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ORIGINAL RESEARCH article

Front. Oncol.

Sec. Thoracic Oncology

Volume 15 - 2025 | doi: 10.3389/fonc.2025.1516348

This article is part of the Research TopicRecent Advances in Radiation Oncology for the Management of Thoracic MalignanciesView all 15 articles

Development of a Predictive Model for Radiation Pneumonitis Based on Plasma Exosomal miR-200b-5p

Provisionally accepted
Shuwei  ZhaiShuwei Zhai1Yajun  ZhuYajun Zhu1Xiaoye  WangXiaoye Wang1Qingfeng  ZhaoQingfeng Zhao2Xu  LiangXu Liang2Shuhao  QueShuhao Que2Enhui  DaiEnhui Dai2Huaiyu  WangHuaiyu Wang2Yuetong  LiYuetong Li2Haihua  YangHaihua Yang3Wei  FengWei Feng2*
  • 1Department of Radiation Oncology, Changzhou jintan first people's hospital, Changzhou, China
  • 2Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China
  • 3Department of Radiation Oncology, The Affiliated Taizhou Hospital, Wenzhou Medical University, Taizhou, China

The final, formatted version of the article will be published soon.

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 independent risk factors for SRP. The nomogram model that incorporated these factors achieved an area under the receiver operating characteristic curve (AUC) of 0.844, outperforming the individual factors alone (lung V5: 0.748, MLD: 0.760, and miR-200b-5p expression: 0.666). Conclusion: The combination of lung V5 >46.36%, MLD >1120 cGy, and miR-200b-5p expression <0.445 can be used to effectively predict the occurrence of SRP in locally advanced NSCLC patients. This model can aid in the early identification of patients at high risk for RP, allowing for personalized treatment adjustments and improved patient outcomes.

Keywords: exosomal miRNAs, radiation pneumonitis (RP), Non-small cell lung cancer (NSCLC), predictive model, miR-200b-5p

Received: 24 Oct 2024; Accepted: 04 Aug 2025.

Copyright: © 2025 Zhai, Zhu, Wang, Zhao, Liang, Que, Dai, Wang, Li, Yang and Feng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Wei Feng, Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China

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