Loss of TP53 cooperates with c-MET overexpression to drive hepatocarcinogenesis

Loss of TP53 cooperates with c-MET overexpression to drive hepatocarcinogenesis | 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 Article Loss of TP53 cooperates with c-MET overexpression to drive hepatocarcinogenesis Xin Chen, Yi Zhou, Guofei Cui, Hongwei Xu, Joanne Chu, Zheng Zhang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2176178/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Jul, 2023 Read the published version in Cell Death & Disease → Version 1 posted 9 You are reading this latest preprint version Abstract Hepatocellular carcinoma (HCC) is a deadly malignancy with high genetic heterogeneity. TP53 loss of function (LOF) mutation and c-MET activation are frequent events in human HCCs. Here, we discovered that the simultaneous LOF mutations in TP53 and activation of c-MET occur in ~ 20% of human HCCs, and these patients show a poor prognosis. Importantly, we found that concomitant deletion of Trp53 and overexpression of c-MET (c-MET/sgp53) in the mouse liver led to HCC formation in vivo . Consistent with human HCCs, RNAseq showed that c-MET/sgp53 mouse HCCs were characterized by activated c-MET and Ras/MAPK cascades and increased tumor cell proliferation. Subsequently, a stably passaged cell line derived from a c-MET/sgp53 HCC and corresponding subcutaneous xenografts were generated. Also, in silico analysis suggested that the MEK inhibitor trametinib has a higher inhibition score in TP53 null human HCC cell lines, which was validated experimentally. We consistently found that trametinib effectively inhibited the growth of c-MET/sgp53 HCC cells and xenografts, supporting the possible usefulness of this drug for treating human HCCs with TP53 -null mutations. Altogether, our study demonstrates that loss of TP53 cooperates with c-MET to drive hepatocarcinogenesis in vivo. The c-MET/sgp53 mouse model and derived HCC cell lines represent novel and useful preclinical tools to study hepatocarcinogenesis in the TP53 null background. Biological sciences/Cancer/Gastrointestinal cancer/Liver cancer Health sciences/Medical research/Experimental models of disease hepatocellular carcinoma p53 c-MET preclinical model Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Primary liver cancer is one of the most common malignant tumors worldwide. Hepatocellular carcinoma (HCC) is the predominant tumor entity, accounting for 75%-85% of the cases 1 . HCC is often associated with chronic liver disease, which causes liver cell death, inflammation, oxidative stress, and fibrosis. At the molecular level, HCC is driven by heterogeneous signaling pathways that produce DNA damage to liver cells, resulting in resistance to cell death, proliferation, and eventually tumorigenesis 2 . Though targeted therapies and immunization treatments for HCC have been extensively investigated, only a few multi-kinase and immune checkpoint inhibitors have been approved for advanced HCCs 3 . Therefore, identifying the specific aberrant molecular pathways that drive hepatocarcinogenesis and generating preclinical models to explore targeted treatments are essential for HCC patients. The TP53 (p53) gene is one of the most critical tumor suppressors. The p53 protein encoded by TP53 is involved in various pathways to regulate multiple processes, such as metabolism, DNA damage repair, cell cycle arrest, and apoptosis. As in other cancer types, TP53 mutation is also one of the main genetic variations in HCC. Accounting for about 30% of HCC cases, TP53 inactivating mutations contribute to HCC initiation and progression 4 , 5 , 6 . In addition, reactivating p53 in tumors with p53 inactivation can induce tumor stabilization or regression 7 , 8 . Therefore, drugs targeting p53 loss of function could represent a promising approach for HCC treatment. MET (c-MET) is a protooncogene that encodes the hepatocyte growth factor (HGF) receptor. Binding to HGF, c-MET activates multiple downstream targets, such as the RAS/MAPK and phosphoinositide 3-kinase (PI3K)/AKT pathways, to drive tumor invasion and metastasis 9 . Previous studies have shown that c-MET activation occurs in 20–44% of HCC patients, and increased expression of c-MET is associated with poor tumor differentiation, augmented intrahepatic metastases, and poor prognosis 10 , 11 . However, c-MET alone cannot induce HCC in mice but requires the presence of additional molecular events, such as AKT overexpression, ꞵ-Catenin activation, or loss of the PTEN oncosuppressor to drive liver malignant transformation 12 , 13 , 14 . Gene expression analysis of HCC specimens from the TGGA database suggests that samples with TP53 mutations are more likely to show upregulation of the c-MET signature. Specifically, about 21% of the HCC patients have both c-MET activation features and LOF TP53 mutations. Clinically, these HCCs are associated with poor patients' prognosis. Therefore, we speculate that LOF TP53 mutations can synergize with c-MET activation to induce hepatocyte malignant transformation. In this study, we established and characterized a novel murine HCC model induced by overexpression of c-MET and CRISPR-Cas9 mediated knockout of Trp53 (encoding mouse p53). In addition, we applied this model for therapeutic testing. Materials And Methods Plasmids and reagents The plasmids used in this study, including pT3-EF1α-c-MET (human c-MET or hMET) and pCMV-sleeping beauty transposase (SB) have been described in our previous studies 13 , 15 , 16 . pX330-sgp53 plasmid was obtained from Addgene (#59910). Plasmids were purified using the Endotoxin free Maxi prep kit (Sigma-Aldrich, St. Louis, MO, USA). Cabozantinib and tametinib were purchased from LC Laboratories (Woburn, MA, USA). Niclosamide and metformin were obtained from Sigma-Aldrich (St. Louis, MO, USA). Hydrodynamic Tail Vein Injection FVB/N mice were obtained from Charles River Laboratories (Wilmington, MA, USA). To generate the c-Met/sgp53 HCC model, 20µg pT3-EF1α-c-MET and 20/40 µg pX330-sgp53 along with 0.8µg pCMV/SB plasmids in 2ml saline (0.9%NaCl) were delivered to 6 ~ 8 week-old mice (half male and half female) by hydrodynamic tail vein injection. Mice were housed, fed and monitored in accordance with protocols approved by the Committee for Animal Research at the University of California, San Francisco and the University of Hawaii Cancer Center. Generating The Stably Passaged Cell Line From C-met/sgp53 Hcc Mice were humanely euthanized and rinsed in 70% ethanol. Liver tumor (2-3g) was dissected, washed in PBS and minced into ~ 1mm fragments using scalpel blade. All procedures were operated in the hood using autoclaved dissecting tools. The tumor fragments were digested with 0.6 mg/L collagenase (Sigma-Aldrich, C5138) in 37°C for 15 ~ 30min, then filtered through 100 µm nylon mesh cell strainer (BD, 352360) and spined (700-1000rpm, 5 min). The cell pellet were resuspended and cultured in 5 ml DMEM with 10% fetal bovine serum (FBS) and 1% Penicillin/Streptomycin at 37°C and 5% CO 2 for ~ 4 weeks. The primary liver tumor cells were generated. In order to obtain a stablely passaged cell line, 1×10 7 primary tumor cells were injected into flanks of 6 ~ 8 week-old FVB/N mice. When the subcutaneous tumor developed, tumor tissue was dissected into small pieces and digested with trypsin (Sigma-Aldrich, T4049). The new generation of liver tumor cells (P0) were cultured and passaged in vitro for 3 times. Then 1×10 7 “P0” cells were implanted into the flanks of a new recipient FVB/N mouse. These procedures were repeated for three rounds. The stably passaged cell line from c-MET/sgp53 HCC (MP cell) was finally generated. Mice Xenografts And Treatment To develop mice xenografts, 200µl (1×10 7 MP cells) suspension of tumor cells in Matrigel (Corning, 354248) were inoculated subcutaneously into the right flank of 6 ~ 8 week-old FVB/N mice (females). On day 14 post implantation, when the tumor size reached to about 100 to 150 mm 3 , mice were randomized into 5 groups for treatment. Metformin (250mg/kg/day), niclosamide (100mg/kg/day), cabozantinib (60mg/kg/day), trametinib (1mg/kg/day) or vehicle was orally administered daily via gavage. Tumor volume was measured every three days and estimated from caliper using the formula V = A×B 2 /2 (A is largest diameter, B is smallest diameter). Body weight was measured everyday. After three weeks treatment, all mice were sacrificed and tumors were harvested for further analysis. Hcc Cell Lines The following human HCC cell lines which used in this study: LM9, HLE, HepG2 and Hep3B, were obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA). In addition, HCC3-4 and HCC4-4 cell lines, isolated from c-Myc mouse liver tumors, were kindly provided by Dr. Felsher of Stanford University. All cell lines were grown in Dulbecco's Modified Eagle Medium (DMEM) supplemented with 10% FBS and penicillin/streptomycin (Gibco, Grand Island, NY, USA) in 5% CO 2 atmosphere, at 37°C. For IC50 determination, cells were seeded in 24-well plates and treated with gradient concentration of trametinib in triplicate for 48 hours. Then cells were enumerated by crystal violet staining. After washing, stained cells were incubated in lysis solution and shaken gently on a rocking shaker for 10 min. Diluted lysate solutions were added to 96-well plates and OD value was measured at 590 nm with the BioTek ELX808 Absorbance Microplate Reader (ThermoFisher Scientific, MA, USA). The IC50 values were calculated using the Prism 9.0 software (GraphPad Software Inc). All experiments were repeated at least three times. Histology And Immunohistochemistry Mouse liver tissues and tumor tissues were fixed in 4% paraformaldehyde, embedded in paraffin and sectioned at 5µm. Then, hematoxylin and eosin (H&E) and immunohistochemical staining were performed. For antigen retrieval, de-paraffinized slides were incubated in antigen retrieval buffer (10mM sodium citrate buffer, pH 6.0) and microwaved for 10 min. After a blocking step with the 5% goat serum and Avidin-Biotin blocking kit (Vector Laboratories Inc., Burlingame, CA), the sections were incubated with the primary antibodies overnight at 4°C. To quench endogenous peroxidase, slides were then subjected to 3% hydrogen peroxide for 10 min and subsequently the secondary antibody was applied for 30 min at room temperature. The immunoreactivity was visualized with the Vectastain ABC Elite kit (Vector Laboratories Inc.) and DAB (Vector Laboratories, Inc.). Slides were counterstained with hematoxylin. The following primary antibodies were used in the present investigation: anti-p53 (sc-126; Santa Cruz, CA, USA), anti-CK19 (ab52625; Abcam, Cambridge, United Kingdom), anti-HNF4a (ab18604; Abcam, Cambridge, United Kingdom), anti-Ki67 (MA5-14520; Thermo Fisher Scientific, MA, USA), and anti-p-ERK (4370; Cell Signaling Technology, MA, USA) were used in the present investigation. Protein Extraction And Western Blot Analysis Protein extraction and Western blot analysis Frozen liver tumors were homogenized in Mammalian Protein Extraction Reagent (Thermo Fisher Scientific, MA, USA) containing the Complete Protease Inhibitor Cocktail (Thermo Fisher Scientific, MA, USA). Protein concentrations were determined with the Bio-Rad Protein Assay Kit (Bio-Rad, CA, USA). Supernatant was denatured by boiling in 2×Laemmli sample buffer (1610737, Bio-Rad, CA, USA). Equal loading was assessed by GAPDH or β-actin. Aliquots of 30 µg protein lysates were separated by SDS-PAGE (M00654, GenScript, Piscataway, NJ, USA) and transferred onto PVDF membranes (Bio-Rad, CA, USA). Membranes were blocked in 10% non-fat milk in Tris-buffered saline containing 0.05% Tween-20, and incubated with primary antibodies at 4°C overnight. Then membranes were incubated with horseradish peroxidase-secondary antibody (Jackson ImmunoResearch Laboratories Inc., PA, USA) for 1 hour at room temperature and developed with ClarityTM Western ECL Substrate (170–5061, Bio-Rad Laboratories, Hercules, CA, USA). The antibodies used are as follows: anti-p53 (sc-126; Santa Cruz, CA, USA), anti-c-MET (71-8000; Invitrogen,CA, USA), anti-p-MET Tyr1234/1235 (3077, Cell Signaling Technology, MA, USA), anti-ERK1/2 (9102; Cell Signaling Technology, MA, USA) and anti-p-ERK1/2 Thr202/Tyr204 (4370; Cell Signaling Technology, MA, USA), anti-GAPDH (5174; Cell Signaling Technology, MA, USA) and anti-β-actin (4970; Cell Signaling Technology, MA, USA). Mouse Genomic Dna Extraction And Sequencing Mouse genomic DNA was extracted from frozen mouse tissue samples using the Mouse Direct PCR Kit, according to the manufacturer's instructions (Biomake, TX, USA). The amplification conditions were 94°C for 5 min, followed by 35 cycles of 94°C for 20 s, 50°C for 30 s, and 72°C for 30 s. The sequences of the primers are as follows: Forward:CCTACTGGATGTCCCACCTTCT; Reverse:CAGACACCCAACACCATACCA. For individual clonal sequencing, PCR products were purified and inserted to pGEM®-T Easy Vector (Promega, WI, USA) according to the manufacturer's instructions.Clones were cultured and plasmids were extracted using Zyppy Plasmid Miniprep kit (Genesee Scientific, CA, USA). The inserted sequence was subsequently sequenced using T7 primers. Rnaseq Analysis Total RNA was extracted from mouse sgp53/c-MET HCCs (n = 3) and FVB/N normal livers (n = 3) using Quick-RNA Miniprep Kit (Zymo Research, CA, USA). The RNA quality control was determined using Agilent RNA 6000 Nano Kit (Agilent Technologies, CA, USA) and Bioanalyzer (Agilent Technologies, CA, UAS). Library preparation and sequencing were performed by Novogene (Sacramento, CA, USA). All analyses were performed in R.Experimental design had 2 groups: “MP” (sgp53/c-MET) and “NL” (FVB/N normal liver). Poor quality reads were trimmed using the fastq-mcf (1.05). Reads quality was checked using the fastqc (v0.11.7). Gene read counts were in Ensembl Gene ID and converted to Entrez Gene ID. Corresponding Symbol annotations and full gene names were added using the “org.Mm.eg.db” library. NA (Not Annotated), duplicate Entrez IDs and genes without symbols were removed. Only the genes having CPM values above 0.5 in at least two libraries were kept. Normalization by TMM (Trimmed mean of M values) was performed by using calcNormFactors function to eliminate composition biases between libraries. R package “edgeR” and glmTreat function were used to identify differentially expressed genes (DEGs). DEGs were limited by a p value of 0.05 and FDR (False Discovery Rate) of 0.05. Total numbers of genes involved, Number of up-regulated genes, Number of down-regulated genes, p value, and Direction of Regulation were obtained for each Gene Ontology analysis. List of DEGs for each Gene Ontology was created for all the comparisons by p value of 0.05 and FDR of 0.05. Genes were mapped to KEGG Pathways using GO.db package, kegga function which obtains the KEGG annotations from http://rest.kegg.jpwebsite . Human Data Hcc Tcga Retrieval And Analysis To investigate the relationship with c-MET activation and TP53 mutation status in human HCC samples, TGCA data set were retrieved based on the the cBioPortal for Cancer Genomics ( http://www.cbioportal.org ). The overall sample size is 410, including 50 surrounding liver tissues (ST) and 360 HCC samples with TP53 mutation data. RNA sequencing data were analyzed in R using multiple packages. Data were normalized using calcNormFactors function to eliminate composition biases between libraries. Gene symbol annotations and full gene names were added using the “org.Hs.eg.db” library. The analysis of c-MET activation status was performed as previously described 15 . In brief, we extracted genes from the “KAPOSI_LIVER_CANCER_MET_UP” gene set, which contains 18 genes which were upregulated in liver cancer samples in response to c-MET activation. FRY gene set test was applied to investigate the enrichment of the c-MET_UP genes in HCC samples. Mann-Whitney test was used for comparison of different gene expression between the ST and TP53 mutated groups. And Fisher’s exact test was employed to compare the difference in composition of samples with c-MET up signature in ST and TP53 mutated groups. Heatmap was generated using Complex heatmap package 17 in R. We standardized the data with mean as 0 and standard deviation (SD) as 1 and ordered by ascending Average of 18-gene expression of each sample from left to right. As the weight of each gene is 1 in this gene set, samples with Averages more than the Average plus 1.5-fold SD of the ST group was considered as HCC with “c-MET activation”. Tissue types and mutation information was also included in the heatmap. Statistical analysis The Prism 9.0 software (GraphPad Software Inc) was used to analyze the data. Statistical analysis was performed using Student’s t-test, Mann-Whitney test, Welch’s t test and Log-rank (Mantel-Cox) test analyses. The data were expressed as the mean ± SD (*, P < 0.05; **, P < 0.01; ***, P < 0.001) of at least three independent experiments. Results c-MET activation and TP53 mutations occur concomitantly in a subset of human HCCs c-MET overexpression and LOF TP53 mutation are two frequent alterations reported in human HCC. To investigate the profile of these genetic aberrations, we analyzed the expression level of c-MET and LOF TP53 mutation status based on The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA LIHC) human HCC dataset 18 . The c-MET activation signature was identified using the KAPOSI_LIVER_CANCER_MET_UP gene set 19 , described previously 15 . First, we determined the c-MET activation signature in LOF TP53 mutant and TP53 wild-type samples. The results showed that the c-MET signature was enriched in LOF TP53 mutant human HCC samples (Fig. 1 A). Indeed, ~ 71% of TP53 mutant HCCs (79/111) in the TCGA dataset showed the activated c-MET signature. In comparison, only 55% of TP53 wild-type HCCs (136/249) showed high c-MET expression (Fig. 1 B). Further analysis showed that in human HCC, ~ 22% of specimens displayed concomitant LOF TP53 mutation and c-MET activation. Importantly, these HCC patients exhibited the shortest overall survival (Fig. 1 C). In summary, LOF TP53 mutation and c-MET activation co-occur in a subset of human HCC patients with poor prognoses. Deletion of Trp53 synergizes with activated c-MET to promote HCC formation in mice Our previous work suggested that long-term overexpression of c-MET alone by hydrodynamic injection in the mouse liver does not trigger liver tumor development while giving rise to dysplastic clear-cell foci 15 , 20 . Similarly, sporadic loss of TP53 in the mouse liver does not induce liver tumor formation 21 . Therefore, we hypothesized that the simultaneous deletion of TP53 and expression of c-MET might lead to hepatocarcinogenesis in mice. Using the CRISPR-Cas9-mediated gene editing method, we stably deleted Trp53 in mouse hepatocytes using the pX330-sgP53 plasmid 21 . The pX330-sgp53 construct was co-expressed with the pT3-EF1α-c-MET and pCMV-SB constructs via hydrodynamic tail-vein injection (c-MET/sgp53) (Fig. 2 A). Consistent with our hypothesis, c-MET/sgp53 combination was able to induce liver tumor formation in vivo (Table S2). Gross tumor nodules were observed in the mouse liver between 20 and 30 weeks post-injection. Tumors varied in size, and histological evaluation revealed that the tumor lesions were consistent with well-differentiated HCC. No extrahepatic metastases developed in these mice. In addition, tumors were characterized by positive HNF-4a immunoreactivity, negative CK19 staining, and high Ki67 immunolabeling (Fig. 2 B). Gene expression analysis demonstrated the upregulation of HCC-related genes, including Afp , Gpc3 , and Prom1 , as well as genes associated with cell proliferation, such as Ccnb1 , Ccne1 , Cdk6, Bub1 , and Mki67 in c-MET/sgp53 tumors (Fig. S1). Furthermore, immunohistochemical (IHC) staining and Western blotting verified the efficient deletion of p53 in the HCC lesions. Western blot analysis also revealed the overexpression of c-MET and the corresponding phosphorylation/activation of c-MET (p-MET). Moreover, c-MET/sgp53 tumor lesions exhibited phosphorylation/activation of the ERK signaling (p-ERK) (Fig. 2 C and Fig. S2). To further validate the effective deletion of the Trp53 gene in c-MET/sgp53 HCCs, we performed genome sequencing on mouse Trp53 alleles in tumor nodules. The Sanger sequencing confirmed the nucleotide deletions of Trp53 on its genomic locus (Fig. S3). Global Gene Expression Profiling Reveals The Activation Of Ras/mapk Cascades In C-met/sgp53 Lesions To fully understand the molecular signatures of c-MET/sgp53 HCCs, we performed RNA sequencing of tissues from normal mouse livers (n = 3) and c-MET/sgp53 liver tumors (n = 3). The heatmap of the gene list showed genetic dissimilarities between the two groups (Fig. 3 A). The differentially expressed genes (DEG) analysis identified 2651 genes that were significantly up-regulated in c-MET/sgp53 HCC samples (fold change, > 1.5; P adj < 0.05) (Fig. S4A and Table S1). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the up-regulated genes were enriched in tumor-associated pathways, including pathways in cancer, focal adhesion, ECM–receptor interaction, and cell cycle, in c-MET/sgp53 HCCs versus normal livers (Fig. 3 B and Fig. S4B). Interestingly, KEGG analysis showed DEGs significantly enriched in the MAPK signaling pathway (Fig. 3 B and Fig. S4B). The corresponding heatmap showed differential expression of MAPK cascade correlated genes in c-MET/sgp53 mouse HCCs compared to normal livers (Fig. S5). To further model c-MET/sgp53 mouse liver tumors to human HCCs, we analyzed a subset of human HCC samples harboring concomitant c-MET activation and TP53 deletion using the TCGA-LIHC dataset, which occurred in 23/360 HCC specimens (Fig. S6A). Multidimensional scaling (MDS) analysis showed genetic dissimilarity among the samples in c-MET-high/TP53-null human HCCS and surrounding tissues (Fig. S6B). Compared to surrounding liver tissues, 2817 genes were up-regulated (fold change, > 1.5; P adj < 0.05) in c-MET-high/ TP53 -null HCC samples, among which 521 genes were also up-regulated in c-MET/sgp53 mouse HCCs (Fig. S4A). KEGG pathway analysis revealed that up-regulated genes were enriched in cancer-related pathways (Fig. S6C). In addition, the 521 overlapping up-regulated genes were mainly enriched in DNA replication, cell cycle, pathways in cancer, focal adhesion, and ECM–receptor interaction. Notably, the overlapping DGEs were also significantly enriched in the MAPK pathway (Fig. 3 C and Fig. S4C). In summary, c-MET/sgp53 mouse HCC tissues exhibit distinct gene expression profiles that partially overlap with human HCCs harboring concomitant c-MET activation and TP53 deletion. Furthermore, both mouse and human HCCs with c-MET activation and TP53 loss show the activation of the MAPK cascade. Establishment And Application Of The Murine Hcc Cell Line Derived From C-met/sgp53 Hcc To investigate the potential therapeutic strategies for c-MET/sgp53 tumors, we developed a stably passaged cell line (MP cells) derived from a c-MET/sgp53 HCC by serial passaging of tumor cells from mouse to mouse (Fig. S7 and S8). Western blot analysis confirmed the deletion of p53 and the upregulation of p-MET and p-ERK protein in MP cells (Fig. 4 A). To verify the usefulness of this tumor cell line, FVB/N mice were injected in the flank with the MP cells. Two weeks after injection, the subcutaneous tumor model was successfully established, supporting the oncogenic potential of this cell line. Cabozantinib is an FDA-approved drug for HCC treatment, and it inhibits HCC growth by targeting the activated c-MET pathway 22 , 23 . Therefore, we hypothesized that MP cells would be sensitive to cabozantinib treatment. To test this hypothesis, we treated MP cells with cabozantinib in culture and found an IC50 value around 16µM (Fig. 4 B), consistent with human HCC cell lines sensitive to cabozantinib 22 . Next, we established a xenograft model to further investigate MP cell sensitivities in vivo . Tumor-bearing mice were treated with a daily dose of cabozantinib (60mg/kg/day) or vehicle control. After three weeks of treatment, cabozantinib-treated mice showed a robust reduction in tumor growth compared to vehicle-treated mice (Fig. 4 C and 4 D) (Table S3). Altogether, these data support the usefulness of the MP cell line and corresponding subcutaneous xenografts for investigating therapeutic strategies targeting p53-defective HCC and/or c-MET-activated HCC. As the loss of TP53 is one of the most frequent genetic events in human HCCs, we applied this unique murine HCC cell line to study drugs that have shown effectiveness against p53-defective tumors. Niclosamide and metformin have been reported to inhibit the growth of xenografts from p53-defective human cancer cells 24 , 25 . Nevertheless, clinical evidence supporting the effectiveness of these drugs for TP53 null human cancers is lacking. We found that both drugs could inhibit MP cell growth in vitro (Fig. 4 B). However, in MP xenograft models, neither niclosamide nor metformin showed any efficacy against MP cells (Fig. 4 C and 4 E) (Table S3). The results suggest that these drugs are unlikely to be useful against human HCCs with LOF TP53 mutations. Trametinib is effective against the TP53 -null Hep3B human HCC cell line As the bioinformatics analysis indicated (Fig. 3 B and 3 C), the MAPK signaling pathway was up-regulated in c-MET/sgp53 mouse HCCs and c-MET-high/ TP53 -null human HCCs. Consistently, we searched drug-response information of the human HCC cell lines in the Genomics of Drug Sensitivity in Cancer database ( www.cancerRxgene.org ). The results suggested that the TP53 -null HCC cell line (Hep3B) has higher sensitivity to multiple MEK inhibitors treatment than p53-mutant and p53-wild-type human HCC cell lines (Fig. S9). Accordingly, we validated the in vitro efficacy of the MEK inhibitor trametinib in the LM9 (p53-mutant), HLE (p53-mutant), and Hep3B (p53-null) human HCC cell lines and the HepG2 (p53-wild type) hepatoblastoma cell line. As expected, trametinib treatment had a lower IC50 value in Hep3B than the other HCC and hepatoblastoma cell lines (Fig. 5 ), demonstrating that inhibition of the MAPK pathway might be a novel therapeutic strategy for TP53 -null HCCs. Trametinib Inhibits The Growth Of C-met/sgp53 Hcc Cells And Xenografts Based on the in vitro studies, we investigated whether the MEK inhibitor effectively inhibits TP53 -defective tumor growth. We selected trametinib, an FDA-approved MEK inhibitor, which has been used to treat BRAF (V600E) mutant metastatic melanoma 26 . First, we administered trametinib to MP cells in culture. We found that trametinib effectively inhibits MP cell growth (Fig. 6 A). Next, we developed MP xenografts and treated tumor-bearing mice with trametinib (1 mg/kg/day) or vehicle control. Consistent with the in vitro data, trametinib successfully suppressed MP cell growth in vivo (Fig. 6 B and Table S3). Mechanistically, tumors from xenografted MP cells showed significant activation of the MAPK signaling, which was significantly decreased/abolished, as assessed by reduced immunoreactivity for phosphorylation of ERK proteins, in trametinib-treated samples (Fig. 6 C). Altogether, these data underline the therapeutic potential of MEK/ERK inhibitors for the treatment of p53-deficient HCC. Discussion Somatic mutations of the p53 tumor suppressor gene occur in ~ 50% of overall human tumors and represent one of the most common genetic variations of HCCs 27 , 28 . In most cases, TP53 mutations abolish the functions of the p53 protein, such as gene transcription, DNA synthesis and repair, cell cycle arrest, senescence, and apoptosis 28 , 29 . It has been shown that such inactivation mutations could lead to HCC onset and tumor progression 30 , 31 , 32 . Therefore, stabilizers of WT p53 or drugs that revert mutant p53 back to WT function have long been investigated for HCC treatment. However, the preclinical HCC models for studying p53 are still limited. According to the TP53 database ( https://tp53.isb-cgc.org/ ), only a few murine liver cancer models with engineered p53 are reported in the scientific literature (Table S4). In addition, most of the mouse models were developed as transgenic mouse strains. However, it takes long latency periods for these transgenic mouse strains to develop liver tumors, which significantly constrains their availability. In the current study, we generated a murine HCC model with hydrodynamic transfection of c-MET oncogene and CRISPR-Cas9 mediated KO of p53, which could be efficiently applied to study TP53 null HCC development in vivo . To further delineate the mechanisms associated with TP53 inactivation-related hepatocarcinogenesis, we have established malignant murine cell lines from this c-MET/sgp53 driven murine HCC model. Notably, these cells express high levels of p-ERK1/2 compared to c-MYC tumor-derived cell lines (HCC3 and HCC4) (Fig. S10). Significantly, the MP cells can be readily implanted into immunocompetent mice with resultant subcutaneous tumor formation. We performed mechanistic studies and drug screening using this unique cell line and MP cell line derived xenograft HCC model. In the future, the MP cells could be applied to establish orthotopic murine HCC models. In addition, this model could have significant utility in investigating oncogenic signaling pathways in HCCs as it allows for manipulation of the murine cells before transplantation. For instance, transfection of the cells with inducible genes or inhibition constructs may elucidate the impact of various oncogenes in HCC progression and survival. Moreover, this model can be exploited to examine the immunologic response and stroma formation in HCC and investigate new therapies for HCC. For p53 mutated HCCs, the current drug development strategies include restoring wild-type p53 conformation and transcriptional activity, inducing the degradation of mutated p53, and inhibiting the interaction of p53 and its negative regulatory factor MDM2. However, the heterogeneity of p53 mutations in tumors limits the use of these drugs. Thus, synthetic lethal effects can serve as a promising therapy for a wide range of functional p53 mutations in HCC. Here, our murine HCC model and the related HCC cell line with deletion of p53 could be a valuable preclinical model in exploring targeted treatments for p53-loss-of-function HCCs in vitro and in vivo . In the current study, we revealed that cabozantinib and trametinib inhibit the growth of c-MET/sgp53 HCC xenografts. These findings highlight the importance of biomarker-based targeted therapies for effective cancer treatment. In a phase I clinical study, trametinib and sorafenib were used to treat unselected patients with hepatocellular carcinoma. Unfortunately, the resulting clinical data indicated this combination therapy has limited efficacy in advanced HCC 33 . However, this is likely because trametinib may be only effective in HCCs harboring TP53 null mutations. Therefore, there is critical to identify a potential biomarker(s) of response to the effective therapy for HCCs. Therefore, preclinical and clinical studies are required to examine the therapeutic efficacy of trametinib against TP53 null human HCCs. Declarations Author contributions S.L, X.C. and H.W. performed study concept and design; Y.Z. and H.W. performed the experiments and drafted the manuscript; G.C., J.C. and Z.Z. provided technical and material support; H.X., L.Y., J.W. performed analysis and interpretation of the sequencing data; S.L, D.F.C., X.C. and H.W. performed review and revision of the paper. All authors read and approved the final paper. Ethics declarations Animal experiments were performed in accordance with protocols approved by Institutional Animal Care Use Committee (IACUC) at UCSF and UH. Conflict of interest statement : The authors declare no potential conflicts of interest. Funding statement: This study is supported by NIH under Grants R01CA239251 and R01CA250227 to XC; P30DK026743 for UCSF Liver Center; National Natural Science Foundation of China (82002967) and the fellowship of China National Postdoctoral Program for Innative Talents (BX20200225) to HW. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 2021, 71 (3): 209–249. Garcia-Lezana T, Lopez-Canovas JL, Villanueva A. Signaling pathways in hepatocellular carcinoma. Adv Cancer Res 2021, 149 : 63–101. Gordan JD, Kennedy EB, Abou-Alfa GK, Beg MS, Brower ST, Gade TP, et al. Systemic Therapy for Advanced Hepatocellular Carcinoma: ASCO Guideline. J Clin Oncol 2020, 38 (36): 4317–4345. Ghebranious N, Sell S. Hepatitis B injury, male gender, aflatoxin, and p53 expression each contribute to hepatocarcinogenesis in transgenic mice. Hepatology 1998, 27 (2): 383–391. Farazi PA, DePinho RA. Hepatocellular carcinoma pathogenesis: from genes to environment. Nat Rev Cancer 2006, 6 (9): 674–687. Farazi PA, Glickman J, Horner J, Depinho RA. Cooperative interactions of p53 mutation, telomere dysfunction, and chronic liver damage in hepatocellular carcinoma progression. Cancer Res 2006, 66 (9): 4766–4773. Xue W, Zender L, Miething C, Dickins RA, Hernando E, Krizhanovsky V, et al. Senescence and tumour clearance is triggered by p53 restoration in murine liver carcinomas. Nature 2007, 445 (7128): 656–660. Wang Y, Suh YA, Fuller MY, Jackson JG, Xiong S, Terzian T, et al. Restoring expression of wild-type p53 suppresses tumor growth but does not cause tumor regression in mice with a p53 missense mutation. J Clin Invest 2011, 121 (3): 893–904. Giordano S, Columbano A. Met as a therapeutic target in HCC: facts and hopes. J Hepatol 2014, 60 (2): 442–452. Suzuki K, Hayashi N, Yamada Y, Yoshihara H, Miyamoto Y, Ito Y, et al. Expression of the c-met protooncogene in human hepatocellular carcinoma. Hepatology 1994, 20 (5): 1231–1236. Ueki T, Fujimoto J, Suzuki T, Yamamoto H, Okamoto E. Expression of hepatocyte growth factor and its receptor, the c-met proto-oncogene, in hepatocellular carcinoma. Hepatology 1997, 25 (3): 619–623. Hu J, Che L, Li L, Pilo MG, Cigliano A, Ribback S, et al. Co-activation of AKT and c-Met triggers rapid hepatocellular carcinoma development via the mTORC1/FASN pathway in mice. Sci Rep 2016, 6 : 20484. Tao J, Xu E, Zhao Y, Singh S, Li X, Couchy G, et al. Modeling a human hepatocellular carcinoma subset in mice through coexpression of met and point-mutant β-catenin. Hepatology 2016, 64 (5): 1587–1605. Xu Z, Hu J, Cao H, Pilo MG, Cigliano A, Shao Z, et al. Loss of Pten synergizes with c-Met to promote hepatocellular carcinoma development via mTORC2 pathway. Exp Mol Med 2018, 50 (1): e417. Qiao Y, Wang J, Karagoz E, Liang B, Song X, Shang R, et al. Axis inhibition protein 1 (Axin1) Deletion-Induced Hepatocarcinogenesis Requires Intact β-Catenin but Not Notch Cascade in Mice. Hepatology 2019, 70 (6): 2003–2017. Xu Z, Xu M, Liu P, Zhang S, Shang R, Qiao Y, et al. The mTORC2-Akt1 Cascade Is Crucial for c-Myc to Promote Hepatocarcinogenesis in Mice and Humans. Hepatology 2019, 70 (5): 1600–1613. Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 2016, 32 (18): 2847–2849. Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma. Cell 2017, 169 (7): 1327–1341.e1323. Kaposi-Novak P, Lee JS, Gòmez-Quiroz L, Coulouarn C, Factor VM, Thorgeirsson SS. Met-regulated expression signature defines a subset of human hepatocellular carcinomas with poor prognosis and aggressive phenotype. J Clin Invest 2006, 116 (6): 1582–1595. Lee SA, Ladu S, Evert M, Dombrowski F, De Murtas V, Chen X, et al. Synergistic role of Sprouty2 inactivation and c-Met up-regulation in mouse and human hepatocarcinogenesis. Hepatology 2010, 52 (2): 506–517. Xue W, Chen S, Yin H, Tammela T, Papagiannakopoulos T, Joshi NS, et al. CRISPR-mediated direct mutation of cancer genes in the mouse liver. Nature 2014, 514 (7522): 380–384. Shang R, Song X, Wang P, Zhou Y, Lu X, Wang J, et al. Cabozantinib-based combination therapy for the treatment of hepatocellular carcinoma. Gut 2021, 70 (9): 1746–1757. D'Alessio A, Prete MG, Cammarota A, Personeni N, Rimassa L. The Role of Cabozantinib as a Therapeutic Option for Hepatocellular Carcinoma: Current Landscape and Future Challenges. J Hepatocell Carcinoma 2021, 8 : 177–191. Kumar R, Coronel L, Somalanka B, Raju A, Aning OA, An O, et al. Mitochondrial uncoupling reveals a novel therapeutic opportunity for p53-defective cancers. Nat Commun 2018, 9 (1): 3931. Buzzai M, Jones RG, Amaravadi RK, Lum JJ, DeBerardinis RJ, Zhao F, et al. Systemic treatment with the antidiabetic drug metformin selectively impairs p53-deficient tumor cell growth. Cancer Res 2007, 67 (14): 6745–6752. Davies MA, Saiag P, Robert C, Grob JJ, Flaherty KT, Arance A, et al. Dabrafenib plus trametinib in patients with BRAF(V600)-mutant melanoma brain metastases (COMBI-MB): a multicentre, multicohort, open-label, phase 2 trial. Lancet Oncol 2017, 18 (7): 863–873. Rebouissou S, Nault JC. Advances in molecular classification and precision oncology in hepatocellular carcinoma. J Hepatol 2020, 72 (2): 215–229. Muller PA, Vousden KH. p53 mutations in cancer. Nat Cell Biol 2013, 15 (1): 2–8. Cao H, Chen X, Wang Z, Wang L, Xia Q, Zhang W. The role of MDM2-p53 axis dysfunction in the hepatocellular carcinoma transformation. Cell Death Discov 2020, 6 : 53. Donehower LA, Harvey M, Slagle BL, McArthur MJ, Montgomery CA, Jr., Butel JS, et al. Mice deficient for p53 are developmentally normal but susceptible to spontaneous tumours. Nature 1992, 356 (6366): 215–221. Ghebranious N, Sell S. The mouse equivalent of the human p53ser249 mutation p53ser246 enhances aflatoxin hepatocarcinogenesis in hepatitis B surface antigen transgenic and p53 heterozygous null mice. Hepatology 1998, 27 (4): 967–973. Liu G, McDonnell TJ, Montes de Oca Luna R, Kapoor M, Mims B, El-Naggar AK, et al. High metastatic potential in mice inheriting a targeted p53 missense mutation. Proc Natl Acad Sci U S A 2000, 97 (8): 4174–4179. Kim R, Tan E, Wang E, Mahipal A, Chen DT, Cao B, et al. A Phase I Trial of Trametinib in Combination with Sorafenib in Patients with Advanced Hepatocellular Cancer. Oncologist 2020, 25 (12): e1893-e1899. Additional Declarations (Not answered) Supplementary Files SupplementaryFiguresOct16.docx SupplementaryTableS1.xlsx SupplementaryTableS2.docx SupplementaryTableS3.docx SupplementaryTableS4.docx ajchecklist.pdf Cite Share Download PDF Status: Published Journal Publication published 27 Jul, 2023 Read the published version in Cell Death & Disease → Version 1 posted Editorial decision: revise 24 Nov, 2022 Review # 2 received at journal 24 Nov, 2022 Review # 1 received at journal 20 Nov, 2022 Reviewer # 2 agreed at journal 04 Nov, 2022 Reviewer # 1 agreed at journal 02 Nov, 2022 Reviewers invited by journal 29 Oct, 2022 Submission checks completed at journal 18 Oct, 2022 First submitted to journal 17 Oct, 2022 Editor assigned by journal 17 Oct, 2022 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2176178","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":147895425,"identity":"81fcc53d-5f4b-4eab-a978-0b9c3389d475","order_by":0,"name":"Xin 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Francisco","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jingxiao","middleName":"","lastName":"Wang","suffix":""},{"id":147895433,"identity":"f394c334-a231-4b54-a10d-79fbf6f45c68","order_by":8,"name":"Diego F Calvisi","email":"","orcid":"","institution":"University of Regensburg","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Diego","middleName":"F","lastName":"Calvisi","suffix":""},{"id":147895434,"identity":"810176cf-84f7-467d-95d1-4ba1cdca7d2f","order_by":9,"name":"Shumei Lin","email":"","orcid":"","institution":"The First Affiliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shumei","middleName":"","lastName":"Lin","suffix":""},{"id":147895435,"identity":"2d3327ed-fd0f-4f51-bf3d-205b61095445","order_by":10,"name":"Haichuan Wang","email":"","orcid":"https://orcid.org/0000-0002-6886-5698","institution":"Sichuan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Haichuan","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2022-10-17 18:21:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2176178/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2176178/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41419-023-05958-y","type":"published","date":"2023-07-27T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":28626085,"identity":"ada4582c-5a12-4ca3-b9b9-ad4ee3ed9c40","added_by":"auto","created_at":"2022-11-03 18:31:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1732323,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA subset of human HCC samples with c-MET activation and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eTP53\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e mutations based on the TCGA dataset.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Heatmap of the human TCGA samples depicting \u003cem\u003eTP53\u003c/em\u003emutations and c-MET activation; (B) c-MET signature is enriched in \u003cem\u003eTP53\u003c/em\u003emutant human HCC samples. (C) Survival curves of patients harboring concomitant \u003cem\u003eTP53\u003c/em\u003e mutation and c-MET activation, indicating a poor prognosis compared to other patients. Data are shown as mean ± SD. (B) Student’s t-test: **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; (C) Log-rank (Mantel-Cox) test. Abbreviations: WT, wild-type.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-2176178/v1/41003671303e467c8d1c1c3a.png"},{"id":28626094,"identity":"7fb0f153-eb89-4bc4-ba27-2134bc977ee3","added_by":"auto","created_at":"2022-11-03 18:31:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":6674176,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLoss of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eTP53\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003esynergizes with c-MET to promote hepatocarcinogenesis in mice.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Study design. (B) Gross images, H\u0026amp;E staining, and immunohistochemical staining of p53, CK19, HNF4a and Ki67 in tumor lesions from c-MET/sgp53 mouse liver. (C) Western blotting analysis of lysates from normal liver and c-MET/sgp53 mouse HCCs. Scale bar: 200 μm.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-2176178/v1/db91379e5a46e0caaf8f767a.png"},{"id":28626087,"identity":"ad162e7e-22da-4334-bba8-e7cecb488118","added_by":"auto","created_at":"2022-11-03 18:31:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1738693,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRNA sequencing data show the activation of MAPK signaling pathway in c-MET/sgp53 HCCs.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Genetic dissimilarity among the samples in c-MET/sgp53 HCCs and normal liver as demonstrated by the heatmap. (B) KEGG analysis of up-regulated DEGs in the c-MET/sgp53 HCCs as compared to normal livers. (C) KEGG analysis of overlapping up-regulated DEGs in c-MET/sgp53 HCCs and c-MET-high/\u003cem\u003eTP53\u003c/em\u003e-null human HCCs. Abbreviations: NL, normal livers; ST, surrounding tissues; DEG, differentially expressed genes.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-2176178/v1/b6b36563a4d433a95b073f03.png"},{"id":28626712,"identity":"b0ca86ab-0be6-427d-b0ae-30e118c69f7b","added_by":"auto","created_at":"2022-11-03 18:39:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2558786,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEstablishment of a stably passaged cell line (MP) derived from c-MET/sgp53 HCC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Western blotting analysis of lysates from normal liver and MP cells. (B) Cell viability analysis for MP cells treated with cabozantinib, niclosamide and metformin. (C) Gross images of MP derived xenografts from mice treated with cabozantinib, niclosamide, metformin and vehicles. (D) Tumor volume of mice treated with cabozantinib and vehicles. (D) Tumor volume of mice treated with niclosamide, metformin and vehicles.\u003c/p\u003e\n\u003cp\u003eData are shown as mean ± SD.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-2176178/v1/d5a5b5ed825b339fef8e587d.png"},{"id":28626086,"identity":"6460bf1c-266b-478a-8bda-e9b7098c6e00","added_by":"auto","created_at":"2022-11-03 18:31:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":792539,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTreatment with trametinib showed a lower IC50 in the \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eTP53\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e-null human HCC cells \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vitro.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThree human HCC cell lines (A) LM9 (p53-mutant), (B) HLE (p53-mutant), (C) Hep3B (p53-null) and one hepatoblastoma cell line (D) HepG2 (p53-wild type) were treated with escalating concentrations of trametinib for 48 hours, and IC50 values were calculated.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-2176178/v1/5851d5f9a6c302b807b53237.png"},{"id":28626089,"identity":"718d0e6d-8264-461e-9053-2f3bc4a1c83c","added_by":"auto","created_at":"2022-11-03 18:31:01","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3188213,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrametinib inhibits the growth of c-MET/sgp53 HCC cells and its xenografts.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Cell viability analysis of MP cells treated with trametinib. (B) Gross images, tumor volume and tumor weight of MP derived xenografts from mice treated with trametinib and vehicles. (C) H\u0026amp;E staining and immunohistochemical staining of p-ERK in xenografts from mice treated with trametinib and vehicles. Student’s t-test: ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001; Scale bar: H\u0026amp;E, 500μm (40X); p-ERK, 200μm (100X).\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-2176178/v1/712530d6805d8cdc771528ee.png"},{"id":40701204,"identity":"a6cdae20-9118-452f-8c26-3fa9f711c232","added_by":"auto","created_at":"2023-07-28 07:11:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2437063,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2176178/v1/5ae3aa6e-dbb9-4782-95e3-da8a3a8319d5.pdf"},{"id":28626090,"identity":"c90321e2-9290-484f-b430-d4bb399d2490","added_by":"auto","created_at":"2022-11-03 18:31:01","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":1752289,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFiguresOct16.docx","url":"https://assets-eu.researchsquare.com/files/rs-2176178/v1/0e49c26dec081ca6dbcbb7ed.docx"},{"id":28626096,"identity":"b57d09c1-85bc-4ed0-8f92-8ea6ec30d038","added_by":"auto","created_at":"2022-11-03 18:31:02","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":1583761,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-2176178/v1/e554bf5ab8eb43f257486726.xlsx"},{"id":28626092,"identity":"2a900bda-0d2e-4c50-b786-e82f8bb13c39","added_by":"auto","created_at":"2022-11-03 18:31:02","extension":"docx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":14755,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS2.docx","url":"https://assets-eu.researchsquare.com/files/rs-2176178/v1/0e2e27cc5de2adce9e33ea2a.docx"},{"id":28626711,"identity":"77e290e5-12bd-4520-9117-add7b7741454","added_by":"auto","created_at":"2022-11-03 18:39:01","extension":"docx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":14966,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS3.docx","url":"https://assets-eu.researchsquare.com/files/rs-2176178/v1/d8c4538fadf1926755d3f657.docx"},{"id":28626088,"identity":"07c2cf1c-5ec4-49b9-bcac-c97934d4566d","added_by":"auto","created_at":"2022-11-03 18:31:01","extension":"docx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":14263,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS4.docx","url":"https://assets-eu.researchsquare.com/files/rs-2176178/v1/d2314d72b375d31f0019711b.docx"},{"id":28626095,"identity":"973567bc-c40a-4b43-a5a9-bab9172fa252","added_by":"auto","created_at":"2022-11-03 18:31:02","extension":"pdf","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":2000021,"visible":true,"origin":"","legend":"","description":"","filename":"ajchecklist.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2176178/v1/209bf16306101e8c616fc06f.pdf"}],"financialInterests":"(Not answered)","formattedTitle":"Loss of \u003ci\u003eTP53\u003c/i\u003e cooperates with c-MET overexpression to drive hepatocarcinogenesis","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePrimary liver cancer is one of the most common malignant tumors worldwide. Hepatocellular carcinoma (HCC) is the predominant tumor entity, accounting for 75%-85% of the cases\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. HCC is often associated with chronic liver disease, which causes liver cell death, inflammation, oxidative stress, and fibrosis. At the molecular level, HCC is driven by heterogeneous signaling pathways that produce DNA damage to liver cells, resulting in resistance to cell death, proliferation, and eventually tumorigenesis \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Though targeted therapies and immunization treatments for HCC have been extensively investigated, only a few multi-kinase and immune checkpoint inhibitors have been approved for advanced HCCs \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Therefore, identifying the specific aberrant molecular pathways that drive hepatocarcinogenesis and generating preclinical models to explore targeted treatments are essential for HCC patients.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eTP53\u003c/em\u003e (p53) gene is one of the most critical tumor suppressors. The p53 protein encoded by \u003cem\u003eTP53\u003c/em\u003e is involved in various pathways to regulate multiple processes, such as metabolism, DNA damage repair, cell cycle arrest, and apoptosis. As in other cancer types, \u003cem\u003eTP53\u003c/em\u003e mutation is also one of the main genetic variations in HCC. Accounting for about 30% of HCC cases, \u003cem\u003eTP53\u003c/em\u003e inactivating mutations contribute to HCC initiation and progression \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. In addition, reactivating p53 in tumors with p53 inactivation can induce tumor stabilization or regression \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Therefore, drugs targeting p53 loss of function could represent a promising approach for HCC treatment.\u003c/p\u003e \u003cp\u003e \u003cem\u003eMET\u003c/em\u003e (c-MET) is a protooncogene that encodes the hepatocyte growth factor (HGF) receptor. Binding to HGF, c-MET activates multiple downstream targets, such as the RAS/MAPK and phosphoinositide 3-kinase (PI3K)/AKT pathways, to drive tumor invasion and metastasis \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Previous studies have shown that c-MET activation occurs in 20\u0026ndash;44% of HCC patients, and increased expression of c-MET is associated with poor tumor differentiation, augmented intrahepatic metastases, and poor prognosis \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. However, c-MET alone cannot induce HCC in mice but requires the presence of additional molecular events, such as AKT overexpression, ꞵ-Catenin activation, or loss of the PTEN oncosuppressor to drive liver malignant transformation \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGene expression analysis of HCC specimens from the TGGA database suggests that samples with \u003cem\u003eTP53\u003c/em\u003e mutations are more likely to show upregulation of the c-MET signature. Specifically, about 21% of the HCC patients have both c-MET activation features and LOF \u003cem\u003eTP53\u003c/em\u003e mutations. Clinically, these HCCs are associated with poor patients' prognosis. Therefore, we speculate that LOF \u003cem\u003eTP53\u003c/em\u003e mutations can synergize with c-MET activation to induce hepatocyte malignant transformation. In this study, we established and characterized a novel murine HCC model induced by overexpression of c-MET and CRISPR-Cas9 mediated knockout of \u003cem\u003eTrp53\u003c/em\u003e (encoding mouse p53). In addition, we applied this model for therapeutic testing.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePlasmids and reagents\u003c/h2\u003e \u003cp\u003eThe plasmids used in this study, including pT3-EF1α-c-MET (human c-MET or hMET) and pCMV-sleeping beauty transposase (SB) have been described in our previous studies\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. pX330-sgp53 plasmid was obtained from Addgene (#59910). Plasmids were purified using the Endotoxin free Maxi prep kit (Sigma-Aldrich, St. Louis, MO, USA). Cabozantinib and tametinib were purchased from LC Laboratories (Woburn, MA, USA). Niclosamide and metformin were obtained from Sigma-Aldrich (St. Louis, MO, USA).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHydrodynamic Tail Vein Injection\u003c/h3\u003e\n\u003cp\u003eFVB/N mice were obtained from Charles River Laboratories (Wilmington, MA, USA). To generate the c-Met/sgp53 HCC model, 20\u0026micro;g pT3-EF1α-c-MET and 20/40 \u0026micro;g pX330-sgp53 along with 0.8\u0026micro;g pCMV/SB plasmids in 2ml saline (0.9%NaCl) were delivered to 6\u0026thinsp;~\u0026thinsp;8 week-old mice (half male and half female) by hydrodynamic tail vein injection. Mice were housed, fed and monitored in accordance with protocols approved by the Committee for Animal Research at the University of California, San Francisco and the University of Hawaii Cancer Center.\u003c/p\u003e\n\u003ch3\u003eGenerating The Stably Passaged Cell Line From C-met/sgp53 Hcc\u003c/h3\u003e\n\u003cp\u003eMice were humanely euthanized and rinsed in 70% ethanol. Liver tumor (2-3g) was dissected, washed in PBS and minced into ~\u0026thinsp;1mm fragments using scalpel blade. All procedures were operated in the hood using autoclaved dissecting tools. The tumor fragments were digested with 0.6 mg/L collagenase (Sigma-Aldrich, C5138) in 37\u0026deg;C for 15\u0026thinsp;~\u0026thinsp;30min, then filtered through 100 \u0026micro;m nylon mesh cell strainer (BD, 352360) and spined (700-1000rpm, 5 min). The cell pellet were resuspended and cultured in 5 ml DMEM with 10% fetal bovine serum (FBS) and 1% Penicillin/Streptomycin at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e for ~\u0026thinsp;4 weeks. The primary liver tumor cells were generated. In order to obtain a stablely passaged cell line, 1\u0026times;10\u003csup\u003e7\u003c/sup\u003e primary tumor cells were injected into flanks of 6\u0026thinsp;~\u0026thinsp;8 week-old FVB/N mice. When the subcutaneous tumor developed, tumor tissue was dissected into small pieces and digested with trypsin (Sigma-Aldrich, T4049). The new generation of liver tumor cells (P0) were cultured and passaged in vitro for 3 times. Then 1\u0026times;10\u003csup\u003e7\u003c/sup\u003e \u0026ldquo;P0\u0026rdquo; cells were implanted into the flanks of a new recipient FVB/N mouse. These procedures were repeated for three rounds. The stably passaged cell line from c-MET/sgp53 HCC (MP cell) was finally generated.\u003c/p\u003e\n\u003ch3\u003eMice Xenografts And Treatment\u003c/h3\u003e\n\u003cp\u003eTo develop mice xenografts, 200\u0026micro;l (1\u0026times;10\u003csup\u003e7\u003c/sup\u003e MP cells) suspension of tumor cells in Matrigel (Corning, 354248) were inoculated subcutaneously into the right flank of 6\u0026thinsp;~\u0026thinsp;8 week-old FVB/N mice (females). On day 14 post implantation, when the tumor size reached to about 100 to 150 mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, mice were randomized into 5 groups for treatment. Metformin (250mg/kg/day), niclosamide (100mg/kg/day), cabozantinib (60mg/kg/day), trametinib (1mg/kg/day) or vehicle was orally administered daily via gavage. Tumor volume was measured every three days and estimated from caliper using the formula V\u0026thinsp;=\u0026thinsp;A\u0026times;B\u003csup\u003e2\u003c/sup\u003e/2 (A is largest diameter, B is smallest diameter). Body weight was measured everyday. After three weeks treatment, all mice were sacrificed and tumors were harvested for further analysis.\u003c/p\u003e\n\u003ch3\u003eHcc Cell Lines\u003c/h3\u003e\n\u003cp\u003eThe following human HCC cell lines which used in this study: LM9, HLE, HepG2 and Hep3B, were obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA). In addition, HCC3-4 and HCC4-4 cell lines, isolated from c-Myc mouse liver tumors, were kindly provided by Dr. Felsher of Stanford University. All cell lines were grown in Dulbecco's Modified Eagle Medium (DMEM) supplemented with 10% FBS and penicillin/streptomycin (Gibco, Grand Island, NY, USA) in 5% CO\u003csub\u003e2\u003c/sub\u003e atmosphere, at 37\u0026deg;C. For IC50 determination, cells were seeded in 24-well plates and treated with gradient concentration of trametinib in triplicate for 48 hours. Then cells were enumerated by crystal violet staining. After washing, stained cells were incubated in lysis solution and shaken gently on a rocking shaker for 10 min. Diluted lysate solutions were added to 96-well plates and OD value was measured at 590 nm with the BioTek ELX808 Absorbance Microplate Reader (ThermoFisher Scientific, MA, USA). The IC50 values were calculated using the Prism 9.0 software (GraphPad Software Inc). All experiments were repeated at least three times.\u003c/p\u003e\n\u003ch3\u003eHistology And Immunohistochemistry\u003c/h3\u003e\n\u003cp\u003eMouse liver tissues and tumor tissues were fixed in 4% paraformaldehyde, embedded in paraffin and sectioned at 5\u0026micro;m. Then, hematoxylin and eosin (H\u0026amp;E) and immunohistochemical staining were performed. For antigen retrieval, de-paraffinized slides were incubated in antigen retrieval buffer (10mM sodium citrate buffer, pH 6.0) and microwaved for 10 min. After a blocking step with the 5% goat serum and Avidin-Biotin blocking kit (Vector Laboratories Inc., Burlingame, CA), the sections were incubated with the primary antibodies overnight at 4\u0026deg;C. To quench endogenous peroxidase, slides were then subjected to 3% hydrogen peroxide for 10 min and subsequently the secondary antibody was applied for 30 min at room temperature. The immunoreactivity was visualized with the Vectastain ABC Elite kit (Vector Laboratories Inc.) and DAB (Vector Laboratories, Inc.). Slides were counterstained with hematoxylin. The following primary antibodies were used in the present investigation: anti-p53 (sc-126; Santa Cruz, CA, USA), anti-CK19 (ab52625; Abcam, Cambridge, United Kingdom), anti-HNF4a (ab18604; Abcam, Cambridge, United Kingdom), anti-Ki67 (MA5-14520; Thermo Fisher Scientific, MA, USA), and anti-p-ERK (4370; Cell Signaling Technology, MA, USA) were used in the present investigation.\u003c/p\u003e\n\u003ch3\u003eProtein Extraction And Western Blot Analysis\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eProtein extraction and Western blot analysis\u003c/div\u003e \u003cp\u003eFrozen liver tumors were homogenized in Mammalian Protein Extraction Reagent (Thermo Fisher Scientific, MA, USA) containing the Complete Protease Inhibitor Cocktail (Thermo Fisher Scientific, MA, USA). Protein concentrations were determined with the Bio-Rad Protein Assay Kit (Bio-Rad, CA, USA). Supernatant was denatured by boiling in 2\u0026times;Laemmli sample buffer (1610737, Bio-Rad, CA, USA). Equal loading was assessed by GAPDH or β-actin. Aliquots of 30 \u0026micro;g protein lysates were separated by SDS-PAGE (M00654, GenScript, Piscataway, NJ, USA) and transferred onto PVDF membranes (Bio-Rad, CA, USA). Membranes were blocked in 10% non-fat milk in Tris-buffered saline containing 0.05% Tween-20, and incubated with primary antibodies at 4\u0026deg;C overnight. Then membranes were incubated with horseradish peroxidase-secondary antibody (Jackson ImmunoResearch Laboratories Inc., PA, USA) for 1 hour at room temperature and developed with ClarityTM Western ECL Substrate (170\u0026ndash;5061, Bio-Rad Laboratories, Hercules, CA, USA). The antibodies used are as follows: anti-p53 (sc-126; Santa Cruz, CA, USA), anti-c-MET (71-8000; Invitrogen,CA, USA), anti-p-MET\u003csup\u003eTyr1234/1235\u003c/sup\u003e (3077, Cell Signaling Technology, MA, USA), anti-ERK1/2 (9102; Cell Signaling Technology, MA, USA) and anti-p-ERK1/2\u003csup\u003eThr202/Tyr204\u003c/sup\u003e (4370; Cell Signaling Technology, MA, USA), anti-GAPDH (5174; Cell Signaling Technology, MA, USA) and anti-β-actin (4970; Cell Signaling Technology, MA, USA).\u003c/p\u003e\n\u003ch3\u003eMouse Genomic Dna Extraction And Sequencing\u003c/h3\u003e\n\u003cp\u003eMouse genomic DNA was extracted from frozen mouse tissue samples using the Mouse Direct PCR Kit, according to the manufacturer's instructions (Biomake, TX, USA). The amplification conditions were 94\u0026deg;C for 5 min, followed by 35 cycles of 94\u0026deg;C for 20 s, 50\u0026deg;C for 30 s, and 72\u0026deg;C for 30 s. The sequences of the primers are as follows: Forward:CCTACTGGATGTCCCACCTTCT; Reverse:CAGACACCCAACACCATACCA. For individual clonal sequencing, PCR products were purified and inserted to pGEM\u0026reg;-T Easy Vector (Promega, WI, USA) according to the manufacturer's instructions.Clones were cultured and plasmids were extracted using Zyppy Plasmid Miniprep kit (Genesee Scientific, CA, USA). The inserted sequence was subsequently sequenced using T7 primers.\u003c/p\u003e\n\u003ch3\u003eRnaseq Analysis\u003c/h3\u003e\n\u003cp\u003eTotal RNA was extracted from mouse sgp53/c-MET HCCs (n\u0026thinsp;=\u0026thinsp;3) and FVB/N normal livers (n\u0026thinsp;=\u0026thinsp;3) using Quick-RNA Miniprep Kit (Zymo Research, CA, USA). The RNA quality control was determined using Agilent RNA 6000 Nano Kit (Agilent Technologies, CA, USA) and Bioanalyzer (Agilent Technologies, CA, UAS). Library preparation and sequencing were performed by Novogene (Sacramento, CA, USA). All analyses were performed in R.Experimental design had 2 groups: \u0026ldquo;MP\u0026rdquo; (sgp53/c-MET) and \u0026ldquo;NL\u0026rdquo; (FVB/N normal liver). Poor quality reads were trimmed using the fastq-mcf (1.05). Reads quality was checked using the fastqc (v0.11.7). Gene read counts were in Ensembl Gene ID and converted to Entrez Gene ID. Corresponding Symbol annotations and full gene names were added using the \u0026ldquo;org.Mm.eg.db\u0026rdquo; library. NA (Not Annotated), duplicate Entrez IDs and genes without symbols were removed. Only the genes having CPM values above 0.5 in at least two libraries were kept. Normalization by TMM (Trimmed mean of M values) was performed by using \u003cem\u003ecalcNormFactors\u003c/em\u003e function to eliminate composition biases between libraries. R package \u0026ldquo;edgeR\u0026rdquo; and \u003cem\u003eglmTreat\u003c/em\u003e function were used to identify differentially expressed genes (DEGs). DEGs were limited by a \u003cem\u003ep\u003c/em\u003e value of 0.05 and FDR (False Discovery Rate) of 0.05. Total numbers of genes involved, Number of up-regulated genes, Number of down-regulated genes, \u003cem\u003ep\u003c/em\u003e value, and Direction of Regulation were obtained for each Gene Ontology analysis. List of DEGs for each Gene Ontology was created for all the comparisons by \u003cem\u003ep\u003c/em\u003e value of 0.05 and FDR of 0.05. Genes were mapped to KEGG Pathways using GO.db package, kegga function which obtains the KEGG annotations from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://rest.kegg.jpwebsite\u003c/span\u003e\u003cspan address=\"http://rest.kegg.jpwebsite\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n\u003ch3\u003eHuman Data Hcc Tcga Retrieval And Analysis\u003c/h3\u003e\n\u003cp\u003eTo investigate the relationship with c-MET activation and \u003cem\u003eTP53\u003c/em\u003e mutation status in human HCC samples, TGCA data set were retrieved based on the the cBioPortal for Cancer Genomics (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cbioportal.org\u003c/span\u003e\u003cspan address=\"http://www.cbioportal.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The overall sample size is 410, including 50 surrounding liver tissues (ST) and 360 HCC samples with \u003cem\u003eTP53\u003c/em\u003e mutation data. RNA sequencing data were analyzed in R using multiple packages. Data were normalized using calcNormFactors function to eliminate composition biases between libraries. Gene symbol annotations and full gene names were added using the \u0026ldquo;org.Hs.eg.db\u0026rdquo; library. The analysis of c-MET activation status was performed as previously described\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. In brief, we extracted genes from the \u0026ldquo;KAPOSI_LIVER_CANCER_MET_UP\u0026rdquo; gene set, which contains 18 genes which were upregulated in liver cancer samples in response to c-MET activation. FRY gene set test was applied to investigate the enrichment of the c-MET_UP genes in HCC samples. Mann-Whitney test was used for comparison of different gene expression between the ST and \u003cem\u003eTP53\u003c/em\u003e mutated groups. And Fisher\u0026rsquo;s exact test was employed to compare the difference in composition of samples with c-MET up signature in ST and \u003cem\u003eTP53\u003c/em\u003e mutated groups. Heatmap was generated using Complex heatmap package\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e in R. We standardized the data with mean as 0 and standard deviation (SD) as 1 and ordered by ascending Average of 18-gene expression of each sample from left to right. As the weight of each gene is 1 in this gene set, samples with Averages more than the Average plus 1.5-fold SD of the ST group was considered as HCC with \u0026ldquo;c-MET activation\u0026rdquo;. Tissue types and mutation information was also included in the heatmap.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe Prism 9.0 software (GraphPad Software Inc) was used to analyze the data. Statistical analysis was performed using Student\u0026rsquo;s t-test, Mann-Whitney test, Welch\u0026rsquo;s t test and Log-rank (Mantel-Cox) test analyses. The data were expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (*, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) of at least three independent experiments.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003ec-MET activation and\u003c/b\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eTP53\u003c/span\u003e \u003cb\u003emutations occur concomitantly in a subset of human HCCs\u003c/b\u003e\u003c/p\u003e \u003cp\u003ec-MET overexpression and LOF \u003cem\u003eTP53\u003c/em\u003e mutation are two frequent alterations reported in human HCC. To investigate the profile of these genetic aberrations, we analyzed the expression level of c-MET and LOF \u003cem\u003eTP53\u003c/em\u003e mutation status based on The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA LIHC) human HCC dataset\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. The c-MET activation signature was identified using the KAPOSI_LIVER_CANCER_MET_UP gene set \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, described previously \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. First, we determined the c-MET activation signature in LOF \u003cem\u003eTP53\u003c/em\u003e mutant and \u003cem\u003eTP53\u003c/em\u003e wild-type samples. The results showed that the c-MET signature was enriched in LOF \u003cem\u003eTP53\u003c/em\u003e mutant human HCC samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Indeed, ~\u0026thinsp;71% of \u003cem\u003eTP53\u003c/em\u003e mutant HCCs (79/111) in the TCGA dataset showed the activated c-MET signature. In comparison, only 55% of \u003cem\u003eTP53\u003c/em\u003e wild-type HCCs (136/249) showed high c-MET expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Further analysis showed that in human HCC, ~\u0026thinsp;22% of specimens displayed concomitant LOF \u003cem\u003eTP53\u003c/em\u003e mutation and c-MET activation. Importantly, these HCC patients exhibited the shortest overall survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn summary, LOF \u003cem\u003eTP53\u003c/em\u003e mutation and c-MET activation co-occur in a subset of human HCC patients with poor prognoses.\u003c/p\u003e \u003cp\u003e \u003cb\u003eDeletion of\u003c/b\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eTrp53\u003c/span\u003e \u003cb\u003esynergizes with activated c-MET to promote HCC formation in mice\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOur previous work suggested that long-term overexpression of c-MET alone by hydrodynamic injection in the mouse liver does not trigger liver tumor development while giving rise to dysplastic clear-cell foci \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Similarly, sporadic loss of TP53 in the mouse liver does not induce liver tumor formation \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Therefore, we hypothesized that the simultaneous deletion of \u003cem\u003eTP53\u003c/em\u003e and expression of c-MET might lead to hepatocarcinogenesis in mice. Using the CRISPR-Cas9-mediated gene editing method, we stably deleted \u003cem\u003eTrp53\u003c/em\u003e in mouse hepatocytes using the pX330-sgP53 plasmid \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The pX330-sgp53 construct was co-expressed with the pT3-EF1α-c-MET and pCMV-SB constructs via hydrodynamic tail-vein injection (c-MET/sgp53) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Consistent with our hypothesis, c-MET/sgp53 combination was able to induce liver tumor formation \u003cem\u003ein vivo\u003c/em\u003e (Table S2). Gross tumor nodules were observed in the mouse liver between 20 and 30 weeks post-injection. Tumors varied in size, and histological evaluation revealed that the tumor lesions were consistent with well-differentiated HCC. No extrahepatic metastases developed in these mice. In addition, tumors were characterized by positive HNF-4a immunoreactivity, negative CK19 staining, and high Ki67 immunolabeling (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Gene expression analysis demonstrated the upregulation of HCC-related genes, including \u003cem\u003eAfp\u003c/em\u003e, \u003cem\u003eGpc3\u003c/em\u003e, and \u003cem\u003eProm1\u003c/em\u003e, as well as genes associated with cell proliferation, such as \u003cem\u003eCcnb1\u003c/em\u003e, \u003cem\u003eCcne1\u003c/em\u003e, \u003cem\u003eCdk6, Bub1\u003c/em\u003e, and \u003cem\u003eMki67\u003c/em\u003e in c-MET/sgp53 tumors (Fig. S1). Furthermore, immunohistochemical (IHC) staining and Western blotting verified the efficient deletion of p53 in the HCC lesions. Western blot analysis also revealed the overexpression of c-MET and the corresponding phosphorylation/activation of c-MET (p-MET). Moreover, c-MET/sgp53 tumor lesions exhibited phosphorylation/activation of the ERK signaling (p-ERK) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC and Fig. S2). To further validate the effective deletion of the \u003cem\u003eTrp53\u003c/em\u003e gene in c-MET/sgp53 HCCs, we performed genome sequencing on mouse \u003cem\u003eTrp53\u003c/em\u003e alleles in tumor nodules. The Sanger sequencing confirmed the nucleotide deletions of \u003cem\u003eTrp53\u003c/em\u003e on its genomic locus (Fig. S3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eGlobal Gene Expression Profiling Reveals The Activation Of Ras/mapk Cascades In C-met/sgp53 Lesions\u003c/h3\u003e\n\u003cp\u003eTo fully understand the molecular signatures of c-MET/sgp53 HCCs, we performed RNA sequencing of tissues from normal mouse livers (n\u0026thinsp;=\u0026thinsp;3) and c-MET/sgp53 liver tumors (n\u0026thinsp;=\u0026thinsp;3). The heatmap of the gene list showed genetic dissimilarities between the two groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The differentially expressed genes (DEG) analysis identified 2651 genes that were significantly up-regulated in c-MET/sgp53 HCC samples (fold change, \u0026gt;\u0026thinsp;1.5; \u003cem\u003eP\u003c/em\u003e adj\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig. S4A and Table S1). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the up-regulated genes were enriched in tumor-associated pathways, including pathways in cancer, focal adhesion, ECM\u0026ndash;receptor interaction, and cell cycle, in c-MET/sgp53 HCCs versus normal livers (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and Fig. S4B). Interestingly, KEGG analysis showed DEGs significantly enriched in the MAPK signaling pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and Fig. S4B). The corresponding heatmap showed differential expression of MAPK cascade correlated genes in c-MET/sgp53 mouse HCCs compared to normal livers (Fig. S5).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo further model c-MET/sgp53 mouse liver tumors to human HCCs, we analyzed a subset of human HCC samples harboring concomitant c-MET activation and \u003cem\u003eTP53\u003c/em\u003e deletion using the TCGA-LIHC dataset, which occurred in 23/360 HCC specimens (Fig. S6A). Multidimensional scaling (MDS) analysis showed genetic dissimilarity among the samples in c-MET-high/TP53-null human HCCS and surrounding tissues (Fig. S6B). Compared to surrounding liver tissues, 2817 genes were up-regulated (fold change, \u0026gt;\u0026thinsp;1.5; \u003cem\u003eP\u003c/em\u003e adj\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in c-MET-high/\u003cem\u003eTP53\u003c/em\u003e-null HCC samples, among which 521 genes were also up-regulated in c-MET/sgp53 mouse HCCs (Fig. S4A). KEGG pathway analysis revealed that up-regulated genes were enriched in cancer-related pathways (Fig. S6C). In addition, the 521 overlapping up-regulated genes were mainly enriched in DNA replication, cell cycle, pathways in cancer, focal adhesion, and ECM\u0026ndash;receptor interaction. Notably, the overlapping DGEs were also significantly enriched in the MAPK pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC and Fig. S4C).\u003c/p\u003e \u003cp\u003eIn summary, c-MET/sgp53 mouse HCC tissues exhibit distinct gene expression profiles that partially overlap with human HCCs harboring concomitant c-MET activation and \u003cem\u003eTP53\u003c/em\u003e deletion. Furthermore, both mouse and human HCCs with c-MET activation and \u003cem\u003eTP53\u003c/em\u003e loss show the activation of the MAPK cascade.\u003c/p\u003e\n\u003ch3\u003eEstablishment And Application Of The Murine Hcc Cell Line Derived From C-met/sgp53 Hcc\u003c/h3\u003e\n\u003cp\u003eTo investigate the potential therapeutic strategies for c-MET/sgp53 tumors, we developed a stably passaged cell line (MP cells) derived from a c-MET/sgp53 HCC by serial passaging of tumor cells from mouse to mouse (Fig. S7 and S8). Western blot analysis confirmed the deletion of p53 and the upregulation of p-MET and p-ERK protein in MP cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). To verify the usefulness of this tumor cell line, FVB/N mice were injected in the flank with the MP cells. Two weeks after injection, the subcutaneous tumor model was successfully established, supporting the oncogenic potential of this cell line.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCabozantinib is an FDA-approved drug for HCC treatment, and it inhibits HCC growth by targeting the activated c-MET pathway \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Therefore, we hypothesized that MP cells would be sensitive to cabozantinib treatment. To test this hypothesis, we treated MP cells with cabozantinib in culture and found an IC50 value around 16\u0026micro;M (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), consistent with human HCC cell lines sensitive to cabozantinib \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Next, we established a xenograft model to further investigate MP cell sensitivities \u003cem\u003ein vivo\u003c/em\u003e. Tumor-bearing mice were treated with a daily dose of cabozantinib (60mg/kg/day) or vehicle control. After three weeks of treatment, cabozantinib-treated mice showed a robust reduction in tumor growth compared to vehicle-treated mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD) (Table S3). Altogether, these data support the usefulness of the MP cell line and corresponding subcutaneous xenografts for investigating therapeutic strategies targeting p53-defective HCC and/or c-MET-activated HCC.\u003c/p\u003e \u003cp\u003eAs the loss of \u003cem\u003eTP53\u003c/em\u003e is one of the most frequent genetic events in human HCCs, we applied this unique murine HCC cell line to study drugs that have shown effectiveness against p53-defective tumors. Niclosamide and metformin have been reported to inhibit the growth of xenografts from p53-defective human cancer cells \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Nevertheless, clinical evidence supporting the effectiveness of these drugs for \u003cem\u003eTP53\u003c/em\u003e null human cancers is lacking. We found that both drugs could inhibit MP cell growth \u003cem\u003ein vitro\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). However, in MP xenograft models, neither niclosamide nor metformin showed any efficacy against MP cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE) (Table S3). The results suggest that these drugs are unlikely to be useful against human HCCs with LOF \u003cem\u003eTP53\u003c/em\u003e mutations.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTrametinib is effective against the\u003c/b\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eTP53\u003c/span\u003e\u003cb\u003e-null Hep3B human HCC cell line\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAs the bioinformatics analysis indicated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC), the MAPK signaling pathway was up-regulated in c-MET/sgp53 mouse HCCs and c-MET-high/\u003cem\u003eTP53\u003c/em\u003e-null human HCCs. Consistently, we searched drug-response information of the human HCC cell lines in the Genomics of Drug Sensitivity in Cancer database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://rest.kegg.jpwebsite\" target=\"_blank\"\u003ewww.cancerRxgene.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.cancerRxgene.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The results suggested that the \u003cem\u003eTP53\u003c/em\u003e-null HCC cell line (Hep3B) has higher sensitivity to multiple MEK inhibitors treatment than p53-mutant and p53-wild-type human HCC cell lines (Fig. S9). Accordingly, we validated the \u003cem\u003ein vitro\u003c/em\u003e efficacy of the MEK inhibitor trametinib in the LM9 (p53-mutant), HLE (p53-mutant), and Hep3B (p53-null) human HCC cell lines and the HepG2 (p53-wild type) hepatoblastoma cell line. As expected, trametinib treatment had a lower IC50 value in Hep3B than the other HCC and hepatoblastoma cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), demonstrating that inhibition of the MAPK pathway might be a novel therapeutic strategy for \u003cem\u003eTP53\u003c/em\u003e-null HCCs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eTrametinib Inhibits The Growth Of C-met/sgp53 Hcc Cells And Xenografts\u003c/h3\u003e\n\u003cp\u003eBased on the \u003cem\u003ein vitro\u003c/em\u003e studies, we investigated whether the MEK inhibitor effectively inhibits \u003cem\u003eTP53\u003c/em\u003e-defective tumor growth. We selected trametinib, an FDA-approved MEK inhibitor, which has been used to treat BRAF (V600E) mutant metastatic melanoma \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. First, we administered trametinib to MP cells in culture. We found that trametinib effectively inhibits MP cell growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Next, we developed MP xenografts and treated tumor-bearing mice with trametinib (1 mg/kg/day) or vehicle control. Consistent with the \u003cem\u003ein vitro\u003c/em\u003e data, trametinib successfully suppressed MP cell growth \u003cem\u003ein vivo\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB and Table S3). Mechanistically, tumors from xenografted MP cells showed significant activation of the MAPK signaling, which was significantly decreased/abolished, as assessed by reduced immunoreactivity for phosphorylation of ERK proteins, in trametinib-treated samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAltogether, these data underline the therapeutic potential of MEK/ERK inhibitors for the treatment of p53-deficient HCC.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSomatic mutations of the p53 tumor suppressor gene occur in ~\u0026thinsp;50% of overall human tumors and represent one of the most common genetic variations of HCCs \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. In most cases, \u003cem\u003eTP53\u003c/em\u003e mutations abolish the functions of the p53 protein, such as gene transcription, DNA synthesis and repair, cell cycle arrest, senescence, and apoptosis \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. It has been shown that such inactivation mutations could lead to HCC onset and tumor progression \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Therefore, stabilizers of WT p53 or drugs that revert mutant p53 back to WT function have long been investigated for HCC treatment. However, the preclinical HCC models for studying p53 are still limited. According to the \u003cem\u003eTP53\u003c/em\u003e database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://tp53.isb-cgc.org/\u003c/span\u003e\u003cspan address=\"https://tp53.isb-cgc.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), only a few murine liver cancer models with engineered p53 are reported in the scientific literature (Table S4). In addition, most of the mouse models were developed as transgenic mouse strains. However, it takes long latency periods for these transgenic mouse strains to develop liver tumors, which significantly constrains their availability. In the current study, we generated a murine HCC model with hydrodynamic transfection of c-MET oncogene and CRISPR-Cas9 mediated KO of p53, which could be efficiently applied to study \u003cem\u003eTP53\u003c/em\u003e null HCC development \u003cem\u003ein vivo\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eTo further delineate the mechanisms associated with \u003cem\u003eTP53\u003c/em\u003e inactivation-related hepatocarcinogenesis, we have established malignant murine cell lines from this c-MET/sgp53 driven murine HCC model. Notably, these cells express high levels of p-ERK1/2 compared to c-MYC tumor-derived cell lines (HCC3 and HCC4) (Fig. S10). Significantly, the MP cells can be readily implanted into immunocompetent mice with resultant subcutaneous tumor formation. We performed mechanistic studies and drug screening using this unique cell line and MP cell line derived xenograft HCC model. In the future, the MP cells could be applied to establish orthotopic murine HCC models. In addition, this model could have significant utility in investigating oncogenic signaling pathways in HCCs as it allows for manipulation of the murine cells before transplantation. For instance, transfection of the cells with inducible genes or inhibition constructs may elucidate the impact of various oncogenes in HCC progression and survival. Moreover, this model can be exploited to examine the immunologic response and stroma formation in HCC and investigate new therapies for HCC.\u003c/p\u003e \u003cp\u003eFor p53 mutated HCCs, the current drug development strategies include restoring wild-type p53 conformation and transcriptional activity, inducing the degradation of mutated p53, and inhibiting the interaction of p53 and its negative regulatory factor MDM2. However, the heterogeneity of p53 mutations in tumors limits the use of these drugs. Thus, synthetic lethal effects can serve as a promising therapy for a wide range of functional p53 mutations in HCC. Here, our murine HCC model and the related HCC cell line with deletion of p53 could be a valuable preclinical model in exploring targeted treatments for p53-loss-of-function HCCs \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eIn the current study, we revealed that cabozantinib and trametinib inhibit the growth of c-MET/sgp53 HCC xenografts. These findings highlight the importance of biomarker-based targeted therapies for effective cancer treatment. In a phase I clinical study, trametinib and sorafenib were used to treat unselected patients with hepatocellular carcinoma. Unfortunately, the resulting clinical data indicated this combination therapy has limited efficacy in advanced HCC \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. However, this is likely because trametinib may be only effective in HCCs harboring \u003cem\u003eTP53\u003c/em\u003e null mutations. Therefore, there is critical to identify a potential biomarker(s) of response to the effective therapy for HCCs. Therefore, preclinical and clinical studies are required to examine the therapeutic efficacy of trametinib against \u003cem\u003eTP53\u003c/em\u003e null human HCCs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS.L, X.C. and H.W. performed study concept and design; Y.Z. and H.W. performed the experiments and drafted the manuscript; G.C., J.C. and Z.Z. provided technical and material support; H.X., L.Y., J.W. performed analysis and interpretation of the sequencing data; S.L, D.F.C., X.C. and H.W. performed review and revision of the paper. All authors read and approved the final paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnimal experiments were performed in accordance with protocols approved by Institutional Animal Care Use Committee (IACUC) at UCSF and UH.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest statement\u003c/strong\u003e: The authors declare no potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement:\u003c/strong\u003e This study is supported by NIH under Grants R01CA239251 and R01CA250227 to XC; P30DK026743 for UCSF Liver Center; National Natural Science Foundation of China (82002967) and the fellowship of China National Postdoctoral Program for Innative Talents (BX20200225) to HW.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, \u003cem\u003eet al.\u003c/em\u003e Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. 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Oncologist 2020, \u003cb\u003e25\u003c/b\u003e(12): e1893-e1899.\u003c/span\u003e\u003c/li\u003e\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":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cell-death-and-disease","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddis","sideBox":"Learn more about [Cell Death \u0026 Disease](http://www.nature.com/cddis/)","snPcode":"41419","submissionUrl":"https://mts-cddis.nature.com/cgi-bin/main.plex","title":"Cell Death \u0026 Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"hepatocellular carcinoma, p53, c-MET, preclinical model","lastPublishedDoi":"10.21203/rs.3.rs-2176178/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2176178/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHepatocellular carcinoma (HCC) is a deadly malignancy with high genetic heterogeneity. \u003cem\u003eTP53\u003c/em\u003e loss of function (LOF) mutation and c-MET activation are frequent events in human HCCs. Here, we discovered that the simultaneous LOF mutations in \u003cem\u003eTP53\u003c/em\u003e and activation of c-MET occur in ~ 20% of human HCCs, and these patients show a poor prognosis. Importantly, we found that concomitant deletion of \u003cem\u003eTrp53\u003c/em\u003e and overexpression of c-MET (c-MET/sgp53) in the mouse liver led to HCC formation \u003cem\u003ein vivo\u003c/em\u003e. Consistent with human HCCs, RNAseq showed that c-MET/sgp53 mouse HCCs were characterized by activated c-MET and Ras/MAPK cascades and increased tumor cell proliferation. Subsequently, a stably passaged cell line derived from a c-MET/sgp53 HCC and corresponding subcutaneous xenografts were generated. Also, \u003cem\u003ein silico\u003c/em\u003e analysis suggested that the MEK inhibitor trametinib has a higher inhibition score in \u003cem\u003eTP53\u003c/em\u003e null human HCC cell lines, which was validated experimentally. We consistently found that trametinib effectively inhibited the growth of c-MET/sgp53 HCC cells and xenografts, supporting the possible usefulness of this drug for treating human HCCs with \u003cem\u003eTP53\u003c/em\u003e-null mutations. Altogether, our study demonstrates that loss of \u003cem\u003eTP53\u003c/em\u003e cooperates with c-MET to drive hepatocarcinogenesis in vivo. The c-MET/sgp53 mouse model and derived HCC cell lines represent novel and useful preclinical tools to study hepatocarcinogenesis in the \u003cem\u003eTP53 null\u003c/em\u003e background.\u003c/p\u003e","manuscriptTitle":"Loss of TP53 cooperates with c-MET overexpression to drive hepatocarcinogenesis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-11-03 18:30:56","doi":"10.21203/rs.3.rs-2176178/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2022-11-24T10:38:01+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2022-11-24T08:25:57+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2022-11-20T14:26:56+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2022-11-04T20:23:00+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2022-11-02T22:22:57+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2022-10-29T14:32:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-10-18T11:05:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cell Death \u0026 Disease","date":"2022-10-17T18:17:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-10-17T18:17:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cell-death-and-disease","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddis","sideBox":"Learn more about [Cell Death \u0026 Disease](http://www.nature.com/cddis/)","snPcode":"41419","submissionUrl":"https://mts-cddis.nature.com/cgi-bin/main.plex","title":"Cell Death \u0026 Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f0a867ef-d625-4c9c-90b1-9069d6a529de","owner":[],"postedDate":"November 3rd, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":16578108,"name":"Biological sciences/Cancer/Gastrointestinal cancer/Liver cancer"},{"id":16578109,"name":"Health sciences/Medical research/Experimental models of disease"}],"tags":[],"updatedAt":"2023-07-28T07:11:44+00:00","versionOfRecord":{"articleIdentity":"rs-2176178","link":"https://doi.org/10.1038/s41419-023-05958-y","journal":{"identity":"cell-death-and-disease","isVorOnly":false,"title":"Cell Death \u0026 Disease"},"publishedOn":"2023-07-27 04:00:00","publishedOnDateReadable":"July 27th, 2023"},"versionCreatedAt":"2022-11-03 18:30:56","video":"","vorDoi":"10.1038/s41419-023-05958-y","vorDoiUrl":"https://doi.org/10.1038/s41419-023-05958-y","workflowStages":[]},"version":"v1","identity":"rs-2176178","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2176178","identity":"rs-2176178","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}