Effect of TLR4/MyD88/NF‐kB axis in paraventricular nucleus on ventricular arrhythmias induced by sympathetic hyperexcitation in post‐myocardial infarction rats

Sympathetic activation after myocardial infarction (MI) leads to ventricular arrhythmias (VAs), which can result in sudden cardiac death (SCD). The toll‐like receptor 4 (TLR4)/myeloid differentiation primary response 88 (MyD88)/nuclear factor‐kappa B (NF‐kB) axis within the hypothalamic paraventricular nucleus (PVN), a cardiac‐neural sympathetic nerve centre, plays an important role in causing VAs. An MI rat model and a PVN‐TLR4 knockdown model were constructed. The levels of protein were detected by Western blotting and immunofluorescence, and localizations were visualized by multiple immunofluorescence staining. Central and peripheral sympathetic activation was visualized by immunohistochemistry for c‐fos protein, renal sympathetic nerve activity (RSNA) measurement, heart rate variability (HRV) analysis and norepinephrine (NE) level detection in serum and myocardial tissue measured by ELISA. The arrhythmia scores were measured by programmed electrical stimulation (PES), and cardiac function was detected by the pressure–volume loop (P‐V loop). The levels of TLR4 and MyD88 and the nuclear translocation of NF‐kB within the PVN were increased after MI, while sympathetic activation and arrhythmia scores were increased and cardiac function was decreased. However, inhibition of TLR4 significantly reversed these conditions. PVN‐mediated sympathetic activation via the TLR4/MyD88/NF‐kB axis ultimately leads to the development of VAs after MI.     

Identification,Design and Bio-Evaluation of Novel Hsp90 Inhibitors by Ligand-Based Virtual Screening

Heat shock protein 90 (Hsp90), whose inhibitors have shown promising activity in clinical trials, is an attractive anticancer target. In this work, we first explored the significant pharmacophore features needed for Hsp90 inhibitors by generating a 3D-QSAR pharmacophore model. It was then used to virtually screen the SPECS databases, identifying 17 hits. Compound S1 and S13 exhibited the most potent inhibitory activity against Hsp90, with IC₅₀ value 1.61±0.28 μM and 2.83±0.67 μM, respectively. Binding patterns analysis of the two compounds with Hsp90 revealed reasonable interaction modes. Further evaluation showed that the compounds exhibited good anti-proliferative effects against a series of cancer cell lines with high expression level of Hsp90. Meanwhile, S13 induced cell apoptosis in a dose-dependent manner in different cell lines. Based on the consideration of binding affinities, physicochemical properties and toxicities, 24 derivatives of S13 were designed, leading to the more promising compound S40, which deserves further optimization.     

Identification of cancer hallmark‐associated gene and lncRNA cooperative regulation pairs and dictate lncRNA roles in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the most common malignant tumour in the oral and maxillofacial region. Numerous cancers share ten common traits (“hallmarks”) that govern the transformation of normal cells into cancer cells. Long non‐coding RNAs (lncRNAs) are important factors that contribute to tumorigenesis. However, very little is known about the cooperative relationships between lncRNAs and cancer hallmark‐associated genes in OSCC. Through integrative analysis of cancer hallmarks, somatic mutations, copy number variants (CNVs) and expression, some OSCC‐specific cancer hallmark‐associated genes and lncRNAs are identified. A computational framework to identify gene and lncRNA cooperative regulation pairs (GLCRPs) associated with different cancer hallmarks is developed based on the co‐expression and co‐occurrence of mutations. The distinct and common features of ten cancer hallmarks based on GLCRPs are characterized in OSCC. Cancer hallmark insensitivity to antigrowth signals and self‐sufficiency in growth signals are shared by most GLCRPs in OSCC. Some key GLCRPs participate in many cancer hallmarks in OSCC. Cancer hallmark‐associated GLCRP networks have complex patterns and specific functions in OSCC. Specially, some key GLCRPs are associated with the prognosis of OSCC patients. In summary, we generate a comprehensive landscape of cancer hallmark‐associated GLCRPs that can act as a starting point for future functional explorations, the identification of biomarkers and lncRNA‐based targeted therapy in OSCC.     

LNRLMI: Linear neighbour representation for predicting lncRNA‐miRNA interactions

LncRNA and miRNA are key molecules in mechanism of competing endogenous RNAs(ceRNA), and their interactions have been discovered with important roles in gene regulation. As supplementary to the identification of lncRNA‐miRNA interactions from CLIP‐seq experiments, in silico prediction can select the most potential candidates for experimental validation. Although developing computational tool for predicting lncRNA‐miRNA interaction is of great importance for deciphering the ceRNA mechanism, little effort has been made towards this direction. In this paper, we propose an approach based on linear neighbour representation to predict lncRNA‐miRNA interactions (LNRLMI). Specifically, we first constructed a bipartite network by combining the known interaction network and similarities based on expression profiles of lncRNAs and miRNAs. Based on such a data integration, linear neighbour representation method was introduced to construct a prediction model. To evaluate the prediction performance of the proposed model, k‐fold cross validations were implemented. As a result, LNRLMI yielded the average AUCs of 0.8475 ± 0.0032, 0.8960 ± 0.0015 and 0.9069 ± 0.0014 on 2‐fold, 5‐fold and 10‐fold cross validation, respectively. A series of comparison experiments with other methods were also conducted, and the results showed that our method was feasible and effective to predict lncRNA‐miRNA interactions via a combination of different types of useful side information. It is anticipated that LNRLMI could be a useful tool for predicting non‐coding RNA regulation network that lncRNA and miRNA are involved in.     

不同病理分期肺腺癌患者血清代谢组学研究

肺癌是当今世界最常见的恶性肿瘤之一,其新发率和死亡率多年来都居于各类癌症之首,其中85%的肺癌都是非小细胞癌,而腺癌又是最常见的非小细胞癌。肺癌的高隐匿性是造成其高死亡率的最主要原因,因此为肺癌的早期诊断和病理分期寻求高效可靠的方法是十分必要的。代谢组学揭示了小分子代谢物的一系列变化,反映了生命活动的最终状态,因此也能直接反映疾病不同发展阶段的病理生理变化。本研究利用核磁共振氢谱(1H-NMR),对在我院就诊的27例不同病理分期的肺腺癌患者和13例健康志愿者进行了血清代谢物分析,运用正交偏最小二乘判别分析(OPLS-DA)对1H-NMR数据进行建模,单变量统计分析对模型进行评价。结果表明肺腺癌患者组的血清中有14种代谢物出现明显差异,其中丙酮酸、丙氨酸、NAC1、乳酸、GPC和甘氨酸比起对照组来有显著上升,而葡萄糖、谷氨酰胺、亮氨酸、异亮氨酸、缬氨酸、丙酮、乙酰乙酸和苏氨酸则显著下降。而在不同分期肺腺癌患者间进行比较后发现,异亮氨酸、乙酰乙酸、NAC1和乳酸的变化与肺腺癌的发展有相关性,可能是肺腺癌早期诊断和分期的潜在生物标志物。