Plasma extracellular vesicle microRNAs for pulmonary ground-glass nodules
In this study, we evaluated the diagnostic value and molecular characteristics of plasma extracellular vesicles (EVs)-derived miRNAs for patients with solitary pulmonary nodules (SPNs), particularly ground-glass nodules (GGNs). This study was registered at www.clinicaltrials.gov under registration n...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-12-01
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| Series: | Journal of Extracellular Vesicles |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/20013078.2019.1663666 |
| _version_ | 1818085748892499968 |
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| author | Jia-Tao Zhang Hao Qin Fiona Ka Man Cheung Jian Su Da-Dong Zhang Shi-Yi Liu Xiao-Fang Li Jing Qin Jun-Tao Lin Ben-Yuan Jiang Song Dong Ri-Qiang Liao Nie Qiang Xue-Ning Yang Hai-Yan Tu Qing Zhou Jin-Ji Yang Xu-Chao Zhang Ya-Nan Zhang Yi-Long Wu Wen-Zhao Zhong |
| author_facet | Jia-Tao Zhang Hao Qin Fiona Ka Man Cheung Jian Su Da-Dong Zhang Shi-Yi Liu Xiao-Fang Li Jing Qin Jun-Tao Lin Ben-Yuan Jiang Song Dong Ri-Qiang Liao Nie Qiang Xue-Ning Yang Hai-Yan Tu Qing Zhou Jin-Ji Yang Xu-Chao Zhang Ya-Nan Zhang Yi-Long Wu Wen-Zhao Zhong |
| author_sort | Jia-Tao Zhang |
| collection | DOAJ |
| description | In this study, we evaluated the diagnostic value and molecular characteristics of plasma extracellular vesicles (EVs)-derived miRNAs for patients with solitary pulmonary nodules (SPNs), particularly ground-glass nodules (GGNs). This study was registered at www.clinicaltrials.gov under registration number NCT03230019. Small RNA sequencing was performed to assess plasma EVs miRNAs in 59 patients, including 12 patients with benign nodules (2017, training set). MiRNA profiles of 40 an additional individuals were sequenced (2018, validation set). Overall, 16 pure GGNs, 21 mixed GGNs, and 42 solid nodules were included, with paired post-operative plasma samples available for 20 patients. The target miRNA/reference miRNA ratio was used to construct a support vector machine (SVM) model. The SVM model with the best specificity showed 100% specificity in both the training and validation sets independently. The model with the best sensitivity showed 100% and 96.9% sensitivity in the training and validation sets, respectively. Principal component analysis revealed that pure GGN distributions were distinct from those of solid nodules, and mixed GGNs had a diffuse distribution. Among differentially expressed miRNAs, miR-500a-3p, miR-501-3p, and miR-502-3p were upregulated in tumor tissues and enhanced overall survival. The SVM classifier accurately distinguished malignant GGNs and benign nodules. The distinct profile characteristics of miRNAs provided insights into the feasibility of EVs miRNAs as prognostic factors in lung cancer. |
| first_indexed | 2024-12-10T20:14:43Z |
| format | Article |
| id | doaj.art-3f69e13fb26f48fcb5282387bc75f415 |
| institution | Directory Open Access Journal |
| issn | 2001-3078 |
| language | English |
| last_indexed | 2024-12-10T20:14:43Z |
| publishDate | 2019-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Extracellular Vesicles |
| spelling | doaj.art-3f69e13fb26f48fcb5282387bc75f4152022-12-22T01:35:13ZengWileyJournal of Extracellular Vesicles2001-30782019-12-018110.1080/20013078.2019.16636661663666Plasma extracellular vesicle microRNAs for pulmonary ground-glass nodulesJia-Tao Zhang0Hao Qin1Fiona Ka Man Cheung2Jian Su3Da-Dong Zhang4Shi-Yi Liu5Xiao-Fang Li6Jing Qin7Jun-Tao Lin8Ben-Yuan Jiang9Song Dong10Ri-Qiang Liao11Nie Qiang12Xue-Ning Yang13Hai-Yan Tu14Qing Zhou15Jin-Ji Yang16Xu-Chao Zhang17Ya-Nan Zhang18Yi-Long Wu19Wen-Zhao Zhong20Guangdong Key Laboratory of Lung Cancer Translational Medicine3D Medicines IncThe Chinese University of Hong Kong, Shatin, New TerritoriesGuangdong Key Laboratory of Lung Cancer Translational Medicine3D Medicines Inc3D Medicines Inc3D Medicines IncThe Chinese University of Hong KongGuangdong Key Laboratory of Lung Cancer Translational MedicineGuangdong Key Laboratory of Lung Cancer Translational MedicineGuangdong Key Laboratory of Lung Cancer Translational MedicineGuangdong Key Laboratory of Lung Cancer Translational MedicineGuangdong Key Laboratory of Lung Cancer Translational MedicineGuangdong Key Laboratory of Lung Cancer Translational MedicineGuangdong Key Laboratory of Lung Cancer Translational MedicineGuangdong Key Laboratory of Lung Cancer Translational MedicineGuangdong Key Laboratory of Lung Cancer Translational MedicineGuangdong Key Laboratory of Lung Cancer Translational Medicine3D Medicines IncGuangdong Key Laboratory of Lung Cancer Translational MedicineGuangdong Key Laboratory of Lung Cancer Translational MedicineIn this study, we evaluated the diagnostic value and molecular characteristics of plasma extracellular vesicles (EVs)-derived miRNAs for patients with solitary pulmonary nodules (SPNs), particularly ground-glass nodules (GGNs). This study was registered at www.clinicaltrials.gov under registration number NCT03230019. Small RNA sequencing was performed to assess plasma EVs miRNAs in 59 patients, including 12 patients with benign nodules (2017, training set). MiRNA profiles of 40 an additional individuals were sequenced (2018, validation set). Overall, 16 pure GGNs, 21 mixed GGNs, and 42 solid nodules were included, with paired post-operative plasma samples available for 20 patients. The target miRNA/reference miRNA ratio was used to construct a support vector machine (SVM) model. The SVM model with the best specificity showed 100% specificity in both the training and validation sets independently. The model with the best sensitivity showed 100% and 96.9% sensitivity in the training and validation sets, respectively. Principal component analysis revealed that pure GGN distributions were distinct from those of solid nodules, and mixed GGNs had a diffuse distribution. Among differentially expressed miRNAs, miR-500a-3p, miR-501-3p, and miR-502-3p were upregulated in tumor tissues and enhanced overall survival. The SVM classifier accurately distinguished malignant GGNs and benign nodules. The distinct profile characteristics of miRNAs provided insights into the feasibility of EVs miRNAs as prognostic factors in lung cancer.http://dx.doi.org/10.1080/20013078.2019.1663666ground-glass noduleextracellular vesiclesmicrornabiomarkersupport vector machine |
| spellingShingle | Jia-Tao Zhang Hao Qin Fiona Ka Man Cheung Jian Su Da-Dong Zhang Shi-Yi Liu Xiao-Fang Li Jing Qin Jun-Tao Lin Ben-Yuan Jiang Song Dong Ri-Qiang Liao Nie Qiang Xue-Ning Yang Hai-Yan Tu Qing Zhou Jin-Ji Yang Xu-Chao Zhang Ya-Nan Zhang Yi-Long Wu Wen-Zhao Zhong Plasma extracellular vesicle microRNAs for pulmonary ground-glass nodules Journal of Extracellular Vesicles ground-glass nodule extracellular vesicles microrna biomarker support vector machine |
| title | Plasma extracellular vesicle microRNAs for pulmonary ground-glass nodules |
| title_full | Plasma extracellular vesicle microRNAs for pulmonary ground-glass nodules |
| title_fullStr | Plasma extracellular vesicle microRNAs for pulmonary ground-glass nodules |
| title_full_unstemmed | Plasma extracellular vesicle microRNAs for pulmonary ground-glass nodules |
| title_short | Plasma extracellular vesicle microRNAs for pulmonary ground-glass nodules |
| title_sort | plasma extracellular vesicle micrornas for pulmonary ground glass nodules |
| topic | ground-glass nodule extracellular vesicles microrna biomarker support vector machine |
| url | http://dx.doi.org/10.1080/20013078.2019.1663666 |
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