# Detection of TERT Promoter Mutations in Papillary Thyroid Carcinoma Using Droplet Digital PCR and Their Association with Aggressive Tumor Features

## TL;DR

This study shows that droplet digital PCR can detect TERT promoter mutations in thyroid cancer samples, which are linked to more aggressive tumor features.

## Contribution

The study validates ddPCR for detecting TERT promoter mutations in FFPE samples and links these mutations to aggressive tumor characteristics in papillary thyroid carcinoma.

## Key findings

- TERT promoter mutations were detected in 4.7% of papillary thyroid carcinoma cases using ddPCR.
- TERT mutations were associated with larger tumor size, extrathyroidal extension, capsular invasion, and lymph node metastasis.
- Age, tumor size, and lymph node metastasis were independently linked to TERT promoter mutations in multivariate analysis.

## Abstract

This study evaluated the reliability of droplet digital polymerase chain reaction (ddPCR) for detecting TERT promoter (pTERT) mutations in formalin-fixed, paraffin-embedded (FFPE) thyroid cancer samples and examined their association with clinicopathological features. A retrospective cohort of 296 postoperative patients with papillary thyroid carcinoma (PTC) was analyzed. DNA extracted from archived FFPE thyroidectomy specimens was examined for TERT promoter mutations using ddPCR. pTERT mutations were detected in 14 cases (4.7%). Tumors harboring pTERT mutations were significantly larger than wild-type tumors (1.5 ± 1.3 cm vs. 1.0 ± 0.7 cm, p = 0.012) and showed higher frequencies of extrathyroidal extension (78.6% vs. 55.0%, p = 0.028), capsular invasion (85.7% vs. 63.1%, p = 0.036), and lymph node metastasis (64.3% vs. 44.0%, p = 0.012). Multivariate analysis demonstrated that increasing age (odds ratio (OR), 1.07; 95% confidence interval (CI), 1.01–1.13; p = 0.015), tumor size (OR, 1.86; 95% CI, 1.12–3.08; p = 0.016), and lymph node metastasis (OR, 3.50; 95% CI, 1.09–6.53; p = 0.026) were independently associated with pTERT mutations. ddPCR enables sensitive detection of pTERT mutations in archived FFPE thyroid cancer specimens and identifies tumors with aggressive clinicopathological features, supporting its utility for postoperative risk stratification in clinical practice.