HighlightsCircACTN4 was upregulated in ICC and is associated with a worse prognosis.CircACTN4 promoted ICC growth and metastasis in vitro and in vivo.CircACTN4 recruited YBX1 to initiate FZD7 transcription.CircACTN4 acted as sponge of miR-424-5p to upregulate YAP1.CircACTN4 enhanced the interaction between the Wnt/b-catenin and Hippo/YAP pathways.

Hepatocellular carcinoma (HCC) samples were clustered into three energy metabolism-related molecular subtypes (C1, C2, and C3) with different prognosis using the gene expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). HCC energy metabolism-related molecular subtype analysis was conducted based on the 594 energy metabolism genes. Differential expression analysis yielded 576 differentially expressed genes (DEGs) among the three subtypes, which were closely related to HCC progression. Six genes were finally selected from the 576 DEGs through LASSO-Cox regression and used in constructing a six-gene signature-associated prognostic risk model, which was validated using the TCGA internal and three GEO external validation cohorts. The risk model showed that high ANLN, ENTPD2, TRIP13, PLAC8, and G6PD expression levels were associated with bad prognosis, and high expression of ADH1C was associated with a good prognosis. The validation results showed that our risk model had a high distinguishing ability of prognosis in HCC patients. The four enriched pathways of the risk model were obtained by gene set enrichment analysis (GSEA) and found to be associated with the tumorigenesis and development of HCC, including the cell cycle, Wnt signaling pathway, drug metabolism cytochrome P450, and primary bile acid biosynthesis. The risk score calculated from the established risk model in 204 samples and other clinical characteristics were used in building a nomogram with a good prognostic prediction ability (C-index = 0.746, 95% CI = 0.714-0.777). The area under the curves (AUCs) of the nomogram model in 1-, 2-, and 3-years were 0.82, 0.77, and 0.79, respectively. Then, qRT-PCR and immunohistochemistry were used to validate the mRNA expression levels of the six genes, and significant differences in mRNA and gene expression were observed among the tumor and adjacent tissues. Overall, our study divided HCC patients into three energy metabolism-related molecular subtypes with different prognosis. Then, a risk model with a good performance in prognostic prediction was built using the TCGA dataset. This model can be used as an independent prognostic evaluation index for HCC patients.

Background: This study developed a novel inflammation score system to predict survival outcomes using preoperational inflammatory markers in hepatocellular carcinoma (HCC) after surgery. Materials and Methods: An inflammation score system was developed using five preoperative inflammatory markers based on the clinical data of 455 HCC patients (training cohort) receiving radical resection in the Eastern Hepatobiliary Surgery Hospital. The system was validated using a cohort from a different hospital (external validation). Kaplan-Meier curves and log-rank test were used to compare the survival of patients with different inflammation scores. A nomogram including inflammation scores for survival prediction was created to exhibit the risk factors of overall survival (OS). Results: The patients in the low-score group showed better OS and recurrence-free survival (RFS) in the training and external validation cohorts than those from the high-score group. Subgroup analysis showed that compared with patients in the training cohort from the high-score group, stage I (eighth TNM stage) patients in the low-score group exhibited better prognosis results, whereas the findings for Stage II and III patients were different. Multivariate Cox analysis revealed that high inflammation score is an independent risk factor of OS and RFS. The nomogram established using the inflammation score with the C-index value of 0.661 (95% confidence interval=0.624-0.698) revealed a good three- and five-year calibration curves. Conclusions: The inflammation score system based on five preoperative inflammatory markers well predicted the survival of HCC patients after surgery, especially in those at the early stage (Stage I).

Long non-coding RNAs (lncRNAs) have extremely complex roles in the progression of intrahepatic cholangiocarcinoma (ICC) and remain to be elucidated. By cytological and animal model experiments, this study demonstrated that the expression of lncRNA MNX1-AS1 was remarkably elevated in ICC cell lines and tissues, and was highly and positively correlated with motor neuron and pancreas homeobox protein 1 (MNX1) expression. MNX1-AS1 significantly facilitated the proliferation, migration, invasion, and angiogenesis in ICC cells in vitro, and remarkably promoted tumor growth and metastasis in vivo. Further study revealed that MNX1-AS1 promoted the expression of MNX1 via recruiting transcription factors c-Myc and myc-associated zinc finger protein (MAZ). Furthermore, MNX1 upregulated the expression of Ajuba protein via binding to its promoter region, and subsequently, Ajuba protein suppressed the Hippo signaling pathway. Taken together, our results uncovered that MNX1-AS1 can facilitate ICC progression via MNX1-AS1/c-Myc and MAZ/MNX1/Ajuba/Hippo pathway, suggesting that MNX1-AS1 may be able to serve as a potential target for ICC treatment.