A six-gene model for differentiating benign from malignant thyroid tumors on the basis of gene expression.

BACKGROUND: Thyroid nodules are common; fine-needle aspirations commonly are read as indeterminate, necessitating surgery to exclude carcinoma. We developed a 6-gene array-based predictor model to diagnose benign versus malignant thyroid lesions. In this study, we verified whether quantitative reverse transcription-polymerase chain reaction (qRT-PCR) using this model reliably can differentiate benign from malignant thyroid nodules.

METHODS: Molecular profiles of benign (follicular adenomas, hyperplastic nodules) and malignant tumors (papillary thyroid carcinomas, follicular variants of papillary thyroid carcinomas) were analyzed using qRT-PCR from our 6-gene model (kit, Hs.296031, Hs.24183, LSM7, SYNGR2, C21orf4). The gold standard was standard pathologic criteria. A diagnosis-predictor model was built by using the training samples and was then used to predict the class of 10 additional samples analyzed as unknowns.

RESULTS: Our predictor model using 47 training samples correctly predicted 9/10 unknowns. One sample diagnosed as benign by standard histologic criteria was diagnosed as malignant by our model (sensitivity 75%; specificity, 100%; positive predictive value, 100%; negative predictive value, 85.7%).

CONCLUSIONS: Molecular diagnosis with our 6-gene model can differentiate between benign and malignant thyroid tumors with high sensitivity and specificity. In combination, these genetic markers may be a reliable test to preoperatively diagnose the malignant potential of thyroid nodules.