Development of a predictive model for radiation pneumonitis based on plasma exosomal miR-200b-5p
ObjectiveThis 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 mi...
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-08-01
|
| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2025.1516348/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849233419904483328 |
|---|---|
| author | Shuwei Zhai Yajun Zhu Xiaoye Wang Qingfeng Zhao Xu Liang Shuhao Que Enhui Dai Huaiyu Wang Yuetong Li Haihua Yang Wei Feng |
| author_facet | Shuwei Zhai Yajun Zhu Xiaoye Wang Qingfeng Zhao Xu Liang Shuhao Que Enhui Dai Huaiyu Wang Yuetong Li Haihua Yang Wei Feng |
| author_sort | Shuwei Zhai |
| collection | DOAJ |
| description | ObjectiveThis 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.MethodsA 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.ResultsAmong 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).ConclusionThe 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. |
| format | Article |
| id | doaj-art-9d68e569b3a84127a4715ef97fc7dda7 |
| institution | Kabale University |
| issn | 2234-943X |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj-art-9d68e569b3a84127a4715ef97fc7dda72025-08-20T05:33:02ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-08-011510.3389/fonc.2025.15163481516348Development of a predictive model for radiation pneumonitis based on plasma exosomal miR-200b-5pShuwei Zhai0Yajun Zhu1Xiaoye Wang2Qingfeng Zhao3Xu Liang4Shuhao Que5Enhui Dai6Huaiyu Wang7Yuetong Li8Haihua Yang9Wei Feng10Department of Radiation Oncology, Changzhou Jintan First People’s Hospital, Changzhou, ChinaDepartment of Radiation Oncology, Changzhou Jintan First People’s Hospital, Changzhou, ChinaDepartment of Radiation Oncology, Changzhou Jintan First People’s Hospital, Changzhou, ChinaDepartment of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, ChinaDepartment of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, ChinaDepartment of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, ChinaDepartment of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, ChinaDepartment of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, ChinaDepartment of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, ChinaDepartment of Radiation Oncology, The Affiliated Taizhou Hospital, Wenzhou Medical University, Taizhou, ChinaDepartment of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, ChinaObjectiveThis 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.MethodsA 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.ResultsAmong 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).ConclusionThe 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.https://www.frontiersin.org/articles/10.3389/fonc.2025.1516348/fullexosomal miRNAsradiation pneumonitis (RP)non-small cell lung cancer (NSCLC)predictive modelmiR-200b-5p |
| spellingShingle | Shuwei Zhai Yajun Zhu Xiaoye Wang Qingfeng Zhao Xu Liang Shuhao Que Enhui Dai Huaiyu Wang Yuetong Li Haihua Yang Wei Feng Development of a predictive model for radiation pneumonitis based on plasma exosomal miR-200b-5p Frontiers in Oncology exosomal miRNAs radiation pneumonitis (RP) non-small cell lung cancer (NSCLC) predictive model miR-200b-5p |
| title | Development of a predictive model for radiation pneumonitis based on plasma exosomal miR-200b-5p |
| title_full | Development of a predictive model for radiation pneumonitis based on plasma exosomal miR-200b-5p |
| title_fullStr | Development of a predictive model for radiation pneumonitis based on plasma exosomal miR-200b-5p |
| title_full_unstemmed | Development of a predictive model for radiation pneumonitis based on plasma exosomal miR-200b-5p |
| title_short | Development of a predictive model for radiation pneumonitis based on plasma exosomal miR-200b-5p |
| title_sort | development of a predictive model for radiation pneumonitis based on plasma exosomal mir 200b 5p |
| topic | exosomal miRNAs radiation pneumonitis (RP) non-small cell lung cancer (NSCLC) predictive model miR-200b-5p |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2025.1516348/full |
| work_keys_str_mv | AT shuweizhai developmentofapredictivemodelforradiationpneumonitisbasedonplasmaexosomalmir200b5p AT yajunzhu developmentofapredictivemodelforradiationpneumonitisbasedonplasmaexosomalmir200b5p AT xiaoyewang developmentofapredictivemodelforradiationpneumonitisbasedonplasmaexosomalmir200b5p AT qingfengzhao developmentofapredictivemodelforradiationpneumonitisbasedonplasmaexosomalmir200b5p AT xuliang developmentofapredictivemodelforradiationpneumonitisbasedonplasmaexosomalmir200b5p AT shuhaoque developmentofapredictivemodelforradiationpneumonitisbasedonplasmaexosomalmir200b5p AT enhuidai developmentofapredictivemodelforradiationpneumonitisbasedonplasmaexosomalmir200b5p AT huaiyuwang developmentofapredictivemodelforradiationpneumonitisbasedonplasmaexosomalmir200b5p AT yuetongli developmentofapredictivemodelforradiationpneumonitisbasedonplasmaexosomalmir200b5p AT haihuayang developmentofapredictivemodelforradiationpneumonitisbasedonplasmaexosomalmir200b5p AT weifeng developmentofapredictivemodelforradiationpneumonitisbasedonplasmaexosomalmir200b5p |