Interaction between TUG1 and METTL3 dynamically regulates liver cancer cell self-renewal

Interaction between TUG1 and METTL3 dynamically regulates liver cancer cell self-renewal | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Interaction between TUG1 and METTL3 dynamically regulates liver cancer cell self-renewal Ping Hou, Rongshou Wu, Juan Luo, Jianyong Deng, Rongguiyi Zhang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5347898/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The long non-coding TUG1 regulates the mRNA stability of target genes by acting as a competing endogenous RNA in the cytoplasm. However, its function in the nucleus and the underlying mechanism are unknown. We examined the potential interaction between TUG1 and METTL3 and the underlying molecular mechanism in liver cancer cells. Methods The expressions of TUG1 and METTL3 in hepatocellular carcinoma (HCC) tissues and liver cancer cell lines were examined by quantitative RT-PCR, western blotting, and fluorescence in situ hybridization. Loss of function experiments were used to examine the role of TUG1 and METTL3 in HCC. A liver cancer tissue microarray was used to identify the influence of METTL3 on prognosis and clinical outcomes. In vitro analyses, whole transcriptome sequencing, RNA sequencing, and database analyses were performed to investigate the molecular mechanism of TUG1 and METTL3 in liver cancer. Results TUG1 and METTL3 were localized in the nucleus of liver cancer cells. Knockdown of TUG1 and METTL3 decreased the proliferative and migration ability of liver cancer cells in vitro, and METTL3 knockdown promoted tumorigenicity in vivo. High METTL3 expression correlated with unfavorable prognosis of HCC patients. Mechanistic studies revealed that TUG1 regulates METTL3 transcriptional expression by binding and recruiting EZH2 to the METTL3 promoter and increasing H3K27me3 levels. TUG1 is regulated by METTL3 in a m6A-YTHDC1-dependent manner. Knockdown of METTL3 substantially abolished the m6A level of TUG1 and augmented TUG1 expression. METTL3 and EZH2 proteins may indirectly interact through the “bridge” of TUG1. The interaction between TUG1 and METTL3 may play a role in liver cancer self-renewal. Conclusion: TUG1 may epigenetically repress METTL3 transcription in liver cancer cells by binding and recruiting EZH2 to the METTL3 promoter region, resulting in increased H3K27me3 levels. METTL3 regulates TUG1 transcription in an m6A-dependent manner. The interaction between METTL3 and TUG1 dynamically regulates liver cancer cell self-renewal activity. TUG1 METTL3 EZH2 Interaction Self-renewal Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Background Hepatocellular carcinoma (HCC) is one of the most common malignancies and the third common cause of cancer-related death. Liver resection is a curative treatment for patients diagnosed at a very early stage. However, most patients, especially those in developing countries, are diagnosed at advanced stage and thus not eligible for liver resection ( 1 ). The complicated etiologies of HCC, including hepatitis virus infection, alcoholic liver disease, nonalcoholic fatty liver disease, and complex pathogenesis, lead to the extreme heterogeneity of HCC, which is an underlying cause of the difficulty to eliminate cancer cells through targeted drugs or precise treatment ( 2 ). Therefore, better understanding of the mechanisms in HCC is critical to identify therapeutic targets and improve patient treatment. LncRNAs in the cytoplasm regulate protein levels, either by maintaining mRNA stability or acting as competing endogenous RNAs. Studies have shown that lncRNAs play key roles in HCC carcinogenesis ( 3 ). The TUG1 lncRNA, located on human chromosome 22q12.2, was first identified in a mouse model of retinal cells treated with taurine ( 4 ). TUG1 has been shown to function as an oncogenic or tumor suppressive lncRNA in different types of cancer and influences the expression of multiple genes ( 5 ). A previous study revealed a novel regulatory association among TUG1, miR-455-3p, AMPKβ2, and HK2 that regulates glycolytic metabolism and metastasis in HCC cells ( 6 ). We previously found that TUG1 competitively binds to miR-29a in the cytoplasm to regulate IFITM3 and promotes the invasion and metastasis of HCC ( 7 ). The nuclear function of TUG1 and related mechanism have not been identified. Hepatocarcinogenesis is a multistep process that involves complex interactions among genetics, epigenetics, and transcriptomic alterations ( 8 ). Studies have shown that aberrant epigenetic regulation is a critical mechanism that leads to profound gene expression changes that promote HCC formation and development ( 8 , 9 ). N6-methyladenosine (m6A) is the most prevalent mechanism of post-transcriptional RNA regulation and influences mRNA splicing, stabilization, and degradation. Studies have shown a role for m6A in the development of disease, including cancer ( 10 ). Methyltransferase-like 3 (METTL3) is a key protein in the m6A methyltransferase complex. Previous studies have revealed the role of METTL3 in multiple biological functions of tumors ( 11 ). A recent report showed that METTL3 increases the m6A methylation level of SOCS2 mRNA, enhancing its recognition by the cytoplasmic reading protein YTHDF2 and promoting its degradation, which results in the malignant progression of HCC ( 12 ). METTL3-mediated m6A modification was also associated with the upregulation of LINC00958 in HCC, likely by regulating transcript stability ( 13 ). A previous study showed that METTL3 knockdown impairs the transcriptional silencing mediated by the lncRNA XIST ( 14 ). Similar to XIST, TUG1 binds RNA-binding proteins in the nucleus, regulating transcriptional repression and tumorigenesis ( 15 , 16 ). Whether TUG1 is regulated by METTL3 has not been investigated. In this study, we investigated the function of TUG1 in liver cancer, the potential interaction with METTL3, and the underlying molecular mechanism in liver cancer cells. Our results provide an insight into the interaction between TUG1 and METTL3 in the nucleus, with a potential role in liver cancer cell self-renewal. Methods 1. Cell cultures and construction stable transfection cell lines The human HCC cell lines SMMC7721, HCCLM3, MHCC97H, and Huh-7,and the immortalized liver cell lines HL7702 were used in this study, and all were procured from the Shanghai Institute of Cell Biology (Shanghai, China). All cell lines were cultured in high-sugar DMEM (Solarbio,Beijing, China) supplemented with 10% FBS (Biological Industries, Beit-Haemek, Israel), 100 U/mL penicillin and 100 µg/mL streptomycin with 5% CO2 and at 37°C in a humidified incubator.Construction of TUG1 and METTL3 shRNA(short hairpin) lentiviral vector,negative control group lentivirus and transfection reagent were manufactured by Genechem Co., Ltd. (Shanghai, China),follow the instructions to establish its stable transfection cell lines,respectively. EZH over- expression plasmid ( HG11337-CY,pCMV-HA-hEZH2)was purchased from Sino Biological Inc. (Beijing, China).Cell transfection using Lipo3000™ reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions.The related targeting series primers are given in Supplementary Table S1 . 2. Flow cytometry EdU incorporation assay Huh7 and HCCLM3 control group and shTUG1 cells ,Huh7 and MHCC-97H control group and shMETTL3 cells were planted in 35 mm glass-bottom dishes (Cellvis, D35-20-1-N) and subjected to the indicated treatments. kFluor647 Click-iT EdU Imaging Kit was utilized to measure cell proliferation based on the manufacturer’s instructions. Briefly, EdU (20 mmol/L) was added to the medium for 2.5 h. After fixation and permeabilization, Add 1mL of Click-iT reaction mixture to each tube, mix well, and incubate the reaction mixture at room temperature protected from light for 30 minutes.Cells were resuspeded in 500µl PBS and tested with flow cytometry(beckmancoulter,USA.). 3. Nuclear-plasma separation assay Cytoplasmic and nuclear RNA and protein extraction were performed using a commercial kit (Beyotime Institute of Biotechnology ,P0028) following the manufacturer’s instructions.liver tumor cells(Huh7) were harvested and suspended by equal volume solution A containing 1% PMSF, and cell lysates weremixed with 10 µl solution B by vortex and placed on ice for 1 min. cell sample fragments were homogenized with a mixture of solutions A and B by a glass homogenizer. Supernatant (cytoplasmic protein and RNA) was obtained after 12,000 rpm centrifugation for5 min; 50 µl solution C was used to suspend the sediment. Samples were mixed by vortex for 30s every 2 min for 15 times, and supernatant (nuclear protein and RNA) was collected after centrifugation. 4. Dual immunofluorescence stain Dry the cell climbing slides slightly and add 50–100 µl of permeabilize working solution. Incubate for 20 min at room temperature. Wash three times with PBS solution, 5 min each.Block with serum: eliminate obvious liquid, cover objective area with 10% donkey serum (for the case of primary antibody originated from goat) at room temperature for 30 min. Incubate cells with anti-mouse EZH2 (AC11; 1:100 dilution; Invitrogen. ThermoFisher scientific, USA) and anti-rabbit METTL3 (ab195352; 1:50 dilution; Abcam, Cambridge, UK), was used for incubating the sections overnight at 4˚C, while for negative controls PBS was used in the place of the antibody, placed in a Rocker device and 5 min each. Incubation with goat anti-mouse IgG (Alexa Fluor 488; GB25301,Servicebio,Wuhan,China) and goat anti-rabbit IgG (Alexa Fluor 488;GB25303, Servicebio,Wuhan,China) secondary antibodies at 25°C for 50 min. Then incubate with DAPI solution at room temperature for 10 min.Microscopy detection and collect images by Fluorescent Microscopy(C1; Nikon, Tokyo, Japan). 5. Biotin-streptavidin pull-down assay and mass spectrometry The oligonucleotides containing biotin on the 5' nucleotide of the sense strand were used in the pull-down assays. 1 µg of each double-stranded oligonucleotide was incubated with 300 µg of nuclear protein for 20 min at room temperature, and 30 µl of poly (dI–dC) preabsorbed streptavidin–agarose beads were added at 4°C for 4 h. The protein–DNA–streptavidin–agarose complex was analyzed with SDS-PAGE.Mass spectrometry for more information see our previous study( 17 ) . 6. RNA immunoprecipitation(RIP) and m6A RNA immunoprecipitation (MeRIP) assay Cells cultured in 10 cm plate was washed twice with ice cold PBS and scraped off in 1 mL PBS. Then the cell was centrifuged and re-suspended in an equal pellet volume of complete RIP lysis buffer (Merck Millipore). 5 µg antibody(anti-YTHDC1 (ab122340, Abcam) was pre-bound to Protein A/G magnetic beads in immunoprecipitation buffer for 2 h and then incubated with 100 µl cell lysates over night at 4°C with rotation. Then RNA was eluted from the beads by incubating with 400 µl elution buffer for 2 h. The eluted RNA was precipitated with ethanol and dissolved with RNase-free water. Enrichment of certain fragments was determined by real-time PCR.For MeRIP, TUG1 extracted from equal amount cell lysates was used as input to measure the m6A-methylated rate of TUG1. Antibodies used in this experiment were as follows: anti-m6A (ab190886, Abcam), Anti-IgG (Cell Signaling Technology,USA).IgG was used for negative control,Primers used for TUG1 and relative antibodies are included in supplementary table 1 and Table 2 . Table 1 Relationship between METTL3 and clinicopathologic factors of HCC patients. Variable Total N = 80 METTL3 P value High expression Low expression Age(years) 0.107 < 55 74 25 49 ≥ 55 6 4 2 Sex Male 68 27 45 0.483 Female 12 2 23 Tumor size(cm) 0.072 < 5 37 18 19 ≥ 5 43 11 32 Tumor number 0.043 Single 73 24 49 Multiple 7 5 4 HBsAg 0.893 Positive 60 22 38 Negative 20 7 13 AFP(ng/ml) 0.079 < 400 42 19 23 ≥ 400 38 10 28 Cirrhosis 0.26 Positive 43 18 25 Negative 37 11 26 Child-pugh 0.485 A 72 27 45 B 8 2 6 Excision range 0.672 Minor 68 24 44 Major 12 5 7 Clinical Stage 0.006 I/II 66 27 39 III/IV 14 2 12 MVI Positive 32 22 25 0.029 Negative 48 7 26 Table 2 Univariable analysis of factors associated with overall survival(OS) and disease-free survival(DFS) for HCC patients. Variable Univariate (P value) Overall survival Disease-free survival Age( years) 0.373 0.370 < 55 ≥ 55 Sex 0.130 0.103 Male Female AFP(ng/ml) 0.108 0.083 < 400 ≥ 400 HBsAg 0.512 0.438 + - Tumor number 0.022 0.020 Single Multiple Tumor size(cm) 0.797 0.973 < 5 ≥ 5 Cirrhosis 0.156 0.152 Positive Negative Child-pugh 0.436 0.512 A B Excision range 0.809 0.822 Minor Major H-score 0.000 0.000 High Low Clinical Stage 0.007 0.000 I/II III/IV MVI 0.039 0.000 Positive Negative 7. Stem sphere-forming assay Resuspend cells in stem cell medium(DMEM/F12 + 1xB27 + 20ng/ml bFGF + 20ng/ml EGF) and count Single-cell suspensions were plated in ultralow attachment six-well plates (Corning) at a density of 5×10 3 cells/ml and grown in modified DMEM, as described in the “Cell Culture” section, without serum supplementation. Medium was replaced every 3 days. Spheres were counted after 14 days (passage one, P1). For the secondary sphere formation assay, the spheres were scattered and re-seeded in 96-well plates at a density of about 100 cells per well. We counted the number of secondary spheres formed at 10 days post-incubation. 8. Chromatin immunoprecipitation (ChIP) assay H3K27me3,EZH2 ChIP-qPCR were performed according to the manufacturer’s instructions for the Simple ChIP Plus Enzymatic Chromatin IP Kit (9005, Cell Signaling Technology, Danvers, MA).In summary,Huh7 and MHCC-LM3 Cells were cross-linked with 1% formaldehyde.Antibodies (rabbit IgG ,H3K27me3 and EZH2) were bound to protein A-coated magnetic beads and incubated for 2 hours at 4°C. The fragmented chromatin was added to antibody-coated beads and incubated on a rotating wheel overnight at 4°C, the sheared chromatin was eluted using DNA elution buffer.Results were normalized using the internal control IgG. Precipitated chromatin DNA was recovered and analyzed by qPCR.Primers used for METTL3 promoter and antibodies are included in supplementary table 1 and Table 2 . 9. Whole transcriptome sequencing, RNA sequencing and analyses Total RNA was isolated and purified using Trizol reagent (Invitrogen, Carlsbad, CA, USA) following the manufacturer's procedure. Approximately 2 ug of total RNA was used to deplete ribosomal RNA according to the manuscript of the Ribo-Zero™ rRNA Removal Kit (Illumina, San Diego, USA). The cleaved RNA fragments were reverse-transcribed to create the cDNA,which were next used to synthesise U-labeled second-stranded DNAs with E. coli DNA polymerase I (NEB, cat.m0209, USA), RNase H (NEB, cat.m0297, USA) and dUTP Solution (Thermo Fisher, cat.R0133, USA). Each adapter contains a T-base overhang for ligating the adapter to the A-tailed fragmented DNA. Single-or dual-index adapters are ligated to the fragments, and size selection was performed with AMPureXP beads.The ligated products are amplified with PCR, the average insert size for the final cDNA library was 300 bp (± 50 bp). At last, we performed the paired-end sequencing on an Illumina Hiseq 6000 (LC-Bio Technology CO., Ltd., Hangzhou, China) following the vendor's recommended protocol.For bioinformatics analysis of RNA-seq, fast p was used to remove the reads that contained adaptor contamination, low quality bases and undetermined bases( 18 ). Then sequence quality was also verified using fast p, we used Bowtie2 and Tophat2 to map reads to the genome of Homo sapiens GRCh37/hg19( 19 , 20 ). The mapped reads of each sample were assembled using StringTie( 21 ). Then, all transcriptome from all samples were merged to reconstruct a comprehensive transcriptome using gffcompare ( https://github.com/gpertea/gffcompare/ ). All transcripts with CPC score <-1 and CNCI score 1 or log2 (fold change) <-1 and with parametric F-test comparing nested linear models (p value < 0.05) by R package edge. 10. Animal experiments The establishment and analysis of subcutaneous xenograft models in nude mice (male BALB/c nu/nu nude mice, 4 -6weeks old) were performed. .As we described previously,1× 10 7 cells in 100 µL of PBS were injected subcutaneously into female BALB/nude mice ( n = 4 per group) (Hunan SJA Laboratory Animal Co., Ltd., Hunan, China)[21]. After 6 weeks, the mice were euthanized under anesthesia, the tumor mass was excised, both the weight and volume of the tumor mass was measured. 11. Statistical analysis R software (version 3.5.1) was used for statistical analysis and data visualization. Protein and RNA levels were compared using two-tailed Student’s t test. Correlations between METTL3 expression in HCC tissues and clinicopathological features were analyzed with Pearson Chisquare (χ2) test. Overall survival (OS) and disease- free survival (DFS) was assessed by Kaplan-Meier method, difference between survival curves was determined by log-rank test. Differences with a p value < 0.05 were considered as statistically significant. Results 1. TUG1 is highly expressed in liver cancer cells and HCC tissues and promotes liver cancer cell proliferation and migration The subcellular localization of TUG1 in various cancer cell lines was predicted using the lncATLAS database. The results indicated that TUG1 is mainly localized in the nucleus. Approximately 60% is present in the nucleus in HepG2 cells, with 39.1% in the cytoplasm ( Fig. 1 A ) . We verified that TUG1 mRNA is mainly expressed in the nucleus of Huh7 by RT-PCR ( Fig. 1 B ) . RNA-FISH further confirmed nuclear localization of TUG1 mRNA in Huh7 cells ( Fig. 1 C ) . We found that TUG1 was expressed at high levels in liver cancer cell lines (Huh7, MHCC-97h, HCC-LM3, SMMC-7721) compared with a normal liver cell line (HLC7702), with the highest expression level detected in Huh7 cells ( Fig. 1 D ) . RNA-FISH analysis of 10 HCC tissues and normal liver tissues showed that TUG1 mRNA was upregulated > 2.0-fold in HCC tissues compared with adjacent normal tissues ( P < 0.001) ( Fig. 1 E, F ). To examine the role of TUG1 in the proliferation and migration of liver cancer cells, we first stably transfected shTUG1 lentiviral vector and control vectors into Huh7 and HCC-LM3 cells and confirmed the downregulation of TUG1 mRNA by RT-PCR ( supplementary Fig. 1A ). CCK8 assays showed that downregulation of TUG1 significantly reduced the cell proliferation ability of Huh7 and HCC-LM3 cells compared with controls ( supplementary Fig. 1B ). Wound-healing assays showed that the migration activity of Huh7 and HCC-LM3 cells was significantly reduced after TUG1 knockdown for 24 h compared with the controls (P < 0.05) ( supplementary Fig. 1C ). EdU assay showed that the proliferation ratio of Huh7 and HCC-LM3 cells was significantly lower after TUG1 stable knockdown compared with the control ( supplementary Fig. 1D ). Colony formation assay showed that the number of single clones formed in Huh7 and HCC-LM3 cells was significantly reduced after TUG1 knockdown ( supplementary Fig. 1E ). 2. TUG1 negatively regulates METTL3 expression by promoting H3K27me3 modification of the METTL3 promoter through the PRC2 core enzyme EZH2. Our results indicated that TUG1 has an important role in the proliferation of liver cells. To explore the underlying molecular mechanisms, we performed transcriptome sequencing in control and shTUG1,3vs3. The transcriptome sequencing results revealed that 14209 genes were upregulated and 14293 genes were downregulated in cells with TUG knockdown; among the differentially expressed genes, there were 981 upregulated and 856 downregulated genes (Fig. 2 A ) . Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated TUG1 is more important in tumor pathway than that in other disease ( Fig. 2 B ) . Gene Ontology (GO) enrichment analysis of the differentially expressed genes showed that the top enriched pathways included DNA-binding transcription factor activity ( Fig. 2 C ) We next examined the transcriptome sequencing results for genes encoding m6A-related proteins (METTL3, METTL14, WTAP, METTL16, RBM15B, RBM15, FTO, ALKBH5, YTHDF1–3, YTHDC1–2, IGFBP1-3). The results revealed that the mRNA expression of METTL3 was significantly increased in cells with TUG1 downregulation compared with controls (Fig. 2 D ). Knockdown of TUG1 in Huh7 and MHCC-97h cells led to upregulated METTL3 mRNA and protein expression levels ( Fig. 2 E, F ). Analysis of a public database (( http://rnainter.org/ ) indicated that TUG1 can be combined with EZH2 ( Fig. 3 A ) . Previous studies reported that TUG1 interacts with the polycomb repressive complex 2 (PRC2) core enzyme EZH2, which leads to increased H3K27me3 modification of promoters and subsequent inhibited gene transcription ( 16 , 23 , 24 ). Western blotting demonstrated that EZH2 and H3K27me3 levels were reduced in Huh7 and MHCC-LM3 cell lines with TUG1 knockdown ( Fig. 3 B ). We next performed rescue experiments. EZH2 overexpression plasmid was transiently transfected into TUG1 knockdown and control Huh7 and MHCC-LM3 cells. The EZH2 transfected group showed increased levels of EZH2 and H3K27me3 and downregulated METTL3 protein. In the shTUG1 group, METTL3 level increased, as described above, while EZH2 and H3K27me3 levels decreased; overexpression of EZH2 in shTUG1 cells led to decreased METTL3 protein level and increased EZH2 and H3K27me3 levels ( Fig. 3 C, D ) . UCSC database predicted the presence of an H3K27me3 site in the METTL3 promoter (supplement Fig .2A) . ChIP-qPCR assays revealed that knockdown of TUG1 decreased the binding of EZH2 to the METTL3 promoter and resulted in reduced H3K27me3 levels in the METTL3 promoter compared with controls ( Fig. 3 E, F ) . We then performed pull-down assays using a biotin-labeled DNA probe specific to the METTL3 promoter region.Mass spectrometry analysis of the results of TUG1 knockdown group and the control group, regardless of whether TUG1 was down regulated, revealed were 2131 proteins overlap between TUG1 knockdown group and the control group( supplement Fig .2B) .the results revealed the decrease of EZH2 protein band in the shTUG1 group ( Fig. 3 G ) .Western blot from the pull down assays revealed decreased levels of EZH2 and H3K27me3 at the METTL3 promoter in the shTUG1 group compared with the control group ( Fig. 3 H ). Taken together, these data suggest that promotes EZH2 occupancy at the METTL3 promoter and increases H3K27me3 at the promoter. 3. METTL3 is highly expressed in liver cancer cells and promotes proliferation in vitro and in vivo We next investigated whether METTL3 plays a role in the proliferation and metastasis of HCC cells. We detected higher METTL3 mRNA expression in Huh7 and MHCC-97h cell lines by RT-qPCR ( Fig. 4 A ) . Immunofluorescence and western blot revealed that METTL3 was expressed at higher levels in the nucleus ( Fig. 4 B, C ) . We used Huh7 and MHCC-97h cell lines to generate stable METTL3 knockdown cell lines, and the knockdown efficiency was over 60% ( Fig. 4 D, E). CCK8 assays revealed that down-regulation of METTL3 significantly reduced the cell proliferation ability of Huh7 and MHCC97H liver cancer cells compared with controls (Fig. 4 F). The number of single clones formed in Huh7 and MHCC97H cells after METTL3 knockdown was significantly reduced compared with controls (Fig. 4 G). EdU assay showed that the proliferation ratio of Huh7 and MHCC97H cells was significantly lower after METTL3 knockdown compared with controls (Fig. 4 H). Wound healing assays revealed significantly reduced migration activity of Huh7 and MHCC97H cells after METTL3 knockdown for 24 h (P < 0.05). We next examined the role of METTL3 in liver cancer cell proliferation in vivo. ShMETTL3 and control Huh7 and MHCC97H cells were injected into nude mice. After 6 weeks, the average tumor weights were significantly smaller in the ShMETTL3 Huh7 and MHCC97H groups compared with controls (P < 0.05) (Fig. 4 I, J). Moreover, the average tumor volume was significantly reduced in the ShMETTL3 Huh7 group compared with controls (P < 0.05) (Fig. 4 K). Taken together, these data indicated that METTL3 promoted HCC cell proliferation in vitro and in vivo. 4. The influence of METTL3 on prognosis and clinical outcome in HCC patients We next examined the expression of METTL3 in liver cancer tissues using RT-PCR, western blot, and tissue microarray (TMA). The protein and mRNA levels of METTL3 in 10 HCC tissues were higher than those in adjacent tissues (Fig. 5 A, B). Immunohistochemical examination of TMA containing samples from 80 HCC patients revealed higher expression of METTL3 in HCC tissues compared with normal tissue, and METTL3 expression was significantly correlated with clinical stage (Fig. 5 C, D). Upregulated expression of METTL3 was significantly associated with tumor size (P = 0.032), tumor number (P = 0.032), clinical stage (P = 0.006) and microvascular invasion(MVI) (P = 0.029) ( Table 1 ). Survival analysis using the Kaplan–Meier method indicated that HCC patients with high METTL3 expression exhibited a worse overall survival (OS) rate and disease-free survival (DFS) rate (Fig. 5 F). Univariate and multivariate analyses showed that high METTL3 expression was an unfavorable independent prognostic for OS ( HR 1.740; 95%CI: 1.401–2.312; P < 0.020) and DFS (HR 1.831; 95%CI: 1.520–2.232; P < 0.020) ( Table 2 ) (Fig. 5 E). Collectively, these results indicated that METTL3 was significantly upregulated in HCC and may be associated with HCC progression. 5. METTL3 negatively regulates TUG1 through a m6A-YTHDC1-dependent pathway M6A modification of lncRNA may affect lncRNA transcription. We examined whether the effects of METTL3 on downregulating TUG1 depends on its m6A-related activity. Compared with control group (3vs3), METTL3 was ectopically knockdown expressed in Huh7 whole transcriptome sequencing, the potential negatived alterations of TUG1 up-expression level were then assessed in integrative genomics viewer (Fig. 6 A).RT-PCR further revealed that knockdown of the m6A enzyme METTL3 in Huh7 and MHCC-97H cells resulted in increased TUG1 lncRNA levels (Fig. 6 B).We downloaded MeRIP sequencing data from the GEO database (GSE102620 and GSE110320) of HepG2 cells with transient transfection of siMETTL3 and siMETTL14 and stable transfection of shMETTL3 and shMETTL14. We observed a potential m6A decreased-modification in the TUG1 (NM_001398476) sequence at Chr22:30978500–30978780 (Fig. 6 C, D). Analysis using an online m6A site predictor (SRAMP) revealed a GAACU motif in Chr22:30978500–30978780 (230 bp) 3’UTR location ( Fig. 6 E ) . The secondary structure of the TUG1 m6A modification site is shown ( supplementary Fig. 2C) . MeRIP-qPCR revealed that m6A modification of TUG1 in Huh7 and MHCC-97H cells was significantly decreased after knockdown of METTL3 compared with controls (Fig. 6 F). These results suggest that METTL3 may be involved in the negative regulation of TUG1 transcription through modulating m6A modification of TUG1. YTHDC1 and YTHDC2 are m6A reader proteins in the nucleus. YTHDC2 is mainly involved in splicing regulation through RNA m6A modification, and YTHDC1 was shown to promote lncRNA degradation through m6A modification. We scanned ENCORI databases and found that YTHDC1 contained multiple putative binding sites for TUG1, one of which was further confirmed by RIP-qPCR, TUG1 mRNA in METTL3-knockdown expressed cell was decreased compared with control group (Supplementary Fig .2D) (Fig. 6 G). Together, these results indicate that METTL3 negatively regulates TUG1 expression in a m6A- and YTHDC1-dependent manner. 6. METTL3 co-localizes with EZH2, and METTL3 and TUG1 regulate liver cancer cell self-renewal We performed whole transcriptome sequencing of Huh7 cells with stable METTL3 knockdown (3vs3); differentially expressed genes are shown in a heat map (Fig. 7 A). GO analysis of differentially expressed genes revealed significant upregulation of RNA binding proteins (Fig. 7 B). Among the differential genes, further GO analysis was continued through histone regulation-related genes. We found that H3K27me3 was significantly upregulated in cells with METTL3 downregulation (Fig. 7 C). Western blot of Huh7 and MHCC-97H cells downregulated for METTL3 showed significant upregulation of EZH2 and H3K27me3 levels compared with controls (Fig. 7 D). We treated METTL3 knockdown cells with EZH2 inhibitors DZnep and GSK126 and found that the up-regulated EZH2 and H3K27me3 levels were decreased, and downregulated METTL3 protein was significantly increased (Fig. 7 E, F). These results suggest METTL3 negatively regulates EZH2 and H3K27me3 levels. Dual-color immunofluorescence revealed the co-localization of METTL3 and EZH2 in the nucleus in liver cancer cell lines and liver cancer tissues (Fig. 8 A, B). However, co-immunoprecipitation analysis indicated no interaction between METTL3 and EZH2 proteins (Fig. 8 C, D). We examined the influence of METTL3 and TUG1 on cell self-renewal activity through sphere formation experiments. The numbers and diameter of spheres were significantly lower in cells with METTL3 or TUG1 knockdown compared with controls (P < 0.05) (Fig. 8 E, F). Discussion Current studies have demonstrated that m6A influences lncRNA stability and translation efficiency in the regulation of liver cancer progression ( 25 ). However, the interactions and mechanisms between m6A and m6A-regulated lncRNA remain largely unknown. Our study suggests that METTL3 and TUG1 interact and regulate the self-renewal of liver cancer cells. Our results showed that TUG1 inhibits the transcription of METTL3 by binding to the PRC2 core enzyme EZH2 and recruiting H3K27me3 to the METTL3 promoter region in liver cancer cells. We further found that METTL3 also participates in m6A regulation of TUG1 and negatively regulates its transcription in a YTHDC1-dependendent manner. Furthermore, we demonstrated that TUG1 may be a “bridge” between METTL3 modificated-m6A and its RNA binding protein EZH2 interaction, regulating the self-renewal of liver cancer cells. Our results describe the potential roles of m6A-lncRNA-histone modification in the self-renewal of liver cancer cells. These results indicate the possibility to develop therapeutic strategies against liver cancer progression by targeting this regulatory mechanism. Interventions targeting TUG1 or its downstream pathways may hold therapeutic promise for liver diseases, especially in HCC ( 23 , 26 , 27 ). A recent investigation revealed that TUG1 in the nucleus regulates H3K27me3 modification of target genes by recruiting EZH2, which is one of the subunits of PRC2 that suppress gene expression ( 28 ). The current study showed that TUG1 not only promotes liver cancer cell proliferation and migration, but also promotes liver cancer cell self-renewal, consistent with recent findings of TUG1 in glioma ( 29 ). We established METTL3 as the downstream regulatory gene of TUG1 in regulating liver cancer cell self-renewal. Research has revealed the vital roles of RNA modification in tumorigenesis. The m6A methyltransferase METTL3 enhances HCC invasion and metastasis in vitro and in vivo by regulation of key EMT factors SNAIL and CTNNB1 ( 30 ). METTL3 is markedly downregulated in samples from patients with sorafenib-resistant HCC, and depletion of METTL3 in human liver cancer cells enhanced sorafenib resistance by regulating the stability of FOXO3 transcript in a YTHDF1-dependent manner ( 31 ). METTL3 is upregulated in lenvatinib-resistant HCC and promotes lenvatinib resistance through the regulation of EGFR mRNA translation in human liver cancer cells ( 32 ). These different roles of METTL3 in the regulation of sorafenib and lenvatinib sensitivity may be because of different downstream targets and its localization-specific function in human cancer cells ( 33 , 34 ). METTL3-knockout mice are embryonic lethal, which is consistent with the observation that Mettl3 inactivation in mouse embryonic stem cells resulted in a loss of self-renewal capabilities ( 35 ). We demonstrated that METTL3 is expressed at high levels in the nucleus of liver cancer cells and HCC tissues; METTL3 promotes liver cancer proliferation and metastasis and regulates the self-renewal of liver cancer cells. We also found that METTL3 was independently associated with advanced disease and poor overall survival in patients with HCC. Moreover, we confirmed that METTL3 may negatively regulate TUG1 transcription in a m6A-YTHDC1-dependent manner. Consistent with literature indicated that the knockdown of METTL3 was lead to up-regulated XIST transcriptional level, mainly because the recognition of m6A on XIST by "Reader" YTHDC1 leads to the decreased decay of XIST ( 14 ). The m6A regulation of XIST was reported in studies on the roles of m6A in stemness-associated genes ( 36 ). Our findings show that after downregulating METTL3, the m6A modification of TUG1 decreased and TUG1 expression was upregulated, which may be because of reduced recognition by the YTHDC1 reader and subsequent degradation. We confirmed that TUG1 and its binding protein EZH2 interact with METTL3 to dynamically regulate the self-renewal of liver cancer cells. Accumulating studies have focused on the interaction between histone enzymes and m6A modifications ( 37 – 39 ). Histone modifications that promote transcription include H3K36me3, H3K4me3, and H3K27ac, all of which are co-localized with the m6A modification site ( 40 ). Histone modification sites that inhibit transcription include H3K9me2, H3K9me3, H3K27me3, all of which are opposed to the m6A modification site ( 41 , 42 ). Wang et al. d emonstrated that in mouse neuronal stem cells with METTL3 knockout, H3K27me3 levels increased by 71%; their results showed that m6A participates in the regulation of self-renewal and gene rearrangement of neural stem cells through specific histone modifications ( 41 ).We found that METTL3 is in the negatively interacting with EZH2, H3K27me3,but not directly bind to EZH2 protein. This led us to speculate whether METTL3 and EZH2 proteins may interact through TUG1. m6A influences RNA stability and translation efficiency in the nucleus and also affects RNA-binding protein interactions, modulating their localization to chromatin and regulating post-translational modifications ( 43 ). m6A modification acts as a “molecular switch” that can affect RNA-protein interactions by adjusting the structure of lncRNA ( 44 ). Long et al. reported that PRC2 does not directly bind to the DNA promoter region of target genes, but requires a bridge lncRNA to participate in regulating its positioning throughout the genome, thereby achieving timely and accurate control of growth and development and pluripotent stem cell differentiation ( 45 ). Consistent with literature reported that numerous lncRNAs are retained in the nucleus through different mechanisms and can provide feedback on transcription and modulate the chromatin state( 46 , 47 ). We speculated whether the m6A methyltransferase complex and histone modification enzymes indirectly interact through the “bridge” of lncRNA to form a large complex that regulates the self-renewal of tumor cells. In future studies, we plan to explore the specific molecular mechanism in depth. Conclusion The regulation between TUG1 and METTL3 provides a new perspective to study liver cell tumorigenesis. Our findings suggest that a m6A-lncRNA-histone model may be dynamically involved in regulating the self-renewal of liver cancer cells. This discovery enriches our understanding of the m6A-lncRNA-histone dynamic network in the progression of liver cancer and provides therapeutic targets. Abbreviations TUG1 Taurine upregulated gene 1 METTL3 methyltransferase-like 3 EZH2 Enhancer of zeste homolog 2 PRC2 polycomb repressive complex 2 H3K27me3 tri-methylation at lysine 27 of histone H3 m6A N6-methyladenosine HCC hepatocellular carcinoma qRT-PCR quantitative real-time polymerase chain reaction WB western blotting FISH fluorescence in situ hybridization.EdU:5-Ethynyl-2ʹdeoxyuridine CCK-8 cell counting Kit-8 TMA tissue microarray CO-IP co-immunoprecipitation RIP RNA immunoprecipitation MeRIP methylated RNA immunoprecipitation ChIP chromatin immunoprecipitation KEGG kyoto encyclopedia of genes and genomes GO gene ontology HR hazard radio MVI microvascular invasion:OS:overall survival RFS recurrence free survival. Declarations Ethics approval and consent to participate All animal experiments were approved by the Animal Experiment Ethics Committee of the Laboratory Animal Science Center of Nanchang University and were carried out in accordance with the guidelines of the British Animal (Scientifc Procedure) Act of 1986 and the European Union Directive 2010/63/EU. Consent for publication The content of this manuscript has not been previously published and is not under consideration for publication elsewhere. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the National Natural Science Foundation of Author Contribution PH and JL designed the study. PH, JL , RSW and JYD performed most of the experiment. LQW, ELL, WWL ,JKW and RGYL performed the operation and followed-up the patients. PH ,JL,LQW, and ELL analyzed data and drafted the manuscript. LQW and ELL provided the overall guidance. All authors read and approved the final Manuscript. Acknowledgements We thank Gabrielle White Wolf, PhD, from Liwen Bianji (Edanz) ( www.liwenbianji.cn ) for editing the English text of a draft of this manuscript. Availability of data and materials All data generated during this study are included either in article or in the additional files. RNA-seq data will be uploaded to GEO database in the future. References Yang JD, Hainaut P, Gores GJ, et al. A global view of hepatocellular carcinoma: trends, risk, prevention and management. Nat Rev Gastroenterol Hepatol. 2019;2019–10–01(10):589–604. Llovet JM, Kelley RK, Villanueva A, et al. Hepatocellular carcinoma. Nat reviews Disease primers. 2021;2021–01–01(1):6. Klingenberg M, Matsuda A, Diederichs S, Patel T. Non-coding RNA in hepatocellular carcinoma: Mechanisms, biomarkers and therapeutic targets. J HEPATOL. 2017;67(3):603–18. Young TL, Matsuda T, Cepko CL. 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Chen Y, Lin Y, Shu Y, He J, Gao W. Interaction between N6-methyladenosine (m6A) modification and noncoding RNAs in cancer. MOL CANCER 2020; 19(1). Huang H, Weng H, Zhou K, et al. Histone H3 trimethylation at lysine 36 guides m6A RNA modification co-transcriptionally. Nature. 2019;567(7748):414–9. Wang Y, Li Y, Yue M, et al. N6-methyladenosine RNA modification regulates embryonic neural stem cell self-renewal through histone modifications. NAT NEUROSCI. 2018;21(2):195–206. Xu W, Li J, He C et al. , .. METTL3 regulates heterochromatin in mouse embryonic stem cells. 2021. Liu J, Dou X, Chen C, et al. N6-methyladenosine of chromosome-associated regulatory RNA regulates chromatin state and transcription. Sci (American Association Advancement Science). 2020;367(6477):580–6. 2020-01-01. Liu N, Zhou KI, Parisien M, et al. N 6-methyladenosine alters RNA structure to regulate binding of a low-complexity protein. NUCLEIC ACIDS RES. 2017;2017–06–02(10):6051–63. Long Y, Hwang T, Gooding AR et al. RNA is essential for PRC2 chromatin occupancy and function in human pluripotent stem cells. NAT GENET 2020 2020-09-01; 52(9): 931–8. Tang J, Wang X, Xiao D, Liu S, Tao Y. The chromatin-associated RNAs in gene regulation and cancer. MOL CANCER. 2023;2023–02–07(1):27. Chen LL. Towards higher-resolution and in vivo understanding of lncRNA biogenesis and function. NAT METHODS 2022 2022-10-01; 19(10): 1152–5. Additional Declarations No competing interests reported. Supplementary Files floatimage1.jpeg Graphical abstract. A. The interaction between METTL3 and TUG1 dynamically regulates liver cancer cell self-renewal. B. TUG1 epigenetically represses METTL3 transcription in liver cancer cells by binding with and recruiting EZH2 to the METTL3 promoter region, increasing H3K27me3 levels. C. METTL3 negatively regulates TUG1 in a m6A-YTHDC1-dependendent manner. SupplementFig1.pdf SupplementaryFig2.pdf Supplementarymethods.docx Supplementarytables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5347898","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":371615295,"identity":"43812408-194b-4aa4-8aba-da1c65441fdb","order_by":0,"name":"Ping Hou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYBACAxCRwMDAw8/efPBBQoUN8VpkJHuOJRs8OJNGpBYgsDG4kaMm+bDtEGEt5uw9Zg8e7qjlMThzhq0ige0AA397dwJeLZY9Z8wNEs8c55E83nvsRgLPHQaJM2c34HfYjRwzicS2Yzx8Z86l3UiQeMZgIJFLpBYGIKMgweAw0VpqeASADIaEBGK0nDlWbpDYdoAHFMgSCQfSeAj75Xjztoc/2+rsQVH58ec/Gzn+9l78WoCADYgPw3k8hJTDtNQRo3AUjIJRMApGKgAAqbhQeE+H/WwAAAAASUVORK5CYII=","orcid":"","institution":"The Second Affiliated Hospital of Nanchang University","correspondingAuthor":true,"prefix":"","firstName":"Ping","middleName":"","lastName":"Hou","suffix":""},{"id":371615297,"identity":"fb1756ea-12a9-403e-80db-c5bfa0fe8c68","order_by":1,"name":"Rongshou Wu","email":"","orcid":"","institution":"The Second Affiliated Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Rongshou","middleName":"","lastName":"Wu","suffix":""},{"id":371615298,"identity":"a2165e31-f56d-43e5-b044-14bcb2dfaf14","order_by":2,"name":"Juan Luo","email":"","orcid":"","institution":"Gannan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Juan","middleName":"","lastName":"Luo","suffix":""},{"id":371615299,"identity":"bb904a27-6434-467a-a275-fca884c0d351","order_by":3,"name":"Jianyong Deng","email":"","orcid":"","institution":"The first Hospital of Nanchang City","correspondingAuthor":false,"prefix":"","firstName":"Jianyong","middleName":"","lastName":"Deng","suffix":""},{"id":371615300,"identity":"e46576c8-1953-4eef-a861-45043bb3743a","order_by":4,"name":"Rongguiyi Zhang","email":"","orcid":"","institution":"The Second Affiliated Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Rongguiyi","middleName":"","lastName":"Zhang","suffix":""},{"id":371615306,"identity":"ba67ee27-3de6-4f04-81f3-7d519a9e585f","order_by":5,"name":"Weiwei Liu","email":"","orcid":"","institution":"Xinqiao Hospital, Third Military Medical University","correspondingAuthor":false,"prefix":"","firstName":"Weiwei","middleName":"","lastName":"Liu","suffix":""},{"id":371615309,"identity":"d15ba7bd-7cba-4254-b010-6c463a3c3636","order_by":6,"name":"Jiakun Wang","email":"","orcid":"","institution":"The Second Affiliated Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Jiakun","middleName":"","lastName":"Wang","suffix":""},{"id":371615312,"identity":"e7124227-b3d3-4871-8d5b-46bde97b7379","order_by":7,"name":"Linquan Wu","email":"","orcid":"","institution":"The Second Affiliated Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Linquan","middleName":"","lastName":"Wu","suffix":""},{"id":371615313,"identity":"967c3b4d-d2f3-429c-b7b5-89a033b8e44b","order_by":8,"name":"Enliang Li","email":"","orcid":"","institution":"The Second Affiliated Hospital of Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Enliang","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-10-28 14:23:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5347898/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5347898/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":69910674,"identity":"012bfd8e-e416-44a7-a87e-84c87deb5ad2","added_by":"auto","created_at":"2024-11-26 13:52:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1277133,"visible":true,"origin":"","legend":"\u003cp\u003eSubcellular localization and expression of TUG1 in liver cancer cells and HCC[G W1] \u0026nbsp;tissues. \u003cstrong\u003eA. \u003c/strong\u003eThe subcellular localization of TUG1 in various cancer cell lines was predicted using the lncATLAS database[G W2] . \u003cstrong\u003eB. \u003c/strong\u003eTUG1 mRNA was examined in nuclear and cytoplasmic fractions of Huh7 by [G W3] RT-PCR. \u003cstrong\u003eC. \u003c/strong\u003eTUG1 mRNA was detected in Huh7 cells by RNA-FISH, with 18S serving as the cytoplasmic control and U6 serving as the nuclear control; representative images are shown (magnification, 50×). \u003cstrong\u003eD. \u003c/strong\u003eTUG1 mRNA was detected in liver cancer cell lines (Huh7, MHCC-97h, HCC-LM3, SMMC-7721) and a normal liver cell line (HLC7702) by RT-PCR. \u003cstrong\u003eE. \u003c/strong\u003eTUG1 mRNA was detected in 10 HCC tissues and adjacent normal tissues by RNA-FISH; representative images are shown (left: 200×, right: [G W4] 50×) (*P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001, independent Student’s t-test).\u003c/p\u003e\n\u003cp\u003ePlease note to define all abbreviations at first use in the legends.\u003c/p\u003e\n\u003cp\u003eThroughout the legends, please be sure to include information on data and sample sources (database information, cell/tissue types, etc.)\u003c/p\u003e\n\u003cp\u003eFor example, please specify the cell or samples examined here. This comment applies to all further instances.\u003c/p\u003e\n\u003cp\u003ePlease replace XX and YY with figure labels (for example, left and right or top and bottom) to clarify which images correspond with which magnification.\u003c/p\u003e","description":"","filename":"Fig1181.png","url":"https://assets-eu.researchsquare.com/files/rs-5347898/v1/34f9ba303675623be2ef21b6.png"},{"id":69910673,"identity":"c264264a-d003-4fb5-bcee-cff536be2bdc","added_by":"auto","created_at":"2024-11-26 13:52:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":183339,"visible":true,"origin":"","legend":"\u003cp\u003eTUG1 negatively regulates the transcriptional expression of METTL3. \u003cstrong\u003eA.\u003c/strong\u003e[G W1] \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe transcriptome sequencing results of Huh7 cells [G W2] downregulated for TUG1 and controls are shown in the heatmap (control vs shTUG1,3vs3[G W3] ). \u003cstrong\u003eB. \u003c/strong\u003eKyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially expressed genes in cells with TUG1 knockdown.\u003cstrong\u003eC. \u003c/strong\u003eGene Ontology (GO) enrichment analysis of differentially expressed genes in cells with TUG1 knockdown. \u003cstrong\u003e\u0026nbsp;D\u003c/strong\u003e. Heatmap analysis of m6A-related gene expressions from the transcriptome sequencing results. \u003cstrong\u003eE\u003c/strong\u003e. RT-PCR of METTL3 mRNA levels in Huh7 and MHCC-97h cells with knockdown of TUG1. \u003cstrong\u003eF.\u003c/strong\u003e Western blot analysis of METTL3 levels in Huh7 and MHCC-97h cells [G W4] with knockdown of TUG1 (*P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, independent Student’s t-test).\u003c/p\u003e\n\u003cp\u003eAs noted in the main text, I recommend presenting the overall results first here as shown. Please change figure panel labels accordingly.\u003c/p\u003e\n\u003cp\u003ePlease specify the cell line.\u003c/p\u003e\n\u003cp\u003ePlease clarify this text.\u003c/p\u003e\n\u003cp\u003ePlease be sure to label the lanes in the figure (clarify the difference between lanes 1 and 3 and lanes 2 and 4)\u003c/p\u003e","description":"","filename":"Fig1182.png","url":"https://assets-eu.researchsquare.com/files/rs-5347898/v1/49898ea7ed16383f27fbc5c4.png"},{"id":69912864,"identity":"288cf83d-60ca-4c3b-9343-ae87618e2848","added_by":"auto","created_at":"2024-11-26 14:08:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":682015,"visible":true,"origin":"","legend":"\u003cp\u003eTUG1 promotes EZH2 occupancy of the METTL3 promoter and enhances H3K27me3 to transcriptionally repress METTL3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA.\u003c/strong\u003e TUG1 interacts with RNA-binding proteins predicated in the public database[G W1] . \u003cstrong\u003eB.\u003c/strong\u003e Western blot analysis of EZH2, H3K27me3, and METTL3 protein levels in shTUG1 stably transfected Huh7 and MHCC-LM3 cells and controls. \u003cstrong\u003eC, D. \u003c/strong\u003eWestern blot analysis of EZH2, H3K27me3, and METTL3 protein levels in Huh7 and MHCC-LM3 cell lines transfected as indicated. \u003cstrong\u003eE, F\u003c/strong\u003e. ChIP-PCR of EZH2 occupancy and H3K27me3 at the METTL3 promoter in shTUG1 and control Huh7 cells; IgG was used as a negative control. \u003cstrong\u003eG.\u003c/strong\u003e Silver staining results of biotin-labeled DNA pull-down assay using METTL3 promoter sequences in shTUG1 and control cells. \u003cstrong\u003eH.\u003c/strong\u003e Western blot of pull-down assays show EZH2 occupancy and H3K27me3 at the METTL3 promoter in shTUG1 and control cells (*P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, independent Student’s t-test)\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis phrasing was not entirely clear, as mentioned in the main text; please reword to help clarify your meaning.\u003c/p\u003e","description":"","filename":"Fig1183.png","url":"https://assets-eu.researchsquare.com/files/rs-5347898/v1/a34733ad54ce52cc813fcb6b.png"},{"id":69910676,"identity":"87139f2e-efb8-45c7-bc8b-0a75231efc14","added_by":"auto","created_at":"2024-11-26 13:52:06","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":970715,"visible":true,"origin":"","legend":"\u003cp\u003eMETTL3 is highly expressed in liver cancer cells and promotes proliferation and migration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA. \u003c/strong\u003eMETTL3 mRNA expression was examined in HCC cell lines and normal liver cells line. \u003cstrong\u003eB. \u003c/strong\u003eImmunofluorescence of METTL3 protein in liver cancer cells. \u003cstrong\u003eC.\u003c/strong\u003e Western blot analysis of METTL3 protein in nuclear and cytoplasmic fractions of liver cancer cells. \u003cstrong\u003eD, E.\u003c/strong\u003e mRNA and protein levels were verified by RT-PCR and western blot analysis in shMETTL3 and control Huh7 and MHCC-97h groups. \u003cstrong\u003eF. \u003c/strong\u003eCCK8 assays of shMETTL3 and control Huh7 and MHCC97H cells.\u003cstrong\u003e F\u003c/strong\u003e. Colony formation assays in shMETTL3 and control Huh7 and MHCC97H cells. \u003cstrong\u003eH\u003c/strong\u003e. EdU assay of shMETTL3 and control Huh7 and MHCC97H cells. \u003cstrong\u003eX. \u003c/strong\u003eWound-healing assay of shMETTL3 and control Huh7 and MHCC97H cells after 24 h[G W1] . \u003cstrong\u003eI, J, K.\u003c/strong\u003e The weights and volumes of tumors from mice injected with shMETTL3 and control Huh7 and MHCC-97H cells. (*P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, independent Student’s t-test).\u003c/p\u003e\n\u003cp\u003ePlease note, the figure is missing this panel.\u003c/p\u003e","description":"","filename":"Fig1184.png","url":"https://assets-eu.researchsquare.com/files/rs-5347898/v1/fb1ea498b35a6df30693ceea.png"},{"id":69912865,"identity":"b335a48b-6547-4f40-8504-426ad86a39c1","added_by":"auto","created_at":"2024-11-26 14:08:06","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1563258,"visible":true,"origin":"","legend":"\u003cp\u003eThe prognostic impact of METTL3 in HCC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA. \u003c/strong\u003eThe protein expression level of METTL3 in 10 cases of HCC tissues and adjacent normal liver was analyzed by western blot. \u003cstrong\u003eB. \u003c/strong\u003eThe mRNA expression level of METTL3 in 10 cases of HCC tissues and adjacent normal liver was analyzed by RT-PCR. \u003cstrong\u003eC.\u003c/strong\u003eRepresentative immunohistochemical images samples from the tissue microarray (TMA) probed with the anti-METTL3 antibody (scale bars=200 µm or 50 µm, respectively). \u003cstrong\u003eD. \u003c/strong\u003eThe distribution of METTL3 immunoreactivity H-scores in HCC and normal tissues using Aipathwell software. \u003cstrong\u003eE.\u003c/strong\u003e Multivariable analyses of METTL3 H-scores and clinical risks were performed in the HCC TMA cohort. Bars correspond to 95% CIs. \u003cstrong\u003eF. \u003c/strong\u003eKaplan–Meier survival analysis of METTL3 expression in patients with HCC in the TMA (P \u0026lt; 0.001, log-rank test).\u003c/p\u003e","description":"","filename":"Fig1185.png","url":"https://assets-eu.researchsquare.com/files/rs-5347898/v1/d4c38e52d549215c4cc6a66b.png"},{"id":69910681,"identity":"09665bc9-14b8-421e-87b0-c86eb3d2ad54","added_by":"auto","created_at":"2024-11-26 13:52:06","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":181299,"visible":true,"origin":"","legend":"\u003cp\u003eMETTL3 negatively regulates TUG1 through a m6A-YTHDC1-dependent pathway. \u003cstrong\u003eA. \u003c/strong\u003eIntegrative genomics viewer plots of TUG1 expression in whole transcriptome sequencing[G W1] . \u003cstrong\u003eB. \u003c/strong\u003eRT-PCR of TUG1 mRNA in cells with METTL3 knockdown. \u003cstrong\u003eC, D.\u003c/strong\u003eIntegrative genomics viewer plots of representative TUG1 m6A modification in MeRIP-sequencing. \u003cstrong\u003eE. \u003c/strong\u003em6AVar predicted potential m6A modification sites in the TUG1 sequence. \u003cstrong\u003eF. \u003c/strong\u003eMeRIP-qPCR was performed to detect m6A expression in[G W2] shMETTL3 and control Huh7 and HCC97H cells \u003cstrong\u003eG. \u003c/strong\u003eRIP-qPCR was performed to detect TUG1 mRNA expression in shMETTL3 and control Huh7 cells.\u003c/p\u003e\n\u003cp\u003eThis phrasing was not entirely clear here or in C; please reword to help clarify your meaning.\u003c/p\u003e\n\u003cp\u003ePlease clarify what is shown in this figure (the figure label was hard to read).\u003c/p\u003e","description":"","filename":"Fig1186.png","url":"https://assets-eu.researchsquare.com/files/rs-5347898/v1/abd44f9e16bed4e88be65ff3.png"},{"id":69911916,"identity":"762dad9a-635e-4167-8ae8-cb6392da9b1e","added_by":"auto","created_at":"2024-11-26 14:00:06","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":475014,"visible":true,"origin":"","legend":"\u003cp\u003eMETTL3 negatively regulates EZH2 and H3K27me3 in liver cancer cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA. \u003c/strong\u003eHeat map of differential expressed genes in shMETTL3 and control groups (3vs3) identified by whole transcriptome sequencing. \u003cstrong\u003eB. \u003c/strong\u003eGene Ontology (GO) analysis of differentially expressed genes. \u003cstrong\u003eC. \u003c/strong\u003eGO analysis of histone-related genes. \u003cstrong\u003eC. \u003c/strong\u003eWestern blot analysis of METTL3, EZH2 and H3K27me3 in ShMETTL3 and control Huh7 and MHCC-97H cells. \u003cstrong\u003eE, F.\u003c/strong\u003e Western blot analysis of METTL3, EZH2 and H3K27me3 in ShMETTL3 and control Huh7 and MHCC-97H cells treated with sEZH2 inhibitors DZnep(10umol/l) and GSK126(8umol/l) for 72h.\u003c/p\u003e","description":"","filename":"Fig1187.png","url":"https://assets-eu.researchsquare.com/files/rs-5347898/v1/aded590a1f479be02b52f950.png"},{"id":69910684,"identity":"5d4542f7-ed62-43e3-babf-9a8a494493fd","added_by":"auto","created_at":"2024-11-26 13:52:06","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":2582290,"visible":true,"origin":"","legend":"\u003cp\u003eMETTL3 co-localizes with EZH2, and [G W1] METTL3 and TUG1 regulate liver cancer cell self-renewal. \u003cstrong\u003eA. \u003c/strong\u003eDual-color immunofluorescence of METTL3 and EZH2 proteins in liver cancer cell lines (scale bars=20 µm or 5 µm). \u003cstrong\u003eB\u003c/strong\u003e. HE staining of METTL3 and EZH2 proteins in liver cancer tissues (scale bars=100 µm or 50 µm). \u003cstrong\u003eC, D. \u003c/strong\u003eCo-immunoprecipitation analysis of the interaction between METTL3 and EZH2 proteins. \u003cstrong\u003eE, F. \u003c/strong\u003eSphere-formation assays in ShMETTL3, ShTUG1, and control Huh7 cells (scale bars=200 µm or 20 µm) (***P \u0026lt; 0.001, independent Student’s t-test).\u003c/p\u003e\n\u003cp\u003eThis was revised to reflect the data in this figure; please check this is agreeable.\u003c/p\u003e","description":"","filename":"Fig1188.png","url":"https://assets-eu.researchsquare.com/files/rs-5347898/v1/19b11b3dc1ba05bd6dcdc412.png"},{"id":78098147,"identity":"bf403da0-a7b9-4221-88f1-2c1d0dc4f004","added_by":"auto","created_at":"2025-03-10 00:31:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9617236,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5347898/v1/72331e15-d280-4f86-ac58-58f8f3bc4365.pdf"},{"id":69911920,"identity":"288fb2f3-fb0b-4342-a085-89b53ecfef35","added_by":"auto","created_at":"2024-11-26 14:00:06","extension":"jpeg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":413197,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraphical abstract. A. \u003c/strong\u003eThe interaction between METTL3 and TUG1 dynamically regulates liver cancer cell self-renewal. \u003cstrong\u003eB. \u003c/strong\u003eTUG1 epigenetically represses METTL3 transcription in liver cancer cells by binding with and recruiting EZH2 to the METTL3 promoter region, increasing H3K27me3 levels. \u003cstrong\u003eC. \u003c/strong\u003eMETTL3 negatively regulates TUG1 in a m6A-YTHDC1-dependendent manner.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5347898/v1/b22025da78fe83d713eb7d18.jpeg"},{"id":69910682,"identity":"6dcbeda9-8cb4-4755-80a7-c217cdb558a8","added_by":"auto","created_at":"2024-11-26 13:52:06","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":8254979,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementFig1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5347898/v1/aea72292f1888f7d0dda3a15.pdf"},{"id":69912867,"identity":"80ca7f4e-d3e8-44f5-a9a6-c1f0bba1194a","added_by":"auto","created_at":"2024-11-26 14:08:06","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":769579,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFig2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5347898/v1/90d1f586726eb93fc0530aed.pdf"},{"id":69910678,"identity":"ef8a9330-cc98-4834-9c3c-f157e1f1bef4","added_by":"auto","created_at":"2024-11-26 13:52:06","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":17765,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymethods.docx","url":"https://assets-eu.researchsquare.com/files/rs-5347898/v1/70d96b82000194d0ff78c523.docx"},{"id":69913886,"identity":"c2b5229a-0500-41f6-8245-1e52d0e63b56","added_by":"auto","created_at":"2024-11-26 14:16:06","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":36362,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytables.docx","url":"https://assets-eu.researchsquare.com/files/rs-5347898/v1/48c84f3b0ae5627f863c33dd.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Interaction between TUG1 and METTL3 dynamically regulates liver cancer cell self-renewal","fulltext":[{"header":"Background","content":"\u003cp\u003eHepatocellular carcinoma (HCC) is one of the most common malignancies and the third common cause of cancer-related death. Liver resection is a curative treatment for patients diagnosed at a very early stage. However, most patients, especially those in developing countries, are diagnosed at advanced stage and thus not eligible for liver resection (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The complicated etiologies of HCC, including hepatitis virus infection, alcoholic liver disease, nonalcoholic fatty liver disease, and complex pathogenesis, lead to the extreme heterogeneity of HCC, which is an underlying cause of the difficulty to eliminate cancer cells through targeted drugs or precise treatment (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Therefore, better understanding of the mechanisms in HCC is critical to identify therapeutic targets and improve patient treatment.\u003c/p\u003e \u003cp\u003eLncRNAs in the cytoplasm regulate protein levels, either by maintaining mRNA stability or acting as competing endogenous RNAs. Studies have shown that lncRNAs play key roles in HCC carcinogenesis (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The TUG1 lncRNA, located on human chromosome 22q12.2, was first identified in a mouse model of retinal cells treated with taurine (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). TUG1 has been shown to function as an oncogenic or tumor suppressive lncRNA in different types of cancer and influences the expression of multiple genes (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). A previous study revealed a novel regulatory association among TUG1, miR-455-3p, AMPKβ2, and HK2 that regulates glycolytic metabolism and metastasis in HCC cells (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). We previously found that TUG1 competitively binds to miR-29a in the cytoplasm to regulate IFITM3 and promotes the invasion and metastasis of HCC (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The nuclear function of TUG1 and related mechanism have not been identified.\u003c/p\u003e \u003cp\u003eHepatocarcinogenesis is a multistep process that involves complex interactions among genetics, epigenetics, and transcriptomic alterations (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Studies have shown that aberrant epigenetic regulation is a critical mechanism that leads to profound gene expression changes that promote HCC formation and development (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). N6-methyladenosine (m6A) is the most prevalent mechanism of post-transcriptional RNA regulation and influences mRNA splicing, stabilization, and degradation. Studies have shown a role for m6A in the development of disease, including cancer (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Methyltransferase-like 3 (METTL3) is a key protein in the m6A methyltransferase complex. Previous studies have revealed the role of METTL3 in multiple biological functions of tumors (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). A recent report showed that METTL3 increases the m6A methylation level of SOCS2 mRNA, enhancing its recognition by the cytoplasmic reading protein YTHDF2 and promoting its degradation, which results in the malignant progression of HCC (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). METTL3-mediated m6A modification was also associated with the upregulation of LINC00958 in HCC, likely by regulating transcript stability (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). A previous study showed that METTL3 knockdown impairs the transcriptional silencing mediated by the lncRNA XIST (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Similar to XIST, TUG1 binds RNA-binding proteins in the nucleus, regulating transcriptional repression and tumorigenesis (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Whether TUG1 is regulated by METTL3 has not been investigated.\u003c/p\u003e \u003cp\u003eIn this study, we investigated the function of TUG1 in liver cancer, the potential interaction with METTL3, and the underlying molecular mechanism in liver cancer cells. Our results provide an insight into the interaction between TUG1 and METTL3 in the nucleus, with a potential role in liver cancer cell self-renewal.\u003c/p\u003e \n\n\n\n \n\n\n\n \n\n\n\n "},{"header":"Methods","content":"\u003ch3\u003e1. Cell cultures and construction stable transfection cell lines\u003c/h3\u003e\u003cp\u003eThe human HCC cell lines SMMC7721, HCCLM3, MHCC97H, and Huh-7,and the immortalized liver cell lines HL7702 were used in this study, and all were procured from the Shanghai Institute of Cell Biology (Shanghai, China). All cell lines were cultured in high-sugar DMEM (Solarbio,Beijing, China) supplemented with 10% FBS (Biological Industries, Beit-Haemek, Israel), 100 U/mL penicillin and 100 µg/mL streptomycin with 5% CO2 and at 37°C in a humidified incubator.Construction of TUG1 and METTL3 shRNA(short hairpin) lentiviral vector,negative control group lentivirus and transfection reagent were manufactured by Genechem Co., Ltd. (Shanghai, China),follow the instructions to establish its stable transfection cell lines,respectively. EZH over- expression plasmid ( HG11337-CY,pCMV-HA-hEZH2)was purchased from Sino Biological Inc. (Beijing, China).Cell transfection using Lipo3000™ reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions.The related targeting series primers are given in \u003cb\u003eSupplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e.\u003c/p\u003e\u003ch2\u003e2. Flow cytometry EdU incorporation assay\u003c/h2\u003e\u003cp\u003eHuh7 and HCCLM3 control group and shTUG1 cells ,Huh7 and MHCC-97H control group and shMETTL3 cells were planted in 35 mm glass-bottom dishes (Cellvis, D35-20-1-N) and subjected to the indicated treatments. kFluor647 Click-iT EdU Imaging Kit was utilized to measure cell proliferation based on the manufacturer’s instructions. Briefly, EdU (20 mmol/L) was added to the medium for 2.5 h. After fixation and permeabilization, Add 1mL of Click-iT reaction mixture to each tube, mix well, and incubate the reaction mixture at room temperature protected from light for 30 minutes.Cells were resuspeded in 500µl PBS and tested with flow cytometry(beckmancoulter,USA.).\u003c/p\u003e\u003ch3\u003e3. Nuclear-plasma separation assay\u003c/h3\u003e\u003cp\u003eCytoplasmic and nuclear RNA and protein extraction were performed using a commercial kit (Beyotime Institute of Biotechnology ,P0028) following the manufacturer’s instructions.liver tumor cells(Huh7) were harvested and suspended by equal volume solution A containing 1% PMSF, and cell lysates weremixed with 10 µl solution B by vortex and placed on ice for 1 min. cell sample fragments were homogenized with a mixture of solutions A and B by a glass homogenizer. Supernatant (cytoplasmic protein and RNA) was obtained after 12,000 rpm centrifugation for5 min; 50 µl solution C was used to suspend the sediment. Samples were mixed by vortex for 30s every 2 min for 15 times, and supernatant (nuclear protein and RNA) was collected after centrifugation.\u003c/p\u003e\u003ch3\u003e4. Dual immunofluorescence stain\u003c/h3\u003e\u003cp\u003e \u003c/p\u003e \u003cp\u003eDry the cell climbing slides slightly and add 50–100 µl of permeabilize working solution. Incubate for 20 min at room temperature. Wash three times with PBS solution, 5 min each.Block with serum: eliminate obvious liquid, cover objective area with 10% donkey serum (for the case of primary antibody originated from goat) at room temperature for 30 min. Incubate cells with anti-mouse EZH2 (AC11; 1:100 dilution; Invitrogen. ThermoFisher scientific, USA) and anti-rabbit METTL3 (ab195352; 1:50 dilution; Abcam, Cambridge, UK), was used for incubating the sections overnight at 4˚C, while for negative controls PBS was used in the place of the antibody, placed in a Rocker device and 5 min each. Incubation with goat anti-mouse IgG (Alexa Fluor 488; GB25301,Servicebio,Wuhan,China) and goat anti-rabbit IgG (Alexa Fluor 488;GB25303, Servicebio,Wuhan,China) secondary antibodies at 25°C for 50 min. Then incubate with DAPI solution at room temperature for 10 min.Microscopy detection and collect images by Fluorescent Microscopy(C1; Nikon, Tokyo, Japan).\u003c/p\u003e\u003c/p\u003e\u003ch3\u003e5. Biotin-streptavidin pull-down assay and mass spectrometry\u003c/h3\u003e\u003cp\u003eThe oligonucleotides containing biotin on the 5' nucleotide of the sense strand were used in the pull-down assays. 1 µg of each double-stranded oligonucleotide was incubated with 300 µg of nuclear protein for 20 min at room temperature, and 30 µl of poly (dI–dC) preabsorbed streptavidin–agarose beads were added at 4°C for 4 h. The protein–DNA–streptavidin–agarose complex was analyzed with SDS-PAGE.Mass spectrometry for more information see our previous study(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) .\u003c/p\u003e\u003ch3\u003e6. RNA immunoprecipitation(RIP) and m6A RNA immunoprecipitation (MeRIP) assay\u003c/h3\u003e\u003cp\u003eCells cultured in 10 cm plate was washed twice with ice cold PBS and scraped off in 1 mL PBS. Then the cell was centrifuged and re-suspended in an equal pellet volume of complete RIP lysis buffer (Merck Millipore). 5 µg antibody(anti-YTHDC1 (ab122340, Abcam) was pre-bound to Protein A/G magnetic beads in immunoprecipitation buffer for 2 h and then incubated with 100 µl cell lysates over night at 4°C with rotation. Then RNA was eluted from the beads by incubating with 400 µl elution buffer for 2 h. The eluted RNA was precipitated with ethanol and dissolved with RNase-free water. Enrichment of certain fragments was determined by real-time PCR.For MeRIP, TUG1 extracted from equal amount cell lysates was used as input to measure the m6A-methylated rate of TUG1. Antibodies used in this experiment were as follows: anti-m6A (ab190886, Abcam), Anti-IgG (Cell Signaling Technology,USA).IgG was used for negative control,Primers used for TUG1 and relative antibodies are included \u003cb\u003ein supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and\u003c/b\u003e Table\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRelationship between METTL3 and clinicopathologic factors of HCC patients.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTotal N\u0026thinsp;=\u0026thinsp;80\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eMETTL3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP\u0026nbsp;value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh\u0026nbsp;expression\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow\u0026nbsp;expression\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.483\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor\u0026nbsp;size(cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.072\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor\u0026nbsp;number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.043\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiple\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHBsAg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAFP(ng/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCirrhosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChild-pugh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.485\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExcision\u0026nbsp;range\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMinor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMajor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClinical\u0026nbsp;Stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI/II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIII/IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMVI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.029\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariable analysis of factors associated with overall survival(OS) and disease-free survival(DFS) for HCC patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnivariate (P value)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall survival\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDisease-free survival\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge( years)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.373\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.370\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 55\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e≥ 55\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAFP(ng/ml)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 400\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e≥ 400\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBsAg\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.438\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor\u0026nbsp;number\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor\u0026nbsp;size(cm)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.973\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e≥ 5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCirrhosis\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChild-pugh\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.436\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExcision\u0026nbsp;range\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.809\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMinor\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH-score\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical\u0026nbsp;Stage\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI/II\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII/IV\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMVI\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003ch2\u003e7. Stem sphere-forming assay\u003c/h2\u003e\u003cp\u003eResuspend cells in stem cell medium(DMEM/F12 + 1xB27 + 20ng/ml bFGF + 20ng/ml EGF) and count Single-cell suspensions were plated in ultralow attachment six-well plates (Corning) at a density of 5×10\u003csup\u003e3\u003c/sup\u003e cells/ml and grown in modified DMEM, as described in the “Cell Culture” section, without serum supplementation. Medium was replaced every 3 days. Spheres were counted after 14 days (passage one, P1). For the secondary sphere formation assay, the spheres were scattered and re-seeded in 96-well plates at a density of about 100 cells per well. We counted the number of secondary spheres formed at 10 days post-incubation.\u003c/p\u003e\u003ch3\u003e8. Chromatin immunoprecipitation (ChIP) assay\u003c/h3\u003e\u003cp\u003eH3K27me3,EZH2 ChIP-qPCR were performed according to the manufacturer’s instructions for the Simple ChIP Plus Enzymatic Chromatin IP Kit (9005, Cell Signaling Technology, Danvers, MA).In summary,Huh7 and MHCC-LM3 Cells were cross-linked with 1% formaldehyde.Antibodies (rabbit IgG ,H3K27me3 and EZH2) were bound to protein A-coated magnetic beads and incubated for 2 hours at 4°C. The fragmented chromatin was added to antibody-coated beads and incubated on a rotating wheel overnight at 4°C, the sheared chromatin was eluted using DNA elution buffer.Results were normalized using the internal control IgG. Precipitated chromatin DNA was recovered and analyzed by qPCR.Primers used for METTL3 promoter and antibodies are included \u003cb\u003ein supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and\u003c/b\u003e Table\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003ch3\u003e9. Whole transcriptome sequencing, RNA sequencing and analyses\u003c/h3\u003e\u003cp\u003eTotal RNA was isolated and purified using Trizol reagent (Invitrogen, Carlsbad, CA, USA) following the manufacturer's procedure. Approximately 2 ug of total RNA was used to deplete ribosomal RNA according to the manuscript of the Ribo-Zero™ rRNA Removal Kit (Illumina, San Diego, USA). The cleaved RNA fragments were reverse-transcribed to create the cDNA,which were next used to synthesise U-labeled second-stranded DNAs with E. coli DNA polymerase I (NEB, cat.m0209, USA), RNase H (NEB, cat.m0297, USA) and dUTP Solution (Thermo Fisher, cat.R0133, USA). Each adapter contains a T-base overhang for ligating the adapter to the A-tailed fragmented DNA. Single-or dual-index adapters are ligated to the fragments, and size selection was performed with AMPureXP beads.The ligated products are amplified with PCR, the average insert size for the final cDNA library was 300 bp (± 50 bp). At last, we performed the paired-end sequencing on an Illumina Hiseq 6000 (LC-Bio Technology CO., Ltd., Hangzhou, China) following the vendor's recommended protocol.For bioinformatics analysis of RNA-seq, fast p was used to remove the reads that contained adaptor contamination, low quality bases and undetermined bases(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Then sequence quality was also verified using fast p, we used Bowtie2 and Tophat2 to map reads to the genome of \u003cem\u003eHomo sapiens\u003c/em\u003e GRCh37/hg19(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The mapped reads of each sample were assembled using StringTie(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Then, all transcriptome from all samples were merged to reconstruct a comprehensive transcriptome using gffcompare (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/gpertea/gffcompare/\u003c/span\u003e\u003cspan address=\"https://github.com/gpertea/gffcompare/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). All transcripts with CPC score \u0026lt;-1 and CNCI score \u0026lt; 0 were removed(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The differentially expressed mRNAs and lncRNAs were selected with log2 (fold change) \u0026gt; 1 or log2 (fold change) \u0026lt;-1 and with parametric F-test comparing nested linear models (p value \u0026lt; 0.05) by R package edge.\u003c/p\u003e\u003ch2\u003e10. Animal experiments\u003c/h2\u003e\u003cp\u003eThe establishment and analysis of subcutaneous xenograft models in nude mice (male BALB/c nu/nu nude mice, 4 -6weeks old) were performed. .As we described previously,1× 10\u003csup\u003e7\u003c/sup\u003e cells in 100 µL of PBS were injected subcutaneously into female BALB/nude mice ( n = 4 per group) (Hunan SJA Laboratory Animal Co., Ltd., Hunan, China)[21]. After 6 weeks, the mice were euthanized under anesthesia, the tumor mass was excised, both the weight and volume of the tumor mass was measured.\u003c/p\u003e\u003ch2\u003e11. Statistical analysis\u003c/h2\u003e\u003cp\u003eR software (version 3.5.1) was used for statistical analysis and data visualization. Protein and RNA levels were compared using two-tailed Student’s t test. Correlations between METTL3 expression in HCC tissues and clinicopathological features were analyzed with Pearson Chisquare (χ2) test. Overall survival (OS) and disease- free survival (DFS) was assessed by Kaplan-Meier method, difference between survival curves was determined by log-rank test. Differences with a p value \u0026lt; 0.05 were considered as statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e1. TUG1 is highly expressed in liver cancer cells and HCC tissues and promotes liver cancer cell proliferation and migration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe subcellular localization of TUG1 in various cancer cell lines was predicted using the lncATLAS database. The results indicated that TUG1 is mainly localized in the nucleus. Approximately 60% is present in the nucleus in HepG2 cells, with 39.1% in the cytoplasm \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA\u003cstrong\u003e)\u003c/strong\u003e. We verified that TUG1 mRNA is mainly expressed in the nucleus of Huh7 by RT-PCR \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB\u003cstrong\u003e)\u003c/strong\u003e. RNA-FISH further confirmed nuclear localization of TUG1 mRNA in Huh7 cells \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC\u003cstrong\u003e)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eWe found that TUG1 was expressed at high levels in liver cancer cell lines (Huh7, MHCC-97h, HCC-LM3, SMMC-7721) compared with a normal liver cell line (HLC7702), with the highest expression level detected in Huh7 cells \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eD\u003cstrong\u003e)\u003c/strong\u003e. RNA-FISH analysis of 10 HCC tissues and normal liver tissues showed that TUG1 mRNA was upregulated\u0026thinsp;\u0026gt;\u0026thinsp;2.0-fold in HCC tissues compared with adjacent normal tissues \u003cstrong\u003e(\u003c/strong\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001) \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eE, F\u003cstrong\u003e).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo examine the role of TUG1 in the proliferation and migration of liver cancer cells, we first stably transfected shTUG1 lentiviral vector and control vectors into Huh7 and HCC-LM3 cells and confirmed the downregulation of TUG1 mRNA by RT-PCR (\u003cstrong\u003esupplementary Fig.\u0026nbsp;1A\u003c/strong\u003e). CCK8 assays showed that downregulation of TUG1 significantly reduced the cell proliferation ability of Huh7 and HCC-LM3 cells compared with controls (\u003cstrong\u003esupplementary Fig.\u0026nbsp;1B\u003c/strong\u003e). Wound-healing assays showed that the migration activity of Huh7 and HCC-LM3 cells was significantly reduced after TUG1 knockdown for 24 h compared with the controls (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (\u003cstrong\u003esupplementary Fig.\u0026nbsp;1C\u003c/strong\u003e). EdU assay showed that the proliferation ratio of Huh7 and HCC-LM3 cells was significantly lower after TUG1 stable knockdown compared with the control (\u003cstrong\u003esupplementary Fig.\u0026nbsp;1D\u003c/strong\u003e). Colony formation assay showed that the number of single clones formed in Huh7 and HCC-LM3 cells was significantly reduced after TUG1 knockdown (\u003cstrong\u003esupplementary Fig.\u0026nbsp;1E\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. TUG1 negatively regulates METTL3 expression by promoting H3K27me3 modification of the METTL3 promoter through the PRC2 core enzyme EZH2.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur results indicated that TUG1 has an important role in the proliferation of liver cells. To explore the underlying molecular mechanisms, we performed transcriptome sequencing in control and shTUG1,3vs3. The transcriptome sequencing results revealed that 14209 genes were upregulated and 14293 genes were downregulated in cells with TUG knockdown; among the differentially expressed genes, there were 981 upregulated and 856 downregulated genes (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA\u003cstrong\u003e)\u003c/strong\u003e. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated TUG1 is more important in tumor pathway than that in other disease \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cstrong\u003e)\u003c/strong\u003e. Gene Ontology (GO) enrichment analysis of the differentially expressed genes showed that the top enriched pathways included DNA-binding transcription factor activity \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe next examined the transcriptome sequencing results for genes encoding m6A-related proteins (METTL3, METTL14, WTAP, METTL16, RBM15B, RBM15, FTO, ALKBH5, YTHDF1\u0026ndash;3, YTHDC1\u0026ndash;2, IGFBP1-3). The results revealed that the mRNA expression of METTL3 was significantly increased in cells with TUG1 downregulation compared with controls (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD\u003cstrong\u003e).\u003c/strong\u003e Knockdown of TUG1 in Huh7 and MHCC-97h cells led to upregulated METTL3 mRNA and protein expression levels \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eE, F\u003cstrong\u003e).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalysis of a public database ((\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://rnainter.org/\u003c/span\u003e\u003c/span\u003e) indicated that TUG1 can be combined with EZH2 \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cstrong\u003e)\u003c/strong\u003e. Previous studies reported that TUG1 interacts with the polycomb repressive complex 2 (PRC2) core enzyme EZH2, which leads to increased H3K27me3 modification of promoters and subsequent inhibited gene transcription (\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e). Western blotting demonstrated that EZH2 and H3K27me3 levels were reduced in Huh7 and MHCC-LM3 cell lines with TUG1 knockdown \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB\u003cstrong\u003e).\u003c/strong\u003e We next performed rescue experiments. EZH2 overexpression plasmid was transiently transfected into TUG1 knockdown and control Huh7 and MHCC-LM3 cells. The EZH2 transfected group showed increased levels of EZH2 and H3K27me3 and downregulated METTL3 protein. In the shTUG1 group, METTL3 level increased, as described above, while EZH2 and H3K27me3 levels decreased; overexpression of EZH2 in shTUG1 cells led to decreased METTL3 protein level and increased EZH2 and H3K27me3 levels \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC, D\u003cstrong\u003e)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eUCSC database predicted the presence of an H3K27me3 site in the METTL3 promoter \u003cstrong\u003e(supplement Fig .2A)\u003c/strong\u003e. ChIP-qPCR assays revealed that knockdown of TUG1 decreased the binding of EZH2 to the METTL3 promoter and resulted in reduced H3K27me3 levels in the METTL3 promoter compared with controls \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eE, F\u003cstrong\u003e)\u003c/strong\u003e. We then performed pull-down assays using a biotin-labeled DNA probe specific to the METTL3 promoter region.Mass spectrometry analysis of the results of TUG1 knockdown group and the control group, regardless of whether TUG1 was down regulated, revealed were 2131 proteins overlap between TUG1 knockdown group and the control group( \u003cstrong\u003esupplement Fig .2B)\u003c/strong\u003e.the results revealed the decrease of EZH2 protein band in the shTUG1 group \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eG\u003cstrong\u003e)\u003c/strong\u003e.Western blot from the pull down assays revealed decreased levels of EZH2 and H3K27me3 at the METTL3 promoter in the shTUG1 group compared with the control group \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eH\u003cstrong\u003e).\u003c/strong\u003eTaken together, these data suggest that promotes EZH2 occupancy at the METTL3 promoter and increases H3K27me3 at the promoter.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. METTL3 is highly expressed in liver cancer cells and promotes proliferation in vitro and in vivo\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe next investigated whether METTL3 plays a role in the proliferation and metastasis of HCC cells. We detected higher METTL3 mRNA expression in Huh7 and MHCC-97h cell lines by RT-qPCR \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA\u003cstrong\u003e)\u003c/strong\u003e. Immunofluorescence and western blot revealed that METTL3 was expressed at higher levels in the nucleus \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB, C\u003cstrong\u003e)\u003c/strong\u003e. We used Huh7 and MHCC-97h cell lines to generate stable METTL3 knockdown cell lines, and the knockdown efficiency was over 60% \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eD, E).\u003c/p\u003e\n\u003cp\u003eCCK8 assays revealed that down-regulation of METTL3 significantly reduced the cell proliferation ability of Huh7 and MHCC97H liver cancer cells compared with controls (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eF). The number of single clones formed in Huh7 and MHCC97H cells after METTL3 knockdown was significantly reduced compared with controls (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eG). EdU assay showed that the proliferation ratio of Huh7 and MHCC97H cells was significantly lower after METTL3 knockdown compared with controls (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eH). Wound healing assays revealed significantly reduced migration activity of Huh7 and MHCC97H cells after METTL3 knockdown for 24 h (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cp\u003eWe next examined the role of METTL3 in liver cancer cell proliferation in vivo. ShMETTL3 and control Huh7 and MHCC97H cells were injected into nude mice. After 6 weeks, the average tumor weights were significantly smaller in the ShMETTL3 Huh7 and MHCC97H groups compared with controls (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eI, J). Moreover, the average tumor volume was significantly reduced in the ShMETTL3 Huh7 group compared with controls (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eK). Taken together, these data indicated that METTL3 promoted HCC cell proliferation in vitro and in vivo.\u003c/p\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e4. The influence of METTL3 on prognosis and clinical outcome in HCC patients\u003c/h2\u003e\n \u003cp\u003eWe next examined the expression of METTL3 in liver cancer tissues using RT-PCR, western blot, and tissue microarray (TMA). The protein and mRNA levels of METTL3 in 10 HCC tissues were higher than those in adjacent tissues (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA, B). Immunohistochemical examination of TMA containing samples from 80 HCC patients revealed higher expression of METTL3 in HCC tissues compared with normal tissue, and METTL3 expression was significantly correlated with clinical stage (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eC, D). Upregulated expression of METTL3 was significantly associated with tumor size (P\u0026thinsp;=\u0026thinsp;0.032), tumor number (P\u0026thinsp;=\u0026thinsp;0.032), clinical stage (P\u0026thinsp;=\u0026thinsp;0.006) and microvascular invasion(MVI) (P\u0026thinsp;=\u0026thinsp;0.029) \u003cstrong\u003e(\u003c/strong\u003eTable \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e Survival analysis using the Kaplan\u0026ndash;Meier method indicated that HCC patients with high METTL3 expression exhibited a worse overall survival (OS) rate and disease-free survival (DFS) rate (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eF). Univariate and multivariate analyses showed that high METTL3 expression was an unfavorable independent prognostic for OS ( HR 1.740; 95%CI: 1.401\u0026ndash;2.312; P\u0026thinsp;\u0026lt;\u0026thinsp;0.020) and DFS (HR 1.831; 95%CI: 1.520\u0026ndash;2.232; P\u0026thinsp;\u0026lt;\u0026thinsp;0.020) \u003cstrong\u003e(\u003c/strong\u003eTable \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eE). Collectively, these results indicated that METTL3 was significantly upregulated in HCC and may be associated with HCC progression.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e5. METTL3 negatively regulates TUG1 through a m6A-YTHDC1-dependent pathway\u003c/h2\u003e\n \u003cp\u003eM6A modification of lncRNA may affect lncRNA transcription. We examined whether the effects of METTL3 on downregulating TUG1 depends on its m6A-related activity. Compared with control group (3vs3), METTL3 was ectopically knockdown expressed in Huh7 whole transcriptome sequencing, the potential negatived alterations of TUG1 up-expression level were then assessed in integrative genomics viewer (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eA).RT-PCR further revealed that knockdown of the m6A enzyme METTL3 in Huh7 and MHCC-97H cells resulted in increased TUG1 lncRNA levels (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eB).We downloaded MeRIP sequencing data from the GEO database (GSE102620 and GSE110320) of HepG2 cells with transient transfection of siMETTL3 and siMETTL14 and stable transfection of shMETTL3 and shMETTL14. We observed a potential m6A decreased-modification in the TUG1 (NM_001398476) sequence at Chr22:30978500\u0026ndash;30978780 (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eC, D). Analysis using an online m6A site predictor (SRAMP) revealed a GAACU motif in Chr22:30978500\u0026ndash;30978780 (230 bp) 3\u0026rsquo;UTR location \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eE\u003cstrong\u003e)\u003c/strong\u003e. The secondary structure of the TUG1 m6A modification site is shown \u003cstrong\u003e( supplementary Fig.\u0026nbsp;2C)\u003c/strong\u003e. MeRIP-qPCR revealed that m6A modification of TUG1 in Huh7 and MHCC-97H cells was significantly decreased after knockdown of METTL3 compared with controls (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eF). These results suggest that METTL3 may be involved in the negative regulation of TUG1 transcription through modulating m6A modification of TUG1.\u003c/p\u003e\n \u003cp\u003eYTHDC1 and YTHDC2 are m6A reader proteins in the nucleus. YTHDC2 is mainly involved in splicing regulation through RNA m6A modification, and YTHDC1 was shown to promote lncRNA degradation through m6A modification. We scanned ENCORI databases and found that YTHDC1 contained multiple putative binding sites for TUG1,\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eone of which\u003c/span\u003e was further confirmed by RIP-qPCR, TUG1 mRNA in METTL3-knockdown expressed cell was decreased compared with control group\u003cstrong\u003e(Supplementary Fig .2D)\u003c/strong\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eG). Together, these results indicate that METTL3 negatively regulates TUG1 expression in a m6A- and YTHDC1-dependent manner.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e6. METTL3 co-localizes with EZH2, and METTL3 and TUG1 regulate liver cancer cell self-renewal\u003c/h2\u003e\n \u003cp\u003eWe performed whole transcriptome sequencing of Huh7 cells with stable METTL3 knockdown (3vs3); differentially expressed genes are shown in a heat map (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eA). GO analysis of differentially expressed genes revealed significant upregulation of RNA binding proteins (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eB). Among the differential genes, further GO analysis was continued through histone regulation-related genes. We found that H3K27me3 was significantly upregulated in cells with METTL3 downregulation (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eC). Western blot of Huh7 and MHCC-97H cells downregulated for METTL3 showed significant upregulation of EZH2 and H3K27me3 levels compared with controls (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eD). We treated METTL3 knockdown cells with EZH2 inhibitors DZnep and GSK126 and found that the up-regulated EZH2 and H3K27me3 levels were decreased, and downregulated METTL3 protein was significantly increased (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eE, F). These results suggest METTL3 negatively regulates EZH2 and H3K27me3 levels. Dual-color immunofluorescence revealed the co-localization of METTL3 and EZH2 in the nucleus in liver cancer cell lines and liver cancer tissues (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003eA, B). However, co-immunoprecipitation analysis indicated no interaction between METTL3 and EZH2 proteins (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003eC, D). We examined the influence of METTL3 and TUG1 on cell self-renewal activity through sphere formation experiments. The numbers and diameter of spheres were significantly lower in cells with METTL3 or TUG1 knockdown compared with controls (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003eE, F).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCurrent studies have demonstrated that m6A influences lncRNA stability and translation efficiency in the regulation of liver cancer progression (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). However, the interactions and mechanisms between m6A and m6A-regulated lncRNA remain largely unknown. Our study suggests that METTL3 and TUG1 interact and regulate the self-renewal of liver cancer cells. Our results showed that TUG1 inhibits the transcription of METTL3 by binding to the PRC2 core enzyme EZH2 and recruiting H3K27me3 to the METTL3 promoter region in liver cancer cells. We further found that METTL3 also participates in m6A regulation of TUG1 and negatively regulates its transcription in a YTHDC1-dependendent manner. Furthermore, we demonstrated that TUG1 may be a \u0026ldquo;bridge\u0026rdquo; between METTL3 modificated-m6A and its RNA binding protein EZH2 interaction, regulating the self-renewal of liver cancer cells. Our results describe the potential roles of m6A-lncRNA-histone modification in the self-renewal of liver cancer cells. These results indicate the possibility to develop therapeutic strategies against liver cancer progression by targeting this regulatory mechanism.\u003c/p\u003e \u003cp\u003eInterventions targeting TUG1 or its downstream pathways may hold therapeutic promise for liver diseases, especially in HCC (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). A recent investigation revealed that TUG1 in the nucleus regulates H3K27me3 modification of target genes by recruiting EZH2, which is one of the subunits of PRC2 that suppress gene expression (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The current study showed that TUG1 not only promotes liver cancer cell proliferation and migration, but also promotes liver cancer cell self-renewal, consistent with recent findings of TUG1 in glioma (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). We established METTL3 as the downstream regulatory gene of TUG1 in regulating liver cancer cell self-renewal.\u003c/p\u003e \u003cp\u003eResearch has revealed the vital roles of RNA modification in tumorigenesis. The m6A methyltransferase METTL3 enhances HCC invasion and metastasis in vitro and in vivo by regulation of key EMT factors SNAIL and CTNNB1 (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). METTL3 is markedly downregulated in samples from patients with sorafenib-resistant HCC, and depletion of METTL3 in human liver cancer cells enhanced sorafenib resistance by regulating the stability of FOXO3 transcript in a YTHDF1-dependent manner (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). METTL3 is upregulated in lenvatinib-resistant HCC and promotes lenvatinib resistance through the regulation of EGFR mRNA translation in human liver cancer cells (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). These different roles of METTL3 in the regulation of sorafenib and lenvatinib sensitivity may be because of different downstream targets and its localization-specific function in human cancer cells (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). METTL3-knockout mice are embryonic lethal, which is consistent with the observation that Mettl3 inactivation in mouse embryonic stem cells resulted in a loss of self-renewal capabilities (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). We demonstrated that METTL3 is expressed at high levels in the nucleus of liver cancer cells and HCC tissues; METTL3 promotes liver cancer proliferation and metastasis and regulates the self-renewal of liver cancer cells. We also found that METTL3 was independently associated with advanced disease and poor overall survival in patients with HCC. Moreover, we confirmed that METTL3 may negatively regulate TUG1 transcription in a m6A-YTHDC1-dependent manner. Consistent with literature indicated that the knockdown of METTL3 was lead to up-regulated XIST transcriptional level, mainly because the recognition of m6A on XIST by \"Reader\" YTHDC1 leads to the decreased decay of XIST (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The m6A regulation of XIST was reported in studies on the roles of m6A in stemness-associated genes (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Our findings show that after downregulating METTL3, the m6A modification of TUG1 decreased and TUG1 expression was upregulated, which may be because of reduced recognition by the YTHDC1 reader and subsequent degradation.\u003c/p\u003e \u003cp\u003eWe confirmed that TUG1 and its binding protein EZH2 interact with METTL3 to dynamically regulate the self-renewal of liver cancer cells. Accumulating studies have focused on the interaction between histone enzymes and m6A modifications (\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Histone modifications that promote transcription include H3K36me3, H3K4me3, and H3K27ac, all of which are co-localized with the m6A modification site (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Histone modification sites that inhibit transcription include H3K9me2, H3K9me3, H3K27me3, all of which are opposed to the m6A modification site (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Wang et al. \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ed\u003c/span\u003eemonstrated that in mouse neuronal stem cells with METTL3 knockout, H3K27me3 levels increased by 71%; their results showed that m6A participates in the regulation of self-renewal and gene rearrangement of neural stem cells through specific histone modifications (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e).We found that METTL3 is in the negatively interacting with EZH2, H3K27me3,but not directly bind to EZH2 protein. This led us to speculate whether METTL3 and EZH2 proteins may interact through TUG1.\u003c/p\u003e \u003cp\u003em6A influences RNA stability and translation efficiency in the nucleus and also affects RNA-binding protein interactions, modulating their localization to chromatin and regulating post-translational modifications (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). m6A modification acts as a \u0026ldquo;molecular switch\u0026rdquo; that can affect RNA-protein interactions by adjusting the structure of lncRNA (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Long et al. reported that PRC2 does not directly bind to the DNA promoter region of target genes, but requires a bridge lncRNA to participate in regulating its positioning throughout the genome, thereby achieving timely and accurate control of growth and development and pluripotent stem cell differentiation (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). Consistent with literature reported that numerous lncRNAs are retained in the nucleus through different mechanisms and can provide feedback on transcription and modulate the chromatin state(\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). We speculated whether the m6A methyltransferase complex and histone modification enzymes indirectly interact through the \u0026ldquo;bridge\u0026rdquo; of lncRNA to form a large complex that regulates the self-renewal of tumor cells. In future studies, we plan to explore the specific molecular mechanism in depth.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe regulation between TUG1 and METTL3 provides a new perspective to study liver cell tumorigenesis. Our findings suggest that a m6A-lncRNA-histone model may be dynamically involved in regulating the self-renewal of liver cancer cells. This discovery enriches our understanding of the m6A-lncRNA-histone dynamic network in the progression of liver cancer and provides therapeutic targets.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTUG1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTaurine upregulated gene 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMETTL3\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emethyltransferase-like 3\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEZH2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEnhancer of zeste homolog 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePRC2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epolycomb repressive complex 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eH3K27me3\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etri-methylation at lysine 27 of histone H3\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003em6A\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eN6-methyladenosine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehepatocellular carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eqRT-PCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003equantitative real-time polymerase chain reaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ewestern blotting\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFISH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efluorescence in situ hybridization.EdU:5-Ethynyl-2ʹdeoxyuridine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCK-8\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecell counting Kit-8\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTMA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etissue microarray\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCO-IP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eco-immunoprecipitation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRIP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRNA immunoprecipitation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMeRIP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emethylated RNA immunoprecipitation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eChIP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003echromatin immunoprecipitation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKEGG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ekyoto encyclopedia of genes and genomes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003egene ontology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehazard radio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMVI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emicrovascular invasion:OS:overall survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRFS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003erecurrence free survival.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e All animal experiments were approved by the Animal Experiment Ethics Committee of the Laboratory Animal Science Center of Nanchang University and were carried out in accordance with the guidelines of the British Animal (Scientifc Procedure) Act of 1986 and the European Union Directive 2010/63/EU.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eThe content of this manuscript has not been previously published and is not under consideration for publication elsewhere.\u003c/p\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the National Natural Science Foundation of\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003ePH and JL designed the study. PH, JL , RSW and JYD performed most of the experiment. LQW, ELL, WWL ,JKW and RGYL performed the operation and followed-up the patients. PH ,JL,LQW, and ELL analyzed data and drafted the manuscript. LQW and ELL provided the overall guidance. All authors read and approved the final Manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe thank Gabrielle White Wolf, PhD, from Liwen Bianji (Edanz) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.liwenbianji.cn\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.liwenbianji.cn\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for editing the English text of a draft of this manuscript.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eAll data generated during this study are included either in article or in the additional files. RNA-seq data will be uploaded to GEO database in the future.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYang JD, Hainaut P, Gores GJ, et al. A global view of hepatocellular carcinoma: trends, risk, prevention and management. Nat Rev Gastroenterol Hepatol. 2019;2019\u0026ndash;10\u0026ndash;01(10):589\u0026ndash;604.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLlovet JM, Kelley RK, Villanueva A, et al. Hepatocellular carcinoma. Nat reviews Disease primers. 2021;2021\u0026ndash;01\u0026ndash;01(1):6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlingenberg M, Matsuda A, Diederichs S, Patel T. Non-coding RNA in hepatocellular carcinoma: Mechanisms, biomarkers and therapeutic targets. J HEPATOL. 2017;67(3):603\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoung TL, Matsuda T, Cepko CL. 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Towards higher-resolution and in vivo understanding of lncRNA biogenesis and function. \u003cem\u003eNAT METHODS\u003c/em\u003e 2022 2022-10-01; 19(10): 1152\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"TUG1, METTL3, EZH2, Interaction, Self-renewal","lastPublishedDoi":"10.21203/rs.3.rs-5347898/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5347898/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe long non-coding TUG1 regulates the mRNA stability of target genes by acting as a competing endogenous RNA in the cytoplasm. However, its function in the nucleus and the underlying mechanism are unknown. We examined the potential interaction between TUG1 and METTL3 and the underlying molecular mechanism in liver cancer cells.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe expressions of TUG1 and METTL3 in hepatocellular carcinoma (HCC) tissues and liver cancer cell lines were examined by quantitative RT-PCR, western blotting, and fluorescence in situ hybridization. Loss of function experiments were used to examine the role of TUG1 and METTL3 in HCC. A liver cancer tissue microarray was used to identify the influence of METTL3 on prognosis and clinical outcomes. In vitro analyses, whole transcriptome sequencing, RNA sequencing, and database analyses were performed to investigate the molecular mechanism of TUG1 and METTL3 in liver cancer.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eTUG1 and METTL3 were localized in the nucleus of liver cancer cells. Knockdown of TUG1 and METTL3 decreased the proliferative and migration ability of liver cancer cells in vitro, and METTL3 knockdown promoted tumorigenicity in vivo. High METTL3 expression correlated with unfavorable prognosis of HCC patients. Mechanistic studies revealed that TUG1 regulates METTL3 transcriptional expression by binding and recruiting EZH2 to the METTL3 promoter and increasing H3K27me3 levels. TUG1 is regulated by METTL3 in a m6A-YTHDC1-dependent manner. Knockdown of METTL3 substantially abolished the m6A level of TUG1 and augmented TUG1 expression. METTL3 and EZH2 proteins may indirectly interact through the \u0026ldquo;bridge\u0026rdquo; of TUG1. The interaction between TUG1 and METTL3 may play a role in liver cancer self-renewal.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003eTUG1 may epigenetically repress METTL3 transcription in liver cancer cells by binding and recruiting EZH2 to the METTL3 promoter region, resulting in increased H3K27me3 levels. METTL3 regulates TUG1 transcription in an m6A-dependent manner. The interaction between METTL3 and TUG1 dynamically regulates liver cancer cell self-renewal activity.\u003c/p\u003e","manuscriptTitle":"Interaction between TUG1 and METTL3 dynamically regulates liver cancer cell self-renewal","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-26 13:52:01","doi":"10.21203/rs.3.rs-5347898/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eaf63f8b-813e-46ee-a8bb-b6d451fdf266","owner":[],"postedDate":"November 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-10T00:23:29+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-26 13:52:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5347898","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5347898","identity":"rs-5347898","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}