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Igor Jurisica

Publications and source records attributed to Igor Jurisica.

16 recordsLinked to original sources
PubMed2005

CpG Island microarray probe sequences derived from a physical library are representative of CpG Islands annotated on the human genome.

An effective tool for the global analysis of both DNA methylation status and protein-chromatin interactions is a microarray constructed with sequences containing regulatory elements. One type of array suited for this purpose takes advantage of the strong association between CpG Islands (CGIs) and gene regulatory regions. We have obtained 20,736 clones from a CGI Library and used these to construct CGI arrays. The utility of this library requires proper annotation and assessment of the clones, including CpG content, genomic origin and proximity to neighboring genes. Alignment of clone sequences to the human genome (UCSC hg17) identified 9595 distinct genomic loci; 64% were defined by a single clone while the remaining 36% were represented by multiple, redundant clones. Approximately 68% of the loci were located near a transcription start site. The distribution of these loci covered all 23 chromosomes, with 63% overlapping a bioinformatically identified CGI. The high representation of genomic CGI in this rich collection of clones supports the utilization of microarrays produced with this library for the study of global epigenetic mechanisms and protein-chromatin interactions. A browsable database is available on-line to facilitate exploration of the CGIs in this library and their association with annotated genes or promoter elements.

Base Sequence↗
PubMed2005

Molecular evidence of placental hypoxia in preeclampsia.

BACKGROUND: Oxygen plays a central role in human placental pathologies including preeclampsia, a leading cause of fetal and maternal death and morbidity. Insufficient uteroplacental oxygenation in preeclampsia is believed to be responsible for the molecular events leading to the clinical manifestations of this disease. DESIGN: Using high-throughput functional genomics, we determined the global gene expression profiles of placentae from high altitude pregnancies, a natural in vivo model of chronic hypoxia, as well as that of first-trimester explants under 3 and 20% oxygen, an in vitro organ culture model. We next compared the genomic profile from these two models with that obtained from pregnancies complicated by preeclampsia. Microarray data were analyzed using the binary tree-structured vector quantization algorithm, which generates global gene expression maps. RESULTS: Our results highlight a striking global gene expression similarity between 3% O(2)-treated explants, high-altitude placentae, and importantly placentae from preeclamptic pregnancies. We demonstrate herein the utility of explant culture and high-altitude placenta as biologically relevant and powerful models for studying the oxygen-mediated events in preeclampsia. CONCLUSION: Our results provide molecular evidence that aberrant global placental gene expression changes in preeclampsia may be due to reduced oxygenation and that these events can successfully be mimicked by in vivo and in vitro models of placental hypoxia.

Adult↗
PubMed2005

High-throughput mapping of a dynamic signaling network in mammalian cells.

Signaling pathways transmit information through protein interaction networks that are dynamically regulated by complex extracellular cues. We developed LUMIER (for luminescence-based mammalian interactome mapping), an automated high-throughput technology, to map protein-protein interaction networks systematically in mammalian cells and applied it to the transforming growth factor-beta (TGFbeta) pathway. Analysis using self-organizing maps and k-means clustering identified links of the TGFbeta pathway to the p21-activated kinase (PAK) network, to the polarity complex, and to Occludin, a structural component of tight junctions. We show that Occludin regulates TGFbeta type I receptor localization for efficient TGFbeta-dependent dissolution of tight junctions during epithelial-to-mesenchymal transitions.

Activin Receptors, Type I↗
PubMed2005

Online predicted human interaction database.

MOTIVATION: High-throughput experiments are being performed at an ever-increasing rate to systematically elucidate protein-protein interaction (PPI) networks for model organisms, while the complexities of higher eukaryotes have prevented these experiments for humans. RESULTS: The Online Predicted Human Interaction Database (OPHID) is a web-based database of predicted interactions between human proteins. It combines the literature-derived human PPI from BIND, HPRD and MINT, with predictions made from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Mus musculus. The 23,889 predicted interactions currently listed in OPHID are evaluated using protein domains, gene co-expression and Gene Ontology terms. OPHID can be queried using single or multiple IDs and results can be visualized using our custom graph visualization program. AVAILABILITY: Freely available to academic users at http://ophid.utoronto.ca, both in tab-delimited and PSI-MI formats. Commercial users, please contact I.J. CONTACT: juris@ai.utoronto.ca SUPPLEMENTARY INFORMATION: http://ophid.utoronto.ca/supplInfo.pdf.

Database Management Systems↗
PubMed2005

Automatic classification and pattern discovery in high-throughput protein crystallization trials.

Conceptually, protein crystallization can be divided into two phases search and optimization. Robotic protein crystallization screening can speed up the search phase, and has a potential to increase process quality. Automated image classification helps to increase throughput and consistently generate objective results. Although the classification accuracy can always be improved, our image analysis system can classify images from 1,536-well plates with high classification accuracy (85%) and ROC score (0.87), as evaluated on 127 human-classified protein screens containing 5,600 crystal images and 189,472 non-crystal images. Data mining can integrate results from high-throughput screens with information about crystallizing conditions, intrinsic protein properties, and results from crystallization optimization. We apply association mining, a data mining approach that identifies frequently occurring patterns among variables and their values. This approach segregates proteins into groups based on how they react in a broad range of conditions, and clusters cocktails to reflect their potential to achieve crystallization. These results may lead to crystallization screen optimization, and reveal associations between protein properties and crystallization conditions. We also postulate that past experience may lead us to the identification of initial conditions favorable to crystallization for novel proteins.

Algorithms↗
PubMed2004

Modeling of lung cancer by an orthotopically growing H460SM variant cell line reveals novel candidate genes for systemic metastasis.

Endobronchial implantation of NCI-H460 cells into the nude rat generates a primary lung tumor with mediastinal lymph node spread, but rarely systemic metastases. We isolated tumor cells from mediastinal nodes, orthotopically reimplanted the cells into nude rats and repeated this four times to derive a cell line, designated H460SM, that spontaneously metastasizes to bone, kidney, brain, soft tissue and contralateral lung. H460SM cells demonstrated higher invasive activity in vitro than parental NCI-H460 cells. Spectral karyotyping revealed a new inversion within 17q and loss of an extra normal copy of chromosome 14 present in parental NCI-H460 cells. Expression profiling of orthotopic primary tumors revealed differential expression of 360 genes. Of these, 173 were represented in the probe set of a 19.2K OCI cDNA microarray previously used to profile the gene expression of surgically resected lung cancer specimens. We have computationally validated clinical importance of these genes by using in silico analysis of 18 cases of pulmonary adenocarcinoma, which were split into two patient groups with markedly different clinical outcome. The model identifies additional novel candidate genes for the progression of lung cancer to systemic metastases and poor prognosis.

Animals↗
PubMed2004

Molecular classification of oral cancer by cDNA microarrays identifies overexpressed genes correlated with nodal metastasis.

Our purpose was to classify OSCCs based on their gene expression profiles, to identify differentially expressed genes in these cancers and to correlate genetic deregulation with clinical and histopathologic data and patient outcome. After conducting proof-of-principle experiments utilizing 6 HNSCC cell lines, the gene expression profiles of 20 OSCCs were determined using cDNA microarrays containing 19,200 sequences and the BTSVQ method of data analysis. We identified 2 sample clusters that correlated with the T3-T4 category of disease (p = 0.035) and nodal metastasis (p = 0.035). BTSVQ analysis identified a subset of 23 differentially expressed genes with the lowest QE scores in the cluster containing more advanced-stage tumors. Expression of 6 of these differentially expressed genes was validated by quantitative real-time RT-PCR. Statistical analysis of quantitative real-time RT-PCR data was performed and, after Bonferroni correction, CLDN1 overexpression was significantly correlated with the cluster containing more advanced-stage tumors (p = 0.007). Despite the clinical heterogeneity of OSCC, molecular subtyping by cDNA microarray analysis identified distinct patterns of gene expression associated with relevant clinical parameters. Application of this methodology represents an advance in the classification of oral cavity tumors and may ultimately aid in the development of more tailored therapies for oral carcinoma.

Adult↗
PubMed2004

Validating the prognostic value of marker genes derived from a non-small cell lung cancer microarray study.

We previously reported that our cDNA microarray analysis of primary non-small cell lung carcinoma (NSCLC) could predict for patients at increased risk of cancer recurrence. From the result of this analysis, we selected 11 genes that were considered candidate prognostic marker genes and used the realtime reverse transcription polymerase chain reaction (RT-PCR) to investigate their expression in the same set of NSCLC cases used in the microarray study. Cluster analysis of the realtime RT-PCR data separated these patients into two groups with significantly different disease-free survivals (log-rank test, P < 0.017). In contrast, cluster analysis failed to confirm the prognostic significance of the realtime RT-PCR results for these 11 genes in a validation series of 92 NSCLC cases. In univariate analysis, hypoxia inducible factor 1alpha, Rho-GDP dissociation inhibitor (GDI) alpha (RhoGDI) and Citron/rho-interacting serine-threonine kinase 21 (Citron K21) were significant prognostic factors for disease-free survival in the entire cohort of 130 NSCLC patients, but none were significant in multivariate analysis. The results demonstrate that the prognostic significance of microarray (SAM) results can be partially validated using realtime RT-PCR, but secondary validation using larger and independent series of tumors is necessary to identify true prognostic marker genes.

Carcinoma, Non-Small-Cell Lung↗
PubMed2004

Current applications of microarrays in head and neck cancer research.

OBJECTIVES/HYPOTHESIS: The objective was to introduce microarray technology and its applications in cancer research to the head and neck clinician. STUDY DESIGN: Literature review combined with methodology and examples from the authors' experiences with microarray analysis of tumors of the head and neck. METHODS: Search of literature and the authors' experience was made for technical details, alternative methods of data analysis, available bioinformatics tools, and applications of microarrays in cancer research. RESULTS: Microarrays allow the simultaneous analysis of the expression of thousands of genes. The use of a well-developed microarray study design leads to informative results. There are various bioinformatics resources widely available to aid in the analysis of microarray data. However, there is not yet a gold standard for analysis because this methodology is still evolving. CONCLUSION: Microarray studies may allow researchers to identify genetic changes relevant to diagnosis and prognosis in patients with head and neck cancer. Although still relatively new, this powerful methodology has immense potential to aid in understanding of the genetic changes that are important in head and neck cancer.

DNA Mutational Analysis↗
PubMed2003

Automatic classification of sub-microlitre protein-crystallization trials in 1536-well plates.

A technique for automatically evaluating microbatch (400 nl) protein-crystallization trials is described. This method addresses analysis problems introduced at the sub-microlitre scale, including non-uniform lighting and irregular droplet boundaries. The droplet is segmented from the well using a loopy probabilistic graphical model with a two-layered grid topology. A vector of 23 features is extracted from the droplet image using the Radon transform for straight-edge features and a bank of correlation filters for microcrystalline features. Image classification is achieved by linear discriminant analysis of its feature vector. The results of the automatic method are compared with those of a human expert on 32 1536-well plates. Using the human-labeled images as ground truth, this method classifies images with 85% accuracy and a ROC score of 0.84. This result compares well with the experimental repeatability rate, assessed at 87%. Images falsely classified as crystal-positive variously contain speckled precipitate resembling microcrystals, skin effects or genuine crystals falsely labeled by the human expert. Many images falsely classified as crystal-negative variously contain very fine crystal features or dendrites lacking straight edges. Characterization of these misclassifications suggests directions for improving the method.

Aldose-Ketose Isomerases↗
PubMed2003

Loss of coordinated androgen regulation in nonmalignant ovarian epithelial cells with BRCA1/2 mutations and ovarian cancer cells.

Epidemiological studies have implicated androgens in the etiology/progression of epithelial ovarian cancer. Because normal and malignant ovarian epithelial cells are growth inhibited by transforming growth factor (TGF) beta, we tested the ability of 5alpha-dihydrotestosterone (DHT) to modulate this response and the expression of TGF-beta receptor types I and II. Cells derived from the ovarian surface epithelium of women undergoing oophorectomy (n = 7) for nonovarian indications or with a germ-line BRCA1 or 2 mutation (n = 9), and from the ascitic fluid of patients with primary ovarian cancer (n = 8) were cultured with and without DHT. Cell proliferation after TGF-beta1 or vehicle treatment was determined, and transcripts for TGF-beta receptors were measured by quantitative reverse transcription-PCR. As low levels of androgen receptor were observed in the cultures, we also measured transcript levels for steroid receptor coactivators SRC-1, ARA70, and AIB1. TGF-beta1 inhibited growth in 12 of 13 cultures tested, and DHT generally reversed this effect, demonstrating that androgens can block TGF-beta-induced growth inhibition in both malignant and nonmalignant ovarian epithelial cells. Transcripts for TGF-beta receptors, SRC-1, and ARA70 were found to be coordinately regulated by androgen in control cells, but not in either malignant or BRCA1/2-positive cell cultures. These findings raise the possibility that by modulating steroid receptor coactivator expression, androgen might affect other hormonal responses and contribute to the initiation of ovarian cancer.

Activin Receptors, Type I↗
PubMed2003

Phenotypic and transcriptional plasticity directed by a yeast mitogen-activated protein kinase network.

The yeast pheromone/filamentous growth MAPK pathway mediates both mating and invasive-growth responses. The interface between this MAPK module and the transcriptional machinery consists of a network of two MAPKs, Fus3 and Kss1; two regulators, Rst1 and Rst2 (a.k.a. Dig1 and Dig2); and two transcription factors, Ste12 and Tec1. Of 16 possible combinations of gene deletions in FUS3, KSS1, RST1, and RST2 in the sigma1278 background, 10 display constitutive invasive growth. Rst1 was the primary negative regulator of invasive growth, while other components either attenuated or enhanced invasive growth, depending on the genetic context. Despite activation of the invasive response by lesions at the same level in the MAPK pathway, transcriptional profiles of different invasive mutant combinations did not exhibit a unified program of gene expression. The distal MAPK regulatory network is thus capable of generating phenotypically similar invasive-growth states (an attractor) from different molecular architectures (trajectories) that can functionally compensate for one another. This systems-level robustness may also account for the observed diversity of signals that trigger invasive growth.

Haploidy↗
PubMed2002

Molecular profiling of non-small cell lung cancer and correlation with disease-free survival.

Recent studies have suggested that information from gene expression profiles could be used to develop molecular classifications of cancer. We hypothesized that expression levels of specific genes in operative specimens could be correlated to recurrence risk in non-small cell lung cancer (NSCLC). We performed expression profiling using 19.2 K cDNA microarrays on tumor specimens from a total of 39 NSCLC patients with known clinical follow-up information. Statistical analysis and clustering approaches were used to determine patterns of gene expression segregating with clinical outcome. The results provide evidence that molecular subtyping of NSCLC can identify distinct profiles of gene expression correlating with disease-free survival.

Adult↗
PubMedDate not supplied

Stability and heterogeneity of expression profiles in lung cancer specimens harvested following surgical resection.

One of the major concerns in microarray profiling studies of clinical samples is the effect of tissue sampling and RNA extraction on data. We analyzed gene expression in lung cancer specimens that were serially harvested from tumor mass and snap-frozen at several intervals up to 120 minutes after surgical resection. Global gene expression was profiled on cDNA microarrays, and selected stress and hypoxia-activated genes were evaluated using real-time reverse transcription polymerase chain reaction (RT-PCR). Remarkably, similar gene expression profiles were obtained for the majority of samples regardless of the time that had elapsed between resection and freezing. Real-time RT-PCR studies showed significant heterogeneity in the expression levels of stress and hypoxia-activated genes in samples obtained from different areas of a tumor specimen at one time point after resection. The variations between multiple samplings were significantly greater than those of elapsed time between sampling/freezing. Overall samples snap-frozen within 30 to 60 minutes of surgical resection are acceptable for gene expression studies, thus making sampling and snap-freezing of tumor samples in a routine surgical pathology laboratory setting feasible. However, sampling and pooling from multiple sites of each tumor may be necessary for expression profiling studies to overcome the molecular heterogeneity present in tumor specimens.

Carcinoma, Non-Small-Cell Lung↗