Circulating small extracellular vesicle-based miRNA classifier for follicular thyroid carcinoma: a diagnostic study.

backgroundThe diagnosis of follicular thyroid carcinoma (FTC) prior to surgery remains a major challenge in the clinic.

methodsThis 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.

resultsThe 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.

conclusionsThe CirsEV-miR classifier could serve as a noninvasive, convenient, specific and stable auxiliary test to help diagnose FTC following ultrasonography.