European journal of endocrinology · 2025
A new broom sweeps clean: CLDN16 surpasses the BRAF-V600E mutation as an unrivaled biomarker in papillary thyroid cancer.
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Cai Yefeng, Guo Yawen, Ma Wenli, Cheng Pu, Jiang Liehao, Shen Shuyan, Song Fahuan, Zhu Lei, Hu Yiqun, Chen Yao, Duan Yanting, Cai Xiujun, Li Quan, Zheng Guowan, Ge Minghua
Аннотация
OBJECTIVE: This study assessed CLDN16 as a potential replacement or improvement biomarker for papillary thyroid cancer (PTC), addressing the limitations associated with the prevalently used BRAF-V600E mutation.
DESIGN: Database analyses, tissue validation, RNA sequencing, and functional assays were conducted to evaluate CLDN16 as a PTC biomarker and its clinical application.
METHODS: CLDN16 expression was examined in PTC and normal thyroid/para-tumor tissues and compared across various cancer types. We evaluated diagnostic accuracy, stability in primary and metastatic sites, and associations with aggressive features. Knockdown experiments were performed to investigate the impact on PTC cell behavior. Additionally, we developed a support vector machine model for diagnosing malignant and high-risk PTCs.
RESULTS: CLDN16 demonstrated high specificity for PTC, with positive detection rates (88.0% in The Cancer Genome Atlas [TCGA] and 88.3% in our center) significantly surpassing BRAF-V600E (47.5% in TCGA and 74.3% in our center). This resulted in superior diagnostic accuracy (ROC-CLDN16 = 0.922 vs ROC-BRAF-V600E = 0.742 in TCGA). CLDN16 exhibited stable expression across primary and metastatic sites and was associated with aggressive features, including extrathyroidal extension and lymph node metastasis. CLDN16 knockdown inhibited migration, invasion, and iodine uptake in PTC cells. Clinically, CLDN16 effectively identified malignancy in BRAF wild patients (94.2%), and combined with BRAF-V600E, achieved 96.9% accuracy. The incorporation of CLDN16 into PTC molecular typing facilitated precise high-risk identification (92.0% accuracy in the training set and 100% in the validation set).
CONCLUSIONS: CLDN16 presents a promising biomarker that could surpass BRAF-V600E, offering effective clinical utility and revolutionizing PTC molecular typing for precise high-risk identification.
DESIGN: Database analyses, tissue validation, RNA sequencing, and functional assays were conducted to evaluate CLDN16 as a PTC biomarker and its clinical application.
METHODS: CLDN16 expression was examined in PTC and normal thyroid/para-tumor tissues and compared across various cancer types. We evaluated diagnostic accuracy, stability in primary and metastatic sites, and associations with aggressive features. Knockdown experiments were performed to investigate the impact on PTC cell behavior. Additionally, we developed a support vector machine model for diagnosing malignant and high-risk PTCs.
RESULTS: CLDN16 demonstrated high specificity for PTC, with positive detection rates (88.0% in The Cancer Genome Atlas [TCGA] and 88.3% in our center) significantly surpassing BRAF-V600E (47.5% in TCGA and 74.3% in our center). This resulted in superior diagnostic accuracy (ROC-CLDN16 = 0.922 vs ROC-BRAF-V600E = 0.742 in TCGA). CLDN16 exhibited stable expression across primary and metastatic sites and was associated with aggressive features, including extrathyroidal extension and lymph node metastasis. CLDN16 knockdown inhibited migration, invasion, and iodine uptake in PTC cells. Clinically, CLDN16 effectively identified malignancy in BRAF wild patients (94.2%), and combined with BRAF-V600E, achieved 96.9% accuracy. The incorporation of CLDN16 into PTC molecular typing facilitated precise high-risk identification (92.0% accuracy in the training set and 100% in the validation set).
CONCLUSIONS: CLDN16 presents a promising biomarker that could surpass BRAF-V600E, offering effective clinical utility and revolutionizing PTC molecular typing for precise high-risk identification.