ABSTRACT
BACKGROUND: Testing for the presence of liver cirrhosis (LC) is one of the most critical diagnostic and prognostic assessments for patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). More non-invasive tools are needed to diagnose LC but the predictive abilities of current models are still inconclusive. This study aimed to develop and validate a novel and non-invasive artificial neural network (ANN) model for diagnosing LC in patients with HBV-related HCC using routine laboratory serological indicators. METHODS: A total of 1152 HBV-related HCC patients who underwent hepatectomy were included and randomly divided into the training set (n = 864, 75%) and validation set (n = 288, 25%). The ANN model was constructed from the training set using multivariate Logistic regression analysis and then verified in the validation set. RESULTS: The morbidity of LC in the training and validation sets was 41.2% and 46.8%, respectively. Multivariate analysis showed that age, platelet count, prothrombin time and total bilirubin were independent risk factors for LC (P < 0.05). The area under the ROC curve (AUC) analyses revealed that the ANN model had higher predictive accuracy than the Logistic model (ANN: 0.757 vs Logistic: 0.721; P < 0.001), and other scoring systems (ANN: 0.757 vs CP: 0.532, MELD: 0.594, ALBI: 0.575, APRI: 0.621, FIB-4: 0.644, AAR: 0.491, and GPR: 0.604; P < 0.05 for all) in diagnosing LC. Similar results were obtained in the validation set. CONCLUSION: The ANN model has better diagnostic capabilities than other commonly used models and scoring systems in assessing LC risk in patients with HBV-related HCC.
ABSTRACT
Dysregulation of genes involved in alternative splicing contributes to hepatocarcinogenesis. SNRPB, a component of spliceosome, is implicated in human cancers, yet its clinical significance and biological function in hepatocellular carcinoma (HCC) remains unknown. Here, we show that SNRPB expression is increased in HCC tissues, compared with the nontumorous tissues, at both messenger RNA and protein levels in two independent cohorts. High expression of SNRPB is significantly associated with higher pathological grade, vascular invasion, serum alpha-fetoprotein level, tumor metastasis, and poor disease-free and overall survivals. Luciferase reporter and chromatin immunoprecipitation assays demonstrate that SNRPB upregulation in HCC is mediated by c-Myc. Positive correlation is found between SNRPB and c-Myc expression in clinical samples. In vitro studies show that ectopic expression of SNRPB promotes HCC cell proliferation and migration, whereas knockdown of SNRPB results in the opposite phenotypes. Collectively, our data suggest SNRPB function as an oncogene and serve as a potential prognostic factor in HCC.
