Angiopoietin 2 displays a vascular endothelial growth factor dependent synergistic effect in hepatocellular carcinoma development in mice

Background: Orchestration of two major classes of angiogenic factors—namely, vascular endothelial growth factor (VEGF) and angiopoietin 2 (Ang-2)—has been shown to play a pivotal role in tumour angiogenesis, including hepatocellular carcinoma (HCC). However, few studies have focused on the direct interaction of these factors on in vivo tumour development and angiogenesis. Aim: To examine the interaction between both factors in murine HCC. Methods: We examined the combination effect of VEGF and Ang-2 overexpression by means of a combination of a retroviral tetracycline (tet) regulated gene manipulating system in vivo, by providing tet in the drinking water, and a conventional plasmid gene expression system. Results: Neither Ang-2 nor VEGF overexpression induced proliferation of HCC cells in vitro. In vivo, although overexpression of Ang-2 did not increase tumour development, simultaneous expression of Ang-2 and VEGF synergistically augmented tumour growth and angiogenesis in murine HCC. Ang-2 plus VEGF induced tumour development was markedly attenuated by treatment with neutralising monoclonal antibodies against VEGF receptors. Ang-2 plus VEGF overexpression significantly increased the activities of matrix metalloproteinase (MMP)-2 and MMP-9 in the tumour. Suppression of intratumoral VEGF almost completely abolished this augmentation of MMPs. Conclusions: These results suggest that Ang-2 synergistically augments VEGF mediated HCC development and angiogenesis. This proangiogenic activity was exerted only in the presence of VEGF, at least partly mediated via induction of MMP-2 and MMP-9 in the tumour

Machine learning in primary biliary cholangitis: A novel approach for risk stratification

Background & Aims: Machine learning (ML) provides new approaches for prognostication through the identification of novel subgroups of patients. We explored whether ML could support disease sub-phenotyping and risk stratification in primary biliary cholangitis (PBC). Methods: ML was applied to an international dataset of PBC patients. The dataset was split into a derivation cohort (training set) and a validation cohort (validation set), and key clinical features were analysed. The outcome was a composite of liver-related death or liver transplantation. ML and standard survival analysis were performed. Results: The training set was composed of 11,819 subjects, while the validation set was composed of 1,069 subjects. ML identified four clusters of patients characterized by different phenotypes and long-term prognosis. Cluster 1 (n = 3566) included patients with excellent prognosis, whereas Cluster 2 (n = 3966) consisted of individuals at worse prognosis differing from Cluster 1 only for albumin levels around the limit of normal. Cluster 3 (n = 2379) included young patients with florid cholestasis and Cluster 4 (n = 1908) comprised advanced cases. Further sub-analyses on the dynamics of albumin within the normal range revealed that ursodeoxycholic acid-induced increase of albumin >1.2 x lower limit of normal (LLN) is associated with improved transplant-free survival. Conclusions: Unsupervised ML identified four novel groups of PBC patients with different phenotypes and prognosis and highlighted subtle variations of albumin within the normal range. Therapy-induced increase of albumin >1.2 x LLN should be considered a treatment goal