Expression Pattern And Prognostic Value Of Cell Adhesion Junction Regulatory Genes In Hepatocellular Carcinoma

BackgroundAdhesion of cells is a dynamic structure of formation,strengthening and spreading,degradation,and subsequent remodeling,which plays a key role in cell proliferation,maintenance of activity,differentiation,and migration.Cell adhesion molecules,as a kind of cell surface transmembrane glycoproteins,are highly concerned about the relationship between tumor occurrence,invasion and metastasis.Once the cell adhesion changes,there will be serious pathological changes,affecting tumor proliferation,metastasis and resistance to apoptosis.In general,Adhesive junctions(AJ),together with Tight junctions(TJ)and desmosomes,form apical junctional complexes that control adhesion and barrier function between epithelial cells,as well as regulation of the actin cytoskeleton,intracellular signaling pathways and transcriptional regulation.It has been proven that tight junctions play an important role in the metastasis of various tumors such as lung cancer and colon cancer.In contrast,there are few studies on adherencial junctions.During the invasion of cancer cells,adherent junctions can enhance the adhesion and migration of cancer cells to the matrix,and may enhance their dissemination by establishing connections with the endothelial barrier.A variety of genes may affect cell growth by controlling the process of cell adhesion junctions,so their related regulatory genes may have prognostic value and become potential therapeutic targets for cancer treatment.In recent years,the incidence of Hepatocellular Carcinoma(HCC)has gradually increased,and its late detection and poor prognosis have caused a huge physical,psychological and economic burden to patients.With the development of chip technology and high-throughput sequencing technology,a large number of gene data have been mined.It has gradually become a current research trend to understand diseases more deeply by studying the mechanism between genes and related diseases.At present,the relationship between cell adhesion related regulatory genes and hepatocellular carcinoma is still unclear.In this paper,we studied the relationship between cell adhesion related regulatory genes and hepatocellular carcinoma through bioinformatics methods in order to further explore the relationship between them.MethodsThe main data set of this study was 424 clinical samples from The Cancer Genome Atlas database,including 374 HCC tissue samples and 50 normal adjacent tumor tissue samples for further analysis.The RNA data of hepatocellular carcinoma patients were downloaded from the database,and the differentially expressed regulatory genes related to cell adhesion junctions in hepatocellular carcinoma tumor tissue samples and normal tissue samples were analyzed.By further screening the prognostic related genes,a multi-gene risk prognostic model for predicting the prognosis of hepatocellular carcinoma was established.According to the risk score calculated by the model,the patients were divided into high-risk group and low-risk group,and the survival status of high and low-risk groups was compared.Combined with the overall survival of HCC patients,the relationship between the prognostic risk model and various clinical factors was analyzed to verify whether the prognostic risk model could accurately predict the prognosis of HCC patients.A new prognostic nomogram was established according to age,gender,histological grade,pathological stage and risk score to predict the prognosis of patients.Finally,the relationship between the model and tumor immune microenvironment was explored based on the results of GESA analysis of high and low risk groups.Results1.Results of screening for key cell adhesion junction genes(1)Based on TCGA database,48 degs(Differentially Expressed Genes)were proved and screened out in cell adhesion junction related regulatory genes that were differentially expressed between HCC tissue samples and normal samples(p<0.05).GO and KEGG enrichment analysis showed that the differentially expressed genes were significantly enriched in cancer pathways.(2)Univariate Cox regression analysis was used to screen differential genes related to prognosis,and further Lasso Cox regression analysis was used to select 10 regulatory genes related to cell adhesion junction with prognosis.Among them,FYN and PTPRB were protective effect genes with HR<l.The remaining PARD3,SSX2 IP,RAC3,CDC42,NECTIN1,WASF1,RAC1 and SMAD2 were risk effectors of HR>l,and the prognostic risk model was constructed based on these 10 key regulatory genes.2.Validation results of prognostic risk models(1)The risk score of each patient was calculated based on the 10 key regulatory genes,and the patients were divided into high-risk group and low-risk group by the median risk score obtained by the risk score calculation formula.Kaplan-Meier survival analysis confirmed that there was a statistically significant difference in survival status between the high risk group and the low risk group(p < 0.001).ROC curve results showed that the area under the curve(AUC,P < 0.001)at 1 year,3 years and 5 years in the low risk group was significantly lower than that in the low risk group.area under the ROC curve)were 0.799,0.708 and 0.645,respectively.(2)Using the same calculation formula and grouping method,combined with the clinical data of HCC patients in an independent cohort in the external GEO database,it was verified again that there was a survival difference between the high risk group and the low risk group(p<0.001).The AUC of 1-year,2-year and 3-year OS in the low risk group was 0.749,0.752 and 0.846,respectively.(3)Further univariate and multivariate Cox analysis and stepwise regression based on Akaike information criterion(AIC)criteria confirmed that the prognostic Risk model had prognostic value and could be used as an independent prognostic factor(Risk Score AUC=0.807,P < 0.05).p<0.001).3.A prognostic nomogram was establishedA novel prognostic nomogram based on age,sex,histological grade,pathological stage and risk score was developed to predict the prognosis of HCC patients.The predictive accuracy of the nomogram was verified by calibration curve.4.Results of correlation analysis between prognostic risk model and tumor immune microenvironment(1)Based on the prognostic risk model,the differential analysis of gene expression between high and low risk groups was performed,and a total of 542 down-regulated genes and 228 up-regulated genes were obtained.(2)GESA enrichment analysis was performed on the differential genes between the high and low risk groups,and the results suggested that the G2 M checkpoint,PI3k-AKT-m TOR signaling pathway,DNA damage repair,MTORC1 signaling pathway and other related biological pathways were activated.(3)Correlation analysis between prognostic model and tumor microenvironment showed that in the high-risk group,Activated B cells,activated CD8+ T cells,follicular helper T cells(Tfh),type 1 helper T cells,type 17 helper T cells(Th17),activated/immature/plasmacytoid dendritic cells,activated/immature B cells,effector CD8+ There was a significant decrease in T cells,macrophages,NK cells,monocytes,neutrophils,eosinophils,and CD56 killer cells.The expression of a large number of immune checkpoints was increased,including ADORA2 A,CD276,CD47,CD80,CD86,and CTLA4.In particular,the expression of CD276,CD47 and CD80 was higher in the high-risk group,while PDCD1(PD-1)and CD274(PD-L1)showed no significant difference between the two groups,but they still showed an upward trend in the high-risk group.5.Results of drug sensitivity analysis based on prognostic risk modelThe results of common drug sensitivity analysis of HCC patients suggested that patients with high risk score were sensitive to axitinib,oxaliplatin,cisplatin,gemcitabine,irinotecan,and 5-fluorouracil.Patients with low risk scores were highly sensitive to sorafenib.It was also found that patients with a low risk score were more susceptible to commonly used chemotherapy drugs for HCC.Conclusion1.Ten adhesion junction regulatory genes that were most relevant to HCC prognosis were identified,among which FYN and PTPRB were HR<1,PARD3,SSX2 IP,RAC3,CDC42,NECTIN1,WASF1,RAC1 and SMAD2 were risk effector genes for HR>l.These 10 key regulatory genes may be key players in HCC tumor progression or suppression,as well as potential therapeutic targets with prognostic value.2.A prognostic risk model was constructed based on 10 key genes,and the survival analysis results verified the prognostic value of the prognostic risk model.Univariate Cox,multivariate Cox and stepwise regression analyses with other clinical factors confirmed that the risk model had independent and accurate prognostic prediction ability.A novel prognostic nomogram was established to accurately predict the 1-,3-and 5-year survival rates of HCC patients.3.Immune correlation analysis confirmed that the prognostic risk model was closely related to the immune status of the tumor microenvironment.Patients in the high and low risk groups were not only different in the immune score and matrix score,but also significantly different in the correlation with different immune infiltrating cells and immune checkpoints,which provided a new idea for the immunotherapy of HCC.4.The results of drug sensitivity analysis based on the prognostic risk model suggested that the risk score of the model may be helpful for the selection of common chemotherapy and targeted drugs for HCC.