| Part Ⅰ: IntroductionOral squamous cell carcinoma(OSCC)is one of the most common malignancies in the world.Currently,the main treatment methods are surgery and chemotherapy,but the 5-year survival rate after diagnosis still low.Therefore,searching for new diagnostic and prognostic markers and exploring the molecular mechanism of OSCC occurrence and development can improve the early diagnosis rate and survival rate of OSCC.Previous literature reported that cervical lymph node metastasis and invasion in OSCC patients were associated with multiple molecular signaling pathways,which were key factors affecting the prognosis of OSCC patients.In this study,bioinformatics such as WGCNA were used to screen key pathways and hub genes related to clinical traits of OSCC,and to further explore the influence of key pathway genes on OSCC survival rate,pathological stage,migration and clarity.Further,we analyzed the relationship between the expressions of β-catenin,a protein related to migration and invasion,and clinical traits in Chinese OSCC patients.We used integrative omics to find a novel association protein related to β-catenin pathway,RUVBL1,which is also related to OSCC survival,migration and invasion.We are also studying the correlation between RUVBL1 and OSCC survival and pathological staging at the molecular,cellular and clinical specimen levels,to prove whether it can become a new target for OSCC treatment and prognosis.Finally,based on immunohistochemical analysis of the expression of β-catenin pathway-related proteins in OSCC,a multivariate Cox regression model and nomogram were constructed to predict the survival and prognosis of OSCC patients.These studies may provide more effective treatment options for OSCC patients and improve the survival rate.Part Ⅱ Weighted gene co-expression network mining key gene modules,signaling pathways and hub genes in OSCCObjective: To mine the key gene modules,signaling pathways and hub genes of OSCC by the weighted gene co-expression network(WGCNA).Methods: 1.Download the TCGA-HNSC expression matrix and related information from the public database to reconstruct the TCGA-OSCC dataset;2.Use WGCNA to screen key modular genes that are highly correlated with clinical traits;3.Build a modular gene interaction network and annotate the signaling pathways of genes in the network;4.Screen survival genes for OSCC based on the constructed gene interaction network combining with gene expression status.Results: 1.Based on the reconstructed TCGA-OSCC dataset and the corresponding clinical information,two modules,MEgreen and MEyellowgreen,related to survival status and grade were obtained by WGCNA analysis;2.KEGG and Reactome pathway analysis showed that these genes in two modules were enriched in multiple tumor pathways,including MAPK,CTNNB1,PI3K-AKT,etc.;3.According to the analysis of gene expression and survival status,two key genes,MAPK3 and CTNNB1,were screened.Conclusion: WGCNA can be used to mine key oncogenes for OSCC,among which MAPK3 and CTNNB1 will be further researched.Part Ⅲ Correlation analysis of β-catenin expression and clinical features in OSCCObjective: To determine β-catenin expression and localization in OSCC and investigate the correlation between the expressions of β-catenin and clinical features such as prognosis.Methods: 1.By analyzing the expression of β-catenin in public database GEO and human atlas protein(HPA),the expression of β-catenin was determined in OSCC patients in different populations and regions and its correlation with survival status;2.The expression of β-catenin in 40 OSCC patients were detected by immunohistochemistry;3.Analysis the correlation between expression of β-catenin and nuclear translocation with the prognosis of OSCC patients.Results: 1 The results of public data analysis show that there were significant differences in the expressions of β-catenin among OSCC patients in different populations and regions;2.Chi-square test results show that the expression ofβ-catenin was closely related to OSCC tumor size,histological grade,TNM stage,survival status and lymph node metastasis(P < 0.05);3.HPA database also found the expression of β-catenin was correlated with overall survival(Log-rank P = 0.0135),and high expression of β-catenin was associated with poor prognosis;4.By analyzing the survival time of 40 samples and the corresponding expression levels of β-catenin using IHC,Kaplan-Meier curve showed high expression of β-catenin was associated with poor prognosis(Log-rank P = 0.0254).OSCC patients withβ-catenin nuclear translocation showed poor prognosis(Log-rank P = 0.0002).Conclusion: The expression of β-catenin and nuclear translocation may be biomarkers for the prognosis of OSCC.Part Ⅳ Screening and identification of key survival-related genes inβ-catenin pathway in OSCCObjective: To screen and identify novel key survival-associated genes inβ-catenin pathway in OSCC.Methods: 1.Using GEO dataset,GEPIA database,Networkanalyst online network,IMEx,STRING databases and Cytoscape to conduct visual analysis forβ-catenin-protein interaction network and key gene screening;2.Using Metascape and KEGG,Reactome pathway database for pathway annotation and analysis ofβ-catenin-related genes;3.Pearson correlation coefficient between β-catenin and related gene expression was analyzed using GPEIA database;4.The affects ofβ-catenin key genes on overall survival were analyzed using heatmap and Kaplan-Meier survival curve in GPEIA database;5.The expression level of RUVBL1 protein in tissue chips was detected by immunohistochemistry,and the correlation between expression and clinical characteristics was analyzed by chi-square test.Results: 1.14 key genes(node connectivity > 10)were screened out from the network construction of β-catenin interacting proteins;2.Signaling pathway enrichment analysis by KEGG,GO and Reactome functional annotation showed that these key genes of β-catenin pathway were enriched in cancer-related pathways,including important signaling pathways related to cell growth,survival and differentiation;3.Pearson correlation coefficient analysis showed that the expression of 12 genes was positively correlated with the expression of β-catenin;4.Overall survival heatmap results and Kaplan-Meier curves showed that DKK1 and RUVBL1 were the two key genes that had the most significant impact on the overall survival of patients.5.Immunohistochemical results of tissue microarray and chi-square test suggested that the expression of RUVBL1 was correlated with histopathological stage.Conclusion: A new key survival-associated gene RUVBL1 in the β-catenin pathway in OSCC was initially screened.Part Ⅴ Targeted inhibition of RUVBL1 inhibits the proliferation,metastasis and invasion of OSCC cell linesObjective: In order to investigate the effect of targeted inhibition of RUVBL1 on the proliferation,metastasis and invasion of OSCC cell lines.Methods: 1.After targeting RUVBL1 with si RNA and CB-6644,the growth and proliferation of OSCC cell lines H157 and Cal-27 cells were detected by CCK8 cytotoxicity assay and clone formation assay;2.After the inhibition of si RNA and CB-6644 targeting RUVBL1,the effects on the migration and invasion of OSCC cells were detected by healing wound assay and cell invasion assay;3.At the same time,the changes of β-catenin,RUVBL1 and other pathway-related proteins were detected by western blotting.Results: 1.After targeting RUVBL1 by si RNA and CB-6644,CCK8 assay showed that the proliferation of OSCC cell lines H157 and Cal-27 was significantly inhibited;2.Cell cloning experiments showed that RUVBL1 si RNA and CB-6644 significantly reduced the growth of H157 cells,and reduced the size of the clone;3.The cell healing wound migration assay showed that the RUVBL1 si RNA group could inhibit about 50% to 30% of the cell migration ability.At the same time,CB-6644 inhibited cell migration in a dose-dependent manner;4.Transwell cell invasion assay showed that both RUVBL1 si RNA and CB-6644 could reduce the number of cells passing through the transwell membrane;5.Western blot results showed that the targeted inhibition of RUVBL1 by si RNA and CB-6644 decreased the expression of RUVBL1,β-catenin and vimentin,and increased the expression of E-cadherinConclusion: RUVBL1 may promote OSCC cell proliferation,metastasis and invasion by participating in the activation of β-catenin pathway,and targeted inhibition of RUVBL1 can inhibit these effects.Part Ⅵ Construction of a survival prediction model for patients with OSCC based on key genes of β-catenin pathway such as RUVBL1Objective: Based on multiple β-catenin pathway-related key genes and clinical information,a multivariate Cox model was constructed to predict survival rate and nomogram for OSCC patients.Methods: 1.Tissue paraffin specimens from OSCC patients were collected from the hospital,and β-catenin,vimentin,RUVBL1,E-cadherin,DKK1 were analyzed by immunohistochemistry,and scored;2.Multivariate Cox regression model,stepwise regression and PCA to select the key genes and clinical factors that affect the survival rate;3.The four-factor Cox risk scoring model was evaluated by methods such as Concordance-index,ROC curve,and Calibration curve;4.In order to visually display the four-factor Cox risk scoring model,Construction of a visual and interactive nomogram model to predict OSCC patient survival.Results: 1.We used IHC to score the expression of five genes(Vimentin,RUVBL1,β-catenin,E-cadherin,DKK1),and constructed a multivariate Cox survival prediction model combined with three clinical traits of age,stage and grade;2.Stepwise regression and PCA found that the Cox regression model constructed only by four factors(Vimentin,RUVBL1,β-catenin expression and stage)can be used to predict OSCC survival status;3.Concordance-index,ROC curve,Calibration curve results show that there is no significant difference between the four-factor Cox risk scoring model and the eight-factor model;4.At the same time,based on the individual expression levels of these four markers and clinical characteristics,we constructed a risk scoring formula to calculate the risk score of each patient: risk score= 0.9127×Stage 1.0003×Vimentin 0.8855×RUVBL1 1.1293×β-catenin.5.At the same time,a visual and interactive nomogram model based on the four-variables Cox risk scoring model was successfully constructed to predict the survival rate of OSCC patients.Conclusion: Based on the expression of multiple β-catenin pathway key genes Vimentin,RUVBL1,β-catenin and clinical information stage,the multivariate Cox model was used to successfully construct the survival prediction model and interactive nomogram in OSCC patients. |
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