Analytical performance of the ThyroSeq v3 genomic classifier for cancer diagnosis in thyroid nodules

Marina N. Nikiforova*, Stephanie Mercurio, Abigail I. Wald, Michelle Barbi de Moura, Keith Callenberg, Lucas Santana-Santos, William E. Gooding, Linwah Yip, Robert L. Ferris, Yuri E. Nikiforov

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

146 Scopus citations


BACKGROUND: Molecular tests have clinical utility for thyroid nodules with indeterminate fine-needle aspiration (FNA) cytology, although their performance requires further improvement. This study evaluated the analytical performance of the newly created ThyroSeq v3 test. METHODS: ThyroSeq v3 is a DNA- and RNA-based next-generation sequencing assay that analyzes 112 genes for a variety of genetic alterations, including point mutations, insertions/deletions, gene fusions, copy number alterations, and abnormal gene expression, and it uses a genomic classifier (GC) to separate malignant lesions from benign lesions. It was validated in 238 tissue samples and 175 FNA samples with known surgical follow-up. Analytical performance studies were conducted. RESULTS: In the training tissue set of samples, ThyroSeq GC detected more than 100 genetic alterations, including BRAF, RAS, TERT, and 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%, the specificity was 81.8%, and the accuracy was 90.9%. Analytical accuracy studies demonstrated a minimal required nucleic acid input of 2.5 ng, a 12% minimal acceptable tumor content, and reproducible test results under variable stress conditions. CONCLUSIONS: The ThyroSeq v3 GC analyzes 5 different classes of molecular alterations and provides high accuracy for detecting all common types of thyroid cancer and parathyroid lesions. The analytical sensitivity, specificity, and robustness of the test have been successfully validated and indicate its suitability for clinical use. Cancer 2018;124:1682-90.

Original languageEnglish (US)
Pages (from-to)1682-1690
Number of pages9
Issue number8
StatePublished - Apr 15 2018
Externally publishedYes


  • cytology
  • genetics
  • molecular diagnosis
  • thyroid cancer
  • thyroid nodules

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


Dive into the research topics of 'Analytical performance of the ThyroSeq v3 genomic classifier for cancer diagnosis in thyroid nodules'. Together they form a unique fingerprint.

Cite this