Establishment Of A Molecular Risk Model For The Prognosis Of Cervical Cancer Based On MicroRNA Expression

Background:Cervical cancer(CC)is the first tumor of the female reproductive system in the word with the highest incidence.A number of studies have shown that the expression level of miRNA is highly correlated with the treatment and diagnosis of cancer patients.This study was to establish a molecular prognostic model of CC based on miRNAs and improve the individualized treatment of CC patients.Methods:Human CC tissues and adjacent normal cervical tissues were selected from the specimen database of the Cancer Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College,for miRNA gene sequencing.CC transcriptome expression data and clinical data were downloaded from TCGA.Distinguishing the common differentially expressed miRNAs of CC miRNA-seq and TCGA-CC.R package was used to perform univariate Cox proportional hazard regression and lasso cox regression for common differentially expressed miRNAs to obtain a molecular prognostic model.Next,the model performance was evaluated using survival analysis,ROC analysis,univariate and multivariate analysis in the TCGA-CC dataset.Tissues and cells were used for qPCR detection to verify the expression changes of miRNA.Transwell was used to verify the role of molecules in CC cell migration and invasion.Results:39 miRNAs were distinguished in TCGA-CC and CC miRNA-seq,lasso regression analysis to obtained the risk model(risk score=-0.310 X expression of hsamiR-142-3p+0.439×expression of hsa-miR-100-3p).The survival analysis,ROC analysis,patient risk assessment,univariate and multivariate analysis showed that risk score model had good predictive ability in assessing patient survival(P<0.01),risk of death and independent prognosis(P<0.01).qPCR detection of clinical samples and cells showed that the expression of hsa-miR-142-3p and hsa-miR-100-3p was consistent with the results of database analysis.Results of transwell indicated that miR-142-3p played an inhibiting factor and miR-100-3p played and promoting factor in CC cell migration and invasion.Conclusion:A prognostic risk model based on miR-142-3p and miR-100-3p can predict the prognosis of CC.miR-142-3p may play an oncogenic role in cervical carcinogenesis and miR-100-3p may play a pro-cancer role in cervical cancer development.miR-142-3p and miR-100-3p in the models are potential biomarkers and candidate drug therapeutic targets in cervical cancer.