Objective:To establish a prognostic prediction model for hepatocellular carcinoma (HCC) using bioinformatics approaches to guide personalized therapy.Methods:Based on bioinformatics, the differential analysis was carried out on the GSE19665 data set of The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) and Gene Expression Omnibus (GEO), and the same differentially expressed genes were obtained by means of Wayne diagram. Functional enrichment analyses using Gene Ontology, Kyoto Encyclopedia of Genes and Genome, and Gene Set Enrichment Analysis were conducted on co-expressed genes. Based on clinicopathological and transcriptomic profiles, TCGA-LIHC patients were stratified into training ( n=246) and internal validation ( n=116) cohorts, with external validation using Japanese liver cancer data ( n=231) from the International Cancer Genome Consortium. A LASSO-Cox regression-derived risk scoring model was established and visualized as a nomogram. The clinical utility of the risk score was evaluated through multiple analytical approaches.A nomogram incorporating the risk score was developed, and its predictive performance was validated using the concordance index (C-index) and calibration curves. The measurement data of normal distribution were expressed as mean±standard deviation( ± s), and the t-test was used for comparison between groups. The measurement data with non-normal distribution were expressed as M( Q1, Q3), and the Wilcoxon test was used for comparison between groups. The Kruskal-Wallis test was applied to evaluate the significance of the differences among multiple groups. The prognostic value of the risk score was estimated using Kaplan-Meier analysis and ROC curve. Multivariate Cox regression clarified the independent prognostic value of the risk score. Results:Differential analysis identified 457 commonly expressed differentially expressed genes (DEGs). Enrichment analysis revealed that these common DEGs were significantly enriched in pathways related to the cell cycle of tumor cells.The LASSO-Cox regression model selected eight candidate genes ( CENPA, NDC80, ANXA10, NEIL3, G6 PD, MCM10, SOCS2, MMP1). The predictive risk score generated using these eight genes demonstrated a strong association with the overall survival of HCC patients.The nomogram combining the predictive risk score with clinicopathological features exhibited high predictive performance in both the training and validation cohorts. Furthermore, the prognostic value of this risk score was successfully validated in the external validation cohort. Conclusion:This study successfully developed a new predictive model that accurately predicts the 1-year, 3-year and 5-year survival rates of patients with liver cancer. This can serve as a potential tool to help guide patients in personalized treatment.

Objective:To study the predictive role of tumor burden score (TBS) for tumor recurrence after radical resection in patients with hepatocellular carcinoma (HCC).Methods:Clinical data of 202 patients with HCC undergoing radical surgery at the 900th Hospital of Joint Logistics Support Force of the Chinese People's Liberation Army, between January 2015 and December 2017 were retrospectively analyzed, including 128 males and 74 females, aged (53.66±11.93) years old. The receiver operating characteristic (ROC) curve was used to assess the accuracy of TBS in predicting postoperative tumor recurrence. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors influencing postoperative tumor recurrence. A nomogram was established and validated using calibration curves and the C-index. Kaplan-Meier survival analysis was utilized to compare survival differences between the two patient groups.Results:The area under the ROC curve for TBS in predicting postoperative tumor recurrence in HCC patients was 0.779 (95% CI: 0.717-0.842), with an optimal cutoff value of 6.2. Univariate analysis revealed that factors such as hepatitis B virus DNA level >500 IU/ml, larger maximum tumor dia-meter, and TBS>6.2 were significant risk factors for postoperative tumor recurrence (all P<0.05). Multivariate analysis further indicated that TBS>6.2 ( OR=3.60, 95% CI: 1.081-12.012, P=0.037) and maximum tumor diameter ( OR=1.240, 95% CI: 1.034-1.487, P=0.020) were independent risk factors for postoperative recurrence. Based on these risk factors, a nomogram model was established, achieving a C-index of 0.788. Kaplan-Meier survival analysis showed a better postoperative overall survival and recurrence-free survival of the low TBS group compared to those of the high TBS group (all P<0.05). Conclusion:TBS can serve as a predictive indicator for the recurrence after radical resection in patients with HCC. Both TBS and tumor size are independent risk factors for postoperative recurrence. The nomogram model can be used for predicting recurrence following radical resection in HCC patients.

AIM:To explore the effects of galectin-3 (GAL-3) on the viability, migration and inflammation of human umbilical vein endothelial cells (HUVECs) and the mechanisms.METHODS:The HUVECs were cultured in vitro and treated with GAL-3 recombinant protein at 2 mg/L or GAL-3 short hairpin RNA (shRNA).The HUVECs were divided into normal group, recombinant GAL-3 group, shControl group and GAL-3-shRNA group.The mRNA expression of GAL-3, monocyte chemotactic protein (MCP)-1, IL-6, matrix metalloproteinase (MMP)-9 and cyclin D1 was detected by real-time quantitative PCR,and the protein expression of GAL-3, IL-6 and MCP-1 was detected by Western blot.The secretion levels of MCP-1 and IL-6 in the culture medium were measured by ELISA.The viability and the ability of migration of the HUVECs were examined by CCK-8 assay and wound healing assay.The protein levels of heat shock protein 90 (HSP90), ERK1/2, p-ERK1/2, JNK and p-JNK were determined by Western blot.RESULTS:The expression of GAL-3, MCP-1 and IL-6 at mRNA and protein levels, the mRNA expression of MMP-9 and cyclin D1, and the secretion levels of MCP-1 and IL-6 in the culture medium were significantly higher than those in normal group (P<0.05) after the HUVECs were treated with GAL-3 recombinant protein.However, these molecules mentioned above in GAL-3-shRNA group were significantly lower than those in normal group and negative control group (P<0.05).Compared with normal group, the viability and migration ability of the HUVECs in recombinant GAL-3 group were significantly increased, but the viability and migration ability of the HUVECs in GAL-3-shRNA group were lower than those in normal group and shControl group (P<0.05).In addition, the protein levels of p-ERK1/2 and HSP90 in recombinant GAL-3 group were higher than those in normal group (P<0.05), but those in GAL-3-shRNA group were lower than those in normal group and shControl group (P<0.05).The protein level of p-JNK was not oviously changed among the 4 groups.CONCLUSION:GAL-3 is involved in regulating the cell growth, migration and the release of inflammatory cytokines in vascular endothelial cells, which may be mediated by HSP90-ERK1/2 signaling pathway.