| BackgroundLung cancer is the most common malignant tumor in China,non-small cell lung cancer carcinomal(NSCLC)is the most common pathological type,which mainly includes adenocarcinoma and squamous cell carcinoma.The occurrence and development of lung cancer is a complex pathophysiological process accompanied by a series of abnormal gene expression,especially the genes involved in DNA damage,cell cycle and differentiation are closely related to the occurrence and metastasis of cancer.With the development of molecular biology technology,a large number of molecular-targeted drugs have been developed and applied in clinical practice,which has alleviated the dilemma of clinical treatment.However,due to the heterogeneity of lung cancer,the treatment of molecular-targeted drugs still have limitations,so it is urgent to explore more potential makers and provide more selectivity for clinical treatment,and provide more effective diagnosis and prognosis molecular marker.Bioinformatics is a new interdisciplinary subject.After obtaining the data of genomics,transcriptome and proteomics,bioinformatics can be used to classify and annotate the data,so as to explore the possible molecular mechanism of disease occurrence and development.With the increasing importance of bioinformatics,the analysis of gene expression data in disease research can provide important basis for the diagnosis,teatment and design of new drugs.PurposeThis study aims to explore potential molecular makers in NSCLC by bioinformatics methods,and identify target genes that are not yet intensively studied.The cancer databases of TCGA and GEO were used to analyze the expression of the target gene in NSCLC and the possible molecular mechanisms of the target gene through strong interaction about gene and protein.Furthermore,it is further verified by clinical sample data,in order to find new markers for early diagnosis and prognosis judgment of NSCLC.Providing new therapeutic targets for the treatment of NSCLC,opening a new way for molecular targeted therapy of NSCLC.MethodsUsing Gene Expression Omnibus(GEO)download data sets about NSCLC,three sets of data are combined and take the intersection by using Calculate and draw custom Venn diagrams,which is the online Venn diagrams tool,thus obtain the differentially expressed genes(DGEs).Oncomine database and literature review were used to further identify GINS2,a target gene with less research on NSCLC with significance.Based on TCGA database,GEO database analysis of GINS2 expression in NSCLC and survival curve analysis,using TCGA database further analyze the interaction gene of GINS2.Based on Genemania database and STRING database,the protein interaction network PPI encoded by DEGs was constructed to further analyze the possible molecular mechanism of GINS2.The fresh cancer tissues and adjacent tissues of NSCLC were newly removed from the Department of Thoracic Surgery of the Second Hospital of Lanzhou and Department of Breast Surgery,940 Hospital of the People's Liberation Army Joint Service.The RT-PCR technique was used to detect GINS2 in different stages,different degrees of differentiation,and different pathological types.The relative expression levels in NSCLC cancer tissues and adjacent tissues were analyzed based on Graphpad Prism7 software TTest to analyze the correlation between the expression of GINS2 and the clinical features of NSCLC.Results1.Based on the GEO database,three data sets were taken and the intersections were obtained,and a total of 17 significantly up-regulated DEGs were obtained.2.Oncomine database analysis and literature review showed that GINS2 had a certain correlation with tumor size,lymph node metastasis and tumor grade3.Using Oncomine database analysis and literature review found that GINS2 in NSCLC research mainly focused on LUSC,which was related to gender and clinical stage.There was no significant difference in the expression of different pathological types.Based on the TCGA database,GINS2 strong interaction genes were CDT1,GMNN and CENPN.Based on the Genemania database and the STRING database,20 kinds of interaction proteins encoded by DEGs were constructed.4.Based on TCGA database,GEO database analysis and clinical sample data,the correlation between GINS2 and clinical features was verified.The results showed that the results of clinical sample analysis differed from the individual results of TCGA big data analysis.Clinical sample analysis showed:(1)GINS2 was significantly different in NSCLC cancer tissues and adjacent tissues(P < 0.05);(2)GINS2 expression was significantly up-regulated in LUSD patients compared with LUAD patients(P < 0.05);GINS2 expression was significantly different in NSCLC patients of different ages(P < 0.05);(3)GINS2 expression was up-regulated in male patients compared with female patients;(4)GINS2 was significantly up-regulated in smoking patients compared with non-smoking patients((P < 0.05);(5)The up-regulated expression of GINS2 was significantly different from tumor size(P < 0.05),lymph node metastasis(p < 0.05),and tumor stage(p < 0.05).TCGA database analysis showed that GINS2 expression was not significantly correlated with pathological type and stage(P > 0.05),and survival curve analysis was not statistically significant(P = 0.78),but GEO database analysis showed statistical significance(P = 0.0002394).Conclusion1.GINS2 is the new maker of NSCLC.2.TCGA database was used for big data analysis and clinical sample data to verify the expression and significance of GINS2 in NSCLC,and it was found that the high expression of GINS2 was related to tumor proliferation and invasion,and smokers and men might be the susceptible groups with up-regulated GINS2 expression.3.GINS2 is a potential diagnostic and prognostic marker and molecular target of NSCLC.Further study on related drugs to inhibit the high expression of GINS2 can open up a new therapeutic approach for clinical treatment of NSCLC,which has important clinical significance for further improving the efficacy,extending the survival period and improving the prognosis of NSCLC patients. |
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