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Background <p><i>BRAF</i><sup>V600E</sup> mutation is the most common genetic change in papillary thyroid carcinoma (PTC). Nevertheless, the association between <i>BRAF</i><sup>V600E</sup> mutation status and abundance and the biological behavior of PTC is unclear. Thus, this study investigated whether <i>BRAF</i><sup>V600E</sup> mutation status and abundance are related to PTC biological behavior and whether <i>BRAF</i><sup>V600E</sup> mutation abundance can be used to further stratify risk.</p> Methods <p>Postoperative formalin-fixed paraffin-embedded (FFPE) specimens from 528 PTC patients formed the retrospective cohort, and preoperative fine-needle aspiration (FNA) specimens from 167 PTC patients formed the prospective cohort. Furthermore, 74 FNA specimens were collected from two additional hospitals to form the external cohort. Droplet digital polymerase chain reaction (ddPCR) was used to detect <i>BRAF</i><sup>V600E</sup> mutation status and abundance in the two types of specimens. The relationship between <i>BRAF</i><sup>V600E</sup> mutation status and abundance and PTC biological behavior was analyzed in the cohorts. To predict <i>BRAF</i><sup>V600E</sup>-positive PTC risk stratification, we constructed postoperative clinicopathological models (Model A, retrospective; Model B, prospective), a preoperative clinical model (Model C), and a fusion model combining <i>BRAF</i><sup>V600E</sup> mutation abundance and preoperative clinical information (Model D). The area under the curve (AUC) values were used to assess the performance of these models.</p> Results <p>Univariate and multivariate analysis of the retrospective, prospective and external cohorts indicated that <i>BRAF</i><sup>V600E</sup> mutation abundance, not status, was significantly associated with PTC biological behavior. An increase in <i>BRAF</i><sup>V600E</sup> mutation abundance was significantly associated with an increased risk of <i>BRAF</i><sup>V600E</sup>-positive PTC. The AUCs of model A, model B, model C, and model D in the validation sets were 0.89 (95% CI, 0.83–0.94), 0.89 (95% CI, 0.83–0.99), 0.65 (95% CI, 0.48–0.82), and 0.86 (95% CI, 0.75–0.98), respectively. The AUCs of model B, model C, and model D in the external sets were 0.78(95% CI, 0.67–0.88), 0.61(95% CI, 0.48–0.75) and 0.82 (95% CI, 0.71–0.93), respectively. The AUC of model D was higher than that of model C in the external validation set by 21% (<i>P</i> = 0.02).</p> Conclusions <p><i>BRAF</i><sup>V600E</sup> mutation abundance, not status, reflects PTC biological behavior. Integrating <i>BRAF</i><sup>V600E</sup> mutation abundance and preoperative clinical information can be used to better preoperatively predict <i>BRAF</i><sup>V600E</sup>-positive PTC risk and guide clinical decision making.</p> Trial registration <p>ChiCTR, ChiCTR2300071472. Registered 31 July 2016 - Retrospectively registered, <a href="https://www.chictr.org.cn/showproj.html?proj=190478">https://www.chictr.org.cn/showproj.html?proj=190478</a>.</p>

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Can mutation abundance assess the biological behavior of BRAFV600E-positive papillary thyroid carcinoma?

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月1日

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  • Yeqin Ni,
  • Ping Song,
  • Xiangfeng Lin,
  • Jingjing Shi,
  • Qian Shi,
  • Yuanhui Li,
  • Siyu Zhu,
  • Tianhan Zhou,
  • Yanping Xun,
  • Shirong Zhang,
  • Xingchang Ren,
  • Kaining Lu,
  • Fan Wu,
  • Wei Wang,
  • Pan Zhao,
  • Rongjing Zhou,
  • Wenhua Zhang,
  • Dandan Li,
  • Jiaoping Zhang,
  • Chuanghua Chen,
  • Linlin Mao,
  • Li Zhou,
  • Gang Pan,
  • You Peng,
  • Yunxian Yu,
  • Yuying Chen,
  • Rong Ni,
  • Guhan Luo,
  • Yu Zhang,
  • Jugao Fang,
  • Haitao Zheng,
  • Dingcun Luo

摘要

Background

BRAFV600E mutation is the most common genetic change in papillary thyroid carcinoma (PTC). Nevertheless, the association between BRAFV600E mutation status and abundance and the biological behavior of PTC is unclear. Thus, this study investigated whether BRAFV600E mutation status and abundance are related to PTC biological behavior and whether BRAFV600E mutation abundance can be used to further stratify risk.

Methods

Postoperative formalin-fixed paraffin-embedded (FFPE) specimens from 528 PTC patients formed the retrospective cohort, and preoperative fine-needle aspiration (FNA) specimens from 167 PTC patients formed the prospective cohort. Furthermore, 74 FNA specimens were collected from two additional hospitals to form the external cohort. Droplet digital polymerase chain reaction (ddPCR) was used to detect BRAFV600E mutation status and abundance in the two types of specimens. The relationship between BRAFV600E mutation status and abundance and PTC biological behavior was analyzed in the cohorts. To predict BRAFV600E-positive PTC risk stratification, we constructed postoperative clinicopathological models (Model A, retrospective; Model B, prospective), a preoperative clinical model (Model C), and a fusion model combining BRAFV600E mutation abundance and preoperative clinical information (Model D). The area under the curve (AUC) values were used to assess the performance of these models.

Results

Univariate and multivariate analysis of the retrospective, prospective and external cohorts indicated that BRAFV600E mutation abundance, not status, was significantly associated with PTC biological behavior. An increase in BRAFV600E mutation abundance was significantly associated with an increased risk of BRAFV600E-positive PTC. The AUCs of model A, model B, model C, and model D in the validation sets were 0.89 (95% CI, 0.83–0.94), 0.89 (95% CI, 0.83–0.99), 0.65 (95% CI, 0.48–0.82), and 0.86 (95% CI, 0.75–0.98), respectively. The AUCs of model B, model C, and model D in the external sets were 0.78(95% CI, 0.67–0.88), 0.61(95% CI, 0.48–0.75) and 0.82 (95% CI, 0.71–0.93), respectively. The AUC of model D was higher than that of model C in the external validation set by 21% (P = 0.02).

Conclusions

BRAFV600E mutation abundance, not status, reflects PTC biological behavior. Integrating BRAFV600E mutation abundance and preoperative clinical information can be used to better preoperatively predict BRAFV600E-positive PTC risk and guide clinical decision making.

Trial registration

ChiCTR, ChiCTR2300071472. Registered 31 July 2016 - Retrospectively registered, https://www.chictr.org.cn/showproj.html?proj=190478.