ABSTRACT
PURPOSE: The current management guidelines for low-risk papillary thyroid microcarcinoma (PTMC) do not specify how to screen for growing tumors. We sought to explore the possible risk factors for tumor enlargement in patients with low-risk PTMC under active surveillance (AS). METHODS: We searched the PubMed and Embase databases for high quality studies up to January 10th, 2024. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of the included studies, and Review Manager 5.4 was used to analyze possible risk factors and calculate pooled risk ratios (RRs) via the inverse-variance calculation method. RESULTS: Eleven studies were included in our meta-analysis. Among the 8880 participants, 464 experienced tumor growth, and the incidence of tumor growth varied from 3.4% to 19.4%. The results of the meta-analysis showed that tumor enlargement was associated with younger age (pooled RR = 2.32, 95% CI = 1.85-2.90, p < 0.00001; 8 studies), and higher serum thyroid-stimulating hormone (TSH) levels (pooled RR = 2.28, 95% CI = 1.19-4.37, p = 0.01; 6 studies), and could be related to pregnancy (pooled RR = 2.54, 95% CI = 1.17-5.52, p = 0.02; 2 studies). However, these following factors showed no significant association with tumor growth: sex (pooled RR = 1.07, 95% CI = 0.63-1.84, p = 0.79; 7 studies), tumor size at diagnosis (pooled RR = 1.08, 95% CI = 0.63-1.85, p = 0.77; 5 studies), and Hashimoto's thyroiditis (HT) (pooled RR = 1.56, 95% CI = 0.93-2.60, p = 0.09; 2 studies). CONCLUSION: Our analysis identified that younger age and higher serum TSH levels were higher risk factors for tumor enlargement in low-risk PTMC patients. Pregnancy is a suspected risk factor.
ABSTRACT
Objective: To explore the potential value of a novel marker, KIF-12, in the progression and prognosis of papillary thyroid carcinoma (PTC) through integrative bioinformatics analysis, and clinical sample validation of the prognostic value of KIF-12. Materials and Methods: We extracted the clinicopathological data of 502 PTC patients from The Cancer Genome Atlas-Thyroid Cancer (TCGA-THCA) dataset to identify reliable differentially expressed genes (DEGs) between high and low KIF12 expression groups. Functional enrichment analysis was performed on upregulated DEGs. Gene set enrichment analysis (GESA) was performed to identify the biological pathways. We further applied Cox analysis to determine independent risk factors associated with the PTC progression-free interval (PFI), and a nomogram was established to predict disease outcome. Finally, the prognostic value of KIF12 was validated by means of clinical samples from PTC patients with and without lateral lymph node metastasis. Results: On the basis of the TCGA-THCA database, we found that low KIF-12 expression was significantly related to a higher TNM stage (p<0.05), BRAF mutation status (p = 0.019), and extrathyroidal extension (p<0.001). KIF-12 was an independent prognostic factor of PTC (OR=0.319, 95% CI=0.130-0.784, P=0.013). The prognostic value of KIF12 was also successfully validated in clinical samples from twenty-nine PTC patients with lateral lymph node metastasis by comparison with twenty-two PTC patients without lymph node metastasis (P = 0.004). Conclusions: We report that KIF-12 has a tumor suppressive function in PTC and may be a useful prognostic tool to predict patient outcomes.
ABSTRACT
Genetic profiling is important for assisting the management of papillary thyroid microcarcinoma (PTMC). Although whole-exome sequencing (WES) of surgically resected PTMC tissue has been performed and revealed potential prognostic biomarkers, its application in PTMC fine-needle aspiration (FNA) specimens has not been explored. This study aimed to evaluate the feasibility of WES using FNA specimens of PTMC. Five PTMC patients were enrolled with clinical characteristics gathered. Fine aspiration cytology needle (23 gauges) was used to collect FNA biopsy with ultrasound guidance. WES analysis of FNA specimens from five PTMC patients and matched blood samples was performed. The WES of FNA samples yielded an average sequencing depth of 281× and average coverage of 99.5%. We identified 534 somatic single-nucleotide variants and 13 indels in total, and per sample, we found a mean of 24 exonic mutations, which affected a total of 120 genes. In the PTMC FNA samples, the most frequently mutated genes were BRAF and ANKRD18B, and the four driver genes were BRAF, AFF3, SRCAP, and EGFR. We also identified several germline cancer predisposing gene mutations. The results suggest that WES of FNA specimens is feasible for PTMC and can identify novel genetic mutations.
