Screening Of Biomarkers For Hepatocellular Carcinoma And The Diagnosis And Prognosis Value And Mechanism Of EIF3B In Hepatocellular Carcinoma

Background:Hepatocellular carcinoma(HCC)is a common malignant tumor with high incidence and mortality rates.Due to the concealment of early HCC symptoms and the limited sensitivity and specificity of AFP in screening for early HCC,early diagnosis is challenging.In the late stages,due to the high heterogeneity of HCC,the effect of systemic treatment is often poor.Furthermore,the lack of routine molecular typing indicators for HCC makes it difficult to implement personalized treatment.Autophagy widely exists in eukaryotic cells.Under normal physiological conditions,cells maintain a low level of basal autophagy,playing a vital role in maintaining cell survival and homeostasis.When autophagy levels are disrupted,it may trigger the occurrence of malignant tumors.Previous studies have found that autophagy activity in primary liver cancer is significantly reduced,less than one-tenth of that in normal liver cells.Moreover,autophagy plays a crucial role in the formation and progression of HCC.Therefore,identifying autophagy-related biomarkers with clinical diagnostic and prognostic value in HCC and clarifying the role and mechanism of these genes in HCC are crucial for improving the diagnosis and treatment of HCC.Objectives:1.To identify autophagy-related genes differentially expressed between HCC and adjacent tissues,evaluate their potential application value in HCC diagnosis,and analyze their impact on HCC prognosis.Additionally,to construct a prognostic model for HCC.2.EIF3B was selected for further exploration of its clinical significance in HCC diagnosis and prognosis assessment.Based on this,a prognostic model for HCC was constructed.Concurrently,the relevant mechanism pathways potentially involved by EIF3B in HCC were analyzed.3.An in-depth study of the role and specific mechanism of EIF3B in HCC was conducted to provide new targets and theoretical bases for the diagnosis and treatment of HCC.Methods:1.Screening of target gene sets:The HCC dataset(LIHC dataset)was obtained from the TCGA database.Differentially expressed genes(DEGs)were identified through R language analysis.Combined with autophagy-related genes(ARGs)from the GeneCards database,autophagy-related differentially expressed genes(ARDEGs)in HCC were determined.Single-factor Cox regression analysis was performed on ARDEGs to identify genes associated with overall survival(OS),disease-specific survival(DSS),and progression-free interval(PFI)in HCC patients,termed cox-ARDEGs.2.Analysis of the cox-ARDEGs:GO and KEGG functional enrichment analyses were performed.Through single-factor and multi-factor Logistic regression analysis,cox-ARDEGs associated with HCC diagnosis(DARDEGs)were screened,and diagnostic ROC curves were plotted.A Cox-LASSO prognostic model was constructed to identify HCC prognosis-related cox-ARDEGs(PARDEGs).Differential expression analysis,correlation analysis,and K-M survival curves for OS were conducted on PARDEGs.3.Analysis of EIF3B:Differential expression analysis of EIF3B in pan-cancer and HCC was performed using the TCGA database,UCSC Xena website,and HPA database.The correlation between EIF3B expression levels and clinicopathological characteristics of HCC patients was analyzed.Diagnostic ROC analysis was used to compare the diagnostic accuracy of EIF3B and AFP.K-M survival curves were employed to analyze the correlation between EIF3B expression levels and OS,DSS,and PFI in HCC patients,as well as the correlation between EIF3B expression levels and OS in various subgroups.A prognostic model including EIF3B was constructed through multi-factor Cox regression analysis and quantitatively presented using a nomogram.Genes correlated with EIF3B gene expression were screened using Pearson correlation analysis.Finally,GSEA analysis was conducted.4.Influence and mechanistic study of EIF3B on the biological behavior of HCC:The relative content of EIF3B in liver cancer cells was detected using real-time fluorescent quantitative PCR.shRNA gene interference technology was used to construct experimental models of EIF3B knockdown and control cells.CCK8 experiments,clone formation experiments,flow experiments,cell scratch experiments,and Transwell experiments were performed to assess cell proliferation,anti-apoptosis,migration,and invasion abilities in each experimental group.The formation of autophagic vesicles in each group was observed using electron microscopy.The expression of LC3B in each group of cells was observed through real-time fluorescent quantitative PCR,immunoblotting,and immunofluorescence experiments.Additionally,a nude mouse tumor-bearing model was constructed to investigate the effect of EIF3B on HCC growth,and the expression of LC3B in each transplanted tumor model was detected using immunoblotting.Finally,the expression of proteins in the PI3K/AKT/mTOR signalingResults:1.From the TCGA-LIHC database,we successfully screened out 15 autophagy-related differentially expressed genes(cox-ARDEGs)that are closely related to the overall survival(OS),disease-specific survival(DSS),and progression-free interval(PFI)of hepatocellular carcinoma(HCC)patients.These genes are overexpressed in HCC.2.Functional enrichment analysis of cox-ARDEGs using GO and KEGG revealed that these genes are primarily enriched in biological processes such as cell division,cell cycle,and signal transduction pathways.3.Through univariate and multivariate logistic regression analysis,we identified two cox-ARDEGs,EIF3B and PATS2,that are closely associated with the diagnosis of HCC.Diagnostic ROC curve analysis showed that the AUC values of EIF3B and PATS2 are as high as 0.959 and 0.975,indicating their high diagnostic accuracy.4.We screened out 5 PARDEGs from the cox-ARDEGs,constructed a PARDEGs-Cox-LASSO prognostic model,and visualized it using a nomogram.Risk factor analysis based on the RiskScores obtained from the model showed that patients in the high-riskscore group have a shorter OS and a higher mortality rate.5.The PARDEGs include PFKFB4,EEF1E1,EIF3B,TRIP13,and TPX2.Differential expression analysis revealed that these 5 genes are overexpressed in HCC.Correlation analysis showed a positive correlation among them.K-M survival analysis further confirmed that the upregulation of these 5 genes is associated with reduced OS in HCC patients.6.Using the TCGA database,UCSC Xena website,and HPA database,we performed differential expression analysis of EIF3B in various cancers and HCC.The results showed that EIF3B is overexpressed in most tumor cells,particularly in HCC,where both mRNA and protein expression levels are significantly elevated.7.When analyzing the correlation between EIF3B expression levels and clinicopathological features of HCC patients,we found that EIF3B expression is higher in Asians,patients with BMI≤25,histological grade G3/G4,pathological stageⅡ/Ⅲ/Ⅳ,T stage T2/T3/T4,tumor burden,vascular invasion,AFP>400ng/ml,deceased patients,disease-related deaths,and disease progression.8.Diagnostic ROC analysis showed that EIF3B has higher diagnostic accuracy than AFP in HCC.Additionally,mass spectrometry can detect EIF3b protein expression in human plasma.Therefore,the combined use of EIF3B and AFP has potential clinical value in HCC diagnosis.9.K-M survival analysis demonstrated that the upregulation of EIF3B is closely associated with reduced OS,DSS,and PFI in HCC patients.Subgroup analysis further showed that high EIF3B expression is associated with reduced OS in subgroups of patients with age ≤60 years,male gender,Asians,BMI≤25,AFP≤400ng/ml,albumin≥3.5g/dl,tumor resection margin achieving R0 status,vascular invasion,inflammatory infiltration in the tumor periphery,tumor burden,and no tumor burden.10.Through univariate and multivariate Cox regression analysis,we identified tumor burden and EIF3B expression level as independent prognostic factors for HCC patients.11.We constructed a prognostic model including EIF3B and quantified it using a nomogram.Compared to traditional staging systems,this model demonstrated improved prediction accuracy.12.Through Pearson correlation analysis,we identified 35 genes that are correlated with EIF3B gene expression.13.GSEA analysis showed that the high expression of EIF3B in HCC is associated with multiple pathways,including PI3K_AKT_MTOR_SIGNALING,MTORC1_SIGNALING,DNA_REPAIR,MYC_ACTIV_PATHWAY,MYC_TARGETS_V1,and MYC_TARGETS_V2.14.EIF3B is overexpressed in hepatoma cell lines.15.Knockdown of EIF3B inhibits the proliferation,migration,and invasiveness of hepatoma cells while promoting apoptosis.Additionally,EIF3B knockdown suppresses the growth of hepatoma tumors in nude mice.16.Knockdown of EIF3B can affect autophagy in hepatocellular carcinoma cells both in vivo and in vitro.17.Knockdown of EIF3B can inhibit the activity of the PI3K/AKT/mTOR signaling pathway in hepatocellular carcinoma cells both in vivo and in vitro.Conclusions:1.EIF3B and PATS2 possess diagnostic value for screening hepatocellular carcinoma,while PFKFB4,EEF1E1,EIF3B,TRIP13,and TPX2 have prognostic evaluation significance.The PARDEGs-Cox-Lasso prognostic model constructed for hepatocellular carcinoma can effectively assess patient prognosis.2.EIF3B demonstrates higher accuracy than AFP in the diagnosis of hepatocellular carcinoma.3.EIF3B is an independent prognostic factor affecting the overall survival of patients.The prognostic model incorporating information on EIF3B expression can effectively evaluate patient prognosis.4.Knockdown of EIF3B can inhibit the proliferation,migration,and invasiveness of liver cancer cells,promote apoptosis in liver cancer cells,and suppress the growth of liver cancer tumors in nude mice.5.EIF3B may be involved in the regulation of autophagy in hepatocellular carcinoma cells.6.EIF3B may regulate the autophagy of hepatocellular carcinoma cells through the PI3K/AKT/mTOR signaling pathway.7.EIF3B is expected to become a potential diagnostic and therapeutic target for hepatocellular carcinoma.