Siqi Bao1, Ting Hu2, Jiaqi Liu3, Jianzhong Su1, Jie Sun1, Yue Ming4, Jiaxin Li3, Nan Wu5, Hongyan Chen6, Meng Zhou7. 1. School of Biomedical Engineering, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, 325027, People's Republic of China. 2. State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, People's Republic of China. 3. Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, People's Republic of China. 4. PET-CT Center, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, People's Republic of China. 5. Department of Orthopedic Surgery, Beijing Key Laboratory for Genetic Research of Skeletal Deformity & Key Laboratory of Big Data for Spinal Deformities, State Key Laboratory of Complex Severe and Rare Diseases, All at Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730, People's Republic of China. dr.wunan@pumch.cn. 6. State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, People's Republic of China. chenhongyan@cicams.ac.cn. 7. School of Biomedical Engineering, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, 325027, People's Republic of China. zhoumeng@wmu.edu.cn.
Abstract
BACKGROUND: Breast cancer (BC) is the most frequently diagnosed cancer and the leading cause of cancer-associated deaths in women. Recent studies have indicated that microRNA (miRNA) regulation in genomic instability (GI) is associated with disease risk and clinical outcome. Herein, we aimed to identify the GI-derived miRNA signature in extracellular vesicles (EVs) as a minimally invasive biomarker for early diagnosis and prognostic risk stratification. EXPERIMENTAL DESIGN: Integrative analysis of miRNA expression and somatic mutation profiles was performed to identify GI-associated miRNAs. Then, we constructed a discovery and validation study with multicenter prospective cohorts. The GI-derived miRNA signature (miGISig) was developed in the TCGA discovery cohort (n = 261), and was subsequently independently validated in internal TCGA validation (n = 261) and GSE22220 (n = 210) cohorts for prognosis prediction, and in GSE73002 (n = 3966), GSE41922 (n = 54), and in-house clinical exosome (n = 30) cohorts for diagnostic performance. RESULTS: We identified a GI-derived three miRNA signature (MIR421, MIR128-1 and MIR128-2) in the serum extracellular vesicles of BC patients, which was significantly associated with poor prognosis in all the cohorts tested and remained as an independent prognostic factor using multivariate analyses. When integrated with the clinical characteristics, the composite miRNA-clinical prognostic indicator showed improved prognostic performance. The miGISig also showed high accuracy in differentiating BC from healthy controls with the area under the receiver operating characteristics curve (ROC) with 0.915, 0.794 and 0.772 in GSE73002, GSE41922 and TCGA cohorts, respectively. Furthermore, circulating EVs from BC patients in the in-house cohort harbored elevated levels of miGISig, with effective diagnostic accuracy. CONCLUSIONS: We report a novel GI-derived three miRNA signature in EVs, as an excellent minimally invasive biomarker for the early diagnosis and unfavorable prognosis in BC.
BACKGROUND:Breast cancer (BC) is the most frequently diagnosed cancer and the leading cause of cancer-associated deaths in women. Recent studies have indicated that microRNA (miRNA) regulation in genomic instability (GI) is associated with disease risk and clinical outcome. Herein, we aimed to identify the GI-derived miRNA signature in extracellular vesicles (EVs) as a minimally invasive biomarker for early diagnosis and prognostic risk stratification. EXPERIMENTAL DESIGN: Integrative analysis of miRNA expression and somatic mutation profiles was performed to identify GI-associated miRNAs. Then, we constructed a discovery and validation study with multicenter prospective cohorts. The GI-derived miRNA signature (miGISig) was developed in the TCGA discovery cohort (n = 261), and was subsequently independently validated in internal TCGA validation (n = 261) and GSE22220 (n = 210) cohorts for prognosis prediction, and in GSE73002 (n = 3966), GSE41922 (n = 54), and in-house clinical exosome (n = 30) cohorts for diagnostic performance. RESULTS: We identified a GI-derived three miRNA signature (MIR421, MIR128-1 and MIR128-2) in the serum extracellular vesicles of BC patients, which was significantly associated with poor prognosis in all the cohorts tested and remained as an independent prognostic factor using multivariate analyses. When integrated with the clinical characteristics, the composite miRNA-clinical prognostic indicator showed improved prognostic performance. The miGISig also showed high accuracy in differentiating BC from healthy controls with the area under the receiver operating characteristics curve (ROC) with 0.915, 0.794 and 0.772 in GSE73002, GSE41922 and TCGA cohorts, respectively. Furthermore, circulating EVs from BC patients in the in-house cohort harbored elevated levels of miGISig, with effective diagnostic accuracy. CONCLUSIONS: We report a novel GI-derived three miRNA signature in EVs, as an excellent minimally invasive biomarker for the early diagnosis and unfavorable prognosis in BC.
Entities:
Keywords:
Breast cancer; Exosomes; Extracellular vesicle; Genomic instability; microRNA
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