Stratifin promotes the malignant progression of HCC via binding and hyperactivating AKT signaling.

Hepatocellular carcinoma (HCC) is a highly aggressive malignant tumor with limited treatment options and poor prognosis. In this study, we reveal the pivotal role of Stratifin (SFN), also recognized as 14-3-3σ, in driving HCC progression. Our investigation underscores a substantial upregulation of SFN within HCC tissues, manifesting a significant association with worse prognostic outcomes among HCC patients. In vitro and in vivo experiments reveal that SFN overexpression significantly amplifies proliferation, mitigates sorafenib-induced effects on HCC cells, and enhances tumorigenesis. While SFN silencing exerts converse effects on HCC progression. Additionally, we unveil a critical interaction between SFN and AKT, where SFN boosts AKT kinase activity by disrupting the binding of PHLPP2 and AKT, thereby intensifying the malignant progression of HCC cells. In conclusion, this study identifies the oncogenic role of SFN and elucidates the regulatory mechanism of the SFN/AKT axis in HCC, which may provide valuable insights into the mechanisms of HCC progression and potential targets for therapeutic intervention.

Dynamic network biomarker C1QTNF1 regulates tumor formation at the tipping point of hepatocellular carcinoma.

Identifying the precise moment before the onset of hepatocellular carcinoma (HCC) remains a significant challenge in the medical field. The existing biomarkers fall short of pinpointing the critical point preceding HCC formation. This study aimed to determine the exact tipping point for the transition from cirrhosis to HCC, identify the core Dynamic Network Biomarker (DNB), and elucidate its regulatory effects on HCC. A spontaneous HCC mouse model was established to mimic HCC formation in patients with chronic hepatitis. Using the DNB method, C1q and tumor necrosis factor (TNF) related 1 (C1QTNF1) protein was identified as the key DNB at the crucial tipping time of spontaneous HCC development. Both in vitro and in vivo studies showed that C1QTNF1 could inhibit tumor growth. Overexpression of C1QTNF1 before the tipping point effectively prevented HCC occurrence. Patients with elevated C1QTNF1 expression demonstrated improved overall survival (OS) (P = 0.03) and disease-free survival (DFS) (P = 0.03). The diagnostic value of C1QTNF1 was comparable to that of alpha-fetoprotein (AFP) (area under the curve [AUC] = 0.84; sensitivity 85%; specificity 80%). Furthermore, our research indicated that platelet-expressed C1QTNF1 is involved in cancer-associated signaling pathways. Our findings introduce a novel perspective by highlighting C1QTNF1 as the pivotal biomarker at the tipping point of primary HCC formation using DNB. We propose C1QTNF1 as a prognostic biomarker for HCC, potentially influencing tumor development through a platelet-related cancer signaling pathway.

Synergistic antitumor efficacy of aspirin plus lenvatinib in hepatocellular carcinoma via regulating of diverse signaling pathways.

It has been established that monotherapy yields limited efficacy in treating hepatocellular carcinoma (HCC), especially advanced HCC. Increasing evidence from preclinical studies and clinical trials indicates that combining multiple drugs can potentially refine treatment efficacy. Accordingly, it is crucial to explore more effective clinically feasible combination therapies to enhance the treatment outcomes of HCC patients. This study evaluated the antitumor efficacy and safety of combination therapy involving aspirin and lenvatinib in HCC. Through in vitro and in vivo assays, we demonstrated that this combination yielded stronger antitumor effects compared to lenvatinib or aspirin monotherapy. Furthermore, no significant adverse events were observed in an HCC mouse model during treatment. Mechanistic studies revealed that aspirin plus lenvatinib could target multiple oncogenes and tumor suppressors, affecting diverse signaling pathways in various biological processes conducive to antitumor effects. Overall, our findings suggest that aspirin plus lenvatinib could serve as a promising combination regimen to improve the therapeutic outcomes of HCC.

Systemic analysis of the prognostic significance and interaction network of miR-26b-3p in cholangiocarcinoma.

MicroRNAs (miRNAs) reportedly play significant roles in the progression of various cancers and hold huge potential as both diagnostic tools and therapeutic targets. Given the ongoing uncertainty surrounding the precise functions of several miRNAs in cholangiocarcinoma (CCA), this research undertakes a comprehensive analysis of CCA data sourced from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The present study identified a novel miRNA, specifically miR-26b-3p, which exhibited prognostic value for individuals with CCA. Notably, miR-26b-3p was upregulated within CCA samples, with an inverse correlation established with patient prognosis (Hazard Ratio = 8.19, p = 0.018). Through a combination of functional enrichment analysis, analysis of the LncRNA-miR-26b-3p-mRNA interaction network, and validation by qRT PCR and western blotting, this study uncovered the potential of miR-26b-3p in potentiating the malignant progression of CCA via regulation of essential genes (including PSMD14, XAB2, SLC4A4) implicated in processes such as endoplasmic reticulum (ER) stress and responses to misfolded proteins. Our findings introduce novel and valuable insights that position miR-26b-3p-associated genes as promising biomarkers for the diagnosis and treatment of CCA.

CircFOXK2 promotes hepatocellular carcinoma progression and leads to a poor clinical prognosis via regulating the Warburg effect.

BACKGROUND: The Warburg effect is well-established to be essential for tumor progression and accounts for the poor clinical outcomes of hepatocellular carcinoma (HCC) patients. An increasing body of literature suggests that circular RNAs (circRNAs) are important regulators for HCC. However, few circRNAs involved in the Warburg effect of HCC have hitherto been investigated. Herein, we aimed to explore the contribution of circFOXK2 to glucose metabolism reprogramming in HCC. METHODS: In the present study, different primers were designed to identify 14 circRNAs originating from the FOXK2 gene, and their differential expression between HCC and adjacent liver tissues was screened. Ultimately, circFOXK2 (hsa_circ_0000817) was selected for further research. Next, the clinical significance of circFOXK2 was evaluated. We then assessed the pro-oncogenic activity of circFOXK2 and its impact on the Warburg effect in both HCC cell lines and animal xenografts. Finally, the molecular mechanisms of how circFOXK2 regulates the Warburg effect of HCC were explored. RESULTS: CircFOXK2 was aberrantly upregulated in HCC tissues and positively correlated with poor clinical outcomes in patients that underwent radical hepatectomy. Silencing of circFOXK2 significantly suppressed HCC progression both in vitro and in vivo. Mechanistically, circFOXK2 upregulated the expression of protein FOXK2-142aa to promote LDHA phosphorylation and led to mitochondrial fission by regulating the miR-484/Fis1 pathway, ultimately activating the Warburg effect in HCC. CONCLUSIONS: CircFOXK2 is a prognostic biomarker of HCC that promotes the Warburg effect by promoting the expression of proteins and miRNA sponges that lead to tumor progression. Overall, circFOXK2 has huge prospects as a potential therapeutic target for patients with HCC.

Identify Key Genes Correlated to Ischemia-Reperfusion Injury in Aging Livers.

Background: With the intensification of population aging, the proportion of aging livers in the donor pool is increasing rapidly. Compared with young livers, aging livers are more susceptible to ischemia-reperfusion injury (IRI) during liver transplantation, which greatly affects the utilization rate of aging livers. The potential risk factors associated with IRI in aging livers have not been fully elucidated. Methods: In this work, five human liver tissue expression profiling datasets (GSE61260, GSE107037, GSE89632, GSE133815, and GSE151648) and a total of 28 young and aging liver tissues of human (N = 20) and mouse (N = 8) were used to screen and verify the potential risk factors associated with aging livers being more prone to IRI. DrugBank Online was used to screen drugs with potential to alleviate IRI in aging livers. Results: The gene expression profile and immune cell composition between young and aging livers had significant differences. Among the differentially expressed genes, aryl hydrocarbon receptor nuclear translocator-like (ARNTL), BTG antiproliferation factor 2 (BTG2), C-X-C motif chemokine ligand 10 (CXCL10), chitinase 3-like 1 (CHI3L1), immediate early response 3 (IER3), Fos proto-oncogene, AP-1 transcription factor subunit (FOS), and peroxisome proliferative activated receptor, gamma, coactivator 1 alpha (PPARGC1A), mainly involved in the regulation of cell proliferation, metabolism, and inflammation, were also dysregulated in liver tissues suffered from IRI and could form a FOS-centered interaction network. Nadroparin was screened out with the potential to target FOS in DrugBank Online. In addition, the proportion of dendritic cells (DCs) was significantly upregulated in aging livers. Conclusions: We combined the expression profiling datasets of liver tissues and samples collected in our hospital for the first time to reveal that the changes in the expression of ARNTL, BTG2, CXCL10, CHI3L1, IER3, FOS, and PPARGC1A and the proportion of dendritic cells may be associated with aging livers being more prone to IRI. Nadroparin may be used to mitigate IRI in aging livers by targeting FOS, and regulation of DC activity may also reduce IRI.

Preoperative identification of microvascular invasion in hepatocellular carcinoma by XGBoost and deep learning.

PURPOSE: Microvascular invasion (MVI) is a valuable predictor of survival in hepatocellular carcinoma (HCC) patients. This study developed predictive models using eXtreme Gradient Boosting (XGBoost) and deep learning based on CT images to predict MVI preoperatively. METHODS: In total, 405 patients were included. A total of 7302 radiomic features and 17 radiological features were extracted by a radiomics feature extraction package and radiologists, respectively. We developed a XGBoost model based on radiomics features, radiological features and clinical variables and a three-dimensional convolutional neural network (3D-CNN) to predict MVI status. Next, we compared the efficacy of the two models. RESULTS: Of the 405 patients, 220 (54.3%) were MVI positive, and 185 (45.7%) were MVI negative. The areas under the receiver operating characteristic curves (AUROCs) of the Radiomics-Radiological-Clinical (RRC) Model and 3D-CNN Model in the training set were 0.952 (95% confidence interval (CI) 0.923-0.973) and 0.980 (95% CI 0.959-0.993), respectively (p = 0.14). The AUROCs of the RRC Model and 3D-CNN Model in the validation set were 0.887 (95% CI 0.797-0.947) and 0.906 (95% CI 0.821-0.960), respectively (p = 0.83). Based on the MVI status predicted by the RRC and 3D-CNN Models, the mean recurrence-free survival (RFS) was significantly better in the predicted MVI-negative group than that in the predicted MVI-positive group (RRC Model: 69.95 vs. 24.80 months, p < 0.001; 3D-CNN Model: 64.06 vs. 31.05 months, p = 0.027). CONCLUSION: The RRC Model and 3D-CNN models showed considerable efficacy in identifying MVI preoperatively. These machine learning models may facilitate decision-making in HCC treatment but requires further validation.

A comprehensive analysis of the MAGE family as prognostic and diagnostic markers for hepatocellular carcinoma.

The Melanoma Antigen Gene (MAGE) family is a large, highly conserved group of proteins which was reported to participate in the progression of multiple cancers in humans. However, the function of distinct MAGE genes in hepatocellular carcinoma (HCC) is largely unclear. In this study, we comprehensively evaluated the expression, clinical significance, genetic alteration, interaction network and functional enrichment of MAGEs in HCC. Our research showed that many MAGE genes were dysregulated in HCC. Among them, MAGEA1, MAGEC2, MAGED1, MAGED2, MAGEF1 and MAGEL2 were significantly associated with clinical stage and differentiation of HCC. MAGED1, MAGED2, MAGEA6, MAGEA12, MAGEA10, MAGEB4, MAGEL2 and MAGEC3 significantly correlated with HCC prognosis. Further functional enrichment analysis suggested the dysregulated MAGEs may play important roles in signal transduction. These results indicate that multiple dysregulated MAGEs might play important roles in the development of HCC and can be exploited as useful biomarkers for diagnosis and treatment in HCC.