Analytical performance of ThyroSeq v3 Genomic Classifier for cancer diagnosis in thyroid nodules

Abstract

Background

Molecular tests have clinical utility for thyroid nodules with indeterminate fine-needle aspiration (FNA) cytology, although their performance requires further improvement. In this study, we evaluated the analytical performance of the newly created ThyroSeq v3 test.

Methods

ThyroSeq version 3 is a DNA and RNA-based next-generation sequencing assay that analyzes 112 genes for a variety of genetic alterations including point mutations, indels, gene fusions, copy number alterations, and abnormal gene expression and uses a Genomic Classifier (GC) to separate malignant from benign lesions. It was validated in 238 tissue and 175 FNA samples with known surgical follow-up. Analytical performance studies were conducted.

Results

Using the training tissue set, ThyroSeq GC detected >100 genetic alterations, including BRAF, RAS, TERT, DICER1 mutations, NTRK1/3, BRAF and RET fusions, 22q loss, and gene expression alterations. GC cutoffs were established to distinguish cancer from benign nodules with 93.9% sensitivity, 89.4% specificity, and 92.1% accuracy. This correctly classified most papillary, follicular, and Hurthle cell lesions, medullary thyroid carcinomas and parathyroid lesions. In the FNA validation set, the GC sensitivity was 98.0%, specificity 81.8%, and accuracy 90.9%. Analytical accuracy studies demonstrated minimal required nucleic acid input of 2.5 ng, a 12% minimal acceptable tumor content, and reproducible test results under variable stress conditions.

Conclusions

ThyroSeq v3 GC analyzes five different classes of molecular alterations and provides high accuracy for detecting all common types of thyroid cancer and parathyroid lesions. Analytical sensitivity, specificity, and robustness of the test were successfully validated, indicating its suitability for clinical use.