# Assessment of extracellular vesicle microRNAs detection in predicting benign and malignant pulmonary ground glass nodules

## TL;DR

This study explores how microRNAs in extracellular vesicles can help distinguish between benign and malignant lung nodules.

## Contribution

The study identifies specific microRNAs as potential biomarkers for differentiating benign and malignant pulmonary ground glass nodules.

## Key findings

- miR-1-3p and miR-92a-2-5p combined achieved 100% sensitivity and specificity in distinguishing benign and malignant nodules.
- Certain microRNAs showed significantly different expression levels between malignant and benign nodules.
- miR-1-3p was the most accurate single marker for diagnosis.

## Abstract

To assess extracellular vesicle microRNAs detection in predicting malignant and benign pulmonary ground glass nodules (GGNs).

A retrospective study was conducted on 96 patients with pulmonary GGNs, hospitalized in Suzhou Kowloon Hospital and The Second Affiliated Hospital of Soochow University, Shanghai Jiaotong University School of Medicine between April 2021 and March 2022. Based on pathological diagnosis, 67 were in the malignant group and 29 in the benign group. Additionally, 50 healthy individuals from the same hospitals were enrolled as controls. Plasma exosomal microRNAs (miRNAs) levels were measured by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) in the three groups. The diagnostic value of candidate miRNAs was analyzed using receiver operating characteristic (ROC) curves.

Nodule size and proportion of pure GGNs were significantly higher in the malignant group than the benign group (p < 0.05). Expression of miR-17-5p and miR-1-3p was lower in malignant GGNs compared to benign ones, while miR-20b-5p, miR-9-5p, and miR-92a-2-5p were higher (p < 0.05). Compared to healthy controls, miR-1-3p and miR-17-5p were decreased, and miR-92a-2-5p, miR-9-5p, and miR-20b-5p were increased in malignant GGNs (p < 0.05). Among individual markers, miR-1-3p had the highest sensitivity and specificity. Sensitivity ranking: miR-1-3p > miR-20b-5p > miR-92a-2-5p > miR-9-5p > miR-17-5p; specificity ranking: miR-92a-2-5p > miR-17-5p > miR-1-3p > miR-9-5p > miR-20b-5p. Combining miR-1-3p and miR-92a-2-5p yielded an AUC of 1.000, with 100% sensitivity and specificity. In the healthy group comparison, miR-1-3p remained the most accurate single marker. Specificity ranking: miR-1-3p > miR-20b-5p > miR-92a-2-5p > miR-9-5p > miR-17-5p; sensitivity ranking: miR-1-3p > miR-17-5p > miR-92a-2-5p > miR-20b-5p > miR-9-5p.

miR-1-3p, miR-9-5p, miR-17-5p, miR-20b-5p, and miR-92a-2-5p show promise as diagnostic biomarkers for GGN.