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Dive into the research topics where Kim M. Lonergan is active.

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Featured researches published by Kim M. Lonergan.


PLOS ONE | 2011

Human Cancer Long Non-Coding RNA Transcriptomes

Ewan A. Gibb; Emily A. Vucic; Katey S. S. Enfield; Greg L. Stewart; Kim M. Lonergan; Jennifer Y. Kennett; Daiana D. Becker-Santos; Calum MacAulay; Stephen Lam; Carolyn J. Brown; Wan L. Lam

Once thought to be a part of the ‘dark matter’ of the genome, long non-coding RNAs (lncRNAs) are emerging as an integral functional component of the mammalian transcriptome. LncRNAs are a novel class of mRNA-like transcripts which, despite no known protein-coding potential, demonstrate a wide range of structural and functional roles in cellular biology. However, the magnitude of the contribution of lncRNA expression to normal human tissues and cancers has not been investigated in a comprehensive manner. In this study, we compiled 272 human serial analysis of gene expression (SAGE) libraries to delineate lncRNA transcription patterns across a broad spectrum of normal human tissues and cancers. Using a novel lncRNA discovery pipeline we parsed over 24 million SAGE tags and report lncRNA expression profiles across a panel of 26 different normal human tissues and 19 human cancers. Our findings show extensive, tissue-specific lncRNA expression in normal tissues and highly aberrant lncRNA expression in human cancers. Here, we present a first generation atlas for lncRNA profiling in cancer.


BMC Genomics | 2007

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

BackgroundLung cancer is the most common cause of cancer-related deaths. Tobacco smoke exposure is the strongest aetiological factor associated with lung cancer. In this study, using serial analysis of gene expression (SAGE), we comprehensively examined the effect of active smoking by comparing the transcriptomes of clinical specimens obtained from current, former and never smokers, and identified genes showing both reversible and irreversible expression changes upon smoking cessation.ResultsTwenty-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.ConclusionExpression 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.


American Journal of Respiratory Cell and Molecular Biology | 2014

DNA Methylation Is Globally Disrupted and Associated with Expression Changes in Chronic Obstructive Pulmonary Disease Small Airways

Emily A. Vucic; Raj Chari; Kelsie L. Thu; Ian M. Wilson; Allison M. Cotton; Jennifer Y. Kennett; May Zhang; Kim M. Lonergan; Katrina Steiling; Carolyn J. Brown; Annette McWilliams; Keishi Ohtani; Marc E. Lenburg; Don D. Sin; Avrum Spira; Calum MacAulay; Stephen Lam; Wan L. Lam

DNA methylation is an epigenetic modification that is highly disrupted in response to cigarette smoke and involved in a wide spectrum of malignant and nonmalignant diseases, but surprisingly not previously assessed in small airways of patients with chronic obstructive pulmonary disease (COPD). Small airways are the primary sites of airflow obstruction in COPD. We sought to determine whether DNA methylation patterns are disrupted in small airway epithelia of patients with COPD, and evaluate whether changes in gene expression are associated with these disruptions. Genome-wide methylation and gene expression analysis were performed on small airway epithelial DNA and RNA obtained from the same patient during bronchoscopy, using Illuminas Infinium HM27 and Affymetrixs Genechip Human Gene 1.0 ST arrays. To control for known effects of cigarette smoking on DNA methylation, methylation and gene expression profiles were compared between former smokers with and without COPD matched for age, pack-years, and years of smoking cessation. Our results indicate that aberrant DNA methylation is (1) a genome-wide phenomenon in small airways of patients with COPD, and (2) associated with altered expression of genes and pathways important to COPD, such as the NF-E2-related factor 2 oxidative response pathway. DNA methylation is likely an important mechanism contributing to modulation of genes important to COPD pathology. Because these methylation events may underlie disease-specific gene expression changes, their characterization is a critical first step toward the development of epigenetic markers and an opportunity for developing novel epigenetic therapeutic interventions for COPD.


Cancer and Metastasis Reviews | 2010

Integrating the multiple dimensions of genomic and epigenomic landscapes of cancer

Raj Chari; Kelsie L. Thu; Ian M. Wilson; William W. Lockwood; Kim M. Lonergan; Bradley P. Coe; Chad A. Malloff; Adi F. Gazdar; Stephen Lam; Cathie Garnis; Calum MacAulay; Carlos E. Alvarez; Wan L. Lam

Advances in high-throughput, genome-wide profiling technologies have allowed for an unprecedented view of the cancer genome landscape. Specifically, high-density microarrays and sequencing-based strategies have been widely utilized to identify genetic (such as gene dosage, allelic status, and mutations in gene sequence) and epigenetic (such as DNA methylation, histone modification, and microRNA) aberrations in cancer. Although the application of these profiling technologies in unidimensional analyses has been instrumental in cancer gene discovery, genes affected by low-frequency events are often overlooked. The integrative approach of analyzing parallel dimensions has enabled the identification of (a) genes that are often disrupted by multiple mechanisms but at low frequencies by any one mechanism and (b) pathways that are often disrupted at multiple components but at low frequencies at individual components. These benefits of using an integrative approach illustrate the concept that the whole is greater than the sum of its parts. As efforts have now turned toward parallel and integrative multidimensional approaches for studying the cancer genome landscape in hopes of obtaining a more insightful understanding of the key genes and pathways driving cancer cells, this review describes key findings disseminating from such high-throughput, integrative analyses, including contributions to our understanding of causative genetic events in cancer cell biology.


Oral Oncology | 2011

Long non-coding RNAs are expressed in oral mucosa and altered in oral premalignant lesions

Ewan A. Gibb; Katey S. S. Enfield; Greg L. Stewart; Kim M. Lonergan; Raj Chari; Raymond T. Ng; Lewei Zhang; Calum MacAulay; Miriam P. Rosin; Wan L. Lam

Oral epithelial dysplasias are believed to progress through a series of histopathological stages; from mild to severe dysplasia, to carcinoma in situ, and finally to invasive OSCC. Underlying this change in histopathological grade are gross chromosome alterations and changes in gene expression of both protein-coding genes and non-coding RNAs. Recent papers have described associations of aberrant expression of microRNAs, one class of non-coding RNAs, with oral cancer. However, expression profiling of long non-coding RNAs (lncRNAs) has not been reported. Long non-coding RNAs are a novel class of mRNA-like transcripts with no protein coding capacity, but with a variety of functions including roles in epigenetics and gene regulation. In recent reports, the aberrant expression of lncRNAs has been associated with human cancers, suggesting a critical role in tumorigenesis. Here, we present the first long non-coding RNA expression map for the human oral mucosa. We describe the expression of 325 long non-coding RNAs, suggesting lncRNA expression contributes significantly to the oral transcriptome. Intriguingly, ∼60% of the detected lncRNAs show aberrant expression in oral premalignant lesions. A number of these lncRNAs have been previously associated with other human cancers.


BMC Medical Genomics | 2010

A sequence-based approach to identify reference genes for gene expression analysis

Raj Chari; Kim M. Lonergan; Larissa A. Pikor; Bradley P. Coe; Chang Qi Zhu; Timothy H.W. Chan; Calum MacAulay; Ming-Sound Tsao; Stephen Lam; Raymond T. Ng; Wan L. Lam

BackgroundAn important consideration when analyzing both microarray and quantitative PCR expression data is the selection of appropriate genes as endogenous controls or reference genes. This step is especially critical when identifying genes differentially expressed between datasets. Moreover, reference genes suitable in one context (e.g. lung cancer) may not be suitable in another (e.g. breast cancer). Currently, the main approach to identify reference genes involves the mining of expression microarray data for highly expressed and relatively constant transcripts across a sample set. A caveat here is the requirement for transcript normalization prior to analysis, and measurements obtained are relative, not absolute. Alternatively, as sequencing-based technologies provide digital quantitative output, absolute quantification ensues, and reference gene identification becomes more accurate.MethodsSerial analysis of gene expression (SAGE) profiles of non-malignant and malignant lung samples were compared using a permutation test to identify the most stably expressed genes across all samples. Subsequently, the specificity of the reference genes was evaluated across multiple tissue types, their constancy of expression was assessed using quantitative RT-PCR (qPCR), and their impact on differential expression analysis of microarray data was evaluated.ResultsWe show that (i) conventional references genes such as ACTB and GAPDH are highly variable between cancerous and non-cancerous samples, (ii) reference genes identified for lung cancer do not perform well for other cancer types (breast and brain), (iii) reference genes identified through SAGE show low variability using qPCR in a different cohort of samples, and (iv) normalization of a lung cancer gene expression microarray dataset with or without our reference genes, yields different results for differential gene expression and subsequent analyses. Specifically, key established pathways in lung cancer exhibit higher statistical significance using a dataset normalized with our reference genes relative to normalization without using our reference genes.ConclusionsOur analyses found NDUFA1, RPL19, RAB5C, and RPS18 to occupy the top ranking positions among 15 suitable reference genes optimal for normalization of lung tissue expression data. Significantly, the approach used in this study can be applied to data generated using new generation sequencing platforms for the identification of reference genes optimal within diverse contexts.


PLOS ONE | 2010

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

Background 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. Methodology/Principal Findings Through the construction and analysis of SAGE libraries, we have determined transcriptome profiles for preinvasive carcinoma-in-situ (CIS) and invasive squamous cell carcinoma (SCC) of the lung, and compared these with expression profiles generated from both bronchial epithelium, and precancerous metaplastic and dysplastic lesions using Ingenuity Pathway Analysis. Expression of genes associated with epidermal development, and loss of expression of genes associated with mucociliary biology, are predominant features of CIS, largely shared with precancerous lesions. Additionally, expression of genes associated with xenobiotic metabolism/detoxification is a notable feature of CIS, and is largely maintained in invasive cancer. Genes related to tissue fibrosis and acute phase immune response are characteristic of the invasive SCC phenotype. Moreover, the data presented here suggests that tissue remodeling/fibrosis is initiated at the early stages of CIS. Additionally, this study indicates that alteration in copy-number status represents a plausible mechanism for differential gene expression in CIS and invasive SCC. Conclusions/Significance This study is the first report of large-scale expression profiling of CIS of the lung. Unbiased expression profiling of these preinvasive and invasive lesions provides a platform for further investigations into the molecular genetic events relevant to early stages of squamous NSCLC development. Additionally, up-regulated genes detected at extreme differences between CIS and invasive cancer may have potential to serve as biomarkers for early detection.


BMC Genomics | 2008

Up regulation in gene expression of chromatin remodelling factors in cervical intraepithelial neoplasia.

Ashleen Shadeo; Raj Chari; Kim M. Lonergan; Andrea L. Pusic; Dianne Miller; Tom Ehlen; Dirk van Niekerk; Jasenka Matisic; Rebecca Richards-Kortum; Michele Follen; Martial Guillaud; Wan L. Lam; Calum MacAulay

BackgroundThe highest rates of cervical cancer are found in developing countries. Frontline monitoring has reduced these rates in developed countries and present day screening programs primarily identify precancerous lesions termed cervical intraepithelial neoplasias (CIN). CIN lesions described as mild dysplasia (CIN I) are likely to spontaneously regress while CIN III lesions (severe dysplasia) are likely to progress if untreated. Thoughtful consideration of gene expression changes paralleling the progressive pre invasive neoplastic development will yield insight into the key casual events involved in cervical cancer development.ResultsIn this study, we have identified gene expression changes across 16 cervical cases (CIN I, CIN II, CIN III and normal cervical epithelium) using the unbiased long serial analysis of gene expression (L-SAGE) method. The 16 L-SAGE libraries were sequenced to the level of 2,481,387 tags, creating the largest SAGE data collection for cervical tissue worldwide. We have identified 222 genes differentially expressed between normal cervical tissue and CIN III. Many of these genes influence biological functions characteristic of cancer, such as cell death, cell growth/proliferation and cellular movement. Evaluation of these genes through network interactions identified multiple candidates that influence regulation of cellular transcription through chromatin remodelling (SMARCC1, NCOR1, MRFAP1 and MORF4L2). Further, these expression events are focused at the critical junction in disease development of moderate dysplasia (CIN II) indicating a role for chromatin remodelling as part of cervical cancer development.ConclusionWe have created a valuable publically available resource for the study of gene expression in precancerous cervical lesions. Our results indicate deregulation of the chromatin remodelling complex components and its influencing factors occur in the development of CIN lesions. The increase in SWI/SNF stabilizing molecule SMARCC1 and other novel genes has not been previously illustrated as events in the early stages of dysplasia development and thus not only provides novel candidate markers for screening but a biological function for targeting treatment.


Oncogene | 2014

EYA4 is inactivated biallelically at a high frequency in sporadic lung cancer and is associated with familial lung cancer risk

Ian M. Wilson; Emily A. Vucic; Katey S. S. Enfield; Kelsie L. Thu; Yuan Zhang; Raj Chari; William W. Lockwood; Niki Radulovich; Daniel T. Starczynowski; Judit P. Banáth; May Zhang; Andrea L. Pusic; Megan Fuller; Kim M. Lonergan; David Rowbotham; John Yee; John C. English; Timon P.H. Buys; Suhaida A. Selamat; Ite A. Laird-Offringa; Pengyuan Liu; Marshall W. Anderson; Ming You; Ming-Sound Tsao; Carolyn J. Brown; Kevin L. Bennewith; Calum MacAulay; Aly Karsan; Adi F. Gazdar; Stephen Lam

In an effort to identify novel biallelically inactivated tumor suppressor genes (TSGs) in sporadic invasive and preinvasive non-small-cell lung cancer (NSCLC) genomes, we applied a comprehensive integrated multiple ‘omics’ approach to investigate patient-matched, paired NSCLC tumor and non-malignant parenchymal tissues. By surveying lung tumor genomes for genes concomitantly inactivated within individual tumors by multiple mechanisms, and by the frequency of disruption in tumors across multiple cohorts, we have identified a putative lung cancer TSG, Eyes Absent 4 (EYA4). EYA4 is frequently and concomitantly deleted, hypermethylated and underexpressed in multiple independent lung tumor data sets, in both major NSCLC subtypes and in the earliest stages of lung cancer. We found that decreased EYA4 expression is not only associated with poor survival in sporadic lung cancers but also that EYA4 single-nucleotide polymorphisms are associated with increased familial cancer risk, consistent with EYA4s proximity to the previously reported lung cancer susceptibility locus on 6q. Functionally, we found that EYA4 displays TSG-like properties with a role in modulating apoptosis and DNA repair. Cross-examination of EYA4 expression across multiple tumor types suggests a cell-type-specific tumorigenic role for EYA4, consistent with a tumor suppressor function in cancers of epithelial origin. This work shows a clear role for EYA4 as a putative TSG in NSCLC.


BMC Genomics | 2007

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

BackgroundMore than half of the approximately 500,000 women diagnosed with cervical cancer worldwide each year will die from this disease. Investigation of genes expressed in precancer lesions compared to those expressed in normal cervical epithelium will yield insight into the early stages of disease. As such, establishing a baseline from which to compare to, is critical in elucidating the abnormal biology of disease. In this study we examine the normal cervical tissue transcriptome and investigate the similarities and differences in relation to CIN III by Long-SAGE (L-SAGE).ResultsWe 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.ConclusionEstablishing 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.

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Wan L. Lam

University of British Columbia

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Stephen Lam

University of British Columbia

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Raymond T. Ng

University of British Columbia

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Ian M. Wilson

University of British Columbia

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Emily A. Vucic

University of British Columbia

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Marco A. Marra

University of British Columbia

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Steven J.M. Jones

University of British Columbia

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Timothy H.W. Chan

University of British Columbia

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