Sara Tomei et al., A molecular computational model improves the preoperative diagnosis of thyroid nodules. BMC Cancer

Sara Tomei1, Ivo Marchetti2, Katia Zavaglia1, Francesca Lessi1, Alessandro Apollo1, Paolo Aretini1, Giancarlo Di Coscio2, Generoso Bevilacqua1,2 and Chiara Mazzanti1

1Division of Surgical, Molecular, and Ultrastructural Pathology, Section of Molecular Pathology, University of Pisa and Pisa University Hospital
2Section of Cytopathology, University of Pisa and Pisa University Hospital

Abstract

Background
Thyroid nodules with indeterminate cytological features on fine needle aspiration (FNA) cytology have a 20% risk of thyroid cancer. The aim of the current study was to determine the diagnostic utility of an 8-gene assay to distinguish benign from malignant thyroid neoplasm.

Methods
The mRNA expression level of 9 genes (KIT, SYNGR2, C21orf4, Hs.296031, DDI2, CDH1, LSM7, TC1, NATH) was analysed by quantitative PCR (q-PCR) in 93 FNA cytological samples. To evaluate the diagnostic utility of all the genes analysed, we assessed the area under the curve (AUC) for each gene individually and in combination. BRAF exon 15 status was determined by pyrosequencing. An 8-gene computational model (Neural Network Bayesian Classifier)