Abstract
Abstract Introduction: Patients with head and neck squamous cell carcinoma (HNSCC) are at high risk for pulmonary metastasis as well as other primary upper aerodigestive malignancies, most commonly lung squamous cell carcinoma (LSCC). Despite adequate tissue sampling, differentiating a pulmonary nodule with SCC features remains a diagnostic challenge. Our goal was to develop a genomic-based classification that can identify the origin of a lung SCC. Methods: RNA extracted from patients with LSCC (n = 8) and HNSCC (n = 8) was hybridized to oligonucleotide microarrays containing 44363 genes. Novel statistical algorithms identified discriminating genes that prospectively classified 24 patients with HNSCC or LSCC in three unaffiliated institutions (Columbia University, University of Minnesota, University of Pennsylvania). Quantitative PCR and immunohistochemistry confirmed results. Results: Gene expression profiling revealed 65 discriminating genes that can predict LSCC from HNSCC. Genes consistently differentially expressed (p Conclusions: These results demonstrate that gene expression profiling can discriminate primary LSCC from HNSCC tumors and has yielded genes not previously described that have major diagnostic importance. Transcript profiling has revealed pathways in the development of squamous cell carcinoma that may have major significance for future targeted biologic therapies.
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