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Data Sheet 1_Mutation interactions of BRAF and TP53 define novel prognostic stratification and therapeutic implications in papillary thyroid carcinoma.docx

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Data_Sheet_1_Mutation_interactions_of_BRAF_and_TP53_define_novel_prognostic_stratification_and_therapeutic_implications_in_papillary_thyroid_carcinoma_docx/30229381
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BackgroundPapillary thyroid carcinoma (PTC) requires improved risk stratification through molecular profiling, yet how mutation interactions shape clinical outcomes remains poorly defined. MethodsThis 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. ResultsWe 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. ConclusionBy 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.
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2025-09-29
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