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March 14, 2026Cell Reports Medicine2 citationsOpen Access

A targeted proteomics assay for the preoperative diagnosis of thyroid nodules

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XCXue CaiYSYi SunDLDingcun Luo

Key Points

  • The study aims to improve preoperative diagnosis of thyroid nodules using a targeted proteomics classifier.
  • Conducted a prospective, noninterventional, blinded, multicenter study.
  • Developed the ThyroProt classifier based on a 3-protein signature and BRAF V600E mutation.
  • Validated the classifier on 837 FNA samples and evaluated in a prospective test set of 322 samples.
  • Analyzed performance in two independent multicenter cohorts.
  • Achieved an area under the curve (AUC) of 0.94 with an overall accuracy of 90.7%.
  • In Bethesda III/IV nodules, accuracy was 88.0%, sensitivity 82.4%, and specificity 100%.
  • Maintained an AUC of 0.87-0.91 and accuracy of 84.3%-85.7% in independent cohorts.

Abstract

Accurate preoperative diagnosis of thyroid nodules via fine-needle aspiration (FNA) biopsy remains challenging, particularly in cases with indeterminate cytology. This prospective, noninterventional, blinded, multicenter study establishes ThyroProt, a diagnostic classifier that integrates targeted mass-spectrometry-based quantification of a 3-protein signature with BRAF V600E mutation status, age, and gender. Developed and validated on 837 FNA samples, the classifier is evaluated in a prospective test set of 322 samples, achieving an area under the curve (AUC) of 0.94 with an overall accuracy of 90.7%. For the critical subgroup of Bethesda III/IV nodules, ThyroProt demonstrates an accuracy of 88.0%, with 82.4% sensitivity and 100% specificity. The classifier's robust performance is further evaluated in two independent multicenter cohorts, where it maintains an AUC of 0.87-0.91 and an accuracy of 84.3%-85.7%. This study supports the clinical utility of mass-spectrometry-based targeted proteomics for improving preoperative diagnosis of thyroid nodules, particularly those with indeterminate cytology.

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Cite This Study

Cai et al. (2026) studied this question.

synapsesocial.com/papers/69b4fac6b39f7826a300b67fhttps://doi.org/10.1016/j.xcrm.2026.102664
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