# Small extracellular vesicle miRNAs as biomarkers for predicting antitumor efficacy in lung adenocarcinoma treated with chemotherapy and checkpoint blockade

## TL;DR

This study explores using small extracellular vesicle miRNAs in blood as non-invasive biomarkers to predict which lung cancer patients will benefit from combined immunotherapy and chemotherapy.

## Contribution

The study identifies specific miRNAs that can predict treatment response in lung adenocarcinoma patients receiving immunochemotherapy.

## Key findings

- 56 differentially expressed miRNAs were identified between responders and nonresponders.
- A prediction model using sEV miRNAs achieved an area under the curve (AUC) > 0.9.
- Specific miRNAs like miR-99b-3p and miR-100-5p were upregulated in responders.

## Abstract

Checkpoint blockade combined with chemotherapy has become an important treatment option for lung cancer patients in clinical settings. However, biomarkers that effectively identify true responders remain lacking. We assessed the potential of plasma small extracellular vesicle (sEV)-derived microRNAs (miRNAs) as biomarkers for predicting and identifying responders to combined immunochemotherapy. A total of 29 patients with lung adenocarcinoma who received pembrolizumab combined with pemetrexed and carboplatin were enrolled. The efficacy evaluation revealed that 24 patients obtained durable clinical benefits from combined immunochemotherapy, and the rest experienced disease progression. Using unsupervised hierarchical clustering, 56 differentially expressed miRNAs (DEMs) were identified between responders and nonresponders. Efficacy prediction models incorporating a combination of sEV miRNAs were established and showed good performance (area under the curve (AUC) > 0.9). In addition, we found that miR-96-5p and miR-6815-5p were notably downregulated in the nonresponder group, while miR-99b-3p, miR-100-5p, miR-193a-5p, and miR-320d were upregulated. These findings were further confirmed by clinical imaging. sEV miRNAs derived from patients with lung cancer showed promise for identifying true responders to combined immunochemotherapy.

Proposed model of sEV miRNAs as a promising non-invasive tool for predicting true responders of lung adenocarcinoma patients receiving immunotherapy combined with chemotherapy.