Dexamethasone Influences Human Clock Gene Expression in Bronchial Epithelium and Peripheral Blood Mononuclear Cells in vitro

We determined whether human peripheral blood mononuclear cells (PBMCs) could be used to analyze clock genes by studying their mRNA expressions in human bronchial epithelium (BEAS‐2B) and PBMCs following stimulation by the glucocorticoid homologue dexamethasone (DEX) in vitro. PBMCs were obtained at 10:00 h from two diurnally active (～07:00 to 23:00 h) healthy volunteers and were evaluated for hPer1 mRNA expression following DEX stimulation in vitro using real time‐PCR analysis. DEX stimulation of human BEAS‐2B cells and PBMCs in vitro led to a remarkable increase of hPer1 mRNA. The glucocorticoid rapidly affected the expression of hPer1 mRNA in PBMCs, suggesting that human PBMCs may be a useful surrogate marker for the investigation of drug effects on clock genes.     

Genetic Variants in MUC4 Gene Are Associated with Lung Cancer Risk in a Chinese Population

Mucin MUC4, which is encoded by the MUC4 gene, plays an important role in epithelial cell proliferation and differentiation. Aberrant MUC4 overexpression is associated with invasive tumor proliferation and poor outcome in epithelial cancers. Collectively, the existing evidence suggests that MUC4 has tumor-promoter functions. In this study, we performed a case-control study of 1,048 incident lung cancer cases and 1,048 age- and sex frequency-matched cancer-free controls in a Chinese population to investigate the role of MUC4 gene polymorphism in lung cancer etiology. We identified nine SNPs that were significantly associated with increased lung cancer risk (P = 0.0425 for rs863582, 0.0333 for rs842226, 0.0294 for rs842225, 0.0010 for rs2550236, 0.0149 for rs2688515, 0.0191 for rs 2641773, 0.0058 for rs3096337, 0.0077 for rs859769, and 0.0059 for rs842461 in an additive model). Consistent with these single-locus analysis results, the haplotype analyses revealed an adverse effect of the haplotype “GGC” of rs3096337, rs859769, and rs842461 on lung cancer. Both the haplotype and diplotype “CTGAGC” of rs863582, rs842226, rs2550236, rs842225, and rs2688515 had an adverse effect on lung cancer, which is also consistent with the single-locus analysis. Moreover, we observed statistically significant interactions for rs863582 and rs842461 in heavy smokers. Our results suggest that MUC4 gene polymorphisms and their interaction with smoking may contribute to lung cancer etiology.     

Yin Yang Gene Expression Ratio Signature for Lung Cancer Prognosis

Many studies have established gene expression-based prognostic signatures for lung cancer. All of these signatures were built from training data sets by learning the correlation of gene expression with the patients'' survival time. They require all new sample data to be normalized to the training data, ultimately resulting in common problems of low reproducibility and impracticality. To overcome these problems, we propose a new signature model which does not involve data training. We hypothesize that the imbalance of two opposing effects in lung cancer cells, represented by Yin and Yang genes, determines a patient’s prognosis. We selected the Yin and Yang genes by comparing expression data from normal lung and lung cancer tissue samples using both unsupervised clustering and pathways analyses. We calculated the Yin and Yang gene expression mean ratio (YMR) as patient risk scores. Thirty-one Yin and thirty-two Yang genes were identified and selected for the signature development. In normal lung tissues, the YMR is less than 1.0; in lung cancer cases, the YMR is greater than 1.0. The YMR was tested for lung cancer prognosis prediction in four independent data sets and it significantly stratified patients into high- and low-risk survival groups (p = 0.02, HR = 2.72; p = 0.01, HR = 2.70; p = 0.007, HR = 2.73; p = 0.005, HR = 2.63). It also showed prediction of the chemotherapy outcomes for stage II & III. In multivariate analysis, the YMR risk factor was more successful at predicting clinical outcomes than other commonly used clinical factors, with the exception of tumor stage. The YMR can be measured in an individual patient in the clinic independent of gene expression platform. This study provided a novel insight into the biology of lung cancer and shed light on the clinical applicability.     

NDRG2基因启动子甲基化与肺腺癌细胞中mRNA表达相关性的实验研究

目的:探讨肺腺癌细胞中NDRG2基因启动子甲基化状态及其与基因表达的关系。方法:甲基化焦磷酸测序技术检测启动子区域甲基化状态,荧光定量PCR技术检测不同药物浓度下培养细胞中NDRG2基因mRNA的表达水平,分析启动子区域甲基化与基因表达之间的关系。结果:在体外培养细胞中检测到NDRG2基因启动子区域呈现不同程度的甲基化,甲基化频率分别为肺癌A549细胞71.8%、GLC-82细胞86.1%、人脐静脉内皮ECV-304细胞36.8%、胃上皮GES-1细胞42.9%。NDRG2基因mRNA表达与其启动子甲基化程度成反比,甲基转移酶抑制剂5-杂氮-2-脱氧胞苷(5-Aza-CdR)作用于细胞后,A549和GLC-82细胞中NDRG2基因的mRNA转录明显上调,至72 h差异显著(P0.05)。结论:肺腺癌细胞中NDRG2基因启动子CpG岛存在高甲基化,甲基化程度与该基因的表达具有负相关性,5-Aza-CdR能在一定程度上提高NDRG2的转录水平。     

寒冷刺激支气管上皮细胞产生外泌体促肺成纤维细胞表达气道重塑相关因子

外泌体可由多种细胞分泌,是具有多种生物学功能的细胞外囊泡,但其在气道重塑中的作用尚不明确。为探讨经寒冷刺激的人支气管上皮细胞（BEAS-2B）分泌的外泌体对人胚肺成纤维细胞(HLF1)气道重塑相关因子表达的影响,收集BEAS-2B细胞株培养液提取外泌体,利用透射电镜及Western印迹对外泌体进行其大小、形态及标志性蛋白的检测;提取的外泌体与HLF1共同培育,分别设置空白对照组、正常对照组（加入未作干预的BEAS 2B细胞所产的外泌体）及寒冷刺激组（加入经寒冷刺激后的BEAS-2B细胞所产的外泌体）。运用Real-time-PCR及Western印迹技术,分别检测各组HLF1表达FGF-2、TNF-α、MMP-9的mRNA及蛋白情况。结果显示,提取BEAS-2B细胞分泌的外泌体为直径小于100 nm的圆形或椭圆形结构,并表达外泌体标志性蛋白CD9、TSG101、ALIX;寒冷刺激组24 h后,其FGF-2、TNF-α、MMP-9的mRNA及蛋白表达均显著高于空白对照组及正常对照组（均P<0.05）。本研究结果表明,BEAS-2B细胞能够释放外泌体;经寒冷刺激后的BEAS 2B细胞所释放的外泌体可以携带并传递生物信号,诱导HLF1表达气道重塑相关因子。     

Impact of Natural Genetic Variation on Gene Expression Dynamics

DNA sequence variation causes changes in gene expression, which in turn has profound effects on cellular states. These variations affect tissue development and may ultimately lead to pathological phenotypes. A genetic locus containing a sequence variation that affects gene expression is called an “expression quantitative trait locus” (eQTL). Whereas the impact of cellular context on expression levels in general is well established, a lot less is known about the cell-state specificity of eQTL. Previous studies differed with respect to how “dynamic eQTL” were defined. Here, we propose a unified framework distinguishing static, conditional and dynamic eQTL and suggest strategies for mapping these eQTL classes. Further, we introduce a new approach to simultaneously infer eQTL from different cell types. By using murine mRNA expression data from four stages of hematopoiesis and 14 related cellular traits, we demonstrate that static, conditional and dynamic eQTL, although derived from the same expression data, represent functionally distinct types of eQTL. While static eQTL affect generic cellular processes, non-static eQTL are more often involved in hematopoiesis and immune response. Our analysis revealed substantial effects of individual genetic variation on cell type-specific expression regulation. Among a total number of 3,941 eQTL we detected 2,729 static eQTL, 1,187 eQTL were conditionally active in one or several cell types, and 70 eQTL affected expression changes during cell type transitions. We also found evidence for feedback control mechanisms reverting the effect of an eQTL specifically in certain cell types. Loci correlated with hematological traits were enriched for conditional eQTL, thus, demonstrating the importance of conditional eQTL for understanding molecular mechanisms underlying physiological trait variation. The classification proposed here has the potential to streamline and unify future analysis of conditional and dynamic eQTL as well as many other kinds of QTL data.     

Dysfunctions Associated with Methylation, MicroRNA Expression and Gene Expression in Lung Cancer

Integrating high-throughput data obtained from different molecular levels is essential for understanding the mechanisms of complex diseases such as cancer. In this study, we integrated the methylation, microRNA and mRNA data from lung cancer tissues and normal lung tissues using functional gene sets. For each Gene Ontology (GO) term, three sets were defined: the methylation set, the microRNA set and the mRNA set. The discriminating ability of each gene set was represented by the Matthews correlation coefficient (MCC), as evaluated by leave-one-out cross-validation (LOOCV). Next, the MCCs in the methylation sets, the microRNA sets and the mRNA sets were ranked. By comparing the MCC ranks of methylation, microRNA and mRNA for each GO term, we classified the GO sets into six groups and identified the dysfunctional methylation, microRNA and mRNA gene sets in lung cancer. Our results provide a systematic view of the functional alterations during tumorigenesis that may help to elucidate the mechanisms of lung cancer and lead to improved treatments for patients.     

Genetic Association Between AGPHD1 Variant and Lung Cancer Risk

The knowledge of molecular mechanism that underlies the genetic predisposition to lung cancer is yet limited. Results from previous studies addressing the association of AGPHD1 variant rs8034191 with lung carcinogenesis remain inconclusive. Herein, we combined these data and re-examined the association. We performed a meta-analysis of Asian studies identified through various ways. Using the data collected from each eligible study, we combined the effect estimates (ORs and its 95 % CIs) with the fixed effects model (Mantel–Haenszel method). Statistical analyses were done using STATA software. Data from nine studies (29,290 subjects) carried out in Asian populations were analyzed in this work. There was no overall association between variant rs8034191 and lung cancer risk under the allele frequency model (OR = 1.03, 95 % CI = 0.93–1.13, Pheterogeneity = 0.522). We observed the same associations under other genetic models and in the subgroup analyses by ethnicity and smoking status. Our results indicate that variant rs8034191 in the AGPHD1 gene may not modify the genetic risk of lung cancer in Asian populations.     

Airway Epithelial Expression of TLR5 Is Downregulated in Healthy Smokers and Smokers with Chronic Obstructive Pulmonary Disease

The TLRs are important components of the respiratory epithelium host innate defense, enabling the airway surface to recognize and respond to a variety of insults in inhaled air. On the basis of the knowledge that smokers are more susceptible to pulmonary infection and that the airway epithelium of smokers with chronic obstructive pulmonary disease (COPD) is characterized by bacterial colonization and acute exacerbation of airway infections, we assessed whether smoking alters expression of TLRs in human small airway epithelium, the primary site of smoking-induced disease. Microarrays were used to survey the TLR family gene expression in small airway (10th to 12th order) epithelium from healthy nonsmokers (n = 60), healthy smokers (n = 73), and smokers with COPD (n = 36). Using the criteria of detection call of present (P call) ≥50%, 6 of 10 TLRs (TLRs 1-5 and 8) were expressed. Compared with nonsmokers, the most striking change was for TLR5, which was downregulated in healthy smokers (1.4-fold, p < 10(-10)) and smokers with COPD (1.6-fold, p < 10(-11)). TaqMan RT-PCR confirmed these observations. Bronchial biopsy immunofluorescence studies showed that TLR5 was expressed mainly on the apical side of the epithelium and was decreased in healthy smokers and smokers with COPD. In vitro, the level of TLR5 downstream genes, IL-6 and IL-8, was highly induced by flagellin in TLR5 high-expressing cells compared with TLR5 low-expressing cells. In the context that TLR5 functions to recognize pathogens and activate innate immune responses, the smoking-induced downregulation of TLR5 may contribute to smoking-related susceptibility to airway infection, at least for flagellated bacteria.