Identification Of Prognostic Four-mRNA Signature Model In Intrahepatic Cholangiocarcinoma Based On TCGA Database

Objective:Intrahapetic cholangiocinoma(ICC),characterised by non-specific symptoms in early stage,has high degree of malignancy and ineffective treatment result.At present,there is still a lack of effective methods for the diagnosis and prognosis of intrahepatic cholangiocinoma.In order to improve the accuracy of clinical prognosis for patients with intrahepatic cholangiocarcinoma,this study intends to construct a risk prognostic model based on transcriptome data of ICC through TCGA database.Methods:Transcriptome data and clinical data of ICC were downloaded through TCGA and were further integrated;differentially expressed genes(DEGs)between tumor and normal tissues were obtained by using 3 differential analysis methods,edgeR,Limma and DESeq2 according to p<0.05 and |log2 FC|>2;the DEGs expression data were further analysised by Univariate COX Regression Analysis,Lasso Regression Analysis and Multivariate COX Regression Analysis,in order to obtain the independent prognostic factors of ICC;based on the regression coefficients of multivariate COX analysis,the risk score of each sample were calculated,and a prognosis model were constructed;ROC curve,C index and kaplan-Meier survival curve were used to evaluated the accuracy of the model;differential gene analysis and immune microenvironment evaluation by ssGSEA were finally implemented according to different risk groups.Results:The ICC transcriptome data downloaded from TCGA were sorted to obtain an expression matrix of 29,696 genes.After three differential analysis methods,3355 differentially expressed genes(DEGs)were obtained.Univariate COX Regression Analysis selects 9 genes(p<0.01).Lasso Regression Analysis filters the collinearity factors,and obtains 7 candidate genes for Multivariate COX Regression Analysis.Finally,4 mRNAs are obtained,and the risk score is calculated according to the regression coefficient.The median value of the risk score is used as the boundary to divide the sample into high and low risks and construct a prognostic model;the time-dependent ROC curve shows that the area under the curve(AUC)of the patient’s 3-year and 5-year survival rate are 0.819 and 0.928;the C index of the overall model is 0.929;differential genes analysis and functional enrichment between the high-risk and low-risk groups showed that the prognostic of ICC was related to the functions of immune cells,the ssGSEA analysis evaluating the immune microenvironment found that the expression of memory B cells in the high-risk group was significantly increased.Conclusion:In this study,a prognostic risk model containing 4 mRNAs was constructed based on TCGA data.The accuracy of the the prediction of prognostic of patients with ICC is relatively high,which can provide a reference for clinicians to evaluate the prognosis of patients.