Bone-related genes expressed in advanced malignancies induce invasion and metastasis in a genetically defined human cancer model

We employed a genetically defined human cancer model to investigate the contributions of two genes up-regulated in several cancers to phenotypic changes associated with late stages of tumorigenesis. Specifically, tumor cells expressing two structurally unrelated bone-related genes, osteonectin and osteoactivin, acquired a highly invasive phenotype when implanted intracranially in immunocompromised mice. Mimicking a subset of gliomas, tumor cells invaded brain along blood vessels and developed altered vasculature at the brain-tumor interface, suggesting that production of those two proteins by tumor cells may create a complex relationship between invading tumor and vasculature co-opted during tumor invasion. Interestingly, the same tumor cells formed massive spontaneous metastases when implanted subcutaneously. This dramatic alteration in tumor phenotype indicates that cellular microenvironment plays an important role in defining the specific effects of those gene products in tumor behavior. In vitro examination of tumor cells expressing either osteonectin or osteoactivin revealed that there was no impact on cellular growth or death but increased invasiveness and expression of MMP-9 and MMP-3. Specific pharmacologic inhibitors of MMP-2/9 and MMP-3 blocked the increased in vitro invasion associated with osteoactivin expression, but only MMP-3 inhibition altered the invasive in vitro phenotype mediated by osteonectin. Results from this genetically defined model system are supported by similar findings obtained from several established tumor cell lines derived originally from human patients. In sum, these results reveal that the expression of a single bone-related gene can dramatically alter or modify tumor cell behavior and may confer differential growth characteristics in different microenvironments. Genetically defined human cancer models offer useful tools in functional genomics to define the roles of specific genes in late stages of carcinogenesis.     

Geometric interpretation of gene coexpression network analysis

THE MERGING OF NETWORK THEORY AND MICROARRAY DATA ANALYSIS TECHNIQUES HAS SPAWNED A NEW FIELD: gene coexpression network analysis. While network methods are increasingly used in biology, the network vocabulary of computational biologists tends to be far more limited than that of, say, social network theorists. Here we review and propose several potentially useful network concepts. We take advantage of the relationship between network theory and the field of microarray data analysis to clarify the meaning of and the relationship among network concepts in gene coexpression networks. Network theory offers a wealth of intuitive concepts for describing the pairwise relationships among genes, which are depicted in cluster trees and heat maps. Conversely, microarray data analysis techniques (singular value decomposition, tests of differential expression) can also be used to address difficult problems in network theory. We describe conditions when a close relationship exists between network analysis and microarray data analysis techniques, and provide a rough dictionary for translating between the two fields. Using the angular interpretation of correlations, we provide a geometric interpretation of network theoretic concepts and derive unexpected relationships among them. We use the singular value decomposition of module expression data to characterize approximately factorizable gene coexpression networks, i.e., adjacency matrices that factor into node specific contributions. High and low level views of coexpression networks allow us to study the relationships among modules and among module genes, respectively. We characterize coexpression networks where hub genes are significant with respect to a microarray sample trait and show that the network concept of intramodular connectivity can be interpreted as a fuzzy measure of module membership. We illustrate our results using human, mouse, and yeast microarray gene expression data. The unification of coexpression network methods with traditional data mining methods can inform the application and development of systems biologic methods.     

Activity of β2-adrenergic receptor in oral squamous cell carcinoma is mediated by overexpression of the ADRBK2 gene: a pilot study

The β2-adrenergic receptor is most frequently involved in carcinogenic processes. Earlier studies have established a relation between the β2-adrenergic receptor and various characteristics of cancer including cell proliferation, apoptosis, chemotaxis, metastasis, tumor growth and angiogenesis. Our goal was to determine differential expression of the genes involved in adrenergic receptors using DNA microarrays and to confirm their under- or overexpression using real-time quantitative PCR. Five of the nine genes investigated showed significantly altered expression levels in tumor cells (p < 0.05). The gene product with the highest Z-score (restrictive statistical technique for selection of appropriate genes to study) was ADRBK2. Significantly, most of the overexpressed genes were related to β-adrenergic receptors. Real-time PCR analysis confirmed the up regulation observed in the microarrays, which indicated overexpression in 100% of the tumors. In oral squamous cell carcinomas, malignant cells and surrounding tissue overexpress the ADRBK2 gene.     

Algorithm to find gene expression profiles of deregulation and identify families of disease-altered genes

MOTIVATION: Alteration of gene expression often results in up- or down-regulated genes and the most common analysis strategies look for such differentially expressed genes. However, molecular disease mechanisms typically constitute abnormalities in the regulation of genes producing strong alterations in the expression levels. The search for such deregulation states in the genomic expression profiles will help to identify disease-altered genes better. RESULTS: We have developed an algorithm that searches for the genes which present a significant alteration in the variability of their expression profiles, by comparing an altered state with a control state. The algorithm provides groups of genes and assigns a statistical measure of significance to each group of genes selected. The method also includes a prefilter tool to select genes with a threshold of differential expression that can be set by the user ad casum. The method is evaluated using an experimental set of microarrays of human control and cancer samples from patients with acute promyelocytic leukemia.     

Mixture models for assessing differential expression in complex tissues using microarray data

MOTIVATION: The use of DNA microarrays has become quite popular in many scientific and medical disciplines, such as in cancer research. One common goal of these studies is to determine which genes are differentially expressed between cancer and healthy tissue, or more generally, between two experimental conditions. A major complication in the molecular profiling of tumors using gene expression data is that the data represent a combination of tumor and normal cells. Much of the methodology developed for assessing differential expression with microarray data has assumed that tissue samples are homogeneous. RESULTS: In this paper, we outline a general framework for determining differential expression in the presence of mixed cell populations. We consider study designs in which paired tissues and unpaired tissues are available. A hierarchical mixture model is used for modeling the data; a combination of methods of moments procedures and the expectation-maximization algorithm are used to estimate the model parameters. The finite-sample properties of the methods are assessed in simulation studies; they are applied to two microarray datasets from cancer studies. Commands in the R language can be downloaded from the URL http://www.sph.umich.edu/~ghoshd/COMPBIO/COMPMIX/.     

Drug Repositioning through Systematic Mining of Gene Coexpression Networks in Cancer

Gene coexpression network analysis is a powerful “data-driven” approach essential for understanding cancer biology and mechanisms of tumor development. Yet, despite the completion of thousands of studies on cancer gene expression, there have been few attempts to normalize and integrate co-expression data from scattered sources in a concise “meta-analysis” framework. We generated such a resource by exploring gene coexpression networks in 82 microarray datasets from 9 major human cancer types. The analysis was conducted using an elaborate weighted gene coexpression network (WGCNA) methodology and identified over 3,000 robust gene coexpression modules. The modules covered a range of known tumor features, such as proliferation, extracellular matrix remodeling, hypoxia, inflammation, angiogenesis, tumor differentiation programs, specific signaling pathways, genomic alterations, and biomarkers of individual tumor subtypes. To prioritize genes with respect to those tumor features, we ranked genes within each module by connectivity, leading to identification of module-specific functionally prominent hub genes. To showcase the utility of this network information, we positioned known cancer drug targets within the coexpression networks and predicted that Anakinra, an anti-rheumatoid therapeutic agent, may be promising for development in colorectal cancer. We offer a comprehensive, normalized and well documented collection of >3000 gene coexpression modules in a variety of cancers as a rich data resource to facilitate further progress in cancer research.     

Key genes and pathways in tumor-educated dendritic cells by bioinformatical analysis

Specific tumor microenvironment signaling might prevent the maturation of dendritic cells (DCs) with tolerogenic and immunosuppressive potential accounting for antigen-specific unresponsiveness in the lymphoid organs and in the periphery. In the present study, dendritic cells treated with LLC lung cancer cell or 4T1 breast cancer cell culture supernatants significantly down-regulated the expression of co-stimulatory molecules MHC-II, CD40, CD80, but up-regulated the inhibitory molecule PD-L1/L2, VISTA, and increased the messengerRNA levels of interleukin (IL)-6, arginase I, and IL-10, but decreased tumor necrosis factor-α and IL-12a. RNA was isolated from the dendritic cells with or without tumor supernatant stimulation and RNA sequencing was done. Then the differential expression genes were sorted, the candidate genes were analyzed and pathway enrichment analysis was done, and the associated protein–protein interaction network (PPI) was established. After integrated bioinformatical analysis, 405 (279 up-regulated and 126 down-regulated) consistently differential expression genes were identified. Using gene ontology and pathway analysis, it was found that differential expression genes were mainly enriched in the immune response, cell–cell interaction, hemostasis, and cell surface interactions with the vascular wall. The PPI data demonstrated that 236 nodes were classified with 1072 edges, and the most remarkable three modules involved 53 central node genes associated with cell survival, cell-substrate adhesion, chemotaxis, migration, immune response, and complement receptor mediated signaling pathway. These findings revealed the immune status of dendritic cells in the tumor environment.     

cDNA expression array analysis of DNA repair genes in human glioma cells that lack or express DNA-PK

M059J cells provide the only example of DNA-PKcs (now known as PRKDC) deficiency in a human cell line. M059K cells, derived from the same tumor specimen, express PRKDC protein and activity and, together with M059J, provide a useful model in which to study the role of DNA-PK in cellular responses to DNA-damaging agents. Because these cells are of tumor origin, we used Atlas human cancer cDNA expression arrays to investigate possible differential expression of other DNA repair genes in control and irradiated samples. cDNA array results indicated differential expression of 14 genes. Northern blotting confirmed relatively greater expression of replication factor C 37-kDa subunit mRNA in M059J cells compared to M059K cells and reduced expression of DNA ligase IV compared to ligase III in both cell lines independent of irradiation. These results suggest that other DNA repair proteins are altered in these cell lines and that repair mechanisms predicted from the study of normal tissues may be fundamentally altered in human cancer cells.     

Tumor suppressor gene 14-3-3sigma is down-regulated whereas the proto-oncogene translation elongation factor 1delta is up-regulated in non-small cell lung cancers as identified by proteomic profiling

Lung cancer, a leading cause of cancer deaths, consists of two major groups: small cell lung cancer (SCLC) and nonsmall cell lung cancer (NSCLC) with the NSCLC accounting for approximately 75% cases of lung cancers. It has been suggested that molecular changes including overexpression of oncogenes and decreased expression of tumor suppressor genes are responsible for lung carcinogenesis. In this study, we analyzed protein profiles of four different human NSCLC cell lines compared with normal human bronchial epithelial cells using two-dimensional PAGE and MALDI-TOF mass spectrometry. We identified 12 protein spots with different expressions between the normal and cancer cells. Of these proteins, vimentin, cytokeratin 8, YB-1, PCNA, Nm23, hnRNP A2/B1, and HSP90beta were known to be up-regulated in lung cancers, which is consistent with the current study. We also found that the expression of M-type pyruvate kinase is altered in NSCLC likely due to changes in translational control and/or differential phosphorylation of the protein. Interestingly, the expression of the tumor suppressor gene 14-3-3sigma is down-regulated while that of the proto-oncogene TEF1delta is up-regulated in NSCLC cells. On the basis of these observations and previous studies, we propose that the altered expression of 14-3-3sigma and TEF1delta may be involved in lung carcinogenesis.     

Interactive gene expression pattern in prostate cancer cells exposed to phenolic antioxidants

Dietary phenolic compounds are known to elicite vital cellular responses such as cell cycle arrest, apoptosis and differentiation by activating a cascade of molecular events. As there is an increasing interest to improve the efficacy of these compounds for use as potential chemopreventive agents, we wanted to understand the impact of phenolic compounds on target genes in prostate cancer. In this study we used human cDNA microarrays with 2400 clones consisting of 17 prosite motifs to characterize alterations in gene expression pattern in response to the phenolic antioxidants ellagic acid (EA) and resveratrol (RE). Over a 48-hr exposure of androgen - sensitive LNCaP cells to EA and RE, a total of 593 and 555 genes respectively, showed more than a two fold difference in expression. A distinct set of genes in both EA-and RE-treated cells may represent the signature profile of phenolic antioxidant-induced gene expression in LNCaP cells. Although extensive similarity was found between effects of EA - and RE - responsive genes in prostate cancer cells, out of 246 genes with overlapping responses, 25 genes showed an opposite effect. Quantitative RT-PCR was used to verify and validate the differential expression of selected genes identified from cDNA microarrays. In-depth analysis of the data from this study provided insight into the alterations in the p53 - responsive genes, p300, Apaf-1, NF-kBp50 and p65 and PPAR families of genes, suggesting the activation of multiple signaling pathways that leads to growth inhibition of LNCaP cells. This is a first study to look for changes in a large number of human genes in response to dietary compounds.     

n5-氟尿嘧啶敏感与非敏感的人胃癌BGC-823细胞基因表达谱差异分析

利用化疗药物5-氟尿嘧啶(5-Fu)对胃癌细胞株进行筛选和诱导,建立具有耐药性的胃癌细胞株.与亲代细胞株对比生长特性及基因表达谱,初步探讨胃癌细胞的耐药机制.采用四唑盐比色法（MTT）测定5-Fu 对胃癌细胞株BGC-823的半数抑制浓度（IC50）;根据IC50设计5-Fu剂量,用大剂量的5-Fu逐渐递增间歇给药的方法,反复筛选,获得5株胃癌耐药细胞株.比较耐药细胞株和亲本细胞株的形态和生长特性,继而再用人类肿瘤基因芯片（human cancer arrays）比较测试亲本与耐药细胞株的基因表达谱差异;对其中189个上调基因和133个下调基因采用Gene Ontology中的BP（Biological Process）分析这些基因相关的功能,并用MAS2.0分析这些基因可能涉及的信号通路．结果提示,胃癌细胞株耐药（5-Fu）相关基因可能与转录因子信号转导、TNF受体介导的细胞凋亡和抗凋亡、细胞周期调节、细胞粘附及MAP激酶类的功能相关．对细胞周期、信号转导相关的6个基因采用定量PCR验证,结果与基因表达芯片结果一致．上述结果有利于进一步发现胃癌细胞的耐药基因和相关信号通路,探索抗胃癌治疗的耐药机制．     

Alteration in gene expression profile and biological behavior in human lung cancer cell line NL9980 by nm23-H1 gene silencing

Lung cancer is the leading cause of cancer death in both men and women. Tumor metastasis is an essential aspect of lung cancer progression. nm23-H1 is a metastasis suppressor gene. The molecular mechanism by which nm23-H1 suppresses the metastasis is still unclear. Here, we compared the gene expression profile of human large cell lung cancer cell line NL9980 by nm23-H1 gene silencing with that of negative control cells to comprehensively investigate nm23-H1-mediated changes in gene expression of NL9980 cells. Microarray assay revealed that expression of 733-known genes (1.9%, 733/38,500) were altered in response to nm23-H1 gene silencing, including 466 upregulated genes and 267 downregulated. real-time PCR assay of the expression changes indicated that 81.82% (45/55) of verified genes were consistent with that observed in microarray assay. The upregulated genes included MMP-1, -2, SNAI2, CXCL1, 2, 3, PAI-2, while the downregulated genes included cystatin B, TIMP-2, E-cadherin, centrin-2, all of which have been associated with tumor metastasis. Furthermore, we confirmed by Western blot that the expression of MMP-1 and -2 were significantly increased while that of cystatin B was dramatically decreased in NL9980-nm23-H1 silencing cells. The NL9980-nm23-H1 silencing cells exhibited significantly more S phase growth and invasive ability. Thus, silencing of nm23-H1 gene caused metastasis-related gene expression changes in lung cancer cells. The knockdown of nm23-H1 expression may change the lung cancer cells to a more invasive phenotype through alteration in the expression of a set of genes.     

Activity of β2-adrenergic receptor in oral squamous cell carcinoma is mediated by overexpression of the ADRBK2 gene: a pilot study

Abstract

The β2-adrenergic receptor is most frequently involved in carcinogenic processes. Earlier studies have established a relation between the β2-adrenergic receptor and various characteristics of cancer including cell proliferation, apoptosis, chemotaxis, metastasis, tumor growth and angiogenesis. Our goal was to determine differential expression of the genes involved in adrenergic receptors using DNA microarrays and to confirm their under- or overexpression using real-time quantitative PCR. Five of the nine genes investigated showed significantly altered expression levels in tumor cells (p < 0.05). The gene product with the highest Z-score (restrictive statistical technique for selection of appropriate genes to study) was ADRBK2. Significantly, most of the overexpressed genes were related to β-adrenergic receptors. Real-time PCR analysis confirmed the up regulation observed in the microarrays, which indicated overexpression in 100% of the tumors. In oral squamous cell carcinomas, malignant cells and surrounding tissue overexpress the ADRBK2 gene.     

Tumor progression--targets for differential therapy

Differential killing of the patient's cancer cells versus normal cells is a necessity for chemotherapy. Advantage can be taken of close regulations of gene expression and of enzyme activity that are essential for normal cell functioning, and that are altered during tumor progression. Summarized here is our research on four such progression changes of cancer cells; some deregulate proliferation control and others decrease programmed death (apoptosis). These processes will be illustrated with examples of potential chemotherapies based on them. Methods for discovery of such changes include Differential Display and microarrays.     

Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues

A critical and difficult part of studying cancer with DNA microarrays is data interpretation. Besides the need for data analysis algorithms, integration of additional information about genes might be useful. We performed genome-wide expression profiling of 36 types of normal human tissues and identified 2503 tissue-specific genes. We then systematically studied the expression of these genes in cancers by reanalyzing a large collection of published DNA microarray datasets. We observed that the expression level of liver-specific genes in hepatocellular carcinoma (HCC) correlates with the clinically defined degree of tumor differentiation. Through unsupervised clustering of tissue-specific genes differentially expressed in tumors, we extracted expression patterns that are characteristic of individual cell types, uncovering differences in cell lineage among tumor subtypes. We were able to detect the expression signature of hepatocytes in HCC, neuron cells in medulloblastoma, glia cells in glioma, basal and luminal epithelial cells in breast tumors, and various cell types in lung cancer samples. We also demonstrated that tissue-specific expression signatures are useful in locating the origin of metastatic tumors. Our study shows that integration of each gene's breadth of expression (BOE) in normal tissues is important for biological interpretation of the expression profiles of cancers in terms of tumor differentiation, cell lineage, and metastasis.     

Diagnostic significance of coexpression of intermediate filaments in fine needle aspirates of human tumors

A study was undertaken of the diagnostic significance of the coexpression of intermediate filaments in fine needle aspirates of human tumors. Three types of coexpression were found: (1) true coexpression, in which tumor cells simultaneously express more than one intermediate filament protein; (2) pseudocoexpression, in which various tumor cell types from histogenetically different parts of a complex tumor show different results; and (3) false coexpression, in which tumor cells with one or two types of intermediate filaments are present together with benign cells expressing a different filament type. True coexpression of vimentin and keratin was documented in renal cell carcinomas, endometrial carcinomas, certain thyroid carcinomas and Hürthle cell adenomas. Coexpression of keratin and neurofilaments was seen in Merkel cell carcinomas, and coexpression of desmin and vimentin was found in leiomyosarcomas. Keratin, vimentin and neurofilament expression was seen in medullary thyroid carcinomas, and keratin, vimentin and glial fibrillary acidic protein expression was observed in pleomorphic adenomas of the salivary gland. Pseudocoexpression was noted in synovial sarcoma, epithelioid sarcoma, benign cystosarcoma phyllodes of the breast, teratocarcinoma, malignant granular cell tumor, progonoma, Wilms' tumor and triton tumor. Sources of false coexpression are also discussed.