Small extracellular vesicle miRNAs as biomarkers for predicting antitumor efficacy in lung adenocarcinoma treated with chemotherapy and checkpoint blockade
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...
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Frontiers Media S.A.
2025-03-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1573043/full |
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| author | Si Sun Si Sun Si Sun Fuchuang Zhang Jiyang Zhang Hui Yu Hui Yu Zhihuang Hu Zhihuang Hu Xiaoya Xu Xinmin Zhao Xinmin Zhao Sheng Chen Yao Zhang Yao Zhang Baoning Nian Ying Lin Ying Lin Zhikuan Li Zhenhua Wu Zhenhua Wu Bo Yu Bo Yu Xianghua Wu Xianghua Wu Huijie Wang Huijie Wang Xiaohua Hui Xiaohua Hui Dadong Zhang Jialei Wang Jialei Wang Jialei Wang |
| author_facet | Si Sun Si Sun Si Sun Fuchuang Zhang Jiyang Zhang Hui Yu Hui Yu Zhihuang Hu Zhihuang Hu Xiaoya Xu Xinmin Zhao Xinmin Zhao Sheng Chen Yao Zhang Yao Zhang Baoning Nian Ying Lin Ying Lin Zhikuan Li Zhenhua Wu Zhenhua Wu Bo Yu Bo Yu Xianghua Wu Xianghua Wu Huijie Wang Huijie Wang Xiaohua Hui Xiaohua Hui Dadong Zhang Jialei Wang Jialei Wang Jialei Wang |
| author_sort | Si Sun |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-6f7f40f52c8d4a3fb2ad70356c046577 |
| institution | DOAJ |
| issn | 1664-3224 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj-art-6f7f40f52c8d4a3fb2ad70356c0465772025-08-20T02:49:59ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-03-011610.3389/fimmu.2025.15730431573043Small extracellular vesicle miRNAs as biomarkers for predicting antitumor efficacy in lung adenocarcinoma treated with chemotherapy and checkpoint blockadeSi Sun0Si Sun1Si Sun2Fuchuang Zhang3Jiyang Zhang4Hui Yu5Hui Yu6Zhihuang Hu7Zhihuang Hu8Xiaoya Xu9Xinmin Zhao10Xinmin Zhao11Sheng Chen12Yao Zhang13Yao Zhang14Baoning Nian15Ying Lin16Ying Lin17Zhikuan Li18Zhenhua Wu19Zhenhua Wu20Bo Yu21Bo Yu22Xianghua Wu23Xianghua Wu24Huijie Wang25Huijie Wang26Xiaohua Hui27Xiaohua Hui28Dadong Zhang29Jialei Wang30Jialei Wang31Jialei Wang32Department of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, ChinaDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, ChinaInstitute of Thoracic Oncology, Fudan University Shanghai Cancer Center, Shanghai, ChinaDepartment of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, ChinaDepartment of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, ChinaDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, ChinaDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, ChinaDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, ChinaDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, ChinaDepartment of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, ChinaDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, ChinaDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, ChinaDepartment of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, ChinaDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, ChinaDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, ChinaDepartment of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, ChinaDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, ChinaDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, ChinaDepartment of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, ChinaDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, ChinaDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, ChinaDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, ChinaDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, ChinaDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, ChinaDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, ChinaDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, ChinaDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, ChinaDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, ChinaDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, ChinaDepartment of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, ChinaDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, ChinaDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, ChinaInstitute of Thoracic Oncology, Fudan University Shanghai Cancer Center, Shanghai, ChinaCheckpoint 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.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1573043/fullsEVsmiRNAimmune checkpoint inhibitorschemotherapylung cancer. sEV miRNAs predicting immunochemotherapy efficacy |
| spellingShingle | Si Sun Si Sun Si Sun Fuchuang Zhang Jiyang Zhang Hui Yu Hui Yu Zhihuang Hu Zhihuang Hu Xiaoya Xu Xinmin Zhao Xinmin Zhao Sheng Chen Yao Zhang Yao Zhang Baoning Nian Ying Lin Ying Lin Zhikuan Li Zhenhua Wu Zhenhua Wu Bo Yu Bo Yu Xianghua Wu Xianghua Wu Huijie Wang Huijie Wang Xiaohua Hui Xiaohua Hui Dadong Zhang Jialei Wang Jialei Wang Jialei Wang Small extracellular vesicle miRNAs as biomarkers for predicting antitumor efficacy in lung adenocarcinoma treated with chemotherapy and checkpoint blockade Frontiers in Immunology sEVs miRNA immune checkpoint inhibitors chemotherapy lung cancer. sEV miRNAs predicting immunochemotherapy efficacy |
| title | Small extracellular vesicle miRNAs as biomarkers for predicting antitumor efficacy in lung adenocarcinoma treated with chemotherapy and checkpoint blockade |
| title_full | Small extracellular vesicle miRNAs as biomarkers for predicting antitumor efficacy in lung adenocarcinoma treated with chemotherapy and checkpoint blockade |
| title_fullStr | Small extracellular vesicle miRNAs as biomarkers for predicting antitumor efficacy in lung adenocarcinoma treated with chemotherapy and checkpoint blockade |
| title_full_unstemmed | Small extracellular vesicle miRNAs as biomarkers for predicting antitumor efficacy in lung adenocarcinoma treated with chemotherapy and checkpoint blockade |
| title_short | Small extracellular vesicle miRNAs as biomarkers for predicting antitumor efficacy in lung adenocarcinoma treated with chemotherapy and checkpoint blockade |
| title_sort | small extracellular vesicle mirnas as biomarkers for predicting antitumor efficacy in lung adenocarcinoma treated with chemotherapy and checkpoint blockade |
| topic | sEVs miRNA immune checkpoint inhibitors chemotherapy lung cancer. sEV miRNAs predicting immunochemotherapy efficacy |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1573043/full |
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