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Background: Hepatocellular carcinoma (HCC) is a high mortality disease, the fifth most general cancer worldwide, and the second leading to cancer-related deaths, with more than 500,000 new patients diagnosed each year. First, the high expression of centromere M (CENPM) in mammary gland tissue of b-catenin transformed mice was identified. Materials and methods: In our study, we evaluated the expression of CENPM in hepatocellular carcinoma based on data obtained from an online database. Multivariate analysis showed that the expression of CENPM and M classification was an independent prognostic factor for patients with hepatocellular carcinoma. Results: Survival analysis showed that patients with high CENPM had a worse prognosis than patients with low CENPM (P < 0.01). A multivariate Cox regression hazard model showed that B cells, CD8+ T cells, macrophages, and dendritic cells infiltrated by immune cells were statistically significant in liver cancer (P < 0.05). Using the network, the 50 most frequently changed neighbor genes of CENPM were shown, and the most common change was RAD21 (18.3%). Conclusion: Our study found that the expression of CENPM was significantly increased in patients with hepatocellular carcinoma, and it was related to a variety of clinical characteristics, its correlation with the level of immune infiltration and poor prognosis, so CENPM can be used as a useful prognosis for patients’ markers and HCC. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC), is the fifth most common cancer in the world and the second most common cause of cancer-related deaths. Over 500,000 new HCC cases are diagnosed each year. Combining advanced genomic analysis with proteomic characterization not only has great potential in the discovery of useful biomarkers but also drives the development of new diagnostic methods.Methods: This study obtained proteomic data from Clinical Proteomic Tumor Analysis Consortium (CPTAC) and validated in The Cancer Proteome Atlas (TCPA) and TCGA dataset to identify HCC biomarkers and the dysfunctional of proteogenomics.Results: The CPTAC database contained data for 159 patients diagnosed with Hepatitis-B related HCC and 422 differentially expressed proteins (112 upregulated and 310 downregulated proteins). Restricting our analysis to the intersection in survival-related proteins between CPTAC and TCPA database revealed four coverage survival-related proteins including PCNA, MSH6, CDK1, and ASNS.Conclusion: This study established a novel protein signature for HCC prognosis prediction using data retrieved from online databases. However, the signatures need to be verified using independent cohorts and functional experiments. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC), one of the most common malignant tumors worldwide, ranks as the fifth most common cancer and has been the second most frequent cause of cancer-related death. RNA binding proteins (RBPs) are proteins that interact with different classes of RNA and are commonly detected in cells.Methods: We used RNA sequencing data from TCGA to display dysfunctional RBPs microenvironments and provide potential useful biomarkers for HCC diagnosis and prognosis.Results: 330 differently expressed RBPs (208 upregulated and 122 downregulated) were identified. KEGG were mainly enriched in RNA degradation, Influenza A, Hepatitis C, RIG-I-like receptor signaling pathway, Herpes simplex virus 1 infection and RNA transport. CBioPortal results demonstrated that these genes were altered in 50 samples out of 357 HCC patients (14%) and the amplification of BRCA1 was the largest frequent copy-number alteration.Conclusion: Based on the online database, we identified novel RBPs markers for the prognosis of hepatocellular carcinoma. [ABSTRACT FROM AUTHOR]

Background: Hexokinase-2 (HK2) and Beta2-adrenergic receptor (Beta2AR) are overexpressed in hepatocellular carcinoma (HCC) tissues and associated with poor prognosis. However, the synergistic effect of HK2 and Beta2AR in HCC prognosis is not elucidated. The present study aims to investigate the association between HK2 and Beta2AR expressions in HCC tissues, and to evaluate the synergistic effect of HK2 and Beta2AR in HCC prognosis.Methods: Immunohistochemistry of HK2 and Beta2AR was performed on 155 paraffin embedded HCC samples retrieved from the archives of pathology department. Corresponding clinical data and prognostic data were collected through searching medical record systems, death registration systems and interviews with patient families. Spearman correlation test was performed to evaluate the association between HK2 and Beta2AR expression. Kaplan-Meier survival curves and Cox regressions were employed to evaluate HK2 and Beta2AR expression in HCC prognosis, respectively and synergistically.Results: 109 of 155 HCC patients reached the death point, the survival time of HCC patients was 46.23 ± 31.01 months after curative surgical resections of HCC. Kaplan-Meier survival analysis showed that large tumor size (more than 5 cm) (hazard ratio (HR) = 8.42, 95 % confidence interval (CI) = 3.81-18.59, P < 0.0001), advanced TNM stage (III and IV stages) (HR = 2.09, 95%CI = 1.21-3.62, P < 0.001) and AFP more than 20 μg/L (HR = 1.49, 95%CI = 1.02-2.18, P = 0.0302) were predictors for poor prognosis. HK2 and Beta2AR positive expression was detected in 66 (42.58) and 122 (78.71 %) HCC samples respectively. In univariate analysis, HK2(+) (HR = 2.70, 95%CI = 1.76-4.15, P < 0.0001) and Beta2AR(+) (HR = 4.61, 96%CI = 3.14-6.76, P < 0.0001) were associated with poor prognosis. In multivariate analysis, HK2(+) (P < 0.0001) and Beta2AR(+) (P < 0.0001) were also associated with poor prognosis. HK2(+)/Beta2AR(+) in HCC samples had poorer prognosis compared with HK2(-)/Beta2AR(-) in both univariate analysis (HR = 4.69, 95%CI = 2.91-7.57, P < 0.0001) and multivariate analysis (P < 0.0001). HK2(+)/Beta2AR(+) in HCC samples had poorer prognosis compared with HK2(-)/Beta2AR(+) in both univariate analysis (HR = 1.76, 95%CI = 1.17-2.64, P = 0.003) and multivariate analysis (P = 0.004).Conclusion: HK2 and Beta2AR play important roles in HCC progression. HK2 and Beta2AR expression in HCC is correlated positively. Beta2AR may increase HCC invasion and metastasis in collaboration with HK2. HK2 and Beta2AR can predict HCC prognosis both independently and synergistically. [ABSTRACT FROM AUTHOR]