Human epidermal growth factor receptor-2 gene amplification in gastric cancer using tissue microarray technology

To assess human epidermal growth factor receptor-2 (HER2)-status in gastric cancer and matched lymph node metastases by immunohistochemistry (IHC) and chromogenic in situ hybridization (CISH).

Serodiagnosis of Echinococcus spp. infection: explorative selection of diagnostic antigens by peptide microarray

BACKGROUND: Production of native antigens for serodiagnosis of helminthic infections is laborious and hampered by batch-to-batch variation. For serodiagnosis of echinococcosis, especially cystic disease, most screening tests rely on crude or purified Echinococcus granulosus hydatid cyst fluid. To resolve limitations associated with native antigens in serological tests, the use of standardized and highly pure antigens produced by chemical synthesis offers considerable advantages, provided appropriate diagnostic sensitivity and specificity is achieved. METHODOLOGY/PRINCIPAL FINDINGS: Making use of the growing collection of genomic and proteomic data, we applied a set of bioinformatic selection criteria to a collection of protein sequences including conceptually translated nucleotide sequence data of two related tapeworms, Echinococcus multilocularis and Echinococcus granulosus. Our approach targeted alpha-helical coiled-coils and intrinsically unstructured regions of parasite proteins potentially exposed to the host immune system. From 6 proteins of E. multilocularis and 5 proteins of E. granulosus, 45 peptides between 24 and 30 amino acids in length were designed. These peptides were chemically synthesized, spotted on microarrays and screened for reactivity with sera from infected humans. Peptides reacting above the cut-off were validated in enzyme-linked immunosorbent assays (ELISA). Peptides identified failed to differentiate between E. multilocularis and E. granulosus infection. The peptide performing best reached 57% sensitivity and 94% specificity. This candidate derived from Echinococcus multilocularis antigen B8/1 and showed strong reactivity to sera from patients infected either with E. multilocularis or E. granulosus. CONCLUSIONS/SIGNIFICANCE: This study provides proof of principle for the discovery of diagnostically relevant peptides by bioinformatic selection complemented with screening on a high-throughput microarray platform. Our data showed that a single peptide cannot provide sufficient diagnostic sensitivity whereas pooling several peptide antigens improved sensitivity; thus combinations of several peptides may lead the way to new diagnostic tests that replace, or at least complement conventional immunodiagnosis of echinococcosis. Our strategy could prove useful for diagnostic developments in other pathogens.

Multiple Lab Comparison of Microarray Platforms

Microarray technology is a powerful tool able to measure RNA expression for thousands of genes at once. Various studies have been published comparing competing platforms with mixed results: some find agreement, others do not. As the number of researchers starting to use microarrays and the number of crossplatform meta-analysis studies rapidly increase, appropriate platform assessments become more important. Here we present results from a comparison study that offers important improvements over those previously described in the literature. In particular, we notice that none of the previously published papers consider differences between labs. For this paper, a consortium of ten labs from the Washington DC/Baltimore (USA) area was formed to compare three heavily used platforms using identical RNA samples: Appropriate statistical analysis demonstrates that relatively large differences exist between labs using the same platform, but that the results from the best performing labs agree rather well. Supplemental material is available from http://www.biostat.jhsph.edu/~ririzarr/techcomp/

On the Synthesis of Microarray Experiments

With many different investigators studying the same disease and with a strong commitment to publish supporting data in the scientific community, there are often many different datasets available for any given disease. Hence there is substantial interest in finding methods for combining these datasets to provide better and more detailed understanding of the underlying biology. We consider the synthesis of different microarray data sets using a random effects paradigm and demonstrate how relatively standard statistical approaches yield good results. We identify a number of important and substantive areas which require further investigation.

An introduction to low-level analysis methods of DNA microarray data

This article gives an overview over the methods used in the low--level analysis of gene expression data generated using DNA microarrays. This type of experiment allows to determine relative levels of nucleic acid abundance in a set of tissues or cell populations for thousands of transcripts or loci simultaneously. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. This includes the design of probes, the experimental design, the image analysis of microarray scanned images, the normalization of fluorescence intensities, the assessment of the quality of microarray data and incorporation of quality information in subsequent analyses, the combination of information across arrays and across sets of experiments, the discovery and recognition of patterns in expression at the single gene and multiple gene levels, and the assessment of significance of these findings, considering the fact that there is a lot of noise and thus random features in the data. For all of these components, access to a flexible and efficient statistical computing environment is an essential aspect.

Development of a genotyping microarray for Usher syndrome

BACKGROUND: Usher syndrome, a combination of retinitis pigmentosa (RP) and sensorineural hearing loss with or without vestibular dysfunction, displays a high degree of clinical and genetic heterogeneity. Three clinical subtypes can be distinguished, based on the age of onset and severity of the hearing impairment, and the presence or absence of vestibular abnormalities. Thus far, eight genes have been implicated in the syndrome, together comprising 347 protein-coding exons. METHODS: To improve DNA diagnostics for patients with Usher syndrome, we developed a genotyping microarray based on the arrayed primer extension (APEX) method. Allele-specific oligonucleotides corresponding to all 298 Usher syndrome-associated sequence variants known to date, 76 of which are novel, were arrayed. RESULTS: Approximately half of these variants were validated using original patient DNAs, which yielded an accuracy of >98%. The efficiency of the Usher genotyping microarray was tested using DNAs from 370 unrelated European and American patients with Usher syndrome. Sequence variants were identified in 64/140 (46%) patients with Usher syndrome type I, 45/189 (24%) patients with Usher syndrome type II, 6/21 (29%) patients with Usher syndrome type III and 6/20 (30%) patients with atypical Usher syndrome. The chip also identified two novel sequence variants, c.400C>T (p.R134X) in PCDH15 and c.1606T>C (p.C536S) in USH2A. CONCLUSION: The Usher genotyping microarray is a versatile and affordable screening tool for Usher syndrome. Its efficiency will improve with the addition of novel sequence variants with minimal extra costs, making it a very useful first-pass screening tool.

Error models for microarray intensities

We derive the additive-multiplicative error model for microarray intensities, and describe two applications. For the detection of differentially expressed genes, we obtain a statistic whose variance is approximately independent of the mean intensity. For the post hoc calibration (normalization) of data with respect to experimental factors, we describe a method for parameter estimation.

Survival Analysis with Large Dimensional Covariates: An Application in Microarray Studies

Use of microarray technology often leads to high-dimensional and low- sample size data settings. Over the past several years, a variety of novel approaches have been proposed for variable selection in this context. However, only a small number of these have been adapted for time-to-event data where censoring is present. Among standard variable selection methods shown both to have good predictive accuracy and to be computationally efficient is the elastic net penalization approach. In this paper, adaptation of the elastic net approach is presented for variable selection both under the Cox proportional hazards model and under an accelerated failure time (AFT) model. Assessment of the two methods is conducted through simulation studies and through analysis of microarray data obtained from a set of patients with diffuse large B-cell lymphoma where time to survival is of interest. The approaches are shown to match or exceed the predictive performance of a Cox-based and an AFT-based variable selection method. The methods are moreover shown to be much more computationally efficient than their respective Cox- and AFT- based counterparts.

Fast DNA serotyping of Escherichia coli by use of an oligonucleotide microarray

Classical antibody-based serotyping of Escherichia coli is an important method in diagnostic microbiology for epidemiological purposes, as well as for a rough virulence assessment. However, serotyping is so tedious that its use is restricted to a few reference laboratories. To improve this situation we developed and validated a genetic approach for serotyping based on the microarray technology. The genes encoding the O-antigen flippase (wzx) and the O-antigen polymerase (wzy) were selected as target sequences for the O antigen, whereas fliC and related genes, which code for the flagellar monomer, were chosen as representatives for the H phenotype. Starting with a detailed bioinformatic analysis and oligonucleotide design, an ArrayTube-based assay was established: a fast and robust DNA extraction method was coupled with a site-specific, linear multiplex labeling procedure and hybridization analysis of the biotinylated amplicons. The microarray contained oligonucleotide DNA probes, each in duplicate, representing 24 of the epidemiologically most relevant of the over 180 known O antigens (O antigens 4, 6 to 9, 15, 26, 52, 53, 55, 79, 86, 91, 101, 103, 104, 111, 113, 114, 121, 128, 145, 157, and 172) as well as 47 of the 53 different H antigens (H antigens 1 to 12, 14 to 16, 18 to 21, 23 to 34, 37 to 43, 45, 46, 48, 49, 51 to 54, and 56). Evaluation of the microarray with a set of defined strains representing all O and H serotypes covered revealed that it has a high sensitivity and a high specificity. All of the conventionally typed 24 O groups and all of the 47 H serotypes were correctly identified. Moreover, strains which were nonmotile or nontypeable by previous serotyping assays yielded unequivocal results with the novel ArrayTube assay, which proved to be a valuable alternative to classical serotyping, allowing processing of single colonies within a single working day.

Microarray based study on virulence-associated genes and resistance determinants of Staphylococcus aureus isolates from cattle

Staphylococcus aureus is a common pathogen which can colonise and infect not only man, but also domestic animals. Especially, infection of cattle is of high economic relevance as S. aureus is an important causal agent of bovine mastitis. In the present contribution, a DNA microarray was applied for the study of 144 different gene targets, including resistance genes and genes encoding exotoxins, in S. aureus isolated from cows. One hundred and twenty-eight isolates from Germany and Switzerland were tested. These isolates were assigned to 20 different strains and nine clonal complexes. The majority of isolates belonged either to apparently closely related clonal complexes 8, 25, and 97 (together 34.4%) or were related to the sequenced bovine strain RF122 (48.4%). Notable characteristics of S. aureus of bovine origin are the carriage of intact haemolysin beta (in 82% of isolates tested), the absence of staphylokinase (in 89.1%), the presence of allelic variants of several exotoxins such as toxic shock syndrome toxin and enterotoxin N, and the occurrence of the leukocidin lukF-P83/lukM (in 53.1%). Two isolates were methicillin-resistant S. aureus (MRSA). One of them was a clonal complex 8 MRSA related to the epidemic MRSA strain Irish 01. The other one belonged to ST398/spa-type 34 resembling a newly emerging MRSA strain which has been described to occur in humans as well as in domestic animals. The presence of these two strains highlights the possibility of transfers of S. aureus strains between different host species.

Generic detection of coronaviruses and differentiation at the prototype strain level by reverse transcription-PCR and nonfluorescent low-density microarray

A nonfluorescent low-cost, low-density oligonucleotide array was designed for detecting the whole coronavirus genus after reverse transcription (RT)-PCR. The limit of detection was 15.7 copies/reaction. The clinical detection limit in patients with severe acute respiratory syndrome was 100 copies/sample. In 39 children suffering from coronavirus 229E, NL63, OC43, or HKU1, the sensitivity was equal to that of individual real-time RT-PCRs.

Clinical significance of cell cycle- and apoptosis-related markers in biliary tract cancer: a tissue microarray-based approach revealing a distinctive immunophenotype for intrahepatic and extrahepatic cholangiocarcinomas

Cholangiocarcinoma is the second most common malignant tumor of the liver. We analyzed, immunohistochemically, the significance of cell cycle- and apoptosis-related markers in 128 cholangiocarcinomas (42 intrahepatic, 70 extrahepatic, and 16 gallbladder carcinomas) combined in a tissue microarray. Follow-up was available for 57 patients (44.5%). In comparison with normal tissue (29 specimens), cholangiocarcinomas expressed significantly more frequently p53, bcl-2, bax, and COX-2 (P.05 <). Intrahepatic tumors were significantly more frequently bcl-2+ and p16+, whereas extrahepatic tumors were more often p53+ (P < .05). Loss of p16 expression was associated with reduced survival of patients. Our data show that p53, bcl-2, bax, and COX-2 have an important role in the pathogenesis of cholangiocarcinomas. The differential expression of p16, bcl-2, and p53 between intrahepatic and extrahepatic tumors demonstrates that there are location-related differences in the phenotype and the genetic profiles of these tumors. Moreover, p16 was identified as an important prognostic marker in cholangiocarcinomas.

Systemic analysis of microarray data sets towards identifying genes regulating root development

Nitrogen and water are essential for plant growth and development. In this study, we designed experiments to produce gene expression data of poplar roots under nitrogen starvation and water deprivation conditions. We found low concentration of nitrogen led first to increased root elongation followed by lateral root proliferation and eventually increased root biomass. To identify genes regulating root growth and development under nitrogen starvation and water deprivation, we designed a series of data analysis procedures, through which, we have successfully identified biologically important genes. Differentially Expressed Genes (DEGs) analysis identified the genes that are differentially expressed under nitrogen starvation or drought. Protein domain enrichment analysis identified enriched themes (in same domains) that are highly interactive during the treatment. Gene Ontology (GO) enrichment analysis allowed us to identify biological process changed during nitrogen starvation. Based on the above analyses, we examined the local Gene Regulatory Network (GRN) and identified a number of transcription factors. After testing, one of them is a high hierarchically ranked transcription factor that affects root growth under nitrogen starvation. It is very tedious and time-consuming to analyze gene expression data. To avoid doing analysis manually, we attempt to automate a computational pipeline that now can be used for identification of DEGs and protein domain analysis in a single run. It is implemented in scripts of Perl and R.

Analysis of independent microarray datasets of renal biopsies identifies a robust transcript signature of acute allograft rejection

Transcriptomics could contribute significantly to the early and specific diagnosis of rejection episodes by defining 'molecular Banff' signatures. Recently, the description of pathogenesis-based transcript sets offered a new opportunity for objective and quantitative diagnosis. Generating high-quality transcript panels is thus critical to define high-performance diagnostic classifier. In this study, a comparative analysis was performed across four different microarray datasets of heterogeneous sample collections from two published clinical datasets and two own datasets including biopsies for clinical indication, and samples from nonhuman primates. We characterized a common transcriptional profile of 70 genes, defined as acute rejection transcript set (ARTS). ARTS expression is significantly up-regulated in all AR samples as compared with stable allografts or healthy kidneys, and strongly correlates with the severity of Banff AR types. Similarly, ARTS were tested as a classifier in a large collection of 143 independent biopsies recently published by the University of Alberta. Results demonstrate that the 'in silico' approach applied in this study is able to identify a robust and reliable molecular signature for AR, supporting a specific and sensitive molecular diagnostic approach for renal transplant monitoring.