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Expression data from head and neck squamous cell carcinoma

ABSTRACT: Forty-four paired (from the same patient) samples of head and neck squamous cell carcinoma (HNSCC) and normal tissue were studied with Affymetrix U95A chips. A stringent multi-test approach, combining 7 traditional and microarray-specific statistical tests, was used to analyze the resultant data. Candidate genes were assigned to tiers of significance based on the number of statistical tests that each gene satisfied. Representative genes (both up-regulated and down-regulated) from each of the 3 tiers would be quantified with RT-PCR on both microarray-tested and new samples of HNSCC. The goal of this study is to identify reliable differentially-expressed genes on HNSCC and to testify our hypothesis whether or not a combinatorial approach (multi-tests) to analyzing microarray data can really identify differentially-expressed genes with fewer false-positives. Keywords: disease state; tumor vs. normal

ORGANISM(S): Homo sapiens

PROVIDER: GSE6631 | GEO | 2007/01/20

SECONDARY ACCESSION(S): PRJNA98861

REPOSITORIES: GEO

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Project description:Introduction: Human Papilloma Virus (HPV) is associated with a subset of head and neck squamous cell carcinoma (HNSCC), between 15% and 35% of HNSCC harboring HPV, almost exclusively of subtype 16. Demographic and exposure differences between HPV-positive (+) and negative (-) HNSCCs suggest that HPV(+) tumors may constitute a subclass with different biology, while clinical differences have also been observed. In this study, gene expression profiles of HPV(+) and (-) tumors were compared to further explore the biological effect of HPV in HNSCC. Methods: Thirty-six HNSCC tumors were analyzed for gene expression using Affymetrix Human 133U Plus 2.0 GeneChip and for HPV using consensus primers for HPV L1, E6 and E7 by PCR and RT-PCR. Results: Eight (22%) of 36 tumors were positive for HPV, all of the HPV 16 subtype, and the HPV positive samples also expressed viral HPV E6 mRNA determined by RT-PCR. Patients with HPV(+) HNSCCs were on average younger than those with HPV(-) tumors (mean age 50.2 vs. 58.7). Statistical analysis using Significance Analysis of Microarrays (SAM) based on HPV status as a supervising parameter resulted in a list of 91 genes that were differentially expressed with statistical significance. Results for a sub-set of these genes were verified by RT-PCR. Genes highly expressed in HPV(+) samples included cell cycle regulators (p16INK4A, p18 and CDK2) and transcription factors (TAF7L, RFC4, RPA2 and TFDP2). The microarray data were also investigated using DIGMap to map genes by chromosomal location. A large number of genes on chromosome 3q24-qter was found to be overrepresented in HPV(+) tumors. Conclusion: The gene expression profile associated with HPV reflects alterations in cell cycle and proliferation signals. Further investigation of differentially expressed genes may reveal the unique pathways in HPV(+) tumors that may explain the different natural history and biological properties of these tumors. These properties may be exploited as a target of novel therapeutic agents in HNSCC treatment. Keywords: HPV, HNSCC, head and neck cancer, human, human papilloma virus

Project description:Serum-driven responses, many of which are related to wound healing, are potentially deregulated in cancer development and associated genomic alterations might have prognostic value. The current study assessed fetal bovine serum-induced transcriptomic changes for clinical relevance in head and neck squamous cell carcinoma (HNSCC) using oral keratinocyte models otherwise routinely cultured without serum, including normal keratinocytes (NOK) and the transformed keratinocyte lines SVpgC2a, SqCC/Y1 and LK0412. Bioinformatics-driven analysis of gene expression implicated primarily serum-induced terminal differentiation in NOK including alterations in 99 genes, 13 gene ontology-categories and 6 molecular networks and involvement of 7 key regulator genes. Compared to NOK, the transformed lines expressed around 3-fold lower numbers of differently expressed transcripts, unique sets of gene ontologies, molecular networks and key regulator genes for each line, and consistent absence of terminal differentiation markers. Assessment of the complete in vitro/serum exposure-derived set of differentially expressed genes (totally 180 genes) relative a clinical, information-rich HNSCC data set identified 17 survival-associated genes of which only 12 had previous association to HNSCC. Multi-step validation of the survival-associated genes relative to several independent tumor data sets, including in the Human Gene Expression Map and Human Protein Atlas databases, confirmed novel association to HNSCC for genes COTL1 and INSIG1 and novel poor outcome prediction for the genes CUL4B and PDGFRL. The definition of normal and aberrant serum responses in keratinocyte models therefore coupled new genes to HNSCC including with relevance to prognosis. Analysis of gene expression changes in serum-exposed normal and transformed cells relative the respective un-exposed states. Significantly differentially expressed genes were next assessed by bioinformatics processing using Gene Ontology categories and network analyses. Findings were also validated relative independent HNSCC data sets as well as transcriptomics and proteomics databases.

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Expression data from head and neck squamous cell carcinoma

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