Sublethal necroptosis signaling promotes inflammation and liver cancer.

It is currently not well known how necroptosis and necroptosis responses manifest in vivo. Here, we uncovered a molecular switch facilitating reprogramming between two alternative modes of necroptosis signaling in hepatocytes, fundamentally affecting immune responses and hepatocarcinogenesis. Concomitant necrosome and NF-κB activation in hepatocytes, which physiologically express low concentrations of receptor-interacting kinase 3 (RIPK3), did not lead to immediate cell death but forced them into a prolonged "sublethal" state with leaky membranes, functioning as secretory cells that released specific chemokines including CCL20 and MCP-1. This triggered hepatic cell proliferation as well as activation of procarcinogenic monocyte-derived macrophage cell clusters, contributing to hepatocarcinogenesis. In contrast, necrosome activation in hepatocytes with inactive NF-κB-signaling caused an accelerated execution of necroptosis, limiting alarmin release, and thereby preventing inflammation and hepatocarcinogenesis. Consistently, intratumoral NF-κB-necroptosis signatures were associated with poor prognosis in human hepatocarcinogenesis. Therefore, pharmacological reprogramming between these distinct forms of necroptosis may represent a promising strategy against hepatocellular carcinoma.

Weakly supervised end-to-end artificial intelligence in gastrointestinal endoscopy.

Artificial intelligence (AI) is widely used to analyze gastrointestinal (GI) endoscopy image data. AI has led to several clinically approved algorithms for polyp detection, but application of AI beyond this specific task is limited by the high cost of manual annotations. Here, we show that a weakly supervised AI can be trained on data from a clinical routine database to learn visual patterns of GI diseases without any manual labeling or annotation. We trained a deep neural network on a dataset of N = 29,506 gastroscopy and N = 18,942 colonoscopy examinations from a large endoscopy unit serving patients in Germany, the Netherlands and Belgium, using only routine diagnosis data for the 42 most common diseases. Despite a high data heterogeneity, the AI system reached a high performance for diagnosis of multiple diseases, including inflammatory, degenerative, infectious and neoplastic diseases. Specifically, a cross-validated area under the receiver operating curve (AUROC) of above 0.70 was reached for 13 diseases, and an AUROC of above 0.80 was reached for two diseases in the primary data set. In an external validation set including six disease categories, the AI system was able to significantly predict the presence of diverticulosis, candidiasis, colon and rectal cancer with AUROCs above 0.76. Reverse engineering the predictions demonstrated that plausible patterns were learned on the level of images and within images and potential confounders were identified. In summary, our study demonstrates the potential of weakly supervised AI to generate high-performing classifiers and identify clinically relevant visual patterns based on non-annotated routine image data in GI endoscopy and potentially other clinical imaging modalities.

Macrophage migration inhibitory factor exerts pro-proliferative and anti-apoptotic effects via CD74 in murine hepatocellular carcinoma.

BACKGROUND AND PURPOSE: Macrophage migration inhibitory factor (MIF) is an inflammatory and chemokine-like protein expressed in different inflammatory diseases as well as solid tumours. CD74-as the cognate MIF receptor-was identified as an important target of MIF. We here analysed the role of MIF and CD74 in the progression of hepatocellular carcinoma (HCC) in vitro and in vivo. EXPERIMENTAL APPROACH: Multilocular HCC was induced using the diethylnitrosamine/carbon tetrachloride (DEN/CCl4 ) model in hepatocyte-specific Mif knockout (Mif Δhep ), Cd74-deficient, and control mice. Tumour burden was compared between the genotypes. MIF, CD74 and Ki67 expression were investigated in tumour and surrounding tissue. In vitro, the effects of the MIF/CD74 axis on the proliferative and apoptotic behaviour of hepatoma cells and respective signalling pathways were assessed after treatment with MIF and anti-CD74 antibodies. KEY RESULTS: DEN/CCl4 treatment of Mif Δhep mice resulted in reduced tumour burden and diminished proliferation capacity within tumour tissue. In vitro, MIF stimulated proliferation of Hepa 1-6 and HepG2 cells, inhibited therapy-induced cell death and induced ERK activation. The investigated effects could be reversed using a neutralizing anti-CD74 antibody, and Cd74-/- mice developed fewer tumours associated with decreased proliferation rates. CONCLUSION AND IMPLICATIONS: We identified a pro-tumorigenic role of MIF during proliferation and therapy-induced apoptosis of HCC cells. These effects were mediated via the MIF cognate receptor CD74. Thus, inhibition of the MIF/CD74 axis could represent a promising target with regard to new pharmacological therapies aimed at HCC.