Pan-cancer proteomic map of 949 human cell lines

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脊髓小脑共济失调2型家系ATXN2基因中间重复病例表型与分子遗传学特征

目的探讨脊髓小脑共济失调2型(SCA2)致病基因ATXN2异常等位基因中间重复个体的表型和分子遗传学特点。方法针对2005—2018年中日友好医院神经科运动障碍与神经遗传病研究中心收集的1383个常染色体显性遗传共济失调家系的先证者和部分家系成员,采用荧光标记毛细管电泳片段分析方法进行动态突变检测,对携带ATXN2基因中间重复的个体进行临床表型和遗传特征分析。结果共检出163个家系(包含先证者和家系成员共203人)携带异常扩展的ATXN2基因CAG重复序列,其中93个家系中有107例的异常扩展等位基因重复次数在29~34次之间。在其中的20个亲子对中,父系遗传16个,异常等位基因的代间扩展增加0~28次,母系遗传4个,异常等位基因的代间扩展增加0~4次。结论对于临床拟诊SCA2家系患者,需对其亲代或成年子代个体进行ATXN2基因检测,以免漏诊。动态突变基因检测有助于识别中间重复的个体,对明确家系致病基因和遗传咨询至关重要。     

Association of vitamin D levels and risk of latent tuberculosis in the hemodialysis population

BackgroundVitamin D is essential in the host defense against tuberculosis (TB). Suboptimal vitamin D status is common in the hemodialysis population. Hemodialysis patients have an increased risk compared to the general population latent tuberculosis infection (LTBI). However, the association between vitamin D deficiency and LTBI in this population remains unclear.Materials and methodsWe conducted a cross-sectional study between March and May 2017. Interferon-gamma release assay (IGRA) through QuantiFERON-TB Gold In-Tube was used to assess LTBI. Plasma 25-hydroxycholecalciferol (25-OHD) levels were measured by Elecsys Vitamin D Total assay. Suboptimal vitamin D levels included vitamin D insufficiency 20–29 ng/mg and vitamin D deficiency <20 ng/mL. Predictors for LTBI were analyzed.ResultsA total of 287 participants were enrolled. The suboptimal vitamin D level was 31.4% (90/287), which including the vitamin D deficiency was 13.9% (40/287). A total of 49.1% (141/287) people received nutritional vitamin D supplementation. The prevalence of IGRA positivity in this study was 25.1% (72/287). There was no significant difference in vitamin D concentrations or the proportion of vitamin D supplementation among the IGRA-positive and IGRA-negative groups (p = 0.789 and 0.496, respectively). In multivariate analysis, age >65 years old (odds ratio (OR), 1.89; 95% CI, 1.08–3.31; p = 0.026) and TB history (OR, 3.51; 95% CI, 1.38–8.91; p = 0.008) were independent predictors of IGRA positivity.ConclusionThis is the first study to report that vitamin D deficiency was not associated with IGRA positivity in a hemodialysis population. Aging and TB history were both independent predictors for LTBI.     

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.     

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.