Department of endocrinology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Department of Thyroid Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
EBioMedicine. 2023 Apr;90:104497. doi: 10.1016/j.ebiom.2023.104497. Epub 2023 Mar 1.
BACKGROUND: Cell-free DNA (cfDNA) is being explored as biomarker for non-invasive diagnosis of cancer. We aimed to establish a cfDNA-based DNA methylation marker panel to differentially diagnose papillary thyroid carcinoma (PTC) from benign thyroid nodule (BTN). METHODS: 220 PTC- and 188 BTN patients were enrolled. Methylation markers of PTC were identified from patients' tissue and plasma by reduced representation bisulfite sequencing and methylation haplotype analyses. They were combined with PTC markers from literatures and were tested on additional PTC and BTN samples to verify PTC-detecting ability using targeted methylation sequencing. Top markers were developed into ThyMet and were tested in 113 PTC and 88 BTN cases to train and validate a PTC-plasma classifier. Integration of ThyMet and thyroid ultrasonography was explored to improve accuracy. FINDINGS: From 859 potential PTC plasma-discriminating markers that include 81 markers identified by us, the top 98 most PTC plasma-discriminating markers were selected for ThyMet. A 6-marker ThyMet classifier for PTC plasma was trained. In validation it achieved an Area Under the Curve (AUC) of 0.828, similar to thyroid ultrasonography (0.833) but at higher specificity (0.722 and 0.625 for ThyMet and ultrasonography, respectively). A combinatorial classifier by them, ThyMet-US, improved AUC to 0.923 (sensitivity = 0.957, specificity = 0.708). INTERPRETATION: The ThyMet classifier improved the specificity of differentiating PTC from BTN over ultrasonography. The combinatorial ThyMet-US classifier may be effective in preoperative diagnosis of PTC. FUNDING: This work was supported by the grants from National Natural Science Foundation of China (82072956 and 81772850).
背景:游离 DNA(cfDNA)正被探索作为癌症无创诊断的生物标志物。本研究旨在建立基于 cfDNA 的甲基化标记物panel,以区分甲状腺乳头状癌(PTC)和良性甲状腺结节(BTN)。
方法:纳入 220 例 PTC 患者和 188 例 BTN 患者。通过重亚硫酸盐限制性测序和甲基化单体型分析,从患者的组织和血浆中鉴定出 PTC 的甲基化标记物。这些标记物与文献中的 PTC 标记物相结合,并在额外的 PTC 和 BTN 样本中进行测试,以使用靶向甲基化测序验证其检测 PTC 的能力。优选的标记物被开发成 ThyMet,并在 113 例 PTC 和 88 例 BTN 病例中进行测试,以训练和验证 PTC 血浆分类器。探索了 ThyMet 与甲状腺超声的整合,以提高准确性。
结果:在 859 个可能的 PTC 血浆区分标记物中,包括我们鉴定的 81 个标记物,选择了前 98 个最具 PTC 血浆区分能力的标记物用于 ThyMet。建立了用于 PTC 血浆的 6 个标记物 ThyMet 分类器。在验证中,其曲线下面积(AUC)为 0.828,与甲状腺超声(0.833)相似,但特异性更高(ThyMet 和超声分别为 0.722 和 0.625)。它们的组合分类器 ThyMet-US,AUC 提高到 0.923(敏感性为 0.957,特异性为 0.708)。
结论:ThyMet 分类器提高了超声区分 PTC 和 BTN 的特异性。组合的 ThyMet-US 分类器可能在 PTC 的术前诊断中有效。
资助:本工作得到国家自然科学基金(82072956 和 81772850)的资助。
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