OR27-3 A Novel Risk Stratification System for Thyroid Nodules with Indeterminate Cytology: A Pilot Cohort Study

Abstract

Background Thyroid ultrasound (US) and US-guided fine needle aspiration biopsy (FNAB) have been widely used to stratify the risk of malignancy in thyroid nodules (TN). Cytology material characterized as category III and IV by the Bethesda System for Reporting Thyroid Cytopathology is associated with thyroid cancer (TC) risk ranging between 5-30%. The use of molecular markers may help defining the management strategy in these indeterminate nodules. The goal of this study was to create a risk stratification system based on US features and the results of molecular profiling of cytologically indeterminate TN and to assess its diagnostic accuracy. Methods We performed a cohort study including patients with TN who underwent thyroid US and FNAB revealing indeterminate cytology (Bethesda III, IV). Final pathology diagnosis was available for all patients. DNA and RNA were extracted from pathology material and subjected to Ion Torrent™ Oncomine™ Comprehensive Assay v3 (OCAv3) next-generation sequencing, analyzing single nucleotide variants (SNV), small insertions and deletions (INDEL), copy number variants (CNV) and gene fusions (GF) from 161 cancer driver genes. Each genetic alteration was annotated (X) based on its strength of association with TC per TCGA and COSMIC database. US features of TN were similarly categorized (Xus) by two independent clinicians, blinded to pathology report. The total risk score (TRS) was estimated based on the following formula TRS= (XSNV/INDEL)*n + XGF + XCNV + XUS , where X is the annotated score and n is the number of SNVs/INDELs. ROC curve was performed to assess the diagnostic accuracy of US alone, OCAv3 alone and TRS. Results We analyzed 84 TN in 50 patients (39 females and 11 males), age 47.2 ± 14.8 years. Thirty-four patients (68%) were diagnosed with TC: 21 papillary (PTC), 6 follicular variant of PTC (FVPTC), 1 noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), 2 Hürthle cell (HTC), 1 poorly differentiated carcinoma (PD) and 3 medullary TC (MTC). The molecular signature revealed the BRAF V600E mutation as the most common in PTC, while KRAS and NRAS mutations were associated with FVPTC. A NIFTP showed a PAX8-PPARG fusion. HTC had pathogenic variants of SLX4, ATM and NRAS genes, PD was associated with HRAS mutation, and MTC with RET pathogenic variants. Benign lesions were characterized by either no mutations or the presence of GNAS, HRAS, NRAS and ESR1 variants. The diagnostic accuracy of US alone was 68% (sensitivity 41.2%, specificity 93.8%), while for OCAv3 alone it was 79% (sensitivity 65%, specificity 93.8%). TRS was associated with the highest diagnostic accuracy of 83.5% (sensitivity 79.4%, specificity 88%). Conclusions Combining risk stratification based on thyroid US and molecular signature improves diagnostic accuracy of TC in patients with indeterminate TN. Our pilot study requires validation in independent larger cohorts.