| Background:Gastric cancer is a deadly disease affecting human health.According to the research results of the International Agency for Research on Cancer(IARC),there were about 1.08 million new cases globally in 2020,accounting for 5.6% of all malignant tumors,and about 769,000(7.7%)deaths of gastric cancer worldwide.Although the incidence and mortality of gastric cancer have been declining due to gastric cancer research,cancer screening,and improvement of diagnosis and treatment.However,as the population grows and ages,the burden of gastric cancer remains severe.Despite the application of targeted therapy,immunotherapy and other methods,the prognosis of patients with advanced gastric cancer is still poor.Therefore,it is particularly important to find the key genes and therapeutic targets that affect the prognosis of gastric cancer.With the development of genomics technology and the emergence of a large number of tumor-related biological data,cancer bioinformatics can analyze the pathogenesis of cancer through the analysis of cancer gene expression profile.Identifying the relationship between tumor biomarkers and tumor prognosis makes it possible to search for molecular markers that can be used as cancer diagnosis,prediction,prognosis and treatment,and it is of great significance.However,cancer is a complex disease involving multiple genes.Although a single gene can be used as a potential prognostic marker,it has certain limitations.Based on the analysis of cancer multi-omics big data,effective bioinformatics analysis methods can be used to find multiple gene combination prognostic models,which can be applied to the diagnosis of cancer patients,prognosis evaluation and treatment effect evaluation.Objective: The TCGA and GSE62254 dataset were analyzed by bioinformatics method,and the prognostic gene model of gastric cancer was constructed based on prognostic related genes.The relationship between risk score model and clinicopathological factors was analyzed,and the relationship between CTNNAL1 expression characteristics and clinicopathological factors and prognosis was further analyzed.Methods:1.The gastric cancer dataset and GSE62254 dataset in TCGA were analyzed by bioinformatics method,and the common prognostic related genes were found.The function enrichment analysis of prognostic related genes was performed by using the R language cluster Profilerpackage.Based on Lasso-Cox regression model,a prognostic risk score model containing six genes was constructed.The Time Receiver Operating Characteristic Curve(t ROC)was used to evaluate the risk scoring model.The relationship between the prognostic model and clinicopathological factors was analyzed.Based on multivariate risk regression analysis,a Nomogram was constructed that included the prognostic assessment model and clinicopathological factors.2.The gene expression profile data of 33 tumor types were downloaded from the TCGA database to analyze the relationship between the expression of CTNNAL1 m RNA and the prognosis of tumor patients.Analyzing the data set of gastric cancer expression and clinicopathological factors in the TCGA database,the patients were divided into two groups according to the median value of CTNNAL1 expression.The difference of CTNNAL1 expression level between the high expression group and the normal control tissue was compared by the chi-square test,and the difference of CTNNAL1 expression between each clinicopathological factor group was analyzed.Surv Miner package was used to determine the best cutoff value of CTNNAL1 m RNA expression and patient prognosis in GSE62254 gastric cancer data set.Then 300 gastric cancer patients in GSE62254 were divided into two groups according to the best cutoff value.Kaplan-Meier method was used to draw the survival curve,and log-rank test was used to compare the survival rates between the two groups.The relationship between CTNNAL1 m RNA expression and clinicopathological factors was analyzed by chi-square test.The expression level of CTNNAL1 gene in Human normal tissues was analyzed by using the Human Protein Atlas database,and the expression characteristics of CTNNAL1 gene at the cellular level were analyzed by using the single cell sequencing data.Furthermore,the expression of CTNNAL1 in different types of cells in gastric tissue was analyzed in GSE134520(Gastric Single Cell Sequencing Data Set).3.The differences of CTNNAL1 in 209 cases of gastric cancer and its adjacent normal mucosa tissues were detected by immunohistochemistry,and the protein expression level of E-cadherin gene in 178 cases of gastric cancer tissues were detected by immunohistochemistry.The correlation between the two,and the relationship between each gene and clinicopathological factors and their significance were analyzed.Results:1.Univariate Cox analysis showed that 761 genes were associated with gastric cancer prognosis in the TCGA GC data set(P<0.05),including 1137 genes with Hazard ratio(HR)>1 and 424 genes with HR < 1.There were 5949 genes related to gastric cancer prognosis in GSE62254 data set(P<0.05),among which there were 2913 genes related to HR >1 and 3036 genes related to HR < 1.The prognostic related genes of both data were457 with poor prognostic genes and 171 with good prognostic factors.Bad prognostic factors were significantly enriched in KEGG signaling pathways including PI3K-Akt signaling pathway,RAP1 signaling pathway,adhesion plaque,RAS signaling pathway,mitogen-activated protein kinase(MAPK)signaling pathway,basement membrane-receptor interaction and other biological pathways.2.TCGA and GSE62254 analysis of the generation of prognosis related gene into the Lasso-Cox regression model,successfully build contains six genetic risk score model,the six gene were PRR15L(proline rich like 15),SP6 transcription factor,CPNE8,NRP1(Neuropilin 1),PDGFRL(platelet-derived growth factor receptor like),and CTNNAL1(catenin alpha like 1).Results of survival analysis showed that the survival rate of gastric cancer patients with high risk score was significantly lower than the patients with low risk score.The 5-year survival rate AUC predicted by this model was0.754,which indicated that this model had a good prognostic value.3.Prognostic risk score of gastric cancer was significantly correlated with histological grade,Lauren typing,TNM staging.4.Risk score and clinicopathological factors(age,gender,histological grade,Lauren type,T stage,N stage,M stage,MSI status and radiotherapy)were included in multivariate Cox regression analysis,and a quantitative Normogram was established to predict the individualized survival time of gastric cancer patients.5.Through univariate regression analysis of the relationship between CTNNAL1 m RNA expression and prognosis of different tumor types,it was found that CTNNAL1 was not only associated with poor prognosis in gastric cancer,but also in renal papillary carcinoma and low-grade glioma.In diffuse large B lymphoma and thymoma,it was associated with a better prognosis.6.CTNNAL1 is highly expressed in normal adrenal glands,ovaries,thyroid glands,testicles,lungs and myocardium.CTNNAL1 gene has a low cell specificity at the single cell level,and the highest expression level is found in trophoblast cells.The expression of CTNNAL1 in endothelial cells and stromal cells followed.The results of GSE134520 analysis showed that CTNNAL1 was expressed in a variety of cells,especially in endothelial cells and tumor cells.CTNNAL1 gene expression was positively correlated with stroma score,number of tumor-associated fibroblasts and number of endothelium cell.7.The CTNNAL1 m RNA expression of diffuse gastric cancer was significantly higher than that of intestinal gastric cancer(P = 0.014).The high expression rate of CTNNAL1 m RNA in G3 group was higher than that in G2 group and G1 group(P = 0.023),and the expression rate of CTNNAL1 m RNA in mesenchymal phenotype of gastric cancer was higher than that in epithelial phenotype(P< 0.001).In GSE62254,the survival rate of gastric cancer patients in the group with high expression of CTNNAL1 m RNA was lower than that in the group with low expression of CTNNAL1 m RNA(P< 0.001),and the expression rate of CTNNAL1 in diffuse gastric cancer was significantly higher than that in intestinal gastric cancer(P = 0.010).MSS/EMT subtype CTNNAL1 had the highest m RNA expression among the ACRG(Asian Cancer Research Group)molecular types of gastric Cancer.Gene Set Enrichment Analysis(GSEA)showed that CTNNAL1 expression was associated with epithelial mesenchymal?transition,MYOGENESIS,and TGF?BETA?SIGNALING pathways.PPI network analysis showed that CTNNAL1 gene was related to epithelial cell-cell adhesion and adhesionjuction.8.Immunohistochemical staining results showed that the high expression rate of CTNNAL1 protein in gastric cancer tissues was significantly higher than that in adjacent normal gastric mucosa tissues.The protein expression of CTNNAL1 was correlated with histological grade(P = 0.026,r=0.146).In Lauren classification,the expression of CTNNAL1 was significantly higher in diffuse gastric cancer than in intestinal gastric cancer(P = 0.008).The deletion rate of E-cadherin in the G3 group was significantly higher than that in the G1 group and G2 group,and the expression of E-caherin was correlated with the histological grade(P< 0.001,r=0.327).In Lauren typing,the deletion rate of E-caherin in diffuse gastric cancer was significantly higher than that in intestinal gastric cancer(P< 0.001).There was no significant correlation between the expression of CTNNAL1 and E-cadherin in 161 cases of gastric cancer(P>0.05).Conclusion:1.Based on the TCGA gastric cancer dataset and GSE62254 dataset,457 common poor prognostic genes and 171 good prognostic genes were obtained in this study,among which the poor prognostic genes were significantly enriched in PI3K-Akt signaling pathway,extracellular matrix adhesion and other pathways closely related to the occurrence and development of cancer.Using Lasoo-Cox regression model and TCGA gastric cancer data set,based on the selected prognostic related genes,a six-gene prognostic model of gastric cancer risk score was constructed.This model has some prognostic value.Based on the clinicopathological data from the TCGA gastric cancer dataset and the risk score model,a Norogram was constructed to predict the prognosis of gastric cancer patients.2.CTNNAL1 gene is closely related to the prognosis of a variety of tumors,and may be a prognostic factor for tumor;CTNNAL1 gene is widely expressed in a variety of tissues.At the single-cell level,CTNNAL1 gene is highly expressed in mesenchymal cells/fibroblasts and endothelial cells.High expression of CTNNAL1 may suggest that the increase of fibroblasts and/or endothelial cells in the tumor microenvironment which leads to poor prognosis of gastric cancer.3.The protein expression of CTNNAL1 in gastric cancer tissues was significantly higher than that in non canceroustissues;The expression of CTNNAL1 was heterogeneous in different histological types of tumor tissues,and the high expression of CTNNAL1 was correlated with diffuse gastric cancer,histological grade and stromal phenotype. |
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