Abstract
OBJECTIVES: Early detection and treatment of an oral squamous cell carcinoma (OSCC) is critical because of its rapid growth, frequent lymph-node metastasis, and poor prognosis. However, no clinically-valuable methods of early diagnosis exist, and genetic analysis of OSCCs has yielded no biomarkers. STUDY DESIGN: We investigated the expression of genes associated with inflammation in OSCCs via a quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) analysis of microarray data. Tumor and normal tissues from five patients with an OSCC were used for microarray analysis. Differentially-expressed genes, identified using permutation, local pooled error (LPE), t-tests, and significance analysis of microarrays (SAM), were selected as candidate genetic markers. RESULTS: Two groups corresponding to tissue identity were evident, implying that their differentially-expressed genes represented biological differences between tissues. Fifteen genes were identified using the Student's paired t-test (p<0.05) and the SAM, with a false discovery rate of less than 0.02. Based on gene expression, these 15 genes can be used to classify an OSCC. A genetic analysis of functional networks and ontologies, validated by using a qRT-PCR analysis of the tissue samples, identified four genes, ADAM15, CDC7, IL12RB2 and TNFRSF8, that demonstrated excellent concordance with the microarray data. CONCLUSIONS: Our study demonstrated that four genes (ADAM15, CDC7, IL12RB2 and TNFRSF8) had potential as novel biomarkers for the diagnosis and the treatment of an OSCC.