ABSTRACT
Objective:To analyze and screen microRNA (miRNA) related to the prognosis of gastric cancer(GC) by bioinformatics analysis, and to construct and validate a risk score model.Methods:The human genome miRNA sequencing data and corresponding clinicopathological data of the 491 samples (446 GC tissue samples and 45 normal gastric tissue samples) were downloaded from the cancer genome atlas (TCGA) database. The differentially expressed microRNA (DEM) was analyzed with edgeR package of R 4.0.2 software and the obtained DEM’s profile was randomly divided into training set and test set according to the ratio of 1∶1. The miRNA related to prognosis were analyzed and screened with univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression analysis was further performed to analyze the screened prognostic-related miRNA and then the prognostic risk score model was constructed. Kaplan-Meier curve, receiver operating characteristic curve (ROC), and dynamic area under the ROC were drawn to evaluate the predictive power of the model.Results:A total of 175 DEM in GC tissues were screened out based on the cut-off criteria of |log2 Fold Change|>1.5 and P<0.01. Six DEMs related to the overall survival rate of patients with GC were screened out by univariate Cox regression and LASSO regression analysis, and then a five-miRNA risk score model was successfully constructed by multivariate Cox regression. The risk score=0.183×hsa-miRNA-184+ 0.086×hsa-miRNA-675-0.231×hsa-miRNA-2115+ 0.548×hsa-miRNA-3943-1.455×hsa-miRNA-1246. In the training set, test set and overall data set, the cumulative survival rates of the patients with higher risk score were lower than those of the patients with lower risk score, respectively, and the differences were statistically significant ( χ2=18.90, 9.50 and 26.70, all P<0.05). The prediction power of the model was better than that of TNM stage. And the results of stratified analysis showed the predictive ability of the model in patients with early GC. The results of univariate Cox regression and multivariate Cox regression demonstrated that the risk score of the model, gae and M stage were independent risk factors for poor prognosis in patients with GC (hazard ratio(95% confidence interval)1.19(1.07 to 1.32), 1.20(1.06 to 1.40), 1.50(1.01 to 2.23), 1.90(1.28 to 2.90), 1.34(1.15 to 1.57), 2.10(1.05 to 4.40); all P<0.05). Conclusion:The 5-miRNA risk score model based on 5 miRNAs which was an independent prognostic factor had high accuracy in predicting the prognosis of patients with GC.
ABSTRACT
Objective To investigate the clinical value of glypican-3 (GPC3) in the diaganosis of hepatocellular carcinoma (HCC),the contents of GPC3 in the serum and tissues of HCC patients were detected.Methods ELISA and immunohistochemical staining were applied to detect GPC3 expressing level in the serum and tissues in 79 cases with HCC,35 cases with post-hepatitis cirrhosis and 30 normal liver specimens and the resuits were compared.The influential factor of GPC3 content in the patients with HCC was analyzed by logistic regression model.Results The serum level of GPC3 in patients with HCC was (143.02±40.26) μg/L which was signifcantly higher than that in patients with post-hepatitis cirrhosis [(6.15±4.31) μg/L] and healthy controls [(4.47±3.22) μg/L] (all P ＜ 0.01).The expression levels of GPC3 was signifeantly higher in post-hepatitis cirrhosis tumor-adjacent tissue and tumor-distant tissue.The expression levels of GPC3 was significantly positively correlated with tumor presence of distant mestasis (x2 =13.182,P ＜ 0.0) and clinical stage (x2 =4.250,P ＜ 0.05),and not correlated with sex,age,tumor size and the level of AFP inserum (P ＜ 0.01).Conclusion GPC3 is specific the diagnosis of HCC.The joint diagnosis of GPC3 and AFP will improve the sensitivity of HCC.Therefore,GPC3 could as a biomarker for evaluating HCC condition and prognsis.