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Afirma Genomic Sequencing Classifier & Xpression Atlas Molecular Findings in Consecutive Bethesda III-VI Thyroid Nodules. The Journal of clinical endocrinology and metabolism Hu, M. I., Waguespack, S. G., Dosiou, C., Ladenson, P. W., Livhits, M. J., Wirth, L. J., Sadow, P. M., Krane, J. F., Stack, B. C., Zafereo, M. E., Ali, S. Z., Weitzman, S. P., Hao, Y., Babiarz, J. E., Kennedy, G. C., Kloos, R. T. 2021

Abstract

CONTEXT: Broad genomic analyses among thyroid histologies have been described from relatively small cohorts.OBJECTIVE: Investigate the molecular findings across a large, real-world cohort of thyroid fine needle aspiration (FNA) samples.DESIGN: Retrospective analysis of RNA sequencing data files.SETTING: CLIA laboratory performing Afirma Genomic Sequencing Classifier (GSC) and Xpression Atlas (XA) testing.PARTICIPANTS: 50,644 consecutive Bethesda III-VI nodules.INTERVENTION: none.MAIN OUTCOME MEASURES: Molecular test results.RESULTS: Of 48,952 Bethesda III/IV FNAs studied, 66% were benign by Afirma GSC. The prevalence of BRAF V600E was 2% among all Bethesda III/IV FNAs and 76% among Bethesda VI FNAs. Fusions involving NTRK, RET, BRAF, and ALK were most prevalent in Bethesda V (10%), and 130 different gene partners were identified. Among small consecutive Bethesda III/IV sample cohorts with one of these fusions and available surgical pathology excision data, the positive predictive value of an NTRK or RET fusion for carcinoma or non-invasive follicular thyroid neoplasm with papillary-like nuclear features was >95%, while for BRAF and ALK fusions it was 81% and 67%, respectively. At least one genomic alteration was identified by the expanded Afirma XA panel in 70% of Medullary Thyroid Carcinoma Classifier positive FNAs, 44% of Bethesda III or IV Afirma GSC suspicious FNAs, 64% of Bethesda V FNAs, and 87% of Bethesda VI FNAs.CONCLUSIONS: This large study demonstrates that almost half of Bethesda III/IV Afirma GSC suspicious and most Bethesda V/VI nodules had at least 1 genomic variant or fusion identified, which may optimize personalized treatment decisions.

View details for DOI 10.1210/clinem/dgab304

View details for PubMedID 34009369