Germline polymorphisms of the NOD2 pathway may predict the effectiveness of radioiodine in differentiated thyroid cancer treatment

NOD2通路种系多态性可能预测放射性碘治疗分化型甲状腺癌的疗效

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Abstract

PURPOSE: Differentiated thyroid cancer (DTC) presents a complex clinical challenge, especially in patients with distant metastases and resistance to standard treatments. This study aimed to investigate the influence of specific genes and their germline single nucleotide polymorphisms (SNPs) linked to both inflammatory processes and other neoplasms on the clinical and pathological characteristics of DTC, particularly their potential impact on radioiodine (RAI) treatment efficacy. METHODS: This retrospective analysis involved a cohort of 646 patients diagnosed with DTC after thyroidectomy. Study covering 1998-2014, updated in 2023, included 567 women and 79 men (median age: 49; range: 7-83). SNP selection targeted functional significance, while mutational status was assessed by pyrosequencing for comprehensive characterization. Patient genetic profiles were assessed for associations with disease characteristics, RAI response, and cancer pathology. RESULTS: Significant correlations emerged between certain SNPs and DTC features. Notably, the NOD2 c.802 T > C variant (rs2066842) was identified as a marker distinguishing between papillary thyroid cancer (PTC) and follicular thyroid cancer (FTC). Moreover, the c.802 T allele was associated with an enhanced response to RAI treatment, indicating a more substantial decrease in posttreatment stimulated thyroglobulin (sTg) concentrations. The NFKB1A allele c.126A (rs696) exhibited connections with lower FTC stages and a reduced probability of multifocality. CONCLUSION: This study explored the molecular mechanisms of particular SNPs, highlighting the role of NOD2 in innate immunity and the stress response, and its potential impact on RAI efficacy. This research underscores the clinical promise of SNP analysis and contributes to personalized treatment strategies for DTC, emphasizing the relevance of genetic factors in cancer progression and treatment outcomes.

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