| Liver cancer is one of the most common digestive system malignancies,of which80-90% are hepatocellular carcinoma(HCC).Liver cancer is the third leading cause of cancer-related death in the world.Most liver patients are diagnosed at advanced stages due to atypical symptoms and the lack of effective diagnostic indicators.Patients with liver cancer at advanced stages miss the best period of surgical resection and lack effective treatment option,with poor prognosis and high mortality rate.LncRNAs are longer than 200 nucleotides and have limited protein-coding potential,which play vital roles in the pathogenesis of various diseases,including cancer.LncRNAs have potential to be molecular targets for diagnosis,prognosis and therapy of cancer due to their detectability in tissues and body fluids.This study is dedicated to exploring the lncRNAs that play vital regulatory roles in the onset and progression of liver cancer and elucidating the underlying molecular mechanisms,which would contribute to understand the pathogenesis of liver cancer and develop effective biomarkers of early diagnosis,precise prognosis and treatment for patients with liver cancer.In addition,with the development of microarray and sequencing technologies,increasing researches are devoted to developing prognostic risk score models based on various tumor-associated gene sets,aiming to provide a reference for the prognosis and personalized management of liver cancer patients.Considering the critical role of splicing factors in the occurrence and development of liver cancer,this study constructed a prognostic risk score model for liver cancer patients based on splicing factors.Part Ⅰ Clinical significance of SNHGs in liver cancerDifferential expression analysis for the gene expression profile of liver cancer in The Cancer Genome Atlas(TCGA)identified 8827 differentially expressed genes(DEGs),including 2853 differentially expressed lncRNAs.Sno RNA host genes(SNHGs)are a class of lncRNAs strongly implicated in the onset and progression of cancer.Among differentially expressed lncRNAs,the expression of multiple SNHGs were significantly elevated in liver tissues and positively correlated with poor prognosis of patients.SNHG1 was selected as the target lncRNA for further study.Both public database analysis and q RT-PCR experimental detection showed that SNHG1 expression was significantly increased in liver cancer tissues and hepatoma cells.Meanwhile,SNHG1 expression was closely correlated with age at diagnosis and tumor histologic grade.Through Kaplan-Meier survival curve,time-dependent receiver operating characteristic(ROC)curve,univariate and multivariate Cox regression analyses,SNHG1 was identified as an independent risk factor for liver cancer patients,which indicating that the high expression of SNHG1 predicts poor prognosis of liver cancer patients.Part Ⅱ The mechanism of SNHG1 expression regulation in liver cancerThe expression of lncRNAs in liver cancer is precisely regulated by various mechanisms.This study focused on exploring the transcription factors involved in the regulation of SNHG1 expression in hepatoma cells.Combined with differential analysis,Pearson correlation analysis and SNHG1 promoter binding site prediction,a total of 9 genes(ESR1,MYBL2,E2F1,FOXM1,LMNB1,ARID3 A,ATF3,AR,and FOS)were identified.Univariate Cox regression analysis and Kaplan-Meier survival analysis showed that among these 9 transcription factors,high expression of ESR1 was positively correlated with good prognosis,whereas high expressions of MYBL2,E2F1,FOXM1,LMNB1,and ARID3 A were positively correlated with poor prognosis of liver cancer patients.Furthermore,using JASPAR database,E2F1 was predicted to have the highest binding scores at-555 bp to-548 bp,434 bp to-427 bp and-179 bp to-172 bp to the SNHG1 transcription start site.The promoting effect of E2F1 on SNHG1 expression in hepatoma cells was validated by transfection technology and q RT-PCR.Combined with the results of Ch IP and dual-luciferase reporter experiments,it is concluded that E2F1 activates the transcription of SNHG1 by binding to the SNHG1 promoter region in hepatoma cells.Part Ⅲ Exploration of the biological function of SNHG1 in liver cancerThe tumor-promoting role of SNHG1 in liver cancer was confirmed by CCK8,clone formation assay and tumor formation assay in nude mice.The activation of SNHG1 on aerobic glycolysis of hepatoma cells was validated by gene set enrichment analysis(GSEA),glucose consumption and lactate production assays.Furthermore,CCK8 and clone formation experiments observed that the glycolysis inhibitor 2-DG could reverse the promoting effect of SNHG1 on the proliferation of hepatoma cells.These results suggest that SNHG1 can promote the proliferation of hepatoma cells by activating the aerobic glycolysis pathway to some extent.Part Ⅳ SNHG1 promotes aerobic glycolysis of hepatoma cells through miR-326/PKM2Overlapping the 8827 DEGs in liver cancer and 12 aerobic glycolysis genes by Venn diagram,two aerobic glycolysis genes(PKM and ALDOA)were identified to be upregulated in liver cancer.The Kaplan-Meier survival curve showed that liver cancer patients with high expression of PKM/ALDOA have worse prognoses.Pearson correlation analysis demonstrated that SNHG1 was positively correlated with PKM2 expression,whereas SNHG1 had no significant correlation with ALDOA expression.PKM2 is the main form of PKM in liver cancer.Thus,it was speculated SNHG1 might regulate aerobic glycolysis in hepatoma cells through PKM2.Western blot assay showed that the expression level of PKM2 was significantly increased in hepatoma cells.q RT-PCR and Western blot assays confirmed that knockdown of SNHG1 expression significantly inhibited PKM2 expression in hepatoma cells.Glucose consumption and lactate consumption assays demonstrated knockdown of PKM2 expression reversed the promotion effect of SNHG1 on aerobic glycolysis of hepatoma cells.Combining with subcellular localization prediction and subcellular fractionation experiments,we confirmed SNHG1 were expressed both in the cytoplasm and nucleus of hepatoma cells.Thus,we speculated that SNHG1 in the cytoplasm might bind to some miRNAs competitively with PKM2 and inhibit the miRNAs-induced PKM2 repression.Through differential analysis for miRNA expression profile of liver cancer in TCGA,we identified 40 downregulated miRNAs in liver cancer tissues.Bioinformatics prediction obtained miRNA-SNHG1 pairs and miRNA-PKM2 pairs.Overlapping downregulated miRNAs,miRNAs in miRNA-SNHG1 pairs and miRNAs in miRNA-PKM2 pairs,only miR-326 was identified as the eligible miRNA.QRT-PCR confirmed miR-326 expression was dramatically decreased in hepatoma cells.QRT-PCR and Western blot assays observed that overexpression of miR-326 significantly reduced PKM2 expression,while inhibition of miR-326 significantly upregulated PKM2 expression.Dual-luciferase reporter assays verified the interactions of miR-326 with the 3’ untranslated regions(3’UTR)of PKM2 and SNHG1,respectively.Combined with dual-luciferase reporter and AGO2-based RNA immunoprecipitation(RIP)assays,we demonstrated that overexpression of SNHG1 could block the interaction of miR-326 and PKM2 3’UTR.QRT-PCR confirmed that miR-326 inhibitor reversed the decrease of PKM2 expression induced by knockdown of SNHG1.Meanwhile,glucose consumption and lactate consumption assays demonstrated that miR-326 inhibitor reversed the decrease of glycolysis level induced by knockdown of SNHG1.Moreover,pc DNA3.1-SNHG1-wt vector or pc DNA3.1-SNHG1-mut vector with mutations at the putative miR-326 binding sites were respectively transfected into hepatoma cells after knockdown endogenous SNHG1;then Western blot validated that the promotion effect of SNHG1 on PKM2 expression was dependent on the interaction of SNHG1 and miR-326.These above results indicates that SNHG1 activates aerobic glycolysis and promotes proliferation of hepatoma cells through the miR-326/PKM2 axis to some extent.Part Ⅴ Construction of a prognostic risk score model for liver cancer patients based on splicing factorThrough differential expression analysis for splicing factor expression profile of liver cancer in TCGA,a total of 40 differentially expressed splicing factors were identified.Following,a prognostic risk score model consisting of DNAJC6,ZC3H13,IGF2BP3 and DDX19 B was established by univariate Cox regression analysis,LASSO regression and multivariate Cox regression analyses.The Kaplan-Meier survival curve and ROC curve analysis confirmed the good performance of the prognostic model.Univariate and multivariate Cox regression analysis validated the independence of the prognostic model.GSEA results suggest that multiple cancer-related pathways and biological processes,including cell cycle,positive regulation of DNA replication,and single-stranded DNA helicase activity,might be activated in liver cancer patients with high risk stratified by this prognostic model.These results might account for the observed poor prognosis of liver cancer patients in high-risk group. |
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