Construction Of Prognosis Model Of Renal Clear Cell Carcinoma Based On Hypoxia-related LncRNAs And Exploration Of Its Molecular Mechanism

CHAPTER 1 AN EFFECTIVE HYPOXIA-RELATED LONG NON-CODING RNAS ASSESSMENT MODEL FOR PROGNOSIS OF CLEAR CELL RENAL CARCINOMAObjective:Hypoxia is a significant clinical feature and regulates various tumor processes in clear cell renal carcinoma（cc RCC）.Increasing evidence has demonstrated that long non-coding RNAs（lnc RNAs）are closely related to the survival outcomes of cc RCC patients and regulate hypoxia-induced tumor processes.Thus,this study aimed to develop a hypoxia-related lnc RNA（HRL）prognostic model for predicting the survival outcomes in cc RCC.In addition,the role of lnc RNAs included in the prognostic model was explored by experiments in vivo and in vitro.Methods:1.Screening of HRL in cc RCC.The transcriptome data of cc RCC were downloaded from TCGA database.The protein-coding genes and lnc RNAs were further extracted according to their Ensembl IDs.The differentially expressed lnc RNAs between cc RCC and normal renal tissue were screened out for subsequent analysis.Hypoxia-related genes were obtained from the molecular signatures database.Co-expression analysis was performed between differentially expressed lnc RNAs and hypoxia-related genes in cc RCC samples to determine HRL.2.Construction of HRL prognostic model for cc RCC.Patients with cc RCC were randomly divided into one training dataset and three validation datasets.Univariate Cox regression analyses were used to extract the hypoxia survival-associated lnc RNAs.A Cox proportional hazards model with a lasso penalty analysis was used to construct the HRL model with the optimal prognostic value.The risk score of each sample was calculated based on the regression coefficients from the model and lnc RNAs’expression.The formula is below:Risk score（patient）=（?）（coef×exp）3.Validation of hypoxia-related lnc RNA model.In the validation sets,the prognostic evaluation model was used to calculate the risk score of each sample.According to the risk score,cc RCC samples were divided into high and low risk groups.The prognostic prediction value was evaluated by ROC curve and Kaplan Meier curve.4.Clinical application of HRL model.The correlations between risk score and clinicopathologic parameters were analyzed.The risk score and clinical characteristics of patients were analyzed in independent prognostic analysis.The independent prognostic factors affecting the overall survival of cc RCC patients were screened,and nomograms were constructed to predict the 1,2 and 3-year survival of patients.The relationship between risk score and tumor immune microenvironment was analyzed in cc RCC samples.Results:1.The differentially expressed lnc RNAs in cc RCC were screened out.137 hypoxia-related genes were downloaded from the molecular signatures database.A total of 598 HRL were obtained by co-expression analysis between differentially expressed lnc RNAs and hypoxia-related genes.2.Patients with cc RCC were randomly divided into a training set（n=255）,1^sttraining set（n=252）,2^ndtraining set（n=153）,and 3^rdtraining set（n=354）.In the training set,598 HRL were analyzed the correlation to overall survival.163 survival-related HRL were screened out.After screening the variables by lasso regression,the multivariate Cox proportional hazards regression model was included to construct the prognosis prediction model including 9 HRLs（ITPR1-DT,AC008760.2,AC084876.1,AC002070.1,LINC02027,AC147651.1,FOXD2-AS1,LINC00944,LINC01615）.3.In the training set,the model is applied to calculate the risk score of each sample,and the median risk score was used to divided cc RCC samples into high and low risk groups.The risk score performs well in predicting the overall survival of cc RCC patients,and the validation results are consistent with the validation set.4.The risk score is related to tumor grade,tumor stage,and tumor immune cell infiltration in cc RCC patients.The risk value,patient age,tumor stage and grade are independent prognostic factors of cc RCC patients.The independent prognostic factors were used to construct a nomogram,which can effectively predict the 1,2,3-year survival rate.Conclusion:This study showed that HRL prognostic model can effectively predict the prognosis of cc RCC patients.In addition,the nine hypoxia-related lnc RNAs in this model may be effective targets for studying the occurrence and development of cc RCC.CHAPTER 2 LONG NON-CODING RNA FOXD2-AS1 PROMOTE THE MALIGNANT BEHAVIORS OF RENAL CLEAR CELL CARCINOMA BY REGULATION OF MIR-206/VEGFA AXISObjective:Based on the first chapter,we further explored the function and mechanism of FOXD2-AS1 which included in HRL prognostic model in cc RCC.Methods:1.Firstly,the GEPIA software was used to analyze the expression of FOXD2-AS1 in cc RCC and normal kidney tissues,and the relationship between the expression of FOXD2-AS1 and overall survival.2.To observe the differential expression and biological behavior of FOXD2-AS1 in cc RCC cells.The expression of FOXD2-AS1 in cc RCC cell line was detected by reverse transcription real-time fluorescence quantitative PCR（q RT-PCR）.Lentivirus was transfected into cc RCC cells to construct sh-FOXD2-AS1 and FOXD2-AS1 overexpression cc RCC cell lines.CCK-8,EDU,colony formation and transwell assays were performed to explore the function of FOXD2-AS1 on the proliferation,migration and invasion of cc RCC cells.Subcutaneous injection with sh-FOXD2-AS1cc RCC cells and sh-NC cc RCC cells to nude mice to explore the effect of FOXD2-AS1 on tumor growth.3.To explore the molecular biological mechanism of FOXD2-AS1 in cc RCC,we constructed FOXD2-AS1 interference and overexpression plasmid transfected cc RCC cell lines.The competitive binding relationship between FOXD2-AS1 and mi R-206 was verified by dual luciferase reporter assay.4.The competitive binding relationship between mi R-206 and VEGFA was detected by dual luciferase reporter assay.The expression of VEGFA in FOXD2-AS1 interference and overexpression plasmid transfected cc RCC cell lines was detected by western blot.After overexpression of FOXD2-AS1 and co-transfection of mi R-206 mimics,the expression of VEGFA was detected by western blot,and the proliferation,migration and invasion function of cc RCC cells were detected by CCK-8,colony formation,transwell migration and invasion assays.Results:1.The GEPIA software showed that FOXD2-AS1 was highly expressed in cc RCC and was closely related to the poor prognosis of cc RCC patients.2.The expression of FOXD2-AS1 in cc RCC cell lines was higher than that in human renal cortical convoluted tubular cell line HK-2 by q RT-PCR.The proliferation,migration and invasion ability of sh-FOXD2-AS1 cells was significantly inhibited in vitro.The proliferation,migration and invasion ability of overexpression FOXD2-AS1 cells was significantly promoted in vitro.Knock down of FOXD2-AS1 inhibited the tumor growth of cc RCC in vivo.3.The dual luciferase reporter assay confirmed the competitive binding relationship between FOXD2-AS1 and mi R-206.4.Western blot showed the positive correlation between the expression of FOXD2-AS1 and the expression of VEGFA.The dual luciferase reporter assay confirmed the binding competitive relationship between mi R-206 and VEGFA.After overexpression of FOXD2-AS1 and co-transfected of mi R-206 mimics,the enhanced effect of FOXD2-AS1 on VEGFA expression and the proliferation function of cc RCC cells can be eliminated by mi R-206 mimics.Conclusion:The present study showed that FOXD2-AS1 can regulate the expression of VEGFA via competitively binding mi R206 in cc RCC cells,and promote the proliferation,migration and invasion of cc RCC cells.