Exosome-depleted MiR-148a-3p derived from Hepatic Stellate Cells Promotes Tumor Progression via ITGA5/PI3K/Akt Axis in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a major cause of cancer-related death worldwide. Although it has been known that hepatic stellate cells (HSCs) play critical roles in the development and progression of HCC, the molecular mechanism underlying crosstalk between HSCs and cancer cells still remains unclear. Here, we investigated the interactions between HSCs and cancer cells through an indirect co-culture system. The expressions of cellular and exosomal miR-148a-3p were evaluated by quantitative real-time PCR. Cell counting kit-8 was used for evaluating cell growth in vitro. Cell migration and invasion ability were evaluated by wound-healing and Transwell assays. Western blot, quantitative real-time PCR and Luciferase reporter assay were performed to determine the target gene of miR-148a-3p. A xenograft liver cancer model was established to study the function of exosomal miR-148a-3p in vivo. We found that miR-148a-3p was downregulated in co-cultured HSCs and overexpression of miR-148a-3p in HSCs impaired the proliferation and invasiveness of HCC both in vitro and in vivo. Moreover, further study showed that the miR-148a-3p was also downexpressed in HSCs-derived exosomes, and increased HSCs-derived exosomal miR-148a-3p suppressed HCC tumorigenesis through ITGA5/PI3K/Akt pathway. In conclusion, our study demonstrated that exosome-depleted miR-148a-3p derived from activated HSCs accelerates HCC progression through ITGA5/PI3K/Akt axis.

Development and validation of a non-invasive model for diagnosing HBV-related liver cirrhosis.

BACKGROUND: Liver cirrhosis is closely related to the abnormal liver function and occurrence of liver cancer. Accurate non-invasive assessment of liver cirrhosis is of great significance for preventing disease progression and treatment decision-making. We aim to develop and validate a non-invasive diagnostic model for liver cirrhosis in patients with chronic hepatitis B (CHB). METHODS: From July 2015 to April 2017, seven-hundred fifty-four patients with primary HBV-related liver cancer who underwent hepatectomy were reprospectively recruited. All patients were examined with 2D-SWE and serologic testing preoperatively, which were utilized for measurement of liver stiffness and serum fibrosis models. The stage of liver fibrosis was evaluated using a resected liver specimen. Least absolute shrinkage and selection operator (Lasso) regression was used for feature selection and binary logistic regression analysis was chosen to build a diagnostic model, which was presented as a nomogram and evaluated for calibration, discrimination and clinical usefulness. The performance of noninvasive model was then prospectively validated in an independent cohort (361 patients) by the ROC curve analysis. RESULTS: The diagnostic model, which consists of 5 selected clinical characteristics (PIII-NP, IV-C, Hyaluronan, Platelet and Liver stiffness), showed the strongest correlation with liver fibrosis stage (ρ = 0.702, P < 0.05). Compared with APRI, FIB-4, King's Score, and Forns Index, the model presented the optimal discrimination and the best predictive performance with the highest AUC in the training cohort (0.866, 95%CI 0.840-0.892, P < 0.05) and validation cohorts (0.852, 95%CI 0.813-0.890, P < 0.05). Decision curve analysis demonstrated that nomogram based on the model was extremely useful for diagnosing cirrhosis in patients with chronic hepatitis B. CONCLUSION: This study proposes a non-invasive diagnostic model that incorporates the clinical predictors which can be conveniently used in the individualized diagnosis of HBV-related liver cirrhosis.