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Identification and Validation of Circulating MicroRNA Signatures for Breast Cancer Early Detection Based on Large Scale Tissue-Derived Data

PURPOSE: Breast cancer is the most commonly occurring cancer among women worldwide, and therefore, improved approaches for its early detection are urgently needed. As microRNAs (miRNAs) are increasingly recognized as critical regulators in tumorigenesis and possess excellent stability in plasma, thi...

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Autores principales: Yu, Xiaokang, Liang, Jinsheng, Xu, Jiarui, Li, Xingsong, Xing, Shan, Li, Huilan, Liu, Wanli, Liu, Dongdong, Xu, Jianhua, Huang, Lizhen, Du, Hongli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Breast Cancer Society 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6310725/
https://www.ncbi.nlm.nih.gov/pubmed/30607157
http://dx.doi.org/10.4048/jbc.2018.21.e56
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author Yu, Xiaokang
Liang, Jinsheng
Xu, Jiarui
Li, Xingsong
Xing, Shan
Li, Huilan
Liu, Wanli
Liu, Dongdong
Xu, Jianhua
Huang, Lizhen
Du, Hongli
author_facet Yu, Xiaokang
Liang, Jinsheng
Xu, Jiarui
Li, Xingsong
Xing, Shan
Li, Huilan
Liu, Wanli
Liu, Dongdong
Xu, Jianhua
Huang, Lizhen
Du, Hongli
author_sort Yu, Xiaokang
collection PubMed
description PURPOSE: Breast cancer is the most commonly occurring cancer among women worldwide, and therefore, improved approaches for its early detection are urgently needed. As microRNAs (miRNAs) are increasingly recognized as critical regulators in tumorigenesis and possess excellent stability in plasma, this study focused on using miRNAs to develop a method for identifying noninvasive biomarkers. METHODS: To discover critical candidates, differential expression analysis was performed on tissue-originated miRNA profiles of 409 early breast cancer patients and 87 healthy controls from The Cancer Genome Atlas database. We selected candidates from the differentially expressed miRNAs and then evaluated every possible molecular signature formed by the candidates. The best signature was validated in independent serum samples from 113 early breast cancer patients and 47 healthy controls using reverse transcription quantitative real-time polymerase chain reaction. RESULTS: The miRNA candidates in our method were revealed to be associated with breast cancer according to previous studies and showed potential as useful biomarkers. When validated in independent serum samples, the area under curve of the final miRNA signature (miR-21-3p, miR-21-5p, and miR-99a-5p) was 0.895. Diagnostic sensitivity and specificity were 97.9% and 73.5%, respectively. CONCLUSION: The present study established a novel and effective method to identify biomarkers for early breast cancer. And the method, is also suitable for other cancer types. Furthermore, a combination of three miRNAs was identified as a prospective biomarker for breast cancer early detection.
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spelling pubmed-63107252019-01-03 Identification and Validation of Circulating MicroRNA Signatures for Breast Cancer Early Detection Based on Large Scale Tissue-Derived Data Yu, Xiaokang Liang, Jinsheng Xu, Jiarui Li, Xingsong Xing, Shan Li, Huilan Liu, Wanli Liu, Dongdong Xu, Jianhua Huang, Lizhen Du, Hongli J Breast Cancer Original Article PURPOSE: Breast cancer is the most commonly occurring cancer among women worldwide, and therefore, improved approaches for its early detection are urgently needed. As microRNAs (miRNAs) are increasingly recognized as critical regulators in tumorigenesis and possess excellent stability in plasma, this study focused on using miRNAs to develop a method for identifying noninvasive biomarkers. METHODS: To discover critical candidates, differential expression analysis was performed on tissue-originated miRNA profiles of 409 early breast cancer patients and 87 healthy controls from The Cancer Genome Atlas database. We selected candidates from the differentially expressed miRNAs and then evaluated every possible molecular signature formed by the candidates. The best signature was validated in independent serum samples from 113 early breast cancer patients and 47 healthy controls using reverse transcription quantitative real-time polymerase chain reaction. RESULTS: The miRNA candidates in our method were revealed to be associated with breast cancer according to previous studies and showed potential as useful biomarkers. When validated in independent serum samples, the area under curve of the final miRNA signature (miR-21-3p, miR-21-5p, and miR-99a-5p) was 0.895. Diagnostic sensitivity and specificity were 97.9% and 73.5%, respectively. CONCLUSION: The present study established a novel and effective method to identify biomarkers for early breast cancer. And the method, is also suitable for other cancer types. Furthermore, a combination of three miRNAs was identified as a prospective biomarker for breast cancer early detection. Korean Breast Cancer Society 2018-12 2018-12-10 /pmc/articles/PMC6310725/ /pubmed/30607157 http://dx.doi.org/10.4048/jbc.2018.21.e56 Text en © 2018 Korean Breast Cancer Society http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Yu, Xiaokang
Liang, Jinsheng
Xu, Jiarui
Li, Xingsong
Xing, Shan
Li, Huilan
Liu, Wanli
Liu, Dongdong
Xu, Jianhua
Huang, Lizhen
Du, Hongli
Identification and Validation of Circulating MicroRNA Signatures for Breast Cancer Early Detection Based on Large Scale Tissue-Derived Data
title Identification and Validation of Circulating MicroRNA Signatures for Breast Cancer Early Detection Based on Large Scale Tissue-Derived Data
title_full Identification and Validation of Circulating MicroRNA Signatures for Breast Cancer Early Detection Based on Large Scale Tissue-Derived Data
title_fullStr Identification and Validation of Circulating MicroRNA Signatures for Breast Cancer Early Detection Based on Large Scale Tissue-Derived Data
title_full_unstemmed Identification and Validation of Circulating MicroRNA Signatures for Breast Cancer Early Detection Based on Large Scale Tissue-Derived Data
title_short Identification and Validation of Circulating MicroRNA Signatures for Breast Cancer Early Detection Based on Large Scale Tissue-Derived Data
title_sort identification and validation of circulating microrna signatures for breast cancer early detection based on large scale tissue-derived data
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6310725/
https://www.ncbi.nlm.nih.gov/pubmed/30607157
http://dx.doi.org/10.4048/jbc.2018.21.e56
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