Correlation between gene mutations and clinical characteristics in papillary thyroid cancer: a retrospective analysis of BRAF mutations and RET rearrangements.

INTRODUCTION

Activation of the MAPK pathway by genetic mutations (such as BRAF and RET) initiates and accelerates the growth of papillary thyroid carcinoma (PTC). However, the correlation between genetic mutations and clinical features remains to be established. Therefore, this study aimed to retrospectively analyze major genetic mutations, specifically BRAF mutations and RET rearrangements, and develop a treatment algorithm by comparing background and clinical characteristics.

METHOD

One hundred thirteen patients with primary PTC were included in this study. BRAF mutations were detected via Sanger sequencing and RET rearrangements were detected via fluorescence in situ hybridization (FISH) analysis, and reverse transcription polymerase chain reaction (RT-PCR). The patients were categorized into two groups based on the presence of BRAF mutations and RET rearrangements and their clinical characteristics (age, sex, TNM, stage, extratumoral extension, tumor size, unifocal/multifocal lesions, vascular invasion, differentiation, chronic thyroiditis, preoperative serum thyroglobulin level, and F-fluorodeoxyglucose (FDG) uptake) were compared subsequently.

RESULT

After excluding unanalyzable specimens, 80 PTC patients (22 males and 58 females, mean age: 57.2 years) were included in the study. RET rearrangements were positive in 8 cases (10%), and BRAF mutation was positive in 63 (78.6%). The RET rearrangement group was significantly associated with younger age (p = 0.024), multifocal lesion (p = 0.048), distant metastasis (p = 0.025) and decreased F-fluorodeoxyglucose uptake (p < 0.001). The BRAF mutation group was significantly associated with unifocal lesions (p = 0.02) and increased F-FDG uptake (p = 0.004).

CONCLUSION

In this study, an increase in M classification cases was found in the RET rearrangements group. However, genetic mutations were not associated with the clinical stage, and no factors that could be incorporated into the treatment algorithm were identified.