基于循环微小细胞外囊泡的 miRNA 分类器在滤泡甲状腺癌中的诊断研究。
Circulating small extracellular vesicle-based miRNA classifier for follicular thyroid carcinoma: a diagnostic study.
机构信息
Division of Thyroid Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China.
The Laboratory of Thyroid and Parathyroid Disease, Frontiers Science Center for Disease-related Molecular Network, West China Hospital of Sichuan University, Chengdu, China.
出版信息
Br J Cancer. 2024 Apr;130(6):925-933. doi: 10.1038/s41416-024-02575-0. Epub 2024 Jan 18.
BACKGROUND
The diagnosis of follicular thyroid carcinoma (FTC) prior to surgery remains a major challenge in the clinic.
METHODS
This multicentre diagnostic study involved 41 and 150 age- and sex-matched patients in the training cohort and validation cohort, respectively. The diagnostic properties of circulating small extracellular vesicle (sEV)-associated and cell-free RNAs were compared by RNA sequencing in the training cohort. Subsequently, using a quantitative real-time polymerase chain reaction (qRT‒PCR) assay, high-quality candidates were identified to construct an RNA classifier for FTC and verified in the validation cohort. The parallel expression, stability and influence of the RNA classifier on surgical strategy were also investigated.
RESULTS
The diagnostic properties of sEV long RNAs, cell-free long RNAs and sEV microRNAs (miRNAs) were comparable and superior to those of cell-free miRNAs in RNA sequencing. Given the clinical application, the circulating sEV miRNA (CirsEV-miR) classifier was developed from five miRNAs based on qRT‒PCR data, which could well identify FTC patients (area under curve [AUC] of 0.924 in the training cohort and 0.844 in the multicentre validation cohort). Further tests revealed that the CirsEV-miR score was significantly correlated with the tumour burden, and the levels of sEV miRNAs were also higher in sEVs from the FTC cell line, organoid and tissue. Additionally, circulating sEV miRNAs remained constant after different treatments, and the addition of the CirsEV-miR classifier as a biomarker improves the current surgical strategy.
CONCLUSIONS
The CirsEV-miR classifier could serve as a noninvasive, convenient, specific and stable auxiliary test to help diagnose FTC following ultrasonography.
背景
术前诊断滤泡状甲状腺癌(FTC)仍然是临床面临的一大挑战。
方法
本项多中心诊断研究纳入了 41 例和 150 例分别来自训练队列和验证队列的年龄和性别匹配患者。通过在训练队列中的 RNA 测序比较循环小细胞外囊泡(sEV)相关和无细胞 RNA 的诊断特性。随后,使用定量实时聚合酶链反应(qRT-PCR)检测,鉴定高质量候选物构建 FTC 的 RNA 分类器,并在验证队列中进行验证。还研究了 RNA 分类器对手术策略的平行表达、稳定性和影响。
结果
sEV 长 RNA、无细胞长 RNA 和 sEV 微小 RNA(miRNA)的诊断特性可与无细胞 miRNA 相媲美,在 RNA 测序中优于无细胞 miRNA。鉴于临床应用,基于 qRT-PCR 数据从 5 个 miRNA 开发了循环 sEV miRNA(CirsEV-miR)分类器,可很好地区分 FTC 患者(训练队列的 AUC 为 0.924,多中心验证队列的 AUC 为 0.844)。进一步的测试表明,CirsEV-miR 评分与肿瘤负荷显著相关,并且在 FTC 细胞系、类器官和组织来源的 sEV 中,sEV miRNA 的水平也更高。此外,循环 sEV miRNAs 在不同处理后保持稳定,添加 CirsEV-miR 分类器作为生物标志物可改善当前的手术策略。
结论
CirsEV-miR 分类器可作为一种非侵入性、简便、特异和稳定的辅助检测方法,用于在超声检查后辅助诊断 FTC。