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LuxS controls bacteriocin production in Streptococcus mutans through a novel regulatory component.

The oral pathogen Streptococcus mutans employs a variety of mechanisms to maintain a competitive advantage over many other oral bacteria which occupy the same ecological niche. Production of the bacteriocin, mutacin I, is one such mechanism. However, little is known about the regulatory mechanisms associated with mutacin I production. Previous work has demonstrated that the production of mutacin I greatly increased with cell density. In this study, we found that high cell density also triggered high level mutacin I gene transcription. However, this response was abolished upon deletion of luxS. Further analysis using real-time reverse transcription polymerase chain reaction (RT-PCR) demonstrated that in the luxS mutant transcription of both the mutacin I structural gene mutA and the mutacin I transcriptional activator mutR was impaired. Through microarray analysis, a putative transcription repressor annotated as Smu1274 in the Los Alamos National Laboratory Oral Pathogens Sequence Database was identified, which was strongly induced in the luxS mutant. Characterization of Smu1274, which we referred to as irvA, suggested that it may act as an inducible repressor to suppress mutacin I gene expression. A luxS and irvA double mutant regained the ability to produce mutacin I; whereas a constitutive irvA-producing strain was impaired in mutacin I production. These findings reveal a novel regulatory pathway for mutacin I gene expression, which may provide clues to the regulatory mechanisms of other cellular functions regulated by luxS in S. mutans.

Bacterial Proteins↗

Ranking the whole MEDLINE database according to a large training set using text indexing.

BACKGROUND: The MEDLINE database contains over 12 million references to scientific literature, with about 3/4 of recent articles including an abstract of the publication. Retrieval of entries using queries with keywords is useful for human users that need to obtain small selections. However, particular analyses of the literature or database developments may need the complete ranking of all the references in the MEDLINE database as to their relevance to a topic of interest. This report describes a method that does this ranking using the differences in word content between MEDLINE entries related to a topic and the whole of MEDLINE, in a computational time appropriate for an article search query engine. RESULTS: We tested the capabilities of our system to retrieve MEDLINE references which are relevant to the subject of stem cells. We took advantage of the existing annotation of references with terms from the MeSH hierarchical vocabulary (Medical Subject Headings, developed at the National Library of Medicine). A training set of 81,416 references was constructed by selecting entries annotated with the MeSH term stem cells or some child in its sub tree. Frequencies of all nouns, verbs, and adjectives in the training set were computed and the ratios of word frequencies in the training set to those in the entire MEDLINE were used to score references. Self-consistency of the algorithm, benchmarked with a test set containing the training set and an equal number of references randomly selected from MEDLINE was better using nouns (79%) than adjectives (73%) or verbs (70%). The evaluation of the system with 6,923 references not used for training, containing 204 articles relevant to stem cells according to a human expert, indicated a recall of 65% for a precision of 65%. CONCLUSION: This strategy appears to be useful for predicting the relevance of MEDLINE references to a given concept. The method is simple and can be used with any user-defined training set. Choice of the part of speech of the words used for classification has important effects on performance. Lists of words, scripts, and additional information are available from the web address http://www.ogic.ca/projects/ks2004/.

Abstracting and Indexing↗

Physiology and pharmacology of two-pore domain potassium channels.

Searching the DNA database has led to the identification of a class of K+ channels now referred to as two-pore or tandem-pore domain K+ (K2P) channels. The K2P channel is structurally unique in that each subunit possesses two pore-forming domains and four transmembrane segments. In mammals, sixteen K2P channel genes have been identified, and their mRNA transcripts are expressed in many different cell types and tissues. K2P channels have properties of background or leak K+ channels, and therefore play a crucial role in setting the resting membrane potential and regulating cell excitability. Some K2P channels are activated by certain physical and chemical factors such as lipids, volatile anesthetics, heat, oxygen, protons and membrane tension. Some K2P channels are targets of agonists that bind receptors coupled to different types of G proteins, and are probably involved in a variety of neurotransmitter and peptide hormone-mediated signal transduction processes. Such diverse properties of K2P channels suggest that they are involved in many different physiological and pathophysiological processes. Therefore, K2P channels could become potentially important therapeutic targets for the treatment of various pathological conditions.

Animals↗

Mechanisms determining course and outcome of diabetic patients who have had acute myocardial infarction.

PURPOSE: To review the pathogenic mechanism that lead to the poor prognosis of diabetic patients after myocardial infarction and to determine the efficacy of current interventions for myocardial infarction in these patients. DATA SOURCES: Search of the MEDLINE database from 1985 to 1995, using the keywords diabetes, myocardial infarction, and cardiomyopathy, and a search of the reference citations of relevant articles. STUDY SELECTION: Experimental and clinical studies on myocardial infarction in diabetic patients and basic research studies relevant to this topic. DATA SYNTHESIS: The excess in-hospital mortality of diabetic patients results primarily from an increased incidence of congestive heart failure. Several combined mechanisms reduce the compensatory ability of the noninfarcted myocardium; such mechanisms include preexisting congestive heart failure caused by diabetic cardiomyopathy, severe coronary artery disease, decreased vasodilatory reserve of epicardial and resistance arteries, and possibly abnormal metabolism of myocardial substrate. Late mortality results from increased reinfarction rates caused by the diffuse nature of the atherosclerotic disease and hypercoagulable state. Platelet hyperactivity, reduced fibrinolytic capacity, increased concentrations of hemostatic proteins, and endothelial dysfunction promote thrombosis at the site of plaque rupture. Autonomic neuropathy predisposes patients to ventricular arrhythmias. Thrombolytic agents, aspirin, beta-blockers, and angiotensin-converting enzyme inhibitors are effective in patients with diabetes. CONCLUSIONS: In the thrombolytic era, mortality rates of diabetic patients who have had acute myocardial infarction remain 1.5 to 2 times higher than those in nondiabetic patients. This increased mortality rate is caused by diverse mechanisms that affect myocardial function and blood supply and by the tendency toward thrombosis in diabetic patients. Current therapies for myocardial infarction are effective in these patients. Improved metabolic control may also decrease mortality rates.

Cardiomyopathies↗

T3-sequencing: targeted characterization of the N- and C-termini of undigested proteins by mass spectrometry.

A novel extension of the "top-down" approach is introduced for the selective characterization of protein termini that does not involve proteolytic digestion steps. N- and C-terminal peptides were generated from intact proteins in the mass spectrometer and further analyzed by MS/MS-an approach referred to as T(3)-sequencing. N-terminal and C-terminal fragment ion series were obtained by the pseudo-MS/MS technique in-source decay (ISD) on a matrix-assisted laser desorption/ionization time-of-flight mass spectrometer (MALDI-TOF MS). These ions provided near-terminal sequence tags from the undigested protein in the ISD spectrum acquired in reflector mode and allowed to screen for the proper processing state of the terminus with respect to a reference sequence. In the second step of T(3)-sequencing, the precursor ions, which have been generated by ISD and which included the N- or C-terminal sequence, were selected in the timed ion gate of a MALDI-TOF/TOF mass spectrometer for MS/MS analysis. These spectra allowed identification of the protein, the proper definition of both termini, and allowed confirmation of suspected terminal modifications. T(3)-Sequencing appears to be an alternative to classical Edman sequencing, which is fast and even permits the analysis of N-terminally blocked proteins and their C-terminus.

Amino Acid Sequence↗

The CDKN2A database: Integrating allelic variants with evolution, structure, function, and disease association.

In this report, we introduce the CDKN2A Database, an online database of germline and somatic variants of the CDKN2A tumor suppressor gene recorded in human disease through the year 2002, annotated with evolutionary, structural, and functional information. The CDKN2A Database improves upon existing resources by: 1) including both somatic mutations and germline variants, thereby adding the perspective of somatic cell carcinogenesis to that of hereditary cancer predisposition; 2) including information that assists with the interpretation of allelic variants, such as other primary data (sequences, structures, alignments, functional measurements, and literature references) and annotations (extensive text, figures, and a tree-based phylogenetic classification); and 3) providing the information in a format that allows a user to either download the database or to easily manipulate it online. We describe the database structure, content, current uses, and potential implications (http://biodesktop.uvm.edu/perl/p16).

Alleles↗

Identification of novel virulence-associated loci in uropathogenic Escherichia coli by suppression subtractive hybridization.

To identify novel virulence-associated genes in uropathogenic Escherichia coli (UPEC) strains, a suppression subtractive hybridization strategy was applied to genomic DNA of four clinical UPEC isolates from patients suffering from cystitis or pyelonephritis. The genomic DNA of four isolates (tester strains) was subtracted from the DNA of two different driver strains, the well characterized UPEC strain CFT073 and the non-pathogenic E. coli K-12 strain MG1655. We determined the sequence of 172 tester strain-specific DNA fragments, 86 of which revealed only low or no homology to nucleotide sequences of public databases. We further determined the virulence association of the 86 novel DNA fragments using each DNA fragment as a probe in Southern hybridizations of a reference strain collection consisting of 60 extraintestinal pathogenic E. coli isolates, and 40 non-virulent E. coli strains from stool samples. From this, 19 novel DNA fragments were demonstrated to be significantly associated with virulent strains and thus may represent new virulence traits. Our results support the idea of a considerable genetic variability among UPEC strains and suggest that novel genomic determinants might contribute to virulence of UPEC.

Bacterial Proteins↗

Nutrient profiling: comparison and critical analysis of existing systems.

BACKGROUND: Nutrient profiling systems aim at positioning foodstuffs relative to each other according to their contribution to a balanced diet. The accuracy and performance of methodologies are still debated. We present here a critical analysis of the structure and efficiency of the current schemes. METHODS: The literature survey detected only four systems addressing the issue on an 'across the board' approach and with enough detail to enable analysis. The building principles of these systems were compared and their performance was estimated via their classification of a series of 125 foodstuffs on the basis of nutritional composition. These classifications were compared with one another and with an empirical classification by expert nutritionists. RESULTS: All systems gave a similar overview, with fruits and vegetables ranked as the most favourable foods and fatty and sugary foods as the least favourable ones, but numerous discrepancies existed in every system, mainly related to their choice of nutrients and thresholds. The FSA scoring system seemed the most consistent approach, although it still generated some questionable rankings. Expert classification did not clearly validate any scheme, and cannot be considered as a true reference. CONCLUSION: Nutrient profiling systems are confirmed to be powerful tools to translate nutritional information related to the whole diet into the level of individual foods. However, the performance of the existing schemes remains moderate. Alternative approaches, such as considering food categories or introducing more stringent validation steps by a panel of expert nutritionists, could be ways to reach more efficient and consensual tools.

Databases, Factual↗

The UCSC Known Genes.

The University of California Santa Cruz (UCSC) Known Genes dataset is constructed by a fully automated process, based on protein data from Swiss-Prot/TrEMBL (UniProt) and the associated mRNA data from Genbank. The detailed steps of this process are described. Extensive cross-references from this dataset to other genomic and proteomic data were constructed. For each known gene, a details page is provided containing rich information about the gene, together with extensive links to other relevant genomic, proteomic and pathway data. As of July 2005, the UCSC Known Genes are available for human, mouse and rat genomes. The Known Genes serves as a foundation to support several key programs: the Genome Browser, Proteome Browser, Gene Sorter and Table Browser offered at the UCSC website. All the associated data files and program source code are also available. They can be accessed at http://genome.ucsc.edu. The genomic coverage of UCSC Known Genes, RefSeq, Ensembl Genes, H-Invitational and CCDS is analyzed. Although UCSC Known Genes offers the highest genomic and CDS coverage among major human and mouse gene sets, more detailed analysis suggests all of them could be further improved.

Base Sequence↗

Ovarian reserve tests for predicting fertility outcomes for assisted reproductive technology: the International Systematic Collaboration of Ovarian Reserve Evaluation protocol for a systematic review of ovarian reserve test accuracy.

BACKGROUND: The presence of a wide range of tests of ovarian reserve suggests that no single test provides a sufficiently accurate result. Many tests are used without reference to an evidence base. So far, individual studies conducted on these tests are too small to give precise estimates of prognostic accuracy. OBJECTIVES: To systematically assess the accuracy of the available tests of ovarian reserve in terms of prediction of fertility outcomes. SEARCH STRATEGY: The search will be conducted using the name of the respective index test being studied (as listed on the MESH database), if more than 2000 citations are listed, 'ovary' and or 'ovarian', 'fertility' and or 'reserve' will be combined with the original search term as required. Studies of the accuracy of tests of ovarian reserve will be obtained without language restrictions from 1980 to 2005 using the following electronic databases and Ovid software: MEDLINE, EMBASE, PUBmed, Biological extracts, Pascal, Cochrane Library (CDSR, DARE, CCTR, HTA), Best Evidence databases, SCISEARCH, Conference Proceedings (ISI Proceedings, Healthstar, Current Contents, Science Citation Index, Cancerlit and Econlit and NHS Economic Evaluation database. The National Research Register, the Medical Research Council's Clinical Trials Register, MEDION, DARE, and the US Clinical Trials register. SELECTION CRITERIA: Studies will be selected if accuracy of tests are compared with a reference standard and include data that can be abstracted into a two-by-two table to calculate sensitivity and specificity. The studies to be included in this review will examine one of the following index 'tests' within a study population of women undergoing assisted reproductive technology: * Clinical variables--age, history of cancelled cycles. * Basal blood tests--follicle-stimulating hormone (FSH), lutenising hormone (LH), FSH:LH ratios, estradiol (E(2)), inhibin A and B, progesterone (P(4)), P(4):E(2) ratios, antimullerian hormone, testosterone, vascular endothelial growth factor, insulin-like growth factor-1:insulin-like growth factor binding protein-1 ratios. * Dynamic tests--clomiphene citrate challenge test, gonadotropin analogue stimulating test, exogenous FSH ovarian reserve test. * Ultrasound tests-antral follicle count, ovarian volume, ovarian stromal peak systolic velocity, including waveform and pulsatility index, ovarian follicular vascularity. * Histology--ovarian biopsy. Data collection and analysis Two independent reviewers will perform quality assessment and data extraction. Prognostic accuracy will be determined by calculating positive and negative likelihood ratios for the following outcomes or reference standards: live birth, ongoing pregnancy, clinical pregnancy, biochemical pregnancy, embryos available for transfer, eggs obtained at oocyte retrieval, cycles cancelled prior to oocyte retrieval. Main results and conclusions N/A.

Data Collection↗

Phylogenetic profiles for the prediction of protein-protein interactions: how to select reference organisms?

The phylogenetic profile method has been widely applied in the prediction of protein-protein interactions (PPIs). Studies often use all of the available complete genomes for this method. With more than 400 genomes complete and new ones on the horizon, it remains unclear how to select reference organisms for profile construction and then influence the PPI prediction. Here, we performed a systematic assessment of reference organism selection from 225 complete genomes with their evolutionary tree. Our results suggest that reference organisms should be selected from moderately and highly genetically distant organisms, from all three domains (Bacteria, Archaea, and Eukarya), and by their even distribution at the fifth hierarchical level in the evolutionary tree. Our study provides important guidance on the construction of phylogenetic profiles for PPI prediction and functional genomics, which has become challenging due to the large and increasing number of available candidate organisms.

Algorithms↗

IMGT, the international ImMunoGeneTics information system: a standardized approach for immunogenetics and immunoinformatics.

IMGT, the international ImMunoGeneTics information system http://imgt.cines.fr, was created in 1989 by the Laboratoire d'ImmunoGénétique Moléculaire (LIGM) (Université Montpellier II and CNRS) at Montpellier, France. IMGT is a high quality integrated knowledge resource specialized in immunoglobulins (IG), T cell receptors (TR), major histocompatibility complex (MHC) of human and other vertebrates, and related proteins of the immune system (RPI) of any species which belong to the immunoglobulin superfamily (IgSF) and to the MHC superfamily (MhcSF). IMGT consists of five databases, ten on-line tools and more than 8,000 HTML pages of Web resources. IMGT provides a common access to standardized data from genome, genetics, proteome and three-dimensional structures. The accuracy and the consistency of IMGT data are based on IMGT-ONTOLOGY, a semantic specification of terms to be used in immunogenetics and immunoinformatics. IMGT-ONTOLOGY comprises six main concepts: IDENTIFICATION, CLASSIFICATION, DESCRIPTION, NUMEROTATION, ORIENTATION and OBTENTION. Based on these concepts, the controlled vocabulary and the annotation rules necessary for the immunogenetics data identification, classification, description and numbering and for the management of IMGT knowledge are defined in the IMGT Scientific chart. IMGT is the international reference in immunogenetics and immunoinformatics for medical research (repertoire analysis of the IG antibody sites and of the TR recognition sites in autoimmune and infectious diseases, AIDS, leukemias, lymphomas, myelomas), veterinary research (IG and TR repertoires in farm and wild life species), genome diversity and genome evolution studies of the adaptive immune responses, biotechnology related to antibody engineering (single chain Fragment variable (scFv), phage displays, combinatorial libraries, chimeric, humanized and human antibodies), diagnostics (detection and follow up of residual diseases) and therapeutical approaches (grafts, immunotherapy, vaccinology). IMGT is freely available at http://imgt.cines.fr.

Journal Article↗

Discovering motif pairs at interaction sites from protein sequences on a proteome-wide scale.

MOTIVATION: Protein-protein interaction, mediated by protein interaction sites, is intrinsic to many functional processes in the cell. In this paper, we propose a novel method to discover patterns in protein interaction sites. We observed from protein interaction networks that there exist a kind of significant substructures called interacting protein group pairs, which exhibit an all-versus-all interaction between the two protein-sets in such a pair. The full-interaction between the pair indicates a common interaction mechanism shared by the proteins in the pair, which can be referred as an interaction type. Motif pairs at the interaction sites of the protein group pairs can be used to represent such interaction type, with each motif derived from the sequences of a protein group by standard motif discovery algorithms. The systematic discovery of all pairs of interacting protein groups from large protein interaction networks is a computationally challenging problem. By a careful and sophisticated problem transformation, the problem is solved using efficient algorithms for mining frequent patterns, a problem extensively studied in data mining. RESULTS: We found 5349 pairs of interacting protein groups from a yeast interaction dataset. The expected value of sequence identity within the groups is only 7.48%, indicating non-homology within these protein groups. We derived 5343 motif pairs from these group pairs, represented in the form of blocks. Comparing our motifs with domains in the BLOCKS and PRINTS databases, we found that our blocks could be mapped to an average of 3.08 correlated blocks in these two databases. The mapped blocks occur 4221 out of total 6794 domains (protein groups) in these two databases. Comparing our motif pairs with iPfam consisting of 3045 interacting domain pairs derived from PDB, we found 47 matches occurring in 105 distinct PDB complexes. Comparing with another putative domain interaction database InterDom, we found 203 matches. AVAILABILITY: http://research.i2r.a-star.edu.sg/BindingMotifPairs/resources. SUPPLEMENTARY INFORMATION: http://research.i2r.a-star.edu.sg/BindingMotifPairs and Bioinformatics online.

Algorithms↗

High diversity of non-human leukocyte antigens in transplant-associated coronary artery disease.

BACKGROUND: Antibodies to endothelial derived non-human leukocyte antigens (HLA) have been associated with transplant (Tx)-associated coronary artery disease (CAD) after cardiac transplantation; however, few have been identified. The aim of this study was to screen a human coronary artery endothelial cell cDNA library with patient sera to establish the diversity and nature of the target antigens. METHODS: A human coronary artery endothelial cell cDNA library was screened with sera from seven long-term cardiac transplant patients with angiographically diagnosed TxCAD and sera from five healthy volunteers. RESULTS: Of the seven patients' sera, five showed reactivity, as did sera from two of the five normal subjects. Eighteen positive cDNA clones were isolated by TxCAD sera; DNA sequence analysis and DNA database searching identified all but one clone; 16 were nuclear or cytoplasmic proteins and 1 of them was the cell surface protein neuropilin 2. Five clones were targeted by normal sera. A different spectrum of reactive clones was identified by the sera of each patient where reactive clones were evident. CONCLUSIONS: A high diversity of non-HLA antigens, probably autoantigens, are involved in the pathogenesis of TxCAD.

Adult↗

Quantitative drug interactions prediction system (Q-DIPS): a computer-based prediction and management support system for drug metabolism interactions.

OBJECTIVE: Drug biotransformation and interactions are a major source of variability in the response to drugs. The superfamily of cytochromes P450 plays a key role in this phenomenon but, because of the complexity of interactions between drugs and isozymes, it becomes more and more difficult for clinicians to master the knowledge required to predict the occurrence of such drug interactions. To predict and help manage the occurrence of cytochrome P450-dependent interactions, we developed an original computer application: Q-DIPS (quantitative drug interactions prediction system). METHODS: A multidisciplinary work team was created, associating clinical pharmacologists, pharmacists and a computer scientist. Major steps of investigation were: (1) the creation of a database to collect qualitative and quantitative data describing substrates, inhibitors and inducers of specific cytochrome P450 isozymes, with quality assessments; (2) the development of multi-access to these data and (3) their incorporation into extrapolation systems allowing the prediction of in vivo drug interactions on the basis of in vitro data. As an example, prediction and validation studies of CYP3A4 inhibition by ketoconazole and fluconazole will be discussed. RESULTS: Q-DIPS gives up-to-date information, in dynamic tables, describing which specific P450 isozymes metabolise a given drug, as well as which drugs may inhibit or induce a given isozyme. To better answer common clinical questions and help to rapidly evaluate the risk of interactions, it is possible to obtain an overview of substances causing interactions with a specific drug or to focus on drugs taken by a patient ("clinical case"). For each question, key references, relevant quantitative data and quality indices are easily accessible. Two modules allowing input with commercial names and the anatomical therapeutic chemical classification were also included. On the basis of enzymatic and pharmacokinetic data generated in vitro or collected in vivo, the extrapolation module integrates quantitative models to predict the impact of a treatment on enzymatic activities. The simplest model predicted a strong but fluctuating inhibition of CYP3A4 by ketoconazole, whereas the impact of fluconazole was lower. Validations with published in vivo data suggested an appropriate prediction of the risk. CONCLUSION: The current Q-DIPS prototype shows promising potential for helping to improve the management of drug interactions involving metabolism. Validation of extrapolation techniques need to be completed, in view of including important factors such as intrahepatocyte drug accumulation, contribution of metabolites to inhibition as well as in vitro non-specific binding to microsomal proteins. The final goal will be to help select the most judicious clinical studies to be performed so as to avoid useless, expensive and unethical investigations in man.

Antifungal Agents↗

Proteomic analysis of Korean ginseng (Panax ginseng C.A. Meyer).

Although many reports have been published regarding the pharmacological effects of ginseng, little is known about the biochemical pathways operant in ginsenoside biosynthesis, or the genes involved therein. Proteomics analysis is an approach to elucidate the physiological characteristics and biosynthetic pathways of ginsenosides, main components of ginseng. In this review, we introduced the recent progress in proteomics studies of ginseng (Panax ginseng C.A. Meyer). We briefly reference the genomic analyses of P. ginseng, without which proteomics approaches would have been impossible. Functional genomics studies regarding secondary metabolism in P. ginseng are also introduced here, in order to introduce possible future prospects for further study.

Databases, Genetic↗

Transcriptional regulation of protein complexes and biological pathways.

The cis-element profile (or cis-profile) of a gene refers to the collection of transcription factor binding sites (TFBS) regulating the transcription of the gene. Underlying the various published studies that attempt to discover cis-elements in the vicinity of co-expressed genes via pattern detection algorithms, there is an implicit assumption that a correlation exists between co-expressed genes and their cis-profiles. In this study, we show that the cis-similarity, defined as the proportion of shared TFBS between two cis-element profiles, is higher for functionally linked interacting proteins as well as for members of a signal transduction pathway. A similar analysis of the enzymes catalyzing the conversion of adjacent substrates to products in a collection of metabolic pathways, did not reveal higher cis-similarity. The analysis is based on three distinct sources of publicly available data, namely, 1) the BIND database of interacting proteins, 2) known interactions in NMDAR protein complex, 3) the apoptosis pathway and nine pathways related to metabolism of cofactors and vitamins all from KEGG. Additionally, we analyze the cis-element profiles of all the genes in the glutamate receptor (GR) sub-complex of NMDAR complex to detect a set of cis-elements that occur adjacent to a majority of the genes. We show that most of the corresponding transcription factors are known to be involved in GR regulation by comparing our findings with the published biomedical literature. In addition, we were able to detect transcripts whose gene products associate with GR by searching for transcripts that share the same regulatory signals as those detected for GR. This suggests a novel computational methodology for constructing high-order gene regulatory models and detecting co-regulated gene products.

Apoptosis↗

Trefoil factor 3 overexpression in prostatic carcinoma: prognostic importance using tissue microarrays.

BACKGROUND: Human intestinal trefoil factor 3 (TFF3) is a member of a family of polypeptides encoded by a cluster of genes on chromosome 21. Through gene expression profiling studies TFF3 mRNA has been found to be overexpressed in prostate cancer. METHODS: We used immunochemistry on tissue microarrays and software tools, collectively referred to as TMAJ, for online assessment of staining to analyze samples from 294 primary tumors and 61 metastatic lesions. RESULTS: Applying a cutoff of 20% of cells staining as positive, the frequency of staining was 18.8% in normal (51 of 272) and 47.0% in primary tumors (126 of 268), P < 0.0001, Wilcoxon rank sum). Expression of TFF3 in metastatic prostate cancer was similar to that in primary tumors. TFF3 expression was not associated with time to biochemical recurrence, development of distant metastasis, or death due to prostate cancer. Scoring data derived from visual estimation of expression correlated highly with semi-automated image analysis using the Automated Cellular Imaging System (ACIS) from Chromavision, Inc. CONCLUSIONS: These studies validate that TFF3 is overexpressed at the protein level in a subset of primary and metastatic prostate cancers, show the first use of the TMAJ database, and demonstrate the ability to semi-automatically scan and score immunohistochemically stained tissue microarray slides.

Biomarkers, Tumor↗