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Volume 16
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10.3390/jpm16010003
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Article

Somatic Mutational Landscape in Follicular Thyroid Cancer: Insights from AACR GENIE Data

by
Beau Hsia
1,*,
Julia Kuzniar
2,
Joey Luzarraga
3,
Asritha Sure
4,
Vinay Veluvolu
5,
Eli Oved
1,
Peter T. Silberstein
6,
Joseph Thirumalareddy
6,
Abubakar Tauseef
6,
Vijay Patel
7 and
Aliasgher Khaku
8
1
School of Medicine-Phoenix, Creighton University, Phoenix, AZ 85012, USA
2
Rutgers Robert Wood Johnson Medical School (RWJMS), New Brunswick, NJ 08901, USA
3
Herbert Wertheim College of Medicine, Miami, FL 33199, USA
4
School of Medicine, Boston University, Boston, MA 02118, USA
5
Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
6
School of Medicine, Creighton University, Omaha, NE 68178, USA
7
Division of Pediatric Otolaryngology, Rady Children’s Hospital, San Diego, CA 92123, USA
8
Department of Otolaryngology-Head and Neck Surgery, Morsani College of Medicine, University of South Florida, Tampa, FL 12901, USA
*
Author to whom correspondence should be addressed.
J. Pers. Med. 2026, 16(1), 3; https://doi.org/10.3390/jpm16010003 (registering DOI)
Submission received: 14 November 2025 / Revised: 15 December 2025 / Accepted: 18 December 2025 / Published: 21 December 2025
(This article belongs to the Special Issue Otolaryngology in Clinical Practice: The Necessity of Personalized Medicine)
Versions Notes

Abstract

Objective(s): To delineate the somatic mutational landscape of follicular thyroid carcinoma (FTC) from a large, real-world cohort to identify molecular subtypes and actionable targets for personalized therapeutic interventions. Methods: Genomic and clinical data for 168 FTC samples were retrieved from the AACR Project GENIE® registry via cBioPortal. This study assessed mutation frequencies, copy number alterations, and subgroup differences (primary vs. metastatic; adult vs. pediatric) using statistical tests. Results: NRAS was the most common mutation (33.9%), followed by TERT (22.6%), DICER1 (15.5%), HRAS (11.9%), and PTEN (10.7%). DICER1 mutations were significantly enriched in pediatric cases (44.4% vs. 4.6% in adults, p < 0.001), while TERT mutations were exclusive to adults (42%). NRAS mutations were more frequent in metastatic tumors (42.4%) than primary tumors (29.2%). Conclusions: FTC tumorigenesis is driven by distinct molecular pathways, with significant heterogeneity between pediatric and adult patients as well as primary and metastatic disease. These findings underscore the necessity of molecular profiling for patient stratification and provide a strong rationale for developing personalized treatment strategies to improve clinical outcomes.
Keywords: follicular thyroid cancer; somatic mutations; AACR GENIE; NRAS; TERT; DICER1 follicular thyroid cancer; somatic mutations; AACR GENIE; NRAS; TERT; DICER1

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MDPI and ACS Style

Hsia, B.; Kuzniar, J.; Luzarraga, J.; Sure, A.; Veluvolu, V.; Oved, E.; Silberstein, P.T.; Thirumalareddy, J.; Tauseef, A.; Patel, V.; et al. Somatic Mutational Landscape in Follicular Thyroid Cancer: Insights from AACR GENIE Data. J. Pers. Med. 2026, 16, 3. https://doi.org/10.3390/jpm16010003

AMA Style

Hsia B, Kuzniar J, Luzarraga J, Sure A, Veluvolu V, Oved E, Silberstein PT, Thirumalareddy J, Tauseef A, Patel V, et al. Somatic Mutational Landscape in Follicular Thyroid Cancer: Insights from AACR GENIE Data. Journal of Personalized Medicine. 2026; 16(1):3. https://doi.org/10.3390/jpm16010003

Chicago/Turabian Style

Hsia, Beau, Julia Kuzniar, Joey Luzarraga, Asritha Sure, Vinay Veluvolu, Eli Oved, Peter T. Silberstein, Joseph Thirumalareddy, Abubakar Tauseef, Vijay Patel, and et al. 2026. "Somatic Mutational Landscape in Follicular Thyroid Cancer: Insights from AACR GENIE Data" Journal of Personalized Medicine 16, no. 1: 3. https://doi.org/10.3390/jpm16010003

APA Style

Hsia, B., Kuzniar, J., Luzarraga, J., Sure, A., Veluvolu, V., Oved, E., Silberstein, P. T., Thirumalareddy, J., Tauseef, A., Patel, V., & Khaku, A. (2026). Somatic Mutational Landscape in Follicular Thyroid Cancer: Insights from AACR GENIE Data. Journal of Personalized Medicine, 16(1), 3. https://doi.org/10.3390/jpm16010003

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