Bioinformatics Combined With Quantitative Proteomics Analyses And Identification Of Prognostic Biomarkers In Cholangiocarcinoma

Background & Aims: Cholangiocarcinoma(CCA)is an invasive malignancy arising from biliary epithelial cells;it is the most common primary tumour of the bile tract.Due to the difficulty in early diagnosis,the prognosis is extremely poor.In recent decades,many biomarkers of CCA have been widely used,but due to their own limitations,these biomarkers are still not enough to fully understand the mechanism of CCA and optimize treatment strategies.We need more effective methods to screen for more valuable biomarkers.The aim of this study was to screen the differentially expressed RNAs(DEGs)related to the prognosis of patients with CCA by bioinformatics analysis.And isobaric tags for relative and absolute quantification(iTRAQ)were used to explore the differentially expressed proteins(DEPs)between CCA and nontumour tissues.The potential biomarkers of CCA were further screened by integrated multiomics analysis.Methods: By searching in Gene Expression Omnibus(GEO)database,we selected and obtained the GSE32225 data set.By using R language to analyze the differential expression of m RNA in this data set,we obtained the DEGs between cancer and normal tissues.The correlation between these DEGs and the prognosis of patients with CCA was analysed using The Cancer Genome Atlas(TCGA)database,and the accuracy of the expression of DEGs related to the prognosis of CCA patients obtained from The GSE32225 data set was further verified using TCGA database.The DEPs between CCA and non-tumour tissues were identified and screened by using iTRAQ techniques.Through further comprehensive analysis of DEGs and DEPs related to prognosis,we obtained candidate proteins: Apolipoprotein F(APOF),Integrin Subunit Alpha V(ITGAV),and Calcium/ calmodule-dependent serine protein kinase(CASK),and immunohistochemistry was used to detect the expression of these proteins in CCA.The relationship between CASK expression and CCA prognosis was further analysed.Results: Through bioinformatics analysis,875 DEGs were identified,and survival analysis showed that 10 DEGs were related to the prognosis of the CCA patients.A total of 487 DEPs were identified by using the iTRAQ technique.Comprehensive analysis of multi-omics data showed that CASK,ITGAV and APOF expression at both the m RNA and protein levels were different in CCA compared with nontumour tissues.CASK was found to be expressed in the cytoplasm and nucleus of CCA cells in 38(45%)of 84 patients with CCA.Our results suggested that patients with positive CASK expression had significantly better overall survival(OS)and recurrence-free survival(RFS)than those with negative CASK expression.Univariate analysis showed that histological grade(P=0.019),stage(P=0.002),vascular invasion(P=0.001),and negative expression of CASK(P=0.012)were independent risk factors for poor overall survival in CCA patients.Histological grade(P=0.017),stage(P=0.035),and negative expression of CASK(P=0.006)were independent risk factors for RFS in CCA patients.The multivariate analysis showed that CASK negative expression(P=0.027)was an independent risk factor for poor prognosis among CCA patients.Histological grade(P=0.036),stage(P=0.035),and negative expression of CASK(P=0.014)were independent risk factors for RFS in CCA patients.Conclusions: In conclusion,our study revealed that CASK may be a tumor suppressor,and its negative expression is an independent risk factor for poor prognosis in CCA patients,which can be used as a prognostic marker with clinical value and may provide a new target for the treatment of CCA.Moreover,a reliable method was found for the screening of biomarkers for CCA,which may provide a comprehensive and systematic perspective for the in-depth study of the pathogenesis of CCA.