No abstract

Disc large associated protein 4 (DLGAP4) plays an important role in neurological diseases, but the role and mechanism of DLGAP4 in hepatocellular carcinoma (HCC) remain unclear. In this study, the prognostic effect of DLGAP4 on HCC patients was investigated by means of bioinformatics. The correlation of DLGAP4 expression with the prognosis of HCC patients was evaluated by TCGA data analysis, and the correlation between DLGAP4 expression and the clinical characteristics of HCC patients was evaluated by the Wilcoxon signed rank test and logistic regression analysis. Kaplan‒Meier and Cox regression methods were used to assess the effect of DLGAP4 expression level on overall survival, and nomograms were used to illustrate the correlation between DLGAP4 gene expression and HCC risk. The genes related to DLGAP4 in HCC were screened, and GO/KEGG enrichment analysis was performed. Furthermore, in vitro and in vivo experiments were conducted to detect the effect of DLGAP4 expression on the proliferation, migration and metastasis of HCC cells. We also examined the effect of DLGAP4 expression on enriched pathway proteins to explore the possible mechanism. The expression levels of DLGAP4 were significantly higher in HCC cell lines and tissue samples than in normal liver cell lines and tissues. The expression of DLGAP4 was significantly associated with clinical characteristics. Survival analysis showed that high expression of DLGAP4 was associated with a poor prognosis in HCC. Multivariate analysis showed that high expression of DLGAP4 was an independent risk factor affecting the overall survival rate in HCC patients. By means of ROC curve analysis and nomograms, we determined the value of DLGAP4 expression in the diagnosis and prognosis evaluation of HCC. GO/KEGG enrichment analysis showed that the PPAR signalling pathway was differentially enriched in patients with high expression of DLGAP4. According to in vitro and in vivo experiments, DLGAP4 knockdown inhibited the proliferation and metastasis of HCC cells and decreased the expression of PPARβ/δ protein. In contrast, overexpression of DLGAP4 promoted the proliferation and metastasis of HCC cell, and increased the expression of PPARβ/δ protein.In contrast, overexpression of DLGAP4 promoted the proliferation and metastasis of HCC cells and increased the expression of PPARβ/δ protein. The results show a close correlation between DLGAP4 expression and clinicopathological features of HCC, and DLGAP4 can be used as a prediction biomarker of HCC.

Objective: Ficolin (FCN) family proteins are part of the innate immune system, play a role as recognition molecules in the complement system, and are associated with tumor development. The mechanism of its role in immunotherapy of hepatocellular carcinoma (HCC) is unclear.Methods: In this study, we used the TCGA database, HPA database, Gene Expression Profile Interaction Analysis (GEPIA), Kaplan-Meier plotter, TCGAportal, cBioPortal, GeneMANIA, TIMER, and TISIDB to analyze Ficolin family proteins (FCN1, FCN2 and FCN3, FCNs) in patients with hepatocellular carcinoma for differential expression, prognostic value, genetic alterations, functional enrichment, and immune factor correlation analysis.Results: The expression levels of FCN1/2/3 were significantly reduced in patients with HCC. Among them, FCN3 showed significant correlation with Overall Survival (OS), Progressive Free Survival (PFS) and Relapse Free Survival (RFS) in HCC. FCN1 and FCN3 may be potential prognostic markers for survival in patients with HCC. In addition, the functions of differentially expressed FCNs were mainly related to complement activation, immune response, apoptotic cell clearance and phagocytosis. FCNs were found to be significantly correlated with multiple immune cells and immune factors. Expression of FCN1 and FCN3 differed significantly in the immune and stromal cell component scores of HCC. analysis of the tumor mutation burden (TMB) and microsatellite instability (MSI) of FCNs with pan-cancer showed that FCN3 was significantly correlated with both.Conclusions: Our study provides new insights into the link between the FCN family and immunotherapy for HCC, and FCN3 may serve as a prognostic biomarker for HCC.

Studies have revealed the contribution of ATP-G protein-coupled P2Y2 receptor (P2RY2) in tumor progression, but the role of P2RY2 in regulating the progression of gastric cancer (GC) and related molecular mechanisms are relatively lacking. Therefore, this study investigates the effects of P2RY2 on the proliferation and migration of GC through in vivo and in vitro experiments. The results showed that P2RY2 was expressed in GC tissues and GC cell lines. ATP increased the calcium influx in AGS and HGC-27 cells, and was dose-dependent with ATP concentration. ATP and UTP increased the intracellular glycogen content, enhanced the actin fiber stress response, and promoted the proliferation and migration of GC cells, while P2RY2 competitive antagonist AR-C118925XX reversed the changes induced by ATP. Knockdown of P2RY2 expression by shRNA inhibited the proliferation of GC cells. Activation of P2RY2 increased the expression of Snail, Vimentin and β-catenin in GC cells, and down-regulated the expression of E-cadherin, while AR-C118925XX decreased the expression of these genes induced by ATP. Activation of P2RY2 activated AKT/GSK-3beta/VEGF signal to promote the proliferation of GC cells, and the P13/AKT signaling pathway LY294002 reversed the corresponding phenomenon, but no synergistic pharmacological properties of AR-C118925XX and LY294002 have been found. In vivo experiments showed that ATP induced tumor growth, while AR-C118925XX inhibited ATP-induced tumor growth. Our conclusion is that P2RY2 activated the AKT/GSK-3beta/VEGF signal to promote the proliferation and migration of GC, suggesting that P2RY2 may be a new potential target for the treatment of GC.

Objective Hepatocellular carcinoma (HCC) immunotherapy is a focus of current research. We established a model that can effectively predict the prognosis and efficacy of HCC immunotherapy by analyzing the immune genes of HCC. Methods Through the data mining of hepatocellular carcinoma in The Cancer Genome Atlas (TCGA), the immune genes with differences in tumor and normal tissues are screened, and then the univariate regression analysis is carried out to screen the immune genes with differences related to prognosis. The prognosis model of immune related genes is constructed by using the minimum absolute contraction and selection operator (lasso) Cox regression model in the TCGA training set data, The risk score of each sample was calculated, and the survival was compared with the Kaplan Meier curve and the receiver operating characteristic (ROC) curve to evaluate the predictive ability. Data sets from ICGC and TCGA were used to verify the reliability of signatures. The correlation between clinicopathological features, immune infiltration, immune escape and risk score was analyzed. Results Seven immune genes were finally determined as the prognostic model of liver cancer. According to these 7 genes, the samples were divided into the high and low risk groups, and the results suggested that the high-risk group had a poorer prognosis, lower risk of immune escape, and better immunotherapy effect. In addition, the expression of TP53 and MSI was positively correlated in the high-risk group. Consensus clustering was performed to identify two main molecular subtypes (named clusters 1 and 2) based on the signature. It was found that compared with cluster 1, better survival outcome was observed in cluster 2. Conclusion Signature construction and molecular subtype identification of immune-related genes could be used to predict the prognosis of HCC, which may provide a specific reference for the development of novel biomarkers for HCC immunotherapy.