A Combination of BRAF and EZH1/SPOP/ZNF148 Three-Gene Mutational Classifier Improves Benign Call Rate in Indeterminate Thyroid Nodules.

Abstract

Reliable preoperative diagnosis of thyroid nodules remained challenging because of the inconclusiveness of fine-needle aspiration (FNA) cytology. In the present study, 583 formalin-fixed paraffin embedded (FFPE) thyroid nodule tissues and 161 FNA specimens were enrolled retrospectively. Then BRAF V600E, EZH1 Q571R, SPOP P94R, and ZNF148 mutations among these samples were identified using Sanger sequencing. Based on this four-gene genomic classifier, we proposed a two-step modality to diagnose thyroid nodules to differentiate benign and malignant thyroid nodules. In the FFPE group, thyroid cancers were effectively diagnosed in 37.7% (220/583) of neoplasms by the primary BRAF V600E testing, and 15.7% (57/363) of thyroid nodules could be further determined as benign by subsequent EZH1 Q571R, SPOP P94R, and ZNF148 (we called them "ESZ") mutation testing. In the FNA group, 161 BRAF wild-type specimens were classified according to The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC). A total of 7 mutated samples fell within Bethesda categories III-IV, and the mutation rate of "ESZ" in Bethesda III-IV categories was 8.4%. The two-step genomic classifier could further improve thyroid nodule diagnosis, which may inform more optimal patient management.