Biomedical subjects

Sorin Draghici

Publications and source records attributed to Sorin Draghici.

At least 19 recordsLinked to original sources

PubMed2006

New Onto-Tools: Promoter-Express, nsSNPCounter and Onto-Translate.

The Onto-Tools suite is composed of an annotation database and eight complementary, web-accessible data mining tools: Onto-Express, Onto-Compare, Onto-Design, Onto-Translate, Onto-Miner, Pathway-Express, Promoter-Express and nsSNPCounter. Promoter-Express is a new tool added to the Onto-Tools ensemble that facilitates the identification of transcription factor binding sites active in specific conditions. nsSNPCounter is another new tool that allows computation and analysis of synonymous and non-synonymous codon substitutions for studying evolutionary rates of protein coding genes. Onto-Translate has also been enhanced to expand its scope and accuracy by fully utilizing the capabilities of the Onto-Tools database. Currently, Onto-Translate allows arbitrary mappings between 28 types of IDs for 53 organisms. Onto-Tools are freely available at http://vortex.cs.wayne.edu/Projects.html.

Binding Sites↗

PubMed2006

Diagnostic markers of ovarian cancer by high-throughput antigen cloning and detection on arrays.

A noninvasive screening test would significantly facilitate early detection of epithelial ovarian cancer. This study used a combination of high-throughput selection and array-based serologic detection of many antigens indicative of the presence of cancer, thereby using the immune system as a biosensor. This high-throughput selection involved biopanning of an ovarian cancer phage display library using serum immunoglobulins from an ovarian cancer patient as bait. Protein macroarrays containing 480 of these selected antigen clones revealed 65 clones that interacted with immunoglobulins in sera from 32 ovarian cancer patients but not with sera from 25 healthy women or 14 patients having other benign or malignant gynecologic diseases. Sequence analysis data of these 65 clones revealed 62 different antigens. Among the markers, we identified some known antigens, including RCAS1, signal recognition protein-19, AHNAK-related sequence, nuclear autoantogenic sperm protein, Nijmegen breakage syndrome 1 (Nibrin), ribosomal protein L4, Homo sapiens KIAA0419 gene product, eukaryotic initiation factor 5A, and casein kinase II, as well as many previously uncharacterized antigenic gene products. Using these 65 antigens on protein microarrays, we trained neural networks on two-color fluorescent detection of serum IgG binding and found an average sensitivity and specificity of 55% and 98%, respectively. In addition, the top 6 of the most specific clones resulted in an average sensitivity and specificity of 32% and 94%, respectively. This global approach to antigenic profiling, epitomics, has applications to cancer and autoimmune diseases for diagnostic and therapeutic studies. Further work with larger panels of antigens should provide a comprehensive set of markers with sufficient sensitivity and specificity suitable for clinical testing in high-risk populations.

Antigens, Neoplasm↗

PubMed2006

Analysis of microarray experiments of gene expression profiling.

The study of gene expression profiling of cells and tissue has become a major tool for discovery in medicine. Microarray experiments allow description of genome-wide expression changes in health and disease. The results of such experiments are expected to change the methods employed in the diagnosis and prognosis of disease in obstetrics and gynecology. Moreover, an unbiased and systematic study of gene expression profiling should allow the establishment of a new taxonomy of disease for obstetric and gynecologic syndromes. Thus, a new era is emerging in which reproductive processes and disorders could be characterized using molecular tools and fingerprinting. The design, analysis, and interpretation of microarray experiments require specialized knowledge that is not part of the standard curriculum of our discipline. This article describes the types of studies that can be conducted with microarray experiments (class comparison, class prediction, class discovery). We discuss key issues pertaining to experimental design, data preprocessing, and gene selection methods. Common types of data representation are illustrated. Potential pitfalls in the interpretation of microarray experiments, as well as the strengths and limitations of this technology, are highlighted. This article is intended to assist clinicians in appraising the quality of the scientific evidence now reported in the obstetric and gynecologic literature.

Algorithms↗

PubMed2006

Epitomics: global profiling of immune response to disease using protein microarrays.

The immune system retains memory of current and past infections and can sense the presence of cancer by elaborating autoantibodies to tumor proteins. In the presence of an autoimmune disease, the immune system is an efficient, natural biosensor. Therefore we exploit the immune system through a high-throughput process to isolate disease-specific epitopes for diagnostic and therapeutic purposes. These cloned disease-specific antigens are robotically spotted onto protein microarrays and interrogated with serum from the subjects under analyses. These arrays deliver personalized profiles of antigenic exposures and therapeutic targets for personalized immunotherapy. The immune system is the ultimate biosensor, superior to anything a human could create and ready to be exploited for biotechnology and biomedicine.

Epitopes↗

PubMed2006

Immunotheranostics: breaking tolerance in immunotherapy using tumor autoantigens identified on protein microarrays.

Cancer patients develop antitumor immune responses, both humoral and cellular, against antigens expressed by their tumors. Low-throughput antigen cloning has been used to identify a number of immunogenic tumor antigens, but this process has limited utility for diagnostics or therapeutic vaccines. A novel approach to the identification of diagnostic antigens that utilizes a combination of high-throughput selection and protein-microarray-based serological detection of complex panels of antigens that are indicative of the presence of cancer, is described herein, and should lead to a great diversity of vaccine candidates. This technology exploits the immune system as a biosensor to diagnose the presence of cancer through serum testing, and the repertoire of antigen biomarkers identified can then be further employed as immunotherapeutic targets. Given the heterogeneity exhibited by tumors, there will be a higher probability of eliciting a cytotoxic antitumor immune response in cancer patients if multiple antigens that are personalized to an individual patient's patterns of autoantibody binding are used for immunotherapy.

Animals↗

PubMed2005

Reliability and reproducibility issues in DNA microarray measurements.

DNA microarrays enable researchers to monitor the expression of thousands of genes simultaneously. However, the current technology has several limitations. Here we discuss problems related to the sensitivity, accuracy, specificity and reproducibility of microarray results. The existing data suggest that for relatively abundant transcripts the existence and direction (but not the magnitude) of expression changes can be reliably detected. However, accurate measurements of absolute expression levels and the reliable detection of low abundance genes are difficult to achieve. The main problems seem to be the sub-optimal design or choice of probes and some incorrect probe annotations. Well-designed data-analysis approaches can rectify some of these problems.

Animals↗

PubMed2005

Recent additions and improvements to the Onto-Tools.

The Onto-Tools suite is composed of an annotation database and six seamlessly integrated, web-accessible data mining tools: Onto-Express, Onto-Compare, Onto-Design, Onto-Translate, Onto-Miner and Pathway-Express. The Onto-Tools database has been expanded to include various types of data from 12 new databases. Our database now integrates different types of genomic data from 19 sequence, gene, protein and annotation databases. Additionally, our database is also expanded to include complete Gene Ontology (GO) annotations. Using the enhanced database and GO annotations, Onto-Express now allows functional profiling for 24 organisms and supports 17 different types of input IDs. Onto-Translate is also enhanced to fully utilize the capabilities of the new Onto-Tools database with an ultimate goal of providing the users with a non-redundant and complete mapping from any type of identification system to any other type. Currently, Onto-Translate allows arbitrary mappings between 29 types of IDs. Pathway-Express is a new tool that helps the users find the most interesting pathways for their input list of genes. Onto-Tools are freely available at http://vortex.cs.wayne.edu/Projects.html.

Animals↗

PubMed2005

A semantic analysis of the annotations of the human genome.

The correct interpretation of any biological experiment depends in an essential way on the accuracy and consistency of the existing annotation databases. Such databases are ubiquitous and used by all life scientists in most experiments. However, it is well known that such databases are incomplete and many annotations may also be incorrect. In this paper we describe a technique that can be used to analyze the semantic content of such annotation databases. Our approach is able to extract implicit semantic relationships between genes and functions. This ability allows us to discover novel functions for known genes. This approach is able to identify missing and inaccurate annotations in existing annotation databases, and thus help improve their accuracy. We used our technique to analyze the current annotations of the human genome. From this body of annotations, we were able to predict 212 additional gene-function assignments. A subsequent literature search found that 138 of these gene-functions assignments are supported by existing peer-reviewed papers. An additional 23 assignments have been confirmed in the meantime by the addition of the respective annotations in later releases of the Gene Ontology database. Overall, the 161 confirmed assignments represent 75.95% of the proposed gene-function assignments. Only one of our predictions (0.4%) was contradicted by the existing literature. We could not find any relevant articles for 50 of our predictions (23.58%). The method is independent of the organism and can be used to analyze and improve the quality of the data of any public or private annotation database.

Chromosome Mapping↗

PubMed2005

A common pattern of persistent gene activation in human neocortical epileptic foci.

Epilepsy is a disease of recurrent seizures that can develop after a wide range of brain insults. Although surgical resection of focal regions of seizure onset can result in clinical improvement, the molecular mechanisms that produce and maintain focal hyperexcitability are not understood. Here, we demonstrate a regional, persistent induction of a common group of genes in human epileptic neocortex in 17 patients with neocortical epilepsy, regardless of the underlying pathology. This relatively small group of common genes, identified using complementary DNA microarrays and confirmed with quantitative reverse transcription polymerase chain reaction and immunostaining, include the immediate early gene transcription factors EGR-1, EGR-2, and c-fos, with roles in learning and memory, and signaling genes such as the dual-specificity kinase/phosphatase MKP-3. Maximal expression of these genes was observed in neurons in neocortical layers II through IV. These neurons also showed persistent cyclic adenosine monophosphate response element binding protein (CREB) activation and nuclear translocation of EGR-2 and c-fos proteins. In two patients, local interictal epileptiform discharge frequencies correlated precisely with the expression of these genes, suggesting that these genes either are directly modulated by the degree of epileptic activity or help sustain ongoing epileptic activity. The identification of a common set of genes and the persistent activation of CREB signaling in human epileptic foci provide a clinically relevant set of biological markers with potential importance for developing future diagnostic and therapeutic options in human epilepsy.

Adolescent↗

PubMed2005

Application of an objective method for localizing bilateral cortical FDG PET abnormalities to guide the resection of epileptic foci.

PURPOSE: In order to improve the objective localization of bilateral cortical abnormalities in positron emission tomography (PET) image volumes, we developed a new three-dimensional image processing technique. The accuracy of this approach with respect to invasive subdural electroencephalography (EEG) data was assessed in a group of children with neocortical epilepsy. METHODS: Glucose PET image volumes were obtained from 12 epileptic children (mean age 5.2 +/- 4.3 years). Bilateral cortical areas of abnormal glucose metabolism were objectively determined using two conditional criteria assessed against a normal database. The normal database was derived from a group of 15 adult controls (mean age 27.6 years). The spatial relationship between seizure onset electrodes and PET abnormalities was assessed using a conventional receiver operating characteristic (ROC) analysis as well as using a newly defined spatial proximity index (SPI), which characterizes the association between adjacent, but not coincident, abnormalities. RESULTS: ROC analysis at the 2 standard deviation (SD) threshold, revealed an accuracy of 65% to detect seizure onset areas with a sensitivity of 64 +/- 17% and a specificity of 66 +/- 24%. Sensitivity decreased to 46 +/- 24% at the 3-SD threshold with a specificity of 80 +/- 21% (accuracy 75%). The average value for the SPI was determined as 3.82 +/- 1.65 which was 20% lower than the SPI value calculated using a simple in-plane two-dimensional asymmetry between homotopic cortical segments (4.52 +/- 3.82). CONCLUSION: The presented image processing technique improves localization of cortical abnormalities and provides valuable imaging clues for placement of subdural EEG grids prior to surgical resection.

Adolescent↗

PubMed2005

In silico and wet-bench identification of nuclear matrix attachment regions.

Chromatin loops are tethered at discrete regions that are approx 100-1000 bp in length. These regions of attachment serve as specific sequence landmarks, anchoring the DNA to the fibers of the chromosomal scaffold. It has been estimated that our genome contains 70,000 nuclear matrix attachment sites that serve as a dynamic nuclear organizer in both the interphase and metaphase cell. Approximately 30,000-40,000 matrix attachment regions (MARs) serve as origins of replication. MARs can also be associated with chromosomal segments densely populated with transcription factor-binding sites. This may facilitate transcription that is initiated within the region of the chromosome coincident with the surface of the nuclear matrix. Assuming an average somatic loop size of 100 kb, it is reasonable to propose that each cell utilizes 30,000 MARs to anchor each of the approx 20,000 active genic domains. This is sufficient to encompass the 30,000 functional genes in our genome that exist as members of single or multigenic families, each constituting a single chromatin domain. With the sequencing phase of various genome projects complete, in silico tools are being developed to identify the long-range control elements that modulate gene expression. This information is necessary to specifically target the time-intensive wet-bench verification and expression experiments that will provide a unified understanding of gene regulation. In this chapter we review some of the in silico strategies that are currently available and a new in vivo method based on the real-time polymerase chain reaction, to assess regions of matrix association.

Actins↗

PubMed2005

Epitomics: serum screening for the early detection of cancer on microarrays using complex panels of tumor antigens.

Efforts toward the development of early detection assays for cancers have traditionally depended on single biomarker molecules. Current technologies have been disappointing and have not resulted in diagnostic tests suitable for clinical practice. Using a high-throughput cloning method, a panel of epitopes/antigens that react with autoantibodies to tumor proteins in the serum of patients with ovarian cancer have been isolated. Discovery of biomarker panels was directed in an unbiased fashion by cloning a large panel of epitopes or tumor antigens, rather than individual biomarkers without a previous notion of their function. The binding properties of these serum antitumor antibodies on microarrays and advanced bioinformatics tools led to a panel of diagnostic antigens. The sequences that were identified using this new technology will lead to the discovery of novel disease-related proteins that have diagnostic value for the presymptomatic detection of cancer. It has been demonstrated that this approach can detect these autoantibodies in the sera of Stage I ovarian cancer patients. There are numerous advantages of employing serum antibodies as the analytes, not the least of which is the ability to rapidly adapt these assays to standard clinical platforms. This technology of global epitope/antigen profiling is referred to as 'epitomics'.

Animals↗

PubMed2005

Identification of genomic signatures for the design of assays for the detection and monitoring of anthrax threats.

Sequences that are present in a given species or strain while absent from or different in any other organisms can be used to distinguish the target organism from other related or un-related species. Such DNA signatures are particularly important for the identification of genetic source of drug resistance of a strain or for the detection of organisms that can be used as biological agents in warfare or terrorism. Most approaches used to find DNA signatures are laboratory based, require a great deal of effort and can only distinguish between two organisms at a time. We propose a more efficient and cost-effective bioinformatics approach that allows identification of genomic fingerprints for a target organism. We validated our approach using a custom microarray, using sequences identified as DNA fingerprints of Bacillus anthracis. Hybridization results showed that the sequences found using our algorithm were truly unique to B. anthracis and were able to distinguish B. anthracis from its close relatives B. cereus and B. thuringiensis.

Animals↗

PubMed2004

Accuracy of cDNA microarray methods to detect small gene expression changes induced by neuregulin on breast epithelial cells.

BACKGROUND: cDNA microarrays are a powerful means to screen for biologically relevant gene expression changes, but are often limited by their ability to detect small changes accurately due to "noise" from random and systematic errors. While experimental designs and statistical analysis methods have been proposed to reduce these errors, few studies have tested their accuracy and ability to identify small, but biologically important, changes. Here, we have compared two cDNA microarray experimental design methods with northern blot confirmation to reveal changes in gene expression that could contribute to the early antiproliferative effects of neuregulin on MCF10AT human breast epithelial cells. RESULTS: We performed parallel experiments on identical samples using a dye-swap design with ANOVA and an experimental design that excludes systematic biases by "correcting" experimental/control hybridization ratios with control/control hybridizations on a spot-by-spot basis. We refer to this approach as the "control correction method" (CCM). Using replicate arrays, we identified a decrease in proliferation genes and an increase in differentiation genes. Using an arbitrary cut-off of 1.7-fold and p values <0.05, we identified a total of 32 differentially expressed genes, 9 with the dye-swap method, 18 with the CCM, and 5 genes with both methods. 23 of these 32 genes were subsequently verified by northern blotting. Most of these were <2-fold changes. While the dye-swap method (using either ANOVA or Bayesian analysis) detected a smaller number of genes (14-16) compared to the CCM (46), it was more accurate (89-92% vs. 75%). Compared to the northern blot results, for most genes, the microarray results underestimated the fold change, implicating the importance of detecting these small changes. CONCLUSIONS: We validated two experimental design paradigms for cDNA microarray experiments capable of detecting small (<2-fold) changes in gene expression with excellent fidelity that revealed potentially important genes associated with the anti-proliferative effects of neuregulin on MCF10AT breast epithelial cells.

Blotting, Northern↗

PubMed2004

Onto-Tools: an ensemble of web-accessible, ontology-based tools for the functional design and interpretation of high-throughput gene expression experiments.

The Onto-Tools suite is composed of an annotation database and five seamlessly integrated web-accessible data mining tools: Onto-Express (OE), Onto-Compare (OC), Onto-Design (OD), Onto-Translate (OT) and Onto-Miner (OM). OM is a new tool that provides a unified access point and an application programming interface for most annotations available. Our database has been enhanced with more than 120 new commercial microarrays and annotations for Rattus norvegicus, Drosophila melanogaster and Carnorhabditis elegans. The Onto-Tools have been redesigned to provide better biological insight, improved performance and user convenience. The new features implemented in OE include support for gene names, LocusLink IDs and Gene Ontology (GO) IDs, ability to specify fold changes for the input genes, links to the KEGG pathway database and detailed output files. OC allows comparisons of the functional bias of more than 170 commercial microarrays. The latest version of OD allows the user to specify keywords if the exact GO term is not known as well as providing more details than the previous version. OE, OC and OD now have an integrated GO browser that allows the user to customize the level of abstraction for each GO category. The Onto-Tools are available online at http://vortex.cs.wayne.edu/Projects.html.

Animals↗

PubMed2004

Gene expression profiles predict survival and progression of pleural mesothelioma.

PURPOSE: Clinical outcomes for malignant pleural mesothelioma (MPM) patients having surgery are imprecisely predicted by histopathology and intraoperative staging. We hypothesized that gene expression profiles could predict time to progression and survival in surgically cytoreduced pleural mesothelioma of all stages. EXPERIMENTAL DESIGN: Gene expression analyses from 21 MPM patients having cytoreductions and identical postoperative adjuvant therapy were performed using the U95 Affymetrix gene chip. Using both dChip and SAM, neural networks constructed a common 27 gene classifier, which was associated with either the high-risk and low-risk group of patients. Data were validated using real-time PCR and immunohistochemical staining. The 27 gene classifier was also used for validation in a separate set of 17 MPM patients from another institution. RESULTS: The groups predicted by the gene classifier recapitulated the actual time to progression and survival of the test set with 95.2% accuracy using 10-fold cross-validation. Clinical outcomes were independent of histology, and heterogeneity of progression and survival in early stage patients was defined by the classifier. The gene classifier had a 76% accuracy in the separate validation set of MPMs. CONCLUSIONS: These data suggest that pretherapy gene expression analysis of mesothelioma biopsies may predict which patients may benefit from a surgical approach.

Disease Progression↗

PubMed2004

Applications and challenges of DNA microarray technology in military medical research.

This review discusses the challenges and applications of DNA microarray technology as it is being used in each of the four major research areas of the U.S. Army Medical Research and Materiel Command: military infectious diseases, combat casualty care, military operational medicine, and medical chemical and biological defense. The overall objective of this review is two-fold. First, the objective is to increase awareness in senior military leadership of the challenges and opportunities presented by DNA microarray technology and the emerging and rapidly changing field of bioinformatics. Second, the aim is to publicize to the civilian research community the additional challenges associated with the use of microarray technology in military medical research. This discussion contains material that would be useful for making programmatic recommendations that team strategic research investments and emerging technologies with U.S. Army Medical Research and Materiel Command resources.

Biological Warfare↗

PubMed2003

Noise sampling method: an ANOVA approach allowing robust selection of differentially regulated genes measured by DNA microarrays.

MOTIVATION: A crucial step in microarray data analysis is the selection of subsets of interesting genes from the initial set of genes. In many cases, especially when comparing a specific condition to a reference, the genes of interest are those which are differentially expressed. Two common methods for gene selection are: (a) selection by fold difference (at least n fold variation) and (b) selection by altered ratio (at least n standard deviations away from the mean ratio). RESULTS: The novel method proposed here is based on ANOVA and uses replicate spots to estimate an empirical distribution of the noise. The measured intensity range is divided in a number of intervals. A noise distribution is constructed for each such interval. Bootstrapping is used to map the desired confidence levels from the noise distribution corresponding to a given interval to the measured log ratios in that interval. If the method is applied on individual arrays having replicate spots, the method can calculate an overall width of the noise distribution which can be used as an indicator of the array quality. We compared this method with the fold change and unusual ratio method. We also discuss the relationship with an ANOVA model proposed by Churchill et al. In silico experiments were performed while controlling the degree of regulation as well as the amount of noise. Such experiments show the performance of the classical methods can be very unsatisfactory. We also compared the results of the 2-fold method with the results of the noise sampling method using pre and post immortalization cell lines derived from the MDAH041 fibroblasts hybridized on Affymetrix GeneChip arrays. The 2-fold method reported 198 genes as upregulated and 493 genes as downregulated. The noise sampling method reported 98 gene upregulated and 240 genes downregulated at the 99.99% confidence level. The methods agreed on 221 genes downregulated and 66 genes upregulated. Fourteen genes from the subset of genes reported by both methods were all confirmed by Q-RT-PCR. Alternative assays on various subsets of genes on which the two methods disagreed suggested that the noise sampling method is likely to provide fewer false positives.

Algorithms↗