| Background:Hepatocellular carcinoma(HCC)is a serious liver disease caused by the malignant transformation of liver cells.It is also the most common primary liver cancer.China is a country with a high incidence of HCC,with about 70% of the population having a background of hepatitis B virus infection.Clinically,surgical resection is the only effective treatment for early HCC.However,HCC has a40%–70% recurrence rate five years after operation,and there is still no worldwide recognized treatment scheme to reduce HCC recurrence.Studies have shown the effectiveness of immunotherapy in hepatocellular carcinoma.However,the treatment effect in most patients is not ideal,and there is an urgent need to find effective biomarkers to screen potential populations that can benefit from immunotherapy so as to achieve accurate diagnosis and treatment of HCC.Basement membrane(BM)is an important component of the extracellular matrix,which plays an important role in the formation and development of tumors.It has been shown that hepatocellular carcinoma cells can infiltrate and metastasize by destroying the basement membrane and invading surrounding tissues.However,the relationship between basement membrane-related genes(BMRGs)and hepatocellular carcinoma(HCC)is still poorly studied.Objective:The aim of this study was to bioinformatically analyze the expression of BMRGs in HCC and its prognostic value and to explore the relationship between the expression of key genes and the efficacy of immunotherapy in order to find potential diagnostic markers and therapeutic targets.Methods:1.Bioinformatics analysisIn this study,clinical and gene expression data of HCC patients were obtained from the Cancer Genome Atlas(TCGA)database and the Gene Expression Omnibus(GEO)database,and BMRG data were obtained from the Gene Cards database.Based on the TCGA database,univariate COX regression and LASSO regression analysis were used to construct the risk model of differentially expressed genes related to prognosis.The TCGA cohort was divided into high-risk groups and low-risk groups according to the median risk score,and external validation was performed based on the GEO cohort.The accuracy of the prognostic model in predicting the prognosis of HCC was verified by the nomogram and ROC curve.We also conducted a protein-protein interaction network screening of central genes that may play a key role and analyzed the relationship between the expression of key genes and the efficacy of immunotherapy by immune infiltration.2.Experimental verificationTo validate the results of bioinformatics analysis,the expression levels of key genes in cancer tissues and corresponding para-cancer tissues of 40 pairs of HCC patients were detected by fluorescence quantitative PCR,and western blot(WB)was used to detect the expression levels of key genes in 10 pairs of HCC cancer tissues and adjacent normal tissues.The relationship between the expression of key genes and the efficacy of immunotherapy in 40 patients with HCC was analyzed.HCC patients were divided into highand low-expression groups according to the median relative expression of key genes.The relationship between immunotherapy and overall survival and relapse-free survival was further analyzed by survival analysis in the high-expression group and the low-expression group.Results:1.A total of 121 differentially expressed BMRGs were screened through bioinformatics analysis.After single-factor COX regression and LASSO regression analysis,six related genes(ADAMTS5,CD151,CTSA,MEP1 A,MMP1,and ROBO3)were ultimately identified to construct a prognostic model.We found that the overall survival period of HCC patients in the high-risk group was significantly shorter than that in the low-risk group(P< 0.01),and the GEO queue showed the same results(P<0.05).According to the prognostic risk model,the ROC curve was plotted,and the area under the curve for predicting the overall survival period of 1,3,and 5 years was 0 773,0.695,and 0 643,indicating the accuracy of the risk model in predicting the overall survival of patients.Risk score and pathological staging are independent factors affecting the prognosis of HCC patients(P<0.05).Through protein interaction network analysis,we identified a key gene,ITGA3,closely related to the prognosis of HCC.We found that it may be able to positively regulate immune responses,and further analysis showed that the high expression group of ITGA3 is associated with higher expression of immune checkpoint genes(PD-1,CTLA4,LAG 3,PD-L1,and PD-L2),which could be a potential target for immunotherapy of HCC.2.In the experiment validation,the expression level of ITGA3 gene in HCC tissues was higher than that in the adjacent tissues(p<0.05).WB assay also showed that the expression level of ITGA3 protein in HCC tissues was higher than that in the adjacent tissues(p<0.05).3.According to the median of relative expression of the ITGA3 gene,40 HCC patients were divided into high-and low-expression groups.We found that the overall survival time of the high expression group was shorter than that of the low expression group(p < 0.05).The overall survival time of the patients with high expression of ITGA3 was longer than that of the patients without immunotherapy(p < 0.05),but there was no significant difference in the patients with low expression of ITGA3(P = 0.192).Further analysis of relapse-free survival showed the same results in both groups.Conclusion:The basement membrane is associated with the occurrence and progression of HCC and can predict the prognosis of HCC patients.Protein interaction network analysis showed that ITGA3 was highly expressed in HCC and positively correlated with immune cells in the immune microenvironment.ITGA3 may play an important role in the regulation of the immune microenvironment in HCC.The results showed that patients with high expression of ITGA3 in HCC were more suitable for immunotherapy.These findings provide a new predictive model for HCC prognosis and response to immunotherapy. |
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