Single-cohort next-generation sequencing analysis of 713 anaplastic thyroid carcinomas: unreported gene alterations and actionable targets.

Authors

Xiaoming Zhang, Naiwei Chen, Sarah Claxton, Mikhail Kovalenko, Dean C Pavlick, Matthew C Hiemenz, Laura M Dooley, Richard D Hammer

Published in

American journal of clinical pathology. Volume 166. Issue 2. Aug 04, 2026.

Abstract

Anaplastic thyroid carcinoma (ATC) is one of the most aggressive and lethal thyroid malignancies, with limited effective treatment options. We aimed to identify previously unreported gene alterations and evaluate the potential for clinically actionable targeted therapies in ATC using the largest single next-generation sequencing (NGS) cohort to date.
This retrospective genomic analysis included deidentified NGS data from 713 patients with ATC obtained from the FoundationCORE database. Pathogenic gene alterations were analyzed for frequency. A comprehensive review of the literature and genomic databases was performed to identify alterations not previously reported in ATC and to assess associated targeted therapies.
Targeted sequencing of 713 ATC tumor specimens identified 250 genes with pathogenic or likely pathogenic alterations, including 108 not previously reported in ATC. Among these novel genes, 24 were altered in 5 or more cases, with MTAP (methylthioadenosine phosphorylase) showing the highest frequency (15.26%). MTAP was also co-deleted with CDKN2A/B at significantly higher rates than previously reported. Notably, 99.58% of cases harbored at least 1 gene alteration associated with a potentially actionable therapy. Among the 250 altered genes, 150 (60.0%) had at least 1 available corresponding targeted therapy, and 75.0% of drug categories demonstrated multiple-gene targeting capabilities.
This largest single-cohort NGS data analysis identified 108 previously unreported genomic alterations in ATC, significantly expanding the understanding of the genomic landscape of this aggressive cancer. Moreover, these findings highlight a broad range of potentially actionable alterations and underscore the importance of identifying driver mutations and combination therapeutic strategies.

PMID:
42569949
Bibliographic data and abstract were imported from PubMed on 09 Aug 2026.

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