Cargando…
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...
Autores principales: | , , , , , , , , , , |
---|---|
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 |
_version_ | 1783383482216480768 |
---|---|
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. |
format | Online Article Text |
id | pubmed-6310725 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Korean Breast Cancer Society |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT yuxiaokang identificationandvalidationofcirculatingmicrornasignaturesforbreastcancerearlydetectionbasedonlargescaletissuederiveddata AT liangjinsheng identificationandvalidationofcirculatingmicrornasignaturesforbreastcancerearlydetectionbasedonlargescaletissuederiveddata AT xujiarui identificationandvalidationofcirculatingmicrornasignaturesforbreastcancerearlydetectionbasedonlargescaletissuederiveddata AT lixingsong identificationandvalidationofcirculatingmicrornasignaturesforbreastcancerearlydetectionbasedonlargescaletissuederiveddata AT xingshan identificationandvalidationofcirculatingmicrornasignaturesforbreastcancerearlydetectionbasedonlargescaletissuederiveddata AT lihuilan identificationandvalidationofcirculatingmicrornasignaturesforbreastcancerearlydetectionbasedonlargescaletissuederiveddata AT liuwanli identificationandvalidationofcirculatingmicrornasignaturesforbreastcancerearlydetectionbasedonlargescaletissuederiveddata AT liudongdong identificationandvalidationofcirculatingmicrornasignaturesforbreastcancerearlydetectionbasedonlargescaletissuederiveddata AT xujianhua identificationandvalidationofcirculatingmicrornasignaturesforbreastcancerearlydetectionbasedonlargescaletissuederiveddata AT huanglizhen identificationandvalidationofcirculatingmicrornasignaturesforbreastcancerearlydetectionbasedonlargescaletissuederiveddata AT duhongli identificationandvalidationofcirculatingmicrornasignaturesforbreastcancerearlydetectionbasedonlargescaletissuederiveddata |