TRIM50 promotes NLRP3 inflammasome activation by directly inducing NLRP3 oligomerization.

Tripartite motif protein (TRIM) 50 is a new member of the tripartite motif family, and its biological function and the molecular mechanism it is involved in remain largely unknown. The NOD-like receptor family protein (NLRP)3 inflammasome is actively involved in a wide array of biological processes while mechanisms of its regulation remain to be fully clarified. Here, we demonstrate the role of TRIM50 in NLRP3 inflammasome activation. In contrast to the conventional E3 ligase functions of TRIM proteins, TRIM50 mediates direct oligomerization of NLRP3, thereby suppressing its ubiquitination and promoting inflammasome activation. Mechanistically, TRIM50 directly interacts with NLRP3 through its RING domain and induces NLRP3 oligomerization via its coiled-coil domain. Finally, we show that TRIM50 promotes NLRP3 inflammasome-mediated diseases in mice. We thus reveal a novel regulatory mechanism of NLRP3 via TRIM50 and suggest that modulating TRIM50 might represent a therapeutic strategy for NLRP3-dependent pathologies.

Inhibiting Src-mediated PARP1 tyrosine phosphorylation confers synthetic lethality to PARP1 inhibition in HCC.

Hepatocellular carcinoma (HCC), a heterogeneous cancer with high mortality, is resistant to single targeted therapy; thus, combination therapy based on synthetic lethality is a promising therapeutic strategy for HCC. Poly (adenosine diphosphate [ADP]-ribose) polymerase 1 (PARP1) is the most recognized target for synthetic lethality; however, the therapeutic effect of PARP1 inhibition on HCC is disappointing. Therefore, exploring new synthetic lethal partners for the efficient manipulation of HCC is urgently required. In this study, we identified Src and PARP1 as novel synthetic lethal partners, and the combination therapy produced significant anti-tumor effects without causing obvious side effects. Mechanistically, Src interacted with PARP1 and phosphorylated PARP1 at the Y992 residue, which further mediated resistance to PARP1 inhibition. Overall, this study revealed that Src-mediated PARP1 phosphorylation induced HCC resistance to PARP1 inhibitors and indicated a therapeutic window of the Y992 phosphorylation of PARP1 for HCC patients. Moreover, synthetic lethal therapy by co-targeting PARP1 and Src have the potential to broaden the strategies for HCC and might benefit HCC patients with high Src activation and resistance to PARP1 inhibitors alone.

Early Prediction of Severe COVID-19 in Patients by a Novel Immune-Related Predictive Model.

During the progression of coronavirus disease 2019 (COVID-19), immune response and inflammation reactions are dynamic events that develop rapidly and are associated with the severity of disease. Here, we aimed to develop a predictive model based on the immune and inflammatory response to discriminate patients with severe COVID-19. COVID-19 patients were enrolled, and their demographic and immune inflammatory reaction indicators were collected and analyzed. Logistic regression analysis was performed to identify the independent predictors, which were further used to construct a predictive model. The predictive performance of the model was evaluated by receiver operating characteristic curve, and optimal diagnostic threshold was calculated; these were further validated by 5-fold cross-validation and external validation. We screened three key indicators, including neutrophils, eosinophils, and IgA, for predicting severe COVID-19 and obtained a combined neutrophil, eosinophil, and IgA ratio (NEAR) model (NEU [109/liter] - 150×EOS [109/liter] + 3×IgA [g/liter]). NEAR achieved an area under the curve (AUC) of 0.961, and when a threshold of 9 was applied, the sensitivity and specificity of the predicting model were 100% and 88.89%, respectively. Thus, NEAR is an effective index for predicting the severity of COVID-19 and can be used as a powerful tool for clinicians to make better clinical decisions. IMPORTANCE The immune inflammatory response changes rapidly with the progression of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and is responsible for clearance of the virus and further recovery from the infection. However, the intensified immune and inflammatory response in the development of the disease may lead to more serious and fatal consequences, which indicates that immune indicators have the potential to predict serious cases. Here, we identified both eosinophils and serum IgA as prognostic markers of COVID-19, which sheds light on new research directions and is worthy of further research in the scientific research field as well as clinical application. In this study, the combination of NEU count, EOS count, and IgA level was included in a new predictive model of the severity of COVID-19, which can be used as a powerful tool for better clinical decision-making.