Papers

PERT: a method for expression deconvolution of human blood samples from varied microenvironmental and developmental conditions.

PLoS Comput Biol. 2012;8(12):e1002838

Authors: Qiao W, Quon G, Csaszar E, Yu M, Morris Q, Zandstra PW

Abstract
The cellular composition of heterogeneous samples can be predicted using an expression deconvolution algorithm to decompose their gene expression profiles based on pre-defined, reference gene expression profiles of the constituent populations in these samples. However, the expression profiles of the actual constituent populations are often perturbed from those of the reference profiles due to gene expression changes in cells associated with microenvironmental or developmental effects. Existing deconvolution algorithms do not account for these changes and give incorrect results when benchmarked against those measured by well-established flow cytometry, even after batch correction was applied. We introduce PERT, a new probabilistic expression deconvolution method that detects and accounts for a shared, multiplicative perturbation in the reference profiles when performing expression deconvolution. We applied PERT and three other state-of-the-art expression deconvolution methods to predict cell frequencies within heterogeneous human blood samples that were collected under several conditions (uncultured mono-nucleated and lineage-depleted cells, and culture-derived lineage-depleted cells). Only PERT's predicted proportions of the constituent populations matched those assigned by flow cytometry. Genes associated with cell cycle processes were highly enriched among those with the largest predicted expression changes between the cultured and uncultured conditions. We anticipate that PERT will be widely applicable to expression deconvolution strategies that use profiles from reference populations that vary from the corresponding constituent populations in cellular state but not cellular phenotypic identity.

PMID: 23284283 [PubMed - indexed for MEDLINE]

Genomic signatures of selection at linked sites: unifying the disparity among species.

Nat Rev Genet. 2013 Apr;14(4):262-74

Authors: Cutter AD, Payseur BA

Abstract
Population genetics theory supplies powerful predictions about how natural selection interacts with genetic linkage to sculpt the genomic landscape of nucleotide polymorphism. Both the spread of beneficial mutations and the removal of deleterious mutations act to depress polymorphism levels, especially in low-recombination regions. However, empiricists have documented extreme disparities among species. Here we characterize the dominant features that could drive differences in linked selection among species--including roles for selective sweeps being 'hard' or 'soft'--and the concealing effects of demography and confounding genomic variables. We advocate targeted studies of closely related species to unify our understanding of how selection and linkage interact to shape genome evolution.

PMID: 23478346 [PubMed - indexed for MEDLINE]

CaPSID: a bioinformatics platform for computational pathogen sequence identification in human genomes and transcriptomes.

BMC Bioinformatics. 2012;13:206

Authors: Borozan I, Wilson S, Blanchette P, Laflamme P, Watt SN, Krzyzanowski PM, Sircoulomb F, Rottapel R, Branton PE, Ferretti V

Abstract
BACKGROUND: It is now well established that nearly 20% of human cancers are caused by infectious agents, and the list of human oncogenic pathogens will grow in the future for a variety of cancer types. Whole tumor transcriptome and genome sequencing by next-generation sequencing technologies presents an unparalleled opportunity for pathogen detection and discovery in human tissues but requires development of new genome-wide bioinformatics tools.
RESULTS: Here we present CaPSID (Computational Pathogen Sequence IDentification), a comprehensive bioinformatics platform for identifying, querying and visualizing both exogenous and endogenous pathogen nucleotide sequences in tumor genomes and transcriptomes. CaPSID includes a scalable, high performance database for data storage and a web application that integrates the genome browser JBrowse. CaPSID also provides useful metrics for sequence analysis of pre-aligned BAM files, such as gene and genome coverage, and is optimized to run efficiently on multiprocessor computers with low memory usage.
CONCLUSIONS: To demonstrate the usefulness and efficiency of CaPSID, we carried out a comprehensive analysis of both a simulated dataset and transcriptome samples from ovarian cancer. CaPSID correctly identified all of the human and pathogen sequences in the simulated dataset, while in the ovarian dataset CaPSID's predictions were successfully validated in vitro.

PMID: 22901030 [PubMed - indexed for MEDLINE]

Towards a theoretical understanding of false positives in DNA motif finding.

BMC Bioinformatics. 2012;13:151

Authors: Zia A, Moses AM

Abstract
BACKGROUND: Detection of false-positive motifs is one of the main causes of low performance in de novo DNA motif-finding methods. Despite the substantial algorithm development effort in this area, recent comprehensive benchmark studies revealed that the performance of DNA motif-finders leaves room for improvement in realistic scenarios.
RESULTS: Using large-deviations theory, we derive a remarkably simple relationship that describes the dependence of false positives on dataset size for the one-occurrence per sequence motif-finding problem. As expected, we predict that false-positives can be reduced by decreasing the sequence length or by adding more sequences to the dataset. Interestingly, we find that the false-positive strength depends more strongly on the number of sequences in the dataset than it does on the sequence length, but that the dependence on the number of sequences diminishes, after which adding more sequences does not reduce the false-positive rate significantly. We compare our theoretical predictions by applying four popular motif-finding algorithms that solve the one-occurrence-per-sequence problem (MEME, the Gibbs Sampler, Weeder, and GIMSAN) to simulated data that contain no motifs. We find that the dependence of false positives detected by these softwares on the motif-finding parameters is similar to that predicted by our formula.
CONCLUSIONS: We quantify the relationship between the sequence search space and motif-finding false-positives. Based on the simple formula we derive, we provide a number of intuitive rules of thumb that may be used to enhance motif-finding results in practice. Our results provide a theoretical advance in an important problem in computational biology.

PMID: 22738169 [PubMed - indexed for MEDLINE]

NetwoRx: connecting drugs to networks and phenotypes in Saccharomyces cerevisiae.

Nucleic Acids Res. 2013 Jan;41(Database issue):D720-7

Authors: Fortney K, Xie W, Kotlyar M, Griesman J, Kotseruba Y, Jurisica I

Abstract
Drug modes of action are complex and still poorly understood. The set of known drug targets is widely acknowledged to be biased and incomplete, and so gives only limited insight into the system-wide effects of drugs. But a high-throughput assay unique to yeast-barcode-based chemogenomic screens-can measure the individual drug response of every yeast deletion mutant in parallel. NetwoRx (http://ophid.utoronto.ca/networx) is the first resource to store data from these extremely valuable yeast chemogenomics experiments. In total, NetwoRx stores data on 5924 genes and 466 drugs. In addition, we applied data-mining approaches to identify yeast pathways, functions and phenotypes that are targeted by particular drugs, compute measures of drug-drug similarity and construct drug-phenotype networks. These data are all available to search or download through NetwoRx; users can search by drug name, gene name or gene set identifier. We also set up automated analysis routines in NetwoRx; users can query new gene sets against the entire collection of drug profiles and retrieve the drugs that target them. We demonstrate with use case examples how NetwoRx can be applied to target specific phenotypes, repurpose drugs using mode of action analysis, investigate bipartite networks and predict new drugs that affect yeast aging.

PMID: 23203867 [PubMed - indexed for MEDLINE]

Analysis and Design of a Genetic Circuit for Dynamic Metabolic Engineering.

ACS Synth Biol. 2013 Apr 9;

Authors: Anesiadis N, Kobayashi H, Cluett WR, Mahadevan R

Abstract
Recent advances in synthetic biology have equipped us with new tools for bioprocess optimization at the genetic level. Previously, we have presented an integrated in silico design for the dynamic control of gene expression based on a density-sensing unit and a genetic toggle switch. In the present paper, analysis of a serine-producing Escherichia coli mutant shows that an instantaneous ON-OFF switch leads to a maximum theoretical productivity improvement of 29.6% compared to the mutant. To further the design, global sensitivity analysis is applied here to a mathematical model of serine production in E. coli coupled with a genetic circuit. The model of the quorum sensing and the toggle switch involves 13 parameters of which 3 are identified as having a significant effect on serine concentration. Simulations conducted in this reduced parameter space further identified the optimal ranges for these 3 key parameters to achieve productivity values close to the maximum theoretical values. This analysis can now be used to guide the experimental implementation of a dynamic metabolic engineering strategy and reduce the time required to design the genetic circuit components.

PMID: 23654263 [PubMed - as supplied by publisher]

Design of pH-responsive nanoparticles of terpolymer of poly(methacrylic acid), polysorbate 80 and starch for delivery of doxorubicin.

Colloids Surf B Biointerfaces. 2013 Jan 1;101:405-13

Authors: Shalviri A, Chan HK, Raval G, Abdekhodaie MJ, Liu Q, Heerklotz H, Wu XY

Abstract
This work focused on the design of new pH-responsive nanoparticles for controlled delivery of anticancer drug doxorubicin (Dox). Nanoparticles of poly(methacrylic acid)-polysorbate 80-grafted starch (PMAA-PS 80-g-St) were synthesized by using a one-pot method that enabled simultaneous grafting of PMAA and PS 80 onto starch and nanoparticle formation in an aqueous medium. The particles were characterized by FTIR, (1)H NMR, TEM, DLS, and potentiometric titration. Dox loading and in vitro release from the nanoparticles were investigated. The FTIR and (1)H NMR confirmed the chemical composition of the graft terpolymer. The nanoparticles were relatively spherical with narrow size distribution and porous morphology. They exhibited pH-dependent swelling in a physiological pH range. The particle size and magnitude of phase transition were dependent on polymer composition and formulation parameters such as concentrations of surfactant and cross-linking agent and total monomer concentration. The nanoparticles with optimized compositions showed high loading capacity for Dox and sustained Dox release. The results suggest that the new pH-responsive terpolymer nanoparticles are useful in controlled drug delivery.

PMID: 23010048 [PubMed - indexed for MEDLINE]

PhenoTips: Patient Phenotyping Software for Clinical and Research Use.

Hum Mutat. 2013 May 1;

Authors: Girdea M, Dumitriu S, Fiume M, Bowdin S, Boycott KM, Chénier S, Chitayat D, Faghfoury H, Meyn MS, Ray PN, So J, Stavropoulos DJ, Brudno M

Abstract
We have developed PhenoTips: open source software for collecting and analyzing phenotypic information for patients with genetic disorders. Our software combines an easy-to-use interface, compatible with any device that runs a Web browser, with a standardized database back-end. The PhenoTips' user interface closely mirrors clinician workflows so as to facilitate the recording of observations made during the patient encounter. Collected data include demographics, medical history, family history, physical and laboratory measurements, physical findings, and additional notes. Phenotypic information is represented using the Human Phenotype Ontology; however the complexity of the ontology is hidden behind a user interface which combines simple selection of common phenotypes with error-tolerant, predictive search of the entire ontology. PhenoTips supports accurate diagnosis by analyzing the entered data, then suggesting additional clinical investigations and providing OMIM links to likely disorders. By collecting, classifying and analyzing phenotypic information during the patient encounter, PhenoTips allows for streamlining of clinic workflow, efficient data entry, improved diagnosis, standardization of collected patient phenotypes, and sharing of anonymized patient phenotype data for the study of rare disorders. Our source code and a demo version of PhenoTips are available at http://phenotips.org.

PMID: 23636887 [PubMed - as supplied by publisher]

Gene network modular-based classification of microarray samples.

BMC Bioinformatics. 2012;13 Suppl 10:S17

Authors: Hu P, Bull SB, Jiang H

Abstract
BACKGROUND: Molecular predictor is a new tool for disease diagnosis, which uses gene expression to classify diagnostic category of a patient. The statistical challenge for constructing such a predictor is that there are thousands of genes to predict for the disease categories, but only a small number of samples are available.
RESULTS: We proposed a gene network modular-based linear discriminant analysis approach by integrating 'essential' correlation structure among genes into the predictor in order that the modules or cluster structures of genes, which are related to the diagnostic classes we look for, can have potential biological interpretation. We evaluated performance of the new method with other established classification methods using three real data sets.
CONCLUSIONS: Our results show that the new approach has the advantage of computational simplicity and efficiency with relatively lower classification error rates than the compared methods in many cases. The modular-based linear discriminant analysis approach induced in the study has the potential to increase the power of discriminant analysis for which sample sizes are small and there are large number of genes in the microarray studies.

PMID: 22759422 [PubMed - in process]

Insights From Mixture Cure Modeling of Molecular Markers for Prognosis in Breast Cancer.

J Clin Oncol. 2013 Apr 29;

Authors: Yilmaz YE, Lawless JF, Andrulis IL, Bull SB

Abstract
With the ultimate aim of improving clinical management of breast cancer, investigators have sought to identify molecular genetic markers that stratify newly diagnosed patients into subtypes differing in short- or long-term prognosis. Conventional survival models can fail to describe adequately the relationship between subtype and disease recurrence, particularly when there is a substantial proportion of long-term disease-free survivors. The observed patterns of disease-free survival in an undifferentiated patient cohort may be explained by an underlying mixture of two subgroups: patients who will remain free of disease in the long term (ie, cured), and those who will experience disease recurrence within their lifetime (ie, susceptible.) In this article, we review the concepts and methods of the mixture cure models and apply them in the analysis of molecular genetic prognostic factors for disease-free survival and time to disease recurrence in a cohort of patients with axillary lymph node-negative breast cancer.

PMID: 23630217 [PubMed - as supplied by publisher]

Clinical genomics information management software linking cancer genome sequence and clinical decisions.

Genomics. 2013 Apr 17;

Authors: Watt S, Jiao W, Brown AM, Petrocelli T, Tran B, Zhang T, McPherson JD, Kamel-Reid S, Bedard PL, Onetto N, Hudson TJ, Dancey J, Siu LL, Stein L, Ferretti V

Abstract
Using sequencing information to guide clinical decision-making requires coordination of a diverse set of people and activities. In clinical genomics, the process typically includes sample acquisition, template preparation, genome data generation, analysis to identify and confirm variant alleles, interpretation of clinical significance, and reporting to clinicians. We describe a software application developed within a clinical genomics study, to support this entire process. The software application tracks patients, samples, genomic results, decisions and reports across the cohort, monitors progress and sends reminders, and works alongside an electronic data capture system for the trial's clinical and genomic data. It incorporates systems to read, store, analyze and consolidate sequencing results from multiple technologies, and provides a curated knowledge base of tumor mutation frequency (from the COSMIC database) annotated with clinical significance and drug sensitivity to generate reports for clinicians. By supporting the entire process, the application provides deep support for clinical decision making, enabling the generation of relevant guidance in reports for verification by an expert panel prior to forwarding to the treating physician.

PMID: 23603536 [PubMed - as supplied by publisher]

A flexible nonparametric approach to find candidate genes associated with disease in microarray experiments.

J Bioinform Comput Biol. 2013 Apr;11(2):1250021

Authors: Hossain A, Willan AR, Beyene J

Abstract
Very often biologists are interested to know the biological function of a particular gene. Its true biological function may depend on other genes. Finding other genes in the same biological pathway of that gene may enhance further understanding of its biological function. Therefore, we are interested in finding other candidate genes whose expression values are highly correlated with that of a "seed" gene. The "seed" gene, which is known and associated with a disease, is used as a reference to extract candidate genes from microarray experiments and enriched pathways. We propose a nonparametric procedure for selecting the candidate genes. The expression levels for these candidate genes are correlated with that of a "seed" gene in microarray experiments. The proposed test statistic compares two Area Under Receiver Operating Characteristic Curves (AUC) for gene pairs, taking implicit correlation between two AUCs into account. The performance of our method is compared to the other well-known methods through the use of simulation and real data analysis.

PMID: 23600812 [PubMed - in process]

Molecular testing prognostic of low risk in epithelioid uveal melanoma in a child.

Br J Ophthalmol. 2013 Mar;97(3):323-6

Authors: Dimaras H, Parulekar MV, Kwok G, Simpson ER, Ali A, Halliday W, Shago M, Harbour JW, Héon E, Gallie BL, Chan HS

Abstract
AIMS: To characterise a histologically unusual paediatric uveal melanoma by gene expression and karyotypic profiling and assess prognosis.
METHODS: The tumour was studied by histopathology, karyotype analysis, single nucleotide polymorphism and gene expression profile analysis for correlation with clinical outcome.
RESULTS: The tumour had predominantly epithelioid histology. Karyotype analysis showed none of the poor prognosis features normally associated with uveal melanoma. single nucleotide polymorphism analysis revealed no imbalance at chromosome 3. Gene expression profiling indicated low risk disease.
CONCLUSIONS: We report a child remaining relapse-free 6 years after diagnosis of a very rare uveal melanoma, with poor prognosis epithelioid histology, but gene expression profiling that accurately predicted low risk disease.

PMID: 23292925 [PubMed - indexed for MEDLINE]

Polymorphisms in the human tropoelastin gene modify in vitro self-assembly and mechanical properties of elastin-like polypeptides.

PLoS One. 2012;7(9):e46130

Authors: He D, Miao M, Sitarz EE, Muiznieks LD, Reichheld S, Stahl RJ, Keeley FW, Parkinson J

Abstract
Elastin is a major structural component of elastic fibres that provide properties of stretch and recoil to tissues such as arteries, lung and skin. Remarkably, after initial deposition of elastin there is normally no subsequent turnover of this protein over the course of a lifetime. Consequently, elastic fibres must be extremely durable, able to withstand, for example in the human thoracic aorta, billions of cycles of stretch and recoil without mechanical failure. Major defects in the elastin gene (ELN) are associated with a number of disorders including Supravalvular aortic stenosis (SVAS), Williams-Beuren syndrome (WBS) and autosomal dominant cutis laxa (ADCL). Given the low turnover of elastin and the requirement for the long term durability of elastic fibres, we examined the possibility for more subtle polymorphisms in the human elastin gene to impact the assembly and long-term durability of the elastic matrix. Surveys of genetic variation resources identified 118 mutations in human ELN, 17 being non-synonymous. Introduction of two of these variants, G422S and K463R, in elastin-like polypeptides as well as full-length tropoelastin, resulted in changes in both their assembly and mechanical properties. Most notably G422S, which occurs in up to 40% of European populations, was found to enhance some elastomeric properties. These studies reveal that even apparently minor polymorphisms in human ELN can impact the assembly and mechanical properties of the elastic matrix, effects that over the course of a lifetime could result in altered susceptibility to cardiovascular disease.

PMID: 23049958 [PubMed - indexed for MEDLINE]

Multiple pesticide exposures and the risk of multiple myeloma in Canadian men.

Int J Cancer. 2013 Apr 6;

Authors: Kachuri L, Demers PA, Blair A, Spinelli JJ, Pahwa M, McLaughlin JR, Pahwa P, Dosman JA, Harris SA

Abstract
Multiple myeloma (MM) has been linked to certain agricultural exposures, including pesticides. This analysis aimed to investigate the association between lifetime use of multiple pesticides and MM risk using two exposure metrics: number of pesticides used and days per year of pesticide use. A frequency-matched, population-based case-control study was conducted among men in six Canadian provinces between 1991 and 1994. Data from 342 MM cases and 1357 controls were analyzed using logistic regression to calculate odds ratios (OR) and 95% confidence intervals. Pesticides were grouped by type, chemical class, and carcinogenic potential, using a composite carcinogenic probability score. Selected individual pesticides were also examined. Regression models were adjusted for age, province of residence, use of proxy respondents, smoking, and selected medical history variables. The overall pattern of results was complex. Positive trends in risk were observed for fungicides (ptrend =0.04) and pesticides classified as probably carcinogenic or higher (ptrend =0.03). Excess risks of MM were observed among men who reported using at least one carbamate pesticide (OR=1.94, 1.16-3.25), one phenoxy herbicide (OR=1.56, 1.09-2.25), and ≥3 organochlorines (OR=2.21, 1.05-4.66). Significantly higher odds of MM were seen for exposure to carbaryl (OR=2.71, 1.47-5.00) and captan (OR=2.96, 1.40-6.24). Use of mecoprop for >2 days per year was also significantly associated with MM (OR=2.15, 1.03-4.48). Focusing on multiple pesticide exposures is important because this more accurately reflects how exposures occur in occupational settings. Significant associations observed for certain chemical classes and individual pesticides suggest that these may be MM risk factors. © 2013 Wiley Periodicals, Inc.

PMID: 23564249 [PubMed - as supplied by publisher]

Fine-scale signatures of molecular evolution reconcile models of indel-associated mutation.

Genome Biol Evol. 2013 Apr 4;

Authors: Jovelin R, Cutter AD

Abstract
Genomic structural alterations that vary within species, known as large copy number variants, represent an unanticipated and abundant source of genetic diversity that associates with variation in gene expression and susceptibility to disease. Even short insertions and deletions (indels) can exert important effects on genomes by locally increasing the mutation rate, with multiple mechanisms proposed to account for this pattern. To better understand how indels promote genome evolution, here we demonstrate that the single nucleotide mutation rate is elevated in the vicinity of indels, with a resolution of tens of basepairs, for the two closely-related nematode species Caenorhabditis remanei and Caenorhabditis sp. 23. In addition to indels being clustered with single nucleotide polymorphisms and fixed differences, we also show that transversion mutations are enriched in sequences that flank indels and that many indels associate with sequence repeats. These observations are compatible with a model that reconciles previously proposed mechanisms of indel-associated mutagenesis, implicating repeat sequences as a common driver of indel errors, which then recruit error-prone polymerases during DNA repair, resulting in a locally-elevated single nucleotide mutation rate. The striking influence of indel variants on the molecular evolution of flanking sequences strengthens the emerging general view that mutations can induce further mutations.

PMID: 23558593 [PubMed - as supplied by publisher]

A transcriptomic analysis of Echinococcus granulosus larval stages: implications for parasite biology and host adaptation.

PLoS Negl Trop Dis. 2012;6(11):e1897

Authors: Parkinson J, Wasmuth JD, Salinas G, Bizarro CV, Sanford C, Berriman M, Ferreira HB, Zaha A, Blaxter ML, Maizels RM, Fernández C

Abstract
BACKGROUND: The cestode Echinococcus granulosus--the agent of cystic echinococcosis, a zoonosis affecting humans and domestic animals worldwide--is an excellent model for the study of host-parasite cross-talk that interfaces with two mammalian hosts. To develop the molecular analysis of these interactions, we carried out an EST survey of E. granulosus larval stages. We report the salient features of this study with a focus on genes reflecting physiological adaptations of different parasite stages.
METHODOLOGY/PRINCIPAL FINDINGS: We generated ~10,000 ESTs from two sets of full-length enriched libraries (derived from oligo-capped and trans-spliced cDNAs) prepared with three parasite materials: hydatid cyst wall, larval worms (protoscoleces), and pepsin/H(+)-activated protoscoleces. The ESTs were clustered into 2700 distinct gene products. In the context of the biology of E. granulosus, our analyses reveal: (i) a diverse group of abundant long non-protein coding transcripts showing homology to a middle repetitive element (EgBRep) that could either be active molecular species or represent precursors of small RNAs (like piRNAs); (ii) an up-regulation of fermentative pathways in the tissue of the cyst wall; (iii) highly expressed thiol- and selenol-dependent antioxidant enzyme targets of thioredoxin glutathione reductase, the functional hub of redox metabolism in parasitic flatworms; (iv) candidate apomucins for the external layer of the tissue-dwelling hydatid cyst, a mucin-rich structure that is critical for survival in the intermediate host; (v) a set of tetraspanins, a protein family that appears to have expanded in the cestode lineage; and (vi) a set of platyhelminth-specific gene products that may offer targets for novel pan-platyhelminth drug development.
CONCLUSIONS/SIGNIFICANCE: This survey has greatly increased the quality and the quantity of the molecular information on E. granulosus and constitutes a valuable resource for gene prediction on the parasite genome and for further genomic and proteomic analyses focused on cestodes and platyhelminths.

PMID: 23209850 [PubMed - indexed for MEDLINE]

The effect of augmented real-time image guidance on task workload during endoscopic sinus surgery.

Int Forum Allergy Rhinol. 2012 Sep-Oct;2(5):405-10

Authors: Dixon BJ, Chan H, Daly MJ, Vescan AD, Witterick IJ, Irish JC

Abstract
BACKGROUND: Due to proximity to critical structures, the need for spatial awareness during endoscopic sinus surgery (ESS) is essential. We have developed an augmented, real-time image-guided surgery (ART-IGS) system that provides live navigational data and proximity alerts to the operating surgeon during ablation. We wished to test the hypothesis that task workload would be reduced when using this technology.
METHODS: A trial involved 8 otolaryngology residents and fellows performing ESS on cadaveric specimens; 1 side in a conventional method (control) and 1 side with ART-IGS. After computed tomography scanning, anatomical contouring, and registration of the head, a three-dimensional (3D) virtual endoscopic view, ablative tool tracking, and proximity alerts were enabled. Each subject completed ESS tasks and rated their workload during and after the exercise using the National Aeronautics and Space Administration (NASA) Task Load Index (TLX). A questionnaire and open feedback interview were completed after the procedure.
RESULTS: There was a significant reduction in mental demand, temporal demand, effort, and frustration when using the ART-IGS system in comparison to the control (p < 0.02). Perceived performance was increased (p = 0.02). Most subjects agreed that the system was sufficiently accurate, caused minimal interruption, and increased confidence. Optical tracking line-of-sight issues were frequently cited as the main limitation early in the study; however, this was largely resolved.
CONCLUSION: ART-IGS reduces task workload for trainees performing ESS. Live navigation and alert zones may be a valuable intraoperative teaching aid.

PMID: 22644966 [PubMed - indexed for MEDLINE]

Feasibility of real time next generation sequencing of cancer genes linked to drug response: results from a clinical trial.

Int J Cancer. 2013 Apr 1;132(7):1547-55

Authors: Tran B, Brown AM, Bedard PL, Winquist E, Goss GD, Hotte SJ, Welch SA, Hirte HW, Zhang T, Stein LD, Ferretti V, Watt S, Jiao W, Ng K, Ghai S, Shaw P, Petrocelli T, Hudson TJ, Neel BG, Onetto N, Siu LL, McPherson JD, Kamel-Reid S, Dancey JE

Abstract
The successes of targeted drugs with companion predictive biomarkers and the technological advances in gene sequencing have generated enthusiasm for evaluating personalized cancer medicine strategies using genomic profiling. We assessed the feasibility of incorporating real-time analysis of somatic mutations within exons of 19 genes into patient management. Blood, tumor biopsy and archived tumor samples were collected from 50 patients recruited from four cancer centers. Samples were analyzed using three technologies: targeted exon sequencing using Pacific Biosciences PacBio RS, multiplex somatic mutation genotyping using Sequenom MassARRAY and Sanger sequencing. An expert panel reviewed results prior to reporting to clinicians. A clinical laboratory verified actionable mutations. Fifty patients were recruited. Nineteen actionable mutations were identified in 16 (32%) patients. Across technologies, results were in agreement in 100% of biopsy specimens and 95% of archival specimens. Profiling results from paired archival/biopsy specimens were concordant in 30/34 (88%) patients. We demonstrated that the use of next generation sequencing for real-time genomic profiling in advanced cancer patients is feasible. Additionally, actionable mutations identified in this study were relatively stable between archival and biopsy samples, implying that cancer mutations that are good predictors of drug response may remain constant across clinical stages.

PMID: 22948899 [PubMed - indexed for MEDLINE]

Altered DNA methylation landscapes of polycomb-repressed loci are associated with Gleason score and ERG oncogene expression in prostate cancer.

Clin Cancer Res. 2013 Apr 2;

Authors: Kron K, Trudel D, Pethe V, Briollais L, Fleshner N, van der Kwast T, Bapat B

Abstract
PURPOSE: To assess differentially methylated 'landscapes' according to prostate cancer (PCa) Gleason score (GS) and ERG oncogene expression status, and to determine the extent of polycomb group (PcG) target gene involvement, we sought to assess the genome-wide DNA methylation profile of PCa according to GS and ERG expression. EXPERIMENTAL DESIGN: Genomic DNA from 39 PCa specimens was hybridized to CpG island microarrays through differential methylation hybridization. We compared methylation profiles between GS and ERG expression status as well as GS stratified by ERG expression status. In addition, we compared results from our dataset to publicly available datasets of histone modifications in benign prostate cells. RESULTS: We discovered hundreds of distinct differentially methylated regions (DMRs) associated with increasing GS and ERG. Furthermore, the number of DMRs associated with GS was greatly expanded by stratifying samples into ERG positive versus ERG negative, with ERG positive/GS associated DMRs being primarily hypermethylated as opposed to hypomethylated. Finally, we found that there was a significant overlap between either GS-related or ERG hypermethylated DMRs and distinct regions in benign epithelial cells that have PcG signatures (H3K27me3, SUZ12) and lack active gene expression signatures (H3K4me3, RNA pol II). CONCLUSIONS: This work defines methylation landscapes of PCa according to GS, and suggests that initiating genetic events may influence the PCa epigenome which is further perturbed as PCa progresses. Moreover, CpG islands with silent chromatin signatures in benign cells are particularly susceptible to PCa related hypermethylation.

PMID: 23549870 [PubMed - as supplied by publisher]