggressiveness in cellular model of HCC and recovery after alcohol withdrawal. Cell Mol Life Sci . 2022;79(7):366. doi:10.1007/s00018-022-04387-y Pfister D, Núñez NG, Pinyol R, et al. NASH limits anti-tumour surveillance in immunotherapy-treated HCC. Nature . 2021;592(7854):450-456. doi:10.1038/s41586-021-03362-0 Heinrich B, Brown ZJ, Diggs LP, et al. Steatohepatitis Impairs T-cell–Directed Immunotherapies Against Liver Tumors in Mice. Gastroenterology . 2021;160(1):331-345.e6. doi:10.1053/j.gastro.2020.09.031 Meyer T, Galani S, Lopes A, Vogel A. Aetiology of liver disease and response to immune checkpoint inhibitors: An updated meta-analysis confirms benefit in those with non-viral liver disease. J Hepatol . 2023;79(2):e73-e76. doi:10.1016/j.jhep.2023.04.012 Rossari F, Tada T, Suda G, et al. Disease Etiology Impact on Outcomes of Hepatocellular Carcinoma Patients Treated with Atezolizumab plus Bevacizumab: A Real-World, Multicenter Study. Liver Cancer . 2024;13(5):522-536. doi:10.1159/000537915 Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1). Eur J Cancer . 2009;45(2):228-247. doi:10.1016/j.ejca.2008.10.026 Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol . 2014;15(12):550. doi:10.1186/s13059-014-0550-8 Chow AKM, Ng L, Lam CSC, et al. The Enhanced Metastatic Potential of Hepatocellular Carcinoma (HCC) Cells with Sorafenib Resistance. Takehara T, ed. PLoS ONE . 2013;8(11):e78675. doi:10.1371/journal.pone.0078675 Tomonari T, Takeishi S, Taniguchi T, et al. MRP3 as a novel resistance factor for sorafenib in hepatocellular carcinoma. Oncotarget . 2016;7(6):7207-7215. doi:10.18632/oncotarget.6889 Fouquet G, Marié C, Collet L, et al. Rescuing SLAMF3 Expression Restores Sorafenib Response in Hepatocellular Carcinoma Cells through the Induction of Mesenchymal-to-Epithelial Transition. Cancers . 2022;14(4):910. doi:10.3390/cancers14040910 Ma Y, Xu R, Liu X, et al. LY3214996 relieves acquired resistance to sorafenib in hepatocellular carcinoma cells. Int J Med Sci . 2021;18(6):1456-1464. doi:10.7150/ijms.51256 Moon H, Ro SW. MAPK/ERK Signaling Pathway in Hepatocellular Carcinoma. Cancers . 2021;13(12):3026. doi:10.3390/cancers13123026 Zhang H, Xia Y, Wang F, et al. Aldehyde Dehydrogenase 2 Mediates Alcohol‐Induced Colorectal Cancer Immune Escape through Stabilizing PD‐L1 Expression. Adv Sci . 2021;8(10):2003404. doi:10.1002/advs.202003404 Zhu Z, Hao X, Yan M, et al. Cancer stem/progenitor cells are highly enriched in CD133 + CD44 + population in hepatocellular carcinoma. Int J Cancer . 2010;126(9):2067-2078. doi:10.1002/ijc.24868 Luo X, Zheng E, Wei L, et al. The fatty acid receptor CD36 promotes HCC progression through activating Src/PI3K/AKT axis-dependent aerobic glycolysis. Cell Death Dis . 2021;12(4):328. doi:10.1038/s41419-021-03596-w Feng WW, Zuppe HT, Kurokawa M. The Role of CD36 in Cancer Progression and Its Value as a Therapeutic Target. Cells . 2023;12(12):1605. doi:10.3390/cells12121605 Qin S, Ren Z, Feng YH, et al. Atezolizumab plus Bevacizumab versus Sorafenib in the Chinese Subpopulation with Unresectable Hepatocellular Carcinoma: Phase 3 Randomized, Open-Label IMbrave150 Study. Liver Cancer . 2021;10(4):296-308. doi:10.1159/000513486 Llovet JM, Kelley RK, Villanueva A, et al. Hepatocellular carcinoma. Nat Rev Dis Primer . 2021;7(1):6. doi:10.1038/s41572-020-00240-3 Schwarzinger M, Ferreira-Borges C, Neufeld M, Alla F, Rehm J. Alcohol rehabilitation and cancer risk: a nationwide hospital cohort study in France. Lancet Public Health . 2024;9(7):e461-e469. doi:10.1016/S2468-2667(24)00107-5 Griswold MG, Fullman N, Hawley C, et al. Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet . 2018;392(10152):1015-1035. doi:10.1016/S0140-6736(18)31310-2 Hamant C, Deneuve S, Albaret MA, et al. Accompagnement des dépendances à l’alcool et au tabac des patients atteints d’un cancer des voies aérodigestives supérieures. Bull Cancer (Paris) . 2018;105(11):1012-1019. doi:10.1016/j.bulcan.2018.07.006 Supplementary Files Supplementarymaterialsandmethods.docx UncroppedgelscansforallpresentedWesternblots.docx Cite Share Download PDF Status: Published Journal Publication published 25 Jan, 2026 Read the published version in Journal of Molecular Medicine → Version 1 posted Editorial decision: Major Revisions Needed 09 Dec, 2025 Reviewers agreed at journal 07 Jul, 2025 Reviewers invited by journal 23 Jun, 2025 Editor assigned by journal 12 Jun, 2025 First submitted to journal 10 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6837338","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":475391457,"identity":"c854dab8-7cfc-45f8-a5fc-247e8cb9aa3d","order_by":0,"name":"Anoïsia Courtois","email":"","orcid":"","institution":"UPJV: Universite de Picardie Jules Verne","correspondingAuthor":false,"prefix":"","firstName":"Anoïsia","middleName":"","lastName":"Courtois","suffix":""},{"id":475391458,"identity":"48f75552-5b29-4f56-b10a-d21102608930","order_by":1,"name":"Constance Marie","email":"","orcid":"","institution":"CHU Amiens-Picardie: Centre Hospitalier Universitaire Amiens-Picardie","correspondingAuthor":false,"prefix":"","firstName":"Constance","middleName":"","lastName":"Marie","suffix":""},{"id":475391459,"identity":"b8de1b6f-5495-4b27-9707-2e8aad93fc6c","order_by":2,"name":"Gregory Fouquet","email":"","orcid":"","institution":"UPJV: Universite de Picardie Jules Verne","correspondingAuthor":false,"prefix":"","firstName":"Gregory","middleName":"","lastName":"Fouquet","suffix":""},{"id":475391460,"identity":"7496863d-ebf7-4466-a66d-529574ab877b","order_by":3,"name":"Momar Diouf","email":"","orcid":"","institution":"CHU Amiens-Picardie: Centre Hospitalier Universitaire Amiens-Picardie","correspondingAuthor":false,"prefix":"","firstName":"Momar","middleName":"","lastName":"Diouf","suffix":""},{"id":475391461,"identity":"a4da0954-f41e-429e-97b9-8ffa98e0ee49","order_by":4,"name":"Damien Esparteiro","email":"","orcid":"","institution":"UPJV: Universite de Picardie Jules Verne","correspondingAuthor":false,"prefix":"","firstName":"Damien","middleName":"","lastName":"Esparteiro","suffix":""},{"id":475391462,"identity":"ab0805fe-3603-4998-8244-f4784f7efcb8","order_by":5,"name":"Gerard Ducournau","email":"","orcid":"","institution":"CHU Amiens-Picardie: Centre Hospitalier Universitaire Amiens-Picardie","correspondingAuthor":false,"prefix":"","firstName":"Gerard","middleName":"","lastName":"Ducournau","suffix":""},{"id":475391463,"identity":"e089d5a2-f952-46bb-91d6-51a0903144de","order_by":6,"name":"Lea Marticho","email":"","orcid":"","institution":"CHU Amiens-Picardie: Centre Hospitalier Universitaire Amiens-Picardie","correspondingAuthor":false,"prefix":"","firstName":"Lea","middleName":"","lastName":"Marticho","suffix":""},{"id":475391464,"identity":"68412e71-5aa5-4848-a635-e80c8baf32e9","order_by":7,"name":"Mickael Naassila","email":"","orcid":"","institution":"UPJV: Universite de Picardie Jules Verne","correspondingAuthor":false,"prefix":"","firstName":"Mickael","middleName":"","lastName":"Naassila","suffix":""},{"id":475391465,"identity":"fdfadace-df95-4e14-8a62-13b9b304f9f7","order_by":8,"name":"Eric Nguyen-Khac","email":"","orcid":"","institution":"CHU Amiens-Picardie: Centre Hospitalier Universitaire Amiens-Picardie","correspondingAuthor":false,"prefix":"","firstName":"Eric","middleName":"","lastName":"Nguyen-Khac","suffix":""},{"id":475391466,"identity":"36e9f2e4-a479-49fd-90da-ab55fa50b995","order_by":9,"name":"Ingrid MARCQ","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIiWNgGAWjYBACNhCRwAblfYCJ8BgwMLA3EKGFcQayFp4DBO1iYGDmgQmAGLi08Em3X/vwoIwhmn/24Ye3bdsY8vjYDz/78KbAhoFHGrseNpkzxTMSzjHkzjiXZmyd28ZQzMaTZjxzjkEaAw9fAnYtEjnJDIltDLkNZ3jYpHPb/ie2STAYM/MYHGaw58GqA6FlPkiLZRuQLcH+GajlPwMPTi3ph8FaNoC0MIK18IBsOYBHSw4zQ8I5idyNZ9iMLXvOgfySU8w4xyCZB5cW+Rnpjxl/lNnkzjvD/PDGjzKGPPn245sZ3vyxk8OlBRJrDBJgJoiEhxJODcB08QDORNEyCkbBKBgFowAGAJdbTDpScIECAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-4031-224X","institution":"UPJV: Universite de Picardie Jules Verne","correspondingAuthor":true,"prefix":"","firstName":"Ingrid","middleName":"","lastName":"MARCQ","suffix":""}],"badges":[],"createdAt":"2025-06-06 13:10:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6837338/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6837338/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00109-026-02645-1","type":"published","date":"2026-01-25T15:59:14+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":85731742,"identity":"30754694-78b8-48e9-8c93-ae0e0a39b755","added_by":"auto","created_at":"2025-07-01 07:26:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1432247,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChronic alcohol exposure induces an increase in the resistance of Huh-7 cells to sorafenib\u003c/strong\u003e. The cell viability of Huh-7 cells treated with sorafenib concentrations (0-50µM) was studied using an MTT \u003cstrong\u003e(A) \u003c/strong\u003eand Cell titer \u003cstrong\u003e(C) \u003c/strong\u003eassay and allowed determination of the sorafenib IC50 \u003cstrong\u003e(B,D)\u003c/strong\u003e.\u003cstrong\u003e \u003c/strong\u003eThe MTT and cell titer assays were performed 72 h after sorafenib treatment. Results were pooled from 4 independent experiments and the corresponding mean ± SEM of sorafenib IC50 is presented (B,D). The Kruskal-Wallis test and the Dunn’s post hoc test was used for the MTT assay. (N=4; **vs Ctl \u003cem\u003ep\u0026lt;0.01\u003c/em\u003e). The Student t test was employed for the cell titer assay (N=4).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6837338/v1/f3c861e9aa8cad8604e2b35a.png"},{"id":85731749,"identity":"96b74ecb-6282-4ea8-be9c-d71aed67464c","added_by":"auto","created_at":"2025-07-01 07:26:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":7144017,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChronic alcohol exposure modifies signaling pathways implicated in sorafenib response. \u003c/strong\u003eProtein expression was analyzed by Western Blot in Huh-7 cells. GAPDH, mTOR (Ser2448), Ras, and ERK1/2 (Thr202/Tyr204) were used as controls (N=4). The mean protein activation and expression levels\u003cstrong\u003e \u003c/strong\u003eare represented \u003cstrong\u003e(A)\u003c/strong\u003e. One of the four independent experiments is presented here \u003cstrong\u003e(B)\u003c/strong\u003e. Results were simplified in schematic \u003cstrong\u003e(C)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eRTK = Receptor Tyrosine Kinases.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6837338/v1/b07af54ffc45add231789517.png"},{"id":85731750,"identity":"05723a12-7341-4399-9262-af7aea64fa87","added_by":"auto","created_at":"2025-07-01 07:26:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":925330,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferentially expressed genes and pathways associated with CAE in huh-7 HCC cells\u003c/strong\u003e. \u003cstrong\u003eA\u003c/strong\u003e. Venn diagram of the number of expressed genes between control Huh-7 cells and EtOH huh-7 cells. \u003cstrong\u003eB\u003c/strong\u003e. Volcano plot of differentially expressed genes obtained by RNA-seq. \u003cstrong\u003eC\u003c/strong\u003e. KEGG pathway classification. The vertical axis represents the pathway. The horizontal axis is the enrichment ratio. The size of the bubble represents the number of genes annotated to KEGG Pathway. The color represents the enriched significance with the specific Q-value. The Q-value was obtained by correction of Pvalue (Qvalue\u0026lt;0.05 is considered as significant enrichment)(EtOH/Ctl). \u003cstrong\u003eD.\u003c/strong\u003e Heat map expression levels of 80 drug resistance genes obtained by RNA sequencing.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6837338/v1/1a9b473e09a5f8fbc1efd80c.png"},{"id":85733570,"identity":"b6574f76-4b3c-48b6-b096-26b3422b088b","added_by":"auto","created_at":"2025-07-01 07:42:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1388829,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAlcohol consumption decreases survival of patients with hepatocellular carcinoma treated by sorafenib\u003c/strong\u003e. The overall survival (OS) \u003cstrong\u003e(A)\u003c/strong\u003e and progression-free survival (PFS) \u003cstrong\u003e(B)\u003c/strong\u003e of 86 HCC patients was presented with Kaplan-Meier curves and compared with logrank test. The number of patients at risk was listed below the survival curves.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6837338/v1/7360b9892666b87fb2e6b678.png"},{"id":101151827,"identity":"91693b95-21d6-4aeb-955e-b0b925a5032f","added_by":"auto","created_at":"2026-01-26 16:06:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":11864937,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6837338/v1/3d72d4a1-bbf5-48a8-9b7f-e57bb1cd7059.pdf"},{"id":85731764,"identity":"3540132a-98d0-4964-b40c-be31b97e3534","added_by":"auto","created_at":"2025-07-01 07:26:18","extension":"docx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":91547,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterialsandmethods.docx","url":"https://assets-eu.researchsquare.com/files/rs-6837338/v1/619ec05b1c8ab70fe6e4f845.docx"},{"id":85733571,"identity":"ec954f01-124b-497f-9e7f-4eadaf6db26a","added_by":"auto","created_at":"2025-07-01 07:42:18","extension":"docx","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":476961,"visible":true,"origin":"","legend":"","description":"","filename":"UncroppedgelscansforallpresentedWesternblots.docx","url":"https://assets-eu.researchsquare.com/files/rs-6837338/v1/e0a6ebe57ec1cabb107cbe12.docx"}],"financialInterests":"","formattedTitle":"Alcohol induces sorafenib resistance in hepatocellular carcinoma: A Translational Study","fulltext":[{"header":"Key messages ","content":"\u003cp\u003eChronic alcohol exposure reduces the effectiveness of sorafenib in hepatocellular carcinoma (HCC), as demonstrated in both \u003cem\u003ein vitro\u003c/em\u003e and clinical settings.\u003c/p\u003e\n\u003cp\u003eIn vitro, alcohol-exposed HCC cells showed increased sorafenib resistance, associated with activation of the ERK signaling pathway and differential expression of 80 genes linked to drug resistance and tumor aggressiveness.\u003c/p\u003e\n\u003cp\u003eClinically, patients with alcohol-related HCC had poorer responses to sorafenib and shorter overall and progression-free survival compared to patients with non-alcohol-related HCC.\u003c/p\u003e\n\u003cp\u003eThese findings suggest that alcohol-related HCC may require alternative or personalized therapeutic strategies beyond standard TKI treatments.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eExcessive and chronic alcohol consumption is responsible for approximately 30% of HCC cases worldwide\u003csup\u003e1\u003c/sup\u003e. Chronic alcohol consumption can induce the development of alcohol-related liver disease (ALD) defined by a large clinical spectrum of liver diseases, such as hepatocellular carcinoma (HCC) which is one of the most severe forms\u003csup\u003e2\u003c/sup\u003e. HCC, the most common form of liver cancer, is the third-leading cause of cancer-related mortality. This cancer is ranked as the sixth most prevalent cancer worldwide\u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe majority of HCC cases are diagnosed at an advanced stage of the disease, which limits curative therapeutic strategies. Additionally, patients with alcohol-related HCC are diagnosed at a later stage of the disease, resulting in lower survival\u003csup\u003e1,4\u003c/sup\u003e. Patients should be stratified by the Barcelona Clinic Liver Cancer (BCLC) staging to determine the indicated treatment\u003csup\u003e5\u003c/sup\u003e. For advanced HCC patients, therefore not eligible for curative strategies, the indicated treatments are immunotherapies and targeted therapies, such as sorafenib\u003csup\u003e6\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSorafenib, a tyrosine kinase inhibitor (TKI), was the first therapy approved for the treatment of advanced HCC. This first-line treatment showed an improvement in overall survival (OS) of only 3 months (10.7 months versus 7.9 months for placebo)\u003csup\u003e7\u003c/sup\u003e. It inhibits tumor proliferation and angiogenesis by targeting tyrosine kinases associated with Vascular Endothelial Growth Factor Receptor (VEGFR) and Platelet-Derived Growth Factor Receptor (PDGFR)\u003csup\u003e7,8\u003c/sup\u003e. Subsequently, other targeted therapies were approved for patients with advanced HCC, such as lenvatinib, another first-line treatment, as well as regorafenib and cabozantinib, second-line treatments\u003csup\u003e9\u003c/sup\u003e. Approximately 50% of HCC patients are receiving systemic therapies during their health care pathway\u003csup\u003e10\u003c/sup\u003e. However, sorafenib remains a fundamental treatment for HCC, administered as a first-line therapy to patients not eligible for immunotherapy, or as second-line therapy to patients for whom immunotherapy was ineffective\u003csup\u003e11\u003c/sup\u003e. Unfortunately, only 30% of patients can benefit from it and these patients usually develop a drug resistance within 6 months\u003csup\u003e12\u003c/sup\u003e. Various mechanisms have been shown to be responsible for the acquisition of resistance to sorafenib. The emergence of this resistance leads to therapeutic failure of these anti-cancer treatments in many patients with HCC. A hypoxic tumour microenvironment, epithelial-mesenchymal transition, the presence of cancer stem cells and increased efflux transporter activity all contribute to the development of this resistance\u003csup\u003e13\u003c/sup\u003e. The ATP-Binding Cassette (ABC) efflux transporters have been shown to play a crucial role in sorafenib resistance by promoting drug efflux. Inhibiting these transporters increases the response of HCC cells to this molecule\u003csup\u003e14\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCancer cells are known to develop drug resistance by activating various signaling pathways through receptor tyrosine kinases (RTKs). Additionally, resistance in HCC cells is acquired via RTK activation, resulting in the reactivation of the RAS/MEK/ERK and AKT pathways\u003csup\u003e15\u003c/sup\u003e. Besides, alcohol exposure induces activation of the MAPK pathway and thus ERK1/2 phosphorylation\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe efficacy of treatments could be affected by different underlying etiologies of HCC. Studies have shown that metabolic dysfunction-associated steatohepatitis (MASH) related HCC is less responsive to immunotherapy\u003csup\u003e17,18\u003c/sup\u003e, but this remains controversial, as post hoc analyses have not shown any difference in response to immunotherapy depending on the etiology\u003csup\u003e19,20\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn a previous study, we demonstrated in a cellular model of HCC that chronic alcohol exposure promotes the progression and aggressiveness of HCC. Alcohol exposure induced an increase in migration and invasion capacities, as well as an increase in the expression of cancerous stem cell markers such as CD133. The latter was also significantly highly expressed in alcohol-related HCC, as observed in biopsies from patients with HCC\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCurrently, the etiology of HCC is not considered in the choice of treatment. Here, we explored the consequences of chronic alcohol exposure (CAE) on the response to sorafenib in both \u003cem\u003ein vitro\u003c/em\u003e model and in patients. First, we determined the effects of CAE on the response to sorafenib in a cellular model to identify potential cellular mechanisms of the resistance. Secondly, we conducted a retrospective study on a cohort of patients with HCC treated with sorafenib to evaluate the impact of alcohol on their survival.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCell line and culture conditions\u003c/h2\u003e \u003cp\u003e Early grade HCC cell line Huh-7 was obtained from the virology department (AGIR laboratory EA 4294, CURS, CHU Sud, Amiens). Cells were maintained in Dulbecco\u0026rsquo;s Modified Eagle\u0026rsquo;s Medium supplemented with 10% foetal calf serum, 2 mM L-glutamine, 100 U/mL penicillin and 100 \u0026micro;g/mL streptomycin (Dutscher, Issy-les-Moulineaux, France). Huh-7 cells were grown in a humidified incubator with 5% CO\u003csub\u003e2\u003c/sub\u003e at 37\u0026deg;C and routinely tested for mycoplasma contamination.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eChronic alcohol exposure (CAE)\u003c/h3\u003e\n\u003cp\u003eHuh-7 cells were exposed to ethanol using the CAE protocol as described in our previous study\u003csup\u003e16\u003c/sup\u003e. The Huh-7 HCC cell line was grown in media containing ethanol for 6 months at different concentrations, 80 mM, 160 mM, and 270 mM. The CAE protocol is represented in Supplementary methods.\u003c/p\u003e\n\u003ch3\u003eCell viability assays and inhibitory concentration 50 (IC50)\u003c/h3\u003e\n\u003cp\u003eThe MethylThiazole Tetrazolium (MTT) salt assay was used to evaluate the response to sorafenib. 24 hours after seeding 1500 cells/well in a 96-well plate, huh-7 cells were treated for 72 hours with the following range of sorafenib: 1, 2, 4, 6, 8, 10, 15, 20, 25, 30 and 50 \u0026micro;M. We used dimethyl sulfoxide (DMSO) as a control and replicated each condition in triplicate on a 96-well plate. They were then rinsed and exposed for 75 min to a 0.5 mg/mL MTT solution resuspended in the culture medium. Reduced purple formazan crystals were dissolved with a solution of DMSO:isopropanol (50:50) and measured at 570 nm using Tecan Infinite M200 Pro.\u003c/p\u003e \u003cp\u003eCellular viability was also measured using Promega\u0026rsquo;s CellTiter-Glo Luminescent Cell Viability Assay (Ref G7571), which generates a luminescent signal proportional to the amount of ATP. 96 well were seeded with 5,000 cells/well 24 h prior to treatment. Huh-7 cells were treated for 72 hours with the following range of sorafenib : 1, 2, 4, 6, 8, 10, 15, 20, 25, 30 and 50 \u0026micro;M. DMSO was used as a control, and each condition was replicated in triplicate. The assay was performed according to the manufacturer\u0026rsquo;s protocol. The luminescent signal was measured using Tecan Infinite M200 Pro. The IC50 values of sorafenib were calculated using GraphPad Prism software (version 9.3.1,GraphPad Software, Inc.,La Jolla,CA,USA).\u003c/p\u003e\n\u003ch3\u003eWestern Blot analysis\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eWestern Blot analysis\u003c/div\u003e \u003cp\u003eTo extract total protein, cells were lysed with Radioimmunoprecipitation assay (RIPA) buffer containing protease and phosphatase inhibitors (Roche, Meylan, France) and Triton-X100 at finally concentration of 0.1%. After protein quantitation (Bradford), equal amounts of each protein sample were separated by electrophoresis and transferred on PVDF membranes (Bio-Rad, Munich, Germany). The used primary antibodies are listed in Supplementary table 3. Revelation was performed using Enhanced ChemiLuminescence (ECL) system (Bio-Rad, Munich, Germany). Results were analysed using ImageLab software (Bio-Rad).\u003c/p\u003e\n\u003ch3\u003eStudy design\u003c/h3\u003e\n\u003cp\u003eThis was a retrospective, monocentric study carried out at Amiens University Hospital. Patients are part of the CHIEF cohort (French national cohort of HCC patients, NCT04348838). Recruitment was performed between 2019 and 2022. Eligible patients were aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years, with HCC diagnosed on liver histology or radiological evidence. Key exclusion criteria included the presence of another serious life-threatening disease, cholangiocarcinoma or hepatocholangiocarcinoma, pregnancy, and minors patients. All patients included provided a signed and informed consent form for the anonymous use of clinical and biological data. The study is classified as MR01 issued by \u0026laquo;la Commission Nationale de l'Informatique et des Libert\u0026eacute;s (CNIL)\u0026raquo;. For the purpose of this study, only patients with HCC treated with sorafenib were included. Patients received oral sorafenib 400 mg twice daily.\u003c/p\u003e \u003cp\u003eWe categorized patients into two groups, HCC of alcohol-related etiology (N\u0026thinsp;=\u0026thinsp;54) and HCC of other etiologies (N\u0026thinsp;=\u0026thinsp;32) (Hepatitis B Virus (HBV), Hepatitis C Virus (HCV), MASH and others). For patients with multiple etiologies, we prioritized alcoholic etiology and included them in the HCC alcoholic group. The response rate of sorafenib was assessed at 3 months of treatment according to Response Evaluation Criteria in Solid Tumors (RECIST) 1.1\u003csup\u003e21\u003c/sup\u003e. Overall survival (OS) was defined as the time from the start of sorafenib treatment until death. Progression Free Survival (PFS) was defined as the time from the start of sorafenib treatment until progression or deaths events.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRNA Sequencing\u003c/h2\u003e \u003cp\u003eTotal RNA of Ctl and 270 mM Huh-7 cells was extracted using ReliaPrep\u0026trade; RNA Miniprep Systems (Promega, Charbonni\u0026egrave;res-les-bains, France). We performed RNA sequencing using Illumina\u0026rsquo;s stranded total RNA Prep ligation with ribo-zero plus kit following the manufacturer\u0026rsquo;s instructions (Illumina, San Diego, USA). RNA and cDNA concentrations were recorded (Qubit 3 Fluorometer, Thermo Fisher Scientific, Waltham, USA) before the library preparation, while RNA quality was assessed using a bioanalyzer 2100 (Agilent). cDNA was quantified once again before pooling the libraries., cDNA were then sequenced with an Illumina NextSeq 550 device using a paired-end read length of 2x75 bases (NextSeq 500/550 High Output Kit v2.5). RNAseq analysis and figures were obtained using Dr TOM software (BGI). Bowtie2 was used to map the clean reads to the gene sequence reference (transcriptome), and RSEM was then used to calculate the gene expression levels. The differential gene expression detection was achieved through DESeq2 R package\u003csup\u003e22\u003c/sup\u003e. RNA sequencing was performed on two separate samples, each replicated four times.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStatistical Analyses\u003c/h3\u003e\n\u003cp\u003eThe propensity score was estimated by the probability of having an alcohol etiology as a function of the following variables of interest: Age, Sex, AST, ALT, Bilirubin, Child Pugh, and BCLC score. In order to calculate the propensity score for all patients, the multiple imputation technique (10 repetitions) was used for each variable containing missing data. For each of the 10 imputated datasets, weights were then calculated according to the IPTW (Inverse probability of treatment weighting) method using the ATE (average treatment effect) estimator through the \u0026lsquo;Matchtem\u0026rsquo; R package. After weighting the overall sample, the comparability of the variables between the two groups was assessed using the standardised mean difference (SMD) and represented graphically by the 'loveplot'. An SMD of less than 0.15 was considered a criterion for the comparability of a variable between the two groups. After weighting by the propensity score, all seven variables were well balanced between the two groups (alcohol \u003cem\u003evs\u003c/em\u003e. other) as the standardised differences were in the range [-0.15;0.15]. Using the mean stabilized weights across the 10 datasets, the weighted survival curves were displayed for each group and compared using a pooled Logrank test for weigthed data (\u0026lsquo;svrlogrank\u0026rsquo; and \u0026lsquo;micombine.chisquare\u0026rsquo; R functions). The χ2 test or Fisher\u0026rsquo;s exact test were used to compare nominal data. The patients analysis was performed using R software version 4.2.3 via the RStudio interface version \u0026copy;2023.06.2.\u003c/p\u003e \u003cp\u003eAll cells data are presented as Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (standard error of the mean). All statistical tests are two-tailed and p-values less than 0.05 were considered statistically significant, with * for p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. ** for p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 and *** for p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. The Kruskal-Wallis test and the Dunn\u0026rsquo;s post hoc test was used for the MTT assay. The Student t test was employed for the cell titer assay. Cellular experiments statistical analyses were performed using GraphPad Prism software (version 9.3.1)(GraphPad Software, Inc., La Jolla, CA, USA).\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eChronic alcohol exposure (CAE) induces resistance to sorafenib in HCC cells\u003c/h2\u003e \u003cp\u003eFirst, in order to determine the effect of CAE on sorafenib sensitivity, we determined the IC50 of sorafenib in Huh-7 cells. Cells were cultured following the CAE protocol, with a 6-month alcohol exposure at different concentrations: 80 mM, 160 mM, and 270 mM. The results show a alcohol dose-dependent shift to the right of the cell viability curve. Compared to the control (Ctl) cells, 270 mM CAE cells exposed to sorafenib had more viability (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Then, for the Ctl condition, the IC50 was 4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u0026micro;M. There was a non-significant increase in the IC50 of sorafenib for the 80 and 160 mM conditions. There was a significant increase in IC50 with CAE at 270 mM, reaching a value of 10.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u0026micro;M (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.006\u003c/em\u003e, Dunn\u0026rsquo;s test)(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). An increase of 134.1% compared with Ctl cells. These results highlight a decrease in the sensitivity to sorafenib, reflecting the acquisition of CAE cell resistance.\u003c/p\u003e \u003cp\u003eWith regard to the results of the cell titer assay, for the control condition, the IC50 was 5.75\u0026micro;M. An increase in IC50 was observed with alcohol exposure, reaching a value of 9.05\u0026micro;M for the 270mM condition (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). However, this increase was not significant (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.135\u003c/em\u003e, Student t test).\u003c/p\u003e \u003cp\u003eWe also studied the effect of CAE on the response to lenvatinib, another first-line tyrosine kinase inhibitor treatment for advanced HCC. We observed an increase in the IC50 of lenvatinib at the 160 mM condition compared with the control condition (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.019\u003c/em\u003e), but not at 270 mM (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.768\u003c/em\u003e) (Suppl Fig.\u0026nbsp;1A and 1B). Secondly, we looked at second-line TKI treatments for patients with advanced HCC, regorafenib and cabozantinib. The results showed a dose-dependent shift to the right of the cell viability (Suppl Fig.\u0026nbsp;1C and 1E). We observed an increase in the IC50 of regorafenib and cabozantinib with CAE at 270 mM (Suppl Fig.\u0026nbsp;1D and 1F). It was significant for cabozantinib (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.033\u003c/em\u003e) but not for regorafenib (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.152\u003c/em\u003e). These results highlight a decrease in the sensitivity to regorafenib and cabozantinib with CAE, reflecting the acquisition of cell resistance. Our results demonstrate the acquisition of resistance to different targeted therapies following exposure to alcohol.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCAE activates ERK signaling pathways in Huh-7 cells treated by sorafenib\u003c/h2\u003e \u003cp\u003eWe investigated the impact of CAE on the signaling pathways involve in sorafenib resistance with Western Blot experiments. In Ctl cells non exposed to ethanol, we observed a significant decrease in mTOR phosphorylation with sorafenib at 5 \u0026micro;M (0.434-fold, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.004\u003c/em\u003e) and 10 \u0026micro;M (0.526-fold, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.013\u003c/em\u003e) compared to non-sorafenib treated Ctl cells. Our experiments demonstrated also a significant decrease of ERK 1/2 phosphorylation in Ctl cells with sorafenib at 10 \u0026micro;M (0.41-fold, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.025\u003c/em\u003e) compared to non-sorafenib treated Ctl cells. Sorafenib at 5 \u0026micro;M and 10 \u0026micro;M in CAE 270 mM had no effect on mTOR and ERK1/2 phosphorylation. Sorafenib treatment did not modify the expression of Ras protein in Ctl and CAE 270 mM cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). These results are schematically summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eEfflux transporters are not involved in the acquisition of sorafenib resistance induced by CAE\u003c/h2\u003e \u003cp\u003eSeveral studies have demonstrated the involvement of efflux transporters in treatment resistance in HCC. Therefore, we wanted to study the impact of CAE on efflux transporter activity. To do this, we studied the effect of CAE on the accumulation of rhodamine123 (R123) in Huh-7 cells. After cell recovery and fluorescence analysis by flow cytometry, we observed a slightly lower retention of R123 in alcohol-treated Huh-7 cells (Suppl Fig.\u0026nbsp;2A). These results would suggest a higher efflux transporter activity with 160mM and 270mM alcohol in Huh-7 cells compared with the 80mM condition (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.004 and p\u0026thinsp;=\u0026thinsp;0.003 respectively)\u003c/em\u003e. However, there was no significant difference with the control condition.\u003c/p\u003e \u003cp\u003eTo confirm this result, we assessed the expression of various efflux transporters of the ABC family, known to be involved in this mechanism of resistance. Our results show a significant increase in the expression of ABBC1 (MRP1) transcripts in 270mM CAE cell (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.049\u003c/em\u003e). No difference in ABCB1 (MDR1) transcript expression was induced by CAE (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.99\u003c/em\u003e). Surprisingly, CAE caused a significant decrease in the expression of ABCG2 transcripts (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.006\u003c/em\u003e, Suppl Fig.\u0026nbsp;2B). We then studied the protein expression of the MRP1 and MDR1 transporters by flow cytometry and CAE does not modulate their protein expression (Suppl Fig.\u0026nbsp;2C). Subsequently, we used the EFFLUX-ID Gold kit (Enzo Life Sciences) to specifically determine the activity of the MRP1/MRP2/MRP3, MDR1 and ABCG2 transporters, using inhibitors, following the manufacturer\u0026rsquo;s instructions. We did not observe a significant difference with alcohol exposure in the activity of the efflux transporters MRP, MDR1 and ABCG2 (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.12\u003c/em\u003e, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.81\u003c/em\u003e, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.11\u003c/em\u003e respectively, ANOVA, Suppl Fig.\u0026nbsp;2D).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003eIdentification by RNAseq of differentially expressed and drug resistance-related genes induced by alcohol\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eIn order to determine the mechanisms of resistance to treatments induced by alcohol exposure, we conducted RNA Sequencing on our Huh-7 control and 270 mM CAE cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on the Venn diagrams, we identified 16,261 common genes between our two conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Additionally, 408 genes are specific to the Ctrl condition, while 786 genes are specific to the 270 mM condition. Among the 16,261 genes, we further extracted 1,405 differentially expressed genes and visualized them in the volcano map (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), including 815 up-regulated and 590 down-regulated genes. The results of the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis showed 20 differentially expressed pathways in Ctrl and 270 mM cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). We obtained a list of drug resistance and aggressiveness genes from the KEGG pathway. A total of 80 genes were retrieved for drug resistance and are depicted in the heat map such as genes involved in angiogenesis (VEGF, PDFGA/B/D). We also find the MRAS (log2\u003csub\u003e270mM/Ctl\u003c/sub\u003e = 3.09), PROM1 (CD133) (log2\u003csub\u003e270mM/Ctl\u003c/sub\u003e = 3.15) and CD36 genes (log2\u003csub\u003e270mM/Ctl\u003c/sub\u003e = 3.07) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). These genes showed a significant differential expression between Ctrl and 270 mM cells. These results show significant differences in the transcriptomic profiles of HCC cells chronically exposed or not to alcohol.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eAlcohol-related HCC patients are less responsive to sorafenib\u003c/h2\u003e \u003cp\u003eA total of 86 patients with HCC were enrolled in this study, including 54 patients in the alcohol-related HCC group and 32 patients in the non\u0026ndash;alcohol-related HCC group. The baseline characteristics of the patients are shown in ​Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\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\u003eBaseline characteristics of HCC patients according to alcohol consumption. Values are expressed in number (percentage) for categorical variables, or median (interquartile range) for numerical variables. Fisher tests were used for categorical variables; Wilcoxon rank sum test was used for continuous variables. p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 are bolded and statistically significant. Abbreviations: AFP, Alpha fetoprotein; ASAT, transaminases; ALAT, Alanine aminotransferase; PTH, Prothrombin Time; BCLC, Barcelona clinic liver cancer.\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlcohol HCC, N\u0026thinsp;=\u0026thinsp;54\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-Alcohol HCC, N\u0026thinsp;=\u0026thinsp;32\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSexe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (65, 75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (61, 80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAFP (\u003c/b\u003eng/mL\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (4, 242)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (4, 250)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAST (\u003c/b\u003eUI/L\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (42, 86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (38, 87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eALT (\u003c/b\u003eUI/L\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (32, 70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (28, 61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal bilirubin (\u003c/b\u003e\u0026micro;mol/L\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (12, 23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (13, 32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePT (\u003c/b\u003e%\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76 (60, 88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 (63, 88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlbumin (\u003c/b\u003eG/L\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.7 (34.0, 39.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.0 (32.0, 39.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCreatinine (\u003c/b\u003e\u0026micro;mol/L\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71 (54, 94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72 (57, 88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBCLC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild Pugh\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (9.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSorafenib Response\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResponders\u003c/p\u003e \u003cp\u003eNon-Responders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (35%)\u003c/p\u003e \u003cp\u003e35 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(63%)\u003c/p\u003e \u003cp\u003e12 (37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe gender distribution is significantly different between our two groups (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.004\u003c/em\u003e). There were 53 (98%) men and 1 (1.9%) woman in the alcohol HCC group and 25 (78%) men and 7 (22%) women in the non-alcohol HCC group. No clinically relevant differences were observed between the groups in terms of median age at the time of inclusion or biochemical characteristics (AST, ALT, alpha-fetoprotein, bilirubin, creatinine, albumin, and prothrombin) at the time of sorafenib treatment.\u003c/p\u003e \u003cp\u003eThe BCLC stage was assessed in 57 (66.3%) patients (information was missing for 29 (33.7%) patients). The distribution of BCLC stages between alcohol and non-alcohol groups did not significantly differ (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.4\u003c/em\u003e). However, the Child\u0026ndash;Pugh liver function class differs between the two groups (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.013\u003c/em\u003e). In the HCC alcohol group, 39 (91%) patients had a Child A score and 4 (9.3%) a B score. In the non-alcohol HCC group, 17 (65%) patients had a Child A score and 9 (35%) a B score.\u003c/p\u003e \u003cp\u003eWe subsequently evaluated the response to sorafenib, taking into account the etiology of HCC, whether alcohol or non-alcohol. Patients with alcohol-related HCC had a significantly lower response rate to sorafenib compared to patients with non-alcohol-related HCC (35% (n\u0026thinsp;=\u0026thinsp;19) versus 63% (n\u0026thinsp;=\u0026thinsp;20) respectively, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.014\u003c/em\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eAlcohol reduces overall survival (OS) and increases HCC progression in HCC patients treated with sorafenib\u003c/h2\u003e \u003cp\u003eBefore conducting the multivariate analysis, variables were balanced using the method of SMD (Suppl Fig.\u0026nbsp;3). The median OS was 10 months (95% CI=[6.1;15.7]) and 12.1 months (95% CI=[7.7;64.9]) in the \"Alcohol\" and \"Other aetiology\" groups, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Alcohol-related HCC significantly shortened the lifespan of patients (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0234\u003c/em\u003e). The proportions of patients at risk of death at 36 months were 4% and 30% in the respective groups.\u003c/p\u003e \u003cp\u003eThe median progression-free survival PFS was 5.72 months (95% CI=[4.63;12.8]) in the alcohol-related HCC group versus 9.66 months (95% CI=[4.40;39.9] in non\u0026ndash;alcohol-related HCC group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Alcohol-related HCC patients had significantly shorter PFS (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0298\u003c/em\u003e). The proportions of patients without progression or at risk of death at 18 months were 11% and 41% in the respective groups. Both OS and PFS were better in the non-alcohol-related HCC group.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn our previous work, we reported that chronic alcohol exposure induces an aggressive phenotype, characterized by altered cell migration and invasion, as well as changes in the expression of cancer stem cell markers (CD133, CD44, CD90)\u003csup\u003e16\u003c/sup\u003e. Several systemic treatments are currently recommended for patients with advanced HCC. Sorafenib was the standard first-line treatment until 2021, but it remains a second-line option for advanced HCC\u003csup\u003e11\u003c/sup\u003e. It has significantly improved the overall survival of patients with advanced HCC. Unfortunately, clinical evidence confirms that many patients develop resistance to sorafenib over time\u003csup\u003e15\u003c/sup\u003e. Several studies have reported the acquisition of sorafenib resistance in vitro following prolonged exposure to the drug\u003csup\u003e23\u0026ndash;25\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSince alcohol is a major etiological factor in HCC and etiology is not considered when choosing treatments for advanced HCC, it seemed important to investigate the effect of chronic alcohol exposure on the efficacy of sorafenib.\u003c/p\u003e \u003cp\u003eOur results indicate that CAE in HCC cells leads to resistance to sorafenib. Several mechanisms of resistance to sorafenib have been documented in the literature. The MAP kinase pathway, including Ras/Raf/MEK/ERK signaling, has been shown to be closely associated with treatment resistance\u003csup\u003e26\u003c/sup\u003e. This pathway regulates various cellular processes, including proliferation, growth, differentiation, and survival. Hyperactivation of the Ras/Raf/MAPK pathway is observed in more than 50% of HCC cases\u003csup\u003e27\u003c/sup\u003e and alcohol exposure has been reported to trigger the activation of ERK1/2 phosphorylation\u003csup\u003e16\u003c/sup\u003e. Previous studies have demonstrated increased ERK1/2 phosphorylation in sorafenib-resistant HCC cells after 10 months of prolonged drug exposure\u003csup\u003e25\u003c/sup\u003e. In HCC cells not exposed to ethanol, we observed a significant reduction in mTOR and ERK1/2 phosphorylation following sorafenib treatment. However, this decrease was not observed in cells that had been chronically exposed to ethanol.\u003c/p\u003e \u003cp\u003eRNA Sequencing has provided valuable insights into the aggressiveness and treatment resistance induced by CAE. Several differentially expressed genes were identified between the control and CAE conditions, including PROM1 and CD36. We previously demonstrated that CD133, encoded by the PROM1 gene, is overexpressed in response to CAE\u003csup\u003e16\u003c/sup\u003e. CD133 is involved in multiple biological processes, including tumorigenicity, differentiation, cellular regeneration, and treatment resistance\u003csup\u003e28\u003c/sup\u003e. Moreover, CD133\u003csup\u003e+\u003c/sup\u003e CD44\u003csup\u003e+\u003c/sup\u003e cells exhibit a strong capability for treatment resistance, which is mediated by an increased expression of ABC efflux transporters\u003csup\u003e29\u003c/sup\u003e. The CD36 receptor has been shown to promote HCC progression through the PI3K/AKT/mTOR signaling pathway\u003csup\u003e30\u003c/sup\u003e. Based on the results obtained in RNA sequencing, it would be interesting to study CD36 in our CAE cellular model. Moreover, CD36 has been investigated as a potential therapeutic target able to suppress HCC proliferation and metastasis. Its role in metabolic reprogramming and the enhancement of fatty acid uptake through the Src/PI3K/AKT signaling pathway further underscores its importance in HCC progression\u003csup\u003e31\u003c/sup\u003e. RNA Sequencing also highlighted the upregulation of angiogenesis-related genes such as VEGF and PDGF in response to alcohol exposure. These investigations could provide new insights into overcoming resistance in alcohol-related HCC patients.\u003c/p\u003e \u003cp\u003eOur clinical study evaluated the response to sorafenib in 86 patients. The results indicate that patients with alcohol-related HCC are less responsive to sorafenib compared to those with HCC of other etiologies. These findings are consistent with our \u003cem\u003ein vitro\u003c/em\u003e results.\u003c/p\u003e \u003cp\u003eFurthermore, Costentin et \u003cem\u003eal\u003c/em\u003e. demonstrated that patients with alcohol-related HCC have a shorter median survival compared to those with non-alcohol-related HCC\u003csup\u003e4\u003c/sup\u003e. In our cohort of HCC patients treated with sorafenib, those with alcohol-related HCC also had a shorter overall survival and progression-free survival. The induction of sorafenib resistance by alcohol suggests that sorafenib may not be effective in treating patients with alcohol-related HCC.\u003c/p\u003e \u003cp\u003eImmunotherapy is also a therapeutic approach used in the treatment of advanced HCC. The IMBrave150 study compared the efficacy of the atezolizumab-bevacizumab combination to that of sorafenib\u003csup\u003e32\u003c/sup\u003e. Atezolizumab is an antibody targeting PD-L1 (Programm Death Ligand 1) and bevacizumab is an antibody targeting VEGF, helping to prevent the inhibition of immune checkpoints. The study showed that patients treated with the atezolizumab-bevacizumab combination had a longer survival (19.2 months) compared to those treated with sorafenib (13.4 months). Due to these promising results, this combination has become the new first-line treatment for advanced HCC\u003csup\u003e32,33\u003c/sup\u003e. Therefore, it would be valuable to investigate the response to this combination in both alcohol-related and non-alcohol-related HCC. Given the differences between these etiologies, personalized treatment may be necessary to optimize outcomes.\u003c/p\u003e \u003cp\u003eFurthermore, the importance of addiction management in the treatment of alcohol-related cancers has been well established. Alcohol rehabilitation or a history of abstinence has been associated with a lower risk of alcohol-associated cancers\u003csup\u003e34\u003c/sup\u003e. The study by Costentin et \u003cem\u003eal\u003c/em\u003e. demonstrated that alcohol withdrawal increases survival in alcohol-related HCC patients, aligning their survival rates closer to those with non-alcohol-related HCC\u003csup\u003e4\u003c/sup\u003e. While alcohol cessation reduces HCC risk by 6 to 7% per year, the harmful effects can persist for decades, requiring a 23-year withdrawal period to match HCC incidence in abstinent patients\u003csup\u003e35\u003c/sup\u003e. To study alcohol withdrawal effects, our lab's chronic alcohol exposure protocol includes a one-month withdrawal period after six months of exposure. This protocol has shown that withdrawal reverses some of the aggressiveness capabilities associated with alcohol-induced HCC, such as decreased cancerous stem cell (CSC) marker expression and reduced cellular migration and invasion\u003csup\u003e16\u003c/sup\u003e. These findings underscore the importance of alcohol withdrawal in the management of HCC. Despite the importance of abstinence, addiction follow-up is not routinely implemented, only 0.9% of cancer patients are aware of resources to manage alcohol consumption\u003csup\u003e36\u003c/sup\u003e. Addiction follow-up during treatment is often lacking, making it difficult to stratify patients into abstinent and non-abstinent groups. Given this, it would be important to investigate whether alcohol withdrawal improves treatment response in HCC patients.\u003c/p\u003e \u003cp\u003eCurrently, the therapeutic strategy for HCC is primarily based on tumor grade. Our team has clearly demonstrated that HCC with an alcohol etiology is less responsive to sorafenib and exhibits increased aggressiveness, with shorter OS and PFS. Our \u003cem\u003ein vitro\u003c/em\u003e models are consistent with the clinical results, underlining the relevance and robustness of our conclusions. Moreover, the resistance induced by alcohol appears to be a class effect impacting all TKI molecules. However, the pathophysiological mechanisms underlying sorafenib resistance induced by alcohol in HCC remain poorly understood. Further research is needed to identify all the molecular factors involved and to better understand the full scope of alcohol's impact on treatment resistance. Strengthening these areas of understanding will be crucial in developing more effective, personalized therapeutic approaches for HCC patients with an alcoholic etiology.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eABC\u003c/strong\u003e : ATP-Binding Cassette\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAFP\u003c/strong\u003e : Alpha fetoprotein\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eALD :\u0026nbsp;\u003c/strong\u003eAlcohol-related liver disease\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eALT\u003c/strong\u003e : Alanine transaminase\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eANOVA\u003c/strong\u003e : Analysis of variance\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAST\u003c/strong\u003e : Aspartate transaminase\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eATE\u003c/strong\u003e : Average treatment effect\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBCLC\u003c/strong\u003e : Barcelona Clinic Liver Cancer\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCAE :\u0026nbsp;\u003c/strong\u003eChronic alcohol exposure\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCNIL\u003c/strong\u003e : Commission nationale de l\u0026apos;informatique et des libert\u0026eacute;s\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCSC :\u0026nbsp;\u003c/strong\u003eCancerous stem cell\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eECL\u0026nbsp;\u003c/strong\u003e: Enhanced ChemiLuminescence\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHBV :\u0026nbsp;\u003c/strong\u003eHepatitis B virus\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHCC :\u0026nbsp;\u003c/strong\u003eHepatocellular carcinoma\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHCV :\u0026nbsp;\u003c/strong\u003eHepatitis C virus\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIPTW\u003c/strong\u003e : Inverse probability of treatment weighting\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMASH\u003c/strong\u003e : Metabolic dysfunction-associated steatohepatitis\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMTT\u003c/strong\u003e : MethylThiazole Tetrazolium\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNP40\u003c/strong\u003e : Nonidet P40\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOS\u003c/strong\u003e : Overall survival\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePDGFR\u003c/strong\u003e : Platelet-Derived Growth Factor Receptor\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePD-L1\u003c/strong\u003e : Programm Death Ligand 1\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePFS\u003c/strong\u003e : Progression free survival\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePTH\u003c/strong\u003e : Prothrombin Time\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eR123\u003c/strong\u003e : Rhodamine123\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRECIST\u003c/strong\u003e : Response evaluation criteria in solid tumors\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRTKs\u003c/strong\u003e : \u0026nbsp;Receptor tyrosine kinases\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSMD\u003c/strong\u003e: Standardized mean difference\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTKI\u003c/strong\u003e : Tyrosine kinase inhibitor\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVEGFR\u003c/strong\u003e: Vascular Endothelial Growth Factor Receptor\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWD :\u0026nbsp;\u003c/strong\u003eWithdrawal\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eClinical trial number :\u0026nbsp;\u003c/strong\u003eThe clinical trial number ofthe CHIEF cohort is NCT04348838, registered with the number 19.04.15.41412 by the “Comité deProtection des Personnes Sud-Est IV” (RCB ID: 2019-A00679-48).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAvailability of data and material : Not applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate :\u0026nbsp;Patients are part of the CHIEF cohort (French national cohort of HCC patients, NCT04348838). All patients included provided a signed and informed consent form for the anonymous use of clinical and biological data. The study was approved by local ethics committees: “Comité de Protection des Personnes Sud-Est IV” (Agence Régionale de santé d’Auvergne-Rhône-Alpes). The study is classified as MR01 issued by «la Commission Nationale de l'Informatique et des Libertés (CNIL)».\u003c/p\u003e\n\u003cp\u003eFinancial support statement: Anoïsia Courtois is the recipient of a doctoral grant attributed by the “Ministère de l’Enseignement Supérieur, de la Recherche et de l’Innovation“(MESRI). The present work and Dr Grégory Fouquet were funded by The “Institut National du Cancer” (INCa) and “Institut pour la Recherche en Santé Publique” (IReSP) call to research projects to reduce and fight against psychoactive substances consumption and addictions grant of 2021. Damien Esparteiro was funded by \u0026nbsp;the “Region Hauts-de-France” and the Amiens-Picardie University Hospital (CHU Amiens-Picardie).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConflict of interest statement:\u0026nbsp;No conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors contributions:\u0026nbsp;CA: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Writing. MC: Investigation, Methodology, Resources. FG: Investigation, Methodology, Resources. DM: Investigation. ED: Writing. DG: Investigation. ML: Investigation. NM: Funding acquisition, Validation, Writing—review. NKE: Funding acquisition, Project administration,\u0026nbsp;Clinical data provinding, Supervision, Writing. MI\u0026nbsp;: Conceptualization, Data curation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing, Writing—review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements :\u0026nbsp;\u003c/strong\u003eWe thank Pr Loïc Garçon and his research team HEMATIM EA4666 for the flow cytometry technique. We also acknowledge the contribution of the Genetics department of the Amiens University Hospital for their expertise in sequencing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGanne-Carri\u0026eacute; N, Nahon P. Hepatocellular carcinoma in the setting of alcohol-related liver disease. \u003cem\u003eJ Hepatol\u003c/em\u003e. 2019;70(2):284-293. doi:10.1016/j.jhep.2018.10.008\u003c/li\u003e\n\u003cli\u003eCeni E, Mello T, Galli A. Pathogenesis of alcoholic liver disease: Role of oxidative metabolism. \u003cem\u003eWorld J Gastroenterol\u003c/em\u003e. 2014;20(47):17756-17772. doi:10.3748/wjg.v20.i47.17756\u003c/li\u003e\n\u003cli\u003eCancer Today. Accessed September 11, 2024. https://gco.iarc.who.int/today/\u003c/li\u003e\n\u003cli\u003eCostentin CE, Mourad A, Lahmek P, et al. Hepatocellular carcinoma is diagnosed at a later stage in alcoholic patients: Results of a prospective, nationwide study: Delayed Diagnosis of Alcohol-Related HCC. \u003cem\u003eCancer\u003c/em\u003e. 2018;124(9):1964-1972. doi:10.1002/cncr.31215\u003c/li\u003e\n\u003cli\u003eMak LY, Cruz-Ram\u0026oacute;n V, Chinchilla-L\u0026oacute;pez P, et al. Global Epidemiology, Prevention, and Management of Hepatocellular Carcinoma. \u003cem\u003eAm Soc Clin Oncol Educ Book\u003c/em\u003e. 2018;(38):262-279. doi:10.1200/EDBK_200939\u003c/li\u003e\n\u003cli\u003eVogel A, Meyer T, Sapisochin G, Salem R, Saborowski A. Hepatocellular carcinoma. \u003cem\u003eThe Lancet\u003c/em\u003e. 2022;400(10360):1345-1362. doi:10.1016/S0140-6736(22)01200-4\u003c/li\u003e\n\u003cli\u003eLlovet JM, Ricci S, Mazzaferro V, et al. Sorafenib in Advanced Hepatocellular Carcinoma. \u003cem\u003eN Engl J Med\u003c/em\u003e. 2008;359(4):378-390. doi:10.1056/NEJMoa0708857\u003c/li\u003e\n\u003cli\u003eWilhelm SM, Carter C, Tang L, et al. BAY 43-9006 Exhibits Broad Spectrum Oral Antitumor Activity and Targets the RAF/MEK/ERK Pathway and Receptor Tyrosine Kinases Involved in Tumor Progression and Angiogenesis. \u003cem\u003eCancer Res\u003c/em\u003e. 2004;64(19):7099-7109. doi:10.1158/0008-5472.CAN-04-1443\u003c/li\u003e\n\u003cli\u003eYang JD, Hainaut P, Gores GJ, Amadou A, Plymoth A, Roberts LR. A global view of hepatocellular carcinoma: trends, risk, prevention and management. \u003cem\u003eNat Rev Gastroenterol Hepatol\u003c/em\u003e. 2019;16(10):589-604. doi:10.1038/s41575-019-0186-y\u003c/li\u003e\n\u003cli\u003eLlovet JM, Castet F, Heikenwalder M, et al. Immunotherapies for hepatocellular carcinoma. \u003cem\u003eNat Rev Clin Oncol\u003c/em\u003e. 2022;19(3):151-172. doi:10.1038/s41571-021-00573-2\u003c/li\u003e\n\u003cli\u003eReig M, Forner A, Rimola J, et al. BCLC strategy for prognosis prediction and treatment recommendation: The 2022 update. \u003cem\u003eJ Hepatol\u003c/em\u003e. 2022;76(3):681-693. doi:10.1016/j.jhep.2021.11.018\u003c/li\u003e\n\u003cli\u003eTang W, Chen Z, Zhang W, et al. The mechanisms of sorafenib resistance in hepatocellular carcinoma: theoretical basis and therapeutic aspects. \u003cem\u003eSignal Transduct Target Ther\u003c/em\u003e. 2020;5(1):87. doi:10.1038/s41392-020-0187-x\u003c/li\u003e\n\u003cli\u003eNiu L, Liu L, Yang S, Ren J, Lai PBS, Chen GG. New insights into sorafenib resistance in hepatocellular carcinoma: Responsible mechanisms and promising strategies. \u003cem\u003eBiochim Biophys Acta BBA - Rev Cancer\u003c/em\u003e. 2017;1868(2):564-570. doi:10.1016/j.bbcan.2017.10.002\u003c/li\u003e\n\u003cli\u003eDi Giacomo S, Briz O, Monte MJ, et al. Chemosensitization of hepatocellular carcinoma cells to sorafenib by \u0026beta;-caryophyllene oxide-induced inhibition of ABC export pumps. \u003cem\u003eArch Toxicol\u003c/em\u003e. 2019;93(3):623-634. doi:10.1007/s00204-019-02395-9\u003c/li\u003e\n\u003cli\u003eLeung CON, Tong M, Chung KPS, et al. Overriding Adaptive Resistance to Sorafenib Through Combination Therapy With Src Homology 2 Domain\u0026ndash;Containing Phosphatase 2 Blockade in Hepatocellular Carcinoma. \u003cem\u003eHepatology\u003c/em\u003e. 2020;72(1):155-168. doi:10.1002/hep.30989\u003c/li\u003e\n\u003cli\u003eMari\u0026eacute; C, Fouquet G, Courtois A, et al. Mechanisms of chronic alcohol exposure-induced aggressiveness in cellular model of HCC and recovery after alcohol withdrawal. \u003cem\u003eCell Mol Life Sci\u003c/em\u003e. 2022;79(7):366. doi:10.1007/s00018-022-04387-y\u003c/li\u003e\n\u003cli\u003ePfister D, N\u0026uacute;\u0026ntilde;ez NG, Pinyol R, et al. NASH limits anti-tumour surveillance in immunotherapy-treated HCC. \u003cem\u003eNature\u003c/em\u003e. 2021;592(7854):450-456. doi:10.1038/s41586-021-03362-0\u003c/li\u003e\n\u003cli\u003eHeinrich B, Brown ZJ, Diggs LP, et al. Steatohepatitis Impairs T-cell\u0026ndash;Directed Immunotherapies Against Liver Tumors in Mice. \u003cem\u003eGastroenterology\u003c/em\u003e. 2021;160(1):331-345.e6. doi:10.1053/j.gastro.2020.09.031\u003c/li\u003e\n\u003cli\u003eMeyer T, Galani S, Lopes A, Vogel A. Aetiology of liver disease and response to immune checkpoint inhibitors: An updated meta-analysis confirms benefit in those with non-viral liver disease. \u003cem\u003eJ Hepatol\u003c/em\u003e. 2023;79(2):e73-e76. doi:10.1016/j.jhep.2023.04.012\u003c/li\u003e\n\u003cli\u003eRossari F, Tada T, Suda G, et al. Disease Etiology Impact on Outcomes of Hepatocellular Carcinoma Patients Treated with Atezolizumab plus Bevacizumab: A Real-World, Multicenter Study. \u003cem\u003eLiver Cancer\u003c/em\u003e. 2024;13(5):522-536. doi:10.1159/000537915\u003c/li\u003e\n\u003cli\u003eEisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1). \u003cem\u003eEur J Cancer\u003c/em\u003e. 2009;45(2):228-247. doi:10.1016/j.ejca.2008.10.026\u003c/li\u003e\n\u003cli\u003eLove MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. \u003cem\u003eGenome Biol\u003c/em\u003e. 2014;15(12):550. doi:10.1186/s13059-014-0550-8\u003c/li\u003e\n\u003cli\u003eChow AKM, Ng L, Lam CSC, et al. The Enhanced Metastatic Potential of Hepatocellular Carcinoma (HCC) Cells with Sorafenib Resistance. Takehara T, ed. \u003cem\u003ePLoS ONE\u003c/em\u003e. 2013;8(11):e78675. doi:10.1371/journal.pone.0078675\u003c/li\u003e\n\u003cli\u003eTomonari T, Takeishi S, Taniguchi T, et al. MRP3 as a novel resistance factor for sorafenib in hepatocellular carcinoma. \u003cem\u003eOncotarget\u003c/em\u003e. 2016;7(6):7207-7215. doi:10.18632/oncotarget.6889\u003c/li\u003e\n\u003cli\u003eFouquet G, Mari\u0026eacute; C, Collet L, et al. Rescuing SLAMF3 Expression Restores Sorafenib Response in Hepatocellular Carcinoma Cells through the Induction of Mesenchymal-to-Epithelial Transition. \u003cem\u003eCancers\u003c/em\u003e. 2022;14(4):910. doi:10.3390/cancers14040910\u003c/li\u003e\n\u003cli\u003eMa Y, Xu R, Liu X, et al. LY3214996 relieves acquired resistance to sorafenib in hepatocellular carcinoma cells. \u003cem\u003eInt J Med Sci\u003c/em\u003e. 2021;18(6):1456-1464. doi:10.7150/ijms.51256\u003c/li\u003e\n\u003cli\u003eMoon H, Ro SW. MAPK/ERK Signaling Pathway in Hepatocellular Carcinoma. \u003cem\u003eCancers\u003c/em\u003e. 2021;13(12):3026. doi:10.3390/cancers13123026\u003c/li\u003e\n\u003cli\u003eZhang H, Xia Y, Wang F, et al. Aldehyde Dehydrogenase 2 Mediates Alcohol‐Induced Colorectal Cancer Immune Escape through Stabilizing PD‐L1 Expression. \u003cem\u003eAdv Sci\u003c/em\u003e. 2021;8(10):2003404. doi:10.1002/advs.202003404\u003c/li\u003e\n\u003cli\u003eZhu Z, Hao X, Yan M, et al. Cancer stem/progenitor cells are highly enriched in CD133\u003csup\u003e+\u003c/sup\u003e CD44\u003csup\u003e+\u003c/sup\u003e population in hepatocellular carcinoma. \u003cem\u003eInt J Cancer\u003c/em\u003e. 2010;126(9):2067-2078. doi:10.1002/ijc.24868\u003c/li\u003e\n\u003cli\u003eLuo X, Zheng E, Wei L, et al. The fatty acid receptor CD36 promotes HCC progression through activating Src/PI3K/AKT axis-dependent aerobic glycolysis. \u003cem\u003eCell Death Dis\u003c/em\u003e. 2021;12(4):328. doi:10.1038/s41419-021-03596-w\u003c/li\u003e\n\u003cli\u003eFeng WW, Zuppe HT, Kurokawa M. The Role of CD36 in Cancer Progression and Its Value as a Therapeutic Target. \u003cem\u003eCells\u003c/em\u003e. 2023;12(12):1605. doi:10.3390/cells12121605\u003c/li\u003e\n\u003cli\u003eQin S, Ren Z, Feng YH, et al. Atezolizumab plus Bevacizumab versus Sorafenib in the Chinese Subpopulation with Unresectable Hepatocellular Carcinoma: Phase 3 Randomized, Open-Label IMbrave150 Study. \u003cem\u003eLiver Cancer\u003c/em\u003e. 2021;10(4):296-308. doi:10.1159/000513486\u003c/li\u003e\n\u003cli\u003eLlovet JM, Kelley RK, Villanueva A, et al. Hepatocellular carcinoma. \u003cem\u003eNat Rev Dis Primer\u003c/em\u003e. 2021;7(1):6. doi:10.1038/s41572-020-00240-3\u003c/li\u003e\n\u003cli\u003eSchwarzinger M, Ferreira-Borges C, Neufeld M, Alla F, Rehm J. Alcohol rehabilitation and cancer risk: a nationwide hospital cohort study in France. \u003cem\u003eLancet Public Health\u003c/em\u003e. 2024;9(7):e461-e469. doi:10.1016/S2468-2667(24)00107-5\u003c/li\u003e\n\u003cli\u003eGriswold MG, Fullman N, Hawley C, et al. Alcohol use and burden for 195 countries and territories, 1990\u0026ndash;2016: a systematic analysis for the Global Burden of Disease Study 2016. \u003cem\u003eThe Lancet\u003c/em\u003e. 2018;392(10152):1015-1035. doi:10.1016/S0140-6736(18)31310-2\u003c/li\u003e\n\u003cli\u003eHamant C, Deneuve S, Albaret MA, et al. Accompagnement des d\u0026eacute;pendances \u0026agrave; l\u0026rsquo;alcool et au tabac des patients atteints d\u0026rsquo;un cancer des voies a\u0026eacute;rodigestives sup\u0026eacute;rieures. \u003cem\u003eBull Cancer (Paris)\u003c/em\u003e. 2018;105(11):1012-1019. doi:10.1016/j.bulcan.2018.07.006\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-molecular-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jmme","sideBox":"Learn more about [Journal of Molecular Medicine](https://www.springer.com/journal/109)","snPcode":"109","submissionUrl":"https://submission.nature.com/new-submission/109/3","title":"Journal of Molecular Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Hepatocellular carcinoma, Alcohol, Sorafenib, Resistance","lastPublishedDoi":"10.21203/rs.3.rs-6837338/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6837338/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Alcohol is a major cause of hepatocellular carcinoma (HCC), accounting for 30% of cases worldwide. Sorafenib, a tyrosine kinase inhibitor (TKI), was the standard first-line treatment for advanced HCC until 2021, but sorafenib resistance is common. We explored the impact of chronic alcohol exposure (CAE) on sorafenib response and sought to identify associated resistance mechanisms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Huh-7 HCC cells were chronically exposed to alcohol for 6 months. Sorafenib resistance was assessed by measuring cell viability (IC50) and evaluating the protein expression of signaling pathways involved in resistance using immunoblotting. RNA sequencing was performed to identify mechanisms of resistance. Sorafenib response was assessed with RECIST 1.1 criteria in HCC patients. A retrospective study of 86 CHIEF cohort HCC patients (alcohol-related vs. non-alcohol-related etiologies) evaluated overall survial (OS) and progression-free survival (PFS) using the log-rank test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e CAE significantly decreased cell sensitivity to sorafenib (\u003cem\u003ep=0.006\u003c/em\u003e), indicating increased resistance. The ERK pathway was involved. RNA sequencing of our cells identified a total of 80 differencially expressed genes associated with drug resistance and aggressiveness. Clinically, alcohol-related HCC patients were less responsive to sorafenib (35% responders vs. 65%, \u003cem\u003ep=0.014\u003c/em\u003e) and had significantly different OS (\u003cem\u003ep=0.0234\u003c/em\u003e). Median OS was 10 months (95% CI=[6.1; 15.7]) for alcohol-related HCC and 12.1 months (95% CI=[7.7; 64.9]) for other etiologies. PFS was lower in the alcohol group (5.72 months (95% CI=[4.63 ;12.8]) vs. 9.66 months (95% CI=[4.40 ; 39.9], \u003cem\u003ep=0.0298\u003c/em\u003e)).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Sorafenib resistance due to chronic alcohol consumption is consistent in both in vitro models and clinical settings.\u003c/p\u003e","manuscriptTitle":"Alcohol induces sorafenib resistance in hepatocellular carcinoma: A Translational Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-01 07:26:13","doi":"10.21203/rs.3.rs-6837338/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major Revisions Needed","date":"2025-12-09T05:25:43+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-07-07T10:36:08+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-23T21:18:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-12T05:23:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Molecular Medicine","date":"2025-06-11T03:46:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-molecular-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jmme","sideBox":"Learn more about [Journal of Molecular Medicine](https://www.springer.com/journal/109)","snPcode":"109","submissionUrl":"https://submission.nature.com/new-submission/109/3","title":"Journal of Molecular Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"2f0777c2-6b04-4367-9243-d0b4e7ee926c","owner":[],"postedDate":"July 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-26T16:02:37+00:00","versionOfRecord":{"articleIdentity":"rs-6837338","link":"https://doi.org/10.1007/s00109-026-02645-1","journal":{"identity":"journal-of-molecular-medicine","isVorOnly":false,"title":"Journal of Molecular Medicine"},"publishedOn":"2026-01-25 15:59:14","publishedOnDateReadable":"January 25th, 2026"},"versionCreatedAt":"2025-07-01 07:26:13","video":"","vorDoi":"10.1007/s00109-026-02645-1","vorDoiUrl":"https://doi.org/10.1007/s00109-026-02645-1","workflowStages":[]},"version":"v1","identity":"rs-6837338","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6837338","identity":"rs-6837338","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}