Ricerc@Sapienza

Thyroid nodules are being identified with increasing frequency in clinical practice, representing a malignant neoplasm only in 5-15% of cases. Fine-needle aspiration biopsy (FNAB) is the most reliable preoperative test to diagnose thyroid cancer. However, non-diagnostic or indeterminate cytological results occur in up to 30% of thyroid FNA samples. A high proportion of these patients undergoes a diagnostic rather than a curative surgery, but only a minority of indeterminate thyroid nodules are diagnosed as malignant at final histology. In this clinical setting, molecular markers may be useful as diagnostic tools, complementing and integrating the information provided by cytology and improving preoperative risk stratification for indeterminate nodules.
In the last few years, a comprehensive investigation of the genomic landscape of thyroid cancer was performed, thus substantially decreasing the dark matter of thyroid cancer genome. This knowledge as well as advances in high-throughput technologies have contributed to molecular test improvement for cancer diagnosis in thyroid nodules. The current availability of targeted Next-Generation Sequencing offers a convenient and cost-effective technique for mutation detection also in those challenging samples like FNA specimens. Additionally, digital PCR provides a unique means for absolute quantification of thyroid cancer-related biomarkers (like miRNAs) in FNA samples, providing a further sensitive approach for cancer diagnosis.
The overall objective of this proposal is to improve the diagnostic and prognostic accuracy of FNA cytology by a combined molecular approach which includes mutation detection and assessment of miRNA expression levels in pre-surgical thyroid nodule specimens. Diagnostic accuracy of molecular methods will be compared with ultrasonography and cytology in order to identify a diagnostic algorithm for thyroid nodules. Potential utility of the diagnostic algorithm in clinical practice will be evaluated.