Cancer Research Infection and Cancer: Biology, Therapeutics, and Prevention  AACR Conference on Molecular Diagnostics - 2008
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[Cancer Research 64, 55-63, January 1, 2004]
© 2004 American Association for Cancer Research


Regular Articles

Identification of a Gene Expression Signature Associated with Recurrent Disease in Squamous Cell Carcinoma of the Head and Neck

Matthew A. Ginos1, Grier P. Page2, Bryan S. Michalowicz3, Ketan J. Patel1, Sonja E. Volker1, Stefan E. Pambuccian4, Frank G. Ondrey5, George L. Adams5 and Patrick M. Gaffney1

1Division of Hematology, Oncology and Transplantation, Department of Medicine, University of Minnesota School of Medicine, Minneapolis, Minnesota; 2Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama; 3Department of Preventive Sciences, University of Minnesota School of Dentistry, Minneapolis, Minnesota; 4Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, Minnesota; and 5Department of Otolaryngology and Head and Neck Surgery, University of Minnesota School of Medicine, Minneapolis, Minnesota

Molecular studies of squamous cell carcinoma of the head and neck (HNSCC) have demonstrated multiple genetic abnormalities such as activation of various oncogenes (Ras, Myc, epidermal growth factor receptor, and cyclin D1), tumor suppressor gene inactivation (TP53 and p16), and loss of heterozygosity at numerous chromosomal locations. Despite these observations, accurate and reliable biomarkers that predict patients at highest risk for local recurrence have yet to be defined. In an effort to identify gene expression signatures that may serve as biomarkers, we studied 41 squamous cell carcinoma tumors (25 primary and 16 locally recurrent) from various anatomical sites and 13 normal oral mucosal biopsy samples from healthy volunteers with microarray analysis using Affymetrix U133A GeneChip arrays. Differentially expressed genes were identified by calculating generalized t tests (P < 0.001) and applying a series of filtering criteria to yield a highly discriminant list of 2890 genes. Hierarchical clustering and image generation using standard software were used to visualize gene expression signatures. Several gene expression signatures were readily identifiable in the HNSCC tumors, including signatures associated with proliferation, extracellular matrix production, cytokine/chemokine expression, and immune response. Of particular interest was the association of a gene expression signature enriched for genes involved in tumor invasion and metastasis with patients experiencing locally recurrent disease. Notably, these tumors also demonstrated a marked absence of an immune response signature suggesting that modulation of tumor-specific immune responses may play a role in local treatment failure. These data provide evidence for a new gene expression-based biomarker of local treatment failure in HNSCC.




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HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
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Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
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Copyright © 2004 by the American Association for Cancer Research.