In recent years, an increasing number of circular RNAs (circRNAs) have been discovered in hepatocellular carcinoma (HCC). However, the functions of most circRNAs require further investigation. Here, we found that circBACH1 was significantly upregulated in HCC tissues and that high circBACH1 levels were closely associated with poor prognosis. In addition, circBACH1 could promote HCC growth by accelerating cell cycle progression in vitro and in vivo. We next investigated the cellular and molecular mechanisms and discovered that circBACH1 inhibited p27 translation, which influenced cell cycle progression. Moreover, we revealed that circBACH1 could combine directly with HuR using RNA immunoprecipitation assays, pull-down assays, and electrophoretic mobility shift assays. The combination of these molecules facilitated HuR translocation from the nucleus to the cytoplasm according to the fluorescence in situ hybridization and immunofluorescence results. Finally, silencing HuR abrogated circBACH1's inhibition of p27 translation and abolished the circBACH1-induced effect on HCC proliferation. In sum, circBACH1 plays a significant role as an oncogene through the circBACH1/HuR/p27 axis in HCC development.

Background: To evaluate the potential of clinical-based model, a biparametric MRI-based radiomics model and a clinical-radiomics combined model for predicting clinically significant prostate cancer (PCa).Methods: In total, 381 patients with clinically suspicious PCa were included in this retrospective study; of those, 199 patients did not have PCa upon biopsy, while 182 patients had PCa. All patients underwent 3.0-T MRI examinations with the same acquisition parameters, and clinical risk factors associated with PCa (age, prostate volume, serum PSA, etc.) were collected. We randomly stratified the training and test sets using a 6:4 ratio. The radiomic features included gradient-based histogram features, grey-level co-occurrence matrix (GLCM), run-length matrix (RLM), and grey-level size zone matrix (GLSZM). Three models were developed using multivariate logistic regression analysis to predict clinically significant PCa: a clinical model, a radiomics model and a clinical-radiomics combined model. The diagnostic performance and clinical net benefit of each model were compared via receiver operating characteristic (ROC) curve analysis and decision curves, respectively.Results: Both the radiomics model (AUC: 0.98) and the clinical-radiomics combined model (AUC: 0.98) achieved greater predictive efficacy than the clinical model (AUC: 0.79). The decision curve analysis also showed that the radiomics model and combined model had higher net benefits than the clinical model. Conclusions:Compared with the evaluation of clinical risk factors associated with PCa only, the radiomics-based machine learning model can improve the predictive accuracy for clinically significant PCa, in terms of both diagnostic performance and clinical net benefit.

T1 and T2 relaxation times are relatively sensitive to early degenerative changes in the patellar cartilage, whereas the MTR may have some limitations with regard to early detection of OA. In addition, The T1 and T2 relaxation times negatively correlate with each other, which is a novel finding.

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By investigating the migration and invasion ability in pancreatic cancer, this study probed into the lncRNA MALAT1 molecular mechanism on Hippo-YAP signaling. The expression of lncRNA MALAT1 in PC tissues and cells was detected by qRT-PCR and Western blot. The effect of si-MALAT1 on proliferation was determined by CCK-8 assay. Cell apoptosis, migration, and invasion were respectively detected by flow cytometry assay, wound healing assay, and transwell assay. Western blot and immunohistochemistry were successively used for detecting LATS1 and YAP1 expression in pancreatic cancer tissues. The microarray analysis determined that lncRNA MALAT1 in pancreatic cancer was highly expressed. LncRNA MALAT1 presented an extremely high expression level in pancreatic cancer tissues and cells. After transfected with si-MALAT1, the proliferation of AsPC-1 cells decreased, induce apoptosis of AsPC-1 cells, and migration and invasion ability were reduced. The tendency of LATS1 expression level was down-regulated and YAP1 show the opposite trend in the Hippo-YAP signaling. The in vivo assay was found that the tumor to be small in size and volume, and the expression of Ki-67 was decreased. High expression of lncRNA MALAT1 in PC disorder the proliferation, apoptosis, and migration and invasion ability via influence Hippo-YAP signaling pathway.