Suppr超能文献

基于二代测序的多基因检测在甲状腺结节良恶性鉴别及风险分层中的价值。

The value of NGS-based multi-gene testing for differentiation of benign from malignant and risk stratification of thyroid nodules.

作者信息

Fei Mingjian, Ding Dongdong, Ouyang Xuanyi, Shen Wenyan, Zhang Fenglan, Zhang Bo, Qin Lan

机构信息

Department of Pathology, The Second Affiliated Hospital of Jiaxing University, Jiaxing, China.

Center for Clinical Genetics and Genomics, Dian Diagnostics Group Co., Ltd., Hangzhou, China.

出版信息

Front Oncol. 2024 Nov 12;14:1414492. doi: 10.3389/fonc.2024.1414492. eCollection 2024.

Abstract

BACKGROUND

Fine-needle aspiration (FNA) biopsy is typically used in conjunction with cytopathologic evaluation to differentiate between benign and malignant thyroid nodules. Even so, the cytology results for 20-30% of thyroid nodules are indeterminate. This study sought to evaluate the usefulness of next-generation sequencing (NGS)-based multi-gene panel testing for risk stratification and the differentiation of benign from malignant thyroid nodules.

METHODS

Thyroid nodule samples were obtained from a cohort of 359 patients who underwent FNA. An NGS-based multi-gene panel testing was conducted for these samples, in which single-nucleotide variants (SNVs) and small insertion/deletions (InDels) can be detected in 11 genes and fusion events can be identified in 5 genes. Surgical resection was conducted for 113 patients (113/359), and then histopathology results were obtained.

RESULTS

In comparison to cytology alone, the diagnostic sensitivity of NGS combination cytology increased from 0.7245 (95% CI: 0.6289-0.8032) to 0.898 (95% CI: 0.8223-0.9437); the associated AUC was 0.8303 (vs. Cytology AUC: 0.7622, < 0.001). was identified in 136 patients, of whom 79 underwent surgery and were diagnosed with papillary thyroid carcinoma (PTC) pathologically. promoter mutations or / co-mutations with other genes were identified in 5 patients, while 4 patients were diagnosed with malignant thyroid cancer using the pathological method. mutations were identified in 27 patients, while 10 patients underwent surgery, which showed that 3 patients were classified as PTC and 7 cases were benign. In addition, 4 fusions, 1 activation mutation, and 3 inactivation mutations were identified in the remaining 8 patients who have not undergone surgery. Negative genetic test results or variants with uncertain significance were identified in 183 patients. Among these patients, 12 malignant thyroid tumors, including 11 PTC and 1 MTC, were diagnosed in 20 patients who received surgery.

CONCLUSION

Thyroid nodules coupled with , promoter variants, / co-mutations with other genes, fusions, and activating mutations were classified as high-risk. Nodules with mutations (, , ) and inactivating mutations were considered to be in the intermediate-risk group, while those with non-pathogenic mutations (negative and variants of uncertain significance) were placed in the low-risk group. When combined with cytopathology, NGS increases the sensitivity of diagnosing benign and malignant thyroid nodules, and the reference is useful for patient risk stratification.

摘要

背景

细针穿刺(FNA)活检通常与细胞病理学评估结合使用,以区分良性和恶性甲状腺结节。即便如此,20%-30%的甲状腺结节的细胞学结果仍不明确。本研究旨在评估基于二代测序(NGS)的多基因检测对甲状腺结节的风险分层以及良恶性鉴别的作用。

方法

从359例行FNA的患者队列中获取甲状腺结节样本。对这些样本进行基于NGS的多基因检测,可检测11个基因中的单核苷酸变异(SNV)和小插入/缺失(InDel),并识别5个基因中的融合事件。113例患者(113/359)接受了手术切除,随后获得组织病理学结果。

结果

与单纯细胞学检查相比,NGS联合细胞学检查的诊断敏感性从0.7245(95%CI:0.6289-0.8032)提高到0.898(95%CI:0.8223-0.9437);相关的AUC为0.8303(vs.细胞学AUC:0.7622,P<0.001)。136例患者检测到BRAF V600E突变,其中79例接受手术,术后病理诊断为甲状腺乳头状癌(PTC)。5例患者检测到TERT启动子突变或与其他基因的共突变,4例患者经病理方法诊断为恶性甲状腺癌。27例患者检测到RAS突变,10例患者接受手术,其中3例为PTC,7例为良性。此外,在其余8例未接受手术的患者中检测到4例RET融合、1例NTRK激活突变和3例TP53失活突变。183例患者基因检测结果为阴性或意义不明确的变异。在这些患者中,20例接受手术的患者诊断出12例恶性甲状腺肿瘤,包括11例PTC和1例MTC。

结论

伴有BRAF V600E、TERT启动子变异、与其他基因的共突变、RET融合和NTRK激活突变的甲状腺结节被分类为高风险。伴有RAS突变(NRAS、HRAS、KRAS)和TP53失活突变的结节被认为处于中风险组,而具有非致病性突变(阴性和意义不明确的变异)的结节被归为低风险组。当与细胞病理学结合时,NGS提高了甲状腺结节良恶性诊断的敏感性,该参考对患者风险分层有用。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验