Abstract
PurposeIn presence of indeterminate lesions by fine needle aspiration (FNA), thyroid cancer cannot always be easily diagnosed by conventional cytology. As a consequence, unnecessary removal of thyroid gland is performed in patients without cancer based on the lack of optimized diagnostic criteria. Aim of this study is identifying a molecular profile based on long noncoding RNAs (lncRNAs) expression capable to discriminate between benign and malignant nodules.MethodsPatients were subjected to surgery (n = 19) for cytologic suspicious thyroid nodules or to FNA biopsy (n = 135) for thyroid nodules suspicious at ultrasound. Three thyroid-specific genes (TG, TPO, and NIS), six cancer-associated lncRNAs (MALAT1, NEAT1, HOTAIR, H19, PVT1, MEG3), and two housekeeping genes (GAPDH and P0) were analyzed using Droplet Digital PCR (ddPCR).ResultsBased on higher co-expression in malignant (n = 11) but not in benign (n = 8) nodules after surgery, MALAT1, PVT1 and HOTAIR were selected as putative cancer biomarkers to analyze 135 FNA samples. Cytological and histopathological data from a subset of FNA patients (n = 34) were used to define a predictive algorithm based on a Naïve Bayes classifier using co-expression of MALAT1, PVT1, HOTAIR, and cytological class. This classifier exhibited a significant separation capability between malignant and benign nodules (P < 0.0001) as well as both rule in and rule out test potential with an accuracy of 94.12% and a negative predictive value (NPV) of 100% and a positive predictive value (PPV) of 91.67%.ConclusionsddPCR analysis of selected lncRNAs in FNA biopsies appears a suitable molecular tool with the potential of improving diagnostic accuracy.
Highlights
Differentiated thyroid carcinoma, including papillary and follicular subtype, is the most common thyroid malignancy, representing more than 90% of all thyroid cancers
MetastasisAssociated Lung Adenocarcinoma Transcript 1 (MALAT1), Homeobox transcript antisense RNA (HOTAIR), and plasmacytoma variant translocation 1 (PVT1) are co-expressed at higher level in thyroid cancer
Fresh post-surgery explants were used to set up detection by Droplet Digital PCR (ddPCR) of a panel of transcripts: three thyroid-specific genes (thyroglobulin (TG), thyroperoxidase (TPO), and sodium/ iodide symporter (NIS)), six cancer-associated long noncoding RNAs (lncRNAs) (MALAT1, nuclear enrich abundant transcript 1 (NEAT1), HOTAIR, H19, PVT1, and maternally expressed gene 3 (MEG3)), and two housekeeping genes (GAPDH and P0) (Supplementary Fig. 4)
Summary
Differentiated thyroid carcinoma, including papillary and follicular subtype, is the most common thyroid malignancy, representing more than 90% of all thyroid cancers. FNAC is the main diagnostic test for thyroid lesions and is an effective screening procedure to select patients for surgical. The rate of surgery for benign lesions at final histology is still elevated [2]. According to the Italian cytology classification, patients with intermediate and high-risk thyroid nodules (TIR3B/ Beth Class IV, TIR4/Beth Class V, and TIR5/Beth Class VI according Italian and Bethesda cytological classification) are candidate to thyroid surgery [3]. Only 25–30% of TIR3B, 50–80% of TIR4, and 95–99% of TIR5 are malignant at final histology. Nodules with TIR3A/Beth Class III cytology diagnosis, which are usually not eligible to surgery, show 10–15% risk of malignancy [3]. A significant number of nodules are not properly treated and new diagnostic tools are needed to better classify them
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
