# Diagnosis and Evaluation of Aggressiveness Using Circulating Plasma miRNAs in Papillary Thyroid Microcarcinoma

**Authors:** Jiwon Jang, Ji Min Kim, Sung-Chan Shin, Yong-il Cheon, Bo Hyun Kim, Mijin Kim, Sang Soo Kim, Byung-Joo Lee

PMC · DOI: 10.3390/cancers17132079 · Cancers · 2025-06-21

## TL;DR

This study explores how specific microRNAs in blood plasma can help diagnose papillary thyroid microcarcinoma and assess its aggressiveness.

## Contribution

The study identifies a six-miRNA combination that effectively differentiates benign nodules from PTMC and predicts tumor aggressiveness.

## Key findings

- A six-miRNA combination (miR-455-3p, miR-548ac, miR-221, miR-222, miR-146a, miR-146b-5p) best distinguishes benign from PTMC with high AUC, sensitivity, and specificity.
- The same miRNA combination can differentiate low-risk PTMC from aggressive PTMC with an AUC of 0.763.
- Individual miRNAs were less effective than the combined six-miRNA panel in classification tasks.

## Abstract

This study investigated whether miRNAs can differentiate PTMCs (papillary thyroid microcarcinoma) from benign nodules and predict their aggressiveness. In a group of 150 thyroidectomy patients, a combination of six miRNAs (miR-455-3p, miR-548ac, miR-221, miR-222, miR-146a, and miR-146b-5p) demonstrated the best ability to distinguish between benign, low-risk, and advanced PTMCs. This miRNA combination was also effective in differentiating low-risk PTMCs from aggressive ones.

Background/Objectives: MicroRNAs are emerging as valuable diagnostic markers for various diseases, including papillary thyroid carcinoma (PTC). However, there is limited research on circulating miRNA expression in papillary thyroid microcarcinoma (PTMC). Therefore, we conducted a study to explore whether plasma-derived miRNAs can distinguish PTMC from benign nodules or predict aggressiveness. Methods: A total of 150 patients who underwent thyroidectomy from January 2013 to July 2021 were enrolled in this study. Patients were divided into three groups: benign, low-risk PTMC, and advanced PTMC. Nine patients from each group were selected for microarray analysis for plasma miRNAs. Six miRNAs were selected for comparison of expression levels using TaqMan assay. The ROC curve was utilized to evaluate the diagnostic and aggressiveness value of the miRNAs. Results: From the microarray analysis, miR-455-3p and miR-548ac were identified as miRNAs that can significantly differentiate between benign nodules and PTMC. A combination of six miRNAs (miR-455-3p, miR-548ac., miR-221, miR-222, miR-146a. miR-146b) rather than individual miRNAs had the highest AUC (0.857), sensitivity (0.867), and specificity (0.800) in differentiating benign and PTMC. In microarray analysis, no significant miRNAs were observed to distinguish between low-risk group and aggressive PTMC. However, in the six-miRNA combination, it was possible to distinguish low-risk PTMC from aggressive PTMC with an AUC of 0.763, sensitivity of 0.739, and the specificity of 0.727. Conclusions: A combination of six miRNAs presents the possibility of distinguishing between benign and PTMC and low-risk and aggressive PTMC with an acceptable AUC, sensitivity, and specificity.

## Linked entities

- **Genes:** MIR548AC (microRNA 548ac) [NCBI Gene 100616384], MIR221 (microRNA 221) [NCBI Gene 407006], MIR222 (microRNA 222) [NCBI Gene 407007], MIR146A (microRNA 146a) [NCBI Gene 406938]
- **Diseases:** papillary thyroid microcarcinoma (MONDO:0011368)

## Full-text entities

- **Genes:** MIR146B (microRNA 146b) [NCBI Gene 574447] {aka MIRN146B, miRNA146B, mir-146b}, MIR222 (microRNA 222) [NCBI Gene 407007] {aka MIRN222, miRNA222, mir-222}, MIR548AC (microRNA 548ac) [NCBI Gene 100616384], MIR221 (microRNA 221) [NCBI Gene 407006] {aka MIRN221, miRNA221, mir-221}, MIR146A (microRNA 146a) [NCBI Gene 406938] {aka MIRN146, MIRN146A, miR-146a, miRNA146A}
- **Diseases:** PTC (MESH:D000077273), PTMC (MESH:C563277)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

8 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12249405/full.md

## References

43 references — full list in the complete paper: https://tomesphere.com/paper/PMC12249405/full.md

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Source: https://tomesphere.com/paper/PMC12249405