• Login
    JavaScript is disabled for your browser. Some features of this site may not work without it.
    Gene expression profiling of head and neck cancer 
    •   QMRO Home
    • Queen Mary University of London Theses
    • Theses
    • Gene expression profiling of head and neck cancer
    •   QMRO Home
    • Queen Mary University of London Theses
    • Theses
    • Gene expression profiling of head and neck cancer
    ‌
    ‌

    Browse

    All of QMROCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects
    ‌
    ‌

    Administrators only

    Login
    ‌
    ‌

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Gene expression profiling of head and neck cancer

    View/Open
    WARNERGeneExpression2004.pdf (11.04Mb)
    Publisher
    Queen Mary University of London
    Metadata
    Show full item record
    Abstract
    The purpose of this study was to classify oral squamous cell carcinomas (OSCCs) based on their gene expression profiles, to identify differentially expressed genes in these cancers, and to correlate genetic deregulation with clinical-histopathological data and patient outcome. After conducting proof of principle experiments utilizing six head and neck squamous cell carcinomas (HNSCCs) cell lines, the gene expression profiles of 20 OSCCs and subsequently an additional 8 OSCCs were determined using cDNA microarrays containing 19,200 sequences and the Binary Tree-Structured Vector Quantization (BTSVQ) method of data analysis. Two sample clusters were identified in the group of 20 tumors that correlated with T3-T4 category of disease (P=0.035) and nodal metastasis( p=0.035). Samplec lustering of 28 OSCCsa nd the 6 cell lines revealed a correlation with disease free survival. BTSVQ analysis identified a subset of 23 differentially expressed genes with the lowest quantization error scores in the cluster containing more advanceds taget umors from the 20 OSCC dataset.T he expressiono f six of these differentially expressedg enesw as validated by quantitative real-time RT-PCR. Statistical analysis of quantitative real-time RT-PCR data was performed and, after Bonferroni correction, CLDNI (p = 0.007) over-expressionw as significantly correlated with the cluster containing more advanced stage tumors. Despite the clinical heterogeneity of OSCC, molecular subtyping by cDNA microarray analysis was able to identify distinct patternso f genee xpressiona ssociatedw ith relevant clinical parameters. The 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.
    Authors
    Warner, Giles C
    URI
    http://qmro.qmul.ac.uk/xmlui/handle/123456789/1857
    Collections
    • Theses [3321]
    Copyright statements
    The copyright of this thesis rests with the author and no quotation from it or information derived from it may be published without the prior written consent of the author
    Twitter iconFollow QMUL on Twitter
    Twitter iconFollow QM Research
    Online on twitter
    Facebook iconLike us on Facebook
    • Site Map
    • Privacy and cookies
    • Disclaimer
    • Accessibility
    • Contacts
    • Intranet
    • Current students

    Modern Slavery Statement

    Queen Mary University of London
    Mile End Road
    London E1 4NS
    Tel: +44 (0)20 7882 5555

    © Queen Mary University of London.