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Search Results: 1 - 10 of 115 matches for " Calum MacAulay "
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Established and Emerging Optical Technologies for the Real-Time Detection of Cervical Neoplasia: A Review  [PDF]
Breana Hill, Sylvia F. Lam, Pierre Lane, Calum MacAulay, Leonid Fradkin, Michele Follen
Journal of Cancer Therapy (JCT) , 2017, DOI: 10.4236/jct.2017.813105
Abstract: Cervical cancer remains a critically important problem for women, especially those women in the developing world where the case-fatality rate is high. There are an estimated 528,000 cases and 266,000 deaths worldwide. Established screening and detection programs in the developed world have lowered the mortality from 40/100,000 to 2/100,000 over the last 60 years. The standard of care has been and continues to be: a screening Papanicolaou smear with or without Human Papilloma Virus (HPV) testing; followed by colposcopy and biopsies and if the smear is abnormal; and followed by treatment if the biopsies show high grade disease (cervical intraepithelial neoplasia (CIN) grades 2 and 3 and Carcinoma-in-situ). Low grade lesions (Pap smears with Atypical Cells of Uncertain Significance (ASCUS), Low Grade Squamous Intraepithelial Lesions (LGSIL), biopsies showing HPV changes or showing CIN 1); are usually followed for two years and then treated if persistent. Treatment can be performed with loop excision, LASER, or cryotherapy. Loop excision yields a specimen which can be reviewed to establish the diagnosis more accurately. LASER vaporizes the lesion and cryotherapy leads to tissue destruction. Under long term study; loop excision, LASER, and cryotherapy have the same rate of cure.
A stepwise framework for the normalization of array CGH data
Mehrnoush Khojasteh, Wan L Lam, Rabab K Ward, Calum MacAulay
BMC Bioinformatics , 2005, DOI: 10.1186/1471-2105-6-274
Abstract: After an investigation of the systematic variations in the data from two array CGH platforms, SMRT (Sub Mega base Resolution Tiling) BAC arrays and cDNA arrays of Pollack et al., we have developed a stepwise normalization framework integrating novel and existing normalization methods in order to reduce intensity, spatial, plate and background biases. We used stringent measures to quantify the performance of this stepwise normalization using data derived from 5 sets of experiments representing self-self hybridizations, replicated experiments, detection of single copy changes, array CGH experiments which mimic cell population heterogeneity, and array CGH experiments simulating different levels of gene amplifications and deletions. Our results demonstrate that the three-step normalization procedure provides significant improvement in the sensitivity of detection of single copy changes compared to conventional single step normalization approaches in both SMRT BAC array and cDNA array platforms.The proposed stepwise normalization framework preserves the minute copy number changes while removing the observed systematic biases.Microarray-based Comparative Genomic Hybridization (array CGH) is used to detect the aberrations in segmental copy numbers at chromosomal loci represented by DNA clones with known genomic locations [1]. CGH microarrays typically contain tens of thousands of spotted DNA sequences such as those derived from bacterial artificial chromosomes (BACs). Sample DNA from a test and a reference genome are labelled with different fluorescent dyes (usually Cyanine-3 and Cyanine-5 dyes) and then hybridized to the genomic microarray. The fluorescent signal intensity of each spot on the microarray serves as a relative measure of the amount of sample DNA bound to the DNA sequence of that spot. The ratio between the Cyanine-3 and the Cyanine-5 intensity of each spot reflects the relative quantities of the test and reference DNA samples.The ratio of the two fluorescent
MD-SeeGH: a platform for integrative analysis of multi-dimensional genomic data
Bryan Chi, Ronald J deLeeuw, Bradley P Coe, Raymond T Ng, Calum MacAulay, Wan L Lam
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-243
Abstract: To address this issue, we have developed an integrative genomic analysis platform MD-SeeGH, a software tool that allows users to rapidly and directly analyze genomic datasets spanning multiple genomic experiments. With MD-SeeGH, users have the flexibility to easily update datasets in accordance with new genomic builds, make a quality assessment of data using the filtering features, and identify genetic alterations within single or across multiple experiments. Multiple sample analysis in MD-SeeGH allows users to compare profiles from many experiments alongside tracks containing detailed localized gene information, microRNA, CpG islands, and copy number variations.MD-SeeGH is a new platform for the integrative analysis of diverse microarray data, facilitating multiple profile analyses and group comparisons.Recent advances in global genomic profiling methodologies have enabled multi-dimensional characterization of biological systems. The deciphering of downstream effects of genetic and epigenetic alterations on expression patterns is paramount in understanding disease phenotype and requires the integration of segmental DNA copy number status, DNA methylation state and single nucleotide polymorphism (SNP) status. The large scale generation of such data has created a need for robust software to integrate multiple large genetically linked data sets generated on diverse microarray platforms. Although several visualization software programs are available publicly (for example [1-5]), there is a growing demand for new bioinformatics tools that allow for the concerted analysis of multiple genome-wide experiments derived from different experimental platforms [6]. Blue Fuse [7] and CGH Analytics [8], two commercially available software tools, offer integrative analysis with expression data but neither contain the full feature set that we deem necessary (Table 1). SeeGH (v1.6) was initially developed to view primarily array CGH data [2] but as we continued to use and develop the
Effect of active smoking on the human bronchial epithelium transcriptome
Raj Chari, Kim M Lonergan, Raymond T Ng, Calum MacAulay, Wan L Lam, Stephen Lam
BMC Genomics , 2007, DOI: 10.1186/1471-2164-8-297
Abstract: Twenty-four SAGE profiles of the bronchial epithelium of eight current, twelve former and four never smokers were generated and analyzed. In total, 3,111,471 SAGE tags representing over 110 thousand potentially unique transcripts were generated, comprising the largest human SAGE study to date. We identified 1,733 constitutively expressed genes in current, former and never smoker transcriptomes. We have also identified both reversible and irreversible gene expression changes upon cessation of smoking; reversible changes were frequently associated with either xenobiotic metabolism, nucleotide metabolism or mucus secretion. Increased expression of TFF3, CABYR, and ENTPD8 were found to be reversible upon smoking cessation. Expression of GSK3B, which regulates COX2 expression, was irreversibly decreased. MUC5AC expression was only partially reversed. Validation of select genes was performed using quantitative RT-PCR on a secondary cohort of nine current smokers, seven former smokers and six never smokers.Expression levels of some of the genes related to tobacco smoking return to levels similar to never smokers upon cessation of smoking, while expression of others appears to be permanently altered despite prolonged smoking cessation. These irreversible changes may account for the persistent lung cancer risk despite smoking cessation.Lung cancer has the highest mortality rate among all types of malignancies, accounting for approximately 29% of all cancer-related deaths in the United States [1]. It has been estimated that in 2006 alone, the number of new lung cancer cases will exceed 174,000 and approximately 163,000 people will die of this disease [1]. Tobacco smoking accounts for 85% of the lung cancers. Former heavy smokers remain at an elevated risk for developing lung cancer even years after they stop smoking [2,3]. Fifty percent of newly diagnosed lung cancer patients are former smokers [4]. It is therefore important to understand the effects of tobacco smoking on the
SeeGH – A software tool for visualization of whole genome array comparative genomic hybridization data
Bryan Chi, Ronald J deLeeuw, Bradley P Coe, Calum MacAulay, Wan L Lam
BMC Bioinformatics , 2004, DOI: 10.1186/1471-2105-5-13
Abstract: We have developed a visualization tool for displaying whole genome array CGH data in the context of chromosomal location. SeeGH is an application that translates spot signal ratio data from array CGH experiments to displays of high resolution chromosome profiles. Data is imported from a simple tab delimited text file obtained from standard microarray image analysis software. SeeGH processes the signal ratio data and graphically displays it in a conventional CGH karyotype diagram with the added features of magnification and DNA segment annotation. In this process, SeeGH imports the data into a database, calculates the average ratio and standard deviation for each replicate spot, and links them to chromosome regions for graphical display. Once the data is displayed, users have the option of hiding or flagging DNA segments based on user defined criteria, and retrieve annotation information such as clone name, NCBI sequence accession number, ratio, base pair position on the chromosome, and standard deviation.SeeGH represents a novel software tool used to view and analyze array CGH data. The software gives users the ability to view the data in an overall genomic view as well as magnify specific chromosomal regions facilitating the precise localization of genetic alterations. SeeGH is easily installed and runs on Microsoft Windows 2000 or later environments.Metaphase comparative genomic hybridization (CGH) is a molecular cytogenetic technique used to detect segmental DNA copy number differences between two samples of DNA [1]. This is accomplished by a competitive hybridization of two differentially labeled samples to normal metaphase chromosomes, allowing the detection of single copy number changes at a resolution of 10–20 Mb [1]. Array CGH improves on the resolution of copy number profiling by utilizing discrete genomic loci spotted onto glass microscope slides as opposed to metaphase chromosomes as the hybridization target [2]. In array CGH the resolution in detecting s
Transcriptome Profiles of Carcinoma-in-Situ and Invasive Non-Small Cell Lung Cancer as Revealed by SAGE
Kim M. Lonergan,Raj Chari,Bradley P. Coe,Ian M. Wilson,Ming-Sound Tsao,Raymond T. Ng,Calum MacAulay,Stephen Lam,Wan L. Lam
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0009162
Abstract: Non-small cell lung cancer (NSCLC) presents as a progressive disease spanning precancerous, preinvasive, locally invasive, and metastatic lesions. Identification of biological pathways reflective of these progressive stages, and aberrantly expressed genes associated with these pathways, would conceivably enhance therapeutic approaches to this devastating disease.
SIGMA2: A system for the integrative genomic multi-dimensional analysis of cancer genomes, epigenomes, and transcriptomes
Raj Chari, Bradley P Coe, Craig Wedseltoft, Marie Benetti, Ian M Wilson, Emily A Vucic, Calum MacAulay, Raymond T Ng, Wan L Lam
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-422
Abstract: Here, we present SIGMA2, a system for the integrative genomic multi-dimensional analysis of cancer genomes, epigenomes, and transcriptomes. Multi-dimensional datasets can be simultaneously visualized and analyzed with respect to each dimension, allowing combinatorial integration of the different assays belonging to the different 'omics.The identification of genes altered at multiple levels such as copy number, loss of heterozygosity (LOH), DNA methylation and the detection of consequential changes in gene expression can be concertedly performed, establishing SIGMA2 as a novel tool to facilitate the high throughput systems biology analysis of cancer.Multiple mechanisms of gene disruption have been shown to be important in the development of cancer. Genetic alterations (mutations, changes in gene dosage, allele imbalance) and epigenetic alterations (changes in DNA methylation and histone modification states) are responsible for changing the expression of genes. High throughput approaches have afforded the ability to interrogate the genomic, epigenomic and gene expression (transcriptomic) profiles at unprecedented resolution [1-6]. However, a gene can be disrupted by one or by a combination of mechanisms, therefore, investigation in a single 'omics dimension (genomics, epigenomics, or transcriptomics) alone cannot detect all disrupted genes in a given tumor. Moreover, individual tumors may have different patterns of gene disruption, by different mechanisms for a given gene while achieving the same net effect on phenotype. Hence, a multi-dimensional approach is required to identify the causal events at the DNA level and understand their downstream consequences.The current state of software for global profile comparison typically focuses on analyzing and displaying data from a single dimension, for example CGH Fusion (infoQuant Ltd, London, UK) for DNA copy number profile analysis and GeneSpring (Agilent Technologies, Santa Clara, CA, USA) for gene expression profile ana
Canadian Optically-guided approach for Oral Lesions Surgical (COOLS) trial: study protocol for a randomized controlled trial
Catherine F Poh, J Scott Durham, Penelope M Brasher, Donald W Anderson, Kenneth W Berean, Calum E MacAulay, J Jack Lee, Miriam P Rosin
BMC Cancer , 2011, DOI: 10.1186/1471-2407-11-462
Abstract: This paper describes the study design of a randomized, multi-centre, double blind, controlled surgical trial, the COOLS trial. Nine institutions across Canada will recruit a total of 400 patients with oral severe dysplasia or carcinoma in situ (N = 160) and invasive squamous cell carcinoma (N = 240). Patients will be stratified by participating institution and histology grade and randomized equally into FV-guided surgery (experimental arm) or white light-guided surgery (control arm). The primary endpoint is a composite of recurrence at or 1 cm within the previous surgery site with 1) the same or higher grade histology compared to the initial diagnosis (i.e., the diagnosis used for randomization); or 2) further treatment due to the presence of severe dysplasia or higher degree of change at follow-up. This is the first randomized, multi-centre trial to validate the effectiveness of the FV-guided surgery.In this paper we described the strategies, novelty, and challenges of this unique trial involving a surgical approach guided by the FV technology. The success of the trial requires training, coordination, and quality assurance across multiple sites within Canada. The COOLS trial, an example of translational research, may result in reduced recurrence rates following surgical treatment of early-stage oral cancer with significant impacts on survival, morbidity, patients' quality of life and the cost to the health care system.Clinicaltrials.gov NCT01039298Oral cancer is a major health problem worldwide, accounting for 274,000 new cases and 145,000 deaths annually [1]. Although it occurs at a site that is easily accessible for examination it is often diagnosed at an advanced stage, with 5-year survival rates ranging from 30-60%, depending on the global locale. Treatment of early stage squamous cell carcinoma is an essential component of effective oral cancer management; a recent large (~190,000) randomized trial of a screening program showed the mortality rate ratio between
SIGMA: A System for Integrative Genomic Microarray Analysis of Cancer Genomes
Raj Chari, William W Lockwood, Bradley P Coe, Anna Chu, Devon Macey, Andrew Thomson, Jonathan J Davies, Calum MacAulay, Wan L Lam
BMC Genomics , 2006, DOI: 10.1186/1471-2164-7-324
Abstract: We have created a user-friendly java application to facilitate sophisticated visualization and analysis such as cross-tumor and cross-platform comparisons. To demonstrate the utility of this software, we assembled array CGH data representing Affymetrix SNP chip, Stanford cDNA arrays and whole genome tiling path array platforms for cross comparison. This cancer genome database contains 267 profiles from commonly used cancer cell lines representing 14 different tissue types.In this study we have developed an application for the visualization and analysis of data from high resolution array CGH platforms that can be adapted for analysis of multiple types of high throughput genomic datasets. Furthermore, we invite researchers using array CGH technology to deposit both their raw and processed data, as this will be a continually expanding database of cancer genomes. This publicly available resource, the System for Integrative Genomic Microarray Analysis (SIGMA) of cancer genomes, can be accessed at http://sigma.bccrc.ca webcite.Array comparative genomic hybridization (CGH) is a method used to detect segmental DNA copy number alterations and is widely used to discover chromosomal aberrations in cancer and other genetic diseases [1,2]. In this method, differentially labeled genomic DNA samples are competitively hybridized to chromosomal targets, and the copy number balance between the two samples is reflected by their signal intensity ratio. Numerous array CGH platforms exist; these vary in the type of elements present on the array and their corresponding coverage of the human genome. With the development of high resolution, genome wide arrays, tens of thousands of loci can be evaluated for copy number status, facilitating the high throughput search for genes potentially involved in pathogenesis. This has allowed the identification of discrete regions of alteration that may have been missed by traditional cytogenetic methods and has proven to be a useful platform for explori
Comprehensive serial analysis of gene expression of the cervical transcriptome
Ashleen Shadeo, Raj Chari, Greg Vatcher, Jennifer Campbell, Kim M Lonergan, Jasenka Matisic, Dirk van Niekerk, Thomas Ehlen, Dianne Miller, Michele Follen, Wan L Lam, Calum MacAulay
BMC Genomics , 2007, DOI: 10.1186/1471-2164-8-142
Abstract: We have sequenced 691,390 tags from four L-SAGE libraries increasing the existing gene expression data on cervical tissue by 20 fold. One-hundred and eighteen unique tags were highly expressed in normal cervical tissue and 107 of them mapped to unique genes, most belong to the ribosomal, calcium-binding and keratinizing gene families. We assessed these genes for aberrant expression in CIN III and five genes showed altered expression. In addition, we have identified twelve unique HPV 16 SAGE tags in the CIN III libraries absent in the normal libraries.Establishing a baseline of gene expression in normal cervical tissue is key for identifying changes in cancer. We demonstrate the utility of this baseline data by identifying genes with aberrant expression in CIN III when compared to normal tissue.Approximately 500,000 women are diagnosed with cervical cancer worldwide each year and more than half of them will die from this disease [1]. The highest incidence rates are observed in developing countries where it is the second most prevalent cancer in women and remains a leading cause of cancer related death [1]. Widely implemented screening programs have been responsible for the much lower incidence and mortality rates seen in the developed world. Present day screening methods primarily identify precancer lesions termed cervical intraepithelial neoplasia (CIN). CIN lesions are classified into three subgroups, CIN I, CIN II and CIN III, corresponding to mild, moderate and severe dysplasia/carcinoma in situ (CIS), respectively. CIN III lesions have a high likelihood of progression to invasive disease if left untreated [2]. Human Papillomavirus (HPV) has long been established as a necessary but not sufficient cause for cervical carcinoma development. HPV is detected in 99% of invasive disease, 94% of CIN lesions and 46% of normal cervical epithelium [2]. The high risk strains HPV 16 and HPV 18 are most prevalent in invasive disease.A comprehensive characterization of gene exp
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