Molecular alteration patterns predict tumor behavior in papillary thyroid carcinoma independent of tumor size: insights from an international multicenter retrospective study - Grégoire B. Morand; Idit Tessler; Simon E. Thurnheer; Kayla E. Payne; Maxine Noik; Josh Krasner; Tzahi Yamin; Marc P. Pusztaszeri; Richard J. Payne; Galit Avior (Thyroid Research)
Abstract Background Molecular testing is a well-established tool that assists in the management of thyroid nodules and allows classification in distinct molecular alteration patterns: BRAF-like, RAS-like and non-BRAF-non-RAS (NBNR). Yet classical TNM classification and ATA guidelines currently rely on tumor size for risk stratification. In this study, we compared tumor behavior according to molecular alteration patterns versus tumor size. Methods Retrospective multicenter multinational study of thyroid nodules that underwent preoperative molecular profiling with ThyGenX/ThyGeNEXT or ThyroSeq V3 between 2015 and 2022. Clinical characteristics, including demographics, cytology results, tumor size, surgical pathology, and molecular alterations, were analyzed. Results The study included 718 patients who underwent surgery for papillary thyroid cancer, with a majority of 556 (77.4%) being female. The distribution of molecular alteration patterns was as follows: BRAF-like in 227 (31.6%), RAS-like in 171 (23.8%), NBNR in 59 (8.2%), BRAF/RAS overlap 8 (1.1%) and no detectable mutation in 224 (31.2%) cases. The median tumor size was 15 mm (IQR 10–24). Extrathyroidal extension (ETE) was observed in 6.2% of cases with gross ETE and 5.6% with minimal ETE. Notably, nodules with BRAF-like molecular alterations were more likely to exhibit ETE compared to those with RAS-like or NBNR alterations (P < 0.001). There was no significant correlation between ETE and median tumor size (P > 0.05). Conclusion Molecular testing of thyroid nodules provides a more accurate prediction of tumor behavior compared to tumor size alone. These findings suggest that future staging systems could benefit from incorporating molecular alteration patterns into their algorithms.