The scavenging capacity of DMBT1 is impaired by germline deletions.

The Scavenger Receptor Cysteine-Rich (SRCR) proteins are an archaic group of proteins characterized by the presence of multiple SRCR domains. They are membrane-bound or secreted proteins, which are generally related to host defense systems in animals. Deleted in Malignant Brain Tumors 1 (DMBT1) is a SRCR protein which is secreted in mucosal fluids and involved in host defense by pathogen binding by its SRCR domains. Genetic polymorphism within DMBT1 leads to DMBT1-alleles giving rise to polypeptides with interindividually different numbers of SRCR domains, ranging from 8 SRCR domains (encoded by 6 kb DMBT1 variant) to 13 SRCR domains (encoded by the 8 kb DMBT1 variant). In the present study, we have investigated whether reduction from 13 to 8 amino-terminal SRCR domains leads to reduction of bacterial binding. The 6 kb variant bound ~20-45% less bacteria compared to the 8 kb variant. These results support the hypothesis that genetic variation in DMBT1 may influence microbial defense.

DMBT1 functions as pattern-recognition molecule for poly-sulfated and poly-phosphorylated ligands.

Deleted in malignant brain tumors 1 (DMBT1) is a secreted glycoprotein displaying a broad bacterial-binding spectrum. Recent functional and genetic studies linked DMBT1 to the suppression of LPS-induced TLR4-mediated NF-kappaB activation and to the pathogenesis of Crohn's disease. Here, we aimed at unraveling the molecular basis of its function in mucosal protection and of its broad pathogen-binding specificity. We report that DMBT1 directly interacts with dextran sulfate sodium (DSS) and carrageenan, a structurally similar sulfated polysaccharide, which is used as a texturizer and thickener in human dietary products. However, binding of DMBT1 does not reduce the cytotoxic effects of these agents to intestinal epithelial cells in vitro. DSS and carrageenan compete for DMBT1-mediated bacterial aggregation via interaction with its bacterial-recognition motif. Competition and ELISA studies identify poly-sulfated and poly-phosphorylated structures as ligands for this recognition motif, such as heparansulfate, LPS, and lipoteichoic acid. Dose-response studies in Dmbt1(-/-) and Dmbt1(+/+) mice utilizing the DSS-induced colitis model demonstrate a differential response only to low but not to high DSS doses. We propose that DMBT1 functions as pattern-recognition molecule for poly-sulfated and poly-phosphorylated ligands providing a molecular basis for its broad bacterial-binding specificity and its inhibitory effects on LPS-induced TLR4-mediated NF-kappaB activation.

In vitro-targeted gene identification in patients with hepatitis C using a genome-wide microarray technology.

UNLABELLED: Iron in association with reactive oxygen species (ROS) is highly toxic, aggravating oxidative stress reactions. Increased iron not only plays an important role in the progression of hereditary hemochromatosis (HH) but also in common liver diseases such as chronic hepatitis C. The underlying mechanisms of hepatitis C virus (HCV)-mediated iron accumulation, however, are poorly understood. We introduce an in vitro-targeted approach to identify ROS/iron-regulated genes in patients with HCV using a genome-wide DNA microarray. The sensitivity of the 32,231 complementary DNA clone-carrying microarray was approximately 20% as estimated by detecting target genes of the genome-wide transcription factor hypoxia inducible factor 1alpha. Upon in vitro challenge to iron and oxidative stress, 265 iron-related and 1326 ROS-related genes could be identified in HepG2 cells; 233 significantly regulated genes were found in patients with mild (HCV) or severe (HH) iron deposition. Notably, 17 of the in vitro-selected genes corresponded to the genes identified in patients with HCV or HH. Among them, natriuretic peptide precursor B (NPPB) was the only iron-regulated gene identified in vitro that was differentially regulated between HCV and HH. Reverse-transcription polymerase chain reaction confirmed most of the microarray-identified genes in an even larger group of patients (n = 12). In patients with HCV, these included genes that are associated with RNA processing (MED9/NFAT, NSUN2), proliferation, differentiation, hypoxia, or iron metabolism (ISG20, MIG6, HIG2, CA9, NDRG1), whereas none of the nine known iron-related genes showed significant differences between HCV and HH. CONCLUSION: Although high-density microarray technology is less suitable for routine liver diagnosis, its use in combination with prior in vitro selection is a powerful approach to identify candidate genes relevant for liver disease.

Differential expression of apoptotic genes PDIA3 and MAP3K5 distinguishes between low- and high-risk prostate cancer.

BACKGROUND: Despite recent progress in the identification of genetic and molecular alterations in prostate cancer, markers associated with tumor progression are scarce. Therefore precise diagnosis of patients and prognosis of the disease remain difficult. This study investigated novel molecular markers discriminating between low and highly aggressive types of prostate cancer. RESULTS: Using 52 microdissected cell populations of low- and high-risk prostate tumors, we identified via global cDNA microarrays analysis almost 1200 genes being differentially expressed among these groups. These genes were analyzed by statistical, pathway and gene enrichment methods. Twenty selected candidate genes were verified by quantitative real time PCR and immunohistochemistry. In concordance with the mRNA levels, two genes MAP3K5 and PDIA3 exposed differential protein expression. Functional characterization of PDIA3 revealed a pro-apoptotic role of this gene in PC3 prostate cancer cells. CONCLUSIONS: Our analyses provide deeper insights into the molecular changes occurring during prostate cancer progression. The genes MAP3K5 and PDIA3 are associated with malignant stages of prostate cancer and therefore provide novel potential biomarkers.

Down-regulation of HLA Class I and NKG2D ligands through a concerted action of MAPK and DNA methyltransferases in colorectal cancer cells.

Most malignant features of cancer cells are triggered by activated oncogenes and the loss of tumor suppressors due to mutation or epigenetic inactivation. It is still unclear, to what extend the escape of emerging cancer cells from recognition and elimination by the immune system is determined by similar mechanisms. We compared the transcriptomes of HCT116 colorectal cancer cells deficient in DNA methyltransferases (DNMTs) and of cells, in which the RAS pathway as the major growth-promoting signaling system is blocked by inhibition of MAPK. We identified the MHC Class I genes HLA-A1/A2 and the ULBP2 gene encoding 1 of the 8 known ligands of the activating NK receptor NKG2D among a cluster of immune genes up-regulated under the conditions of both DNMT-deficiency and MEK-inhibition. Bisulphite sequencing analyses of HCT116 with DNMT deficiency or after MEK-inhibition showed that de-methylation of the ULPB2 promoter correlated with its enhanced surface expression. The HLA-A promoters were not methylated indicating that components of the HLA assembly machinery were also suppressed in DNMT-deficient and MEK-inhibited cells. Increased HLA-A2 surface expression was correlated with enhanced recognition and lysis by A2-specific CTL. On the contrary, elevated ULBP2 expression was not reflected by enhanced recognition and lysis by NK cells. Cosuppression of HLA Class I and NKG2D ligands and genes encoding peptide transporters or proteasomal genes mediates a strong functional link between RAS activation, DNMT activity and disruption of the antigen presenting system controlling immune recognition in colorectal cancer cells.

Effects of infiltrating lymphocytes and estrogen receptor on gene expression and prognosis in breast cancer.

The involvement of the immune system for the course of breast cancer, as evidenced by varying degrees of lymphocyte infiltration (LI) into the tumor is still poorly understood. The aim of this study was to evaluate the prognostic value of LI in breast cancer samples using microarray-based screening for LI-associated genes. Starting from the observation that most published ER gene signatures are heavily influenced by the LI effect, we developed and applied a novel approach to dissect molecular signatures. Further, a meta-analysis encompassing 1,044 hybridizations showed that LI alone is not sufficient to highlight breast cancer patients with different prognosis. However, for ER positive patients, high LI was associated with shorter survival times, whereas for ER negative patients, high LI is significantly associated with longer survival. Annotation of LI, in addition to ER status, is important for breast cancer patient prognosis and may have implications for the future treatment of breast cancer.

Estimating large-scale signaling networks through nested effect models with intervention effects from microarray data.

MOTIVATION: Targeted interventions using RNA interference in combination with the measurement of secondary effects with DNA microarrays can be used to computationally reverse engineer features of upstream non-transcriptional signaling cascades based on the nested structure of effects. RESULTS: We extend previous work by Markowetz et al., who proposed a statistical framework to score different network hypotheses. Our extensions go in several directions: we show how prior assumptions on the network structure can be incorporated into the scoring scheme by defining appropriate prior distributions on the network structure as well as on hyperparameters. An approach called module networks is introduced to scale up the original approach, which is limited to around 5 genes, to infer large-scale networks of more than 30 genes. Instead of the data discretization step needed in the original framework, we propose the usage of a beta-uniform mixture distribution on the P-value profile, resulting from differential gene expression calculation, to quantify effects. Extensive simulations on artificial data and application of our module network approach to infer the signaling network between 13 genes in the ER-alpha pathway in human MCF-7 breast cancer cells show that our approach gives sensible results. Using a bootstrapping and a jackknife approach, this reconstruction is found to be statistically stable. AVAILABILITY: The proposed method is available within the Bioconductor R-package nem.

Predicting pathway membership via domain signatures.

MOTIVATION: Functional characterization of genes is of great importance for the understanding of complex cellular processes. Valuable information for this purpose can be obtained from pathway databases, like KEGG. However, only a small fraction of genes is annotated with pathway information up to now. In contrast, information on contained protein domains can be obtained for a significantly higher number of genes, e.g. from the InterPro database. RESULTS: We present a classification model, which for a specific gene of interest can predict the mapping to a KEGG pathway, based on its domain signature. The classifier makes explicit use of the hierarchical organization of pathways in the KEGG database. Furthermore, we take into account that a specific gene can be mapped to different pathways at the same time. The classification method produces a scoring of all possible mapping positions of the gene in the KEGG hierarchy. Evaluations of our model, which is a combination of a SVM and ranking perceptron approach, show a high prediction performance. Moreover, for signaling pathways we reveal that it is even possible to forecast accurately the membership to individual pathway components. AVAILABILITY: The R package gene2pathway is a supplement to this article.

Global gene expression analysis reveals specific patterns of cell junctions in non-small cell lung cancer subtypes.

Non-small cell lung cancer (NSCLC) can be classified into the major subtypes adenocarcinoma (AC) and squamous cell carcinoma (SCC). Although explicit molecular, histological and clinical characteristics have been reported for both subtypes, no specific therapy exists so far. However, the characterization of suitable molecular targets holds great promises to develop novel therapies in NSCLC. In the present study, global gene expression profiling of 58 human NSCLC specimens revealed large transcriptomic differences between AC and SCC subtypes: more than 1700 genes were found to be differentially expressed. The assignment of these genes to biological processes pointed to the deregulation of distinct sets of genes coding for cell junctions in both tumor subtypes. We focused on 17 cell adhesion genes and 11 reported marker genes for epithelial-mesenchymal transition (EMT), and investigated their expression in matched tumor-normal specimens by quantitative real-time PCR. The majority of the cell adhesion genes was significantly up-regulated in at least one tumor subtype compared to normal tissue, predominantly desmosomes and gap junctions in SCC, and tight junctions in AC. The higher expression of EMT marker transcripts in tumor specimens suggested a large potential for invasion and migration processes in NSCLC. Our results indicate that AC and SCC in the lung are characterized by the expression of distinct sets of cell adhesion molecules which may represent promising targets for novel specific therapies.

DMBT1 expression distinguishes anorectal from cutaneous melanoma.

AIMS: Anorectal melanoma (AM) forms a rare but highly malignant subset of mucosal melanoma with an extremely poor prognosis. Although AMs display histological and immunohistochemical features very similar to cutaneous melanoma (CM), no association exists either with exposure to ultraviolet light or with melanocytic naevi. While AMs are clearly distinguished from CM by displaying few BRAF mutations, they are commonly indistinguishable from CM at the level of gene expression. The aim was to carry out expression analyses of classical immunohistochemical markers and of the protein deleted in malignant brain tumours 1 (DMBT1) in cases of primary anorectal malignant melanoma and CM. METHODS AND RESULTS: Expression analyses of classical immunohistochemical markers (S100, HMB45, Melan A and MiTF) and of the protein DMBT1 were carried out in 27 cases of primary anorectal malignant melanoma and 26 cases of CM. All AM cases analysed showed expression of at least three of the classical markers for melanoma. However, immunohistochemistry showed 19 out of 27 AM to be positive for DMBT1, which represented a statistically significant difference (P = 0.0009) compared with CM (six out of 26), which more commonly are negative for DMBT1 expression. CONCLUSION: These results identify DMBT1 as a molecular feature that may allow distinction between AM and CM and support the notion that AM represents an entity molecularly distinct from CM.

FARP2, HDLBP and PASK are downregulated in a patient with autism and 2q37.3 deletion syndrome.

We describe a patient with autism and brachymetaphalangy, meeting criteria for 2q37 deletion syndrome (also called Albright Hereditary Osteodystrophy-like syndrome or Brachydactyly-Mental Retardation syndrome, OMIM 600430). Our molecular cytogenetic studies, including array comparative genomic hybridization (aCGH) and fluorescence in situ hybridization (FISH), define the extent of the de novo deletion to a 3.5 Mb region on 2q37.3. Although a number of reports of patients with 2q37 deletion syndrome have been published, it remains unclear if gene expression and/or translation are altered by the deletion, thus contributing to the observed phenotypes. To address this question, we selected several candidate genes for the neuropsychiatric and skeletal anomalies found in this patient (autism and brachymetaphalangy). The deleted region in 2q37.3 includes the FERM, RhoGEF and pleckstrin domain protein 2 (FARP2), glypican 1 (GPC1), vigilin (HDLBP), kinesin family member 1A (KIF1A) and proline-alanine-rich STE20-related kinase (PASK), all of which are involved in skeletal or neural differentiation processes. Expression analyses of these genes were performed using RNA from lymphoblastoid cell lines of the patient and his family members. Here we demonstrate that three of these genes, FARP2, HDLBP, and PASK, are considerably downregulated in the patient's cell line. We hypothesize that haploinsufficiency of these genes may have contributed to the patient's clinical phenotype.

Contact spotting of protein microarrays coupled with spike-in of normalizer protein permits time-resolved analysis of ERBB receptor signaling.

Protein microarrays allow highly accurate comparison and quantification of numerous biological samples in parallel while requiring only little material. This qualifies protein arrays for systems biology and clinical research where only limited sample material is available, but a precise readout is required. With the introduction of signal normalization steps to monitor the drop size of manually contact-spotted RP protein arrays, the usefulness of normalizer proteins to ensure a high-throughput but inexpensive protein analysis was demonstrated. This approach was applied for the analysis of signaling through ERBB receptor activated kinases in the breast cancer cell line MCF-7. Activation of ERK1/2 and AKT by ERBB1 (EGFR), ERRB2 (HER2/neu), and ERBB3-4 was monitored in a time-resolved manner. Analysis of pathway activation by stimulation with epidermal growth factor and heregulin, or inhibition by blocking with gefitinib or herceptin allowed a characterization of the distinct signaling properties of the different ERBB receptor subtypes.

Quantitative protein microarrays for time-resolved measurements of protein phosphorylation.

The quantitative analysis of signaling networks requires highly sensitive methods for the time-resolved determination of protein phosphorylation. For this reason, we developed a quantitative protein microarray that monitors the activation of multiple signaling pathways in parallel, and at high temporal resolution. A label-free sandwich approach was combined with near infrared detection, thus permitting the accurate quantification of low-level phosphoproteins in limited biological samples corresponding to less than 50,000 cells, and with a very low standard deviation of approximately 5%. The identification of suitable antibody pairs was facilitated by determining their accuracy and dynamic range using our customized software package Quantpro. Thus, we are providing an important tool to generate quantitative data for systems biology approaches, and to drive innovative diagnostic applications.

Extending pathways based on gene lists using InterPro domain signatures.

BACKGROUND: High-throughput technologies like functional screens and gene expression analysis produce extended lists of candidate genes. Gene-Set Enrichment Analysis is a commonly used and well established technique to test for the statistically significant over-representation of particular pathways. A shortcoming of this method is however, that most genes that are investigated in the experiments have very sparse functional or pathway annotation and therefore cannot be the target of such an analysis. The approach presented here aims to assign lists of genes with limited annotation to previously described functional gene collections or pathways. This works by comparing InterPro domain signatures of the candidate gene lists with domain signatures of gene sets derived from known classifications, e.g. KEGG pathways. RESULTS: In order to validate our approach, we designed a simulation study. Based on all pathways available in the KEGG database, we create test gene lists by randomly selecting pathway genes, removing these genes from the known pathways and adding variable amounts of noise in the form of genes not annotated to the pathway. We show that we can recover pathway memberships based on the simulated gene lists with high accuracy. We further demonstrate the applicability of our approach on a biological example. CONCLUSION: Results based on simulation and data analysis show that domain based pathway enrichment analysis is a very sensitive method to test for enrichment of pathways in sparsely annotated lists of genes. An R based software package domainsignatures, to routinely perform this analysis on the results of high-throughput screening, is available via Bioconductor.

Genomic analysis reveals poor separation of human cardiomyopathies of ischemic and nonischemic etiologies.

Clinically, the differentiation between ischemic (ICM) and nonischemic (NICM) human cardiomyopathies is highly relevant, because ICM and NICM differ with respect to prognosis and certain aspects of pharmacological therapy, despite a common final phenotype characterized by ventricular dilatation and reduced contractility. So far, it is unclear whether microarray-based signatures can be used to infer the etiology of heart failure. Using three different classification algorithms, we independently analyzed one cDNA and two publicly available high-density oligonucleotide microarray studies comprising a total of 279 end-stage human heart failure samples. When classifiers identified in a single study were applied to the remaining studies, misclassification rates >25% for ICM and NICM specimens were noted, indicating poor separation of both etiologies. However, data mining of 458 classifier genes that were concordantly identified in at least two of the three data sets points to different biological processes in ICM vs. NICM. Consistent with the underlying ischemia, cytokine signaling pathways and immediate-early response genes were overrepresented in ICM samples, whereas NICM samples displayed a deregulation of cytoskeletal transcripts, genes encoding for the major histocompatibility complex, and antigen processing and presentation pathways, potentially pointing to immunologic processes in NICM. Overall, our results suggest that ICM and NICM exhibit substantial heterogeneity at the transcriptomic level. Prospective studies are required to test whether etiology-specific gene expression patterns are present at earlier disease stages or in subsets of both etiologies.

DMBT1 confers mucosal protection in vivo and a deletion variant is associated with Crohn's disease.

BACKGROUND & AIMS: Impaired mucosal defense plays an important role in the pathogenesis of Crohn's disease (CD), one of the main subtypes of inflammatory bowel disease (IBD). Deleted in malignant brain tumors 1 (DMBT1) is a secreted scavenger receptor cysteine-rich protein with predominant expression in the intestine and has been proposed to exert possible functions in regenerative processes and pathogen defense. Here, we aimed at analyzing the role of DMBT1 in IBD. METHODS: We studied DMBT1 expression in IBD and normal tissues by quantitative reverse transcription-polymerase chain reaction, immunohistochemistry, and mRNA in situ hybridization. Genetic polymorphisms within DMBT1 were analyzed in an Italian IBD case-control sample. Dmbt1(-/-) mice were generated, characterized, and analyzed for their susceptibility to dextran sulfate sodium-induced colitis. RESULTS: DMBT1 levels correlate with disease activity in inflamed IBD tissues. A highly significant fraction of the patients with IBD displayed up-regulation of DMBT1 specifically in the intestinal epithelial surface cells and Paneth cells. A deletion allele of DMBT1 with a reduced number of scavenger receptor cysteine-rich domain coding exons is associated with an increased risk of CD (P = .00056; odds ratio, 1.75) but not for ulcerative colitis. Dmbt1(-/-) mice display enhanced susceptibility to dextran sulfate sodium-induced colitis and elevated Tnf, Il6, and Nod2 expression levels during inflammation. CONCLUSIONS: DMBT1 may play a role in intestinal mucosal protection and prevention of inflammation. Impaired DMBT1 function may contribute to the pathogenesis of CD.

Identification of aberrant chromosomal regions from gene expression microarray studies applied to human breast cancer.

MOTIVATION: In cancer, chromosomal imbalances like amplifications and deletions, or changes in epigenetic mechanisms like DNA methylation influence the transcriptional activity. These alterations are often not limited to a single gene but affect several genes of the genomic region and may be relevant for the disease status. For example, the ERBB2 amplicon (17q21) in breast cancer is associated with poor patient prognosis. We present a general, unsupervised method for genome-wide gene expression data to systematically detect tumor patients with chromosomal regions of distinct transcriptional activity. The method aims to find expression patterns of adjacent genes with a consistently decreased or increased level of gene expression in tumor samples. Such patterns have been found to be associated with chromosomal aberrations and clinical parameters like tumor grading and thus can be useful for risk stratification or therapy. RESULTS: Our approach was applied to 12 independent human breast cancer microarray studies comprising 1422 tumor samples. We prioritized chromosomal regions and genes predominantly found across all studies. The result highlighted not only regions which are well known to be amplified like 17q21 and 11q13, but also others like 8q24 (distal to MYC) and 17q24-q25 which may harbor novel putative oncogenes. Since our approach can be applied to any microarray study it may become a valuable tool for the exploration of transcriptional changes in diverse disease types. AVAILABILITY: The R source codes which implement the method and an exemplary analysis are available at http://www.dkfz.de/mga2/people/buness/CTP/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Antibody microarrays as an experimental platform for the analysis of signal transduction networks.

A significant bottleneck for the time-resolved and quantitative description of signaling networks is the limited sample capacity and sensitivity of existing methods. Recently, antibody microarrays have emerged as a promising experimental platform for the quantitative and comprehensive determination of protein abundance and protein phosphorylation. This review summarizes the development of microarray applications involving antibody-based capture of target proteins with a focus on quantitative applications. Technical aspects regarding the production of antibody microarrays, identification of suitable detection and capture antibody pairs, signal detection methods, detection limit, and data analysis are discussed in detail.

Automated production of recombinant human proteins as resource for proteome research.

BACKGROUND: An arbitrary set of 96 human proteins was selected and tested to set-up a fully automated protein production strategy, covering all steps from DNA preparation to protein purification and analysis. The target proteins are encoded by functionally uncharacterized open reading frames (ORF) identified by the German cDNA consortium. Fusion proteins were produced in E. coli with four different fusion tags and tested in five different purification strategies depending on the respective fusion tag. The automated strategy relies on standard liquid handling and clone picking equipment. RESULTS: A robust automated strategy for the production of recombinant human proteins in E. coli was established based on a set of four different protein expression vectors resulting in NusA/His, MBP/His, GST and His-tagged proteins. The yield of soluble fusion protein was correlated with the induction temperature and the respective fusion tag. NusA/His and MBP/His fusion proteins are best expressed at low temperature (25 degrees C), whereas the yield of soluble GST fusion proteins was higher when protein expression was induced at elevated temperature. In contrast, the induction of soluble His-tagged fusion proteins was independent of the temperature. Amylose was not found useful for affinity-purification of MBP/His fusion proteins in a high-throughput setting, and metal chelating chromatography is recommended instead. CONCLUSION: Soluble fusion proteins can be produced in E. coli in sufficient qualities and microg/ml culture quantities for downstream applications like microarray-based assays, and studies on protein-protein interactions employing a fully automated protein expression and purification strategy. Future applications might include the optimization of experimental conditions for the large-scale production of soluble recombinant proteins from libraries of open reading frames.

Identification of cellular targets for the human papillomavirus E6 and E7 oncogenes by RNA interference and transcriptome analyses.

Specific types of human papillomaviruses (HPVs) cause cervical cancer, the second most common tumor in women worldwide. Both cellular transformation and the maintenance of the oncogenic phenotype of HPV-positive tumor cells are linked to the expression of the viral E6 and E7 oncogenes. To identify downstream cellular target genes for the viral oncogenes, we silenced endogenous E6 and E7 expression in HPV-positive HeLa cells by RNA interference (RNAi). Subsequently, we assessed changes of the cellular transcriptome by genome-wide microarray analysis. We identified 648 genes, which were either downregulated (360 genes) or upregulated (288 genes), upon inhibition of E6/E7 expression. A large fraction of these genes is involved in tumor-relevant processes, such as apoptosis control, cell cycle regulation, or spindle formation. Others may represent novel cellular targets for the HPV oncogenes, such as a large group of C-MYC-associated genes involved in RNA processing and splicing. Comparison with published microarray data revealed a substantial concordance between the genes repressed by RNAi-mediated E6/E7 silencing in HeLa cells and genes reported to be upregulated in HPV-positive cervical cancer biopsies.