乳腺癌致病microRNA调控网络的识别与生物信息学分析

目的:构建并解析乳腺癌致病microRNA(miRNA)调控网络,探究其在乳腺癌发生发展中的调控机制。方法:整合TCGA、ENCODE、Fantom等公共数据库资源,得到miRNA、转录因子和基因候选调控关系数据,结合差异表达、变异系数与PCA,构建乳腺癌miRNA调控网络,解析调控网络的度中心性与聚类系数,使用DAVID进行功能富集分析,构建Cox回归模型作生存曲线。结果:共识别miRNA调控网络262个,其中包含5个显著差异表达miRNA,8个转录因子和130个基因。通过功能富集分析发现这些miRNA靶基因显著参与细胞周期、细胞分化、细胞生长、转移等转录后调控的肿瘤生物进程,并与FoxO信号通路、p53信号通路、基因监测通路等信号通路高度相关。通过分析生存曲线发现hsa-mir-144与hsa-mir-133a-2显著与乳腺癌患者生存相关。结论:识别的乳腺癌致病miRNA调控网络中miRNA之间有相互作用,且网络整体功能不仅受hub网络影响,也受元件自身特性影响,这些miRNA靶基因显著富集于肿瘤相关生物学进程与信号通路中。     

乳腺癌增强子-miRNA调控网络识别与分析

乳腺癌发病率位列女性恶性肿瘤之首.先前研究表明增强子可通过调控miRNA影响肿瘤的发生发展.然而,增强子与miRNA在乳腺癌中形成何种调控网络目前尚不清楚.为了探究乳腺癌中增强子与miRNA形成的调控网络,通过分析 112个乳腺浸润癌样本和104个正常组织样本,共识别了 220对增强子-miRNA调控关系,其中包括22...     

Down-Regulation of Filamin Ainteracting protein 1-like Is Associated with Promoter Methylation and an Invasive Phenotype in Breast,Colon, Lung and Pancreatic Cancers

Identifying key mediators of cancer cell invasion and metastasis is critical to the development of more effective cancer therapies. We previously identified Filamin A interacting protein 1-like (FILIP1L) as an important inhibitor of cell migration and invasion in ovarian cancer. FILIP1L expression was inversely correlated with the invasive potential of ovarian cancer cell lines and ovarian cancer specimens. We also demonstrated that DNA methylation in the FILIP1L promoter was a mechanism by which FILIP1L was down-regulated in ovarian cancer. In our present study, we tested this observation in other cancer histologies: breast, colon, lung and pancreatic cancers. Both mRNA and protein expression of FILIP1L were down-regulated in these cancer cells compared with their normal epithelial cells. As in ovarian cancer, DNA methylation is a mechanism by which FILIP1L is down-regulated in these cancer histologies. Methylation status of the FILIP1L promoter was inversely correlated with FILIP1L expression. Reduced methylation in the FILIP1L promoter following treatment with a DNA demethylating agent was associated with restoration of FILIP1L expression in these cancer cells. Further, FILIP1L expression was inversely correlated with the invasive potential of these cancer cells. Re-expression of FILIP1L in FILIP1L-low expressing, highly-invasive cancer cell lines resulted in inhibition of cell invasion. Correspondingly, knockdown of FILIP1L in FILIP1L-high expressing, low-invasive cancer cell lines resulted in increase of cell invasion. Overall, these findings suggest that down-regulation of FILIP1L associated with DNA methylation is related with the invasive phenotype in various cancers. Thus, modulation of FILIP1L expression has the potential to be a target for cancer therapy.     

Electron Spin Resonance Studies of Nitrosyl Haemoglobin in Human Liver, Colon and Stomach Tumour Tissues

Iron nitrosyl haemoglobin (HbFeNO) gives well defined ESR spectra, and can be detected at room temperature, in contrast with most transition metal complexes of biological importance. This is because the unpaired electron remains strongly localised on the NO ligand. It is of importance because it proves the formation of nitric oxide, which unfortunately cannot be detected directly by ESR spectroscopy. We have studied a range of tissues taken from human liver, colon and stomach tumours which have been directly frozen to 77K and studied at 77K. The results show that formation of HbFeNO is rare in tissue adjacent to tumour tissue (“peripheral tissue”), but is always found in necrotic central regions, if present. However, in several cases, HbFeNO was also detected in tumour tissue which was not necrotic. Two factors contribute to the formation of this complex. One is the presence of “free” NO molecules in the cellular regions, and the other is the presence of deoxyferrohaemoglobin, since neither ferrihaemoglobin nor oxyhaemoglobin react to give this complex. [For systems containing myoglobin these comments include the possibility of the formation of nitrosylmyoglobin, which gives very similar ESR spectra.]     

Urinary Nucleosides as Biomarkers of Breast,Colon, Lung,and Gastric Cancer in Taiwanese

Urinary nucleosides are associated with many types of cancer. In this study, six targeted urinary nucleosides, namely adenosine, cytidine, 3-methylcytidine, 1-methyladenosine, inosine, and 2-deoxyguanosine, were chosen to evaluate their role as biomarkers of four different types of cancer: lung cancer, gastric cancer, colon cancer, and breast cancer. Urine samples were purified using solid-phase extraction (SPE) and then analyzed using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The Mann-Whitney U test and Principal Component Analysis (PCA) were used to compare differences in urinary nucleosides between patients with one of four types of cancer and healthy controls. The diagnostic sensitivity of single nucleosides for different types of cancer ranged from 14% to 69%. In contrast, the diagnostic sensitivity of a set of six nucleosides ranged from 37% to 69%. The false-positive identification rate associated with the set of six nucleosides in urine was less than 2% compared with that of less than 5% for a single nucleoside. Furthermore, combining the set of six urinary nucleosides with carcinoembryonic antigen improved the diagnostic sensitivity for colon cancer. In summary, the study show that a set of six targeted nucleosides is a good diagnostic marker for breast and colon cancers but not for lung and gastric cancers.     

Metabolic Profiles are Principally Different between Cancers of the Liver,Pancreas and Breast

Molecular profiling of primary tumors may facilitate the classification of patients with cancer into more homogenous biological groups to aid clinical management. Metabolomic profiling has been shown to be a powerful tool in characterizing the biological mechanisms underlying a disease but has not been evaluated for its ability to classify cancers by their tissue of origin. Thus, we assessed metabolomic profiling as a novel tool for multiclass cancer characterization. Global metabolic profiling was employed to identify metabolites in paired tumor and non-tumor liver (n=60), breast (n=130) and pancreatic (n=76) tissue specimens. Unsupervised principal component analysis showed that metabolites are principally unique to each tissue and cancer type. Such a difference can also be observed even among early stage cancers, suggesting a significant and unique alteration of global metabolic pathways associated with each cancer type. Our global high-throughput metabolomic profiling study shows that specific biochemical alterations distinguish liver, pancreatic and breast cancer and could be applied as cancer classification tools to differentiate tumors based on tissue of origin.     

Single Nucleotide Polymorphisms of One-Carbon Metabolism and Cancers of the Esophagus,Stomach, and Liver in a Chinese Population

One-carbon metabolism (folate metabolism) is considered important in carcinogenesis because of its involvement in DNA synthesis and biological methylation reactions. We investigated the associations of single nucleotide polymorphisms (SNPs) in folate metabolic pathway and the risk of three GI cancers in a population-based case-control study in Taixing City, China, with 218 esophageal cancer cases, 206 stomach cancer cases, 204 liver cancer cases, and 415 healthy population controls. Study participants were interviewed with a standardized questionnaire, and blood samples were collected after the interviews. We genotyped SNPs of the MTHFR, MTR, MTRR, DNMT1, and ALDH2 genes, using PCR-RFLP, SNPlex, or TaqMan assays. To account for multiple comparisons and reduce the chances of false reports, we employed semi-Bayes (SB) shrinkage analysis. After shrinkage and adjusting for potential confounding factors, we found positive associations between MTHFR rs1801133 and stomach cancer (any T versus C/C, SB odds-ratio [SBOR]: 1.79, 95% posterior limits: 1.18, 2.71) and liver cancer (SBOR: 1.51, 95% posterior limits: 0.98, 2.32). There was an inverse association between DNMT1 rs2228612 and esophageal cancer (any G versus A/A, SBOR: 0.60, 95% posterior limits: 0.39, 0.94). In addition, we detected potential heterogeneity across alcohol drinking status for ORs relating MTRR rs1801394 to esophageal (posterior homogeneity P = 0.005) and stomach cancer (posterior homogeneity P = 0.004), and ORs relating MTR rs1805087 to liver cancer (posterior homogeneity P = 0.021). Among non-alcohol drinkers, the variant allele (allele G) of these two SNPs was inversely associated with the risk of these cancers; while a positive association was observed among ever-alcohol drinkers. Our results suggest that genetic polymorphisms related to one-carbon metabolism may be associated with cancers of the esophagus, stomach, and liver. Heterogeneity across alcohol consumption status of the associations between MTR/MTRR polymorphisms and these cancers indicates potential interactions between alcohol drinking and one-carbon metabolic pathway.     

EGFR Pathway-Based Gene Signatures of Druggable Gene Mutations in Melanoma,Breast, Lung,and Thyroid Cancers

Biochemistry (Moscow) - EGFR, BRAF, PIK3CA, and KRAS genes play major roles in EGFR pathway, and accommodate activating mutations that predict response to many targeted therapeutics. However,...     

Systems Level Analysis and Identification of Pathways and Networks Associated with Liver Fibrosis

Toxic liver injury causes necrosis and fibrosis, which may lead to cirrhosis and liver failure. Despite recent progress in understanding the mechanism of liver fibrosis, our knowledge of the molecular-level details of this disease is still incomplete. The elucidation of networks and pathways associated with liver fibrosis can provide insight into the underlying molecular mechanisms of the disease, as well as identify potential diagnostic or prognostic biomarkers. Towards this end, we analyzed rat gene expression data from a range of chemical exposures that produced observable periportal liver fibrosis as documented in DrugMatrix, a publicly available toxicogenomics database. We identified genes relevant to liver fibrosis using standard differential expression and co-expression analyses, and then used these genes in pathway enrichment and protein-protein interaction (PPI) network analyses. We identified a PPI network module associated with liver fibrosis that includes known liver fibrosis-relevant genes, such as tissue inhibitor of metalloproteinase-1, galectin-3, connective tissue growth factor, and lipocalin-2. We also identified several new genes, such as perilipin-3, legumain, and myocilin, which were associated with liver fibrosis. We further analyzed the expression pattern of the genes in the PPI network module across a wide range of 640 chemical exposure conditions in DrugMatrix and identified early indications of liver fibrosis for carbon tetrachloride and lipopolysaccharide exposures. Although it is well known that carbon tetrachloride and lipopolysaccharide can cause liver fibrosis, our network analysis was able to link these compounds to potential fibrotic damage before histopathological changes associated with liver fibrosis appeared. These results demonstrated that our approach is capable of identifying early-stage indicators of liver fibrosis and underscore its potential to aid in predictive toxicity, biomarker identification, and to generally identify disease-relevant pathways.     

Exome Analysis Reveals Differentially Mutated Gene Signatures of Stage,Grade and Subtype in Breast Cancers

Breast cancers exhibit highly heterogeneous molecular profiles. Although gene expression profiles have been used to predict the risks and prognostic outcomes of breast cancers, the high variability of gene expression limits its clinical application. In contrast, genetic mutation profiles would be more advantageous than gene expression profiles because genetic mutations can be stably detected and the mutational heterogeneity widely exists in breast cancer genomes. We analyzed 98 breast cancer whole exome samples that were sorted into three subtypes, two grades and two stages. The sum deleterious effect of all mutations in each gene was scored to identify differentially mutated genes (DMGs) for this case-control study. DMGs were corroborated using extensive published knowledge. Functional consequences of deleterious SNVs on protein structure and function were also investigated. Genes such as ERBB2, ESP8, PPP2R4, KIAA0922, SP4, CENPJ, PRCP and SELP that have been experimentally or clinically verified to be tightly associated with breast cancer prognosis are among the DMGs identified in this study. We also identified some genes such as ARL6IP5, RAET1E, and ANO7 that could be crucial for breast cancer development and prognosis. Further, SNVs such as rs1058808, rs2480452, rs61751507, rs79167802, rs11540666, and rs2229437 that potentially influence protein functions are observed at significantly different frequencies in different comparison groups. Protein structure modeling revealed that many non-synonymous SNVs have a deleterious effect on protein stability, structure and function. Mutational profiling at gene- and SNV-level revealed differential patterns within each breast cancer comparison group, and the gene signatures correlate with expected prognostic characteristics of breast cancer classes. Some of the genes and SNVs identified in this study show high promise and are worthy of further investigation by experimental studies.     

肺癌组织和肿瘤细胞系中BRG1的表达分析

BRG1（brahma—related gene 1）是进化上高度保守的SWI／SNF染色质重塑复合物的成员之一．研究表明：BRG1具有抑瘤基因的特征,可能与肿瘤的发生发展有关．我们采用RT—PCR、Northern杂交和Western blotting证实：肺腺癌细胞系A549和鼻咽癌细胞系HNE2、HNE3、CNE1中无BRG1的表达,而肺鳞癌细胞系NCI-H520、永生化正常人支气管上皮细胞系HBE和鼻咽癌细胞系HONE1、HNE1、CNE2中有BRG1的表达．同时,通过RT—PCR检测10例肺癌组织标本．发现60％（6／10）的肺癌组织中日RGG1的mRNA水平明显下调,而配对正常肺组织中BRG1的mRNA表达未见改变．对29例肺癌组织和10例配对正常肺组织切片进行免疫组化染色,结果显示：肺癌组织中BRG1蛋白表达的阳性率为37．9％（11／29）,配对正常肺组织中BRG1蛋白表达的阳性率为90％（9／10）,两者的差异有显著性（P〈0．05）．这提示BRG1确实在肺癌组织及多种肿瘤细胞系中表达下调或缺失,在肺癌发病过程中可能起一定的作用．     

乳腺癌转移相关基因的筛选与生物信息学分析

乳腺癌是女性最常见的恶性肿瘤,转移与复发是乳腺癌患者死亡的主要原因. 研究与乳腺癌细胞转移相关的分子靶点对预防乳腺癌术后复发、提高疗效有重要意义. 本研究以3组乳腺癌转移相关的基因表达谱数据(GSE2034, GSE2603, GSE12276)为分析材料,采用GeneSpring软件筛选乳腺癌原发瘤与转移瘤芯片数据的差异表达基因,结合生物信息学工具PATHER、STRING、pSTIING和文献挖掘工具iHOP对差异基因及其相互作用关系进行分析. 结果显示,共筛选出乳腺癌转移共同差异基因147个,其中表达上调93个,表达下调54个. 这些差异基因主要涉及细胞周期与增殖、细胞粘附、细胞迁移、血管形成及信号转导等生物通路和生物过程. 差异基因编码蛋白间的相互作用主要集中在14个蛋白,且在更为复杂的网络图谱中仍可见其中9个基因（CXCR4、MMP1、MMP2、MMP3、CTGF、COL1A1、MEF2C、PTGS2及SPARC）在重要的节点位置. 文献挖掘发现,COL1A1基因可能为新发现的乳腺癌转移候选基因,为乳腺癌转移的发病机制提供新的思路,也为转移性乳腺癌的分子诊断和个体化治疗奠定基础.     

A Method for Serial Tissue Processing and Parallel Analysis of Aberrant Crypt Morphology,Mucin Depletion,and Beta-Catenin Staining in an Experimental Model of Colon Carcinogenesis

The use of architectural and morphological characteristics of cells for establishing prognostic indicators by which individual pathologies are assigned grade and stage is a well-accepted practice. Advances in automated micro- and macroscopic image acquisition and digital image analysis have created new opportunities in the field of prognostic assessment; but, one area in experimental pathology, animal models for colon cancer, has not taken advantage of these opportunities. This situation is primarily due to the methods available to evaluate the colon of the rodent for the presence of premalignant and malignant pathologies. We report a new method for the excision and processing of the entire colon of the rat and illustrate how this procedure permitted the quantitative assessment of aberrant crypt foci (ACF), a premalignant colon pathology, for characteristics consistent with progression to malignancy. ACF were detected by methylene blue staining and subjected to quantitative morphometric analysis. Colons were then restained with high iron diamine–alcian blue for assessment of mucin depletion using an image overlay to associate morphometric data with mucin depletion. The subsequent evaluation of ACF for beta-catenin staining is also demonstrated. The methods described are particularly relevant to the screening of compounds for cancer chemopreventive activity.     

Expressions of ER,PR, HER-2, COX-2, and VEGF in Primary and Relapsed/Metastatic Breast Cancers

In the present study, we evaluated expressions of estrogen receptor (ER), progestin receptor (PR), human epidermal growth factor receptor-2 (HER-2), cyclooxygenase-2 (COX-2), and vascular endothelial growth factor (VEGF) in primary and relapsed/metastatic breast cancers to elucidate the clinical significance of these markers. The markers were evaluated by immunohistochemistry in specimens of 50 patients with primary or metastatic breast cancer. Positive rates of ER were significantly (p = 0.002) higher in primary versus relapsed/metastatic breast cancer (70 vs. 38 %, respectively). The VEGF positive expression rates were also significantly higher in primary versus metastatic cancer (82 vs. 38 %, respectively; p < 0.001). By contrast, positive rates of HER-2 and COX-2 were not significantly different between different types of cancer. COX-2 correlated with HER-2 expression in both primary and relapsed/metastatic focuses of breast cancer. COX-2 also correlated with VEGF expression in primary breast cancer. Expressions of ER, PR, HER2, and COX-2 did not correlate between primary and relapsed/metastatic breast cancers, indicating that the treatment decision should be made according to the status of these markers in relapsed/metastatic focuses. The total change rates of ER, PR, HER-2, COX-2, and VEGF were 26, 18, 10, 30, and 58 %, respectively. In conclusion, HER-2 and COX-2, along with VEGF, appear to play a role in the development and progression of breast cancer. In addition, all of the studied markers may serve as indicators of prognosis.     

牛血清白蛋白胰蛋白酶酶解产物的色谱-质谱联用分析及其三种数据库搜寻鉴定方法的比较

利用反相高效液相色谱 (RP HPLC)和电喷雾串联质谱 (ESI MS MS)联用技术直接对模式蛋白分子 (牛血清白蛋白 ,BSA)的胰蛋白酶酶解产物进行分离和测定 .获得的一系列BSA酶解片段的一级 (MS)和二级 (MS MS)质谱数据经分析软件处理后 ,分别在不同处理和不同参数条件下 ,用 3种不同的方法通过网上蛋白质数据库进行蛋白质搜寻鉴定 .结果显示 ,3种搜寻法都能正确地鉴定该蛋白质 ,其中以利用MS数据的肽质量指纹谱搜寻法 (PMF法 )较为快捷方便 ,但鉴定结果易受数据处理和数据库搜寻鉴定时参数设置等因素的影响 ;利用未解析MS MS数据 (rawMS MSdata)的搜寻法可在较宽的搜寻参数变化范围内获得明确的鉴定结果 ;而借助从头测序 (denovosequencing)结果的序列搜寻法 (sequencequery)则显示出更高的专一性 ,利用较少酶解片段数据就能得到稳定和明确的鉴定结果 ,搜寻参数变化的影响很小 .就酶解条件、数据处理和搜寻参数设置对蛋白质鉴定结果的影响展开详细的讨论 ,为蛋白质组学研究中的数据处理和库搜寻鉴定积累了可借鉴的资料     

Reverse Engineering of Oxygen Transport in the Lung: Adaptation to Changing Demands and Resources through Space-Filling Networks

The space-filling fractal network in the human lung creates a remarkable distribution system for gas exchange. Landmark studies have illuminated how the fractal network guarantees minimum energy dissipation, slows air down with minimum hardware, maximizes the gas- exchange surface area, and creates respiratory flexibility between rest and exercise. In this paper, we investigate how the fractal architecture affects oxygen transport and exchange under varying physiological conditions, with respect to performance metrics not previously studied.We present a renormalization treatment of the diffusion-reaction equation which describes how oxygen concentrations drop in the airways as oxygen crosses the alveolar membrane system. The treatment predicts oxygen currents across the lung at different levels of exercise which agree with measured values within a few percent. The results exhibit wide-ranging adaptation to changing process parameters, including maximum oxygen uptake rate at minimum alveolar membrane permeability, the ability to rapidly switch from a low oxygen uptake rate at rest to high rates at exercise, and the ability to maintain a constant oxygen uptake rate in the event of a change in permeability or surface area. We show that alternative, less than space-filling architectures perform sub-optimally and that optimal performance of the space-filling architecture results from a competition between underexploration and overexploration of the surface by oxygen molecules.