| BackgroundNon Small Cell Lung Cancer(NSCLC)is one of the most common human malignant tumors with high morbidity and mortality.Most of the patients are already diagnosed late,so the treatment and prognosis are poor.The study found that if NSCLC early detection and timely treatment can take reasonable,can greatly improve patient survival rate.So looking for a high sensitivity and specificity of early diagnostic markers for the treatment of NSCLC is of great significance.MicroRNA(miRNA)is a non-coding RNA about 20 bp in length.Recently,some reports have reported that it can be used as a potential diagnostic marker for NSCLC.ObjectiveThe purpose of this study was to investigate the relationship between the expression of miRNA in tissues and plasma of patients with NSCLC and its clinical features.Based on this,combined with bioinformatics methods such as GO analysis and KEGG analysis,we initially established a regulatory network of lung cancer related genes for clinical lung cancer Of the targeted therapy to provide a theoretical basis.1.To investigate the relationship between miRNA expression in NSCLC tissueand plasma and the clinicopathological features of NSCLC patients so as to evaluate its potential clinical value in predicting the prognosis of patients.2.On the basis of the previous studies,we initially established a regulatory network of lung cancer-related genes by referring to the literature,combined with GO analysis and KEGG database,to provide a new theoretical and experimental basis for exploring the mechanisms of development and individualized treatment of lung cancer.Materials and methods1.Real-time fluorescent quantitative PCR was used to detect the expression of miR-21,miR-31 and miR-92 a in 40 NSCLC patients and adjacent non-cancerous normal tissues.miR-31 and miR-92 a,and to explore their correlation with the clinicopathological features of the patients.To evaluate the relationship between miR-21,miR-31 and miR-92 a by establishing receiver operating characteristic(ROC)curves Expression in the diagnosis of NSCLC value;preclude the use of Kplan-meire survival analysis of miR-21,miR-31 and miR-92 a expression and patient survival time relationship.2.Real-time fluorescent quantitative PCR was used to detect the plasma levels of miR-21,miR-31 and let-7 in 50 patients with NSCLC and 24 normal controls.The plasma miR-21 was compared between NSCLC patients and 24 healthy controls miR-31 and let-7,and to explore their correlation with the clinicopathological features of patients.The plasma miR-21,miR-31 and let-7 were assessed by establishing receiver operating characteristic(ROC)curves Expression in the diagnosis of NSCLC value;preclude the use of Kplan-meire survival analysis of miR-21,miR-31 and let-7 expression and patient survival time relationship.3.Examine the susceptibility genes of lung cancer by meta-analysis of the literature,combining the target genes PTEN,ITGA5,and KRAS corresponding to miR-21,miR-31,let-7,and using GO analysis and KEGG pathway analysis to construct the miRNAs and genes mentioned above.Lung cancer regulation network model;Analysis of the changes in the structure and function of lung cancer-relatedgenes erbB4 before and after the previous study of this issue,the use of KEGG to build erbB4 involved in the signal pathway;erbB4 added to the lung cancer control network constructed,and initially established A lung cancer regulatory network model consisting of miR-21,miR-31,let-7 and EGFR,P53,ITGA5,PTEN,KRAS,erbB4.Results1.The relative expression levels of miRNA-21,miRNA-31 and miRNA-92 a in NSCLC patients and adjacent normal tissues were significantly higher than that of miRNA-21,miRNA-31 and miRNA-There was no correlation between the expression of miRNA-21,miRNA-31 and miRNA-92 a and clinical pathological features such as sex,age,smoking history,tumor size and subtype in the correlation analysis of clinical features P> 0.05).The ROC curve analysis showed that the plasma high expression group were lower than that of low expression group.miRNA-21,miRNA-31 and miRNA-92 a had certain diagnostic efficacy on NSCLC,while the combination of miRNA-31 and miRNA-92 a had better diagnostic efficacy on NSCLC.Survival curves of patients with NSCLC showed that the median survival time of lung cancer patients with miRNA-21,miRNA-31 and miRNA-92 a.2.The relative expression levels of miR-21 and miR-31 in NSCLC patients and normal controls were significantly higher than those in normal controls and miR-31 and miRNA-The expression of miR-31 and let-7 in NSCLC patients with lymph node metastasis was significantly higher than that in NSCLC patients without lymph node metastasis(P <0.05)in the correlation analysis of clinical features).The other clinicopathological features were not correlated with the relative expression of miR-21,miR-31 and let-7(P> 0.05).ROC curve analysis showed that plasma miR-21,miRNA-The diagnosis of NSCLC was more effective.The survival curves of NSCLC patients showed that the median survival time of NSCLC patients with miR-21 and miR-31 overexpression groups were lower than those with low expression levels,While the median survival time of NSCLC patients with let7 high expression group was higher than that of low expression group.3.Meta-analysis was used to identify four lung cancer susceptibility genes:KRAS,EGFR,PTEN,P53,combined with miR-21,miR-31,let-7 corresponding target genes PTEN,ITGA5,KRAS to construct a lung cancer regulatory network.Based on the analysis of changes in the structure and function of the lung cancer-related gene erbB4 mutation in the earlier period of this issue,combined with erbB4's participation in the signal pathway found by KEGG,the erbB4 was added to the lung cancer regulatory network constructed this time and was initially established by miR-21,miR-31,let-7 and EGFR,P53,ITGA5,PTEN,KRAS,erbB4 lung cancer regulatory network model.ConclusionsThis article explores the potential value of tissue and plasma miRNAs in the diagnosis of NSCLC in NSCLC patients.The results show that miR-21,miR-31 and miR-92 a,and plasma miR-21,miR-31 and let-7 are all possible Based on the NSCLC diagnostic markers,using data mining combined with intelligent algorithms such as GO analysis,KEGG analysis,and meta-analysis,we initially established miR-21,miR-31,let-7 and EGFR,P53,ITGA5,and PTEN.The KRAS and erbB4 lung cancer regulatory network provides a theoretical basis for the individual treatment of lung cancer. |
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