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Integrated extracellular microRNA profiling for ovarian cancer screening
A major obstacle to improving prognoses in ovarian cancer is the lack of effective screening methods for early detection. Circulating microRNAs (miRNAs) have been recognized as promising biomarkers that could lead to clinical applications. Here, to develop an optimal detection method, we use microar...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6192980/ https://www.ncbi.nlm.nih.gov/pubmed/30333487 http://dx.doi.org/10.1038/s41467-018-06434-4 |
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author | Yokoi, Akira Matsuzaki, Juntaro Yamamoto, Yusuke Yoneoka, Yutaka Takahashi, Kenta Shimizu, Hanako Uehara, Takashi Ishikawa, Mitsuya Ikeda, Shun-ichi Sonoda, Takumi Kawauchi, Junpei Takizawa, Satoko Aoki, Yoshiaki Niida, Shumpei Sakamoto, Hiromi Kato, Ken Kato, Tomoyasu Ochiya, Takahiro |
author_facet | Yokoi, Akira Matsuzaki, Juntaro Yamamoto, Yusuke Yoneoka, Yutaka Takahashi, Kenta Shimizu, Hanako Uehara, Takashi Ishikawa, Mitsuya Ikeda, Shun-ichi Sonoda, Takumi Kawauchi, Junpei Takizawa, Satoko Aoki, Yoshiaki Niida, Shumpei Sakamoto, Hiromi Kato, Ken Kato, Tomoyasu Ochiya, Takahiro |
author_sort | Yokoi, Akira |
collection | PubMed |
description | A major obstacle to improving prognoses in ovarian cancer is the lack of effective screening methods for early detection. Circulating microRNAs (miRNAs) have been recognized as promising biomarkers that could lead to clinical applications. Here, to develop an optimal detection method, we use microarrays to obtain comprehensive miRNA profiles from 4046 serum samples, including 428 patients with ovarian tumors. A diagnostic model based on expression levels of ten miRNAs is constructed in the discovery set. Validation in an independent cohort reveals that the model is very accurate (sensitivity, 0.99; specificity, 1.00), and the diagnostic accuracy is maintained even in early-stage ovarian cancers. Furthermore, we construct two additional models, each using 9–10 serum miRNAs, aimed at discriminating ovarian cancers from the other types of solid tumors or benign ovarian tumors. Our findings provide robust evidence that the serum miRNA profile represents a promising diagnostic biomarker for ovarian cancer. |
format | Online Article Text |
id | pubmed-6192980 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-61929802018-10-19 Integrated extracellular microRNA profiling for ovarian cancer screening Yokoi, Akira Matsuzaki, Juntaro Yamamoto, Yusuke Yoneoka, Yutaka Takahashi, Kenta Shimizu, Hanako Uehara, Takashi Ishikawa, Mitsuya Ikeda, Shun-ichi Sonoda, Takumi Kawauchi, Junpei Takizawa, Satoko Aoki, Yoshiaki Niida, Shumpei Sakamoto, Hiromi Kato, Ken Kato, Tomoyasu Ochiya, Takahiro Nat Commun Article A major obstacle to improving prognoses in ovarian cancer is the lack of effective screening methods for early detection. Circulating microRNAs (miRNAs) have been recognized as promising biomarkers that could lead to clinical applications. Here, to develop an optimal detection method, we use microarrays to obtain comprehensive miRNA profiles from 4046 serum samples, including 428 patients with ovarian tumors. A diagnostic model based on expression levels of ten miRNAs is constructed in the discovery set. Validation in an independent cohort reveals that the model is very accurate (sensitivity, 0.99; specificity, 1.00), and the diagnostic accuracy is maintained even in early-stage ovarian cancers. Furthermore, we construct two additional models, each using 9–10 serum miRNAs, aimed at discriminating ovarian cancers from the other types of solid tumors or benign ovarian tumors. Our findings provide robust evidence that the serum miRNA profile represents a promising diagnostic biomarker for ovarian cancer. Nature Publishing Group UK 2018-10-17 /pmc/articles/PMC6192980/ /pubmed/30333487 http://dx.doi.org/10.1038/s41467-018-06434-4 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Yokoi, Akira Matsuzaki, Juntaro Yamamoto, Yusuke Yoneoka, Yutaka Takahashi, Kenta Shimizu, Hanako Uehara, Takashi Ishikawa, Mitsuya Ikeda, Shun-ichi Sonoda, Takumi Kawauchi, Junpei Takizawa, Satoko Aoki, Yoshiaki Niida, Shumpei Sakamoto, Hiromi Kato, Ken Kato, Tomoyasu Ochiya, Takahiro Integrated extracellular microRNA profiling for ovarian cancer screening |
title | Integrated extracellular microRNA profiling for ovarian cancer screening |
title_full | Integrated extracellular microRNA profiling for ovarian cancer screening |
title_fullStr | Integrated extracellular microRNA profiling for ovarian cancer screening |
title_full_unstemmed | Integrated extracellular microRNA profiling for ovarian cancer screening |
title_short | Integrated extracellular microRNA profiling for ovarian cancer screening |
title_sort | integrated extracellular microrna profiling for ovarian cancer screening |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6192980/ https://www.ncbi.nlm.nih.gov/pubmed/30333487 http://dx.doi.org/10.1038/s41467-018-06434-4 |
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