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    Spectral clustering of microarray data elucidates the roles of microenvironment remodeling and immune responses in survival of head and neck squamous cell carcinoma.

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    Authors
    Thurlow, Johanna K
    Peña Murillo, Claudia L
    Hunter, Keith
    Buffa, Francesca M
    Patiar, Shalini
    Betts, Guy N J
    West, Catharine M L
    Harris, Adrian L
    Parkinson, Eric K
    Harrison, Paul R
    Ozanne, Bradford W
    Partridge, Max
    Kalna, Gabriela
    Affiliation
    The Beatson Institute for Cancer Research, Glasgow, Scotland, United Kingdom.
    Issue Date
    2010-06-10
    
    Metadata
    Show full item record
    Abstract
    PURPOSE: To identify functionally related prognostic gene sets for head and neck squamous cell carcinoma (HNSCC) by unsupervised statistical analysis of microarray data. PATIENTS AND METHODS: Microarray analysis was performed on 14 normal oral epithelium and 71 HNSCCs from patients with outcome data. Spectral clustering (SC) analysis of the data set identified multiple vectors representing distinct aspects of gene expression heterogeneity between samples. Gene ontology (GO) analysis of vector gene lists identified gene sets significantly enriched within defined biologic pathways. The prognostic significance of these was established by Cox survival analysis. RESULTS: The most influential SC vectors were V2 and V3. V2 separated normal from tumor samples. GO analysis of V2 gene lists identified pathways with heterogeneous expression between HNSCCs, notably focal adhesion (FA)/extracellular matrix remodeling and cytokine-cytokine receptor (CR) interactions. Similar analysis of V3 gene lists identified further heterogeneity in CR pathways. V2CR genes represent an innate immune response, whereas high expression of V3CR genes represented an adaptive immune response that was not dependent on human papillomavirus status. Survival analysis demonstrated that the FA gene set was prognostic of poor outcome, whereas classification for adaptive immune response by the CR gene set was prognostic of good outcome. A combined FA&CR model dramatically exceeded the performance of current clinical classifiers (P < .001 in our cohort and, importantly, P = .007 in an independent cohort of 60 HNSCCs). CONCLUSION: The application of SC and GO algorithms to HNSCC microarray data identified gene sets highly significant for predicting patient outcome. Further large-scale studies will establish the usefulness of these gene sets in the clinical management of HNSCC.
    Citation
    Spectral clustering of microarray data elucidates the roles of microenvironment remodeling and immune responses in survival of head and neck squamous cell carcinoma. 2010, 28 (17):2881-8 J Clin Oncol
    Journal
    Journal of Clinical Oncology
    URI
    http://hdl.handle.net/10541/109051
    DOI
    10.1200/JCO.2009.24.8724
    PubMed ID
    20458058
    Type
    Article
    Language
    en
    ISSN
    1527-7755
    ae974a485f413a2113503eed53cd6c53
    10.1200/JCO.2009.24.8724
    Scopus Count
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