Association of Gene Expression Alterations with Aggressive Features in Papillary Thyroid Carcinomas Harboring Low Allele Frequency BRAF V600E Mutations

Abstract

Importance

BRAF V600E mutations are frequently associated with aggressive papillary thyroid carcinomas (PTCs), yet tumors with low allele frequency (AF) are often considered to be indolent. However, exceptions exist, suggesting additional factors may influence tumor behavior. Gene expression alterations (GEA) may help identify tumors with more aggressive molecular phenotypes.

Objective

To evaluate whether aggressive clinicopathologic features are associated with GEA positivity in low AF BRAF V600E-mutated PTCs.

Design

Retrospective cohort study.

Setting

Two McGill University Academic Hospitals, 2019 to 2024.

Participants

Patients with PTC harboring BRAF V600E (AF ≤ 25%) who underwent preoperative testing.

Intervention or Exposure

Low AF BRAF V600E mutation (≤25%) characterized using ThyroSeq v3 genomic classifier.

Main Outcome Measures

The primary outcome was GEA status. Tumor aggressiveness (defined by extrathyroidal extension, lymph node metastasis, lymphovascular invasion, high-risk histology, or aggressive variants), Bethesda classification, and AF were evaluated as predictors of GEA using logistic regression. Stratified analysis was performed based on AF (≤10% vs. >10%).

Results

Among 49 patients identified (mean age 49 ± 14 years; 86% female; mean AF 11% ± 8%), 73% (36/49) had aggressive features and 61% (30/49) had GEA-positive tumors. Among GEA-positive tumors, 80% (24/30) were classified as aggressive and had a significantly-higher median AF (16.5%) than GEA-negative tumors (P = .0003). Stratified analysis showed that Bethesda VI nodules significantly predicted GEA positivity in tumors with AF > 10% (P = .03).

Conclusion

In low AF BRAF V600E-mutated PTCs, GEA positivity is associated with high-risk cytology, higher AF, and aggressive tumor features.

Relevance

GEA may be a useful molecular marker of aggressive tumor biology in low AF PTCs and holds potential as a complementary tool for preoperative risk stratification.

Graphical Abstract

Keywords

papillary thyroid carcinoma allele frequency gene expression alterations head and neck oncology Thyroseq v3 molecular testing surgical management

Key Messages

- Low allele frequency BRAF V600E mutations do not always indicate indolent papillary thyroid carcinoma; gene expression alterations can identify a subset of these tumors with aggressive behavior.

- Among low allele frequency BRAF V600E-mutated papillary thyroid carcinomas, a Bethesda VI cytology result and higher allele frequency (>10%) are independently associated with positive gene expression alterations, which correlates with aggressive histopathologic features.

- Tumors with positive gene expression alterations and low allele frequency BRAF V600E mutations may warrant more aggressive management strategies.

Introduction

Papillary thyroid carcinomas (PTCs), which constitute 95% of thyroid carcinomas¹ are commonly associated with the BRAF V600E mutation, found in up to 60% of cases.² BRAF is a key component of the mitogen‑activated protein kinase (MAPK) signaling pathway, which is essential for the activation of transcription factors involved in cell cycle regulation and survival. Mutations in BRAF result in constitutive activation of the MAPK pathway, leading to uncontrolled cell proliferation and survival.³ Studies have shown that this mutation is often linked with gross extrathyroidal extension (ETE), lymph node metastases (LNM), and high-risk histology.⁴ Additionally, research has demonstrated that BRAF V600E is associated with increased cancer-related mortality among patients with PTCs,⁵ and a higher allele frequency (AF) of this mutation is correlated with poorer disease outcomes and more aggressive behaviors.^6,7

Although low AF BRAF V600E mutations are generally perceived as less aggressive,⁶ some low AF tumors still exhibit high-risk behavior. This observation suggests that factors beyond mutational burden, such as gene expression alterations (GEA), may contribute to tumor phenotype.⁸ The GEA reflects the activity of various genes within the tumor, which can affect tumor behavior by modulating pathways involved in proliferation, invasion, and resistance to apoptosis.⁹ For instance, certain GEAs may upregulate oncogenes or downregulate tumor suppressor genes, leading to a more aggressive tumor phenotype.¹⁰ Alternatively, a GEA that activates additional signaling pathways or enhances the tumor microenvironment’s support for cancer growth could also contribute to tumor proliferation, invasion, and treatment response.¹¹

This study builds on our previously-published work examining the relationship between BRAF V600E AF and GEA across a broader cohort of PTCs.⁶ In contrast, the present analysis focuses exclusively on tumors with low AF (≤25%) and represents the first study, to our knowledge, to evaluate predictors of GEA within this specific subgroup. By narrowing the focus, we aim to clarify the clinical relevance of GEA in a population typically considered low risk but potentially harboring aggressive biological behavior.

Given the gaps in knowledge surrounding low AF BRAF V600E-mutated tumors, our objective was to evaluate whether aggressive tumor features are associated with GEA positivity within this subgroup. Specifically, we assessed whether AF, Bethesda score, and histopathologic markers of aggressiveness predicted the presence of GEA. By identifying these predictors, we aimed to determine whether GEA can serve as a molecular correlate of high-risk disease in low AF PTCs and inform more nuanced preoperative risk stratification and management.

Materials and Methods

Study Design and Population

In this retrospective cohort analysis, we identified patients who underwent preoperative molecular testing for thyroid nodules using ThyroSeq v3 genomic classifier, as described previously^6,8 and validated in a prospective trial by Kim et al. (2023).¹² The assay is based on targeted next-generation sequencing of DNA and RNA and evaluates 112 genes for point mutations, insertions, deletions, gene fusions, and GEA. The test also provides information on the AF. Medical records were collected from two McGill University Academic Hospitals between January 2019 and January 2024. Eligible patients were over 18 years of age, had a thyroid tumor with a BRAF V600E mutation and an AF ≤ 25%, and had available GEA data from preoperative molecular testing reports.

We defined “low AF” as ≤25%, a priori threshold chosen to capture the clinically-ambiguous range in which prior work has shown lower AF to associate with less-aggressive histopathology⁶ while avoiding the higher AF range (≈30–35% and above) that other studies have linked more consistently to adverse pathology and recurrence.^7,13 This threshold was specified before analysis and was not data-derived in the current cohort.

The thyroid fine needle aspiration (FNA) samples were classified according to the Bethesda classification for reporting thyroid cytology.^14,15 Nodules were categorized into aggressive and nonaggressive groups based on the presence of gross ETE, lymphovascular invasion (LVI), LNM, high-risk histological features, or aggressive subtypes (such as tall cell, columnar, hobnail/micropapillary, and diffuse sclerosing). Samples exhibiting the classical PTCs subtype with tall cell features ≥10% were grouped under the tall cell variant due to their increased risk for aggressive clinical outcomes compared with classical PTCs.¹⁶ Final pathological diagnoses adhered to the 2017 World Health Organization (WHO) classification of endocrine tumors.¹⁷ Evaluation of cytology and final pathology samples was conducted by board-certified head and neck pathologists. Participants’ personal information was anonymized and securely stored throughout data collection and analysis. Ethics approval was obtained by the Research Ethics Committee at the McGill University Hospital Center (MP-37-2021-7560).

Statistical Analyses

Statistical analyses were conducted using the R software (version 4.3.2). The patients identified were categorized based on tumors’ GEA status into GEA-positive and GEA-negative groups based on their molecular testing results. Categorical variables were compared between the two groups using the chi-squared test or Fisher’s exact test. Continuous variables such as age and AF were described as mean ± SD and were compared between the two groups using independent samples t-test or the Mann-Whitney U test. Logistic regression analyses were used to determine the independent predictive factors for GEA. Any point with a Cook’s distance over 0.08 was considered to be an outlier and was excluded from our regression model. Variables associated with a P < .3 in the univariate analysis were then introduced in our multivariate analysis model. Finally, we stratified the patients into two categories based on their AF ≤ 10% and >10% to investigate the effect of predictive factors in our multivariate regression model in patients with different AF. A P-value of < .05 was considered as the threshold for establishing statistical significance.

Results

Baseline Demographics

A total of 49 patients were analyzed; 30/49 (61%) were GEA-positive and 36/49 (73%) had aggressive features. Mean age was 49 ± 14 years and 42/49 (86%) were female. The overall mean AF was 11% ± 8%. Full demographics are shown in Table 1.

Table 1.

Baseline Demographics of all Study Participants.

	Total (n = 49)	GEA positive (n = 30)	GEA negative (n = 19)
Age in years, mean ± SD	49 ± 14	48 ± 15	52 ± 12
Female, n (%)	42 (86%)	26 (87%)	16 (84%)
Average AF in %, mean ± SD	11 ± 8	14 ± 7	7 ± 6
Cancer aggressivity, n (%)
Aggressive	36 (73%)	24 (80%)	12 (63%)
Not Aggressive	13 (27%)	6 (20%)	7 (37%)
Histologic subtype, n (%)
Classical	18 (37%)	11 (37%)	7 (37%)
Hobnail	1 (2%)	1 (3%)	0 (0%)
Solid	1 (2%)	0 (0%)	1 (5%)
Follicular	5 (10%)	1 (3%)	4 (21%)
Tall Cell	24 (49%)	17 (57%)	7 (37%)
Lymphovascular invasion, n (%)	4 (8%)	3 (10%)	1 (5%)
Lymph node involvement, n (%)
0	29 (59%)	16 (53%)	13 (68%)
<3	13 (27%)	9 (30%)	4 (21%)
>3	7 (14%)	5 (17%)	2 (11%)
SLN presence, n (%)	6 (12%)	5 (17%)	1 (5%)
Tumor size in cm, n (%)
<1	9 (18%)	6 (20%)	3 (16%)
1–2	34 (69%)	21 (70%)	13 (68%)
>2	6 (12%)	3 (10%)	3 (16%)
Tumor site,^a n (%)
Isthmus	1 (2%)	1 (3%)	0 (0%)
Left	20 (41%)	13 (43%)	7 (37%)
Right	28 (57%)	16 (53%)	12 (63%)
Bethesda score, n (%)
III	7 (14%)	2 (7%)	5 (26%)
IV	2 (4%)	0 (0%)	2 (11%)
V	7 (14%)	4 (13%)	3 (16%)
VI	33 (67%)	24 (80%)	9 (47%)
Gross ETE presence, n (%)	1 (2%)	0 (0%)	1 (5%)

Some cases involve multiple locations. The location with the highest Bethesda score was reported.

Abbreviations: AF, allele frequency; ETE, extrathyroidal extension; GEA, gene expression alterations; SD, standard deviation; SLN, sentinel lymph node.

GEA and AF

GEA-positive tumors had higher AF (median 16.5%, IQR 8.5–20) than GEA-negative tumors (median 5%, IQR 2–10; P = .0003; Figure 1).

Figure 1.

Comparison of allele frequency between negative and positive gene expression alterations.

Predictors of GEA

In univariate analysis, we found that both AF and Bethesda score VI were significant predictors of GEA (OR: 1.19, 95% CI [1.07, 1.32], P = .001; OR: 6.67, [1.09, 40.73], P = .04, respectively) (Table 2). Similarly in our multivariate analysis accounting for cancer aggressivity, Bethesda score, and AF, higher AF (OR per 1% increase 1.19, [1.05, 1.34]; P = .006) and Bethesda VI (OR 9.66, [1.10, 84.56]; P = .041) independently predicted GEA. (Table 2).

Table 2.

Predictors of Gene Expression Alterations: Results of Univariate and Multivariate Analyses.

Variant	Analysis of factors related to GEA
	Univariate analysis					Multivariate analysis
	ß	SE	OR	95% CI	P	ß	SE	OR	95% CI	P
Cancer aggressivity
Nonaggressive	Reference
Aggressive	0.85	0.66	2.33	[0.64, 8.49]	0.20	0.67	0.80	1.96	[0.41, 9.43]	0.40
Bethesda score
III	Reference					Reference
IV	−15.65	1696.74	NA	NA	0.99	−13.98	1696.74	NA	NA	0.99
V	1.20	1.13	3.33	[0.36, 30.70]	0.29	1.26	1.31	3.52	[0.27, 45.66]	0.34
VI	1.90	0.92	6.67	[1.09, 40.73]	0.04	2.27	1.10	9.66	[1.10, 84.56]	0.04
Lymph node involvement
0	Reference
≤3	0.60	0.71	2.03	[0.46, 7.32]	0.39
≥3	0.71	0.92	1.40	[0.34, 12.24]	0.44
Lymphovascular invasion	0.64	1.194	1.90	[0.18, 19.73]	1
Tumor size	0.33	0.54	1.40	[0.48, 4.03]	0.54
Tumor side
Left	Reference
Right	0.41	0.60	1.5	[0.46, 4.86]	0.50
Histologic subtype
Tall cell	Reference
Classical	0.00	0.60	1.00	[0.30, 3.28]	1
Hobnail	0.24	0.61	1.27	[0.04, 39.70]	1
Solid	−1.15	1.76	0.32	[0.01, 9.93]	0.40
Follicular	−1.84	1.76	0.16	[0.02, 1.55]	0.07
AF	0.17	1.16	1.19	[1.07, 1.32]	0.001	0.17	0.06	1.19	[1.05, 1.34]	0.006

Abbreviations: AF, allele frequency; CI, confidence interval; GEA, gene expression alterations; NA, not applicable; OR, odds ratio; SE, standard error.

Stratification by AF

Stratified analysis based on the AF category showed that in tumors with AF > 10%, Bethesda VI predicted GEA (OR 20.55, 95% CI [1.26, 336.33]; P = .03), whereas no predictor reached significance when AF ≤ 10% (Table 3).

Table 3.

Multivariate Predictors of Gene Expression Alterations Stratified by Allele Frequency.

Variable	AF category	ß	SE	OR	95% CI	P
Bethesda score
III	Reference
IV	≤10%	−17.12	2797.44	NA	NA	.99
	>10%	NA	NA	NA	NA	NA
V	≤10%	−0.48	1.71	0.62	[0.02, 17.55]	0.78
	>10%	19.51	3765.85	NA	NA	1
VI	≤10%	1.01	1.35	2.75	[0.20, 38.75]	0.45
	>10%	3.02	1.43	20.55	[1.26, 336.33]	0.03
Cancer aggressivity
Nonaggressive	Reference
Aggressive	≤10%	0.81	0.94	2.25	[0.36, 14.19]	0.39
	>10%	0.32	1.44	1.37	[0.08, 23.18]	0.83

Abbreviations: AF, allele frequency; CI, confidence interval; NA, not applicable; OR, odds ratio; SE, standard error.

Overall

In summary, within the group of low AF (<25%) BRAF V600E-mutated PTCs, tumors with higher AF (>10%) were significantly more likely to be GEA positive. Because GEA positivity was associated with aggressive pathological features, our findings indicate that low AF alone does not necessarily imply indolence. Instead, the presence of GEA can alter tumor behavior and aggressiveness and should be carefully considered in clinical evaluation.

Discussion

The findings of this study underscore the complexity of the interplay between BRAF V600E mutation AF and PTC aggressivity. While BRAF V600E with an AF ≤25% are often considered indicative of indolent tumor behavior, our analysis reveals that their impact may be modulated by the tumor’s GEA. GEA emerged as a potential molecular correlate of aggressive pathological features in low AF BRAF V600E-mutated PTCs. Tumors that were GEA-positive more frequently exhibited features typically associated with aggressive behavior. This suggests that transcriptional alterations reflected in the GEA might amplify or attenuate the oncogenic potential of even low AF mutations, emphasizing the multifaceted role of GEA in thyroid tumor biology.

In PTC, GEA can provide insights into the molecular characteristics of the tumor, such as the activation of specific signaling pathways and the expression of genes involved in processes like cell proliferation, apoptosis, and metastasis. When BRAF V600E is present, GEA can help identify additional molecular changes that contribute to tumor aggressiveness or indolence. For example, in tumors with low AF in the BRAF V600E mutation, GEA might reveal patterns of gene expression that align more with indolent behavior, whereas a high-risk gene signature could be linked to more aggressive disease.

GEA can also potentially identify biomarkers associated with drug resistance or sensitivity, potentially offering insights into therapeutic strategies. In BRAF V600E-mutated PTC, the GEA might reveal upregulation of pathways that could be targeted by specific therapies, such as MEK or BRAF inhibitors, or it may indicate coexisting molecular alterations that complicate treatment.

A key finding from our study is the association between a higher Bethesda score (VI) and a positive GEA in patients with AF > 10%. This combination was more frequently observed in tumors with aggressive features, suggesting a possible link that merits further study. Previous studies have demonstrated that higher Bethesda categories correlate with a higher risk of malignancy and aggressive disease features. For example, a study by Kleiman et al.¹⁸ reported that patients with Bethesda V and VI lesions had a higher rate of gross ETE and LNM than those with lower Bethesda scores. Similarly, a retrospective analysis by Gweon et al.¹⁹ highlighted that higher Bethesda scores were predictive of advanced tumor stages and poor prognosis in patients with PTC. This also aligns with the findings in Mascarella et al.,²⁰ who reported that higher Bethesda categories (VI) were strongly associated with malignancy in PTC patients with the BRAF V600E mutation, underlining the importance of integrating molecular data and cytology for more precise tumor assessment.

Our results carry important clinical implications and challenge the current paradigm that low BRAF V600E AF uniformly signals a less-aggressive clinical course. The finding that tumors with low AF but high-risk GEA mimic the behavior of high AF BRAF V600E-mutated PTCs necessitates a reassessment of AF as an isolated marker. This aligns with the recent literature suggesting that AF should be interpreted in the context of other molecular and histological markers, rather than as a standalone prognostic factor.⁶ While current American Thyroid Association guidelines prioritize detecting BRAF V600E mutation for risk stratification,²¹ there is no mention of other molecular predictors like GEA. Integrating GEA into the evaluation of PTCs could enhance risk stratification and guide therapeutic decision-making. For instance, patients with low AF BRAF V600E-mutated PTCs and high-risk GEA may benefit from more aggressive surgical and adjuvant treatment approaches traditionally reserved for high AF cases. Conversely, identifying low-risk GEA in such tumors might spare patients unnecessary interventions. The role of GEA testing, however, must be balanced against its cost and accessibility, particularly in resource-limited settings. For example, patients with low AF BRAF V600E mutations and high-risk GEA may warrant a total thyroidectomy rather than a hemi-thyroidectomy, given the higher risk of aggressive behavior and the potential need for adjuvant radioactive iodine and reliable thyroglobulin monitoring. This decision carries significant weight, as total thyroidectomy entails lifelong implications, including mandatory thyroid hormone replacement therapy and a heightened risk of postoperative complications, such as hypoparathyroidism and recurrent laryngeal nerve injury. A more precise understanding of the relationship between AF, GEA, and clinical outcomes could refine surgical decision-making, enabling more personalized treatment strategies that balance oncologic control with quality-of-life considerations. Given that GEA and AF are both generated from ThyroSeq v3, incorporating GEA leverages existing workflows without additional procedures or separate assays, which may improve economic efficiency in centers already using these platforms.

To aid clinical translation, Figure 2 presents a simple, hypothesis-generating algorithm that integrates AF and GEA from the same ThyroSeq v3 report to guide preoperative risk stratification in BRAF V600E-positive PTC.

Figure 2.

Conceptual algorithm for BRAF V600E-positive PTC using AF and GEA from the same ThyroSeq v3 assay.

Several limitations warrant discussion. This study’s retrospective design may introduce selection bias, and wide confidence intervals observed in some analyses reflect the exploratory nature of this first investigation; nevertheless, the observed effect sizes are clinically meaningful.

Although modest, the 49-patient cohort is well-suited to this first, targeted evaluation of GEA within low-AF BRAF V600E tumors and provides clinically-meaningful effect-size estimates to guide subsequent validation studies. Furthermore, while the correlation between GEA and aggressivity is compelling, causality cannot be inferred. Prospective, multicentered studies with larger cohorts and functional assays are essential to validate these findings. Additionally, exploring the interplay of other molecular alterations, such as TERT promoter mutations or copy number variations, with BRAF V600E and GEA could provide a more comprehensive understanding of PTCs behaviors. Insurance coverage limitations also affect the availability of molecular testing, further impacting the representativeness of our sample. Nonetheless, our study adds to the growing evidence that PTC tumor aggressivity is multifactorial, influenced by both genetic mutations and GEA patterns. While the BRAF V600E mutation remains a key marker in PTC, our findings suggest that in cases with low AF, GEA may play a critical role in determining clinical outcomes. In summary, the combination of BRAF V600E mutation status and GEA allows for a more comprehensive assessment of PTC, improving prognostication and aiding clinical decision-making. GEA can refine risk stratification, guiding the treatment approach for individual patients by identifying tumors more likely to exhibit aggressive behavior or those with a more favorable, indolent course. Future research should focus on validating these findings in larger patient populations and exploring the potential of GEA as a prognostic tool in thyroid cancer management.

Conclusion

Our study investigates the relationship between BRAF V600E mutation AF and GEA in patients with PTC and a low AF (≤25%). Our findings reveal that tumors with a positive GEA tend to have a significantly-higher median AF than those with a negative GEA. While higher AF levels are generally associated with more aggressive tumor behavior, our results suggest that in cases with low AF, a positive GEA, especially when combined with a high Bethesda score (VI), can still indicate an elevated risk of aggressive disease. These findings highlight the potential value of incorporating GEA analysis into clinical practice, as it may provide a more nuanced risk assessment and guide treatment strategies for patients who would otherwise be considered low risk based solely on AF. This approach could ultimately improve patient management and outcomes by identifying those at higher risk who may benefit from more aggressive treatment.

Footnotes

Acknowledgements

None.

Authors’ Note

This study was presented at the 2024 Congres de l’association ORL du Quebec, the 2025 Canadian Society of Otolaryngology—Head & Neck Surgery Conference and the 2025 World Congress on Thyroid Cancer.

Author Contributions

A.K.: conceptualization, methodology, formal analysis, visualization, project administration, writing—original draft, and writing—review and editing; C.L.: data curation, writing—review and editing; S.B.: writing—review and editing; V.I.F., M.P.: resources, writing—review and editing; R.J.P.: conceptualization, resources, supervision, and writing—review and editing. All authors read and approved the final manuscript.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Alexandra Katz

Saruchi Bandargal

References

Kure

Ishino

Kudo

, et al. Incidence of BRAF V600E mutation in patients with papillary thyroid carcinoma: a single-institution experience. J Int Med Res 2019;47:5560-5572.

Al-Masri

Al-Shobaki

Al-Najjar

, et al. BRAF V600E mutation in papillary thyroid carcinoma: it’s relation to clinical features and oncologic outcomes in a single cancer centre experience. Endocr Connect. 2021;10:1531-1537.

Shan

Rehman

Ivanov

, et al. Molecular targeting of the BRAF proto-oncogene/mitogen-activated protein kinase (MAPK) pathway across cancers. Int J Mol Sci 2024;25(1):624.

Lee

Schneider

Zeiger

MA.

BRAF V600E mutation and its association with clinicopathological features of papillary thyroid cancer: a meta-analysis. J Clin Endocrinol Metab 2012;97:4559-4570.

Xing

Alzahrani

Carson

, et al. Association between BRAF V600E mutation and mortality in patients with papillary thyroid cancer. JAMA 2013;309:1493-1501.

Abdulhaleem

Bandargal

Pusztaszeri

, et al. The impact of BRAF V600E mutation allele frequency on the histopathological characteristics of thyroid cancer. Cancers (Basel) 2023;16(1):13.

Schumm

Nikiforov

Nikiforova

, et al. Association of BRAF V600E Allele frequency with clinicopathologic outcomes in papillary thyroid cancer. J Clin Endocrinol Metab 2025;110:2164-2171.

Salameh

Rajab

Forest

, et al. Surgical outcomes of thyroid nodules positive for gene expression alterations using ThyroSeq V3 genomic classifier. Cancers (Basel) 2022;15(1):49.

Fastner

Shen

Hartman

, et al. Prognostic gene expression profile testing to inform use of adjuvant therapy: a survey of melanoma experts. Cancer Med. 2023;12(24):22103-22108. doi: 10.1002/cam4.6819.

10.

Dahiya

Richardson

, et al. Gene expression profiling of the tumor microenvironment during breast cancer progression. Breast Cancer Res. 2009;11(1):R7. doi: 10.1186/bcr2222

11.

Villaseñor-Altamirano

Balderas-Martínez

Medina-Rivera

Review of gene expression using microarray and RNA-seq. Rigor and Reproducibility in Genetics and Genomics 2024;159-87. doi: 10.1016/B978-0-12-817218-6.00008-5

12.

Kim

Raghunathan

Hughes

, et al. Bethesda III and IV Thyroid nodules managed nonoperatively after molecular testing with Afirma GSC or Thyroseq v3. J Clin Endocrinol Metab. 2023;108(9):e698-e703. doi: 10.1210/clinem/dgad181

13.

Guerra

Fugazzola

Marotta

, et al. A high percentage of BRAFV600E alleles in papillary thyroid carcinoma predicts a poorer outcome. J Clin Endocrinol Metab. 2012;97(7):2333-2340. doi: 10.1210/jc.2011-3106

14.

Coca-Pelaz

Shah

Hernandez-Prera

, et al. Papillary Thyroid cancer-aggressive variants and impact on management: a narrative review. Adv Ther 2020;37:3112-3128.

15.

Lloyd

Osamura

Klöppel

GJR

. WHO Classification of Tumours of Endocrine Organs. 4th ed. World Health Organization; 2017.

16.

Vuong

Long

Anh

, et al. Papillary thyroid carcinoma with tall cell features is as aggressive as tall cell variant: a meta-analysis. Endocr Connect 2018;7:R286-R293.

17.

Lubitz

Economopoulos

Pawlak

, et al. Hobnail variant of papillary thyroid carcinoma: an institutional case series and molecular profile. Thyroid. 2014;24:958-965.

18.

Kleiman

Beninato

Soni

, et al. Does Bethesda category predict aggressive features in malignant thyroid nodules? Ann Surg Oncol. 2013;20(11):3484-3490. doi: 10.1245/s10434-013-3076-5

19.

Gweon

Koo

Son

, et al. Prognostic role of the Bethesda System for conventional papillary thyroid carcinoma. Head Neck. 2016;38(10):1509-1514. doi: 10.1002/hed.24466

20.

Mascarella

Peeva

Forest

, et al. Association of Bethesda category and molecular mutation in patients undergoing thyroidectomy. Clin Otolaryngol. 2022;47(1):75-80. doi: 10.1111/coa.13859

21.

Haugen

Alexander

Bible

, et al. 2015 American Thyroid Association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: The American Thyroid Association guidelines task force on thyroid nodules and differentiated thyroid cancer. Thyroid. 2016;26(1):1-133. doi: 10.1089/thy.2015.0020