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  • Title: Molecular phenotyping of thyroid tumors identifies a marker panel for differentiated thyroid cancer diagnosis.
    Author: Wiseman SM, Melck A, Masoudi H, Ghaidi F, Goldstein L, Gown A, Jones SJ, Griffith OL.
    Journal: Ann Surg Oncol; 2008 Oct; 15(10):2811-26. PubMed ID: 18612701.
    Abstract:
    BACKGROUND: Currently, a large proportion of individuals undergo thyroidectomy as a diagnostic procedure for cancer. The objective of this work was to evaluate the molecular phenotype of differentiated thyroid cancer (DTC) and benign thyroid lesions to identify molecular markers that allow for accurate thyroid cancer diagnosis. METHODS: Tissue microarrays consisting of 100 benign and 105 malignant thyroid lesions, plus 24 lymph node samples, were stained for a panel of 57 molecular markers. Significant associations between marker staining and tumor pathology (DTC versus benign) were determined using contingency table and Mann-Whitney U (MU) tests. A Random Forests classifier algorithm was also used to identify useful/important molecular classifiers. RESULTS: Of the 57 diagnostic markers evaluated 35 (61%) were significantly associated with a DTC diagnosis after multiple testing correction. Of these, in DTC compared with benign thyroid tumors, 8 markers were downregulated and 27 upregulated. The most significant markers for DTC diagnosis were: Galectin-3, Cytokeratin 19, Vascular Endothelial Growth Factor, Androgen Receptor, p16, Aurora-A, and HBME-1. Using the entire molecular marker panel, a Random Forests algorithm was able to classify tumors as DTC or benign with an estimated sensitivity of 87.9%, specificity of 94.0%, and an accuracy of 91.0%. CONCLUSION: Evaluation of the DTC and benign thyroid tumor molecular phenotype has allowed for identification of a marker panel, composed of both established and novel markers, useful for thyroid cancer diagnosis. These results suggest that further study of the molecular profile of thyroid tumors is warranted, and a diagnostic molecular marker panel may potentially improve patient selection for thyroid surgery.
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