Development of a predictive model for radiation pneumonitis based on plasma exosomal miR-200b-5p

作者：Shuwei Zhai, Yajun Emily Zhu, Xiaoye Wang, Qianfei Zhao, Liang Xu, Shuhao Que, Enhui Dai, Huaiyu Wang, Yuetong Li, Haihua Yang, Wei Feng · 发表于：Frontiers in Oncology · 年份：2025 · DOI：10.3389/fonc.2025.1516348 · 被引用次数：2 · 研究领域：Effects of Radiation Exposure、Lung Cancer Research Studies、Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis

Objective This study aims to explore the association between plasma exosomal miRNAs and the development of radiation pneumonitis (RP) in non-small cell lung cancer (NSCLC) patients who underwent radiotherapy, and develop a predictive model for symptomatic radiation pneumonitis (SRP) by integrating miRNA expression levels with clinical and dosimetric parameters. Methods A total of 95 NSCLC patients, who were scheduled to receive definitive radiotherapy, were prospectively enrolled. Plasma exosomes were collected before the radiotherapy, and high-throughput sequencing followed by bioinformatics analysis was performed to identify the candidate miRNAs associated to SRP. Then, the expression levels of these miRNAs were validated using RT-qPCR. Afterwards, a predictive model for SRP was constructed using a nomogram, which combined the miRNA expression data with the clinical and dosimetric factors. Results Among the 95 patients, 20 (21.10%) patients developed SRP. The high-throughput sequencing revealed 220 differentially expressed miRNAs. Among these miRNAs, 168 miRNAs were upregulated and 52 miRNAs were downregulated in SRP patients ( p <0.05). The bioinformatics analysis identified miR-200b-5p as the key candidate miRNA. The univariate and multivariate analyses revealed that lung V5 (OR: 1.264, 95% CI: 1.042-1.532, p =0.018), mean lung dose (MLD; OR: 1.013, 95% CI: 1.004-1.023, p =0.006), and miR-200b-5p expression (OR: 0.144, 95% CI: 0.024-0.877, p =0.032) were the indepe...