Background Papillary thyroid carcinoma (PTC) requires improved risk stratification through molecular profiling, yet how mutation interactions shape clinical outcomes remains poorly defined. Methods This single-center retrospective study analyzed 72 PTC cases using next-generation sequencing to characterize mutation patterns and pathway evolution, with validation against The Cancer Genome Atlas datasets. Results We identified three key molecular features: BRAF mutations (47.2%) predicted recurrence risk (p 0.001), TP53 mutations (15.3%) were more prevalent in advanced thyroid cancers, and mutual exclusivity between BRAF and RET / NRAS mutations (p 0.01), defining distinct oncogenic pathways. Paradoxically, BRAF mutations correlated with survival improvement (hazard ratio = 0.397), challenging conventional prognostic models. Pathway analysis revealed a potential shift from MAPK dominance in PTC to PI3K/NOTCH activation in advanced thyroid cancers, suggesting targetable vulnerabilities for mTOR inhibitors. Conclusion By integrating BRAF / TP53 status with conventional staging, we establish a mutation-guided framework that may refine risk prediction and inform treatment strategies, bridging molecular heterogeneity with clinical decision-making. This work provides insights for personalizing thyroid cancer management.
L et al. (Mon,) studied this question.