PARP7 negatively regulates the type I interferon response in cancer cells and its inhibition triggers antitumor immunity

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Fluoxetine-induced hepatic lipid accumulation is mediated by prostaglandin endoperoxide synthase 1 and is linked to elevated 15-deoxy-Δ12,14PGJ2

Major depressive disorder and other neuropsychiatric disorders are often managed with long-term use of antidepressant medication. Fluoxetine, an SSRI antidepressant, is widely used as a first-line treatment for neuropsychiatric disorders. However, fluoxetine has also been shown to increase the risk of metabolic diseases such as non-alcoholic fatty liver disease. Fluoxetine has been shown to increase hepatic lipid accumulation in vivo and in vitro. In addition, fluoxetine has been shown to alter the production of prostaglandins which have also been implicated in the development of non-alcoholic fatty liver disease. The goal of this study was to assess the effect of fluoxetine exposure on the prostaglandin biosynthetic pathway and lipid accumulation in a hepatic cell line (H4-II-E-C3 cells). Fluoxetine treatment increased mRNA expression of prostaglandin biosynthetic enzymes (Ptgs1, Ptgs2, and Ptgds), PPAR gamma (Pparg), and PPAR gamma downstream targets involved in fatty acid uptake (Cd36, Fatp2, and Fatp5) as well as production of 15-deoxy-Δ^12,14PGJ₂ a PPAR gamma ligand. The effects of fluoxetine to induce lipid accumulation were attenuated with a PTGS1 specific inhibitor (SC-560), whereas inhibition of PTGS2 had no effect. Moreover, SC-560 attenuated 15-deoxy-Δ^12,14PGJ₂ production and expression of PPAR gamma downstream target genes. Taken together these results suggest that fluoxetine-induced lipid abnormalities appear to be mediated via PTGS1 and its downstream product 15d-PGJ₂ and suggest a novel therapeutic target to prevent some of the adverse effects of fluoxetine treatment.     

Hepatotoxicity of cantharidin is associated with the altered bile acid metabolism

Cantharidin (CTD) is an effective antitumor agent. However, it exhibits significant hepatotoxicity, the mechanism of which remains unclear. In this study, biochemical and histopathological analyses complemented with ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS)-based targeted metabolomic analysis of bile acids (BAs) were employed to investigate CTD-induced hepatotoxicity in rats. Sixteen male and female Sprague–Dawley rats were randomly divided into two groups: control and CTD (1.0 mg/kg) groups. Serum and liver samples were collected after 28 days of intervention. Biochemical, histopathological, and BA metabolomic analyses were performed for all samples. Further, the key biomarkers of CTD-induced hepatotoxicity were identified via multivariate and metabolic pathway analyses. In addition, metabolite–gene–enzyme network and Kyoto Encyclopedia of Genes and Genomes pathway analyses were used to identify the signaling pathways related to CTD-induced hepatotoxicity. The results revealed significantly increased levels of biochemical indices (alanine aminotransferase, aspartate aminotransferase, and total bile acid). Histopathological analysis revealed that the hepatocytes were damaged. Further, 20 endogenous BAs were quantitated via UHPLC-MS/MS, and multivariate and metabolic pathway analyses of BAs revealed that hyocholic acid, cholic acid, and chenodeoxycholic acid were the key biomarkers of CTD-induced hepatotoxicity. Meanwhile, primary and secondary BA biosynthesis and taurine and hypotaurine metabolism were found to be associated with the mechanism by which CTD induced hepatotoxicity in rats. This study provides useful insights for research on the mechanism of CTD-induced hepatotoxicity.     

SLC及其受体CCR7与Ⅰ期非小细胞肺癌淋巴结微转移的相关性

目的 探讨溶质载体蛋白（SLC）及其受体趋化因子受体7（CCR7）与I期非小细胞肺癌（NSCLC）淋巴结微转移的相关性。方法 选取2019年1月~2020年3月于我院就诊的I期NSCLC患者127例为研究对象，按照淋巴结微转移情况分为对照组92例和转移组35例，所有患者入院后均通过根治术切除病灶，通过免疫组化方式检测病灶中SLC7A11及CCR7含量，并收集患者临床资料、实验室检查资料及影像学检查资料。通过Logistic回归分析评价SLC7A11及CCR7与淋巴结微转移之间的关系。最后通过建立ROC曲线分析两者及其联合检测对NSCLC患者微淋巴结转移的预测价值。结果 两组患者SLC7A11及CCR7表达水平存在显著差异（P＜0.05）。转移组患者病灶直径、支气管受累及TLG显著高于对照组（P＜0.05）。病灶直径（OR=49.254,95%CI=11.062~507.604）是影响NSCLC淋巴结微转移的独立危险因素（P＜0.05）。SLC7A11（OR=8.622）及CCR7（OR=8.709）表达水平是影响NSCLC淋巴结微转移的独立因素（P＜0.05）。SLC7A11、CCR7及联合诊断对NSCLC淋巴结微转移具有较好的检测价值（均P＜0.05）。联合检测特异度显著高于 SLC7A11及CCR7单独检测（2=7.292，15.125；均P＜0.01）。结论 SLC家族的中SLC7A11及其受体CCR7与NSCLC患者微淋巴结转移显著相关。     

Predicting Survival for Chimeric Antigen Receptor T-Cell Therapy: A Validation of Survival Models Using Follow-Up Data From ZUMA-1

ObjectivesSurvival extrapolation for chimeric antigen receptor T-cell therapies is challenging, owing to their unique mechanistic properties that translate to complex hazard functions. Axicabtagene ciloleucel is indicated for the treatment of relapse or refractory diffuse large B-cell lymphoma after 2 or more lines of therapy based on the ZUMA-1 trial. Four data snapshots are available, with minimum follow-up of 12, 24, 36, and 48 months. This analysis explores how survival extrapolations for axicabtagene ciloleucel using ZUMA-1 data can be validated and compared.MethodsThree different parametric modeling approaches were applied: standard parametric, spline-based, and cure-based models. Models were compared using a range of metrics, across the 4 data snapshot, including visual fit, plausibility of long-term estimates, statistical goodness of fit, inspection of hazard plots, point-estimate accuracy, and conditional survival estimates.ResultsStandard and spline-based parametric extrapolations were generally incapable of fitting the ZUMA-1 data well. Cure-based models provided the best fit based on the earliest data snapshot, with extrapolations remaining consistent as data matured. At 48 months, the maximum survival overestimate was 8.3% (Gompertz mixture-cure model) versus the maximum underestimate of 33.5% (Weibull standard parametric model).ConclusionsWhere a plateau in the survival curve is clinically plausible, cure-based models may be helpful in making accurate predictions based on immature data. The ability to reliably extrapolate from maturing data may reduce delays in patient access to potentially lifesaving treatments. Additional research is required to understand how models compare in broader contexts, including different treatments and therapeutic areas.     

Recent advances in lipid nanoparticles for delivery of nucleic acid,mRNA, and gene editing-based therapeutics

Lipid nanoparticles (LNPs) are becoming popular as a means of delivering therapeutics, including those based on nucleic acids and mRNA. The mRNA-based coronavirus disease 2019 vaccines are perfect examples to highlight the role played by drug delivery systems in advancing human health. The fundamentals of LNPs for the delivery of nucleic acid- and mRNA-based therapeutics, are well established. Thus, future research on LNPs will focus on addressing the following: expanding the scope of drug delivery to different constituents of the human body, expanding the number of diseases that can be targeted, and studying the change in the pharmacokinetics of LNPs under physiological and pathological conditions. This review article provides an overview of recent advances aimed at expanding the application of LNPs, focusing on the pharmacokinetics and advantages of LNPs. In addition, analytical techniques, library construction and screening, rational design, active targeting, and applicability to gene editing therapy have also been discussed.